Different fluorescent labels report distinct components of spHCN channel voltage sensor movement.

We used voltage clamp fluorometry to probe the movement of the S4 helix in the voltage-sensing domain of the sea urchin HCN channel (spHCN) expressed in Xenopus oocytes. We obtained markedly different fluorescence responses with either ALEXA-488 or MTS-TAMRA covalently linked to N-terminal Cys332 of the S4 helix. With hyperpolarizing steps, ALEXA-488 fluorescence increased rapidly, consistent with it reporting the initial inward movement of S4, as previously described. In contrast, MTS-TAMRA fluorescence increased more slowly and its early phase correlated with that of channel opening. Additionally, a slow fluorescence component that tracked the development of the mode shift, or channel hysteresis, could be resolved with both labels. We quantitated this component as an increased deactivation tail current delay with concomitantly longer activation periods and found it to depend strongly on the presence of K+ ions in the pore. Using collisional quenching experiments and structural predictions, we established that ALEXA-488 was more exposed to solvent than MTS-TAMRA. We propose that components of S4 movement during channel activation can be kinetically resolved using different fluorescent probes to reveal distinct biophysical properties. Our findings underscore the need to apply caution when interpreting voltage clamp fluorometry data and demonstrate the potential utility of different labels to interrogate distinct biophysical properties of voltage-gated membrane proteins.

Identification and Evaluation of Olive Phenolics in the Context of Amine Oxidase Enzyme Inhibition and Depression: In Silico Modelling and In Vitro Validation.

The Mediterranean diet well known for its beneficial health effects, including mood enhancement, is characterised by the relatively high consumption of extra virgin olive oil (EVOO), which is rich in bioactive phenolic compounds. Over 200 phenolic compounds have been associated with Olea europaea, and of these, only a relatively small fraction have been characterised. Utilising the OliveNetTM library, phenolic compounds were investigated as potential inhibitors of the epigenetic modifier lysine-specific demethylase 1 (LSD1). Furthermore, the compounds were screened for inhibition of the structurally similar monoamine oxidases (MAOs) which are directly implicated in the pathophysiology of depression. Molecular docking highlighted that olive phenolics interact with the active site of LSD1 and MAOs. Protein-peptide docking was also performed to evaluate the interaction of the histone H3 peptide with LSD1, in the presence of ligands bound to the substrate-binding cavity. To validate the in silico studies, the inhibitory activity of phenolic compounds was compared to the clinically approved inhibitor tranylcypromine. Our findings indicate that olive phenolics inhibit LSD1 and the MAOs in vitro. Using a cell culture model system with corticosteroid-stimulated human BJ fibroblast cells, the results demonstrate the attenuation of dexamethasone- and hydrocortisone-induced MAO activity by phenolic compounds. The findings were further corroborated using human embryonic stem cell (hESC)-derived neurons stimulated with all-trans retinoic acid. Overall, the results indicate the inhibition of flavin adenine dinucleotide (FAD)-dependent amine oxidases by olive phenolics. More generally, our findings further support at least a partial mechanism accounting for the antidepressant effects associated with EVOO and the Mediterranean diet.

Surgical gestures to evaluate apical dissection of robot-assisted radical prostatectomy.

Previously, our group established a surgical gesture classification system that deconstructs robotic tissue dissection into basic surgical maneuvers. Here, we evaluate gestures by correlating the metric with surgeon experience and technical skill assessment scores in the apical dissection (AD) of robotic-assisted radical prostatectomy (RARP). Additionally, we explore the association between AD performance and early continence recovery following RARP. 78 AD surgical videos from 2016 to 2018 across two international institutions were included. Surgeons were grouped by median robotic caseload (range 80-5,800 cases): less experienced group (< 475 cases) and more experienced (≥ 475 cases). Videos were decoded with gestures and assessed using Dissection Assessment for Robotic Technique (DART). Statistical findings revealed more experienced surgeons (n = 10) used greater proportions of cold cut (p = 0.008) and smaller proportions of peel/push, spread, and two-hand spread (p < 0.05) than less experienced surgeons (n = 10). Correlations between gestures and technical skills assessments ranged from - 0.397 to 0.316 (p < 0.05). Surgeons utilizing more retraction gestures had lower total DART scores (p < 0.01), suggesting less dissection proficiency. Those who used more gestures and spent more time per gesture had lower efficiency scores (p < 0.01). More coagulation and hook gestures were found in cases of patients with continence recovery compared to those with ongoing incontinence (p < 0.04). Gestures performed during AD vary based on surgeon experience level and patient continence recovery duration. Significant correlations were demonstrated between gestures and dissection technical skills. Gestures can serve as a novel method to objectively evaluate dissection performance and anticipate outcomes.

Capturing relationships between suturing sub-skills to improve automatic suturing assessment.

Suturing skill scores have demonstrated strong predictive capabilities for patient functional recovery. The suturing can be broken down into several substep components, including needle repositioning, needle entry angle, etc. Artificial intelligence (AI) systems have been explored to automate suturing skill scoring. Traditional approaches to skill assessment typically focus on evaluating individual sub-skills required for particular substeps in isolation. However, surgical procedures require the integration and coordination of multiple sub-skills to achieve successful outcomes. Significant associations among the technical sub-skill have been established by existing studies. In this paper, we propose a framework for joint skill assessment that takes into account the interconnected nature of sub-skills required in surgery. The prior known relationships among sub-skills are firstly identified. Our proposed AI system is then empowered by the prior known relationships to perform the suturing skill scoring for each sub-skill domain simultaneously. Our approach can effectively improve skill assessment performance through the prior known relationships among sub-skills. Through the proposed approach to joint skill assessment, we aspire to enhance the evaluation of surgical proficiency and ultimately improve patient outcomes in surgery.

Utilization of the EpiMed Coronabank Chemical Collection to identify potential SARS-CoV-2 antivirals: in silico studies targeting the nsp14 ExoN domain and PLpro naphthalene binding site.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome encodes 29 proteins including four structural, 16 nonstructural (nsps), and nine accessory proteins (https://epimedlab.org/sars-cov-2-proteome/). Many of these proteins contain potential targetable sites for the development of antivirals. Despite the widespread use of vaccinations, the emergence of variants necessitates the investigation of new therapeutics and antivirals. Here, the EpiMed Coronabank Chemical Collection (https://epimedlab.org/crl/) was utilized to investigate potential antivirals against the nsp14 exoribonuclease (ExoN) domain. Molecular docking was performed to evaluate the binding characteristics of our chemical library against the nsp14 ExoN site. Based on the initial screen, trisjuglone, ararobinol, corilagin, and naphthofluorescein were identified as potential lead compounds. Molecular dynamics (MD) simulations were subsequently performed, with the results highlighting the stability of the lead compounds in the nsp14 ExoN site. Protein-RNA docking revealed the potential for the lead compounds to disrupt the interaction with RNA when bound to the ExoN site. Moreover, hypericin, cyanidin-3-O-glucoside, and rutin were previously identified as lead compounds targeting the papain-like protease (PLpro) naphthalene binding site. Through performing MD simulations, the stability and interactions of lead compounds with PLpro were further examined. Overall, given the critical role of the exonuclease activity of nsp14 in ensuring viral fidelity and the multifunctional role of PLpro in viral pathobiology and replication, these nsps represent important targets for antiviral drug development. Our databases can be utilized for in silico studies, such as the ones performed here, and this approach can be applied to other potentially druggable SARS-CoV-2 protein targets.

Clinical applications of artificial intelligence in robotic surgery.

Artificial intelligence (AI) is revolutionizing nearly every aspect of modern life. In the medical field, robotic surgery is the sector with some of the most innovative and impactful advancements. In this narrative review, we outline recent contributions of AI to the field of robotic surgery with a particular focus on intraoperative enhancement. AI modeling is allowing surgeons to have advanced intraoperative metrics such as force and tactile measurements, enhanced detection of positive surgical margins, and even allowing for the complete automation of certain steps in surgical procedures. AI is also Query revolutionizing the field of surgical education. AI modeling applied to intraoperative surgical video feeds and instrument kinematics data is allowing for the generation of automated skills assessments. AI also shows promise for the generation and delivery of highly specialized intraoperative surgical feedback for training surgeons. Although the adoption and integration of AI show promise in robotic surgery, it raises important, complex ethical questions. Frameworks for thinking through ethical dilemmas raised by AI are outlined in this review. AI enhancements in robotic surgery is some of the most groundbreaking research happening today, and the studies outlined in this review represent some of the most exciting innovations in recent years.

Identification of inhibitors from a functional food-based plant Perillae Folium against hyperuricemia via metabolomics profiling, network pharmacology and all-atom molecular dynamics simulations.

Introduction: Hyperuricemia (HUA) is a metabolic disorder caused by purine metabolism dysfunction in which the increasing purine levels can be partially attributed to seafood consumption. Perillae Folium (PF), a widely used plant in functional food, has been historically used to mitigate seafood-induced diseases. However, its efficacy against HUA and the underlying mechanism remain unclear. Methods: A network pharmacology analysis was performed to identify candidate targets and potential mechanisms involved in PF treating HUA. The candidate targets were determined based on TCMSP, SwissTargetPrediction, Open Targets Platform, GeneCards, Comparative Toxicogenomics Database, and DrugBank. The potential mechanisms were predicted via Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) analyses. Molecular docking in AutoDock Vina and PyRx were performed to predict the binding affinity and pose between herbal compounds and HUA-related targets. A chemical structure analysis of PF compounds was performed using OSIRIS DataWarrior and ClassyFire. We then conducted virtual pharmacokinetic and toxicity screening to filter potential inhibitors. We further performed verifications of these inhibitors' roles in HUA through molecular dynamics (MD) simulations, text-mining, and untargeted metabolomics analysis. Results: We obtained 8200 predicted binding results between 328 herbal compounds and 25 potential targets, and xanthine dehydrogenase (XDH) exhibited the highest average binding affinity. We screened out five promising ligands (scutellarein, benzyl alpha-D-mannopyranoside, elemol, diisobutyl phthalate, and (3R)-hydroxy-beta-ionone) and performed MD simulations up to 50 ns for XDH complexed to them. The scutellarein-XDH complex exhibited the most satisfactory stability. Furthermore, the text-mining study provided laboratory evidence of scutellarein's function. The metabolomics approach identified 543 compounds and confirmed the presence of scutellarein. Extending MD simulations to 200 ns further indicated the sustained impact of scutellarein on XDH structure. Conclusion: Our study provides a computational and biomedical basis for PF treating HUA and fully elucidates scutellarein's great potential as an XDH inhibitor at the molecular level, holding promise for future drug design and development.

The influence of zwitterionic and anionic phospholipids on protein aggregation.

The progressive aggregation of misfolded proteins is the underlying molecular cause of numerous pathologies including Parkinson's disease and injection and transthyretin amyloidosis. A growing body of evidence indicates that protein deposits detected in organs and tissues of patients diagnosed with such pathologies contain fragments of lipid membranes. In vitro experiments also showed that lipid membranes could strongly change the aggregation rate of amyloidogenic proteins, as well as alter the secondary structure and toxicity of oligomers and fibrils formed in their presence. In this review, the effect of large unilamellar vesicles (LUVs) composed of zwitterionic and anionic phospholipids on the aggregation rate of insulin, lysozyme, transthyretin (TTR) and α- synuclein (α-syn) will be discussed. The manuscript will also critically review the most recent findings on the lipid-induced changes in the secondary structure of protein oligomers and fibrils, as well as reveal the extent to which lipids could alter the toxicity of protein aggregates formed in their presence.

Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert Evaluation.

OBJECTIVE: Surgical skill assessment tools such as the End-to-End Assessment of Suturing Expertise (EASE) can differentiate a surgeon's experience level. In this simulation-based study, we define a competency benchmark for intraoperative robotic suturing using EASE as a validated measure of performance. DESIGN: Participants conducted a dry-lab vesicourethral anastomosis (VUA) exercise. Videos were each independently scored by 2 trained, blinded reviewers using EASE. Inter-rater reliability was measured with prevalence-adjusted bias-adjusted Kappa (PABAK) using 2 example videos. All videos were reviewed by an expert surgeon, who determined if the suturing skills exhibited were at a competency level expected for residency graduation (pass or fail). The Contrasting Group (CG) method was then used to set a pass/fail score at the intercept of the pass and fail cohorts' EASE score distributions. SETTING: Keck School of Medicine, University of Southern California. PARTICIPANTS: Twenty-six participants: 8 medical students, 8 junior residents (PGY 1-2), 7 senior residents (PGY 3-5) and 3 attending urologists. RESULTS: After 1 round of consensus-building, average PABAK across EASE subskills was 0.90 (Range 0.67-1.0). The CG method produced a competency benchmark EASE score of >35/39, with a pass rate of 10/26 (38%); 27% were deemed competent by expert evaluation. False positives and negatives were defined as medical students who passed and attendings who failed the assessment, respectively. This pass/fail score produced no false positives or negatives, and fewer JR than SR were considered competent by both the expert and CG benchmark. CONCLUSIONS: Using an absolute standard setting method, competency scores were set to identify trainees who could competently execute a standardized dry-lab robotic suturing exercise. This standard can be used for high stakes decisions regarding a trainee's technical readiness for independent practice. Future work includes validation of this standard in the clinical environment through correlation with clinical outcomes.

Artificial intelligence and urology: ethical considerations for urologists and patients.

The use of artificial intelligence (AI) in medicine and in urology specifically has increased over the past few years, during which time it has enabled optimization of patient workflow, increased diagnostic accuracy and enhanced computer analysis of radiological and pathological images. However, before further use of AI is undertaken, possible ethical issues need to be evaluated to improve understanding of this technology and to protect patients and providers. Possible ethical issues that require consideration when applying AI in clinical practice include patient safety, cybersecurity, transparency and interpretability of the data, inclusivity and equity, fostering responsibility and accountability, and the preservation of providers' decision-making and autonomy. Ethical principles for the application of AI to health care and in urology are proposed to guide urologists, patients and regulators to improve use of AI technologies and guide policy-making.

γH2AX in mouse embryonic stem cells: Distribution during differentiation and following γ-irradiation.

Phosphorylated histone H2AX (γH2AX) represents a sensitive molecular marker of DNA double-strand breaks (DSBs) and is implicated in stem cell biology. We established a model of mouse embryonic stem cell (mESC) differentiation and examined the dynamics of γH2AX foci during the process. Our results revealed high numbers of γH2AX foci in undifferentiated mESCs, decreasing as the cells differentiated towards the endothelial cell lineage. Notably, we observed two distinct patterns of γH2AX foci: the typical discrete γH2AX foci, which colocalize with the transcriptionally permissive chromatin mark H3K4me3, and the less well-characterized clustered γH2AX regions, which were only observed in intermediate progenitor cells. Next, we explored responses of mESCs to γ-radiation (137Cs). Following exposure to γ-radiation, mESCs showed a reduction in cell viability and increased γH2AX foci, indicative of radiosensitivity. Despite irradiation, surviving mESCs retained their differentiation potential. To further exemplify our findings, we investigated neural stem progenitor cells (NSPCs). Similar to mESCs, NSPCs displayed clustered γH2AX foci associated with progenitor cells and discrete γH2AX foci indicative of embryonic stem cells or differentiated cells. In conclusion, our findings demonstrate that γH2AX serves as a versatile marker of DSBs and may have a role as a biomarker in stem cell differentiation. The distinct patterns of γH2AX foci in differentiating mESCs and NSPCs provide valuable insights into DNA repair dynamics during differentiation, shedding light on the intricate balance between genomic integrity and cellular plasticity in stem cells. Finally, the clustered γH2AX foci observed in intermediate progenitor cells is an intriguing feature, requiring further exploration.

Artificial Intelligence-Based Video Feedback to Improve Novice Performance on Robotic Suturing Skills: A Pilot Study.

Introduction: Automated skills assessment can provide surgical trainees with objective, personalized feedback during training. Here, we measure the efficacy of artificial intelligence (AI)-based feedback on a robotic suturing task. Materials and Methods: Forty-two participants with no robotic surgical experience were randomized to a control or feedback group and video-recorded while completing two rounds (R1 and R2) of suturing tasks on a da Vinci surgical robot. Participants were assessed on needle handling and needle driving, and feedback was provided via a visual interface after R1. For feedback group, participants were informed of their AI-based skill assessment and presented with specific video clips from R1. For control group, participants were presented with randomly selected video clips from R1 as a placebo. Participants from each group were further labeled as underperformers or innate-performers based on a median split of their technical skill scores from R1. Results: Demographic features were similar between the control (n = 20) and feedback group (n = 22) (p > 0.05). Observing the improvement from R1 to R2, the feedback group had a significantly larger improvement in needle handling score (0.30 vs -0.02, p = 0.018) when compared with the control group, although the improvement of needle driving score was not significant when compared with the control group (0.17 vs -0.40, p = 0.074). All innate-performers exhibited similar improvements across rounds, regardless of feedback (p > 0.05). In contrast, underperformers in the feedback group improved more than the control group in needle handling (p = 0.02). Conclusion: AI-based feedback facilitates surgical trainees' acquisition of robotic technical skills, especially underperformers. Future research will extend AI-based feedback to additional suturing skills, surgical tasks, and experience groups.

Simulation training in urology.

PURPOSE OF REVIEW: This review outlines recent innovations in simulation technology as it applies to urology. It is essential for the next generation of urologists to attain a solid foundation of technical and nontechnical skills, and simulation technology provides a variety of safe, controlled environments to acquire this baseline knowledge. RECENT FINDINGS: With a focus on urology, this review first outlines the evidence to support surgical simulation, then discusses the strides being made in the development of 3D-printed models for surgical skill training and preoperative planning, virtual reality models for different urologic procedures, surgical skill assessment for simulation, and integration of simulation into urology residency curricula. SUMMARY: Simulation continues to be an integral part of the journey towards the mastery of skills necessary for becoming an expert urologist. Clinicians and researchers should consider how to further incorporate simulation technology into residency training and help future generations of urologists throughout their career.

A repository of COVID-19 related molecular dynamics simulations and utilisation in the context of nsp10-nsp16 antivirals.

The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of establishing systems and infrastructure to develop vaccines, antiviral drugs, and therapeutic antibodies against emerging pathogens. Typical drug discovery processes involve targeting suitable proteins to effect pathogen replication or to attenuate host responses, by examining either large chemical databases or protein-protein interactions. Following initial screens, molecular dynamics (MD) simulations are critical for gaining further insight into molecular interactions. During the COVID-19 pandemic, many research groups made their simulations widely available, as highlighted by the comprehensive D.E. Shaw Research trajectory database. To investigate protein target sites and evaluate potential lead compounds, we performed over 300 MD simulations relating to COVID-19. We organised our simulations into a repository, which is publicly available at https://epimedlab.org/trajectories/. The trajectories cover a large part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome, and the majority of our MD simulations focused on the identification of potential antivirals. For example, we focused on the S-adenosyl-l-methionine binding site of the nsp10-nsp16 complex, a critical component of viral replication, revealing verbascoside as a potential lead. Moreover, we utilised MD trajectories to explore the interface between the spike protein receptor binding domain and human angiotensin-converting enzyme 2 receptor, with the ultimate aim being investigation of new variants in real-time. Overall, MD simulations are a critical component of the in silico drug discovery process and as highlighted throughout the pandemic, data sharing enables accelerated progress. We have organised our extensive collection of COVID-19 related MD trajectories into an easily accessible repository.

Identification of Potential Modulators of a Pathogenic G Protein-Gated Inwardly Rectifying K+ Channel 4 Mutant: In Silico Investigation in the Context of Drug Discovery for Hypertension.

Genetic abnormalities have been associated with primary aldosteronism, a major cause of secondary hypertension. This includes mutations in the KCNJ5 gene, which encodes G protein-gated inwardly rectifying K+ channel 4 (GIRK4). For example, the substitution of glycine with glutamic acid gives rise to the pathogenic GIRK4G151E mutation, which alters channel selectivity, making it more permeable to Na+ and Ca2+. While tertiapin and tertiapin-Q are well-known peptide inhibitors of the GIRK4WT channel, clinically, there is a need for the development of selective modulators of mutated channels, including GIRK4G151E. Using in silico methods, including homology modeling, protein-peptide docking, ligand-binding site prediction, and molecular docking, we aimed to explore potential modulators of GIRK4WT and GIRK4G151E. Firstly, protein-peptide docking was performed to characterize the binding site of tertiapin and its derivative to the GIRK4 channels. In accordance with previous studies, the peptide inhibitors preferentially bind to the GIRK4WT channel selectivity filter compared to GIRK4G151E. A ligand-binding site analysis was subsequently performed, resulting in the identification of two potential regions of interest: the central cavity and G-loop gate. Utilizing curated chemical libraries, we screened over 700 small molecules against the central cavity of the GIRK4 channels. Flavonoids, including luteolin-7-O-rutinoside and rutin, and the macrolides rapamycin and troleandomycin bound strongly to the GIRK4 channels. Similarly, xanthophylls, particularly luteoxanthin, bound to the central cavity with a strong preference towards the mutated GIRK4G151E channel compared to GIRK4WT. Overall, our findings suggest potential lead compounds for further investigation, particularly luteoxanthin, that may selectively modulate GIRK4 channels.

Stuttering associated with a pathogenic variant in the chaperone protein cyclophilin 40.

Stuttering is a common speech disorder that interrupts speech fluency and tends to cluster in families. Typically, stuttering is characterized by speech sounds, words or syllables which may be repeated or prolonged and speech that may be further interrupted by hesitations or 'blocks'. Rare variants in a small number of genes encoding lysosomal pathway proteins have been linked to stuttering. We studied a large four-generation family in which persistent stuttering was inherited in an autosomal dominant manner with disruption of the cortico-basal-ganglia-thalamo-cortical network found on imaging. Exome sequencing of three affected family members revealed the PPID c.808C>T (p.Pro270Ser) variant that segregated with stuttering in the family. We generated a Ppid p.Pro270Ser knock-in mouse model and performed ex vivo imaging to assess for brain changes. Diffusion-weighted MRI in the mouse revealed significant microstructural changes in the left corticospinal tract, as previously implicated in stuttering. Quantitative susceptibility mapping also detected changes in cortico-striatal-thalamo-cortical loop tissue composition, consistent with findings in affected family members. This is the first report to implicate a chaperone protein in the pathogenesis of stuttering. The humanized Ppid murine model recapitulates network findings observed in affected family members.

Mechanisms of Nelumbinis folium targeting PPARγ for weight management: A molecular docking and molecular dynamics simulations study.

The lotus leaf, Nelumbinis folium (NF), has frequently appeared in obesity clinical trials as an intervention to promote weight loss and improve metabolic profiles. However, the molecular mechanisms by which it interacts with important obesity targets and pathways, such as the peroxisome proliferator-activated receptor gamma (PPARγ) within the PPAR signalling pathway, were not well understood. This study aims to screen for candidate compounds from NF with desirable pharmacokinetic properties and examine their binding feasibility at the PPARγ ligand-binding domain (LBD). Ligand- and structure-based screening of NF compounds were performed, and a consensus approach has been applied to identify druggable candidates. By examining the pharmacokinetic profiles, a large proportion of NF compounds exhibited favourable drug-likeness and oral bioavailability properties. Furthermore, the binding affinity scores and poses provided new insights on the distinctive binding behaviours of NF compounds at the LBD of PPARγ in its inactive form. Several NF compounds could bind strongly to PPARγ at sub-pockets where partial agonists and antagonists were found to bind and may induce conformational changes that influence co-repressor binding, trans-repression, and gene expression inhibition. Subsequent molecular dynamics simulations of a candidate compound (NF129 narcissin) bound to PPARγ revealed conformational stability, residue fluctuation, and binding behaviours comparable to that of the known inhibitor, SR1664. Therefore, it can be proposed that narcissin exhibits characteristics of a PPARγ antagonist. Further experimental validation to support the development of NF129 as a future anti-obesity agent is warranted.

Chronicling the 3-year evolution of the COVID-19 pandemic: analysis of disease management, characteristics of major variants, and impacts on pathogenicity.

Announced on December 31, 2019, the novel coronavirus arising in Wuhan City, Hubei Province resulted in millions of cases and lives lost. Following intense tracking, coronavirus disease 2019 (COVID-19) was declared a pandemic by the World Health Organization (WHO) in 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified as the cause of COVID-19 and the continuous evolution of the virus has given rise to several variants. In this review, a comprehensive analysis of the response to the pandemic over the first three-year period is provided, focusing on disease management, development of vaccines and therapeutics, and identification of variants. The transmissibility and pathogenicity of SARS-CoV-2 variants including Alpha, Beta, Gamma, Delta, and Omicron are compared. The binding characteristics of the SARS-CoV-2 spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor and reproduction numbers are evaluated. The effects of major variants on disease severity, hospitalisation, and case-fatality rates are outlined. In addition to the spike protein, open reading frames mutations are investigated. We also compare the pathogenicity of SARS-CoV-2 with SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Overall, this study highlights the strengths and weaknesses of the global response to the pandemic, as well as the importance of prevention and preparedness. Monitoring the evolution of SARS-CoV-2 is critical in identifying and potentially predicting the health outcomes of concerning variants as they emerge. The ultimate goal would be a position in which existing vaccines and therapeutics could be adapted to suit new variants in as close to real-time as possible.

EpiMed Coronabank Chemical Collection: Compound selection, ADMET analysis, and utilisation in the context of potential SARS-CoV-2 antivirals.

Antiviral drugs are important for the coronavirus disease 2019 (COVID-19) response, as vaccines and antibodies may have reduced efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. Antiviral drugs that have been made available for use, albeit with questionable efficacy, include remdesivir (Veklury®), nirmatrelvir-ritonavir (Paxlovid™), and molnupiravir (Lagevrio®). To expand the options available for COVID-19 and prepare for future pandemics, there is a need to investigate new uses for existing drugs and design novel compounds. To support these efforts, we have created a comprehensive library of 750 molecules that have been sourced from in vitro, in vivo, and in silico studies. It is publicly available at our dedicated website (https://epimedlab.org/crl/). The EpiMed Coronabank Chemical Collection consists of compounds that have been divided into 10 main classes based on antiviral properties, as well as the potential to be used for the management, prevention, or treatment of COVID-19 related complications. A detailed description of each compound is provided, along with the molecular formula, canonical SMILES, and U.S. Food and Drug Administration approval status. The chemical structures have been obtained and are available for download. Moreover, the pharmacokinetic properties of the ligands have been characterised. To demonstrate an application of the EpiMed Coronabank Chemical Collection, molecular docking was used to evaluate the binding characteristics of ligands against SARS-CoV-2 nonstructural and accessory proteins. Overall, our database can be used to aid the drug repositioning process, and for gaining further insight into the molecular mechanisms of action of potential compounds of interest.

Characterization of K562 cells: uncovering novel chromosomes, assessing transferrin receptor expression, and probing pharmacological therapies.

Human erythroleukemic K562 cells represent the prototypical cell culture model of chronic myeloid leukemia (CML). The cells are pseudo-triploid and positive for the Philadelphia chromosome. Therefore, K562 cells have been widely used for investigating the BCR/ABL1 oncogene and the tyrosine kinase inhibitor, imatinib-mesylate. Further, K562 cells overexpress transferrin receptors (TfR) and have been used as a model for targeting cytotoxic therapies, via receptor-mediated endocytosis. Here, we have characterized K562 cells focusing on the karyotype of cells in prolonged culture, regulation of expression of TfR in wildtype (WT) and doxorubicin-resistant cells, and responses to histone deacetylase inhibition (HDACi). Karyotype analysis indicates novel chromosomes and gene expression analysis suggests a shift of cultured K562 cells away from patient-derived leukemic cells. We confirm the high expression of TfR on K562 cells using immunofluorescence and cell-surface receptor binding radioassays. Importantly, high TfR expression is observed in patient-derived cells, and we highlight the persistent expression of TfR following doxorubicin acquired resistance. Epigenetic analysis indicates that permissive histone acetylation and methylation at the promoter region regulates the transcription of TfR in K562 cells. Finally, we show relatively high expression of HDAC enzymes in K562 cells and demonstrate the chemotoxic effects of HDACi, using the FDA-approved hydroxamic acid, vorinostat. Together with a description of morphology, infrared spectral analysis, and examination of metabolic properties, we provide a comprehensive characterization of K562 cells. Overall, K562 cell culture systems remain widely used for the investigation of novel therapeutics for CML, which is particularly important in cases of imatinib-mesylate resistance.