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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.

Upon researching predictive models related to West Nile virus disease, it is discovered that there are numerous parameters and extensive information in most models, thus contributing to unnecessary complexity. Another challenge frequently encountered is the lead time, which refers to the period for which predictions are made and often is too short. This paper addresses these issues by introducing a parsimonious method based on ICC curves, offering a logistic distribution model derived from the vector-borne SEIR model. Unlike existing models relying on diverse environmental data, our approach exclusively utilizes historical and present infected human cases (number of new cases). With a year-long lead time, the predictions extend throughout the 12 months, gaining precision as new data emerge. Theoretical conditions are derived to minimize Bayesian loss, enhancing predictive precision. We construct a Bayesian forecasting probability density function using carefully selected prior distributions. Applying these functions, we predict month-specific infections nationwide, rigorously evaluating accuracy with probabilistic metrics. Additionally, HPD credible intervals at 90%, 95%, and 99% levels is performed. Precision assessment is conducted for HPD intervals, measuring the proportion of intervals that does not include actual reported cases for 2020–2022.

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 .

Japanese encephalitis virus (JEV) is associated with encephalitis in humans and reproductive and neurological illness in pigs. JEV has expanded beyond its native distribution in southeast Asia, with identifications in Europe (2010) and Africa (2016), and most recently, its spread into mainland Australia (2021−2022). The introduction of JEV into the United States (US) is a public health risk, and could also impact animal health and the food supply. To efficiently and cost-effectively manage risk, a better understanding of how and where diseases will be introduced, transmitted, and spread is required. To achieve this objective, we updated our group's previous qualitative risk assessment using an established semi-quantitative risk assessment tool (MINTRISK) to compare the overall rate of introduction and risk, including impacts, of JEV in seven US regions. The rate of introduction from the current region of distribution was considered negligible for the Northeast, Midwest, Rocky Mountain, West, Alaska, and Hawaii regions. The South region was the only region with a pathway that had a non-negligible rate of introduction; infected mosquito eggs and larvae introduced via imported used tires (very low; 95% uncertainty interval (UI) = negligible to high). The overall risk estimate for the South was very high (95% UI = very low to very high). Based on this risk assessment, the South region should be prioritized for surveillance activities to ensure the early detection of JEV. The assumptions used in this risk assessment, due to the lack of information about the global movement of mosquitoes, number of feral pigs in the US, the role of non-ardeid wild birds in transmission, and the magnitude of the basic reproduction ratio of JEV in a novel region, need to be fully considered as these impact the estimated probability of establishment.

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.

Jie Deng,1 Lorne M Golub,2 Hsi-Ming Lee,2 Veena Raja,2 Francis Johnson,3 Allan Kucine,4 Wonsae Lee,5 Tian-Min Xu,1 Ying Gu6 1Department of Orthodontics, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing, 100081, People’s Republic of China; 2Department of Oral Biology and Pathology, School of Dental Medicine, Stony Brook University, Stony Brook, NY, 11794, USA; 3Department of Chemistry and Pharmacological Sciences, School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA; 4Department of Oral & Maxillofacial Surgery, School of Dental Medicine, Stony Brook University, Stony Brook, NY, 11794, USA; 5Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, 11794, USA; 6Department of General Dentistry, School of Dental Medicine, Stony Brook University, Stony Brook, NY, 11794, USACorrespondence: Jie DengDepartment of Orthodontics, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, 22 Zhongguancun South Avenue, Haidian District, Beijing, 100081, People’s Republic of ChinaTel +1 631 632-3172Fax +1 631 632-9705Email jie.deng917@gmail.comTian-Min Xu Email tmxuortho@163.comPurpose: Clinically, it is challenging to manage diabetic patients with periodontitis. Biochemically, both involve a wide range of inflammatory/collagenolytic conditions which exacerbate each other in a “bi-directional manner.” However, standard treatments for this type of periodontitis rely on reducing the bacterial burden and less on controlling hyper-inflammation/excessive-collagenolysis. Thus, there is a crucial need for new therapeutic strategies to modulate this excessive host response and to promote enhanced resolution of inflammation. The aim of the current study is to evaluate the impact of a novel chemically-modified curcumin 2.24 (CMC2.24) on host inflammatory response in diabetic rats.Methods: Type I diabetes was induced by streptozotocin injection; periodontal breakdown then results as a complication of uncontrolled hyperglycemia. Non-diabetic rats served as controls. CMC2.24, or the vehicle-alone, was administered by oral gavage daily for 3 weeks to the diabetics. Micro-CT was used to analyze morphometric changes and quantify bone loss. MMPs were analyzed by gelatin zymography. Cell function was examined by cell migration assay, and cytokines and resolvins were measured by ELISA.Results: In this severe inflammatory disease model, administration of the pleiotropic CMC2.24 was found to normalize the excessive accumulation and impaired chemotactic activity of macrophages in peritoneal exudates, significantly decrease MMP-9 and pro-inflammatory cytokines to near normal levels, and markedly increase resolvin D1 (RvD1) levels in the thioglycolate-elicited peritoneal exudates (tPE). Similar effects on MMPs and RvD1 were observed in the non-elicited resident peritoneal washes (rPW). Regarding clinical relevance, CMC2.24 significantly inhibited the loss of alveolar bone height, volume and mineral density (ie, diabetes-induced periodontitis and osteoporosis).Conclusion: In conclusion, treating hyperglycemic diabetic rats with CMC2.24 (a tri-ketonic phenylaminocarbonyl curcumin) promotes the resolution of local and systemic inflammation, reduces bone loss, in addition to suppressing collagenolytic MMPs and pro-inflammatory cytokines, suggesting a novel therapeutic strategy for treating periodontitis complicated by other chronic diseases.Keywords: hyperglycemia, periodontitis, matrix metalloproteinases, inflammation, resolvins, host-modulatory therapy

ABSTRACT: Objectives: Bacterial antimicrobial resistance is a serious global public-health threat. Intestinal commensal drug-resistant bacteria have been suggested as an important reservoir of antimicrobial resistance genes (ARGs), which may be acquired via food. We aimed to identify risk factors associated with faecal carriage of drug-resistant commensal Escherichia coli among healthy adults focused on their dietary habits. Methods: We conducted a cross-sectional study targeting healthy adult volunteers in a college community. Faecal samples and questionnaires were obtained from 113 volunteers. We conducted backward elimination logistic regression and least absolute shrinkage and selection operator (LASSO) methods to identify risk factors. Results: We analysed responses from 81 of 113 volunteers who completed the questionnaire. The logistic regression and LASSO methods identified red meat consumption to be associated with an increased risk [OR = 6.13 (95% CI 1.83–24.2) and 1.82, respectively] and fish consumption with a reduced risk [OR = 0.27 (95% CI 0.08–0.85) and 0.81] for carriage of multidrug-resistant (MDR) E. coli, adjusted for biological sex, employment status, frequently used supermarket and previous travel. Conclusion: Dietary habits are associated with risk of faecal carriage of MDR E. coli. This study supports the growing evidence that food may be an important source of ARGs present in human commensal E. coli.

Mycobacterium tuberculosis (Mtb), which is responsible for more than a million deaths annually, uses lipids as the source of carbon and energy for its survival in the latent phase of infection. Mtb cannot synthesize all of the lipid molecules required for its growth and pathogenicity. Therefore, it relies on transporters such as the mammalian cell entry (Mce) complexes to import lipids from the host across the cell wall. Despite their importance for the survival and pathogenicity of Mtb, information on the structural properties of these proteins is not yet available. Each of the four Mce complexes in Mtb (Mce1–4) comprises six substrate-binding proteins (SBPs; MceA–F), each of which contains four conserved domains (N-terminal transmembrane, MCE, helical and C-terminal unstructured tail domains). Here, the properties of the various domains of Mtb Mce1A and Mce4A, which are involved in the import of mycolic/fatty acids and cholesterol, respectively, are reported. In the crystal structure of the MCE domain of Mce4A (MtMce4A39–140) a domain-swapped conformation is observed, whereas solution studies, including small-angle X-ray scattering (SAXS), indicate that all Mce1A and Mce4A domains are predominantly monomeric. Further, structural comparisons show interesting differences from the bacterial homologs MlaD, PqiB and LetB, which form homohexamers when assembled as functional transporter complexes. These data, and the fact that there are six SBPs in each Mtb mce operon, suggest that the MceA–F SBPs from Mce1–4 may form heterohexamers. Also, interestingly, the purification and SAXS analysis showed that the helical domains interact with the detergent micelle, suggesting that when assembled the helical domains of MceA–F may form a hydrophobic pore for lipid transport, as observed in EcPqiB. Overall, these data highlight the unique structural properties of the Mtb Mce SBPs.

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.

Di Mei,1,&ast; Xiaolong Guo,2,&ast; Yirong Wang,1 Xiaofei Huang,1 Li Guo,1 Pengfei Zou,3 Delong Ge,1 Xinxin Wang,1 Wenhui Lee,4 Tongyi Sun,1 Zhiqin Gao,1 Yuanyuan Gao3 1School of Life Science and Technology, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biopharmaceuticals, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 2School of Basic Medicine, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 3School of Pharmacy, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of China; 4Key Laboratory of Animal Models and Human Disease Mechanism, Institute of Zoology, Kunming, Yunnan, 650233, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Zhiqin GaoSchool of Life Science and Technology, Shandong Key Laboratory of Proteins and Peptides Pharmaceutical Engineering, Shandong Universities Key Laboratory of Biopharmaceuticals, Weifang Medical University, Weifang, Shandong, 261053, People’s Republic of ChinaTel +86 5368462066Email zhiqingao2013@163.comYuanyuan GaoSchool of Pharmacy, Weifang Medical University, Baotong Road, Weifang, Shandong Province, 261053, People’s Republic of ChinaTel +86 536 846 2067Email yyg20062006@126.comBackground: The treatment of Staphylococcus aureus (S. aureus)-infected wounds is difficult. It causes extreme pain to tens of thousands of patients and increases the cost of medical care. The antimicrobial peptide OH-CATH30 (OH30) has a good killing activity against S. aureus and can play a role in accelerating wound healing and immune regulation. Therefore, it shows great potential for wound healing.Purpose: The aim of this study was to overcome the short half-life and easy enzymolysis of OH30 by using graphene oxide conjugated with polyethylene glycol to load OH30 (denoted as PGO-OH30), as well as to evaluate its effect on wounds infected by S. aureus.Methods: PGO-OH30 nanoparticles were prepared by π–π conjugation and characterized. Their cell cytotoxicity, cell migration, infectious full-thickness dermotomy models, and histopathology were evaluated.Results: Characterization and cytotoxicity experiments revealed that the PGO-OH30 drug-delivery system had good biocompatibility and excellent drug-delivery ability. Cell-migration experiments showed that PGO-OH30 could promote the migration of human immortalized keratinocytes (HaCaT) cells compared with the control group (P< 0.05). In a mouse model of skin wound infection, PGO-OH30 accelerated skin-wound healing and reduced the amount of S. aureus in wounds compared with the control group (P< 0.05). In particular, on day 7, the number of S. aureus was 100 times lower in the PGO-OH30 group than in the control group.Conclusion: The PGO-OH30 drug-delivery system had good biocompatibility and excellent drug-delivery ability, indicating its good therapeutic effect on a skin wound-infection model.Keywords: OH-CATH30, bacterial infection, graphene oxide, skin wound

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.

Khalil Issa,1,* Ralph Abi Hachem,1,* Alexander Gordee,2 Tracy Truong,2 Richard Pfohl,3 Barry Doublestein,4 Walter Lee1 1Department of Head and Neck Surgery & Communication Sciences, Duke University Health System, Durham, NC, USA; 2Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA; 3School of Business, LeTourneau University, Longview, TX, USA; 4School of Business & Leadership, Regent University, Virginia Beach, VA, USA*These authors contributed equally to this workCorrespondence: Walter LeeDepartment of Head and Neck Surgery & Communication Sciences, Duke University Health System, Room 3532 - Blue Zone, Durham, NC, 27710, USATel +1 919-681-8449Fax +1 919-613-6524Email Walter.lee@duke.eduPurpose: To analyze self and 360-evaluation scores of the professionalism intelligence model domains within an academic Otolaryngology-Head and Neck Surgery Department.Methods: A leadership course was introduced within the Department of Head and Neck Surgery & Communication Sciences at Duke University Medical Center. A 360 evaluation assessing domains of the professional intelligence model was recorded for all participants. Participant demographics included gender (male vs female), generation group (generation Y vs older generations) and physician status of participants (physician vs non-physician). Differences in mean self-scores were modeled using linear regression. When analyzing the evaluator scores, gaps were defined as self-score minus evaluator-score for each member of a participant’s evaluator groupings (supervisor, peer, and direct report). Two types of linear mixed models were fit with a random intercept to account for the correlated gaps in the same participant.Results: Scores of 50 participants and 394 evaluators were analyzed. The average age was 40.6 (standard deviation 9.3) years, and 50% (N=25) of participants were females. Physicians accounted for 36% (N=18) of the cohort, and 61% (N=11) of physicians were residents. Physicians scored themselves lower than non-physicians when assessing leadership intelligence, interpersonal relations, empathy, and focused thinking. On average, participants under-rated themselves compared to their evaluators with direct reports giving higher scores than managers and peers. When compared with generation Y, older generations tended to rate themselves lower than their peers and managers in cognitive intelligence. No significant association was observed between gender and any scores.Conclusion: Participants rate themselves lower on average than their evaluators. This work is important in understanding how perceived leadership qualities are assessed and developed within an academic surgical department. Finally, the results presented could serve as a model to address the gap between self- and other-perceptions of defined leadership virtues in future leadership development activities.Keywords: leadership intelligence, healthcare workers, emotional intelligence, cognitive intelligence, physicians

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.

Abstract Biting midges of the genus Culicoides transmit disease-causing agents resulting in a significant economic impact on livestock industries in many parts of the world. Localized control efforts, such as removal of larval habitat or pesticide application, can be logistically difficult, expensive and ineffective if not instituted and maintained properly. With these limitations, a population-level approach to the management of Culicoides midges should be investigated as a means to replace or supplement existing control strategies. Next-generation control methods such as Wolbachia- and genetic-based population suppression and replacement are being investigated in several vector species. Here we assess the feasibility and applicability of these approaches for use against biting midges. We also discuss the technical and logistical hurdles needing to be addressed for each method to be successful, as well as emphasize the importance of addressing community engagement and involving stakeholders in the investigation and development of these approaches.

The performance of data-driven models depends on training samples. For accurately predicting dengue fever cases, historical incidence data are inadequate in many locations. This work aims to enhance temporally limited dengue case data by methodological addition of epidemically relevant case data from nearby locations as predictors (features). A novel framework is presented for windowing incidence data and computing time-shifted correlation-based metrics to quantify feature relevance. The framework ranks incidence data of adjacent locations around a target by combining metrics based on correlation, spatial distance, and local prevalence. Recurrent neural network models achieve up to 33.6% accuracy improvement on average using the proposed method. These models achieve mean absolute error (MAE) values as low as 0.128 on [0, 1] normalized incidence data for a municipality with the highest dengue prevalence in Brazil’s Espirito Santo. When predicting aggregate cases over geographical ecoregions, the models improve by 16.5%, using only 6.5% of ranked incidence data. This paper also presents two correlation window allocation methods: fixed-size and outbreak detection. Both perform comparably well, although the outbreak detection method uses less data for computations. The proposed framework is generalized, and it can be used to improve time-series predictions of many spatiotemporal datasets.

Dengue fever is an acute mosquito-borne viral infection that results in a heavy social burden in many tropical and subtropical regions. Accurate forecasts of dengue outbreak allow the local health officials to take proactive action such as positioning mosquito control equipment or preparing medical resources. We developed a new model for dengue outbreak estimation and forecast that adopts the vector-borne disease model SEIR-SEI with compartments Susceptible-Exposed-Infectious-Recovered (for host) and Susceptible-Exposed-Infectious (for vector) into the ensemble Kalman filtering (EnKF) assimilation method. The SEIR-SIR-EnKF model was first validated using synthetic dengue outbreak in twin experiments. Then, the model produced good performance when applied to estimate and forecast the dengue outbreak dynamics with real historical time-series cases in 3 different cities. Furthermore, we compared the accuracy of the real-time predictions between SEIR-SEI-EnKF model, SEIR-EnKF model, and SIR-EnKF model; we found the SEIR-SEI-EnKF model had the most accurate predictions.

Abstract Current diagnostic tests for tuberculosis (TB) are not able to predict reactivation disease progression from latent TB infection (LTBI). The main barrier to predicting reactivation disease is the lack of our understanding of host biomarkers associated with progression from latent infection to active disease. Here, we applied an immune-based gene expression profile by NanoString platform to identify whole blood markers that can distinguish active TB from other lung diseases (OPD), and that could be further evaluated as a reactivation TB predictor. Among 23 candidate genes that differentiated patients with active TB from those with OPD, nine genes (CD274, CEACAM1, CR1, FCGR1A/B, IFITM1, IRAK3, LILRA6, MAPK14, PDCD1LG2) demonstrated sensitivity and specificity of 100%. Seven genes (C1QB, C2, CCR2, CCRL2, LILRB4, MAPK14, MSR1) distinguished TB from LTBI with sensitivity and specificity between 82 and 100%. This study identified single gene candidates that distinguished TB from OPD and LTBI with high sensitivity and specificity (both > 82%), which may be further evaluated as diagnostic for disease and as predictive markers for reactivation TB.

Abstract Background The number of patients undergoing autologous haematopoietic cell transplant (HCT) is growing, but little is known about the factors that predict adverse outcomes. Low muscle mass and obesity are associated with disability and premature mortality in individuals with non‐malignant diseases and may predict outcomes after autologous HCT. Methods This was a retrospective cohort study of 320 patients who underwent autologous HCT for Hodgkin or non‐Hodgkin lymphoma between 2009 and 2014. Sarcopenia {skeletal muscle index male:

Background: Evidence on how weight loss correlates to health-related quality-of-life (HRQOL) among obese breast cancer (BC) patients is limited. We aimed to evaluate associations between weight changes and HRQOL. Methods: We included 993 obese women with stage I-II-III BC from CANTO, a multicenter, prospective cohort collecting longitudinal, objectively-assessed anthropometric measures and HRQOL data (NCT01993498). Associations between weight changes (±5% between diagnosis and post-treatment [shortly after completion of surgery, adjuvant chemo- or radiation-therapy]) and patient-reported HRQOL (EORTC QLQ-C30/B23) were comprehensively evaluated. Changes in HRQOL and odds of severely impaired HRQOL were assessed using multivariable generalized estimating equations and logistic regression, respectively. Results: 14.1% women gained weight, 67.3% remained stable and 18.6% lost weight. Significant decreases in functional status and exacerbation of symptoms were observed overall post-treatment. Compared to gaining weight or remaining stable, obese women who lost weight experienced less of a decline in HRQOL, reporting better physical function (mean change [95%CI] for gain, stability and loss: −12.9 [-16.5,-9.3], −6.9 [-8.2,-5.5] and −6.2 [-8.7,-3.7]; pinteraction[weight-change-by-time] = 0.006), less dyspnea (+18.9 [+12.3,+25.6], +9.2 [+6.5,+11.9] and +3.2 [-1.0,+7.3]; pinteraction = 0.0003), and fewer breast symptoms (+22.1 [+16.8,+27.3], +18.0 [+15.7,+20.3] and +13.4 [+9.0,+17.2]; pinteraction = 0.044). Weight loss was also significantly associated with reduced odds of severe pain compared with weight gain (OR [95%CI] = 0.51 [0.31–0.86], p = 0.011) or stability (OR [95%CI] = 0.62 [0.41–0.95], p = 0.029). No associations between weight loss and worsening of other physical or psychosocial parameters were found. Conclusions: This large contemporary study suggests that weight loss among obese BC patients during early survivorship was associated with better patient-reported outcomes, without evidence of worsened functionality or symptomatology in any domain of HRQOL.

Abstract Community‐acquired urinary tract infections (UTIs) are one of the most common bacterial infections worldwide. Escherichia coli is the most common cause of community‐acquired UTI. In general, UTI results from E. coli in the intestine that enters the bladder via the urethra. However, whether these E. coli strains that cause UTI represent members of the intestinal commensal E. coli or a distinct subgroup of pathogenic E. coli remains unestablished. Here, we analyzed E. coli isolates from fecal samples of healthy volunteers and urine samples of UTI patients obtained from a university‐affiliated health center. The E. coli isolates were genotyped by multilocus sequence typing (MLST). From May to October 2018, we analyzed 89 E. coli isolates from 76 (75%) rectal swabs from 113 unique healthy volunteers. We also analyzed 106 (27%) E. coli isolates from 398 unique urine samples collected between August and October 2018. Fecal and urine E. coli isolates each contained 31 distinct sequence types (STs). Nine STs were shared by fecal and urine E. coli isolates, which accounted for approximately 50% of urine isolates typed by MLST. Among the shared genotypes, ST10 and ST131 were significantly more frequently found in fecal samples, whereas ST95 and ST127 were significantly more frequently recovered from UTI samples. ST73 was found only among urine samples. These E. coli genotypes clustered and fluctuated over time. These observations suggest that E. coli genotypes found to cause UTI transiently colonize the intestine and that their primary reservoir may reside outside of the human intestine.

Abstract Background Antimicrobial resistance is a serious public health problem. Fecal carriage of drug-resistant bacteria has been suggested as an important source of antimicrobial resistant genes (ARGs). We aimed to identify risk factors associated with fecal carriage of drug-resistant commensal Escherichia coli among healthy adult population. Methods We conducted a systematic review and meta-analysis following the PRISMA guideline. We identified observational studies published from 2014 to 2019 through PubMed, Embase, and Web of Science. Studies were eligible if they investigated and reported risk factors and accompanying measure of associations for fecal carriage of drug-resistant E. coli for healthy population aged 18-65. Data on risk factors assessed in three or more studies were extracted. Results Fifteen of 395 studies involving 11480 healthy individuals were included. The pooled prevalence of drug-resistant Enterobacteriaceae was 14% (95% confidence interval [CI] 8-23%). Antimicrobial use within the 12 months prior to stool culture (odds ratio [OR] 1.84 [95%CI 1.35-2.51]), diarrhea symptoms (OR 1.56 [95%CI 1.09-2.25]), travel to India (OR 4.15 [95%CI 2.54-6.78]), and vegetarian diet (OR 1.60 [95%CI 1.00(1.0043)-2.56(2.5587)]) were associated with increased risk of fecal carriage of drug-resistant E. coli. Among travellers, antimicrobial use (OR 2.81 [95%CI 1.47-5.36]), diarrhea symptoms (OR 1.65 [95%CI 1.02-2.68]), travel to India (OR 3.80 [95%CI 2.23-6.47]), and vegetarian diet (OR 1.92 [95%CI 1.13-3.26]) were associated with increased risk. Among general adult population, antimicrobial use (OR 1.51 [95%CI 1.17-1.94]), diarrhea symptoms (OR 1.53 [95%CI 1.27-1.84]), and travel to Southeast Asia (OR 1.67 [95%CI 1.02-2.73]) were associated with the increased risk of drug-resistant E. coli carriage. Conclusions The findings indicate that dietary habit as well as past antimicrobial use and travel to high-risk country are associated with the risk of fecal carriage of drug-resistant commensal E. coli.

As an emerging infectious disease, the 2019 coronavirus disease (COVID-19) has developed into a global pandemic. During the initial spreading of the virus in China, we demonstrated the ensemble Kalman filter performed well as a short-term predictor of the daily cases reported in Wuhan City. Second, we used an individual-level network-based model to reconstruct the epidemic dynamics in Hubei Province and examine the effectiveness of non-pharmaceutical interventions on the epidemic spreading with various scenarios. Our simulation results show that without continued control measures, the epidemic in Hubei Province could have become persistent. Only by continuing to decrease the infection rate through 1) protective measures and 2) social distancing can the actual epidemic trajectory that happened in Hubei Province be reconstructed in simulation. Finally, we simulate the COVID-19 transmission with non-Markovian processes and show how these models produce different epidemic trajectories, compared to those obtained with Markov processes. Since recent studies show that COVID-19 epidemiological parameters do not follow exponential distributions leading to Markov processes, future works need to focus on non-Markovian models to better capture the COVID-19 spreading trajectories. In addition, shortening the infectious period via early case identification and isolation can slow the epidemic spreading significantly.

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.