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A hallmark of coronavirus transcription is the generation of negative-sense RNA intermediates that serve as the templates for the synthesis of positive-sense genomic RNA (gRNA) and an array of subgenomic mRNAs (sgRNAs) encompassing sequences arising from discontinuous transcription. Existing PCR-based diagnostic assays for SAR-CoV-2 are qualitative or semi-quantitative and do not provide the resolution needed to assess the complex transcription dynamics of SARS-CoV-2 over the course of infection. We developed and validated a novel panel of sensitive, quantitative RT-ddPCR assays designed to target regions spanning the genome of SARS-CoV-2. Our assays target untranslated regions (5', 3') as well as different coding regions, including non-structural genes that are only found in full length (genomic) RNA and structural genes that are found in genomic as well as different subgenomic RNAs. Application of these assays to clinically relevant samples will enhance our understanding of SARS-CoV-2 gene expression and may also inform the development of improved diagnostic tools and therapeutics.

Interactions between faculty and students in higher education has the potential to influence and shape many aspects of teaching, learning, curricula, student experiences and performance, yet has received little attention as an area of study. This study investigates student-faculty interactions within a physiotherapy curriculum from the perspectives of students, faculty and physiotherapy managers at a South African university. The data, produced through multiple methods, derive from students, faculty and physiotherapy managers underpinned by critical-feminist perspectives. Thematic analysis of the data produced four themes. Two dominant threads emerging from the analysis as characterising student-faculty relationships are the deeply hierarchical relations of power characterised by a lack of caring and concern for students, and the exclusion of wider constructs for interaction; deriving from a particular entrenched medical model. Ironically, while caring relationships with patients are overtly advocated and developed, they appear to be largely absent in the same physiotherapy curriculum spaces in the relationships between faculty and students. These findings raise questions about how the most foundational attribute of a health science professional, that of caring, is being produced through the curriculum in the relationship between faculty and students in the health sciences.

The replication of SARS-CoV-2 and other coronaviruses depends on transcription of negative-sense RNA intermediates that serve as the templates for the synthesis of positive-sense genomic RNA (gRNA) and multiple different subgenomic mRNAs (sgRNAs) encompassing fragments arising from discontinuous transcription. Recent studies have aimed to characterize the expression of subgenomic SARS-CoV-2 transcripts in order to investigate their clinical significance. Here, we describe a novel panel of reverse transcription droplet digital PCR (RT-ddPCR) assays designed to specifically quantify multiple different subgenomic SARS-CoV-2 transcripts and distinguish them from transcripts that do not arise from discontinuous transcription at each locus. These assays can be applied to samples from SARS-CoV-2 infected patients to better understand the regulation of SARS-CoV-2 transcription and how different sgRNAs may contribute to viral pathogenesis and clinical disease severity.

An 83-year-old female had asymptomatic SARS-CoV-2 infection while taking ruxolitinib. She remained RT-PCR positive for viral RNA for >120 days, and Pegylated interferon for 4 weeks led to viral RNA clearance. The observations support combination therapy of ruxolitinib + interferon for COVID-19.

PurposeWe recently identified CD46 as a novel therapeutic target in prostate cancer. In this study, we developed a CD46-targeted PET radiopharmaceutical, [89Zr]DFO-YS5, and evaluated its performance for immunoPET imaging in murine prostate cancer models.Experimental design[89Zr]DFO-YS5 was prepared and its in vitro binding affinity for CD46 was measured. ImmunoPET imaging was conducted in male athymic nu/nu mice bearing DU145 [AR-, CD46+, prostate-specific membrane antigen-negative (PSMA-)] or 22Rv1 (AR+, CD46+, PSMA+) tumors, and in NOD/SCID gamma mice bearing patient-derived adenocarcinoma xenograft, LTL-331, and neuroendocrine prostate cancers, LTL-331R and LTL-545.Results[89Zr]DFO-YS5 binds specifically to the CD46-positive human prostate cancer DU145 and 22Rv1 xenografts. In biodistribution studies, the tumor uptake of [89Zr]DFO-YS5 was 13.3 ± 3.9 and 11.2 ± 2.5 %ID/g, respectively, in DU145 and 22Rv1 xenografts, 4 days postinjection. Notably, [89Zr]DFO-YS5 demonstrated specific uptake in the PSMA- and AR-negative DU145 model. [89Zr]DFO-YS5 also showed uptake in the patient-derived LTL-331 and -331R models, with particularly high uptake in the LTL-545 neuroendocrine prostate cancer tumors (18.8 ± 5.3, 12.5 ± 1.8, and 32 ± 5.3 %ID/g in LTL-331, LTL-331R, and LTL-545, respectively, at 4 days postinjection).Conclusions[89Zr]DFO-YS5 is an excellent PET imaging agent across a panel of prostate cancer models, including in both adenocarcinoma and neuroendocrine prostate cancer, both cell line- and patient-derived xenografts, and both PSMA-positive and -negative tumors. It demonstrates potential for clinical translation as an imaging agent, theranostic platform, and companion biomarker in prostate cancer.

Determining the aggressiveness of renal cell carcinoma (RCC) noninvasively is a critical part of the diagnostic workup for treating this disease that kills more than 15,000 people annually in the USA. Recently, we have shown that not only the amount of lactate produced, as a consequence of the Warburg effect, but also its efflux out of the cell, is a critical marker of RCC aggressiveness and differentiating RCCs from benign renal tumors. Enzymatic conversions can now be measured in situ with hyperpolarized (HP) 13 C magnetic resonance (MR) on a sub-minute time scale. Using RCC models, we have shown that this technology can interrogate in real time both lactate production and compartmentalization, which are associated with tumor aggressiveness. The dynamic HP MR data have enabled us to robustly characterize parameters that have been elusive to measure directly in intact living cells and murine tumors thus far. Specifically, we were able to measure the same intracellular lactate longitudinal relaxation time in three RCC cell lines of 16.42 s, and lactate efflux rate ranging from 0.14 to 0.8 s-1 in the least to the most aggressive RCC cell lines and correlate it to monocarboxylate transporter isoform 4 expression. We also analyzed dynamic HP lactate and pyruvate data from orthotopic murine RCC tumors using a simplified one-compartment model, and showed comparable apparent pyruvate to lactate conversion rate (kPL ) values with those measured in vitro. This kinetic modeling was then extended to characterize the lactate dynamics in patient-derived living RCC tissue slices; and even without direct measurement of the extracellular lactate signal the efflux parameter was still assessed and was distinct between the benign renal tumors and RCCs. Across all these preclinical models, the rate parameters of kPL and lactate efflux correlated to cancer aggressiveness, demonstrating the validity of our modeling approach for noninvasive assessment of RCC aggressiveness.

Immunomodulatory drugs can inhibit bacterial growth, yet their mechanism of action, spectrum, and clinical relevance remain unknown. Methotrexate (MTX), a first-line rheumatoid arthritis (RA) treatment, inhibits mammalian dihydrofolate reductase (DHFR), but whether it directly impacts gut bacteria is unclear. We show that MTX broadly alters the human gut microbiota. Drug sensitivity varied across strains, but the mechanism of action against DHFR appears conserved between mammalian and bacterial cells. RA patient microbiotas were sensitive to MTX, and changes in gut bacterial taxa and gene family abundance were distinct between responders and non-responders. Transplantation of post-treatment samples into germ-free mice given an inflammatory trigger led to reduced immune activation relative to pre-treatment controls, enabling identification of MTX-modulated bacterial taxa associated with intestinal and splenic immune cells. Thus, conservation in cellular pathways across domains of life can result in broad off-target drug effects on the human gut microbiota with consequences for immune function.

The COVID-19 virus has made a huge impact on people’s lives ever since the outbreak happened in December 2019. Unfortunately, the COVID-19 virus has not completely vanished from the world yet, and thus, global agitation is still increasing with mutations and variants of the same. Early diagnosis is the best way to decline the mortality risk associated with it. This urges the necessity of developing new computational approaches that can analyze a large dataset and predict the disease in time. Currently, automated virus diagnosis is a major area of research for accurate and timely predictions. Artificial intelligent (AI)-based techniques such as machine learning (ML) and deep learning (DL) can be deployed for this purpose. In this, compared to traditional machine learning techniques, deep Learning approaches show prominent results. Yet it still requires optimization in terms of complex space problems. To address this issue, the proposed method combines deep learning predictive models such as convolutional neural network (CNN), long short-term memory (LSTM), auto-encoder (AE), cross-validation (CV), and synthetic minority oversampling techniques (SMOTE). This method proposes six different combinations of deep learning forecasting models such as CV-CNN, CV-LSTM+CNN, IMG-CNN, AE+CV-CNN, SMOTE-CV-LSTM, and SMOTE-CV-CNN. The performance of each model is evaluated using various metrics on the standard dataset that is approved by The Montefiore Medical Center/Albert Einstein College of Medicine Institutional Review Board. The experimental results show that the SMOTE-CV-CNN model outperforms the other models by achieving an accuracy of 98.29%. Moreover, the proposed SMOTE-CV-CNN model has been compared to existing mortality risk prediction methods based on both machine learning (ML) and deep learning (DL), and has demonstrated superior accuracy. Based on the experimental analysis, it can be inferred that the proposed SMOTE-CV-CNN model has the ability to effectively predict mortality related to COVID-19.

Preclinical imaging is a critical component in translational research with significant complexities in workflow and site differences in deployment. Importantly, the National Cancer Institute’s (NCI) precision medicine initiative emphasizes the use of translational co-clinical oncology models to address the biological and molecular bases of cancer prevention and treatment. The use of oncology models, such as patient-derived tumor xenografts (PDX) and genetically engineered mouse models (GEMMs), has ushered in an era of co-clinical trials by which preclinical studies can inform clinical trials and protocols, thus bridging the translational divide in cancer research. Similarly, preclinical imaging fills a translational gap as an enabling technology for translational imaging research. Unlike clinical imaging, where equipment manufacturers strive to meet standards in practice at clinical sites, standards are neither fully developed nor implemented in preclinical imaging. This fundamentally limits the collection and reporting of metadata to qualify preclinical imaging studies, thereby hindering open science and impacting the reproducibility of co-clinical imaging research. To begin to address these issues, the NCI co-clinical imaging research program (CIRP) conducted a survey to identify metadata requirements for reproducible quantitative co-clinical imaging. The enclosed consensus-based report summarizes co-clinical imaging metadata information (CIMI) to support quantitative co-clinical imaging research with broad implications for capturing co-clinical data, enabling interoperability and data sharing, as well as potentially leading to updates to the preclinical Digital Imaging and Communications in Medicine (DICOM) standard.

Diabetes is a category of metabolic disease commonly known as a chronic illness. It causes the body to generate less insulin and raises blood sugar levels, leading to various issues and disrupting the functioning of organs, including the retinal, kidney and nerves. To prevent this, people with chronic illnesses require lifetime access to treatment. As a result, early diabetes detection is essential and might save many lives. Diagnosis of people at high risk of developing diabetes is utilized for preventing the disease in various aspects. This article presents a chronic illness prediction prototype based on a person's risk feature data to provide an early prediction for diabetes with Fuzzy Entropy random vectors that regulate the development of each tree in the Random Forest. The proposed prototype consists of data imputation, data sampling, feature selection, and various techniques to predict the disease, such as Fuzzy Entropy, Synthetic Minority Oversampling Technique (SMOTE), Convolutional Neural Network (CNN) with Stochastic Gradient Descent with Momentum (SGDM), Support Vector Machines (SVM), Classification and Regression Tree (CART), K-Nearest Neighbor (KNN), and Naïve Bayes (NB). This study uses the existing Pima Indian Diabetes (PID) dataset for diabetic disease prediction. The predictions' true/false positive/negative rate is investigated using the confusion matrix and the receiver operating characteristic area under the curve (ROCAUC). Findings on a PID dataset are compared with machine learning algorithms revealing that the proposed Random Forest Fuzzy Entropy (RFFE) is a valuable approach for diabetes prediction, with an accuracy of 98 percent.

Abstract Pomegranate crops are prone to wilt complex disease, which is known to severely hamper the crop yield. There have been limited studies that have explored bacteria–plant–host associations in wilt complex disease affecting pomegranate crops. In the present study, wilt infected rhizosphere soil samples (ISI, ASI) in pomegranate were studied in comparison to a healthy control (HSC). The 16S metagenomics sequencing approach using the MinION platform was employed for screening of bacterial communities and predictive functional pathways. Altered physicochemical properties in the soil samples were recorded showing a comparatively acidic pH in the ISI (6.35) and ASI (6.63) soil samples to the HSC soil (7.66), along with higher electrical conductivity in the ISI (139.5 µS/cm), ASI soil (180 µS/cm), HSC soil sample (123.33 µS/cm). While concentration of micronutrients such as Cl and B were significantly higher in the ISI and ASI soil as compared to the HSC, Cu and Zn were significantly higher in the ASI soil. The effectiveness and accuracy of 16S metagenomics studies in identifying beneficial and pathogenic bacterial communities in multi-pathogen–host systems depend on the completeness and consistency of the available 16S rRNA sequence repositories. Enhancing these repositories could significantly improve the exploratory potential of such studies. Thus, multiple 16S rRNA data repositories (RDP, GTDB, EzBioCloud, SILVA, and GreenGenes) were benchmarked, and the findings indicated that SILVA yields the most reliable matches. Consequently, SILVA was chosen for further analysis at the species level. Relative abundance estimates of bacterial species showed variations of growth promoting bacteria, namely, Staphylococcus epidermidis, Bacillus subtilis, Bacillus megatarium, Pseudomonas aeruginosa, Pseudomonas putida, Pseudomonas stutzeri and Micrococcus luteus. Functional profiling predictions employing PICRUSt2 revealed a number of enriched pathways such as transporter protein families involved in signalling and cellular processes, iron complex transport system substrate binding protein, peptidoglycan biosynthesis II (staphylococci) and TCA cycle VII (acetate-producers). In line with past reports, results suggest that an acidic pH along with the bioavailability of micronutrients such as Fe and Mn could be facilitating the prevalence and virulence of Fusarium oxysporum, a known causative pathogen, against the host and beneficial bacterial communities. This study identifies bacterial communities taking into account the physicochemical and other abiotic soil parameters in wilt-affected pomegranate crops. The insights obtained could be instrumental in developing effective management strategies to enhance crop yield and mitigate the impact of wilt complex disease on pomegranate crops.

Abstract Since its discovery in 2012, CRISPR Cas9 has been tried as a direct treatment approach to correct the causative gene mutation and establish animal models in neurodegenerative disorders. Since no strategy developed until now could completely cure Parkinson's disease (PD), neuroscientists aspire to use gene editing technology, especially CRISPR/Cas9, to induce a permanent correction in genetic PD patients expressing mutated genes. Over the years, our understanding of stem cell biology has improved. Scientists have developed personalized cell therapy using CRISPR/Cas9 to edit embryonic and patient-derived stem cells ex-vivo. This review details the importance of CRISPR/Cas9-based stem cell therapy in Parkinson's disease in developing PD disease models and developing therapeutic strategies after elucidating the possible pathophysiological mechanisms. Graphical Abstract

Abstract Background Pregnant women at high risk for developing a hypertensive disorder of pregnancy require frequent antenatal assessments, especially of their blood pressure. This expends significant resources for both the patient and healthcare system. An alternative to in-clinic assessments is a remote blood pressure monitoring strategy, in which patients self-record their blood pressure at home using a validated blood pressure machine. This has the potential to be cost-effective, increase patient satisfaction, and reduce outpatient visits, and has had widespread uptake recently given the increased need for remote care during the ongoing COVID-19 pandemic. However robust evidence supporting this approach over a traditional face-to-face approach is lacking, and the impact on maternal and foetal outcomes has not yet been reported. Thus, there is an urgent need to assess the efficacy of remote monitoring in pregnant women at high risk of developing a hypertensive disorder of pregnancy. Methods The REMOTE CONTROL trial is a pragmatic, unblinded, randomised controlled trial, which aims to compare remote blood pressure monitoring in high-risk pregnant women with conventional face-to-face clinic monitoring, in a 1:1 allocation ratio. The study will recruit patients across 3 metropolitan Australian teaching hospitals and will evaluate the safety, cost-effectiveness, impact on healthcare utilisation and end-user satisfaction of remote blood pressure monitoring. Discussion Remote blood pressure monitoring is garnering interest worldwide and has been increasingly implemented following the COVID-19 pandemic. However, robust data regarding its safety for maternofoetal outcomes is lacking. The REMOTE CONTROL trial is amongst the first randomised controlled trials currently underway, powered to evaluate maternal and foetal outcomes. If proven to be as safe as conventional clinic monitoring, major potential benefits include reducing clinic visits, waiting times, travel costs, and improving delivery of care to vulnerable populations in rural and remote communities. Trial registration The trial has been prospectively registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12620001049965p, on October 11th, 2020).

Abstract Background Physiotherapists and physiotherapy undergraduates have direct contact with patients which make them transmitters of infections if they do not follow standard precautions. Hence, the purpose of this study was to assess the knowledge of nosocomial infections, standard precautions, and source of information among physiotherapy undergraduates in Sri Lanka. Methods An observational Google based survey study was conducted among 294 physiotherapy undergraduates, of which there were 103 in University of Peradeniya, 103 in University of Colombo, and 88 in General Sir John Kotelawala Defence University. The Infection Control Standardized Questionnaire comprising three domains: knowledge of nosocomial infections, standard precautions and hand hygiene was used for data collection along with a self-constructed data sheet for socio-demographic information and source of information. Results Participants achieved mean knowledge of 67.1 ± 16.8, 84.4 ± 14.7 and 66.4 ± 15.4 for nosocomial infections, standard precautions, and hand hygiene respectively. Of the total sample, 225 (76.5%) achieved adequate level of total knowledge. Eighty-three of them (28.3%) equally mentioned, formal teaching at faculty and informal sources as the most important source of knowledge. There was no significant impact of university and the duration of clinical exposure on knowledge of nosocomial infections, standard precautions, hand hygiene and total knowledge. The study year has a significant impact on standard precautions (P = 0.004) and total knowledge (P = 0.035) and final years had highest knowledge compared to the other study years. Conclusion Knowledge of nosocomial infections and infection control measures were satisfactory among the physiotherapy undergraduates in Sri Lanka. Further developments of formal sources of information about nosocomial infections are recommended.

Abstract Background Finegoldia magna (formerly known as Peptococcus magnus or Peptostreptococcus magnus) belonging to phylum Firmicutes, class Clostridia and genus Finegoldia, is the only species known to cause infections in human beings. Amongst Gram positive anaerobic cocci, F. magna is known to be the most virulent with a high pathogenic potential. Significant upsurge in antimicrobial resistance among anaerobes has been documented by various studies. F. magna is known to be susceptible to most of the anti-anaerobic antimicrobials, however, multidrug resistant strains are being reported in literature. The present study was undertaken to highlight the role of F. magna in clinical infections and to analyze their antimicrobial susceptibility patterns. Methods The present study was conducted in a tertiary care teaching hospital in Southern India. 42 clinical isolates of F. magna recovered from diverse clinical infections between January 2011 to December 2015 were studied. These isolates were subjected to antimicrobial susceptibility testing against metronidazole, clindamycin, cefoxitin, penicillin, chloramphenicol and linezolid. Results Among the 42 isolates studied, majority of them were revived from diabetic foot infections (31%) followed by necrotizing fasciitis (19%) and deep-seated abscesses (19%). All the F. magna isolates showed good in-vitro activity against metronidazole, cefoxitin, linezolid and chloramphenicol. Clindamycin and penicillin resistance were observed against 9.5% and 2.4% of the isolates respectively. However, β-lactamase activity was not detected. Conclusion The antimicrobial resistance among anaerobes varies from pathogen to pathogen and region to region. Hence, a deep understanding of resistance pattern is necessary for better management of clinical infections.

Abstract Although the SARS-CoV-2 Omicron variant (BA.1) spread rapidly across the world and effectively evaded immune responses, its viral fitness in cell and animal models was reduced. The precise nature of this attenuation remains unknown as generating replication-competent viral genomes is challenging because of the length of the viral genome (~30 kb). Here, we present a plasmid-based viral genome assembly and rescue strategy (pGLUE) that constructs complete infectious viruses or noninfectious subgenomic replicons in a single ligation reaction with >80% efficiency. Fully sequenced replicons and infectious viral stocks can be generated in 1 and 3 weeks, respectively. By testing a series of naturally occurring viruses as well as Delta-Omicron chimeric replicons, we show that Omicron nonstructural protein 6 harbors critical attenuating mutations, which dampen viral RNA replication and reduce lipid droplet consumption. Thus, pGLUE overcomes remaining barriers to broadly study SARS-CoV-2 replication and reveals deficits in nonstructural protein function underlying Omicron attenuation.

Introduction: Mast cells are heterogenous group of immune cells involved in multiple biological events they play vital role in various inflammatory and immunological reactions, linking humoral and cell mediated phases of processes. Aim and Objective: In this study we have tried to compare the density and distribution of mast cells in various endometrial lesions. Material and Methods: A prospective study with 101 cases of post hysterectomy were studied. Hysterectomy specimens were cut open from anterior wall, incorporated endometrium and myometrium, fixed in 10% formalin after routine processing, embedded in paraffin, 5 micron thickness section taken and stained with Haematoxillin-Eosin, and toludine blue to visualize mast cells. Results: It showed a significant p value which was < 0.001. Conclusion: Mast cell profile may be an additional diagnostic/prognostic tool in different endometrial lesions.

The availability of high-fidelity animal models for oncology research has grown enormously in recent years, enabling preclinical studies relevant to prevention, diagnosis, and treatment of cancer to be undertaken. This has led to increased opportunities to conduct co-clinical trials, which are studies on patients that are carried out parallel to or sequentially with animal models of cancer that mirror the biology of the patients’ tumors. Patient-derived xenografts (PDX) and genetically engineered mouse models (GEMM) are considered to be the models that best represent human disease and have high translational value. Notably, one element of co-clinical trials that still needs significant optimization is quantitative imaging. The National Cancer Institute has organized a Co-Clinical Imaging Resource Program (CIRP) network to establish best practices for co-clinical imaging and to optimize translational quantitative imaging methodologies. This overview describes the ten co-clinical trials of investigators from eleven institutions who are currently supported by the CIRP initiative and are members of the Animal Models and Co-clinical Trials (AMCT) Working Group. Each team describes their corresponding clinical trial, type of cancer targeted, rationale for choice of animal models, therapy, and imaging modalities. The strengths and weaknesses of the co-clinical trial design and the challenges encountered are considered. The rich research resources generated by the members of the AMCT Working Group will benefit the broad research community and improve the quality and translational impact of imaging in co-clinical trials.

Metabolite-specific echo-planar imaging (EPI) sequences with spectral–spatial (spsp) excitation are commonly used in clinical hyperpolarized [1-13C]pyruvate studies because of their speed, efficiency, and flexibility. In contrast, preclinical systems typically rely on slower spectroscopic methods, such as chemical shift imaging (CSI). In this study, a 2D spspEPI sequence was developed for use on a preclinical 3T Bruker system and tested on in vivo mice experiments with patient-derived xenograft renal cell carcinoma (RCC) or prostate cancer tissues implanted in the kidney or liver. Compared to spspEPI sequences, CSI were found to have a broader point spread function via simulations and exhibited signal bleeding between vasculature and tumors in vivo. Parameters for the spspEPI sequence were optimized using simulations and verified with in vivo data. The expected lactate SNR and pharmacokinetic modeling accuracy increased with lower pyruvate flip angles (less than 15°), intermediate lactate flip angles (25° to 40°), and temporal resolution of 3 s. Overall SNR was also higher with coarser spatial resolution (4 mm isotropic vs. 2 mm isotropic). Pharmacokinetic modelling used to fit kPL maps showed results consistent with the previous literature and across different sequences and tumor xenografts. This work describes and justifies the pulse design and parameter choices for preclinical spspEPI hyperpolarized 13C-pyruvate studies and shows superior image quality to CSI.

Providing method descriptions that are more detailed than currently available in typical peer reviewed journals has been identified as an actionable area for improvement. In the biochemical and cell biology space, this need has been met through the creation of new journals focused on detailed protocols and materials sourcing. However, this format is not well suited for capturing instrument validation, detailed imaging protocols, and extensive statistical analysis. Furthermore, the need for additional information must be counterbalanced by the additional time burden placed upon researchers who may be already overtasked. To address these competing issues, this white paper describes protocol templates for positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance imaging (MRI) that can be leveraged by the broad community of quantitative imaging experts to write and self-publish protocols in protocols.io. Similar to the Structured Transparent Accessible Reproducible (STAR) or Journal of Visualized Experiments (JoVE) articles, authors are encouraged to publish peer reviewed papers and then to submit more detailed experimental protocols using this template to the online resource. Such protocols should be easy to use, readily accessible, readily searchable, considered open access, enable community feedback, editable, and citable by the author.

Abstract Background Many children and adolescents with Type 1 Diabetes Mellitus (T1DM) don’t meet the recommended levels of physical activity. Healthcare professionals (HCPs) have a key role in supporting and encouraging children and adolescents with T1DM to be physically active. This study aims to understand the perspectives of HCPs in relation to supporting physical activity and implementing guidelines relating to physical activity. Methods An online mixed methods survey was circulated to HCPs in pediatric diabetes units in England and Wales. Participants were asked about how they support physical activity in their clinic and their perceptions of barriers/enablers of providing physical activity support to children and adolescents with T1DM. Quantitative data were analysed descriptively. An deductive thematic approach was applied to the free text responses using the Capability Opportunity Motivation model of Behaviour (COM-B) as a framework. Results Responses were received from 114 individuals at 77 different pediatric diabetes units (45% of pediatric diabetes units in England and Wales). HCPs surveyed felt that the promotion of physical activity is important (90%) and advised patients to increase levels of physical activity (88%). 19% of the respondents felt they did not have sufficient knowledge to provide support. HCPs reported limited knowledge and confidence, time and resources as barriers to providing support. They also felt the current guidance was too complicated with few practical solutions. Conclusion Pediatric HCPs need training and support to be able to encourage and support children and adolescents with T1D to be a physical activity. In addition, resources that provide simple and practical advice to manage glucose around exercise are needed.

Currently, no clinical methods reliably predict the development of castration-resistant prostate cancer (CRPC) that occurs almost universally in men undergoing androgen deprivation therapy. Hyperpolarized (HP) 13C magnetic resonance imaging (MRI) could potentially detect the incipient emergence of CRPC based on early metabolic changes. To characterize metabolic shifts occurring upon the transition from androgen-dependent to castration-resistant prostate cancer (PCa), the metabolism of [U-13C]glucose and [U-13C]glutamine was analyzed by nuclear magnetic resonance spectroscopy. Comparison of steady-state metabolite concentrations and fractional enrichment in androgen-dependent LNCaP cells and transgenic adenocarcinoma of the murine prostate (TRAMP) murine tumors versus castration-resistant PC-3 cells and treatment-driven CRPC TRAMP tumors demonstrated that CRPC was associated with upregulation of glycolysis, tricarboxylic acid metabolism of pyruvate; and glutamine, glutaminolysis, and glutathione synthesis. These findings were supported by 13C isotopomer modeling showing increased flux through pyruvate dehydrogenase (PDH) and anaplerosis; enzymatic assays showing increased lactate dehydrogenase, PDH and glutaminase activity; and oxygen consumption measurements demonstrating increased dependence on anaplerotic fuel sources for mitochondrial respiration in CRPC. Consistent with ex vivo metabolomic studies, HP [1-13C]pyruvate distinguished androgen-dependent PCa from CRPC in cell and tumor models based on significantly increased HP [1-13C]lactate.

The exact mechanism of coronavirus replication and transcription is not fully understood; however, a hallmark of coronavirus transcription is the generation of negative-sense RNA intermediates that serve as the templates for the synthesis of positive-sense genomic RNA (gRNA) and an array of subgenomic mRNAs (sgRNAs) encompassing sequences arising from discontinuous transcription. Existing PCR-based diagnostic assays for SAR-CoV-2 are qualitative or semi-quantitative and do not provide the resolution needed to assess the complex transcription dynamics of SARS-CoV-2 over the course of infection. We developed and validated a novel panel of specially designed SARS-CoV-2 ddPCR-based assays to map the viral transcription profile. Application of these assays to clinically relevant samples will enhance our understanding of SARS-CoV-2 replication and transcription and may also inform the development of improved diagnostic tools and therapeutics. Highlights We developed a novel panel of 7 quantitative RT-ddPCRs assays for SARS-Cov-2 Our panel targets nongenic and genic regions in genomic and subgenomic RNAs All assays detect 1-10 copies and are linear over 3-4 orders of magnitude All assays correlated with the clinical Abbott SARS-CoV-2 Viral Load Assay Clinical samples showed higher copy numbers for targets at the 3’ end of the genome

The December 2019 outbreak of a novel respiratory virus, SARS-CoV-2, has become an ongoing global pandemic due in part to the challenge of identifying symptomatic, asymptomatic, and pre-symptomatic carriers of the virus. CRISPR diagnostics can augment gold-standard PCR-based testing if they can be made rapid, portable, and accurate. Here, we report the development of an amplification-free CRISPR-Cas13a assay for direct detection of SARS-CoV-2 from nasal swab RNA that can be read with a mobile phone microscope. The assay achieved ∼100 copies/μL sensitivity in under 30 min of measurement time and accurately detected pre-extracted RNA from a set of positive clinical samples in under 5 min. We combined crRNAs targeting SARS-CoV-2 RNA to improve sensitivity and specificity and directly quantified viral load using enzyme kinetics. Integrated with a reader device based on a mobile phone, this assay has the potential to enable rapid, low-cost, point-of-care screening for SARS-CoV-2.

ScaleLIT encountered unique challenges surrounding equity and inclusion due to changes brought about by COVID-19. Our position as a coalition that supports a variety of local, state, and national initiatives makes us a key player in the integration of leading with learning, not with technology; the implementation of Navigators and One Stop Operator at Cook County American Job Centers; and organizing virtual advocacy efforts to gain more involvement from community members and elected officials.

Purpose: The paper aims at examining the employability skills relevant in the unprecedented times of turbulence in businesses due to COVID-19 in the Indian context. Design/methodology/approach: The study examined the recent skills model through an extensive literature review. Exploratory factor analysis (EFA) is conducted to identify the employability skills perceived as important by multiple stakeholders. ANOVA was applied to examine the differences in perceived importance attached to these dimensions by the three stakeholders. Findings: The ten-factorial solution was extracted based on the results of EFA The findings offer a fresh perspective on digital competencies perceived as most important to ensure successful long-term employability, followed by business fundamentals and behavioral skills. Research limitations/implications: The study has been able to map perceptions of employers, faculty and students based in Delhi-NCR regarding essential employability skills. It would be worthwhile to validate the proposed employability skills framework across different geographical sections of India and ascertain if the perceptions vary in the employment sector and employer size. Practical implications: Although the study has put forth practical employability skills, there is a need for convergence between the business stakeholders and Higher Education Institutes (HEIs) to develop a broad skill-base for the fresh graduates. The study will prepare them for the volatile business environment. Originality/value: Many previous studies have lacked the employability skill framework in the Indian context from the multiple stakeholders' perspective. The HEIs can rethink their current employability, including the most prominent skills required in succeeding in a technology-enabled business environment transformed by the pandemic.

General internal medicine (GIM) fellowships play an important role in the development of physician scientists and clinical educators, as well as leaders in academic medicine. Nevertheless, the challenges of developing another novel aspect to one's career, along with balancing coursework, research productivity, clinical duties, and personal life during fellowship, can be overwhelming. Similarly, successfully securing a job at the end of fellowship can be a daunting process. In this article, we discuss the foundational tenets and themes of the GIM fellowship. These themes include (1) finding your purpose and passion, with a focus on selecting research coursework and developing an area of study; (2) the role and importance of mentorship, including the various kinds of mentorship that fellows require (traditional and peer mentorship, sponsors, and coaches), as well as how to be an effective mentee; (3) securing research funding; (4) landing a job; (5) and protecting time to meet personal goals. There is an increased need for a vibrant, diverse, and successful generation of general internal medicine researchers to advance our understanding of complex issues in clinical medicine and healthcare delivery and to inform health policy. It is our hope that this piece helps to support that mission.

Lessons learnedAndrogen receptor as assessed by immunohistochemistry is expressed in a high proportion of patients with hepatocellular carcinoma (HCC). Enzalutamide at 160 mg orally daily is safe and tolerable in patients with advanced HCC but has no single-agent antitumor activity. Enzalutamide, a CYP3A4 inducer, at a standard dose of 160 mg reduces the exposure of sorafenib, a CYP3A4 substrate. Enzalutamide and sorafenib is safe and tolerable in patients with advanced HCC, but the addition of enzalutamide to sorafenib did not enhance the antitumor activity of sorafenib.BackgroundAndrogen receptor (AR) interference is deleterious to hepatocellular carcinoma (HCC) in preclinical models.MethodsThis is a multicenter, phase Ib study of enzalutamide ± sorafenib in patients with advanced HCC. In part 1, a 3 + 3 dose de-escalation design with expansion established the recommended phase II dose (RP2D) of enzalutamide in patients in whom sorafenib treatment had failed. In part 2, a 3 + 3 dose escalation with expansion established the safety of enzalutamide with sorafenib in treatment-naive patients with HCC. Secondary objectives included objective response rate (ORR), progression-free survival (PFS), overall survival (OS), pharmacokinetics (PK), and determination of AR expression by immunohistochemistry. A 7-day run-in with sorafenib alone in part 2 allowed assessment of the impact of enzalutamide on sorafenib pharmacokinetics.ResultsIn part 1, 16 patients received enzalutamide 160 mg daily. No dose-limiting toxicity (DLT) occurred; 1 patient required dose reduction. Responses were not observed; median PFS and OS were 1.8 (95% confidence interval [CI]: 1.6-3.6) and 7 (95% CI: 3.6 to not reached [NR]) months, respectively. In part 2, patients received sorafenib 400 mg daily (4) or twice a day (8) both with enzalutamide at the recommended phase II dose-no DLTs were observed. ORR was 10% (95% CI: 0.3-44.5), and median PFS and OS were 2.9 (95% CI: 1.6 to NR) and 6.7 (95% CI: 4.6 to NR) months, respectively. Enzalutamide reduced sorafenib exposure by 60%. Tumor AR expression did not associate with outcome.ConclusionEnzalutamide is ineffective in HCC; further development is not supported by this study.

Common cooking methods were used to prepare basmati rice products, including boiling 1 (boiling by absorption), boiling 2 (boiling in extra amount of water), frying, and pressure cooking. The cooked rice was held at various temperatures and times as follows: it was made fresh (T1), kept at room temperature (20–22 °C) for 24 h (T2), kept at 4 °C for 24 h (T3), and then reheated after being kept at 4 °C for 24 h (T4). The proximate composition, total dietary fibre, resistant starch (RS), and in vitro starch digestion rate of products were examined. The effect of RS on blood glucose and lipid profiles was measured in humans and rats, including a histopathological study of the liver and pancreas in rats. The basmati rice that was prepared via boiling 1 and stored with T3 was found to be low in glycaemic index and glycaemic load, and to be high in resistant starch. Similarly, in rats, the blood glucose level, cholesterol, triglycerides, and LDL were reduced by about 29.7%, 37.9%, 31.3%, and 30.5%, respectively, after the consumption of basmati rice that was prepared via boiling 1 and stored with T3. Awareness should be raised among people about the health benefits of resistant starch consumption and the right way of cooking.

Background: Neonate is essential time for child to grow. Worldwide, Neonatal mortality are estimated to be about 3 million due to insufficient care. In 2021, 2.3 million neonates have died in first four weeks of life, roughly 6400 neonatal deaths per day. Lack of knowledge in new born care, inappropriate new born care practices are some of the contributors to neonatal mortality. Newborn care practice interventions can prevent neonatal deaths. Understanding the community and traditional newborn care practices is necessary to implement effective programme for promotion of newborns health. Hence present study was done to describe selected newborn care practices in urban slums of Kurnool. Objectives: To assess Newborn-Care Practices and to determine the relationship between Newborn-Care Practices and selected socio-demographic variables. Methodology: A Community-based, Cross-sectional study was done among 220mothers who were residing in urban slums of Kurnool City, Data were collected between October 2023 to November 2023 using Semi-structured questionnaire by Simple Random sampling technique. IEC permission was obtained. Written informed consent was obtained from participants. Data were analyzed using SPSS-Version23. Results: Mothers who were practicing delayed-bathing were observed in the age group 18-24 years 135(61.36%)followed by 25-30 years 60(27.2%),the difference was statistically significant(x2=9.84)(p=0.043),Safe cord care practices were observed more among 18-24 years132(60%),it was found to be statistically significant(x2=23.5)(p=

Background and Objectives: Coronavirus disease 2019 (COVID-19) caused several cardiovascular complications, including acute myocardial infarction (AMI), in infected patients. This study aims to understand the overall trends of AMI among COVID-19 patients during the first two years of the pandemic and the disparities and outcomes between the first and second years. Materials and Methods: The retrospective analysis was conducted via the 2020 and 2021 National Inpatient Sample (NIS) database for hospitalizations between April 2020 and December 2021 being analyzed for adults with a primary diagnosis of COVID-19 who experienced events of AMI. A comparison of month-to-month events of AMI and mortality of AMI patients with concomitant COVID-19 was made alongside their respective patient characteristics. Results: Out of 2,541,992 COVID-19 hospitalized patients, 3.55% experienced AMI. The highest rate of AMI was in December 2021 (4.35%). No statistical differences in trends of AMI mortality were noted over the 21 months. AMI cases in 2021 had higher odds of undergoing PCI (aOR 1.627, p < 0.01). They experienced higher risks of acute kidney injury (aOR 1.078, p < 0.01), acute ischemic stroke (aOR 1.215, p < 0.01), cardiac arrest (aOR 1.106, p < 0.01), need for mechanical ventilation (aOR 1.133, p < 0.01), and all-cause mortality (aOR 1.032, 95% CI 1.001–1.064, p = 0.043). Conclusions: The incidence of AMI among COVID-19 patients fluctuated over the 21 months of this study, with a peak in December 2021. COVID-19 patients reporting AMI in 2021 experienced higher overall odds of multiple complications, which could relate to the exhaustive burden of the pandemic in 2021 on healthcare, the changing impact of the virus variants, and the hesitancy of infected patients to seek care.