An update on novel approaches for diagnosis and treatment of SARS-CoV-2 infection

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has made a serious public health and economic crisis worldwide which united global efforts to develop rapid, precise, and cost-efficient diagnostics, vaccines, and therapeutics. Numerous multi-disciplinary studies and techniques have been designed to investigate and develop various approaches to help frontline health workers, policymakers, and populations to overcome the disease. While these techniques have been reviewed within individual disciplines, it is now timely to provide a cross-disciplinary overview of novel diagnostic and therapeutic approaches summarizing complementary efforts across multiple fields of research and technology. Accordingly, we reviewed and summarized various advanced novel approaches used for diagnosis and treatment of COVID-19 to help researchers across diverse disciplines on their prioritization of resources for research and development and to give them better a picture of the latest techniques. These include artificial intelligence, nano-based, CRISPR-based, and mass spectrometry technologies as well as neutralizing factors and traditional medicines. We also reviewed new approaches for vaccine development and developed a dashboard to provide frequent updates on the current and future approved vaccines

Investigating the Mechanism of Arsenic-induced Ferroptosis in the Skin

Background: Ferroptosis, an oxidative and iron-dependent cell death, is a new type of regulated cell death. There are few studies on the mechanisms of ferroptosis in the skin and related diseases. Arsenic is shown to induce ferroptosis cell death. This study aimed to decipher the relationship between arsenic exposure and ferroptosis cell death in the skin. Methods: Arsenic-gene interactions were obtained. Then, skin-specific arsenic-gene interactions were screened. Ferroptosis-related genes were identified. Analysis of functional and biological interactions was performed to identify possible mechanisms. Results: The arsenic-gene interactions and the ferroptosis-related genes showed an overlap of 59 genes. Functional enrichment, protein-protein interaction, and transcription factor (TF)/miRNA target gene interaction analyses were used to look into the mechanism of arsenic-induced ferroptosis in the skin. ACTB, CTNNB1, HSPA8, SRC, RACK1, CD44, and SQSTM1 were identified as key proteins. Gene ontology analysis of these proteins indicated the mitochondrial morphology and functionality changes following arsenic-induced ferroptosis in the skin. HIF1A and SP1 TFs regulate a large number of genes compared to other TFs. Ten miRNAs with high interaction with ferroptosis-associated genes were identified. Conclusion: This work investigated the mechanism of arsenic-induced ferroptosis in the skin and identified key genes and regulators, and functional analysis highlighted the role of mitochondria in this skin exposure

Investigation of the relationship between self-esteem and depressive symptoms among young patients with Multiple Sclerosis

For downloading the full-text of this article please click here.Background and Objectives: Multiple Sclerosis (MS) is a chronic inflammatory disorder of the central nervous system, which aggravates the loss of self-esteem in patients and impairs their ability to cope with the disabilities. The present study investigated the relationship between self-esteem and anxiety among MS patients in Shiraz. Materials and Methods: A descriptive-analytical study was carried out on all young MS patients when the disease was not in an acute stage, aged 20-40 years old in Fars Province in 2009-10. 150 MS patients (90 males and 60 females) were selected through in-access sampling method from a pool of patients who received services from Charity Foundation for Special Diseases (CFSD). The data were collected using self-esteem questionnaire and researcher-made questionnaire of anxiety. Data were analyzed with SPSS V.16 using Regression and Correlation with α=0.05. Results: Our findings indicated that there was an inverse and significant relationship between self-esteem and anxiety in MS patients of both sexes, with self-esteem predicting 0.66 anxiety of the participants.Conclusion: According to our findings, holding sessions to provide insights into the importance of self-esteem would help MS patients and their families to deal with the disease problems more rationally, thus decreasing major part of their concerns. Keywords: Multiple Sclerosis (MS), Self-esteem, AnxietyFor downloading the full-text of this article please click here

Unraveling Kinase Activation Dynamics Using Kinase-Substrate Relationships from Temporal Large-Scale Phosphoproteomics Studies.

In response to stimuli, biological processes are tightly controlled by dynamic cellular signaling mechanisms. Reversible protein phosphorylation occurs on rapid time-scales (milliseconds to seconds), making it an ideal carrier of these signals. Advances in mass spectrometry-based proteomics have led to the identification of many tens of thousands of phosphorylation sites, yet for the majority of these the kinase is unknown and the underlying network topology of signaling networks therefore remains obscured. Identifying kinase substrate relationships (KSRs) is therefore an important goal in cell signaling research. Existing consensus sequence motif based prediction algorithms do not consider the biological context of KSRs, and are therefore insensitive to many other mechanisms guiding kinase-substrate recognition in cellular contexts. Here, we use temporal information to identify biologically relevant KSRs from Large-scale In Vivo Experiments (KSR-LIVE) in a data-dependent and automated fashion. First, we used available phosphorylation databases to construct a repository of existing experimentally-predicted KSRs. For each kinase in this database, we used time-resolved phosphoproteomics data to examine how its substrates changed in phosphorylation over time. Although substrates for a particular kinase clustered together, they often exhibited a different temporal pattern to the phosphorylation of the kinase. Therefore, although phosphorylation regulates kinase activity, our findings imply that substrate phosphorylation likely serve as a better proxy for kinase activity than kinase phosphorylation. KSR-LIVE can thereby infer which kinases are regulated within a biological context. Moreover, KSR-LIVE can also be used to automatically generate positive training sets for the subsequent prediction of novel KSRs using machine learning approaches. We demonstrate that this approach can distinguish between Akt and Rps6kb1, two kinases that share the same linear consensus motif, and provide evidence suggesting IRS-1 S265 as a novel Akt site. KSR-LIVE is an open-access algorithm that allows users to dissect phosphorylation signaling within a specific biological context, with the potential to be included in the standard analysis workflow for studying temporal high-throughput signal transduction data

Investigating the Mechanism of Arsenic-induced Ferroptosis in the Skin

Background: Ferroptosis, an oxidative and iron-dependent cell death, is a new type of regulated cell death. There are few studies on the mechanisms of ferroptosis in the skin and related diseases. Arsenic is shown to induce ferroptosis cell death. This study aimed to decipher the relationship between arsenic exposure and ferroptosis cell death in the skin. Methods: Arsenic-gene interactions were obtained. Then, skin-specific arsenic-gene interactions were screened. Ferroptosis-related genes were identified. Analysis of functional and biological interactions was performed to identify possible mechanisms. Results: The arsenic-gene interactions and the ferroptosis-related genes showed an overlap of 59 genes. Functional enrichment, protein-protein interaction, and transcription factor (TF)/miRNA target gene interaction analyses were used to look into the mechanism of arsenic-induced ferroptosis in the skin. ACTB, CTNNB1, HSPA8, SRC, RACK1, CD44, and SQSTM1 were identified as key proteins. Gene ontology analysis of these proteins indicated the mitochondrial morphology and functionality changes following arsenic-induced ferroptosis in the skin. HIF1A and SP1 TFs regulate a large number of genes compared to other TFs. Ten miRNAs with high interaction with ferroptosis-associated genes were identified. Conclusion: This work investigated the mechanism of arsenic-induced ferroptosis in the skin and identified key genes and regulators, and functional analysis highlighted the role of mitochondria in this skin exposure

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations

Medication Errors and its Contributing Factors among Midwives

Introduction: Medication errors are among the most serious health errors threatening patient safety in all countries, with major impacts on public health. Midwives as members of healthcare systems are prone to such errors. Therefore, in this study, we aimed to determine medication errors and the contributing factors among midwives working in maternity units of Mashhad University of Medical Sciences, Mashhad, Iran in 2015. Methods: This descriptive, cross-sectional study was performed on 104 employed midwives at four hospitals (Imam Reza, Ghaem, Omolbanin, and Hashemi Nezhad hospitals), affiliated to Mashhad University of Medical Sciences. The validity and reliability of the data collection tools were confirmed through content validity and internal consistency (Cronbach's alpha), respectively. For data analysis, descriptive and analytical tests, multiple linear regression, and negative binomial regression analysis were performed, using SPSS version 20 and STATA version 11. Results: The average incidence of medication errors for each midwife was 21.24±2.89 in the past six months. Among reasons against reporting medication errors, fear of confrontation with authorities (3.79±1.5) and attributing the medication error to individual factors by officials (3.88±1.34) had the highest average scores. The most common causes of medication errors were overcrowding of the ward (4.32±1.01), excessive workload and overexertion (4.19±1.08), and presence of critically ill patients in the ward (4.03±1.18). Conclusion: Overcrowding of the ward, fear of authorities, and attributing the medication error to individual factors were the main reasons against reporting medication errors, respectively. Therefore, more attention should be paid to error reporting systems, and workshops in this area are highly recommended

Harnessing liquid biopsies to guide immune checkpoint inhibitor therapy

Immunotherapy (IO), involving the use of immune checkpoint inhibition, achieves improved response-rates and significant disease-free survival for some cancer patients. Despite these beneficial effects, there is poor predictability of response and substantial rates of innate or acquired resistance, resulting in heterogeneous responses among patients. In addition, patients can develop life-threatening adverse events, and while these generally occur in patients that also show a tumor response, these outcomes are not always congruent. Therefore, predicting a response to IO is of paramount importance. Traditionally, tumor tissue analysis has been used for this purpose. However, minimally invasive liquid biopsies that monitor changes in blood or other bodily fluid markers are emerging as a promising cost-effective alternative. Traditional biomarkers have limitations mainly due to difficulty in repeatedly obtaining tumor tissue confounded also by the spatial and temporal heterogeneity of tumours. Liquid biopsy has the potential to circumvent tumor heterogeneity and to help identifying patients who may respond to IO, to monitor the treatment dynamically, as well as to unravel the mechanisms of relapse. We present here a review of the current status of molecular markers for the prediction and monitoring of IO response, focusing on the detection of these markers in liquid biopsies. With the emerging improvements in the field of liquid biopsy, this approach has the capacity to identify IO-eligible patients and provide clinically relevant information to assist with their ongoing disease management

Anti-cancer potential of synergistic phytochemical combinations is influenced by the genetic profile of prostate cancer cell lines

Introduction: Despite strong epidemiological evidence that dietary factors modulate cancer risk, cancer control through dietary intervention has been a largely intractable goal for over sixty years. The effect of tumour genotype on synergy is largely unexplored. Methods: The effect of seven dietary phytochemicals, quercetin (0–100 μM), curcumin (0–80 μM), genistein, indole-3-carbinol (I3C), equol, resveratrol and epigallocatechin gallate (EGCG) (each 0–200 μM), alone and in all paired combinations om cell viability of the androgen-responsive, pTEN-null (LNCaP), androgen-independent, pTEN-null (PC-3) or androgen-independent, pTEN-positive (DU145) prostate cancer (PCa) cell lines was determined using a high throughput alamarBlue® assay. Synergy, additivity and antagonism were modelled using Bliss additivism and highest single agent equations. Patterns of maximum synergy were identified by polygonogram analysis. Network pharmacology approaches were used to identify interactions with known PCa protein targets. Results: Synergy was observed with all combinations. In LNCaP and PC-3 cells, I3C mediated maximum synergy with five phytochemicals, while genistein was maximally synergistic with EGCG. In contrast, DU145 cells showed resveratrol-mediated maximum synergy with equol, EGCG and genistein, with I3C mediating maximum synergy with only quercetin and curcumin. Knockdown of pTEN expression in DU145 cells abrogated the synergistic effect of resveratrol without affecting the synergy profile of I3C and quercetin. Discussion: Our study identifies patterns of synergy that are dependent on tumour cell genotype and are independent of androgen signaling but are dependent on pTEN. Despite evident cell-type specificity in both maximally-synergistic combinations and the pathways that phytochemicals modulate, these combinations interact with similar prostate cancer protein targets. Here, we identify an approach that, when coupled with advanced data analysis methods, may suggest optimal dietary phytochemical combinations for individual consumption based on tumour molecular profile