Introducing "best single template" models as reference baseline for the Continuous Automated Model Evaluation (CAMEO).

Critical blind assessment of structure prediction techniques is crucial for the scientific community to establish the state of the art, identify bottlenecks, and guide future developments. In Critical Assessment of Techniques in Structure Prediction (CASP), human experts assess the performance of participating methods in relation to the difficulty of the prediction task in a biennial experiment on approximately 100 targets. Yet, the development of automated computational modeling methods requires more frequent evaluation cycles and larger sets of data. The "Continuous Automated Model EvaluatiOn (CAMEO)" platform complements CASP by conducting fully automated blind prediction evaluations based on the weekly pre-release of sequences of those structures, which are going to be published in the next release of the Protein Data Bank (PDB). Each week, CAMEO publishes benchmarking results for predictions corresponding to a set of about 20 targets collected during a 4-day prediction window. CAMEO benchmarking data are generated consistently for all methods at the same point in time, enabling developers to cross-validate their method's performance, and referring to their results in publications. Many successful participants of CASP have used CAMEO-either by directly benchmarking their methods within the system or by comparing their own performance to CAMEO reference data. CAMEO offers a variety of scores reflecting different aspects of structure modeling, for example, binding site accuracy, homo-oligomer interface quality, or accuracy of local model confidence estimates. By introducing the "bestSingleTemplate" method based on structure superpositions as a reference for the accuracy of 3D modeling predictions, CAMEO facilitates objective comparison of techniques and fosters the development of advanced methods.

Epidemiology of migraine in men: Results from the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study.

OBJECTIVE: To assess migraine epidemiology in men by examining gender differences in disease presentation, comorbidities, and prognosis. PATIENTS AND METHODS: The Chronic Migraine Epidemiology and Outcomes (CaMEO) Study is a longitudinal survey of US adults with migraine identified by web questionnaire. Data were stratified by gender, collected between September 2012-November 2013, and included sociodemographics, headache features, Migraine Disability Assessment, Migraine Symptom Severity Score, Allodynia Symptom Checklist, and comorbidities. Discrete time hazard models addressed 1-year likelihood of transition from episodic to chronic migraine headache frequency. RESULTS: Of the 16,789 migraine respondents, 4294 were men (25.6%). Compared to women, men were slightly older at onset of their headaches (mean 24.1 vs. 22.3 years) and had fewer headache days/month (4.3 vs. 5.3 days), slightly less severe attacks (Migraine Symptom Severity Score, 21.6 vs. 22.6), reduced frequencies of grade IV Migraine Disability Assessment scores (15.7% vs. 24.1%), allodynia (32.6% vs. 49.7%), chronic migraine (6.5% vs. 9.6%, each p < 0.001), and common comorbidities. Men were less likely to report consulting a doctor for their headaches and receiving a migraine diagnosis if they consulted. Men and women with episodic migraine had similar crude 1-year risk of chronic migraine onset. Controlling for known risk factors (i.e. depression, headache frequency, allodynia), men had greater likelihood of chronic migraine onset at 6, 9, and 12 months (each p < 0.05). CONCLUSIONS: Findings confirmed gender differences. Men with migraine generally have less severe attacks and disability and are less likely to receive a diagnosis than women with migraine. Prognostic factors may be better understood for women than men.

Sleep Disorders Among People With Migraine: Results From the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study.

OBJECTIVES: We examined the cross-sectional association of sleep apnea and indices of sleep quality with both episodic migraine (EM) and chronic migraine (CM). BACKGROUND: Sleep apnea and abnormal patterns of sleep, such as insomnia, were associated with migraine onset, severity, and progression in previous research. METHODS: The Chronic Migraine Epidemiology & Outcomes Study, a longitudinal study, used a series of web-based surveys to assess migraine symptoms, burden, and patterns of health care utilization. Quota sampling was used from September 2012 to November 2013 to generate a representative sample of the US population. Persons who screened positive for sleep apnea on the Berlin Questionnaire are said to be at "high risk" for sleep apnea. Respondents indicated if they believed that they had sleep apnea, if a physician had diagnosed it, and if and how they were treated. Other aspects of sleep quality were assessed using the Medical Outcomes Study (MOS) Sleep Measures. RESULTS: Of 12,810 eligible respondents with migraine and data on sleep, 11,699 with EM (91.3%) and 1111 with CM (8.7%) provided valid data for this analyses. According to the Berlin Questionnaire, 4739/12,810 (37.0%) were at "high risk" for sleep apnea, particularly persons with CM vs EM (575/1111 [51.8%] vs 4164/11,699 [35.6%]), men vs women (1431/3220 [44.4%] vs 3308/9590 [34.5%]), people with higher body mass index, and older people (all P < .001). Among respondents to the MOS Sleep Measures, persons with CM were more likely to report poor sleep quality than those with EM, including sleep disturbance (mean [SD] values: 53.2 [26.9] vs 37.9 [24.3]), snoring (38.0 [33.9] vs 31.0 [32.1]), shortness of breath (34.9 [29.8] vs 15.3 [20.6]), somnolence (44.1 [23.4] vs 32.2 [21.2]), and less likely to report sleep adequacy (34.0 [24.2] vs 39.2 [22.1]). CONCLUSIONS: Compared with respondents with EM, a larger proportion of those with CM were at "high risk" for sleep apnea and reported poor sleep quality. This reflects an association between CM vs EM and sleep apnea and poor sleep quality; the potential relationships are discussed.

Continuous Automated Model EvaluatiOn (CAMEO) complementing the critical assessment of structure prediction in CASP12.

Every second year, the community experiment "Critical Assessment of Techniques for Structure Prediction" (CASP) is conducting an independent blind assessment of structure prediction methods, providing a framework for comparing the performance of different approaches and discussing the latest developments in the field. Yet, developers of automated computational modeling methods clearly benefit from more frequent evaluations based on larger sets of data. The "Continuous Automated Model EvaluatiOn (CAMEO)" platform complements the CASP experiment by conducting fully automated blind prediction assessments based on the weekly pre-release of sequences of those structures, which are going to be published in the next release of the PDB Protein Data Bank. CAMEO publishes weekly benchmarking results based on models collected during a 4-day prediction window, on average assessing ca. 100 targets during a time frame of 5 weeks. CAMEO benchmarking data is generated consistently for all participating methods at the same point in time, enabling developers to benchmark and cross-validate their method's performance, and directly refer to the benchmarking results in publications. In order to facilitate server development and promote shorter release cycles, CAMEO sends weekly email with submission statistics and low performance warnings. Many participants of CASP have successfully employed CAMEO when preparing their methods for upcoming community experiments. CAMEO offers a variety of scores to allow benchmarking diverse aspects of structure prediction methods. By introducing new scoring schemes, CAMEO facilitates new development in areas of active research, for example, modeling quaternary structure, complexes, or ligand binding sites.

Identifying Natural Subgroups of Migraine Based on Comorbidity and Concomitant Condition Profiles: Results of the Chronic Migraine Epidemiology and Outcomes (CaMEO) Study.

OBJECTIVE: To identify natural subgroups of people with migraine based on profiles of comorbidities and concomitant conditions, hereafter referred to as comorbidities. BACKGROUND: Migraine is a heterogeneous disease. Identifying natural subgroups (endophenotypes) may facilitate biological and genetic characterization and the development of personalized treatment. METHODS: The Chronic Migraine Epidemiology and Outcomes Study is a prospective web-based survey study designed to characterize the course of migraine and related comorbidities in a systematic US sample of people with migraine. Respondents were asked if they ever had a specific comorbidity and, if present, whether the comorbidity was confirmed/diagnosed by a "doctor"; 62 comorbidities were available for analysis. Latent class analysis (LCA) modeling determined the optimal number of classes and a parsimonious set of comorbidities. RESULTS: Of the 12,810 respondents with migraine, 11,837 reported ≥1 comorbidity and were included in this analysis. After statistical analysis and clinical judgment reduced the number of comorbidities, we selected an 8-class model based on 22 comorbidities. Each class had a distinct pattern summarized as follows: Class 1, Most Comorbidities; Class 2, Respiratory/Psychiatric; Class 3, Respiratory/Pain; Class 4, Respiratory; Class 5, Psychiatric; Class 6, Cardiovascular; Class 7, Pain; Class 8, Fewest Comorbidities. The distribution of individuals across models was variable, with one-third of respondents in Class 8 (Fewest Comorbidities) and <10% in Class 1 (Most Comorbidities). Demographic and headache characteristics, not used in assigning class membership, varied across classes. For example, comparing Class 1 (Most Comorbidities) and Class 8 (Fewest Comorbidities), Class 1 had a greater proportion of individuals with severe disability (Migraine Disability Assessment grade IV; 48.1% vs 22.3% of overall individuals) and higher rates of allodynia (67.6% vs 47.0%), medication overuse (36.4% vs 15.0%), chronic migraine (23.1% vs 9.1%), and aura (40.1% vs 28.8%). CONCLUSIONS: LCA modeling identified 8 natural subgroups of persons with migraine based on comorbidity profiles. These classes show differences in demographic and headache features not used to form the classes. Subsequent research will assess prognostic and biologic differences among the classes.

Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling.

Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The threshold value was long assumed to be around 20-30%. Below this level, obtained sequence identity was getting dangerously close to values that can be obtained by chance, after aligning any random, unrelated sequences. In these cases, other approaches, including ab initio folding simulations or fragment assembly, were usually employed. The most recent editions of the CASP and CAMEO community-wide modeling methods assessment have brought some surprising outcomes, proving that much more clues can be inferred from protein sequence analyses than previously thought. In this chapter, we focus on recent advances in the field of difficult protein modeling, pushing the threshold deep into the "twilight zone", with particular attention devoted to improvements in applications of machine learning and model evaluation.

Emergency response plan for methane and chlorine with dispersion modelling using CAMEO.

There is a significant need in the current industrial scenario for methods to be formulated to treat dangerous chemicals most safely. Accidental release of toxic chemicals will result in emergencies. Hence, an emergency response plan (ERP) is inevitable. The most toxic chemicals in the water and wastewater sector are chlorine and hydrogen sulphide, whereas methane is a flammable gas. CAMEO software is used in this research to predict the region that toxic gas release impacts. This research deals with a sewage treatment plant ERP and control measures for methane and chlorine gases. The affected area of hazard will depend upon the weather conditions and the time of the accident. Comparing two different seasons, the impacted distance is more significant in summer than in winter. It is observed that the night and early morning is more dangerous than the afternoon and evening as it shows the larger impacted distance.

Open-access data: A cornerstone for artificial intelligence approaches to protein structure prediction.

The Protein Data Bank (PDB) was established in 1971 to archive three-dimensional (3D) structures of biological macromolecules as a public good. Fifty years later, the PDB is providing millions of data consumers around the world with open access to more than 175,000 experimentally determined structures of proteins and nucleic acids (DNA, RNA) and their complexes with one another and small-molecule ligands. PDB data users are working, teaching, and learning in fundamental biology, biomedicine, bioengineering, biotechnology, and energy sciences. They also represent the fields of agriculture, chemistry, physics and materials science, mathematics, statistics, computer science, and zoology, and even the social sciences. The enormous wealth of 3D structure data stored in the PDB has underpinned significant advances in our understanding of protein architecture, culminating in recent breakthroughs in protein structure prediction accelerated by artificial intelligence approaches and deep or machine learning methods.

Estimating the Quality of 3D Protein Models Using the ModFOLD7 Server.

Assessing the accuracy of 3D models has become a keystone in the protein structure prediction field. ModFOLD7 is our leading resource for Estimates of Model Accuracy (EMA), which has been upgraded by integrating a number of the pioneering pure-single- and quasi-single-model approaches. Such an integration has given our latest version the strengths to accurately score and rank predicted models, with higher consistency compared to older EMA methods. Additionally, the server provides three options for producing global score estimates, depending on the requirements of the user: (1) ModFOLD7_rank, which is optimized for ranking/selection, (2) ModFOLD7_cor, which is optimized for correlations of predicted and observed scores, and (3) ModFOLD7 global for balanced performance. ModFOLD7 has been ranked among the top few EMA methods according to independent blind testing by the CASP13 assessors. Another evaluation resource for ModFOLD7 is the CAMEO project, where the method is continuously automatically evaluated, showing a significant improvement compared to our previous versions. The ModFOLD7 server is freely available at http://www.reading.ac.uk/bioinf/ModFOLD/ .

In silico Identification and Characterization of Protein-Ligand Binding Sites.

Protein-ligand binding site prediction methods aim to predict, from amino acid sequence, protein-ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein-ligand interactions has become extremely important to help determine a protein's functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein-ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein-ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein-ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Toolbox for Protein Structure Prediction.

Protein tertiary structure prediction algorithms aim to predict, from amino acid sequence, the tertiary structure of a protein. In silico protein structure prediction methods have become extremely important, as in vitro-based structural elucidation is unable to keep pace with the current growth of sequence databases due to high-throughput next-generation sequencing, which has exacerbated the gaps in our knowledge between sequences and structures.Here we briefly discuss protein tertiary structure prediction, the biennial competition for the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and its role in shaping the field. We also discuss, in detail, our cutting-edge web-server method IntFOLD2-TS for tertiary structure prediction. Furthermore, we provide a step-by-step guide on using the IntFOLD2-TS web server, along with some real world examples, where the IntFOLD server can and has been used to improve protein tertiary structure prediction and aid in functional elucidation.

Clinical Assessment and Management Examination--Outpatient (CAMEO): its validity and use in a surgical milestones paradigm.

OBJECTIVES: Clinical Assessment and Management Examination--Outpatient (CAMEO) is a metric for evaluating the clinical performance of surgery residents. The aim of this study was to investigate the measurement characteristics of CAMEO and propose how it might be used as an evaluation tool within the general surgery milestones project. DESIGN: A total of 117 CAMEO evaluations were gathered and used for analysis. Internal consistency reliability was estimated, and item characteristics were explored. A Kruskal-Wallis procedure was performed to discern how well the instrument discriminated between training levels. An exploratory factor analysis was also conducted to understand the dimensionality of the evaluation. SETTING: CAMEO evaluations were collected from 2 departments of surgery geographically located in the Midwestern United States. Combined, the participating academic institutions graduate approximately 18 general surgery residents per year. PARTICIPANTS: In this retrospective data analysis, the number of evaluations per resident ranged from 1 to 7, and evaluations were collected from 2006 to 2013. For the purpose of data analysis, residents were classified as interns (postgraduate year 1 [PGY1]), juniors (PGY2-3), or seniors (PGY4-5). RESULTS: CAMEO scores were found to have high internal consistency (Cronbach's α = 0.96), and all items were highly correlated (≥ 0.86) to composite CAMEO scores. Scores discriminated between senior residents (PGY4-5) and lower level residents (PGY1-3). Per an exploratory factor analysis, CAMEO was revealed to measure a single dimension of "clinical competence." CONCLUSIONS: The findings of this research aligned with related literature and verified that CAMEO scores have desirable measurement properties, making CAMEO an attractive resource for evaluating the clinical performance of surgery residents.

Expression pattern and tissue localization of the class B scavenger receptor BmSCRBQ4 in Bombyx mori.

Class B scavenger receptors (SR-Bs) are cell surface glycoproteins involved in various physiological processes in vivo, including the transport and metabolism of lipids, binding and phagocytosis of xenobiotics, and signaling. But little information is available about silkworm SR-Bs; it is necessary to study these SR-Bs for revealing their function. In this study, we cloned the full-length coding sequence of BmSCRBQ4, a SR-B gene from the silkworm Bombyx mori L. We found that the BmSCRBQ4 gene consists of nine exons and eight introns, with an open reading frame of 1371 bp encoding 456 amino acids. Gene expression studies determined that BmSCRBQ4 messenger RNA (mRNA) was expressed in unfertilized eggs, during embryonic development and throughout the majority of the larval period. Expression of mRNA was detected in the mid gut, middle silk gland, posterior silk gland, head, integumentum, fat body, testes and the ovaries of the larval B. mori Dazao strain, as well as in the silkworm cell lines BmN and BmE. Protein expression studies found BmSCRBQ4 protein was expressed only in the testes, fat body and middle silk gland of larvae, as well as in the silkworm cell lines BmN and BmE. The BmSCRBQ4 protein showed variability in banding patterns in different tissues and cells when analyzed by Western blotting. Immunohistochemical staining showed that the BmSCRBQ4 protein localizes to the constitutive membranes or cellular membranes of these tissues. These results indicated that BmSCRBQ4 gene may play some physiologically relevant roles at the cell surface in each tissue.

Analysis of a silkworm F1 hybrid with yellow cocoon generated by crossing two white-cocoon strains: further evidences for the roles of Cameo2 and CBP in formation of yellow cocoon.

In this report, we examined the gene expression related to carotenoid transport for a silkworm F1 hybrid with yellow cocoon generated by crossing two white-cocoon strains, Qiubai and 12-260. Our results showed that, in Qiubai, Cameo2, a transmembrane protein gene belonging to the CD36 family genes, was expressed normally in the silk gland, but no intact carotenoid-binding protein (CBP) mRNA (only the truncated CBP mRNA) was detected in the midgut. In 12-260, we detected the intact CBP mRNA expression in the midgut, but no Cameo2 expression in the silk gland. Regarding the F1 hybrid from crossing Qiubai and 12-260, both Cameo2 and intact CBP mRNA expressed normally in the silk gland and midgut. HPLC detection confirmed that in the F1 hybrid the carotenoids could be absorbed from dietary mulberry leaves through the midgut and transferred to silk gland via the hemolymph, which eventually colored cocoons into yellow. We also identified four CBP mRNA isoforms expressed in the midgut of the F1 hybrid, subsequently named as variants 5-8. Our results provide further evidences for the roles of Cameo2 and CBP in the formation of yellow cocoon of silkworm.