CRISPR single base-editing: in silico predictions to variant clonal cell lines.

Engineering single base edits using CRISPR technology including specific deaminases and single-guide RNA (sgRNA) is a rapidly evolving field. Different types of base edits can be constructed, with cytidine base editors (CBEs) facilitating transition of C-to-T variants, adenine base editors (ABEs) enabling transition of A-to-G variants, C-to-G transversion base editors (CGBEs) and recently adenine transversion editors (AYBE) that create A-to-C and A-to-T variants. The base-editing machine learning algorithm BE-Hive predicts which sgRNA and base editor combinations have the strongest likelihood of achieving desired base edits. We have used BE-Hive and TP53 mutation data from The Cancer Genome Atlas (TCGA) ovarian cancer cohort to predict which mutations can be engineered, or reverted to wild-type (WT) sequence, using CBEs, ABEs or CGBEs. We have developed and automated a ranking system to assist in selecting optimally designed sgRNA that considers the presence of a suitable protospacer adjacent motif (PAM), the frequency of predicted bystander edits, editing efficiency and target base change. We have generated single constructs containing ABE or CBE editing machinery, an sgRNA cloning backbone and an enhanced green fluorescent protein tag (EGFP), removing the need for co-transfection of multiple plasmids. We have tested our ranking system and new plasmid constructs to engineer the p53 mutants Y220C, R282W and R248Q into WT p53 cells and shown that these mutants cannot activate four p53 target genes, mimicking the behaviour of endogenous p53 mutations. This field will continue to rapidly progress, requiring new strategies such as we propose to ensure desired base-editing outcomes.

Faecal microbial transfer and complex carbohydrates mediate protection against COPD.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major cause of global illness and death, most commonly caused by cigarette smoke. The mechanisms of pathogenesis remain poorly understood, limiting the development of effective therapies. The gastrointestinal microbiome has been implicated in chronic lung diseases via the gut-lung axis, but its role is unclear. DESIGN: Using an in vivo mouse model of cigarette smoke (CS)-induced COPD and faecal microbial transfer (FMT), we characterised the faecal microbiota using metagenomics, proteomics and metabolomics. Findings were correlated with airway and systemic inflammation, lung and gut histopathology and lung function. Complex carbohydrates were assessed in mice using a high resistant starch diet, and in 16 patients with COPD using a randomised, double-blind, placebo-controlled pilot study of inulin supplementation. RESULTS: FMT alleviated hallmark features of COPD (inflammation, alveolar destruction, impaired lung function), gastrointestinal pathology and systemic immune changes. Protective effects were additive to smoking cessation, and transfer of CS-associated microbiota after antibiotic-induced microbiome depletion was sufficient to increase lung inflammation while suppressing colonic immunity in the absence of CS exposure. Disease features correlated with the relative abundance of Muribaculaceae, Desulfovibrionaceae and Lachnospiraceae family members. Proteomics and metabolomics identified downregulation of glucose and starch metabolism in CS-associated microbiota, and supplementation of mice or human patients with complex carbohydrates improved disease outcomes. CONCLUSION: The gut microbiome contributes to COPD pathogenesis and can be targeted therapeutically.

Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions.

One of the mechanisms viruses use in hijacking host cellular machinery is mimicking Short Linear Motifs (SLiMs) in host proteins to maintain their life cycle inside host cells. In the face of the escalating volume of virus-host protein-protein interactions (vhPPIs) documented in databases; the accurate prediction of molecular mimicry remains a formidable challenge due to the inherent degeneracy of SLiMs. Consequently, there is a pressing need for computational methodologies to predict new instances of viral mimicry. Our present study introduces a DMI-de-novo pipeline, revealing that vhPPIs catalogued in the VirHostNet3.0 database effectively capture domain-motif interactions (DMIs). Notably, both affinity purification coupled mass spectrometry and yeast two-hybrid assays emerged as good approaches for delineating DMIs. Furthermore, we have identified new vhPPIs mediated by SLiMs across different viruses. Importantly, the de-novo prediction strategy facilitated the recognition of several potential mimicry candidates implicated in the subversion of host cellular proteins. The insights gleaned from this research not only enhance our comprehension of the mechanisms by which viruses co-opt host cellular machinery but also pave the way for the development of novel therapeutic interventions.

Prediction of virus-host interactions and identification of hot spot residues of DENV-2 and SH3 domain interactions.

Dengue virus, particularly serotype 2 (DENV-2), poses a significant global health threat, and understanding the molecular basis of its interactions with host cell proteins is imperative for developing targeted therapeutic strategies. This study elucidated the interactions between proline-enriched motifs and Src homology 3 (SH3) domain. The SH3 domain is pivotal in mediating protein-protein interactions, particularly by recognizing and binding to proline-rich regions in partner proteins. Through a computational pipeline, we analyzed the interactions and binding modes of proline-enriched motifs with SH3 domains, identified new potential DENV-2 interactions with the SH3 domain, and revealed potential hot spot residues, underscoring their significance in the viral life cycle. This comprehensive analysis provides crucial insights into the molecular basis of DENV-2 infection, highlighting conserved and serotype-specific interactions. The identified hot spot residues offer potential targets for therapeutic intervention, laying the foundation for developing antiviral strategies against Dengue virus infection. These findings contribute to the broader understanding of viral-host interactions and provide a roadmap for future research on Dengue virus pathogenesis and treatment.

Experiences of cardiac care nurses related to the management and delayed removal of trans-radial band of patients at a private tertiary care hospital, Islamabad.

Objectives: To explore the experiences of cardiac care nurses in managing transradial band of patients in a tertiary care setting. METHODS: The exploratory, descriptive, qualitative study was conducted at a private-sector tertiary care hospital in Islamabad, Pakistan, from March to September 2021, and comprised registered cardiac care nurses with >6 months of relevant experience. Data was collected through face-to-face interviews using a semi-structured interview guide. Data was analysed qualitatively using the Creswell and Creswell framework. RESULTS: Of the 10 nurses, 5(50%) were males and 5(50%) were females. In terms of age, 5(50%) were aged <25 years. Cardiac specialisation had been done by 2(20%) nurses, and none of the subjects had formal training related to transradial band. The main theme that emerged from the data was nurses' management of patients with transradial band, and the three categories were nurses' knowledge and practices about transradial band, reasons for delayed transradial band removal, and strategies to minimise complications. CONCLUSIONS: To minimise transradial band-related complications, in-service training of nurses and ensuring a safe nursepatient ratio are necessary.

RIPK1 kinase-dependent inflammation and cell death contribute to the pathogenesis of COPD.

BACKGROUND: Receptor-interacting protein kinase 1 (RIPK1) is a key mediator of regulated cell death (including apoptosis and necroptosis) and inflammation, both drivers of COPD pathogenesis. We aimed to define the contribution of RIPK1 kinase-dependent cell death and inflammation in the pathogenesis of COPD. METHODS: We assessed RIPK1 expression in single-cell RNA sequencing (RNA-seq) data from human and mouse lungs, and validated RIPK1 levels in lung tissue of COPD patients via immunohistochemistry. Next, we assessed the consequences of genetic and pharmacological inhibition of RIPK1 kinase activity in experimental COPD, using Ripk1 S25D/S25D kinase-deficient mice and the RIPK1 kinase inhibitor GSK'547. RESULTS: RIPK1 expression increased in alveolar type 1 (AT1), AT2, ciliated and neuroendocrine cells in human COPD. RIPK1 protein levels were significantly increased in airway epithelium of COPD patients compared with never-smokers and smokers without airflow limitation. In mice, exposure to cigarette smoke (CS) increased Ripk1 expression similarly in AT2 cells, and further in alveolar macrophages and T-cells. Genetic and/or pharmacological inhibition of RIPK1 kinase activity significantly attenuated airway inflammation upon acute and subacute CS exposure, as well as airway remodelling, emphysema, and apoptotic and necroptotic cell death upon chronic CS exposure. Similarly, pharmacological RIPK1 kinase inhibition significantly attenuated elastase-induced emphysema and lung function decline. Finally, RNA-seq on lung tissue of CS-exposed mice revealed downregulation of cell death and inflammatory pathways upon pharmacological RIPK1 kinase inhibition. CONCLUSIONS: RIPK1 kinase inhibition is protective in experimental models of COPD and may represent a novel promising therapeutic approach.

Bioinformatics prediction and screening of viral mimicry candidates through integrating known and predicted DMI data.

Domain-motif interactions (DMIs) represent transient bonds formed when a Short Linear Motif (SLiM) engages a globular domain via a compact contact interface. Understanding the mechanics of DMIs is critical for maintaining diverse regulatory processes and deciphering how various viruses hijack host cellular machinery. However, identifying DMIs through traditional in vitro and in vivo experiments is challenging due to their degenerate nature and small contact areas. Predictions often carry a high rate of false positives, necessitating rigorous in-silico validation before embarking on experimental work. This study assessed the binding energy changes in predicted SLiM instances through in-silico peptide exchange experiment, elucidating how they interact with known 3D DMI complexes. We identified a subset of potential mimicry candidates that exhibited effective binding affinities with native DMI structures, suggesting their potential to be true mimicry candidates. The identified viral SLiMs can be potential targets in developing therapeutics, opening new opportunities for innovative treatments that can be finely tuned to address the complex molecular underpinnings of various diseases. To gain a comprehensive understanding of identified DMIs, it is imperative to conduct further validation through experimental approaches.

Increased SARS-CoV-2 Infection, Protease, and Inflammatory Responses in Chronic Obstructive Pulmonary Disease Primary Bronchial Epithelial Cells Defined with Single-Cell RNA Sequencing.

Rationale: Patients with chronic obstructive pulmonary disease (COPD) develop more severe coronavirus disease (COVID-19); however, it is unclear whether they are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and what mechanisms are responsible for severe disease. Objectives: To determine whether SARS-CoV-2 inoculated primary bronchial epithelial cells (pBECs) from patients with COPD support greater infection and elucidate the effects and mechanisms involved. Methods: We performed single-cell RNA sequencing analysis on differentiated pBECs from healthy subjects and patients with COPD 7 days after SARS-CoV-2 inoculation. We correlated changes with viral titers, proinflammatory responses, and IFN production. Measurements and Main Results: Single-cell RNA sequencing revealed that COPD pBECs had 24-fold greater infection than healthy cells, which was supported by plaque assays. Club/goblet and basal cells were the predominant populations infected and expressed mRNAs involved in viral replication. Proteases involved in SARS-CoV-2 entry/infection (TMPRSS2 and CTSB) were increased, and protease inhibitors (serpins) were downregulated more so in COPD. Inflammatory cytokines linked to COPD exacerbations and severe COVID-19 were increased, whereas IFN responses were blunted. Coexpression analysis revealed a prominent population of club/goblet cells with high type 1/2 IFN responses that were important drivers of immune responses to infection in both healthy and COPD pBECs. Therapeutic inhibition of proteases and inflammatory imbalances reduced viral titers and cytokine responses, particularly in COPD pBECs. Conclusions: COPD pBECs are more susceptible to SARS-CoV-2 infection because of increases in coreceptor expression and protease imbalances and have greater inflammatory responses. A prominent cluster of IFN-responsive club/goblet cells emerges during infection, which may be important drivers of immunity. Therapeutic interventions suppress SARS-CoV-2 replication and consequent inflammation.

Racism and the mental health of East Asian diasporas in North America: a scoping review.

BACKGROUND: The COVID-19 pandemic heightened anti-Asian racism towards East Asian diasporas in North America. Experiences of racism encountered by East Asian communities have been documented to negatively impact their mental health. METHODS: A scoping review was undertaken following Arksey and O'Malley's (2005) methodology to (a) map the foci of literature on racism and the mental health of East Asian diasporas in North America and (b) identify gaps in the current literature. RESULTS: A total of 1309 articles were identified in May 2021. Based on the inclusion criteria, 35 records were included. Two distinct mental health foci were found: mental health outcomes and mental healthcare access and utilization. The majority (n = 22) of the articles focused on racism at the interpersonal level. Six articles provided anti-racism solutions at the individual level, such as overcoming biases. Five articles targeted anti-racism solutions from both the individual and institutional levels, while 1 article addressed barriers at the institutional level, such as dismantling sanctioned power hierarchies. CONCLUSION: The expanding knowledge base on COVID-19-related racial discrimination is reminiscent of previous literature examining the history of anti-Asian racism in North America. Greater attention is needed to navigate impactful anti-racism solutions for East Asian populations' mental health in North America.

In silico analysis of five missense mutations in CYP1B1 gene in Pakistani families affected with primary congenital glaucoma.

PURPOSE: The purpose of this study was to characterize the five missense mutations in CYP1B1 gene identified in Pakistani families affected with primary congenital glaucoma (PCG) using various bioinformatics and protein modeling tools. METHODS: We previously reported four novel missense mutations in CYP1B1 gene segregating in consanguineous Pakistani families. These mutations were identified by direct sequencing of all coding exons, the exon-intron boundaries and the 5' untranslated region of CYP1B1 using genomic DNA from affected and unaffected family members. In order to understand the effect of CYP1B1 mutations on protein structure and function, we used bioinformatics tools to investigate five mutations including four novels (W434R, D374E, L487P and L177R) and one known (E229K) mutation previously reported by our group in four Pakistani PCG-affected families. RESULTS: In silico analysis of the missense mutations using the computational algorithms SNAP, I-Mutant 2.0 IUPred, PrDOS and PASTA predicted pathogenic effects on stability and function of protein. CONCLUSION: In silico analysis of identified mutations confirmed their molecular pathogenicity. Similar analysis will be helpful in understanding of the biological role of CYP1B1 and the effect of mutations on the regulatory and enzymatic functions of CYP1B1 that result in PCG.

Proteome-wide assessment of human interactome as a source of capturing domain-motif and domain-domain interactions.

Protein-protein interactions (PPIs) play a crucial role in various biological processes by establishing domain-motif (DMI) and domain-domain interactions (DDIs). While the existence of real DMIs/DDIs is generally assumed, it is rarely tested; therefore, this study extensively compared high-throughput methods and public PPI repositories as sources for DMI and DDI prediction based on the assumption that the human interactome provides sufficient data for the reliable identification of DMIs and DDIs. Different datasets from leading high-throughput methods (Yeast two-hybrid [Y2H], Affinity Purification coupled Mass Spectrometry [AP-MS], and Co-fractionation-coupled Mass Spectrometry) were assessed for their ability to capture DMIs and DDIs using known DMI/DDI information. High-throughput methods were not notably worse than PPI databases and, in some cases, appeared better. In conclusion, all PPI datasets demonstrated significant enrichment in DMIs and DDIs (p-value <0.001), establishing Y2H and AP-MS as reliable methods for predicting these interactions. This study provides valuable insights for biologists in selecting appropriate methods for predicting DMIs, ultimately aiding in SLiM discovery.

Digital Knowledge Translation Tools for Disseminating Sexual and Reproductive Health Information to Adolescents: Protocol for an Evidence Gap Map Review.

BACKGROUND: Digital or eHealth knowledge translation (KT) interventions have been identified as useful public health tools, particularly to advance sexual and reproductive health (SRH) among adolescents. Existing literature reviews on digital health interventions for adolescents' SRH demonstrate limitations, including shortcomings in reporting and comprehensiveness that limit the utility and trustworthiness of findings. However, there is a lack of evidence synthesis on the effectiveness of available digital or mobile health KT tools to promote SRH interventions for adolescents. OBJECTIVE: We aim to identify, map, and describe existing empirical evidence on the digital KT tools developed to improve adolescent SRH outcomes globally. METHODS: This study will be conducted using an evidence gap map (EGM) approach to address the objectives, including reviewing relevant literature and a landscape analysis of the outcomes of interest. The following electronic databases will be searched for retrieval of literature: MEDLINE (1946-present), Embase (1974-present), and Global Health (1910-present) via OVID; CINAHL (1936-present) via EBSCOhost; Scopus (1976-present); and Cochrane Library (1993-present) via Wiley. We will include only those studies that focused on adolescents aged 10-19 years and addressed SRH outcomes. We will include experimental studies (randomized or cluster randomized and nonrandomized controlled trials, including quasi-randomized, controlled before-after, and interruptive time series) and observational studies, that is, including prospective cohort and case-control studies. The experimental and observational studies will only be included in the presence of control or comparison arms. Studies with a historical control arm will be excluded. The systematic review software, Covidence (Ventas Health Innovation), will be used to screen and select the studies. Further, 2 independent reviewers will complete the first and second levels of screening of studies and any conflicts arising will be resolved by consensus between the 2 reviewers or by involving the third reviewer. We will conduct the quality assessment of all included studies using the Risk of Bias tool for randomized controlled trials and nonrandomized controlled trials, and AMSTAR2 for systematic reviews. RESULTS: Papers screening, data extraction, and synthesis will be completed by March 2024. We will use EPPI-Mapper (The International Public Policy Observatory) software to generate an online evidence map and to produce the tables and figures for the descriptive report. This EGM review will identify areas with high-quality, evidence-based digital KT tools (for immediate scale and spread) and areas where few or no KT tools exist (for targeted KT tool development and research or policy prioritization). CONCLUSIONS: This protocol focused on mapping eHealth KT tools that have been used in the literature to address SRH among adolescents. This will be the first EGM exercise to map digital KT tools to promote adolescents' SRH and will incorporate a range of published sources. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55081.

Exploring Viral-Host Protein Interactions as Antiviral Therapies: A Computational Perspective.

The interactions between human and viral proteins are pivotal in viral infection and host immune responses. These interactions traverse different stages of the viral life cycle, encompassing initial entry into host cells, replication, and the eventual deployment of immune evasion strategies. As viruses exploit host cellular machinery for their replication and survival, targeting key protein-protein interactions offer a strategic approach for developing antiviral drugs. This review discusses how viruses interact with host proteins to develop viral-host interactions. In addition, we also highlight valuable resources that aid in identifying new interactions, incorporating high-throughput methods, and computational approaches, ultimately helping to understand how these tools can be effectively utilized to study viral-host interactions.

Uncovering domain motif interactions using high-throughput protein-protein interaction detection methods.

Protein-protein interactions (PPIs) are often mediated by short linear motifs (SLiMs) in one protein and domain in another, known as domain-motif interactions (DMIs). During the past decade, SLiMs have been studied to find their role in cellular functions such as post-translational modifications, regulatory processes, protein scaffolding, cell cycle progression, cell adhesion, cell signalling and substrate selection for proteasomal degradation. This review provides a comprehensive overview of the current PPI detection techniques and resources, focusing on their relevance to capturing interactions mediated by SLiMs. We also address the challenges associated with capturing DMIs. Moreover, a case study analysing the BioGrid database as a source of DMI prediction revealed significant known DMI enrichment in different PPI detection methods. Overall, it can be said that current high-throughput PPI detection methods can be a reliable source for predicting DMIs.

Digital Health Education and Training for Undergraduate and Graduate Nursing Students: Scoping Review.

BACKGROUND: As technology will continue to play a pivotal role in modern-day health care and given the potential impact on the nursing profession, it is vitally important to examine the types and features of digital health education in nursing so that graduates are better equipped with the necessary knowledge and skills needed to provide safe and quality nursing care and to keep abreast of the rapidly evolving technological revolution. OBJECTIVE: In this scoping review, we aimed to examine and report on available evidence about digital health education and training interventions for nursing students at the undergraduate and graduate levels. METHODS: This scoping review was conducted using the Joanna Briggs Institute methodological framework and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive search strategy was developed and applied to identified bibliographic databases including MEDLINE (Ovid; 1946 to present), Embase (Ovid; 1974 to present), CINAHL (EBSCOhost; 1936 to present), ERIC (EBSCOhost; 1966 to present), Education Research Complete (EBSCOhost; inception to present), and Scopus (1976 to present). The initial search was conducted on March 3, 2022, and updated searches were completed on January 11, 2023, and October 31, 2023. For gray literature sources, the websites of select professional organizations were searched to identify relevant digital health educational programs or courses available to support the health workforce development. Two reviewers screened and undertook the data extraction process. The review included studies focused on the digital health education of students at the undergraduate or graduate levels or both in a nursing program. Studies that discussed instructional strategies, delivery processes, pedagogical theory and frameworks, and evaluation strategies for digital health education; applied quantitative, qualitative, and mixed methods; and were descriptive or discussion papers, with the exception of review studies, were included. Opinion pieces, editorials, and conference proceedings were excluded. RESULTS: A total of 100 records were included in this review. Of these, 94 records were identified from database searches, and 6 sources were identified from the gray literature. Despite improvements, there are significant gaps and limitations in the scope of digital health education at the undergraduate and graduate levels, consequently posing challenges for nursing students to develop competencies needed in modern-day nursing practice. CONCLUSIONS: There is an urgent need to expand the understanding of digital health in the context of nursing education and practice and to better articulate its scope in nursing curricula and enforce its application across professional nursing practice roles at all levels and career trajectories. Further research is also needed to examine the impact of digital health education on improving patient outcomes, the quality of nursing care, and professional nursing role advancement. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.11124/JBIES-22-00266.

HCV Envelope protein 2 sequence comparison of Pakistani isolate and In-silico prediction of conserved epitopes for vaccine development.

BACKGROUND: HCV is causing hundreds of cases yearly in Pakistan and has become a threat for Pakistani population. HCV E2 protein is a transmembrane protein involved in viral attachment and thus can serve as an important target for vaccine development but because of its variability, vaccine development against it has become a challenge. Therefore, this study was designed to isolate the HCV E2 gene from Pakistani HCV infected patients of 3a genotype, to perform In-silico analysis of HCV E2 isolated in Pakistan and to analyze HCV E2 protein sequence in comparison with other E2 proteins belonging to 3a and 1a genotypes to find potential conserved B-cells and T-cell epitopes that can be important in designing novel inhibitory compounds and peptide vaccine against genotype 3a and 1a. PATIENTS AND METHODS: Patients were selected on the basis of elevated serum ALT and AST levels at least for six months, histological examination, and detection of serum HCV RNA anti-HCV antibodies (3rd generation ELISA). RNA isolation, cDNA synthesis, amplification, cloning and sequencing was performed from 4 patient's serum samples in order to get the HCV E2 sequence. HCV E2 protein of Pakistani origin was analyzed using various bioinformatics tools including sequence and structure tools. RESULTS: HCV E1 protein modeling was performed with I-TASSER online server and quality of the model was assessed with ramchandran plot and Z-score. A total of 3 B-cell and 3 T-cell epitopes were found to be highly conserved among HCV 3a and 1a genotype. CONCLUSION: The present study revealed potential conserved B-cell and T-cell epitopes of the HCV E2 protein along with 3D protein modeling. These conserved B-cell and T-cell epitopes can be helpful in developing effective vaccines against HCV and thus limiting threats of HCV infection in Pakistan.

Structural analysis and epitope prediction of HCV E1 protein isolated in Pakistan: an in-silico approach.

BACKGROUND: HCV infection is a major health problem causing acute and chronic hepatitis. HCV E1 protein is a transmembrane protein that is involved in viral attachment and therefore, can serve as an important target for vaccine development. Consequently, this study was designed to analyze the HCV E1 protein sequence isolated in Pakistan to find potential conserved epitopes/antigenic determinants. RESULTS: HCV E1 protein isolated in Pakistan was analyzed using various bio-informatics and immuno-informatics tools including sequence and structure tools. A total of four antigenic B cell epitopes, 5 MHC class I binding peptides and 5 MHC class II binding peptides were predicted. Best designed epitopes were subjected to conservation analyses with other countries. CONCLUSION: The study was conducted to predict antigenic determinants/epitopes of HCV E1 protein of genotype 3a along with the 3D protein modeling. The study revealed potential B-cell and T-cell epitopes that can raise the desired immune response against HCV E1 protein isolated in Pakistan. Conservation analysis can be helpful in developing effective vaccines against HCV and thus limiting threats of HCV infection in Pakistan.

Development of global consensus sequence of HCV glycoproteins involved in viral entry.

BACKGROUND: HCV affects>170 million people worldwide and is a leading cause of liver diseases such as hepatocellular carcinoma. Each year, Pakistan reports hundreds of cases and now it has become a serious health issue. HCV has two transmembrane glycoproteins (E1 and E2) that are involved in virus entry through viral attachment, but because of their hypervariable nature they have become difficult targets for vaccine development. METHODS: A total of 150 protein sequences of E1 and E2 belonging to genotypes 3a and 1a were retrieved from the NCBI protein database and were subjected to conservation and variation analysis using the multiple sequence alignment feature of the CLC workbench. A consensus sequence of each genotype of E1 and E2 was obtained and these consensus sequences were further analyzed to construct a global consensus sequence, which was used to design potentially conserved peptides. RESULTS: From the sequence conservation analysis, highly conserved residues were identified and were used to design peptides. Only two peptides were found to be conserved in the E1 protein of genotypes 3a and 1a and a total of nine conserved peptides were designed for the HCV E2 protein of those genotypes. These designed peptides could serve as useful targets in developing new inhibitory compounds. CONCLUSION: This study was designed to perform conservation and variability analysis of HCV glycoproteins and to find potentially conserved peptides among genotypes 3a and 1a (the most prevalent genotypes in Pakistan) that could serve as useful targets in the development of novel inhibitory compounds, thus reducing the threat of HCV infection in Pakistan.

How different viruses perturb host cellular machinery via short linear motifs.

The virus interacts with its hosts by developing protein-protein interactions. Most viruses employ protein interactions to imitate the host protein: A viral protein with the same amino acid sequence or structure as the host protein attaches to the host protein's binding partner and interferes with the host protein's pathways. Being opportunistic, viruses have evolved to manipulate host cellular mechanisms by mimicking short linear motifs. In this review, we shed light on the current understanding of mimicry via short linear motifs and focus on viral mimicry by genetically different viral subtypes by providing recent examples of mimicry evidence and how high-throughput methods can be a reliable source to study SLiM-mediated viral mimicry.

Digital health education and training for undergraduate and graduate nursing students: a scoping review protocol.

OBJECTIVE: The objective of this review is to collate and analyze literature reporting on digital health education and training courses, or other pedagogical interventions, for nursing students at the undergraduate and graduate level to identify gaps and inform the development of future educational interventions. INTRODUCTION: In this era of technology-driven health care, upskilling and/or reskilling the nursing workforce is urgently needed for nurses to lead the digital health future and improve patient care. While informatics competency frameworks serve to inform nursing education and practice, they do not address the entire digital health spectrum. INCLUSION CRITERIA: This review will include research studies, theoretical/discussion papers, and reports, as well as gray literature from relevant sources published in the last 10 years. Opinion pieces, editorials, conference proceedings, and papers published in languages other than English will be excluded. METHODS: The JBI methodology for scoping reviews will be followed. Searches will be conducted in Embase, CINAHL, ERIC, MEDLINE, Scopus, and Education Research Complete to retrieve potentially relevant studies. Hand searches of reference lists of included studies will be conducted. Two reviewers will independently screen records against predefined eligibility criteria and consult a third reviewer if conflicts arise. Decisions will be documented using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. Quantitative data will be analyzed using descriptive statistics. Content analysis will be applied to qualitative data to identify categories and themes. Findings will be synthesized and reported in tables and narrative format. REVIEW REGISTRATION NUMBER: Open Science Framework osf.io/42eug.