Short turnaround time of seven to nine hours from sample collection until informed decision for sepsis treatment using nanopore sequencing.

Bloodstream infections (BSIs) and sepsis are major health problems, annually claiming millions of lives. Traditional blood culture techniques, employed to identify sepsis-causing pathogens and assess antibiotic susceptibility, usually take 2-4 days. Early and accurate antibiotic prescription is vital in sepsis to mitigate mortality and antibiotic resistance. This study aimed to reduce the wait time for sepsis diagnosis by employing shorter blood culture incubation times for BD BACTEC™ bottles using standard laboratory incubators, followed by real-time nanopore sequencing and data analysis. The method was tested on nine blood samples spiked with clinical isolates from the six most prevalent sepsis-causing pathogens. The results showed that pathogen identification was possible at as low as 102-104 CFU/mL, achieved after just 2 h of incubation and within 40 min of nanopore sequencing. Moreover, all the antimicrobial resistance genes were identified at 103-107 CFU/mL, achieved after incubation for 5 h and only 10 min to 3 h of sequencing. Therefore, the total turnaround time from sample collection to the information required for an informed decision on the right antibiotic treatment was between 7 and 9 h. These results hold significant promise for better clinical management of sepsis compared with current culture-based methods.

Trichotillomania, Trichophagia and Trichobezoar in a Male Paediatric Patient: A Case Report and Literature Review.

INTRODUCTION AND IMPORTANCE: Trichotillomania and tricophagia, characterized by compulsive hair-pulling and subsequent ingestion which results in a compact mass of hair called trichobezoar. It represents an uncommon psychiatric disorder, especially in young children. CASE PRESENTATION: This case report describes a distinctive and rare occurrence of trichotillomania, tricophagia and trichobezoar in a 11-year-old male child. Concerns raised by the parents regarding noticeable hair loss, who initially presented to medical outdoor patient with complaints of abdominal pain on and off from the last one year. He had a history of pica and weight-loss. He was then diagnosed with a gastric trichobezoar for which he was operated upon and a giant trichobezoar was retrieved from his stomach. Post-operatively patient remained admitted in ward and was discharged home on fifth post-operative day and sent for psychiatry evaluation. CLINICAL DISCUSSION: Trichotillomania and tricophagia often have roots in psychosocial stressors, anxiety, and depression. Children may engage in hair-pulling as a coping mechanism, especially in response to familial or environmental stressors. The literature emphasizes the importance of understanding the psychosocial context to tailor interventions effectively. CONCLUSION: Trichotillomania and tricophagia is very rare in paediatric population and if presents a multidisciplinary team comprising of a paediatrition, paediatric surgeon and paediatric psychiatrist should be involved and if diagnosed with a gastric trichobezoar should be removed surgically in order to prevent complications.

Beyond the silence: A comprehensive exploration of long non-coding RNAs as genetic whispers and their essential regulatory functions in cardiovascular disorders.

Long non-coding RNAs (lncRNAs) are RNA molecules that regulate gene expression at several levels, including transcriptional, post-transcriptional, and translational. They have a length of more than 200 nucleotides and cannot code. Many human diseases have been linked to aberrant lncRNA expression, highlighting the need for a better knowledge of disease etiology to drive improvements in diagnostic, prognostic, and therapeutic methods. Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide. LncRNAs play an essential role in the complex process of heart formation, and their abnormalities have been associated with several CVDs. This Review article looks at the roles and relationships of long non-coding RNAs (lncRNAs) in a wide range of CVDs, such as heart failure, myocardial infarction, atherosclerosis, and cardiac hypertrophy. In addition, the review delves into the possible uses of lncRNAs in diagnostics, prognosis, and clinical treatments of cardiovascular diseases. Additionally, it considers the field's future prospects while examining how lncRNAs might be altered and its clinical applications.

A uretheral stone causing urinary obstruction in a paediatric patient.

Urinary retention in pediatric patients is an uncommon presentation, particularly when attributed to urethral stones. We present the case of an 8 year old child who experienced acute urinary retention due to a urethral stone, an infrequent occurrence in this age group. Initial assessment revealed signs of obstructive voiding, prompting further investigation. Imaging studies confirmed the presence of a urethral stone causing complete obstruction. Management involved a multidisciplinary approach, incorporating surgical intervention. This case report underlines the need for awareness about the rare occurrence of urethral stones in pediatric age group which must be kept in mind while treating children.

Cardiovascular diseases crossroads: cGAS-STING signaling and disease progression.

It is now widely accepted that inflammation is critical in cardiovascular diseases (CVD). Here, studies are being conducted on how cyclic GMP-AMP synthase (cGAS), a component of innate immunity's DNA-sensing machinery, communicates with the STING receptor, which is involved in activating the immune system's antiviral response. Significantly, a growing body of research in recent years highlights the strong activation of the cGAS-STING signalling pathways in several cardiovascular diseases, such as myocardial infarction, heart failure, and myocarditis. This developing collection of research emphasises these pathways' crucial role in initiating and advancing cardiovascular disease. In this extensive narrative, we explore the role of the cGAS-STING pathway in the development of CVD. We elaborate on the basic mechanisms involved in the onset and progression of CVD. This review explores the most recent developments in the recognition and characterization of cGAS-STING pathway. Additionally, it considers the field's future prospects while examining how cGAS-STING pathway might be altered and its clinical applications for cardiovascular diseases.

Cardiovascular challenges in the era of antiretroviral therapy for AIDS/ HIV: A comprehensive review of research advancements, pathophysiological insights, and future directions.

Cardiovascular disease, particularly coronary heart disease, is becoming more common among those living with HIV. Individuals with HIV face an increased susceptibility to myocardial infarction, also known as a heart attack, as compared to the general population in developed countries. This heightened risk can be attributed mainly to the presence of effective antiretroviral drugs and the resulting longer lifespan. Some cardiac issues linked to non-antiretroviral medications, including myocarditis, endocarditis, cardiomyopathy with dilation, pulmonary hypertension, and oedema of the heart, may affect those not undergoing highly active antiretroviral therapy (ART). Impaired immune function and systemic inflammation are significant contributors to this phenomenon after initiating highly aggressive antiretroviral treatment ART. It is becoming more challenging to determine the best course of treatment for HIV-associated cardiomyopathy due to new research suggesting that protease inhibitors might have a negative impact on the development of HF. Currently, the primary focus of research on ART medications is centered on the cardiovascular adverse effects of nucleoside reverse transcriptase inhibitors and protease inhibitors. This review paper thoroughly evaluates the advancements achieved in cardiovascular disease research and explores the potential implications for prospects. Additionally, it considers the field's future prospects while examining how ART might be altered and its clinical applications.

SERS Nanowire Chip and Machine Learning-Enabled Classification of Wild-Type and Antibiotic-Resistant Bacteria at Species and Strain Levels.

Antimicrobial resistance (AMR) is a major health threat worldwide and the culture-based bacterial detection methods are slow. Surface-enhanced Raman spectroscopy (SERS) can be used to identify target analytes in real time with sensitivity down to the single-molecule level, providing a promising solution for the culture-free bacterial detection. We report the fabrication of SERS substrates having tightly packed silver (Ag) nanoparticles loaded onto long silicon nanowires (Si NWs) grown by the metal-assisted chemical etching (MACE) method for the detection of bacteria. The optimized SERS chips exhibited sensitivity down to 10-12 M concentration of R6G molecules and detected reproducible Raman spectra of bacteria down to a concentration of 100 colony forming units (CFU)/mL, which is a thousand times lower than the clinical threshold of bacterial infections like UTI (105 CFU/mL). A Siamese neural network model was used to classify SERS spectra from bacteria specimens. The trained model identified 12 different bacterial species, including those which are causative agents for tuberculosis and urinary tract infection (UTI). Next, the SERS chips and another Siamese neural network model were used to differentiate AMR strains from susceptible strains of Escherichia coli (E. coli). The enhancement offered by SERS chip-enabled acquisitions of Raman spectra of bacteria directly in the synthetic urine by spiking the sample with only 103 CFU/mL E. coli. Thus, the present study lays the ground for the identification and quantification of bacteria on SERS chips, thereby offering a potential future use for rapid, reproducible, label-free, and low limit detection of clinical pathogens.

Increased growth temperature and vitamin B12 supplementation reduces the lag time for rapid pathogen identification in BHI agar and blood cultures.

Background: The rapid diagnostics of pathogens is essential to prescribe appropriate and early antibiotic therapy. The current methods for pathogen detection require the bacteria to grow in a culture medium, which is time-consuming. This increases the mortality rate and the global burden of antimicrobial resistance. Culture-free detection methods are still under development and are not used in the clinical routine. Therefore decreasing the culture time for accurate detection of infection and resistance is vital for diagnosis. Methods: In this study, we wanted to investigate easy-to-implement factors (in a minimal laboratory set-up), including inoculum size, incubation temperature, and additional supplementation ( e.g., vitamin B12 and trace metals), that can significantly reduce the lag time (t lag). These factors were arranged in simple two-level factorial designs using Gram-positive ( Escherichia coli and Pseudomonas aeruginosa) and Gram-negative ( Staphylococcus aureus and Bacillus subtilis) bacteria, including clinical isolates with known antimicrobial resistance profiles. Blood samples spiked with a clinical isolate of E. coli CCUG17620 were also tested to see the effect of elevated incubation temperature on bacterial growth in blood cultures. Results: We observed that increased incubation temperature (42°C) along with vitamin B12 supplementation significantly reduced the t lag (10 - 115 minutes or 4% - 49%) in pure clinical isolates and blood samples spiked with E. coli CCUG17620. In the case of the blood sample, PCR results also detected bacterial DNA after only 3h of incubation and at three times the CFU/mL. Conclusions: Enrichment of bacterial culture media with growth supplements such as vitamin B12 and increased incubation temperature can be a cheap and rapid method for the early detection of pathogens. This is a proof-of-concept study restricted to a few bacterial strains and growth conditions. In the future, the effect of other growth conditions and difficult-to-culture bacteria should be explored to shorten the lag phase.

Highly sensitive quantitative phase microscopy and deep learning aided with whole genome sequencing for rapid detection of infection and antimicrobial resistance.

Current state-of-the-art infection and antimicrobial resistance (AMR) diagnostics are based on culture-based methods with a detection time of 48-96 h. Therefore, it is essential to develop novel methods that can do real-time diagnoses. Here, we demonstrate that the complimentary use of label-free optical assay with whole-genome sequencing (WGS) can enable rapid diagnosis of infection and AMR. Our assay is based on microscopy methods exploiting label-free, highly sensitive quantitative phase microscopy (QPM) followed by deep convolutional neural networks-based classification. The workflow was benchmarked on 21 clinical isolates from four WHO priority pathogens that were antibiotic susceptibility tested, and their AMR profile was determined by WGS. The proposed optical assay was in good agreement with the WGS characterization. Accurate classification based on the gram staining (100% recall for gram-negative and 83.4% for gram-positive), species (98.6%), and resistant/susceptible type (96.4%), as well as at the individual strain level (100% sensitivity in predicting 19 out of the 21 strains, with an overall accuracy of 95.45%). The results from this initial proof-of-concept study demonstrate the potential of the QPM assay as a rapid and first-stage tool for species, strain-level classification, and the presence or absence of AMR, which WGS can follow up for confirmation. Overall, a combined workflow with QPM and WGS complemented with deep learning data analyses could, in the future, be transformative for detecting and identifying pathogens and characterization of the AMR profile and antibiotic susceptibility.

Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics-Current State and Whole Genome Sequencing Implementation Perspectives.

Antimicrobial resistance (AMR), defined as the ability of microorganisms to withstand antimicrobial treatment, is responsible for millions of deaths annually. The rapid spread of AMR across continents warrants systematic changes in healthcare routines and protocols. One of the fundamental issues with AMR spread is the lack of rapid diagnostic tools for pathogen identification and AMR detection. Resistance profile identification often depends on pathogen culturing and thus may last up to several days. This contributes to the misuse of antibiotics for viral infection, the use of inappropriate antibiotics, the overuse of broad-spectrum antibiotics, or delayed infection treatment. Current DNA sequencing technologies offer the potential to develop rapid infection and AMR diagnostic tools that can provide information in a few hours rather than days. However, these techniques commonly require advanced bioinformatics knowledge and, at present, are not suited for routine lab use. In this review, we give an overview of the AMR burden on healthcare, describe current pathogen identification and AMR screening methods, and provide perspectives on how DNA sequencing may be used for rapid diagnostics. Additionally, we discuss the common steps used for DNA data analysis, currently available pipelines, and tools for analysis. Direct, culture-independent sequencing has the potential to complement current culture-based methods in routine clinical settings. However, there is a need for a minimum set of standards in terms of evaluating the results generated. Additionally, we discuss the use of machine learning algorithms regarding pathogen phenotype detection (resistance/susceptibility to an antibiotic).

Normalization of gene expression data revisited: the three viewpoints of the transcriptome in human skeletal muscle undergoing load-induced hypertrophy and why they matter.

BACKGROUND: The biological relevance and accuracy of gene expression data depend on the adequacy of data normalization. This is both due to its role in resolving and accounting for technical variation and errors, and its defining role in shaping the viewpoint of biological interpretations. Still, the choice of the normalization method is often not explicitly motivated although this choice may be particularly decisive for conclusions in studies involving pronounced cellular plasticity. In this study, we highlight the consequences of using three fundamentally different modes of normalization for interpreting RNA-seq data from human skeletal muscle undergoing exercise-training-induced growth. Briefly, 25 participants conducted 12 weeks of high-load resistance training. Muscle biopsy specimens were sampled from m. vastus lateralis before, after two weeks of training (week 2) and after the intervention (week 12), and were subsequently analyzed using RNA-seq. Transcript counts were modeled as (1) per-library-size, (2) per-total-RNA, and (3) per-sample-size (per-mg-tissue). RESULT: Initially, the three modes of transcript modeling led to the identification of three unique sets of stable genes, which displayed differential expression profiles. Specifically, genes showing stable expression across samples in the per-library-size dataset displayed training-associated increases in per-total-RNA and per-sample-size datasets. These gene sets were then used for normalization of the entire dataset, providing transcript abundance estimates corresponding to each of the three biological viewpoints (i.e., per-library-size, per-total-RNA, and per-sample-size). The different normalization modes led to different conclusions, measured as training-associated changes in transcript expression. Briefly, for 27% and 20% of the transcripts, training was associated with changes in expression in per-total-RNA and per-sample-size scenarios, but not in the per-library-size scenario. At week 2, this led to opposite conclusions for 4% of the transcripts between per-library-size and per-sample-size datasets (↑ vs. ↓, respectively). CONCLUSION: Scientists should be explicit with their choice of normalization strategies and should interpret the results of gene expression analyses with caution. This is particularly important for data sets involving a limited number of genes or involving growing or differentiating cellular models, where the risk of biased conclusions is pronounced.

Ultrafast and Cost-Effective Pathogen Identification and Resistance Gene Detection in a Clinical Setting Using Nanopore Flongle Sequencing.

Rapid bacterial identification and antimicrobial resistance gene (ARG) detection are crucial for fast optimization of antibiotic treatment, especially for septic patients where each hour of delayed antibiotic prescription might have lethal consequences. This work investigates whether the Oxford Nanopore Technology's (ONT) Flongle sequencing platform is suitable for real-time sequencing directly from blood cultures to identify bacteria and detect resistance-encoding genes. For the analysis, we used pure bacterial cultures of four clinical isolates of Escherichia coli and Klebsiella pneumoniae and two blood samples spiked with either E. coli or K. pneumoniae that had been cultured overnight. We sequenced both the whole genome and plasmids isolated from these bacteria using two different sequencing kits. Generally, Flongle data allow rapid bacterial ID and resistome detection based on the first 1,000-3,000 generated sequences (10 min to 3 h from the sequencing start), albeit ARG variant identification did not always correspond to ONT MinION and Illumina sequencing-based data. Flongle data are sufficient for 99.9% genome coverage within at most 20,000 (clinical isolates) or 50,000 (positive blood cultures) sequences generated. The SQK-LSK110 Ligation kit resulted in higher genome coverage and more accurate bacterial identification than the SQK-RBK004 Rapid Barcode kit.

A culture-, amplification-independent, and rapid method for identification of pathogens and antibiotic resistance profile in bovine mastitis milk.

Introduction: Rapid and accurate diagnosis of causative pathogens in mastitis would minimize the imprudent use of antibiotics and, therefore, reduce the spread of antimicrobial resistance. Whole genome sequencing offers a unique opportunity to study the microbial community and antimicrobial resistance (AMR) in mastitis. However, the complexity of milk samples and the presence of a high amount of host DNA in milk from infected udders often make this very challenging. Methods: Here, we tested 24 bovine milk samples (18 mastitis and six non-mastitis) using four different commercial kits (Qiagens' DNeasy® PowerFood® Microbial, Norgens' Milk Bacterial DNA Isolation, and Molzyms' MolYsis™ Plus and Complete5) in combination with filtration, low-speed centrifugation, nuclease, and 10% bile extract of male bovine (Ox bile). Isolated DNA was quantified, checked for the presence/absence of host and pathogen using PCR and sequenced using MinION nanopore sequencing. Bioinformatics analysis was performed for taxonomic classification and antimicrobial resistance gene detection. Results: The results showed that kits designed explicitly for bacterial DNA isolation from food and dairy matrices could not deplete/minimize host DNA. Following using MolYsis™ Complete 5 + 10% Ox bile + micrococcal nuclease combination, on average, 17% and 66.5% of reads were classified as bovine and Staphylococcus aureus reads, respectively. This combination also effectively enriched other mastitis pathogens, including Escherichia coli and Streptococcus dysgalactiae. Furthermore, using this approach, we identified important AMR genes such as Tet (A), Tet (38), fosB-Saur, and blaZ. We showed that even 40 min of the MinION run was enough for bacterial identification and detecting the first AMR gene. Conclusion: We implemented an effective method (sensitivity of 100% and specificity of 92.3%) for host DNA removal and bacterial DNA enrichment (both gram-negative and positive) directly from bovine mastitis milk. To the best of our knowledge, this is the first culture- and amplification-independent study using nanopore-based metagenomic sequencing for real-time detection of the pathogen (within 5 hours) and the AMR profile (within 5-9 hours), in mastitis milk samples. These results provide a promising and potential future on-farm adaptable approach for better clinical management of mastitis.

Hybrid Assembly Provides Improved Resolution of Plasmids, Antimicrobial Resistance Genes, and Virulence Factors in Escherichia coli and Klebsiella pneumoniae Clinical Isolates.

Emerging new sequencing technologies have provided researchers with a unique opportunity to study factors related to microbial pathogenicity, such as antimicrobial resistance (AMR) genes and virulence factors. However, the use of whole-genome sequence (WGS) data requires good knowledge of the bioinformatics involved, as well as the necessary techniques. In this study, a total of nine Escherichia coli and Klebsiella pneumoniae isolates from Norwegian clinical samples were sequenced using both MinION and Illumina platforms. Three out of nine samples were sequenced directly from blood culture, and one sample was sequenced from a mixed-blood culture. For genome assembly, several long-read, (Canu, Flye, Unicycler, and Miniasm), short-read (ABySS, Unicycler and SPAdes) and hybrid assemblers (Unicycler, hybridSPAdes, and MaSurCa) were tested. Assembled genomes from the best-performing assemblers (according to quality checks using QUAST and BUSCO) were subjected to downstream analyses. Flye and Unicycler assemblers performed best for the assembly of long and short reads, respectively. For hybrid assembly, Unicycler was the top-performing assembler and produced more circularized and complete genome assemblies. Hybrid assembled genomes performed substantially better in downstream analyses to predict putative plasmids, AMR genes and ß-lactamase gene variants, compared to MinION and Illumina assemblies. Thus, hybrid assembly has the potential to reveal factors related to microbial pathogenicity in clinical and mixed samples.

Chronic obstructive pulmonary disease does not impair responses to resistance training.

BACKGROUND: Subjects with chronic obstructive pulmonary disease (COPD) are prone to accelerated decay of muscle strength and mass with advancing age. This is believed to be driven by disease-inherent systemic pathophysiologies, which are also assumed to drive muscle cells into a state of anabolic resistance, leading to impaired abilities to adapt to resistance exercise training. Currently, this phenomenon remains largely unstudied. In this study, we aimed to investigate the assumed negative effects of COPD for health- and muscle-related responsiveness to resistance training using a healthy control-based translational approach. METHODS: Subjects with COPD (n = 20, GOLD II-III, FEV1predicted 57 ± 11%, age 69 ± 5) and healthy controls (Healthy, n = 58, FEV1predicted 112 ± 16%, age 67 ± 4) conducted identical whole-body resistance training interventions for 13 weeks, consisting of two weekly supervised training sessions. Leg exercises were performed unilaterally, with one leg conducting high-load training (10RM) and the contralateral leg conducting low-load training (30RM). Measurements included muscle strength (nvariables = 7), endurance performance (nvariables = 6), muscle mass (nvariables = 3), muscle quality, muscle biology (m. vastus lateralis; muscle fiber characteristics, RNA content including transcriptome) and health variables (body composition, blood). For core outcome domains, weighted combined factors were calculated from the range of singular assessments. RESULTS: COPD displayed well-known pathophysiologies at baseline, including elevated levels of systemic low-grade inflammation ([c-reactive protein]serum), reduced muscle mass and functionality, and muscle biological aberrancies. Despite this, resistance training led to improved lower-limb muscle strength (15 ± 8%), muscle mass (7 ± 5%), muscle quality (8 ± 8%) and lower-limb/whole-body endurance performance (26 ± 12%/8 ± 9%) in COPD, resembling or exceeding responses in Healthy, measured in both relative and numeric change terms. Within the COPD cluster, lower FEV1predicted was associated with larger numeric and relative increases in muscle mass and superior relative improvements in maximal muscle strength. This was accompanied by similar changes in hallmarks of muscle biology such as rRNA-content↑, muscle fiber cross-sectional area↑, type IIX proportions↓, and changes in mRNA transcriptomics. Neither of the core outcome domains were differentially affected by resistance training load. CONCLUSIONS: COPD showed hitherto largely unrecognized responsiveness to resistance training, rejecting the notion of disease-related impairments and rather advocating such training as a potent measure to relieve pathophysiologies. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02598830. Registered November 6th 2015, https://clinicaltrials.gov/ct2/show/NCT02598830.

AMR-Diag: Neural network based genotype-to-phenotype prediction of resistance towards ß-lactams in Escherichia coli and Klebsiella pneumoniae.

Antibiotic resistance poses a major threat to public health. More effective ways of the antibiotic prescription are needed to delay the spread of antibiotic resistance. Employment of sequencing technologies coupled with the use of trained neural network algorithms for genotype-to-phenotype prediction will reduce the time needed for antibiotic susceptibility profile identification from days to hours. In this work, we have sequenced and phenotypically characterized 171 clinical isolates of Escherichia coli and Klebsiella pneumoniae from Norway and India. Based on the data, we have created neural networks to predict susceptibility for ampicillin, 3rd generation cephalosporins and carbapenems. All networks were trained on unassembled data, enabling prediction within minutes after the sequencing information becomes available. Moreover, they can be used both on Illumina and MinION generated data and do not require high genome coverage for phenotype prediction. We cross-checked our networks with previously published algorithms for genotype-to-phenotype prediction and their corresponding datasets. Besides, we also created an ensemble of networks trained on different datasets, which improved the cross-dataset prediction compared to a single network. Additionally, we have used data from direct sequencing of spiked blood cultures and found that AMR-Diag networks, coupled with MinION sequencing, can predict bacterial species, resistome, and phenotype as fast as 1-8 h from the sequencing start. To our knowledge, this is the first study for genotype-to-phenotype prediction: (1) employing a neural network method; (2) using data from more than one sequencing platform; and (3) utilizing sequence data from spiked blood cultures.

Vitamin D3 supplementation does not enhance the effects of resistance training in older adults.

BACKGROUND: Lifestyle therapy with resistance training is a potent measure to counteract age-related loss in muscle strength and mass. Unfortunately, many individuals fail to respond in the expected manner. This phenomenon is particularly common among older adults and those with chronic diseases (e.g. chronic obstructive pulmonary disease, COPD) and may involve endocrine variables such as vitamin D. At present, the effects of vitamin D supplementation on responses to resistance training remain largely unexplored. METHODS: Ninety-five male and female participants (healthy, n = 71; COPD, n = 24; age 68 ± 5 years) were randomly assigned to receive either vitamin D3 or placebo supplementation for 28 weeks in a double-blinded manner (latitude 61°N, September-May). Seventy-eight participants completed the RCT, which was initiated by 12 weeks of supplementation-only (two weeks with 10 000 IU/day, followed by 2000 IU/day), followed by 13 weeks of combined supplementation (2000 IU/day) and supervised whole-body resistance training (twice weekly), interspersed with testing and measurements. Outcome measures included multiple assessments of muscle strength (nvariables  = 7), endurance performance (n = 6), and muscle mass (n = 3, legs, primary), as well as muscle quality (legs), muscle biology (m. vastus lateralis; muscle fibre characteristics, transcriptome), and health-related variables (e.g. visceral fat mass and blood lipid profile). For main outcome domains such as muscle strength and muscle mass, weighted combined factors were calculated from the range of singular assessments. RESULTS: Overall, 13 weeks of resistance training increased muscle strength (13% ± 8%), muscle mass (9% ± 8%), and endurance performance (one-legged, 23% ± 15%; whole-body, 8% ± 7%), assessed as weighted combined factors, and were associated with changes in health variables (e.g. visceral fat, -6% ± 21%; [LDL]serum , -4% ± 14%) and muscle tissue characteristics such as fibre type proportions (e.g. IIX, -3% points), myonuclei per fibre (30% ± 65%), total RNA/rRNA abundances (15%/6-19%), and transcriptome profiles (e.g. 312 differentially expressed genes). Vitamin D3 supplementation did not affect training-associated changes for any of the main outcome domains, despite robust increases in [25(OH)D]serum (∆49% vs. placebo). No conditional effects were observed for COPD vs. healthy or pre-RCT [25(OH)D]serum . In secondary analyses, vitamin D3 affected expression of gene sets involved in vascular functions in muscle tissue and strength gains in participants with high fat mass, which advocates further study. CONCLUSIONS: Vitamin D3 supplementation did not affect muscular responses to resistance training in older adults with or without COPD.

The new COST Action European Venom Network (EUVEN)-synergy and future perspectives of modern venomics.

Venom research is a highly multidisciplinary field that involves multiple subfields of biology, informatics, pharmacology, medicine, and other areas. These different research facets are often technologically challenging and pursued by different teams lacking connection with each other. This lack of coordination hampers the full development of venom investigation and applications. The COST Action CA19144-European Venom Network was recently launched to promote synergistic interactions among different stakeholders and foster venom research at the European level.

Plasmid Identification and Plasmid-Mediated Antimicrobial Gene Detection in Norwegian Isolates.

Norway is known for being one of the countries with the lowest levels of antimicrobial resistance (AMR). AMR, through acquired genes located on transposons or conjugative plasmids, is the horizontal transmission of genes required for a given bacteria to withstand antibiotics. In this work, bioinformatic analysis of whole-genome sequences and hybrid assembled data from Escherichia coli, and Klebsiella pneumoniae isolates from Norwegian patients was performed. For detection of putative plasmids in isolates, the plasmid assembly mode in SPAdes was used, followed by annotation of resulting contigs using PlasmidFinder and two curated plasmid databases (Brooks and PLSDB). Furthermore, ResFinder and Comprehensive Antibiotic Resistance Database (CARD) were used for the identification of antibiotic resistance genes (ARGs). The IncFIB plasmid was detected as the most prevalent plasmid in both E. coli, and K. pneumoniae isolates. Furthermore, ARGs such as aph(3″)-Ib, aph(6)-Id, sul1, sul2, tet(D), and qnrS1 were identified as the most abundant plasmid-mediated ARGs in Norwegian E. coli and K. pneumoniae isolates, respectively. Using hybrid assembly, we were able to locate plasmids and predict ARGs more confidently. In conclusion, plasmid identification and ARG detection using whole-genome sequencing data are heavily dependent on the database of choice; therefore, it is best to use several tools and/or hybrid assembly for obtaining reliable identification results.