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Abstract We developed and evaluated the Digital Platform for Exercise (DPEx): a decentralized, patient-centric approach designed to enhance all aspects of clinical investigation of exercise therapy. DPEx integrated provision of a treadmill with telemedicine and remote biospecimen collection permitting all study procedures to be conducted in patient’s homes. Linked health biodevices enabled high-resolution monitoring of lifestyle and physiological response. Here we describe the rationale and development of DPEx as well as feasibility evaluation in three different cohorts of patients with cancer: a phase 0a development study among three women with post-treatment primary breast cancer; a phase 0b proof-of-concept trial of neoadjuvant exercise therapy in 13 patients with untreated solid tumors; and a phase 1a level-finding trial of neoadjuvant exercise therapy in 53 men with localized prostate cancer. Collectively, our study demonstrates the utility of a fully digital, decentralized approach to conduct clinical trials of exercise therapy in a clinical population.

Abstract Background Physical activity and metformin pharmacotherapy are associated with improved clinical outcomes in breast and colorectal cancer survivors. Myokines are cytokines secreted from skeletal muscle that may mediate these associations. Methods This hypothesis‐generating analysis used biospecimens collected from a multi‐centre 2 × 2 factorial randomized design of 116 patients with stage I–III breast and colorectal cancer who were randomized to 12 weeks of (1) aerobic exercise (moderate intensity titrated to 220 min/week); (2) metformin (850 mg daily for 2 weeks and then titrated to 850 mg twice per day); (3) aerobic exercise and metformin; or (4) control. Fourteen myokines were quantified using a multiplex panel. Myokine concentrations were log‐transformed, and main effects analyses were conducted using linear mixed‐effects regression models. The type I error rate was controlled with the Holm sequential testing procedure. Results Randomization to exercise increased leukaemia inhibitory factor (1.26 pg/mL, 95% confidence interval [CI]: 0.69, 1.84; adjusted P = 0.001) and interleukin‐15 (2.23 pg/mL, 95% CI: 0.87, 3.60; adjusted P = 0.013) compared with randomization to no exercise. Randomization to metformin decreased apelin (−2.69 pg/mL, 95% CI: −4.31, −1.07; adjusted P = 0.014) and interleukin‐15 (−1.74 pg/mL, 95% CI: −2.79, −0.69; adjusted P = 0.013) compared with randomization to no metformin. Metformin decreased myostatin, irisin, oncostatin M, fibroblast growth factor 21 and osteocrin; however, these changes were not statistically significant after correction for multiple comparisons. Conclusions This pilot study demonstrates that randomization to exercise and metformin elicit unique effects on myokine concentrations in cancer patients. This hypothesis‐generating observation warrants further basic, translational and clinical investigation and replication.

Pretreatment prognostication, on-treatment monitoring, and early detection of physiological symptoms are considerable challenges in cancer. We describe the feasibility of high-resolution wearable data (steps per day, walking speed) to longitudinally profile physiological trajectories extracted from Apple Health data in three patients with lung cancer from diagnosis through cancer treatment after obtaining informed consent. We used descriptive statistics to describe our approach of building longitudinal physiological profiles. The wearable data monitoring period ranged from 58 to 135 weeks, with between 34,319 and 103,535 distinct digital physiological measures collected during this period—the equivalent to 41 measures per day/patient. Longitudinal profiling revealed that wearable data accurately captured physiological changes linked with clinical events such as surgery and hospitalizations as well as initiation (and cessation) of systemic cancer treatment in all three patients. These findings suggest that wearable devices could play a critical role in the management of lung cancer, although larger studies are needed to confirm these preliminary observations and validate their generalizability. Wearable devices hold significant promise for the development of personalized “digital biomarkers,” which may enhance risk stratification and management in oncology.

Abstract We report on a new ground-level neutron monitor design for studying cosmic rays and fluxes of solar energetic particles at the Earth’s surface. The first-of-its-kind instrument, named the NM-2023 after the year it was standardised and following convention, will be installed at a United Kingdom Meteorological Office observatory (expected completion mid 2024) and will reintroduce such monitoring in the UK for the first time since ca. 1984. Monte Carlo radiation transport code is used for the development and application of parameterised models to investigate alternative neutron detectors, their location and bulk material geometry in a realistic cosmic ray neutron field. Benchmarked against a model of the current and most widespread design standardised in 1964 (the NM-64), two main parameterisation studies are conducted; a simplified standard model and a concept slab parameterisation. We show that the NM-64 standard is well optimised for the intended large-diameter boron trifluoride (BF $$_3$$ 3 ) proportional counters but not for multiple smaller diameter counters. The new design (based on a novel slab arrangement) produces comparable counting efficiencies to an NM-64 with six BF $$_3$$ 3 counters and has the added advantage of being more compact, lower cost and avoids the use of highly toxic BF $$_3$$ 3 .

ABSTRACT Most pneumococcal disease occurs among infants and older adults and is thought to be driven by the transmission of Streptococcus pneumoniae from young children to these vulnerable age groups. However, pneumococcal disease outbreaks also affect non-elderly adults living or working in congregate, close-contact settings. Little is known about pneumococcal carriage in such populations. From July to November 2020, we collected saliva from low-income adult farmworkers in Monterey County, California, and tested for pneumococcal carriage following culture enrichment via quantitative PCR assays targeting the pneumococcal lytA and piaB genes. Participants were considered to carry pneumococci if lytA and piaB cycle threshold values were both below 40. Among 1,283 participants enrolled in our study, 117 (9.1%) carried pneumococci. Carriers tended more often than non-carriers to be exposed to children aged 2–4 and >4 persons per bedroom vs ≤2 persons per bedroom]. Household overcrowding remained associated with increased risk of carriage among participants not exposed to children aged 2 vs ≤2 persons per bedroom]. Exposure to children aged

Ji Yeong Kim,1,&ast; Yookyung Jang,2,&ast; Eun Jang Yoon,1 Wootaek Lee,1 Jaewoo Kim,2 Jae Chul Koh2 1Department of Anesthesiology and Pain Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea; 2Department of Anesthesiology and Pain Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea&ast;These authors contributed equally to this workCorrespondence: Jae Chul Koh, Department of Anesthesiology and Pain Medicine, Korea University Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, Republic of Korea, Tel +82-2-920-5632, Fax +82-2-928-2275, Email jaykoh@korea.ac.krPurpose: The aim of this prospective study was to develop a virtual reality simulator (VRS) for spinal cord stimulation (SCS) trials and establish its effectiveness.Methods: We developed a VRS for SCS training by integrating patient imaging data analytics, creating artificial X-ray images, and using spatial alignment techniques and virtual reality technologies. The simulator was created by a physician with considerable experience in performing SCS, and can simulate the feeling of the procedure in a virtual environment. The efficacy of the simulator for SCS trials was assessed using a cohort of 20 novice trainees. The primary outcomes were duration of the procedure, checklist score, number of C-arm images captured, and overall trainee satisfaction.Results: The cohort that utilized the VRS had better Zwisch scale scores (P < 0.001), completed the procedure in a shorter time (P < 0.001), took fewer C-arm images (P < 0.001), and reported better overall satisfaction (P = 0.011) than the cohort that did not.Conclusion: We developed a realistic and efficient VRS for educating novice trainees on SCS trials, thereby eliminating the risk of radiation exposure associated with cadaver training. The results of this study indicate that our VRS has potential as an instrumental resource that can be integrated into the educational framework for SCS trials.Keywords: surgical procedure, simulation training, spinal cord stimulator, virtual reality, virtual reality simulator

Vesicular stomatitis (VS) is a viral disease that affects horses, cattle, and swine that is transmitted by direct contact and hematophagous insects. In 2023, a multi-state outbreak of vesicular stomatitis New Jersey virus (VSNJV) occurred in California, Nevada, and Texas, infecting horses, cattle, and rhinoceros. To identify possible insect vectors, we conducted insect surveillance at various locations in San Diego County, CA, including at a wildlife park. CO2 baited traps set from mid-May to mid-August 2023 collected 2357 Culicoides biting midges and 1215 Simulium black flies, which are insect genera implicated in VSNJV transmission. Insects were pooled by species, location, and date, then tested for viral RNA. Nine RNA-positive pools of Culicoides spp. and sixteen RNA-positive pools of Simulium spp were detected. Infectious virus was detected by cytopathic effect in 96% of the RNA-positive pools. This is the first report of VSNJV in wild-caught C. bergi, C. freeborni, C. occidentalis, S. argus, S. hippovorum, and S. tescorum. The vector competency of these species for VSNJV has yet to be determined but warrants examination. Active vector surveillance and testing during disease outbreaks increases our understanding of the ecology and epidemiology of VS and informs vector control efforts.

Background: Androgen deprivation therapy (ADT) is a common treatment modality for men with prostate cancer. Increases in adipose tissue mass and decreases in skeletal muscle mass are known on-target adverse effects of standard ADT. The effects of newer agents such as abiraterone acetate (ABI) and enzalutamide (ENZA) on body composition and how these compare with standard luteinizing hormone-releasing hormone agonists (aLHRHs) are unclear. Objective: To assess the effects of different forms of androgen deprivation therapy on body composition in men with prostate cancer. Design, setting, and participants: Using a retrospective design, 229 patients receiving aLHRHs alone (n = 120) or in combination with ABI (n = 53) or ENZA (n = 56) were studied. Outcome measurements and statistical analysis: Muscle, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) were assessed at baseline, 6 mo, and 18 mo after initiating therapy using a cross-sectional densitometry analysis performed on standard of care computed tomography images. Response trajectories for all treatment groups were calculated via a two-way analysis of variance post hoc test, for both within-group and between-group differences. Results and limitations: Treatment with aLHRHs, ABI, and ENZA was associated with a median muscle volume loss of –1.4%, –4.8%, and –5.5% at 6 mo, and –7.1%, –8.1%, and –8.3% at 18 mo, respectively. Therapy with aLHRHs was associated with minimal changes in VAT (0.3% at 6 mo and –0.1% at 18 mo). ABI therapy was associated with significant increases in VAT at 6 mo (4.9%) but not at 18 mo (0.5%), and ENZA therapy was associated with significant decreases in VAT (–4.6% at 6 mo and –5.4% at 18 mo). With respect to SAT, treatment with aLHRHs was associated with increases over time (8.6% at 6 mo and 4.7% at 18 mo), ABI was associated with decreases over time (–3.6% at 6 mo and –6.8% at 18 mo), and ENZA had no clear effects (1.7% at 6 mo and 3.3% at 18 mo). Conclusions: ADT regimens cause significant short-term losses in muscle mass, with the most rapid effects occurring with ABI and ENZA. The three regimens have disparate effects on SAT and VAT, suggesting distinct roles of androgens in these tissues. Patient summary: Androgen deprivation therapy alters body composition in men with prostate cancer. Abiraterone and enzalutamide are associated with losses in muscle mass compared with luteinizing hormone-releasing hormone agonists. These treatments impact subcutaneous and visceral fat mass, suggesting distinct roles of androgens in these tissues.

Abstract The coronavirus 2019 (COVID-19) pandemic has had significant impacts on health systems, population dynamics, public health awareness, and antibiotic stewardship, which could affect antibiotic resistant bacteria (ARB) emergence and transmission. In this study, we aimed to compare knowledge, attitudes, and practices (KAP) of antibiotic use and ARB carriage in Ecuadorian communities before versus after the COVID-19 pandemic began. We leveraged data collected for a repeated measures observational study of third-generation cephalosporin-resistant E. coli (3GCR-EC) carriage among children in semi-rural communities in Quito, Ecuador between July 2018 and September 2021. We included 241 households that participated in surveys and child stool sample collection in 2019, before the pandemic, and in 2021, after the pandemic began. We estimated adjusted Prevalence Ratios (aPR) and 95% Confidence Intervals (CI) using logistic and Poisson regression models. Child antibiotic use in the last 3 months declined from 17% pre-pandemic to 5% in 2021 (aPR: 0.30; 95% CI 0.15, 0.61) and 3GCR-EC carriage among children declined from 40 to 23% (aPR: 0.48; 95% CI 0.32, 0.73). Multi-drug resistance declined from 86 to 70% (aPR: 0.32; 95% CI 0.13; 0.79), the average number of antibiotic resistance genes (ARGs) per 3GCR-EC isolate declined from 9.9 to 7.8 (aPR of 0.79; 95% CI 0.65, 0.96), and the diversity of ARGs was lower in 2021. In the context of Ecuador, where COVID-19 prevention and control measures were strictly enforced after its major cities experienced some of the world’s the highest mortality rates from SARS-CoV-2 infections, antibiotic use and ARB carriage declined in semi-rural communities of Quito from 2019 to 2021.

Japanese encephalitis is a disease caused by the Japanese encephalitis virus (JEV) and is a concern for U.S. military personnel stationed in the Republic of Korea (ROK). The recent literature reports a potential shift from GI to GV as the dominant genotype circulating in east Asia. In the ROK, GV has been reported in a few Culex spp., but not in the main JEV vector, Cx. tritaeniorhynchus. The goal of this surveillance was to shed light on the current knowledge of the epidemiology of JEV in the ROK by analyzing mosquito collection data from three consecutive years, 2021–2023, and molecularly detecting and genotyping JEV in all Culex spp. collected in several military locations across the ROK. In this study, we detected only JEV GI in Cx. tritaeniorhynchus in 2021 samples. In contrast, all 2022 and 2023 positive samples were GV and detected in Cx. bitaeniorhynchus, Cx. orientalis, and Cx. pipiens. Results support a shift in JEV genotype in the ROK and suggest that for GV, Culex spp. other than Cx. tritaeniorhynchus may be playing an important role.

Vesicular stomatitis (VS) is a vector-borne livestock disease caused by the vesicular stomatitis New Jersey virus (VSNJV). This study presents the first application of an SEIR-SEI compartmental model to analyze VSNJV transmission dynamics. Focusing on the 2014–2015 outbreak in the United States, the model integrates vertebrate hosts and insect vector demographics while accounting for heterogeneous competency within the populations and observation bias in documented disease cases. Key epidemiological parameters were estimated using Bayesian inference and Markov chain Monte Carlo (MCMC) methods, including the force of infection, effective reproduction number (Rt), and incubation periods. The model revealed significant underreporting, with only 10–24% of infections documented, 23% of which presented with clinical symptoms. These findings underscore the importance of including competence and imperfect detection in disease models to depict outbreak dynamics and inform effective control strategies accurately. As a baseline model, this SEIR-SEI implementation is intended to serve as a foundation for future refinements and expansions to improve our understanding of VS dynamics. Enhanced surveillance and targeted interventions are recommended to manage future VS outbreaks.

ABSTRACT Extraintestinal pathogenic Escherichia coli (ExPEC) belonging to multilocus sequence type 95 (ST95) is one of the most geographically widespread ExPEC lineages causing bloodstream infection (BSI) and urinary tract infection (UTI). In contrast to other widespread ExPEC sequence types, a large proportion of ST95 strains remains susceptible to all antimicrobial agents used to treat BSI or UTI. We aimed to identify the genomic features of ST95 associated with its relatively high drug-susceptible frequency. We analyzed whole genomes of 1,749 ST95 isolates, 80 from patients with BSI or UTI in Northern California and 1,669 isolates from the EnteroBase database. We first compared whole-genome sequences (WGSs) of 887 drug-susceptible strains and 862 strains resistant to one or more drugs (defined genotypically as strains harboring drug-resistance genes annotated in the ResFinder database) to identify genetic features associated with strains devoid of drug resistance genes. We then conducted a pan-genome-wide association study on human clinical isolates of ST95, which included 553 UTI and BSI ST95 isolates. We found 44 accessory genes to be significantly associated with ST95 strains lacking drug resistance genes. Fifteen of these were not found in any of the WGSs of ST131 ExPEC strains, which are frequently multidrug-resistant. These genes were annotated to encode transporter or transfer systems and DNA repair polymerases. A large proportion of ST95 strains may have evolved to adapt to antibiotic-imposed stresses without acquiring drug resistance genes. IMPORTANCE Despite the increasing prevalence of antibiotic-resistant Escherichia coli strains that cause urinary tract and bloodstream infections, a major pandemic lineage of extraintestinal pathogenic E. coli (ExPEC) ST95 has a comparatively low frequency of drug resistance. We compared the genomes of 1,749 ST95 isolates to identify genetic features that may explain why most strains of ST95 resist becoming drug-resistant. Identification of such genomic features could contribute to the development of novel strategies to prevent the spread of antibiotic-resistant genes and devise new measures to control antibiotic-resistant infections.

Bluetongue virus (BTV) is a segmented, double-stranded RNA virus transmitted by Culicoides midges that infects ruminants. As global temperatures increase and geographical ranges of midges expand, there is increased potential for BTV outbreaks from incursions of novel serotypes into endemic regions. However, an understanding of the effect of temperature on reassortment is lacking. The objectives of this study were to compare how temperature affected Culicoides survival, virogenesis, and reassortment in Culicoides sonorensis coinfected with two BTV serotypes. Midges were fed blood meals containing BTV-10, BTV-17, or BTV serotype 10 and 17 and maintained at 20 °C, 25 °C, or 30 °C. Midge survival was assessed, and pools of midges were collected every other day to evaluate virogenesis of BTV via qRT-PCR. Additional pools of coinfected midges were collected for BTV plaque isolation. The genotypes of plaques were determined using next-generation sequencing. Warmer temperatures impacted traits related to vector competence in offsetting ways: BTV replicated faster in midges at warmer temperatures, but midges did not survive as long. Overall, plaques with BTV-17 genotype dominated, but BTV-10 was detected in some plaques, suggesting parental strain fitness may play a role in reassortment outcomes. Temperature adds an important dimension to host–pathogen interactions with implications for transmission and evolution.

BackgroundThe spread of antibiotic-resistant bacteria may be driven by human-animal-environment interactions, especially in regions with limited restrictions on antibiotic use, widespread food animal production, and free-roaming domestic animals. In this study, we aimed to identify risk factors related to commercial food animal production, small-scale or "backyard" food animal production, domestic animal ownership, and practices related to animal handling, waste disposal, and antibiotic use in Ecuadorian communities.Methods and findingsWe conducted a repeated measures study from 2018 to 2021 in 7 semirural parishes of Quito, Ecuador to identify determinants of third-generation cephalosporin-resistant E. coli (3GCR-EC) and extended-spectrum beta-lactamase E. coli (ESBL-EC) in children. We collected 1,699 fecal samples from 600 children and 1,871 domestic animal fecal samples from 376 of the same households at up to 5 time points per household over the 3-year study period. We used multivariable log-binomial regression models to estimate relative risks (RR) of 3GCR-EC and ESBL-EC carriage, adjusting for child sex and age, caregiver education, household wealth, and recent child antibiotic use. Risk factors for 3GCR-EC included living within 5 km of more than 5 commercial food animal operations (RR: 1.26; 95% confidence interval (CI): 1.10, 1.45; p-value: 0.001), household pig ownership (RR: 1.23; 95% CI: 1.02, 1.48; p-value: 0.030) and child pet contact (RR: 1.23; 95% CI: 1.09, 1.39; p-value: 0.001). Risk factors for ESBL-EC were dog ownership (RR: 1.35; 95% CI: 1.00, 1.83; p-value: 0.053), child pet contact (RR: 1.54; 95% CI: 1.10, 2.16; p-value: 0.012), and placing animal feces on household land/crops (RR: 1.63; 95% CI: 1.09, 2.46; p-value: 0.019). The primary limitations of this study are the use of proxy and self-reported exposure measures and the use of a single beta-lactamase drug (ceftazidime with clavulanic acid) in combination disk diffusion tests for ESBL confirmation, potentially underestimating phenotypic ESBL production among cephalosporin-resistant E. coli isolates. To improve ESBL determination, it is recommended to use 2 combination disk diffusion tests (ceftazidime with clavulanic acid and cefotaxime with clavulanic acid) for ESBL confirmatory testing. Future studies should also characterize transmission pathways by assessing antibiotic resistance in commercial food animals and environmental reservoirs.ConclusionsIn this study, we observed an increase in enteric colonization of antibiotic-resistant bacteria among children with exposures to domestic animals and their waste in the household environment and children living in areas with a higher density of commercial food animal production operations.

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

Hansen’s disease (HD) is an infectious, treatable, and chronic disease. It is the main cause of infectious peripheral neuropathy. Due to the current limitations of laboratory tests for the diagnosis of HD, early identification of infected contacts is an important factor that would allow us to control the magnitude of this disease in terms of world public health. Thus, a cross-sectional study was conducted in the Brazilian southeast with the objective of evaluating humoral immunity and describing the accuracy of the immunoassay based on IgA, IgM, and IgG antibodies against surface protein Mce1A of Mycobacterium, the predictive potential of these molecules, the clinical significance of positivity, and the ability to segregate new HD cases (NC; n = 200), contacts (HHC; n = 105), and healthy endemic controls (HEC; n = 100) as compared to α-PGL-I serology. α-Mce1A levels for all tested antibodies were significantly higher in NC and HHC than in HEC (p 0.85) for screening HD patients. Among HD patients (NC), positivity was 77.5% for IgA α-Mce1A ELISA, 76.5% for IgM, and 61.5% for IgG, while α-PGL-I serology showed only 28.0% positivity. Multivariate PLS-DA showed two defined clusters for the HEC and NC groups [accuracy = 0.95 (SD = 0.008)] and the HEC and HHC groups [accuracy = 0.93 (SD = 0.011)]. IgA was the antibody most responsible for clustering HHC as compared to NC and HEC, evidencing its usefulness for host mucosal immunity and as an immunological marker in laboratory tests. IgM is the key antibody for the clustering of NC patients. Positive results with high antibody levels indicate priority for screening, new clinical and laboratory evaluations, and monitoring of contacts, mainly with antibody indexes ≥2.0. In light of recent developments, the incorporation of new diagnostic technologies permits to eliminate the main gaps in the laboratory diagnosis of HD, with the implementation of tools of greater sensitivity and accuracy while maintaining satisfactory specificity.

Abstract Background Proper vector surveillance relies on the ability to identify species of interest accurately and efficiently, though this can be difficult in groups containing cryptic species. Culicoides Latreille is a genus of small biting flies responsible for the transmission of numerous pathogens to a multitude of vertebrates. Regarding pathogen transmission, the C. variipennis species complex is of particular interest in North America. Of the six species within this group, only C. sonorensis Wirth & Jones is a proven vector of bluetongue virus and epizootic hemorrhagic disease virus. Unfortunately, subtle morphological differences, cryptic species, and mitonuclear discordance make species identification in the C. variipennis complex challenging. Recently, single-nucleotide polymorphism (SNP) analysis enabled discrimination between the species of this group; however, this demanding approach is not practical for vector surveillance. Methods The aim of the current study was to develop a reliable and affordable way of distinguishing between the species within the C. variipennis complex, especially C. sonorensis. Twenty-five putative microsatellite markers were identified using the C. sonorensis genome and tested for amplification within five species of the C. variipennis complex. Machine learning was then used to determine which markers best explain the genetic differentiation between species. This led to the development of a subset of four and seven markers, which were also tested for species differentiation. Results A total of 21 microsatellite markers were successfully amplified in the species tested. Clustering analyses of all of these markers recovered the same species-level identification as the previous SNP data. Additionally, the subset of seven markers was equally capable of accurately distinguishing between the members of the C. variipennis complex as the 21 microsatellite markers. Finally, one microsatellite marker (C508) was found to be species-specific, only amplifying in the vector species C. sonorensis among the samples tested. Conclusions These microsatellites provide an affordable way to distinguish between the sibling species of the C. variipennis complex and could lead to a better understanding of the species dynamics within this group. Additionally, after further testing, marker C508 may allow for the identification of C. sonorensis with a single-tube assay, potentially providing a powerful new tool for vector surveillance in North America. Graphical Abstract

Culicoides are small biting midges with the capacity to transmit important livestock pathogens around much of the world, and their impacts on animal welfare are likely to expand. Hemorrhagic diseases resulting from Culicoides-vectored viruses, for example, can lead to millions of dollars in economic damages for producers. Chemical insecticides can reduce Culicoides abundance but may not suppress population numbers enough to prevent pathogen transmission. These insecticides can also cause negative effects on non-target organisms and ecosystems. RNA interference (RNAi) is a cellular regulatory mechanism that degrades mRNA and suppresses gene expression. Studies have examined the utility of this mechanism for insect pest control, and with it, have described the hurdles towards producing, optimizing, and applying these RNAi-based products. These methods hold promise for being highly specific and environmentally benign when compared to chemical insecticides and are more transient than engineering transgenic insects. Given the lack of available control options for Culicoides, RNAi-based products could be an option to treat large areas with minimal environmental impact. In this study, we describe the state of current Culicoides control methods, successes and hurdles towards using RNAi for pest control, and the necessary research required to bring an RNAi-based control method to fruition for Culicoides midges.

Abstract The inability to distinguish between species can be a serious problem in groups responsible for pathogen transmission. Culicoides biting midges transmit many pathogenic agents infecting wildlife and livestock. In North America, the C. variipennis species complex contains three currently recognized species, only one of which is a known vector, but limited species-specific characters have hindered vector surveillance. Here, genomic data were used to investigate population structure and genetic differentiation within this species complex. Single nucleotide polymorphism data were generated for 206 individuals originating from 17 locations throughout the United States and Canada. Clustering analyses suggest the occurrence of two additional cryptic species within this complex. All five species were significantly differentiated in both sympatry and allopatry. Evidence of hybridization was detected in three different species pairings indicating incomplete reproductive isolation. Additionally, COI sequences were used to identify the hybrid parentage of these individuals, which illuminated discordance between the divergence of the mitochondrial and nuclear datasets.

The World Health Organization released a statement warning of increased risk for the incidence of multidrug resistant microorganisms and the absence of new drugs to control such infections soon. Since the beginning of the COVID-19 pandemic, the prescription of antimicrobial agents has increased and may have accelerated the emergence of multidrug resistant (MDR) bacteria. This study aimed to evaluate maternal and pediatric infections within a hospital from January 2019 to December 2021. An observational retrospective cohort study was performed at a quaternary referral hospital in a metropolitan area of Niteroi city, Rio de Janeiro state, Brazil. A total of 196 patients’ medical records were analyzed. The data from 90 (45.9%) patients were collected before the SARS-CoV-2 pandemic, 29 (14.8%) from the 2020 pandemic period, and 77 (39.3%) from the 2021 pandemic period. A total of 256 microorganisms were identified during this period. Out of those, 101 (39.5%) were isolated in 2019, 51 (19.9%) in 2020, and 104 (40.6%) in 2021. Antimicrobial susceptibility tests were performed on 196 (76.6%) clinical isolates. The exact binomial test showed that the distribution of Gram-negative bacteria was predominant. The most common microorganism was Escherichia coli (23%; n = 45), followed by Staphylococcus aureus (17.9%, n = 35), Klebsiella pneumoniae (12.8%, n = 25), Enterococcus faecalis (7.7%, n = 15), Staphylococcus epidermidis (6.6%, n = 13) and Pseudomonas aeruginosa (5.6%, n = 11). Staphylococcus aureus was the predominant species among resistant bacteria. Among the antimicrobial agents tested, the following were resistant, presented on a descending scale: penicillin (72.7%, p = 0.001, Binomial test), oxacillin (68.3%, p = 0.006, Binomial test), ampicillin (64.3%, p = 0.003, Binomial test), and ampicillin/sulbactam (54.9%, p = 0.57, Binomial test). Infections with S. aureus were 3.1 times greater in pediatrics and maternal units than in other hospital wards. Despite the global reduction in the incidence of MRSA, we observed an increase in MDR S. aureus in this study. No changes were observed in the frequency of resistance profiles of the clinical isolates after the establishment of the global SARS-CoV-2 pandemic. More comprehensive studies are needed to understand the impact of the global SARS-CoV-2 pandemic on the resistance levels of bacteria associated with neonate and pediatric patients.

Abstract Background Poor cardiorespiratory fitness (CRF) is a cardinal feature of post‐treatment primary lung cancer. The most effective exercise therapy regimen to improve CRF has not been determined. Methods In this parallel‐group factorial randomized controlled trial, lung cancer survivors with poor CRF (below age–sex sedentary values) were randomly allocated to receive 48 consecutive supervised sessions thrice weekly of (i) aerobic training (AT)—cycle ergometry at 55% to >95% of peak oxygen consumption (VO2peak); (ii) resistance training (RT)—lower and upper extremity exercises at 50–85% of maximal strength; (iii) combination training (CT)—AT plus RT; or (iv) stretching attention control (AC) for 16 weeks. The primary endpoint was change in CRF (VO2peak, mL O2·kg−1·min−1). Secondary endpoints were body composition, muscle strength, patient‐reported outcomes, tolerability (relative dose intensity of exercise), and safety. Analysis of covariance determined change in primary and secondary endpoints from baseline to post‐intervention (Week 17) with adjustment for baseline values of the endpoint and other relevant clinical covariates. Results Ninety patients (65 ± 9 years; 66% female) were randomized (AT, n = 24; RT, n = 23; CT, n = 20; and AC, n = 23) of the planned n = 160. No serious adverse events were observed. For the overall cohort, the lost‐to‐follow‐up rate was 10%. Mean attendance was ≥75% in all groups. In intention‐to‐treat analysis, VO2peak increased 1.1 mL O2·kg−1·min−1 [95% confidence interval (CI): 0.0, 2.2, P = 0.04] and 1.4 mL O2·kg−1·min−1 (95% CI: 0.2, 2.5, P = 0.02) in AT and CT, respectively, compared with AC. There was no difference in VO2peak change between RT and AC (−0.1 mL O2·kg−1·min−1, 95% CI: −1.2, 1.0, P = 0.88). Favourable improvements in maximal strength and body composition were observed in RT and CT groups compared with AT and AC groups (Ps

ABSTRACT Antimicrobial resistance in urinary tract infections (UTIs) is a major public health concern. This study aims to characterize the phenotypic and genetic basis of multidrug resistance (MDR) among expanded-spectrum cephalosporin-resistant (ESCR) uropathogenic Escherichia coli (UPEC) causing UTIs in California patient populations. Between February and October 2019, 577 ESCR UPEC isolates were collected from patients at 6 clinical laboratory sites across California. Lineage and antibiotic resistance genes were determined by analysis of whole-genome sequence data. The lineages ST131, ST1193, ST648, and ST69 were predominant, representing 46%, 5.5%, 4.5%, and 4.5% of the collection, respectively. Overall, 527 (91%) isolates had an expanded-spectrum β-lactamase (ESBL) phenotype, with blaCTX-M-15, blaCTX-M-27, blaCTX-M-55, and blaCTX-M-14 being the most prevalent ESBL genes. In the 50 non-ESBL phenotype isolates, 40 (62%) contained blaCMY-2, which was the predominant plasmid-mediated AmpC (pAmpC) gene. Narrow-spectrum β-lactamases, blaTEM-1B and blaOXA-1, were also found in 44.9% and 32.1% of isolates, respectively. Among ESCR UPEC isolates, isolates with an ESBL phenotype had a 1.7-times-greater likelihood of being MDR than non-ESBL phenotype isolates (P < 0.001). The cooccurrence of blaCTX-M-15, blaOXA-1, and aac(6′)-Ib-cr within ESCR UPEC isolates was strongly correlated. Cooccurrence of blaCTX-M-15, blaOXA-1, and aac(6′)-Ib-cr was associated with an increased risk of nonsusceptibility to piperacillin-tazobactam, cefepime, fluoroquinolones, and amikacin as well as MDR. Multivariate regression revealed the presence of blaCTX-M-55, blaTEM-1B, and the ST131 genotype as predictors of MDR. IMPORTANCE The rising incidence of resistance to expanded-spectrum cephalosporins among Escherichia coli strains, the most common cause of UTIs, is threatening our ability to successfully empirically treat these infections. ESCR E. coli strains are often MDR; therefore, UTI caused by these organisms often leads to treatment failure, increased length of hospital stay, and severe complications (D. G. Mark, Y.-Y. Hung, Z. Salim, N. J. Tarlton, et al., Ann Emerg Med 78:357–369, 2021, https://doi.org/10.1016/j.annemergmed.2021.01.003). Here, we performed an in-depth analysis of genetic factors of ESCR E. coli associated with coresistance and MDR. Such knowledge is critical to advance UTI diagnosis, treatment, and antibiotic stewardship.

Abstract Vesicular stomatitis (VS) is a vector‐borne viral disease that causes lesions in livestock, premises, county and state quarantines, and important economic losses. We investigated vector–habitat characteristics for vectors associated with VS in regions of recurrent disease within the western United States (US) that consistently lead to the environment where vector, host, and pathogen populations intersect to enable pathogen transmission. We analyzed the habitats of previously identified insect vectors, including black flies (BFs) (Simulium vittatum complex), biting midges (BMs) (Culicoides variipennis complex, which includes Culicoides sonorensis), and sand flies (SFs) (Lutzomyia shannoni) in six regions of interest (ROIs) containing hotspots of VS ranging from Texas (TX) to Wyoming. This analysis broadened the understanding of (1) how regions of reoccurring VS differ from the broader western US, (2) how geographically separated regions and hotspots are similar across time, and (3) how vector–environment habitat a priori knowledge relates to observed hotspots. Analysis of watershed factors (livestock densities, land‐cover proportions, stream and lake densities, and irrigation methods) indicated a complex system separating areas with high, recurring VS from the broader western US. Although no single characteristic separated the six ROIs from other areas, we found two distinct emerging groups (northern ROI and TX). Hotspots, estimated from monthly VS concentrations, evolved northward throughout the year and most hotspots were closer to flowing water and agricultural land than the broader ROI. All ROIs contained environmental conditions suitable for multiple vectors at some point in the year, but BFs had the highest suitability scores, whereas BM scores were lower and varied annually with higher suitability in summer. SFs had the lowest suitability score in all ROIs, consistent with their low likelihood of being vectors. BM habitat patches were often orders of magnitude smaller than BF patches, and hotspot patches reinforce the likelihood that BF may be the most critical vector in northern ROI, whereas both BM and BF have similar likelihood in southern ROI. Given limited existing vector data, this analysis provides an alternate pathway for using habitat information to associate likely vectors responsible for transmission. Results could support early warning and mitigation efforts to reduce the incidence of VS.

The GENCOV study aims to identify patient factors which affect COVID-19 severity and outcomes. Here, we aimed to evaluate patient characteristics, acute symptoms and their persistence, and associations with hospitalization. Participants were recruited at hospital sites across the Greater Toronto Area in Ontario, Canada. Patient-reported demographics, medical history, and COVID-19 symptoms and complications were collected through an intake survey. Regression analyses were performed to identify associations with outcomes including hospitalization and COVID-19 symptoms. In total, 966 responses were obtained from 1106 eligible participants (87% response rate) between November 2020 and May 2022. Increasing continuous age (aOR: 1.05 [95%CI: 1.01–1.08]) and BMI (aOR: 1.17 [95%CI: 1.10–1.24]), non-White/European ethnicity (aOR: 2.72 [95%CI: 1.22–6.05]), hypertension (aOR: 2.78 [95%CI: 1.22–6.34]), and infection by viral variants (aOR: 5.43 [95%CI: 1.45–20.34]) were identified as risk factors for hospitalization. Several symptoms including shortness of breath and fever were found to be more common among inpatients and tended to persist for longer durations following acute illness. Sex, age, ethnicity, BMI, vaccination status, viral strain, and underlying health conditions were associated with developing and having persistent symptoms. By improving our understanding of risk factors for severe COVID-19, our findings may guide COVID-19 patient management strategies by enabling more efficient clinical decision making.

The association of tuberculosis and type 2 diabetes mellitus has been a recognized re-emerging challenge in management of the convergence of the two epidemics. Though much of the literature has studied this association, there is less knowledge in the field of genetic diversities that might occur in strains infecting tuberculosis patients with and without diabetes. Our study focused on determining the extent of diversity of genotypes of Mycobacterium tuberculosis in both these categories of patients. We subjected 55 M. tuberculosis isolates from patients diagnosed with pulmonary TB with and without type 2 diabetes mellitus to whole-genome sequencing on Illumina Hi Seq platform. The most common lineage identified was lineage 1, the Indo-Oceanic lineage (n = 22%), followed by lineage 4, the Euro-American lineage (n = 18, 33%); lineage 3, the East-African Indian lineage (n = 13, 24%); and lineage 2, the East-Asian lineage (n = 1, 2%). There were no significant differences in the distribution of lineages in both diabetics and non-diabetics in the South Indian population, and further studies involving computational analysis and comparative transcriptomics are needed to provide deeper insights.

Hansen’s disease (HD) is an ancient disease, but more than 200,000 new cases were reported worldwide in 2019. Currently, there are not many satisfactory immunoassay methods for its diagnosis. We evaluated antibodies against Mce1A as a promising new serological biomarker. We collected plasma from new cases, contacts, and endemic controls in the city of Parnaíba and treated patients at Carpina, a former HD colony in Piauí state, northeastern Brazil. Receiver operating characteristic (ROC) curves were used to assess the assay thresholds, specificity and sensitivity of the IgA, IgM, and IgG antibodies against α-Mce1A by indirect ELISA and compared it with IgM anti-PGL-I and molecular diagnosis by quantitative polymerase chain reaction (qPCR). Venn diagrams were generated to represent the overlap in the antibody positivity pattern. Multivariate analysis was performed to assess the potential predictor of antibodies for the outcome of having an HD diagnosis. IgA and IgG were positive in 92.3 and 84% of patients, respectively. IgM was negative for all treated patients. IgG had a sensitivity and specificity of 94.7 and 100%, respectively. IgM-positive individuals had a 3.6 chance of being diagnosed with HD [OR = 3.6 (95% CI = 1.1–11.6); p = 0.028], while IgA-positive individuals had a 2.3 chance [OR = 2.3 (95% CI = 1.2–4.3); p = 0.005] compared to endemic controls. We found that the Mce1A antibody profile can be an excellent diagnostic method of HD. IgA is an ideal biomarker for confirming contact with the bacillus. IgM has potential in the detection of active disease. IgG antibodies confirm the performance of these serological markers in diagnosis and therapeutic follow-up.

Dengue fever remains a significant public health concern in many tropical and subtropical countries, and there is still a need for a system that can effectively combine global risk assessment with timely incidence forecasting. This research describes an integrated application called PICTUREE—Aedes, which can collect and analyze dengue-related data, display simulation results, and forecast outbreak incidence. PICTUREE—Aedes automatically updates global temperature and precipitation data and contains historical records of dengue incidence (1960–2012) and Aedes mosquito occurrences (1960–2014) in its database. The application utilizes a mosquito population model to estimate mosquito abundance, dengue reproduction number, and dengue risk. To predict future dengue outbreak incidence, PICTUREE—Aedes applies various forecasting techniques, including the ensemble Kalman filter, recurrent neural network, particle filter, and super ensemble forecast, which are all based on user-entered case data. The PICTUREE—Aedes’ risk estimation identifies favorable conditions for potential dengue outbreaks, and its forecasting accuracy is validated by available outbreak data from Cambodia.

Urinary tract infection (UTI) accounts for a significant morbidity and mortality across the world and is a leading cause for antibiotic prescriptions in the community especially in developing countries. Empirical choice of antibiotics for treatment of UTI is often discordant with the drug susceptibility of the etiologic agent. This study aimed to estimate the prevalence of community-acquired UTI caused by antibiotic resistant organisms. This was a cross-sectional study where urine samples were prospectively collected from 4,500 patients at the icddr,b diagnostic clinic in Dhaka, Bangladesh during 2016–2018. Urine samples were analyzed by standard culture method and the isolated bacteria were tested for antibiotic susceptibility by using disc diffusion method and VITEK-2. Descriptive statistics were used to estimate the prevalence of community acquired UTI (CA-UTI) by different age groups, sex, and etiology of infection. Relationship between the etiology of CA-UTI and age and sex of patients was analyzed using binary logistic regression analysis. Seasonal trends in the prevalence of CA-UTI, multi-drug resistant (MDR) pathogens and MDR Escherichia coli were also analyzed. Around 81% of patients were adults (≥18y). Of 3,200 (71%) urine samples with bacterial growth, 920 (29%) had a bacterial count of ≥1.0x105 CFU/ml indicating UTI. Women were more likely to have UTI compared to males (OR: 1.48, CI: 1.24–1.76). E. coli (51.6%) was the predominant causative pathogen followed by Streptococcus spp. (15.7%), Klebsiella spp. (12.1%), Enterococcus spp. (6.4%), Pseudomonas spp. (4.4%), coagulase-negative Staphylococcus spp. (2.0%), and other pathogens (7.8%). Both E. coli and Klebsiella spp. were predominantly resistant to penicillin (85%, 95%, respectively) followed by macrolide (70%, 76%), third-generation cephalosporins (69%, 58%), fluoroquinolones (69%, 53%) and carbapenem (5%, 9%). Around 65% of patients tested positive for multi-drug resistant (MDR) uropathogens. A higher number of male patients tested positive for MDR pathogens compared to the female patients (p = 0.015). Overall, 71% of Gram-negative and 46% of Gram-positive bacteria were MDR. The burden of community-acquired UTI caused by MDR organisms was high among the study population. The findings of the study will guide clinicians to be more selective about their antibiotic choice for empirical treatment of UTI and alleviate misuse/overuse of antibiotics in the community.

A large volume of freshwater is incorporated in the relatively fresh (salinity ~32-33) Pacific Ocean waters that are transported north through the Bering Strait relative to deep Atlantic salinity in the Arctic Ocean (salinity ~34.8). These freshened waters help maintain the halocline that separates cold Arctic surface waters from warmer Arctic Ocean waters at depth. The stable oxygen isotope composition of the Bering Sea contribution to the upper Arctic Ocean halocline was established as early as the late 1980's as having a δ18OV-SMOW value of approximately -1.1‰. More recent data indicates a shift to an isotopic composition that is more depleted in 18O (mean δ18O value ~-1.5‰). This shift is supported by a data synthesis of >1400 water samples (salinity from 32.5 to 33.5) from the northern Bering and Chukchi seas, from the years 1987-2020, which show significant year-to-year, seasonal and regional variability. This change in the oxygen isotope composition of water in the upper halocline is consistent with observations of added freshwater in the Canada Basin, and mooring-based estimates of increased freshwater inflows through Bering Strait. Here, we use this isotopic time-series as an independent means of estimating freshwater flux changes through the Bering Strait. We employed a simple end-member mixing model that requires that the volume of freshwater (including runoff and other meteoric water, but not sea ice melt) flowing through Bering Strait has increased by ~40% over the past two decades to account for a change in the isotopic composition of the 33.1 salinity water from a δ18O value of approximately -1.1‰ to a mean of -1.5‰. This freshwater flux change is comparable with independent published measurements made from mooring arrays in the Bering Strait (freshwater fluxes rising from 2000-2500 km3 in 2001 to 3000-3500 km3 in 2011).

Decreased sea ice cover in the northern Bering Sea has altered annual phytoplankton phenology owing to an expansion of open water duration and its impact on ocean stratification. Limitations of satellite remote sensing such as the inability to detect bloom activity throughout the water column, under ice, and in cloudy conditions dictate the need for shipboard based measurements to provide more information on bloom dynamics. In this study, we adapted remote sensing land cover classification techniques to provide a new means to determine bloom stage from shipboard samples. Specifically, we used multiyear satellite time series of chlorophyll a to determine whether in-situ blooms were actively growing or mature (i.e., past-peak) at the time of field sampling. Field observations of chlorophyll a and pheophytin (degraded and oxidized chlorophyll products) were used to calculate pheophytin proportions, i.e., (Pheophytin/(Chlorophyll a + Pheophytin)) and empirically determine whether the bloom was growing or mature based on remotely sensed bloom stages. Data collected at 13 north Bering Sea stations each July from 2013-2019 supported a pheophytin proportion of 28% as the best empirical threshold to distinguish a growing vs. mature bloom stage. One outcome was that low vs. high sea ice years resulted in significantly different pheophytin proportions in July; in years with low winter-to-spring ice, more blooms with growing status were observed, compared to later stage, more mature blooms following springs with abundant seasonal sea ice. The detection of growing blooms in July following low ice years suggests that changes in the timing of the spring bloom triggers cascading effects on mid-summer production.

BACKGROUND: Higher education institutions are adapting and innovating like never before to provide highly individualized learning environments for both traditional and non-traditional students. This seismic upheaval in the higher education landscape is being observed across the world. The present study aimed to evaluate the effectiveness of a blended learning approach on nursing students' self-directed learning readiness. MATERIALS AND METHODS: This study is a quasi-experimental approach in which a non-equivalent control group was used in a post-test design. A comparison was carried out with two separate semester cohort students representing the control and intervention groups which had 24 and 30 students, respectively. This study included first-year nursing students that enrolled in a course called “Anatomy and Physiology” course of nursing education at a private university. The control group received all their teaching face-to-face, and the intervention group used information technology and prescribed activities in their online e-book. The self-directed learning readiness (SDLR) tool measures the learners' readiness in self-directed learning in both groups. This scale comprises three subscales which are “self-management,” “desire for learning,” and “self-control.” An independent-samples t-test was conducted to compare self-directed learning readiness in the control and intervention groups. Data were analyzed using IBM SPSS Statistics 25 software to measure the independent t-test. RESULTS: The self-directed readiness scores were significantly higher in the intervention group with P = 0.019. The intervention group showed a higher mean value on the subscales of self-management and self-control, which demonstrated a significant difference with P values of 0.018 and 0.028, respectively. The subscale desire for learning was insignificant with a P value of 0.166. CONCLUSION: This study concluded that the overall results demonstrate that incorporating blended learning using e-books for anatomy and physiology courses in nursing education can contribute to students' readiness for self-directed learning. Specifically, the blended learning teaching and learning strategy had a positive impact on nursing students' capacity for self-management and self-control.

Exacerbation due to antimicrobial-drug-resistant bacteria among chronic obstructive pulmonary disease (AECOPD) patients contributes to mortality and morbidity. We examined the prevalence of the bacterial organisms and trends in drug resistance in AECOPD. In this retrospective study, between January 2016 to December 2020, among 3027 AECOPD patients, 432 (14.3%) had bacteria isolated. The regression and generalized estimating equations (GEE) were used for trends in the resistance patterns over five years, adjusting for age, gender, and comorbidities. Klebsiella pneumoniae (32.4%), Pseudomonas aeruginosa (17.8%), Acinetobacter baumannii (14.4%), Escherichia coli (10.4%), and Staphylococcus aureus (2.5%) were common. We observed high levels of drug resistance in AECOPD patients admitted to ICU (87.8%) and non-ICU (86.5%). A Cox proportional hazard analysis, observed infection with Acinetobacter baumannii and female sex as independent predictors of mortality. Acinetobacter baumannii had 2.64 (95% confidence interval (CI): 1.08–6.43) higher odds of death, compared to Klebsiella pneumoniae. Females had 2.89 (95% CI: 1.47–5.70) higher odds of death, compared to males. A high proportion of bacterial AECOPD was due to drug-resistant bacteria. An increasing trend in drug resistance was observed among females.

Declines in seasonal sea ice in polar regions have stimulated projections of how primary production has shifted in response to greater light penetration over a longer open water season. Despite the limitations of remotely sensed observations in an often cloudy environment, remote sensing data provide strong indications that surface chlorophyll biomass has increased (since 2000) as sea ice has declined in the Pacific Arctic region. We present here shipboard measurements of chlorophyll-a that have been made annually in July since 2000 from the Distributed Biological Observatory (DBO) stations in the Bering Strait region. This time series as well as shipboard observations made in other months since the late 1980s implicate complexities that intrude on a simple expectation that, as open water periods increase, the production and biomass of phytoplankton will increase predictably. These shipboard observations indicate that there have not been sharp increases in chlorophyll-a, for either maxima observed in the water column or integrated over the whole water column, at the DBO stations over a time-series extending for as long as 20 years coinciding with seasonal sea ice declines. On the other hand, biomass may be increasing in other months: we provide a shipboard confirmation of a fall bloom in October as wind mixing introduced nutrients back into the upper water column. The productive DBO stations may be at a high enough production already that additional enhancements in chlorophyll-a biomass should not be expected, but our time-series record does not exclude the possibility that additional enhanced production may be present in other areas outside the DBO station grid. These findings may also reflect limitations imposed by nutrient cycling and water column structure. The increasing freshwater component of waters flowing through the Bering Strait is likely associated with increased stratification that limits the potential change in biological production associated with decreases in seasonal sea ice persistence.

Rhizoctonia solani, causing Rhizoctonia crown and root rot, is a major risk to sugar beet (Beta vulgaris L.) cultivation. The development of resistant varieties accelerated by marker-assisted selection is a priority of breeding programs. We report the identification of a single-nucleotide polymorphism (SNP) marker linked to Rhizoctonia resistance using restriction site-associated DNA (RAD) sequencing of two geographically discrete sets of plant materials with different degrees of resistance/susceptibility to enable a wider selection of superior genotypes. The variant calling pipeline utilized SAMtools for variant calling and the resulting raw SNPs from RAD sequencing (15,988 and 22,439 SNPs) were able to explain 13.40% and 25.45% of the phenotypic variation in the two sets of material from different sources of origin, respectively. An association analysis was carried out independently on both the datasets and mutually occurring significant SNPs were filtered depending on their contribution to the phenotype using principal component analysis (PCA) biplots. To provide a ready-to-use marker for the breeding community, a systematic molecular validation of significant SNPs distributed across the genome was undertaken to combine high-resolution melting, Sanger sequencing, and rhAmp SNP genotyping. We report that RsBv1 located on Chromosome 6 (9,000,093 bp) is significantly associated with Rhizoctonia resistance (p < 0.01) and able to explain 10% of the phenotypic disease variance. The related SNP assay is thus ready for marker-assisted selection in sugar beet breeding for Rhizoctonia resistance.

Epizootic hemorrhagic disease (EHD) is an insect-transmitted viral disease of wild and domestic ruminants. It was first described following a 1955 epizootic in North American white-tailed deer (Odocoileus virginianus), a species which is highly susceptible to the causative agent of EHD, epizootic hemorrhagic disease virus (EHDV). EHDV has been detected globally across tropical and temperate regions, largely corresponding to the presence of Culicoides spp. biting midges which transmit the virus between ruminant hosts. It regularly causes high morbidity and mortality in wild and captive deer populations in endemic areas during epizootics. Although cattle historically have been less susceptible to EHDV, reports of clinical disease in cattle have increased in the past two decades. There is a pressing need to identify new methods to prevent and mitigate outbreaks and reduce the considerable impacts of EHDV on livestock and wildlife. This review discusses recent research advancements towards the control of EHDV, including the development of new investigative tools and progress in basic and applied research focused on virus detection, disease mitigation, and vector control. The potential impacts and implications of these advancements on EHD management are also discussed.

The galaxy cluster A746 (z = 0.214), featuring a double radio relic system, two isolated radio relics, a possible radio halo, disturbed V-shaped X-ray emission, and intricate galaxy distributions, is a unique and complex merging system. We present a weak-lensing analysis of A746 based on wide-field imaging data from Subaru/Hyper Suprime-Cam observations. The mass distribution is characterized by a main peak, which coincides with the center of the X-ray emission. At this main peak, we detect two extensions toward the north and west tracing the cluster galaxy and X-ray distributions. Despite the ongoing merger, our estimate of the A746 global mass M 500 = 4.4 ± 1.0 × 1014 M ⊙ is consistent with the previous results from Sunyaev-Zel'dovich and X-ray observations. We conclude that reconciling the distributions of mass, galaxies, and intracluster medium with the double radio relic system and other radio features remains challenging.