text:
Skip to main content

A-Prot: protein structure modeling using MSA transformer

The accuracy of protein 3D structure prediction has been dramatically improved with the help of advances in deep learning. In the recent CASP14, Deepmind demonstrated that their new version of AlphaFold (AF) produces highly accurate 3D models almost close to experimental structures. The success of AF shows that the multiple sequence alignment of a sequence contains rich evolutionary information, leading to accurate 3D models. Despite the success of AF, only the prediction code is open, and training a similar model requires a vast amount of computational resources. Thus, developing a lighter prediction model is still necessary.

In this study, we propose a new protein 3D structure modeling method, A-Prot, using MSA Transformer, one of the state-of-the-art protein language models. An MSA feature tensor and row attention maps are extracted and converted into 2D residue-residue distance and dihedral angle predictions for a given MSA. We demonstrated that A-Prot predicts long-range contacts better than the existing methods. Additionally, we modeled the 3D structures of the free modeling and hard template-based modeling targets of CASP14. The assessment shows that the A-Prot models are more accurate than most top server groups of CASP14.

These results imply that A-Prot accurately captures the evolutionary and structural information of proteins with relatively low computational cost. Thus, A-Prot can provide a clue for the development of other protein property prediction methods.

Peer Review reports

Modeling the 3D structure of a protein from its sequence has been one of the most critical problems in biophysics and biochemistry [1, 2]. The knowledge of the 3D structure of a protein facilitates the discovery of novel ligands, function annotation, and protein engineering. Due to its importance, the community of computational protein scientists have been developing various prediction methods and assessed their performance in the large-scale blind tests, CASPs, which have continued for over two decades [2]. In CASP14, Deepmind demonstrated that their deep learning-based model, AlphaFold2 (AF2), predicts the 3D structures of proteins from their sequences with extremely high accuracy, comparable to experimental accuracy [3]. The source code of AF2 became publicly available recently, and many model structures of genes of biologically important organisms have been released [3].

The success of AF2 can be attributed to the accurate extraction of coevolutionary information from multiple sequence alignments (MSA). The idea of using coevolutionary information for contact prediction or structure modeling has been widely used [4,5,6,7,8,9,10,11,12]. However, previous attempts were not successful enough because coevolutionary signals in MSAs were not strong enough or too noisy. Various statistical mechanics-based models were proposed, but their accuracy, discriminating actual contacts from false contacts, was limited. In CASP13, AlphaFold and RaptorX used coevolutionary information from MSAs as input and predicted inter-residue distances [13,14,15]. They achieved significant improvements than previous CASPs, but their predictions were not accurate enough to obtain model structures comparable to experiments. Finally, in CASP14, with the help of the attention algorithm, truly accurate extraction of actual residue-residue contact signals from MSAs becomes available [3].

Despite this remarkable achievement of AF2, certain limitations remain for this technology to be widely accessible and used for further development. First, the source code for training AF2 is not open-sourced yet. In the first release of AF2, only the production, model generation, part of AF2, and the model parameters are open. Second, training the AF2 architecture is computationally expensive. It is reported that Deepmind used 128 TPUv3 cores for approximately one week and four more days to train AF2. This amount of computational resources are not readily accessible for most academic groups. Thus, developing lighter and general models is still necessary.

To extract evolutionary information from MSAs, various protein language models have been proposed [16,17,18,19,20,21,22]. Rao et al. proposed the MSA transformer model, an unsupervised protein language model using the MSA of a query sequence instead of a single query sequence. The model uses row and column attention of input MSAs and masked language modeling objectives. It is demonstrated that the model successfully predicted long-range contacts between residues. In addition, the model predicted other properties of proteins, such as secondary structure prediction and mutational effects, with high accuracy [20]. These results indicate that the MSA Transformer model extracts the characteristics of proteins from their MSA profiles efficiently.

This study developed a new protein 3D structure prediction method, A-Prot, using MSA Transformer [22]. For a given MSA, we extracted evolutionary information with MSA Transformer. The extracted row attention map and input features were converted to a 2D residue-residue distance map and dihedral angle predictions. We benchmarked the 3D protein structure modeling performance using the FM/TBM-hard targets of CASP13 and 14 [23, 24]. The results show that A-Prot outperforms most top server groups of CASP13 and 14 in terms of long-range contact predictions and 3D protein structure modeling.

The overall pipeline of the proposed protein 3D structure prediction method is shown in Fig. 1. We mainly combine the works of the MSA Transformer [22] and the trRosetta [25]. Given an MSA, it will input to the MSA Transformer to output MSA features and row attention maps. After a series of transformations like dimension reduction and concatenation etc., these two kinds of features will be transformed and combined into 2D feature maps, which is suitable for input to the trRosetta to finally output protein 3D structure.

Fig. 1
figure 1

Pipeline of the proposed protein 3D structure prediction method. Input an MSA to the MSA Transformer to extract MSA Features and row attention maps. Then, the MSA features corresponding to the query sequence and the row attention maps are combined to a 2D feature maps by a set of transformations. Next, the 2D feature maps are input to a Dilated ResNet after dimension reduction to output inter-residue geometries, which further input to the trRosetta Protein Structure Modeling to output a predicted protein 3D structure

The MSA Transformer used in this paper was an already pre-trained version that was learned from 26 million MSAs. It plays a role as a feature extractor that inputs an MSA and outputs its relative features.

trRosetta consists of a deep neural network part and protein structure modeling part. The deep neural network is modified to receive the MSA features from the MSA Transformer instead of the original manually engineered features generated by the statistic approach. Nevertheless, the protein structure modeling part remains the same.

Dataset and MSA generation

We used the procedure with MSA transformer to generate the MSAs of target sequences (Rao, Liu, et al., 2021). The MSA of a query sequence was generated using Jackhammer [26], HHblits ver. 3.3.0, and HHsearch [27] together with the unicluster30_2017_10 [28] and BFD [29] databases. If not specified, all training and test MSAs are used BFD. If the number of detected homologous sequences exceeds 256, up to 256 sequences were selected through diversity minimization [22]. The upper limit of the number of sequences was determined by the maximum size of GPU memory of the NVIDIA Quadro RTX 8000 GPU (48 GB) card.

To perform contact predictions, a customized non-redundant protein structure database is compiled, and we named it PDB30. The PDB30 dataset consists of protein structures deposited in PDB before Apr-30–2018 whose resolution is higher than 2.5 A and sequence length is longer than 40 amino acids. Using 102,300 sequences that satisfy the condition, clustering analysis was performed using MMSeq2 [30] with a threshold of sequence identity of 30%, leading to 16,612 non-redundant sequences.

Network architecture

Let us define an input MSA as an \(r \times c\) character matrix, where \(r\) and \(c\) are rows (number of sequences) and columns (sequence length) in the MSA, respectively. Through the token and position embedding of the MSA Transformer, the input MSA is embedded into a \(r \times c \times 768\) tensor which is the input and output of each attention block. The attention block is composed in the order of row attention layer, column attention layer, and feed-forward layer. A layer normalization operation is followed by each layer. And each attention layer has 12 attention heads. The MSA Transformer is a stack of 12 such attention blocks.

Two kinds of features were extracted from the MSA Transformer to construct 2D feature maps by a series of transformations. (1) One is the last attention block’s output, a \(r \times c \times 768\) tensor; we named it MSA features (Fig. 1). Only features corresponding to the query sequence are selected, which is a \(1 \times c \times 768\) tensor. Then, the dimension of this feature is reduced to 128 by an MLP (multi-layer perceptron) consist of 3 linear layers with neuron sizes 384, 192, 128. The dimension reduced 1D feature is then outer concatenated (redundantly expanding horizontally and vertically and then stacked together) to form a query sequence feature of a \(c \times c \times 256\) tensor. (2) The other one is row attention maps that are derived from each attention head of each row attention layer, totally \(12 \times 12 = 144\) attention maps stacked to shape in \(c \times c \times 144\). Then it is symmetrized by adding it to its transposed tensor to yield symmetrized row attention maps. The query sequence feature and the symmetrized row attention maps are concatenated in the feature map dimension to form a 2D feature map that is a \(c \times c \times 400\) tensor.

The dimension of the 2D feature maps afterward reduced to 64 by three convolutional layers that consist of 256, 128, 64 kernels of size \(1 \times 1\) [31], where each convolutional layer is followed by an instance normalization and a ReLU activation. Then this \(c \times c \times 64\) tensor is input to the Dilated ResNet consist of 28 residual blocks [32], each having one instance normalization, two ReLU activations, and two convolutional layers each with 64 kernels of size \(3 \times 3\). Dilation is applied to the convolutional layers cycle through the residual blocks with rates of 1, 2, 4. After the last residual block, there are four independent convolutional layers with 25, 13, 25, 37 kernels of size \(1 \times 1\), each for predicting inter-residue geometries of \(\theta ,{ }\varphi ,{ }\omega ,{\text{ d}}\), respectively. Please refer to the reference [25] for more details about the inter-residue geometries as we used the same settings. Finally, the trRosetta Protein Structure Modeling module will predict and modeling the protein 3D structure based on the inter-residue geometries information.

Training and inference

At the training stage, we fixed the parameters in the MSA Transformer. In contrast, parameters in the other deep neural networks were trained with a batch size of 16 with gradient accumulation steps, a learning rate of 1e − 3, using the RAdam optimizer [33], the categorical cross-entropy loss was calculated with equal weight for the four inter-residue geometry objectives [25]. The ground truth values for the inter-residue geometries are all discretized into bins which have same number as corresponding convolutional kernels (\(\theta\) for 25 bins, \(\varphi\) for 13 bins, \(\omega\) for 25 bins, \({\text{d}}\) for 37 bins); each bin is treated as a classification label. The total model was trained end-to-end on an NVIDIA Quadro RTX 8000 GPU (48 GB) for around 40 epochs which took about five days.

An MSA subsampling strategy is applied during training, not only for regarding as data augmentation to train a robust model, but also for preventing the GPU from running out of memory when filled with large MSA. We randomly select MSA rows, up to a maximum of \(2^{14} /c\), and down to a minimum of 16, though always including the query sequences in the first row. Large proteins of more than 1023 residues long were discarded during training. We subsampled MSA with 256 sequences at the inference stage by adding the sequence with the lowest average hamming distance. We performed trRosetta protein structure modeling five times with the same input and selected the structure with the lowest energy for protein structure similarity measurement.

Results and discussion

Benchmarking contact prediction

First, we benchmarked the long-range contact prediction performance of A-Prot using the FM and FM/TBM targets of CASP13 [24]. The benchmark results show that the performance of our model outperforms that of the existing methods (Table 1). We compared the precision of our model's top L/5, L/2, long-range contact predictions (long-range: sequence separation of the residue pair ≥ 24) and the other existing methods. The performance measures of the other methods are adopted from the reference [34]. The top L/5, Top L/2, and L contact precisions of our model are 0.812, 0.710, and 0.562, which are higher than those of the other methods. For example, DeepDist, one of the state-of-the-art methods, predicted the top L/5, L/2, and L with precisions of 0.793, 0.661, and 0.517. Also, compared with AlphaFold predictions of CASP13, A-Prot predicted more accurately in all three measures by 7–9%.

Table 1 Contact Precision on CASP13 FM and FM/TBM targets corresponding to 43 domains (results are

We also compared the contact prediction accuracy of A-Prot with MSA-Transformer, which is the baseline of A-Prot. The performance of long-range Top L and Top L/5 for supervised contact prediction on CASP13 FM targets were 0.546 and 0.775 respectively (Rao, Meier, et al., 2021). The contact precision of Top L and Top L/5 for A-prot were 0.539 and 0.785, which is comparable to those of MSA Transformer (Additional file 1: Table S2). We also investigated the effect of a MSA to contact prediction by predicting structures with the MSAs obtained without BFD and obtained with DeepMSA [35]. The assessment shows that not using BFD deteriorates the quality of models. The accuracies of Top L and Top L/5 contacts decreased by 2.5% and 4.0%, respectively. When DeepMSA was used, the Top L and Top L/5 accuracies dropped by 3.9% and 2.0%, respectively. These results show that considering a gigantic meta-genome DB helps improve prediction quality, but not significantly.

To investigate how the number of residual blocks affects the prediction quality, ablation tests were performed by changing the number of the residual blocks (Additional file 1: Table S4). We performed contact and structure prediction with 4, 16, 28, and 40 residual blocks. The contact prediction results show that A-Prot calculations with 28 blocks resulted in the best contact prediction. Interestingly, using more blocks, 40, decreased contact prediction accuracy. Fewer residual blocks, 4 and 16, led to significantly worse contact prediction results. In terms of model accuracy, A-Prot with 40 blocks resulted in the highest TMscore although contact predictions were most accurate with 28 blocks. These results show that A-Prot with 28 blocks is close to the optimal model considering both the prediction accuracy and computational cost.

Benchmark on model accuracy

In addition to contact prediction, we also compared the quality of protein models predicted by A-Prot with those submitted by the top-performing server groups of CASP14 (Table 2). The highest score of each column is highlighted in bold. First, we modeled the structures of 25 FM/TBM and TBM-hard targets of CASP14. The average TM-score and lDDT score of the models were compared with those of the following server groups: FEIG-S [36], BAKER-ROSETTASERVER [37], Zhang-Server, and QUARK [38]. The model structures of the other groups were downloaded from the archive of the CASP14 website, and TM-score and lDDT scores were recalculated with the crystal structures and domain information for a fair comparison.

Table 2 The average TM-score and lDDT of the model structures of 25 CASP14 FM, FM/TBM, and TBM-hard domains

A-Prot outperforms the other top server groups in terms of lDDT. Compared with BAKER- ROSETTASERVER and FEIG-S, A-Prot models are consistently more accurate in both measures. The P-values show that A-Prot outperforms ROSETTASERVER and FEIG-S statistically significantly. These results show that the accuracy of A-Prot is comparable to or better than the top-performing server groups that participated in CASP14 [23]. In terms of TM-score, A-Prot is showing slightly worse results, 0.576, than Zhang-Server and QUARK, whose TM-scores are 0.595 and 0.588. However, the P-values show that the A-Prot results are not meaningfully different.

We also compared the performance of A-Prot with trRosetta [25] by modeling structures using trRosetta with the identical MSAs that we used for A-Prot (Table 3). The results show that A-Prot significantly outperforms trRosetta using the identical MSAs. In terms of dihedral angle predictions, A-Prot improved the correlation coefficient between ground truth and predictions by 0.071 in average. In addition, A-Prot generated better models with higher TMscore and lDDT values than the trRosetta results. The average TMscore and lDDT enhanced by 0.048 and 0.042 respectively.

Table 3 Performance of A-Prot and trRosetta using same MSA of ours on 25 CASP14 FM, FM/TBM, TBM-Hard domains. (Inter-residue distance and angles are measured using Pearson correlation between predicted bin indexes of max probability and ground truth, Top L for long range contact precision)

In contrast to MSA-Transformer or ROSETTA, A-Prot used the subsampling strategy that minimizes the diversity of sequences to reduce the sizes of MSAs. For protein language models, four subsampling strategies have been tested: random, diversity maximization, diversity minimization, and HHFilter to reduce the size of input MSAs while preserving prediction accuracies. It was shown that diversity maximizing performed best for the supervised contact prediction [22]. On the contrary, trRosetta generates a MSA in a similar manner to the diversity minimizing approach [25]. During the development of A-Prot, we tried both diversity minimization and maximization approaches. The prediction results show that diversity minimizing yields more accurate models than diversity maximization (Additional file 1: Table S3). We predicted the structures of 43 domains of CASP13 FM, FM/TBM and 25 domains of CASP14 FM, FM/TBM and TBM-hard targets using MSAs subsampled with diversity minimization and maximization. In average, the models generated with the MSAs obtained with diversity minimization have higher TM-scores, 0.658 and 0.555 for the CASP13 and CASP14 targets, than those with diversity maximization, 0.603 and 0.532. Thus, we employed the diversity minimization approach for A-Prot.

A head-to-head comparison with ROSETTASERVER

Because A-Prot uses trRosetta for modeling structure at the final stage, we performed a head-to-head comparison of A-Prot models with the ROSETTASERVER models to identify improvement in residue-residue distance predictions (Fig. 2). In terms of TM-score, many predictions made by A-Prot are significantly better than BAKER-ROSETTASERVER. For instance, the model qualities of five targets that were predicted to have TM-score less than 0.4 by ROSETTASERVER were improved higher than 0.4, corresponding to a correct fold prediction. Four highly accurate models are depicted in Fig. 3.

Fig. 2
figure 2

TM-score and lDDT on CASP14 FM, FM/TBM and TBM-hard 25 domains compared with BAKER-ROSETTASERVER

Fig. 3
figure 3

Model comparison of four high-quality CASP14 models generated from our method versus their native structures. Brown: native structure; Blue: model

Similarly, in terms of the lDDT measure, prediction results of eight targets were improved significantly. On the contrary, only two targets deteriorated more than 0.05. Therefore, A-Prot predicts residue-residue distances and dihedral angles better than most server groups participated in CASP14 [2].

On the other hand, nearly all worse predictions by A-Prot deteriorated only by a small margin except the T1026-D1 target. For T1026-D1, A-Prot did not predict its correct fold. This incorrect prediction is attributed to an incomplete MSA. T1026-D1 is a protein consisting of a virus capsid (PDB ID: 6S44). Our sequence search procedure found only less than 30 sequences, which appear to be not enough to extract correct evolutionary information. When T1026-D1 is modelled with the MSA of trRosetta containing more than 100 sequences, T1026-D1, a model with a similar TM-score is obtained. Thus, the failure of T1026-D1 suggests that having enough homologous sequences is critical in accurate 3D structure modeling using MSA-Transformer. In other words, a more extensive sequence search may improve the model accuracy of A-Pro. Except for T1026-D1, the deviations of all worse predictions than ROSETTASERVER were less than 0.1 TM-score, much smaller than the improvements.

In this study, we introduced a new protein structure prediction method, A-Prot, using MSA Transformer. Our benchmark results on the CASP13 TBM/FM and FM targets show that A-Prot predicts long-range residue-residue contacts more accurately than the existing methods. We also assessed the quality of protein structure models based on the predicted residue-residue distance information. The model generated by A-Prot is more accurate than most of the server groups that participated in CASP14. The average lDDT of A-Prot models is higher than that of all server group models. In terms of TM-score, our model is slightly worse than QUARK and Zhang-Server. These results show that our approach yields highly accurate residue-residue distance predictions.

A-Prot requires less computational resources than the other state-of-the-art protein structure prediction models [2]. The source code of AlphaFold2 is only partially open [3]. Its model parameters are fixed, and only the structure modeling part is open. Thus, it is hard to tune AlphaFold2 for bespoken purposes. In addition, training the AlphaFold2 architecture requires a significant amount of computational resources, which is not assessable for most academic groups. On the other hand, A-Prot can be trained with a single GPU card. In summary, A-Prot will open new possibilities for training novel deep-learning-based models to predict various properties of proteins only using sequence information.

Availability of data and materials

All predicted model structures and the multiple sequences alignments used as the inputs for the A-Prot models are available at

Multiple sequence alignment

Free modeling

Template-based modeling

Root mean square deviation

  1. Kwon S, Won J, Kryshtafovych A, Seok C. Assessment of protein model structure accuracy estimation in CASP14: old and new challenges. Proteins Struct Funct Bioinform. 2021;89:1940–8.

    CAS  Article  Google Scholar

  2. Pereira J, Simpkin AJ, Hartmann MD, Rigden DJ, Keegan RM, Lupas AN. High-accuracy protein structure prediction in CASP14. Proteins Struct Funct Bioinform. 2021;89:1687–99.

    CAS  Article  Google Scholar

  3. Jumper J, Evans R, Pritzel A, Green T, Figurnov M, Ronneberger O, et al. Highly accurate protein structure prediction with AlphaFold. Nature. 2021.

    Article  PubMed  PubMed Central  Google Scholar

  4. Tillier ERM, Charlebois RL. The human protein coevolution network. Genome Res. 2009;19:1861–71.

    CAS  Article  Google Scholar

  5. Weigt M, White RA, Szurmant H, Hoch JA, Hwa T. Identification of direct residue contacts in protein–protein interaction by message passing. Proc Natl Acad Sci. 2009;106:67–72.

    CAS  Article  Google Scholar

  6. Lunt B, Szurmant H, Procaccini A, Hoch JA, Hwa T, Weigt M. Inference of direct residue contacts in two-component signaling. In: Methods in enzymology. 2010. pp. 17–41.

  7. Ovchinnikov S, Kamisetty H, Baker D. Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information. eLife. 2014;2014:1–21.

    Google Scholar

  8. de Juan D, Pazos F, Valencia A. Emerging methods in protein co-evolution. Nat Rev Genet. 2013;14:249–61.

    Article  Google Scholar

  9. Marks DS, Hopf TA, Sander C. Protein structure prediction from sequence variation. Nat Publ Group. 2012.

    Article  Google Scholar

  10. Seemayer S, Gruber M, Söding J. CCMpred: fast and precise prediction of protein residue-residue contacts from correlated mutations. Bioinformatics. 2014;30:3128–30.

    CAS  Article  Google Scholar

  11. Jones DT, Singh T, Kosciolek T, Tetchner S. MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins. Bioinformatics. 2015;31:999–1006.

    CAS  Article  Google Scholar

  12. Hopf TA, Schärfe CPI, Rodrigues JPGLM, Green AG, Kohlbacher O, Sander C, et al. Sequence co-evolution gives 3D contacts and structures of protein complexes. eLife. 2014; 3.

  13. Senior AW, Evans R, Jumper J, Kirkpatrick J, Sifre L, Green T, et al. Improved protein structure prediction using potentials from deep learning. Nature. 2020;577:706–10.

    CAS  Article  Google Scholar

  14. Xu J, Wang S. Analysis of distance-based protein structure prediction by deep learning in CASP13. Proteins Struct Funct Bioinform. 2019;87:1069–81.

    CAS  Article  Google Scholar

  15. Xu J. Distance-based protein folding powered by deep learning. Proc Natl Acad Sci USA. 2019;116:16856–65.

    CAS  Article  Google Scholar

  16. Bepler T, Berger B. Learning the protein language: evolution, structure, and function. Cell Syst. 2021;12:654-669.e3.

    CAS  Article  Google Scholar

  17. Strodthoff N, Wagner P, Wenzel M, Samek W. UDSMProt: Universal deep sequence models for protein classification. Bioinformatics. 2020;36:2401–9.

    CAS  Article  Google Scholar

  18. Vig J, Madani A, Varshney LR, Xiong C, Socher R, Rajani NF. BERTology meets biology: interpreting attention in protein language models. 2020.

  19. Madani A, McCann B, Naik N, Keskar NS, Anand N, Eguchi RR, et al. ProGen: language modeling for protein generation. 2020.

  20. Rives A, Meier J, Sercu T, Goyal S, Lin Z, Liu J, et al. Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. Proc Natl Acad Sci. 2021;118:e2016239118.

    CAS  Article  Google Scholar

  21. Rao R, Meier J, Sercu T, Ovchinnikov S, Rives A. Transformer protein language models are unsupervised structure learners. In: ICLR 2021 conference. 2021.

  22. Rao R, Liu J, Verkuil R, Meier J, Canny JF, Abbeel P, et al. MSA transformer. 2021.

  23. Kinch LN, Schaeffer RD, Kryshtafovych A, Grishin NV. Target classification in the 14th round of the critical assessment of protein structure prediction (CASP14). Proteins Struct Funct Bioinform. 2021;89:1618–32.

    CAS  Article  Google Scholar

  24. Kinch LN, Kryshtafovych A, Monastyrskyy B, Grishin NV. CASP13 target classification into tertiary structure prediction categories. Proteins Struct Funct Bioinform. 2019;87:1021–36.

    CAS  Article  Google Scholar

  25. Yang J, Anishchenko I, Park H, Peng Z, Ovchinnikov S, Baker D. Improved protein structure prediction using predicted interresidue orientations. Proc Natl Acad Sci USA 2020;117.

  26. Eddy SR. Accelerated profile HMM searches. PLOS Comput Biol. 2011;7:1002195.

    Article  Google Scholar

  27. Steinegger M, Meier M, Mirdita M, Vöhringer H, Haunsberger SJ, Söding J. HH-suite3 for fast remote homology detection and deep protein annotation. BMC Bioinform. 2019; 20.

  28. Mirdita M, von den Driesch L, Galiez C, Martin MJ, Söding J, Steinegger M. Uniclust databases of clustered and deeply annotated protein sequences and alignments. Nucleic Acids Res. 2017;45:D170–6.

    CAS  Article  Google Scholar

  29. Steinegger M, Mirdita M, Söding J. Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold. Nat Methods. 2019;16:603–6.

    CAS  Article  Google Scholar

  30. Steinegger M, Söding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017;35:1026–8.

    CAS  Article  Google Scholar

  31. Lin M, Chen Q, Yan S. Network in network. 2013; arXiv:1312.4400.

  32. He K, Zhang X, Ren S, Sun J. Identity mappings in deep residual networks. In: Leibe Bastian and Matas J and SN and WM, editor. Computer vision—ECCV 2016. Cham: Springer International Publishing; 2016. p. 630–45.

  33. Liu L, Jiang H, He P, Chen W, Liu X, Gao J, et al. On the variance of the adaptive learning rate and beyond. In: Eighth international conference on learning representations (ICLR). 2020.

  34. Wu T, Guo Z, Hou J, Cheng J. DeepDist: real-value inter-residue distance prediction with deep residual convolutional network. BMC Bioinform. 2021; 22.

  35. Zhang C, Zheng W, Mortuza SM, Li Y, Zhang Y. DeepMSA: Constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins. Bioinformatics. 2020;36:2105–12.

    CAS  Article  Google Scholar

  36. Heo L, Janson G, Feig M. Physics-based protein structure refinement in the era of artificial intelligence. Proteins Struct Funct Bioinform. 2021;89:1870–87.

    CAS  Article  Google Scholar

  37. Anishchenko I, Baek M, Park H, Hiranuma N, Kim DE, Dauparas J, et al. Protein tertiary structure prediction and refinement using deep learning and Rosetta in CASP14. Proteins Struct Funct Bioinform. 2021;89:1722–33.

    CAS  Article  Google Scholar

  38. Zheng W, Li Y, Zhang C, Zhou X, Pearce R, Bell EW, et al. Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14. Proteins Struct Funct Bioinform. 2021;89:1734–51.

    CAS  Article  Google Scholar

Download references

We wish to thank CASP organizers and predictors for sharing the data used in this work.

JL was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (Nos. 2018R1C1B600543513, 2019M3E5D4066898 and 2020M3A9G710393).

Author information

Authors and Affiliations

YH, JL and JK conceived the research. YH wrote the code, performed simulations. YH, JL, and JK analyzed the results and wrote the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Juyong Lee.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no conflict of interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1

. The additional analysis on the modeling results are provided.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Hong, Y., Lee, J. & Ko, J. A-Prot: protein structure modeling using MSA transformer. BMC Bioinformatics 23, 93 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:

  • Protein structure prediction
  • Multiple sequence alignment
  • Protein language model
  • Deep learning


Content-Type: application/http; msgtype=response

WARC-Identified-Payload-Type: text/html

WARC-Type: response

text:
Skip to main content

Table 3 Illustration of the process of aggregating themes and developing common categories

From: Integrating HIV care into nurse-led primary health care services in South Africa: a synthesis of three linked qualitative studies

Primary and secondary themes from the individual studies Common categories identified and further developed through reciprocal translation
Study 1 Category Sub-category
At one clinic patients accessing HIV treatment were sent to one nurse who had access to computer based records for HIV care Health systems influence on service integration Administration requirements with medical records, files, registers and monthly reporting specific to different programmes influences service integration
A clinic that initially integrated ART care into the work of all nurses experienced problems with recording of TB statistics and had to revert to more vertical delivery of care so that one nurse could concentrate on care of TB patients and collection of TB statistics
Study 2
Multiple registers for each programme require huge amounts of paperwork, which is one of the reasons why it is easier to have vertical programmes so each nurse has a specialty and the register to fill in for that specific condition.
Because of the lack of resources, vertical approach simplifies and streamlines the large patient load (especially administration).
Study 3
Administrative demands on nurses to report on care provided and computer systems that require specific training and skills can support the separation of care.

warcinfo:
isPartOf: CC-MAIN-2022-33
publisher: Common Crawl
description: Wide crawl of the web for August 2022
operator: Common Crawl Admin (info@commoncrawl.org)
hostname: ip-10-67-67-91
software: Apache Nutch 1.18 (modified, https://github.com/commoncrawl/nutch/)
robots: checked via crawler-commons 1.4-SNAPSHOT (https://github.com/crawler-commons/crawler-commons)
format: WARC File Format 1.1
conformsTo: https://iipc.github.io/warc-specifications/specifications/warc-format/warc-1.1/


text:
Brienne of Tarth, maybe.

The first time Jacob Will saw Hannah, Brienne of Tarth from the Game of Thrones TV series came to mind: not so much the perpetual scowl but her countenance. Uncommonly tall, uncommonly beautiful, and a dazzling smile. But why was she with an older, a much older man? And in Key West. All of it seemed unlikely.

And like Jaime Lannister, Jacob would be smitten too and it would change his life forever. But that wouldn’t happen until he had committed his own eleven little deaths.

Losing his religion… if he’d had any to begin with.

Jacob Will was never big on religion, not that he wasn’t exposed to it. At some point, it didn’t “take.” Maybe it was the glut of televangelists on TV that turned him off. So going into a church for his best friend’s funeral was not high on his list, bucket or otherwise.

And a conversation with the minister afterwards was completely unexpected. What made it more so was the life-altering effect it was to have on him.

Had he given it any thought, the lyrics from an R.E.M. song, Losing My Religion might have resonated with him.

A friend’s influence can last forever.

Cowboys from Newfoundland.

I really hope this comes to Discovery Channel in the US.

‘Cold Water Cowboys’ puts the spotlight on Newfoundland

Cold Water Cowboys
(Cold Water Cowboys/Facebook)

It says something about Newfoundland’s legendary hospitality that when fishing boat captain Richard Gillett is talking to a reporter from the mainland – as those on the Rock refer to the rest of Canada – he does his best to tone down his accent a bit.

“I’m talking to you right now, and I’m trying to do the best that I can,” says Gillett with a laugh, on the phone from his home on Newfoundland’s northeastern shore.

“I can tell you, if you were here now with me and my dad, and we were into a conversation, you’d be looking at the two of us sayin’, ‘What kind of language is this?’”

Viewers might be asking the same thing when they tune into Cold Water Cowboys, a new reality series that follows the captains and crews of several Newfoundland-based fishing boats. Think Deadliest Catch, but with smaller vessels, more bleeped-out swearing and accents so delightfully thick that sometimes subtitles are needed.

“One of the producers told me, ‘Speak English, speak English!’” recalls Gillett, who captains the Midnight Shadow, based in the scenic coastal town of Twillingate. “But when we get out and everybody gets excited and a bit of fish is on the go… it’s understandable they got subtitles on us. Because some people do have a little bit of trouble understanding.”

Premiering Tuesday on Discovery Canada, Cold Water Cowboys follows six boats as they ply the waters of the North Atlantic in search of crab, mackerel, herring and more. After the 1992 cod moratorium that devastated Newfoundland’s fishing economy, the fishermen who have stuck it out must voyage much farther from home than their fathers and grandfathers did.

It’s hard and dangerous work, as seen in the show’s first episode when a stabilizer snaps off one of the boats and threatens to puncture its hull.

“In the blink of an eye, it went from a boring steaming trip to the dangers of a stabilizer breaking off and piercing the boat and the boat going to the bottom and the guys ending up in the drink,” says Gillett.

Gillett, a fifth-generation fisherman, says he and the other captains were initially a bit wary about having camera crews on their boats. “When it first started off, I expressed my views that I didn’t want anything staged,” he says. “I told them I’ve been at this long enough now that you’re going to see stuff break and you’re going to see trouble and you’re going to see dangerous situations.”

But the final product is an accurate look at the captains, crews and their communities, something else Gillett says sets it apart from Deadliest Catch.

“This show is not only about fishing,” he says. “This show shows the communities and the families and the relationships between the fishermen and the communities.”

Because really, Newfoundland is as much a star of the show as the fishermen are, b’y.

“As far as I’m concerned, the beauty of Newfoundland is second to none,” says Gillett. “In the summertime I can sit down on my bridge and watch the whales feed on small capelin. I’ve had times there have been 21 icebergs out in front of my place. Where else in the world can you do that?”

Twitter: @stevetilley


text:
Skip to main content
Non-financial boards have been closed.

Non-financial boards have been closed but will continue to be accessible in read-only form. If you're disappointed, we understand. Thank you for being an active participant in this community. We have more community features in development that we look forward to sharing soon. | The Motley Fool Community
Message Font: Serif | Sans-Serif
No. of Recommendations: 0
I can see where other's should be used when it means each other's, but suppose I am talking to a lot of other people and listening to the others' stories. (Should we write others' then?)

How about this quote from the President of Pacific University: At Pacific, you are encouraged to step out into the community and learn from other’s experiences while applying what you hear, see and do in the classroom.

Print the post

When Life Gives You Lemons
We all have had hardships and made poor decisions. The important thing is how we respond and grow. Read the story of a Fool who started from nothing, and looks to gain everything.
Contact Us
Contact Customer Service and other Fool departments here.
What was Your Dumbest Investment?
Share it with us -- and learn from others' stories of flubs.
Work for Fools?
Winner of the Washingtonian great places to work, and Glassdoor #1 Company to Work For 2015! Have access to all of TMF's online and email products for FREE, and be paid for your contributions to TMF! Click the link and start your Fool career.


text:
Give Your Patients the Best Online Experience in Town

Your website is equal to your hospital or clinic’s front desk. It’s where patients will get their first impression of your services; it needs to be easy to use and look professional.

Small Business Owners Managing Responsive Websites on Phones
5 Stars
Top Rated & Featured On
5 Stars on Google Reviews
Fiverr PRO

What to Expect from Our Healthcare & Medical Website Design

Modern & User Friendly

We follow design trends to understand how to create a stunning website that meets your patient’s expectations. Your website will work great on all devices.

Patient Forms & Resources

Streamline your medical operation by allowing patients to complete forms online, request or book appointments online, or review your treatments online.

Web Accessibility & Security

We’ll make sure your website meets the necessary levels of web accessibility and spend extra time securing your website, so you can feel confident that patient data is collected and stored in a responsible manner.

Stay Organized with a Staff Portal

Your patients aren’t the only ones who prefer digital options. We can create a secured area on your website for your Staff to log in to access documents or sensitive information.

Examples of Our Healthcare & Medical Web Design Work

Yahoo News

Make the Right First Impression with Your Patients!

We’ll help you achieve better online exposure for your hospital or clinic and increase referrals to improve patient numbers.


text:
The Ultimate Chocolate Sauce

Every Fall the leaves change, the days get shorter, the morning air turns crisp, and my wife begins to hint that it’s time to order chocolate.

One of the best things that you will ever put in your mouth is the Bittersweet Chocolate Sauce from The Kings Cupboard. They are a family run company in Red Lodge, MT doing what they do best, making unbelievably yummy chocolate sauces.

King's Cupboard Bittersweet Chocolate Sauce

King’s Cupboard Bittersweet Chocolate Sauce

It is positively, absolutely,  the best gourmet chocolate sauce you will ever taste. Do yourself a favor and get your own, we’re not sharing ours.

Yes Dear, this means I placed an order for a case today, it will be here Friday.


text:
Are we more expensive because we are a bigger company?

One question we are asked regularly is that because we are a big company with an incredible reputation, does that make our prices more?

We have a straight forward pricing structure which means that you will get the best possible quote within 2-3 hours of inspection.

Competitively priced, that’s why we have grown to the scale we have.

At Boiler 24-7, no job is too big or too small. Our aim is to provide a fast, efficient, cost effective service offering all plumbing services from basic boiler repairs and maintenance to a complete central heating installation.

Professionalism and customer service is vital to our success. Our Engineers are Gas Safe registered as well as being qualified on all appliances. They are more than happy to accommodate your requirements and for added peace of mind all engineers carry photo ID.

We are on-call for our customers 24-7, 365 days-a-year. After we get an enquiry, we guarantee to respond within the hour. For your convenience our engineer will contact you 60 minutes prior to arrival and in an emergency we will endeavour to be with you within 24 hours.

If you urgently need your central heating fixed, feel free to contact us though our website or call us at 0203 103 0390.

Feel free to email us at any time: [email protected] and 0203 103 0390.

Share this Post


text:
The Bhaitards

Salman-Khan-Shahrukh-Khan (800x600)

Two years ago, I had a heart-to-heart chat with Shah Rukh Khan in Singapore.

I was part of the media contingent that was there to cover an award function and as usual, Shah Rukh was the star performer.

Unlike other bosses, my editor knew that I had a tough week looking for exclusives and she had indulgently said that the interviews of the top stars attending the event would suffice for the editorial agenda.

“Just send me the interviews and then you can relax,” she had said.

It basically meant that I only needed to speak to Shah Rukh Khan, Priyanka Chopra and Aishwarya Rai-Bachchan.

After going through a horrible week that assignment looked easy and I was quite happy.

Shah Rukh arrived on the day of his performance and said he will need just an hour to sync in with the background dancers and the stage management team.

The rest of the time, he declared, will be devoted to us – me and a journalist-friend from another reputed English newspaper. We decided to speak to him at his exclusive but cramped green room, backstage.

The day was going like clockwork as Shah Rukh finished his practice well in time and settled down with us, incessantly puffing on his trademark Classic cigarettes which comes in red packets.

Just before he joined us, I was checking his Twitter account and found that he hadn’t tweeted for a long time. That made me curious. I had started wondering whether he had stopped using his newly gifted Iphone or had shifted back to his old love, a black and silver Blackberry Bold.

‘Twitter broke my heart’

Those were the exact words he used to describe his experiences when I asked him why he had stopped tweeting. Frankly, I was not expecting such an answer.

Shah Rukh then went on to describe how a bunch of faceless, nameless morons who had opened fake and misleading handles on the micro-blogging site would go on showering expletives on him and his family.

The worst part? They would do it just for the kick of it and there wouldn’t be any apparent reason for that action.

Some would just wake up, post a few gaalis in Hindi or in absolutely wrong English and then go back to sleep again. The gaalis would mostly contain words that referred to a man’s or a woman’s genitals.

I never heard a similar complaint from Salman Khan. I then went back to check with Aamir because he too was on Twitter and didn’t seem to tweet much. I was told Aamir too was upset with those faceless people on Twitter.

Salman wasn’t complaining probably because he had practically never clicked on “@”.  He was just happy tweeting.

After a few more meetings with the other stars attending the event, I realised that the problem was generic and much bigger than I had imagined.

Most of the stars were reeling under the negativity that these ‘twit fans’ were spreading.

The reports of stars getting abused on social media were not new but the monstrosity of the problem sunk in when I actually spoke to a lot of them in person.

Every star was capable of giving these ‘twits’ a fitting reply and trust me, they perhaps knew more sinister Hindi gaalis. The problem was: They couldn’t do it because they were public figures on social media.

A few actors showed me some of those abusive tweets and I was ashamed of the fact that I breathe the same air as those people posting those tweets.

Who are these people?

I did a small survey of people who have opened those so-called funny and fake accounts on twitter and frequently post explicit jokes. When they are not doing that, these ‘jokers’ go on a star-abusing spree.

Take this now: A large part of these frustrated ‘tards’ include senior managers, students studying technology/engineering, senior officials in IT and people calling themselves journalists.

A little investigation and diligence can expose 80% of this population.

A large part of that ‘twit universe’ is occupied by two sets of people: One who called themselves fans of Shah Rukh Khan and the others, the Salman Khan fans.

We can do without these ‘Bhaitards’

shah rukh and salman lastIt happened again on Tuesday night.

Suddenly two contrasting trends appeared on Twitter’s India map. One was directed towards Salman Khan and the other, towards Shah Rukh Khan.

The worst part of those trends was that it included terms describing one’s sexuality in the most regressive way possible.

I don’t want to go into the details of these trends because I don’t think I am a part of this ‘tards’ brigade. I saw the tweets and it made me puke in disgust.

Trust me, both Shah Rukh Khan and Salman Khan can do without you guys.

Both SRK and Sallu don’t want fans like you.

Go ask them.

You guys have no shame, no education, no courage and absolutely no sense of decency.

You guys are a bunch of frustrated and sexually starved morons. It is just masturbation that you indulge in everyday by giving gaalis to a Bollywood star who you seem to have fallen in love with and just want his attention.

Some of you are more clever. You go and tweet with the same derogatory hashtag and say that those hashtags should not be used while tweeting.

After posting a tweet like that you may feel aroused but people like us who have studied beyond class ten can see through your act.

None of you have the courage to come out with your photograph or your name.

You know that if anybody caught you, they can teach you some better gaalis that involves your family members or your genitals.

We have studied beyond standard ten, you know. And pity, that you guys look like uneducated idiots.

I am so ashamed of you guys.

I am sure Salman and Shah Rukh are ashamed of you too.

You don’t like this post? Why don’t you go ahead and post all the gaalis that involve my mother who’s no more, my sister, my girlfriend or an imaginary boyfriend.

I will read each one of your tweets, comments and posts.

Arrey! Are you climaxing hearing that?

Yeah baby!

Short-link of the post ->

Here is another report on Firstpost about the disgusting Twitter trends yesterday ->

9 replies »

  1. 1. It is not just twitter it is online phenomenon in India. Many sadist just abuse star family, their personal life, their religion, even go to their bed room life . All these qualified but uneducated class prowling all over internet. May be few are just satisfying their frustration by abusing other.

    2. It require a deep analysis on why we the so called qualified youth indulge in such crap activity on online platform , weather that is starting from stars to politics , majority views are always those gallis, personal attack etc. instead any meaningful exchange of thoughts , emotions, expression.

  2. I am not regular follower of your articles, but when I go through some of the articles you’ve written, its so damn true about the happenings in society currently. Now coming to this article it makes no sense why these so called fans fight all the time and not even leaving their family members behind.

  3. Please tell SRK to cry us a river in his UK mansion, or with the 100 crores he just won, or with the shitty new movie with Farah, whose husband he slapped and didn’t have the humility to apologize to (They apologized to him! LOL)

    Am I sexually frustrated? Yeah. Is masturbation the only form of exercise I get in any given week? Sure. Do I abuse stars on twitter? Nah… I never thought they’d check. Now that you’re telling me they do, I’m getting ideas…. lol. Nah, it’s cool man. Just don’t make these people, who won the biggest fucking lottery of life, to be some sort of victims. They chose to put themselves there, and with the bouquets (and more wealth than 99.999% of the country) come the brickbats too.

    • So you’re saying they deserve to get abused on twitter by some morons who mostly happen to be fans of a rival star? They’re humans as well, famous or not. Shitty movie? Great judgement without watching it though I can guarantee majority of viewers will love it as they did with their past two films and you’ll still end up watching it ;).

      And are you close to SRK and Farah’s husband? They made up shortly after that. But what’s it to you? If there was any issue would SRK and Farah be working together?

      And yes he is rich, why don’t you go try to accumulate some wealth for yourself instead of posting lame comments.

      • I’m not saying they deserve anything. Like I said in my last comment, if you put yourself out there (WAY out there in some cases), you’re gonna get the good with the bad. That’s how people are.

        I’m not talking about fans of rival stars, there are people who look at their lifestyle and try to get their attention by using shock value. Others just wanna vent.

        Yeah, with the track record being Main Hoon Na and Om Shanti Om, I’m not expecting their next movie to make it to the Oscars.

        What is it to me? What is it to you? I’m talking about the person who comes across as being humble and down to earth, when the reality is anything but. Would they be working together? I think after Tees Maar Khan, Farah has learnt where the money comes from.

        If my comment was lame and got you to reply, what does that make your comment?

  4. Yes Soumya, those trends were lame. I love salman khan, no matter what. I have never abused or used galis to anyone nor will I do ever. I feel shame on behalf of salman khan fans who tried their best to stop those trends and failed. I tried myself too to stop people on that day, but I failed. Even today, some SRK fans comes and spit galis on my TL, just because I tweet how much I love Salman. I reply in a calm manner, but they keep nagging. I believe this kind of abuse is thrown from both side.
    I ask myself, why do One have to show their hatred to the person next to you. If you cannot say something good, please don’t say bad either.
    I don’t remember at the moment, but someone said, you don’t need to hate srk to love salman khan and you don’t need to hate salman khan to love srk .

Let us know whether you liked the post or not

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.


text:
The Leibniz Institute for the Analysis of Biodiversity Change

is a research museum of the Leibniz Association

Our Permanent Exhibition: " Our Blue Planet - The Living Network"

Understanding our "life in the global network" makes us comprehend the need for conservation of and research on the biodiversity on our planet and lets us realise how mankind depends on it.

"Life" is all about diversity – the diversity of organisms and different life forms, habitats, species and genes. This diversity, or biodiversity, is itself the basis for life on Earth. Because every living being – whether microorganism, fungus, animal, plant or human – interacts with numerous other organisms in a variety of ways. Thus, at the same time, it shapes the habitat and the ecosystem it lives in, it also depends on it. The different ecosystems on earth in turn are connected to one another. The result is the "living network", of which human beings are a part.

As the growth of human population is enormous, Humans are the fundamental cause of one of the three biggest mass extinctions the world has ever seen. Thus, involved in a race against time, museum scientists study biodiverstiy in nearly every region of the world, from the African and South American tropics to Antarctica but also in Europe and Germany.

Our permanent exhibit provides insights into the most important ecosystems on earth and into the "laws of nature":
Why are bushfires important in the savannah? How do animals adapt to extreme conditions in the Arctic and Antarctic? What role do driver ants play in the rainforest? How is the Sahara desert linked to Central Europe and why does the Amazon rainforest depend on it? How do freshwater habitats function?

The exhibitions show that precise knowledge about species, that is, elements of life communities, allow well-founded prognoses about the cooperation in the ecosystems. The vital research of the Zoologisches Forschungsmuseum Alexander Koenig contributes to the maintenance of the functionality of our environment.

Biodiversity research - Unravelling the nature of diversity

Freshwater - Life in Flow

UNDER CONSTRUCTION: Rainforest - Canopy

Rainforest - The Understorey

Savanna - Changeful Paradise

Arctic / Antarctic - Survival in Ice

Desert - World of Extremes

Central Europe - Discover Homeland

Dioramas within the Permanent Exhibition

Contact person

Head of Exhibition Department
+49 228 9122-226
+49 228 9122-212
t.gerken [at]

Opening hours

Opening hours
Tue to Sun: 10:00 to 18:00
(last entrance: 17:15h)

Wed: until 21:00h
(last entrance: 20:00h)

Mondays: only on public holidays

Mondays (except on public holidays)
Christmas eve, Christmas day und New year's eve

Entrance fee (1 day ticket)
6,00 € (regular)
3,00 € (discounted)


text:
Glee Club Cardiff
World Comedy Clash 2022 (18+)
Sunday 19th June 2022

London's number 1 original and longest running comedy clash show comes to CARDIFF by popular demand with a star-studded, action packed line up.
Full COVID-safety guidelines available here.
This event was rescheduled from 12th April 2020, 1st November 2020 and 20th June 2021- All tickets remain valid for the new date.
All under 25s may require government-issued photo ID to gain entry. (See FAQs)

Booking for this event has now closed.
There will be a small number of tickets available on the door, first-come-first served.

World Comedy Clash Cardiff

Aurie Styla

Rudi Lickwood

Jay Handley

Dana Alexander

Drew Taylor

Kane Brown

Advance Ticket Prices

  • Show Entry

  • Booking fee £1.85

  • Doors open 6:30PM
  • Last entry 7:15PM

More information

  • Unallocated seating
  • Food available
  • Minimum age: 18+


text:
Release Blitz

Royally Indecent by Kelly Jamieson

Royally Indecent by Kelly Jamieson is available now!
Available on All Platforms

A warrior. A prince. The one woman who can reconnect their broken hearts…

Chelsea Alderich

From the moment Ford rescues me from a bad date, I feel a spark. Too bad he’s gay, but he quickly becomes my best friend. And a roommate I can’t stop having hot dreams about. Then, at a charity gala, I meet Prince Griffin of Eria, a reformed playboy who runs a non-profit for veterans. And it isn’t long before flirting turns into falling in love.

Griffin Marlow

This American girl is messing with my head. I can’t stop thinking about her. She’s sweet and pure, and I’m falling hard, but there’s no way we can have a future together. I’m only here in the U.S. temporarily. I have to go back to Eria to take my place in line to the throne.

Ford Sullivan

Chelsea’s my best friend and my roommate, and even though my feelings for her are more than friendship, I won’t touch her unless she wants it. I know she’s seeing someone else, and to be honest, I’m a little jealous. Until I walk into our apartment and meet her new boyfriend—Prince Griffin of Eria. Then I’m freakin’ ballistic.

About Kelly Jamieson

Kelly Jamieson is a USA Today bestselling author of over 40 romance novels and novellas.

Her writing has been described as “emotionally complex”, “sweet and satisfying” and “blisteringly sexy”. She likes black coffee, white wine and high heels…and of course cheering on her Winnipeg Jets during hockey season!

Connect with KellyWebsite:

Leave a Reply

Please log in using one of these methods to post your comment: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.


text:
Ísland (Iceland) Fairy Tales

img_7408Book: Iceland Fairy Tales by Anonymous

Date Read: July 11, 2018

Rating: 4 (of 5) stars

I first saw this little book at the Museum of Icelandic Sorcery and Witchcraft in Hólmavík. While I decided to pass on it then, it kept nudging at me each time that I saw it. I thought I had left without it, but when my flight home was pushed back an additional 2 days, I ended up back in Reykjavík at a gift shop I had not yet visited. There it was, and I decided that I would take it as a sign that the book needed to come home with me.

Although clearly intended as a book for tourists, it was a nice little introduction to Icelandic folklore. There were definitely some familiar elements in some of the stories, but more emphasis on ogres, trolls, and similar creatures. After experiencing some of Iceland, I understand why there is a history of these kinds of beliefs. I can easily imagine trolls or elves hiding in the nooks and crannies of the Icelandic landscape. Despite some issues with editing (and perhaps poor translating), it was a quick little read that left me satisfied with the content. I also found other books that I am hoping will give me a more in depth picture of the country’s mythological history.

Boris’s thoughts: “I’m glad your home, but I’m not talking to you yet. 2 paws. I guess.”


text:
#6Degrees — Wolfe Island to…

This month we are starting with the book Wolfe Island by Lucy Treloar. I looked it up AFTER I wrote what follows. NOT EVEN CLOSE, hahahaha! The Devilreads synopsis makes it sound like a piece of trash, even though I know that isn’t what they were going for.

wolfeisland (Custom)I imagine that Wolfe Island is a paranormal romance (which is even worse than regular romance in my opinion as it gets as close to bestiality as it can) in which our heroine has been fired from her job as a cop in Big Town X by her sexist boss. Wolfe Island is a small community and she becomes sheriff and meets Hunky Wolfy AND finds out that her ex-Boss is a Warlock. In the end, I would gladly kill them all.  One of my issues with PNR is that the male characters are never real men, but are just assholes with good looks.

markofaman (Custom)

A book about Real Men, as opposed to just macho testosterone, is The Mark of a Man by Elizabeth Elliot. In it she writes to her nephew about what a Christian Man should be. She uses the example of her dead husband Jim (he was a missionary who was eaten by cannibals). She gets specific about just how Jim exhibited the best and worst of Manhood, all to show her nephew something important. She shows him what a Man should look like from a Woman’s Perspective.

playtheman (Custom)

How to be a Man, from a Man’s Perspective, is what Mark Batterson’s book Play the Man is all about.  Men aren’t just boys that have reached a certain age, boys have to be taught what it means to BE a man. Just like soldiers. You don’t throw a civilian into a combat situation and expect good results. It takes training AND experience.

jokerone (Custom)

A book about a real life soldier getting experience is Joker One. A young LT in Iraq tells of his tour. Not my favorite book but it was good to be reminded just what our boys have gone through for us. With a title like Joker One,  there is really only one direction I can go, right?

ijoker (Custom)

I, Joker is one of the very few Elseworld graphic novels to get 5 stars from me. The role reversal between the Batman and Joker persona worked for me. I doubt it will ever work for me again in another book. It is a very red cover, isn’t it?

The final book in this chain also has a red cover. The Brothers Karamazov. I only gave it 3 stars back when I first read it in ’07. I wonder what I’ll give it the next time I read it?

And that is how you get from Wolfe Island to The Brothers Karamazov.

If you’d like to participate in the #6degrees series of posts, head over to #6Degrees Meme to find out the starting point for each month. They’re not always punctual, so sometimes you have to wait until a week into the month.

bookstooge (Custom)

12 thoughts on “#6Degrees — Wolfe Island to…

    1. This is about the only monthly meme that I participate in regularly. I have a blast doing it and it has the up-side of helping me get my blog organized 😀

      shudder indeed…

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s


text:
Just One Touch

I should have known this would happen…
Nothing about my fraternity was ever simple. Parties, tequila – tons of tequila – and wild souvenirs from our kind of crazy.
Never, and I do mean never, did I expect my brother’s girl to target me in a midnight prank. A prank that backfired and left me squealing in pain.
Have you ever seen those shows, the ones that say the “dirty deed” sent you to the ER? Well, I went to the ER, and yes, my manhood was involved. Let me just say I gained absolutely no pleasure from it. Unless, of course, you consider that sweet nurse who treated me.
The problem? She hated me…and I had no idea why, but I wasn’t willing to let her walk away until I figured it out.
Emelie was feisty, and I’d never felt the type of excitement I did after spending only five seconds in her line of fire. I was gonna enjoy this…way more than I should, and I knew it.
She saw, she conquered, and I was defeated.
All it took was just one touch, and oh, what a ride it was.

My Review: 4 stars

What a sweet story. This story has a bit of insta-love in it and that is not usually my kind of read. But this book is just so sweet, that I can handle the insta-love.

Clayton and Emelie don’t start out on the right foot. Emelie automatically dismisses Clayton because she believes he is a player. He is a frat-boy and she believes they are all the same.

Clayton is attracted to Emelie from the moment he sees her. When she dismisses him, he takes that as a challenge.

Clayton doesn’t give up on Emelie and when a run in happens at the laundry mat, everything changes.

Emelie has secrets. Emelie has trust issues. Emelie has a hard life.

Clayton wants to do whatever he can for Emelie but he know she won’t take the help without a fight.

Mainly, Clayton wants to love Emelie and he hopes she will love him back.

jsut one touch 3But can Emelie love someone after everything she has been through? How can she trust someone when everyone else in her life, besides her best-friend, has let her down?

This is a really sweet story. Clayton and Emelie’s story make my heart smile. I usually read books that are darker but this is just the kind of read I needed this weekend.

Great job!!!

Buy Now:

About the Author:

harms .jpg

C.A. Harms is an avid romance and mystery reader. She’s always had a love for books, getting lost in writing and storytelling even as a young girl. She enjoys happy endings and HEA love stories.

She lives in Illinois and enjoys spending time with her husband and two children. She holds an addiction for Starbucks White Chocolate Mocha’s and KitKat when she should really be focusing on water and maybe a fruit or two to make herself feel less guilty, but that feeling quickly passes…thankfully.

She is easy going, fun, and although she may seem like one of the quiet ones at first, you just wait until she gets to know you better…that quietness changes, fast

7 thoughts on “Just One Touch

Add yours

Leave a Reply to Saturday Nite Reader Cancel reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

Create a free website or blog at WordPress.com.

Up ↑

%d bloggers like this:


text:
When it comes down to a nice beverage to enjoy, it is hard to beat a nicely steeped tea. Wether it be at the end of a long day or a nice way to just start your morning off there seems to be a tea for almost every occasion. Now what if I told you there where teas infused with cannabis? Just like a regular tea a cannabis tea can pair well with different occasions. Here at Boondom we have done our best to bring you a few of our favorite teas.

A Heavenly Haven

1. Rise by Haven St.

Some people live by a morning coffee others by a nice warm tea. Haven St. understands this concept and has made a wonderful cannabis tea called Rise Number 550. This Citrus Berry Tea brews when added to warm water and left to steep for 3-5 minutes. When it is done it is a beautiful purple color. Each tea contains 10mg of THC and is sold as an individual packet.

Like an Arnold Palmer but better!

2. Lemonade Ice Tea by Summit

This summer has been a hot one and nothing seems to beat the heat like a nice cold drink. Well what if we took two summertime favorites, mixed them together and infused them with cannabis? That is exactly what the Lemonade Ice Tea by Summit is. While not your typical cannabis tea it has become a fan favorite due to it’s 10mg infusion and lightly sweet yet refreshing taste. If a nice cold drink sounds good to you be sure to check these ones out and don’t wait they go quickly.

A Beautiful Vibrant Blend

3. Happy Hibiscus Mate Tea by TGOD

If you are interested in trying a cannabis tea but feel that 10mg may be too high of a dose maybe the Happy Hibiscus Mate Tea by TGOD is right for you! Unlike the Rise Tea this cannabis tea comes in a pack of two tea bags each having a dosage of 5mg. This tea boasts flavors of hibiscus, cacao, orange peel and turmeric and has a beautiful cherry red color when steeped.


text:
What gives sugar its white color?

Sugar is naturally white. When the sugar is initially extracted from the plants, it has a golden color because of the non-sugar materials attached to and within the sugar crystals. This golden sugar is then purified, where these plant fibers and molasses are removed, extracting the sugar molecules from the non-sugar materials and restoring the sugar crystals to their natural white color.

Open chat


text:
The Lind Boracay Review

The Lind is a luxurious beachfront hotel that’s located in the northern part of Station 1, Boracay. In this review I’ll cover the place in detail…

Among other topics, I’ll discuss its main charms, its location details, its highlight worthy amenities, the best rooms, how to contact them, plus I’ll also cover both its pros and cons.

Once read you should have a very good idea of what to expect, and if it’s the right place to stay for you.

About The Lind & Its Location

You’ll find The Lind at Station 1 of White Beach, a little north near Willy’s Rock. Locals know that prices rise the closer you get to the end of Station 1, and The Lind is pretty high up in there. The reason for this is the superior ocean views and finer sand on the northern side of the beach.

The Lind is right next to many great restaurants like Fridays (seafood and bar with a tropical flair); and Kasbah (Moroccan-Mediterranean, great vegan and Halal dishes).

Willy’s Rock, a minuscule island that rests on the shallow beach of Station 1 is also nearby. At the top of it is a statue of Mary and a platform, where you have a bird’s-eye view of the White Beach.

The Lind has taken full advantage of their prime beachfront spot by giving each room a view. Some are overlooking the ocean, some the garden and some both. Another way they highlighted their beautiful spot is with an infinity pool facing the waters, it’s a modern touch that you wont find in mid-range resorts. In fact, the whole resort designed modernly with luxurious touches.

One thing to note is the lack of budget restaurants and stores in the area, since this is the fancier side of Boracay. So be ready to pay a pretty penny for sodas and other small items on your day at the beach. You can always visit the main road or D’mall for more affordable grocery stores and restaurants, though.

See The Lind in Detail & Check its Best Price on Agoda

  • Huge room capacities great for families and groups
  • Close to the center and easy access to the main road
  • Good room amenities such as kitchenettes
  • Slow Wi-Fi and a busy breakfast area

Highlight-Worthy Amenities

The Lind has a spa inside their resort, so once you arrive, you can unwind from your flight with a spa treatment right away. Very convenient if you’re getting a massage, since you can go straight to your room in a fluffy robe if you want to.

If your idea of self-care is hitting the gym instead then don’t worry, The Lind has a fitness center inside, too. You can burn the calories you had from the delicious restaurant inside the resort.

Now let’s talk about the main event, the rooms. They are spacious, furnished with taste and the decor has this subtle patters of the sea. They’re understated but decadent. Each has a big balcony with seating that overlooks either the White Beach and sunset or the garden and pool.

You also have all the modern comforts like a flat screen TV, satellite cable and WiFi, among other things, in case you want to take it slow spend the day in.

How does a private pool sound? Some rooms at the Lind have their very own dipping pool. Ideal for private pool parties, skinny dipping… or maybe just meditation. Either way, it will be your private oasis.

The biggest highlight for me, though has to be is the infinity pool outside, because of its good size and closeness to the beach, not to mention it looks great… It even has a dedicated area for children and a jacuzzi.

You can go back and forth between swimming on the ocean and having a relaxing dip in the pool… or just sunbathe at the poolside daybeds, with a fruit shake away from the busy crowd. Ah, what could be better in the scorching heat of Boracay?

My Top 3 Room Recommendations

Choosing a room at The Lind’s can be a challenge since they all look amazing online. I understand, there’s a lot of money on the line and it’s kinda hard to pick especially if you can’t check it out in person, right? Don’t worry, I’m here to help you narrow down the perfect room for your holiday. .

Note: All the rooms below are good for two adults, but two children under 12 can stay for free.

Your safest bet is the Garden Room, especially if you know your stay in Boracay will be an activity-filled one and you won’t be spending a ton of time in the room. You’re getting the luxurious ambiance, the balcony over-looking the garden, all the things expensive touches you can expect from a five-star hotel without paying for any premium features that you’re not really gonna use. It just makes sense.

The price difference of the Garden Room to the other rooms is significant enough that it’s really worth considering, you can put the extra dollars you’ll be saving on a fancy dinner and trust me, you won’t feel the difference in price once you’re in there. It’s still a fancy room.

Tip: if you’re travelling with children, you can opt for 2 Twin beds instead of the King with no additional charges

On the other hand, if you plan on spending more time enjoying the resort and taking it easy during your holiday, let me recommend you the the Sea Premier. It is absolutely perfect for unwinding and lounging because of the way it’s set up, I think you’ll find the room very large. And only does it overlook the ocean, because the Lind is on the White Beach you will be facing the sunset everyday.

Call room service for some tropical drinks (or cocktails to start the happy hour early!) and you have yourself the perfect no-plans vacation. Between you and me, the Sea Premier is great value for your money, since it makes your resort room the highlight of your stay, you won’t really need to supplement with other activities if you don’t want to.

Now, for those of you who’ve been to The Lind’s website, we all know this one is coming up: Sea with Pool room. Imagine, your very own dipping pool looking out into the best waters of the country. There’s a veranda with daybeds for sunbathing or massages… I think this room is so ideal for couples whether you’re on your honeymoon or just want a romantic weekend.

This room is also going to be ideal for anyone who loves to party, I mean, that gorgeous room with an open veranda and private pool is just begging for a pool party. You will have Instagram pictures to die for.

Now I wouldn’t recommend the Garden Pool room, solely because it’s too close to the main pools and personally I think personal pools demand a lot of privacy.

What Guests Say & My Take

The Lind is rated 9 in Agoda, that’s considered exceptional and I agree with all the praises, the most recent guests seems to be all very happy. All good.

In they are rated 9.2, again great score. I think the only consistent thing resembling a complaint is the check-in and check-out time. Some guests find the process longer than usual, but even that is not severe enough to be an issue, in my opinion.

Guests from TripAdvisor gave The Lind a 4.5 out of 5. I’m seeing some people mention the restaurants. I don’t see too much negativity but many wish the menus would be expanded.

Now seeing all these and being a local, let me tell you some things… First, this is a great resort with unbeatable location. If you want to stay in Station 1 (and you should) I think this place is a solid find.

Some guests compare The Lind to Shangri-La, and that’s unfair. On paper they sound the same, both are five-star resorts and located on the same side of the island but take it from me, these two have very different functions.

Shangri-La is inaccessible to the public and very exclusive. You need a special boat or shuttle to go there, so it’s ideal for those that love serenity and private luxury. On the other hand, the Lind is at the expensive side of the White Beach. There you have access to the best things Boracay has to offer when it comes to restaurants and activities.

Both are great on what they do, but some guests are critical against the Lind when they compare it to Shang. I think what they’re also forgetting is the enormous price difference of the rooms, especially on the bigger suites. If you factor all that in, you’ll see that The Lind actually holds it’s own.

Conclusion & Summary

The Lind is a beautiful luxury resort, located at the most desirable area in Boracay.

Here’s a quick summary of the 3 most important points made in this review:

  • There’s a balcony with a view in every room
  • It’s located at the Northern side of Station 1
  • It’s a five-star resort is competitively priced

Hope this review helps you have the perfect stay in Boracay. Have a good trip! 🙂

The Lind Contact Info

Contact number: +63 36 288 1059
Facebook page:
Address: Station 1, Barangay Balabag, Boracay Island, Malay, Aklan, 5608, Philippines

P.S. If you’re not yet sure if The Lind is the right place for you, 3 good alternative hotels to have a look at with similar price-points and locations are are Two Seasons, Discovery Shores, and Shangri-la.


WARC-Identified-Payload-Type: application/xhtml+xml

text:
Draft Day

by Kilian Melloy

EDGE Staff Reporter

Friday April 11, 2014

Kevin Costner stars in ’Draft Day’
Kevin Costner stars in ’Draft Day’  (Source:Summit Entertainment)

Ivan Reitman's new comedy, "Draft Day," doesn't exactly fumble the ball, but the director behind "Ghostbusters" and "Meatballs" -- who also has served as producer on more subtle fare such as "Up in the Air" -- certainly spends a lot of time and energy zigging and zagging on his way to a touchdown that never quite happens.

Kevin Costner (no stranger to the sports movie genre, though his earlier entries have tended to focus on baseball) plays Sonny Weaver, Jr., the general manager of the Cleveland Browns. (One of the film's conceits is that it zooms around the country, paying visits to the various home stadiums of real football teams.) It's "draft day," the day when NFL teams jockey and make deals behind the scenes before publicly announcing their draft picks. GMs like Weaver have a chance to energize their team's fans base by picking hot new talent; young players looking to go pro have a chance for fame, glory, and -- depending how high up on the draft pick list they land -- pay checks that run to the mega-milllions.

Weaver's under pressure from all sides. The team owner (layer by Frank Langella) wants a pick like the aristocratic Bo Callahan (Josh Pence), touted to be the next big thing on the field. Weaver himself is more a fan of Vontae Mack (Chadwick Boseman, another alum of baseball movies, namely last year's Jackie Robinson biopic, "42"), an athlete from a working class background who takes to Twitter to press his campaign. Team Coach Penn (Denis Leary) feels that Weaver isn't including him in the process; the team's quarterback, Brian Drew (Tom Welling) fears that he's about to be replaced; his mother (Ellen Burstyn) has chosen this day, of all days, to scatter his father's ashes (on the field, of course); and a shy young intern keeps getting underfoot.

Oh, and then there's the matter of his co-worker, Ali (Jennifer Garner), who is also Weaver's girlfriend. The two of them have some serious talking to do, and they keep retreating to the storage closet for their heart to heart chats. There's a lot about this movie that seems forced and tired, from Costner himself (isn't he little too old to be playing the guy whom a tough and capable woman like Ali is trying to nail down?), and the recurring gag of the closet is only one irritating device; another is the steady succession of personal and family revelations that Weaver trots out, one after the next, to melt Ali's heart and explain actions that look, to outsiders, heartless or bone-headed. There's so much melodrama here that a better title might have been "Football Camp."

If the storyline, with it myriad of characters, cameos (Sam Elliott appears for one scene; Rosanna Arquette for another) didn't make the film feel over-stuffed, Reitman adopts a visual style that drives it right over the edge. Again and again, as characters converse on the phone, Reitman's split-screen spills from one setting into the other; at one juncture, a character walks right out of his half of the screen and across the scene where, in another location, a meeting is underway. A sports movie that takes the form of a succession of heated one-to-ones and conference calls is hard to justify in the sense that it's not living up to the physical rush of athletics, and this technique lends the film some dynamism, but it also tends to take the viewer out of the experience. Worse, it can be visually confusing and make an unnecessary jumble out of scenes that ought to be cleanly delineated.

Garner's character possesses some real chops: At one point, after Costner and Penn get into a scrap that involves a small fire, Ali -- after dousing the blaze -- offers the guys some coffee. Distracted, they accept her offer, at which point she underscores the point she's making: "I'm not getting you idiots anything." But aside from a few moments when she gets to show she's as much a force to be reckoned with as any of the males in the club house, Garner is relegated to the gender-stereotype conforming role of the supportive female, who always has her man's back even as she's lending him her sympathetic ear.

The story's athletes play only tiny roles. We get a glimpse of Vonae Mack's hunger and simmering sense of injustice at the prospect -- which seems ever more likely -- of being passed over for a coveted Number One spot on the draft pick list, and we see Callahan as little more than an entitled, insincere, and (possibly) unpopular-in-the-locker-room brat. We even see Browns' QB Drew's terror and fury at the idea that he might be bumped. All this is potentially meaty stuff, but it's used as filler. Even Leary's deadpan rants have a warmed-over quality.

The real heat emanates from the back-room wheeling and dealing, which takes us from city to city in a whooshing, graphics-laden tour of some of the NFL's teams, but there's a cartoonish patina to the project that leaches away substance and drama. It's as though the idea were to leave the hard hits on the field of play and not jolt the box of popcorn out of anyone's hands. The result falls somewhere between "Monday Night Football" and "The Young and the Restless."

Kilian Melloy serves as EDGE Media Network's Associate Arts Editor and Staff Contributor. His professional memberships include the National Lesbian & Gay Journalists Association, the Boston Online Film Critics Association, The Gay and Lesbian Entertainment Critics Association, and the Boston Theater Critics Association's Elliot Norton Awards Committee.


text:
Abrau-Durso Blanc de Blancs Brut d’Or 2018

Award-winning Russian sparkling wine
No reviews. Be the first!
  • $63.00

Learn More About This Product

Primary Notes: Apple / Pear Lemon / Lime White Flowers Oyster-y

Secondary Notes: Brioche, Butter Pastry

Tertiary Notes:

Body: Full

Dryness: Very Dry

Acidity: Medium +

Tannin: Light

Alcohol (%): 12

Origin: Krasnodar, Russia

Maker: Abrau-Durso

Grape: Chardonnay

Fermentation: Steel Only

Awards: >90 pts

Serving Temperature: Best served between 8–10 degrees.

Asian Food Pairing: Chilli crab, Korean fried chicken, Thai fried rice

Western Food Pairing: Lobster and crab dishes, various appetisers, cheeses and fruit desserts.

Abrau-Durso Blanc de Blancs Brut d’Or 2018

Abrau-Durso Blanc de Blancs Brut is an award-winning Russian sparkling wine. Subtle gold colour with straw-yellow reflections. Fresh and intense bouquet of buttery pastry, brioche, white flowers and a hint of apples. Soft mouthfeel and creamy texture. Full-bodied palate of fresh green apple and lemon citrus fruit flavours with complex mineral notes. Closes in an afterglow of mineral notes. Excellent as an aperitif!

100% Chardonnay. Assembling the finest quality Chardonnays of the same vintage in different parts of the Abrau-Durso vineyards. Harvesting the grapes with special care so as not to damage the berries and stems, they are then kept cold before pressing. Second fermentation takes place in deep mountain tunnels. Riddling is done both manually and automatically. The wine ages on lees for about 3 to 4 years.
The terroir of Abrau-Durso includes a unique soft climate, an authentic composition of soils and a special compass rose of Caucasus foothills. The wind carries aromas of local nature into the vineyards, which the wine styles reflect. The winds of Abrau-Durso valley in the foothills of Navagir Mountains create a mixture of dry herb, steppe flowers, salty sea and fresh lake aromas.

Millions of years ago, Abrau-Durso vineyards were the ocean floor. Today, sea minerals give power to the vines. Limestone dominates the soils, which makes it similar to some of the world’s best winemaking areas (such as Chablis). The proximity of the Black Sea and the green forests of the North Caucasus National Park create the perfect conditions for Abrau-Durso’s vineyards. Located amphitheatrically in between green hills, they get the most of the sun. The proximity of the sea is especially important at night when the vines need a chill for the grapes to ripen in the right way.

How about a Red from Greece? Check out Anatolikos Fine Mavroudi of Thrace Red 2017.


text:
Weekend Edition: September 20

Posted on: September 20th, 2009 at 9:56 am by

Recent Stories

Uncapped: Nobody Beats IZ THE WIZ

  IZ the WIZ: hands down one of the most illustrious and renowned graffiti writers in and outside of our fair city. May he continue to Rest in Peace. In this installation of Uncapped, guest contributor, Freddy Alva, is back with an excerpt from the new issue of his Black Book Series magazine: Pound for […]

Four Teenagers Arrested with Loaded Guns at PUBLIC Hotel on Chrystie Street

Four teens were busted with three loaded guns inside the PUBLIC Hotel this week. Jarell Swan (19), Anton Philips (18), Linwood Spruill (18), and an unidentified 15-year-old boy were arrested at the swanky, 28-story Chrystie Street lodge on Wednesday, and charged with weapons possession. The four friends were reportedly smoking weed in their room shortly […]

No Return in Sight for Tenants and Businesses Displaced by Mulberry Street Fire

Months after the deadly fire at 78 Mulberry Street, displaced tenants – residential and commercial – are still waiting for renovations to begin. The two-alarm fire broke out at 78 Mulberry Street just before 4:00am on April 15. Roughly one hundred firefighters responded to extinguish the flames, which reportedly spread from the fifth floor. The […]

Counterfeit Goods Raid on Mott Street Yields Air

Morning strollers yesterday were treated to a sight when Counterfeit goods contractors pulled up in a van, and forcibly gained entry into a gift shop on Mott Street. Shun Fat Gifts at 49 Mott was shuttered at the time of the raid, so the contractors cut the lock then drilled the control lock for the […]

Kyle Martino Readies Soccer Bistro ‘No One Home’ at 141 Chrystie

A former professional soccer player for Major League Soccer is planning a nightspot inspired by the sport on Chrystie Street. Kyle Martino, who split seven seasons as a midfielder for both the Columbus Crew and Los Angeles Galaxy, is currently reading No One Home. The principal describes the businesses in liquor license paperwork as a […]


text:
Hollywood's latest power throuple? New photos of Taika Waititi, Rita Ora and Tessa Thompson aroused speculation that the three stars could be dating.

Published by the Daily Mail on Sunday (May 23), the pictures in question depict the director draping his arms around both Ora and Thompson as they laugh and pack on the PDA. In one photo, the "Let Me Love You" singer appears to be giving the Thor: Ragnarok star a peck on the cheek, while in another she's kissing the side of her director boyfriend's mouth while Thompson's caught with her mouth open.

In separate photos, the two women can be seen nose to nose as they share an intimate moment, while in another photo taken later, Waititi leans close over Thompson's face as she relaxes in a white lounge chair.

While Thompson's possible addition to their budding relationship is certainly news, Waititi and Ora first sparked romance rumors late last month when the latter posted a snuggly pic of the two canoodling on her Instagram. (Interestingly, in the same carousel of photos, Ora also shared a selfie with Thompson, who's currently in the midst of filming Thor: Love and Thunder under Waititi's direction. Ora, meanwhile, is in Sydney to film the Australian iteration of The Voice.)

Naturally, the photos of the trio have gone viral, leading to a plethora of funny and clever reactions across social media.

"Is there room for another in this rita ora, taika waititi, tessa thompson thing? asking for a friend (myself)," one fan asked, while another tweeted, "TAIKA WAITITI IS TRENDING BUT DON'T CLICK ON IT BECAUSE YOU'LL JUST BE JEALOUS NO MATTER HOW YOU IDENTIFY."

Another hilariously summed up the situation by writing, "Me finding out in a matter of seconds that Taika Waititi has actually not been married for years now and also he’s dating Rita Ora and also they were seen making out with Tessa Thompson" alongside a popular meme featuring SpongeBob SquarePants' Mr. Krabs.

Check out some of the best reactions to Waititi, Ora and Thompson's PDA session below.

Celebrities Remember Their Awkward First Kiss


text:
A sought after educator, Brad Mahon has instructed at several institutions as an adjunct faculty member including Mount Royal University, Ambrose University, Boston University, Burman University, University of Lethbridge, University of Regina, and the University of Calgary where, at the latter, he was nominated for a Student’s Union Teaching Excellence Award.

Dr. Mahon’s classroom lecturers are constantly praised for their high energy and student engagement while his guitar students have received scholarships, awards, and prizes at local, provincial, national, and international music festivals and competitions. Former students have also been accepted into notable post-secondary music programs in the United States, Europe, and Canada.

Brad is also a distinguished member of the Royal Conservatory of Music’s College of Examiners and a popular, habitual judge at music festivals, adjudicating and giving clinics across Canada.

Please contact Brad directly to inquire about private instruction and/or sessional university classes.


text:
Canadian Students Among World’s Most Computer Literate, Study Shows

Ontario students are among the world’s most computer literate, according to a new international test.

The International Computer and Information Literacy Study, which last year was administered to 60,000 high school students across 20 countries, showed Ontario students average a computer literacy score of nearly 550 (out of 600), well above the average of 500.

Ontario, which represented Canada in the study, tied for top spot with Australia and the Czech Republic.

Ontario students’ computer literacy comes despite the fact that, according to the report, Canadian put less priority on it than other countries in the study, which included Hong Kong, Korea, and Switzerland.

The test was broken down into three parts: multiple-choice or constructed response items based on realistic stimulus material; software simulations of generic applications so that students are required to complete an action in response to an instruction; and authentic tasks that require students to modify and create information products using live computer software applications.