MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions

Background The alignment of multiple protein sequences is one of the most commonly performed tasks in bioinformatics. In spite of considerable research and efforts that have been recently deployed for improving the performance of multiple sequence alignment (MSA) algorithms, finding a highly accurate alignment between multiple protein sequences is still a challenging problem. Results We propose a novel and efficient algorithm called, MSAIndelFR, for multiple sequence alignment using the information on the predicted locations of IndelFRs and the computed average log–loss values obtained from IndelFR predictors, each of which is designed for a different protein fold. We demonstrate that the introduction of a new variable gap penalty function based on the predicted locations of the IndelFRs and the computed average log–loss values into the proposed algorithm substantially improves the protein alignment accuracy. This is illustrated by evaluating the performance of the algorithm in aligning sequences belonging to the protein folds for which the IndelFR predictors already exist and by using the reference alignments of the four popular benchmarks, BAliBASE 3.0, OXBENCH, PREFAB 4.0, and SABRE (SABmark 1.65). Conclusions We have proposed a novel and efficient algorithm, the MSAIndelFR algorithm, for multiple protein sequence alignment incorporating a new variable gap penalty function. It is shown that the performance of the proposed algorithm is superior to that of the most–widely used alignment algorithms, Clustal W2, Clustal Omega, Kalign2, MSAProbs, MAFFT, MUSCLE, ProbCons and Probalign, in terms of both the sum–of–pairs and total column metrics

Tetrazine-Triggered Release of Carboxylic-Acid-Containing Molecules for Activation of an Anti-inflammatory Drug.

In addition to its use for the study of biomolecules in living systems, bioorthogonal chemistry has emerged as a promising strategy to enable protein or drug activation in a spatially and temporally controlled manner. This study demonstrates the application of a bioorthogonal inverse electron-demand Diels-Alder (iEDDA) reaction to cleave trans-cyclooctene (TCO) and vinyl protecting groups from carboxylic acid-containing molecules. The tetrazine-mediated decaging reaction proceeded under biocompatible conditions with fast reaction kinetics (<2 min). The anti-inflammatory activity of ketoprofen was successfully reinstated after decaging of the nontoxic TCOprodrug in live macrophages. Overall, this work expands the scope of functional groups and the application of decaging reactions to a new class of drugs

The state of HRM in the Middle East:Challenges and future research agenda

Based on a robust structured literature analysis, this paper highlights the key developments in the field of human resource management (HRM) in the Middle East. Utilizing the institutional perspective, the analysis contributes to the literature on HRM in the Middle East by focusing on four key themes. First, it highlights the topical need to analyze the context-specific nature of HRM in the region. Second, via the adoption of a systematic review, it highlights state of development in HRM in the research analysis set-up. Third, the analysis also helps to reveal the challenges facing the HRM function in the Middle East. Fourth, it presents an agenda for future research in the form of research directions. While doing the above, it revisits the notions of “universalistic” and “best practice” HRM (convergence) versus “best-fit” or context distinctive (divergence) and also alternate models/diffusion of HRM (crossvergence) in the Middle Eastern context. The analysis, based on the framework of cross-national HRM comparisons, helps to make both theoretical and practical implications

Guidance on Noncorticosteroid Systemic Immunomodulatory Therapy in Noninfectious Uveitis: Fundamentals Of Care for UveitiS (FOCUS) Initiative

Topic: An international, expert-led consensus initiative to develop systematic, evidence-based recommendations for the treatment of noninfectious uveitis in the era of biologics. Clinical Relevance: The availability of biologic agents for the treatment of human eye disease has altered practice patterns for the management of noninfectious uveitis. Current guidelines are insufficient to assure optimal use of noncorticosteroid systemic immunomodulatory agents. Methods: An international expert steering committee comprising 9 uveitis specialists (including both ophthalmologists and rheumatologists) identified clinical questions and, together with 6 bibliographic fellows trained in uveitis, conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review of the literature (English language studies from January 1996 through June 2016; Medline [OVID], the Central Cochrane library, EMBASE, CINAHL, SCOPUS, BIOSIS, and Web of Science). Publications included randomized controlled trials, prospective and retrospective studies with sufficient follow-up, case series with 15 cases or more, peer-reviewed articles, and hand-searched conference abstracts from key conferences. The proposed statements were circulated among 130 international uveitis experts for review. A total of 44 globally representative group members met in late 2016 to refine these guidelines using a modified Delphi technique and assigned Oxford levels of evidence. Results: In total, 10 questions were addressed resulting in 21 evidence-based guidance statements covering the following topics: when to start noncorticosteroid immunomodulatory therapy, including both biologic and nonbiologic agents; what data to collect before treatment; when to modify or withdraw treatment; how to select agents based on individual efficacy and safety profiles; and evidence in specific uveitic conditions. Shared decision-making, communication among providers and safety monitoring also were addressed as part of the recommendations. Pharmacoeconomic considerations were not addressed. Conclusions: Consensus guidelines were developed based on published literature, expert opinion, and practical experience to bridge the gap between clinical needs and medical evidence to support the treatment of patients with noninfectious uveitis with noncorticosteroid immunomodulatory agents

Non-Intrusive Identification of Student Attentiveness and Finding their Correlation with Detectable Facial Emotions

Teachers use observational cues in the classroom to identify attentiveness of students and guide the pace of their lecture, however, with increased class sizes it has become less effective. This paper presents an approach for automating these observational cues of the students, identifying the attentiveness of students. The approach includes a neural network machine learning model to detect whether a student is attentive or inattentive depending on their facial expressions. Results of the deep learning CNN model were compared with the range of confidence values obtained from a cloud-based emotion recognition service to identify the correlations with the human observer