Search

Escherichia coli has been attributed to playing a major role in a cascade of events that affect the prevalence and severity of uterine disease in cattle. The objectives of this project were to (i) define the association between the prevalence of specific antimicrobial resistance and virulence factor genes in E. coli with the clinical status related to uterine infection, (ii) identify the genetic relationship between E. coli isolates from cows with diarrhea, with mastitis, and with and without metritis, and (iii) determine the association between the phenotypic and genotypic antimicrobial resistance identified on the E. coli isolated from postpartum cattle. Bacterial isolates (n = 148) were obtained from a larger cross-sectional study. Cows were categorized into one of three clinical groups before enrollment: metritis, cows with purulent discharge, and control cows. For genomic comparison, public genomes (n = 130) from cows with diarrhea, mastitis, and metritis were included in a genome-wide association study, to evaluate differences between the drug classes or the virulence factor category among clinical groups. A distinct E. coli genotype associated with metritis could not be identified. Instead, a high genetic diversity among the isolates from uterine sources was present. A virulence factor previously associated with metritis (fimH) using PCR was not associated with metritis. There was moderate accuracy for whole-genome sequencing to predict phenotypic resistance, which varied depending on the antimicrobial tested. Findings from this study contradict the traditional pathotype classification and the unique intrauterine E. coli genotype associated with metritis in dairy cows.IMPORTANCEMetritis is a common infectious disease in dairy cattle and the second most common reason for treating a cow with antimicrobials. The pathophysiology of the disease is complex and is not completely understood. Specific endometrial pathogenic Escherichia coli have been reported to be adapted to the endometrium and sometimes lead to uterine disease. Unfortunately, the specific genomic details of the endometrial-adapted isolates have not been investigated using enough genomes to represent the genomic diversity of this organism to identify specific virulence genes that are consistently associated with disease development and severity. Results from this study provide key microbial ecological advances by elucidating and challenging accepted concepts for the role of Intrauterine E. coli in metritis in dairy cattle, especially contradicting the existence of a unique intrauterine E. coli genotype associated with metritis in dairy cows, which was not found in our study.

PURPOSE: Treatment guidelines for gender-affirming hormone therapy with estrogen (GAHT-E) recommend specific dosing regimens based on limited data. Well-controlled efficacy trials are essential to tailoring treatment to patient goals as the guidelines recommend. The goal of this study was to take a foundational step toward designing community-centered effectiveness trials for gender-diverse individuals seeking GAHT-E. METHODS: Our team developed a cross-sectional survey based on broad clinical experience and consultation with our community advisory board. The survey included 60 items covering demographics, transition history, goals and priorities for treatment, indicators of treatment success, sexual function goals, and future research priorities. The survey was distributed during the summer of 2021, primarily through social networks designed for gender-expansive individuals seeking treatment with estrogen. RESULTS: A total of 1270 individuals completed the survey. Overall treatment goals most frequently rated extremely important or very important were the following: (1) improved satisfaction with life (81%), (2) appearing more feminine (80%), (3) appearing less masculine (77%), (4) improved mental health (76%), and (5) being seen as your true gender by others (75%). The three body characteristics most frequently rated highest priority or high priority among changes were the following: (1) facial hair (85%), (2) breast shape or size (84%), and (3) body shape (80%). The highest-rated research priority was comparing feminization with different routes of estrogen administration. CONCLUSION: The goals and experiences of individuals seeking GAHT-E are diverse. Future clinical trials of GAHT-E should be grounded in the needs and priorities of community stakeholders.

A 16-year-old trans female patient presented to our Gender Health Program for gender-affirming care. Her intake evaluation revealed signs of hepatocellular injury and fibrosis concerning for metabolic dysfunction-associated steatohepatitis (MASH) and she was referred to a Pediatric Hepatologist. Subsequent delays in initiating hormone therapy caused a decline in her mental health, and she began experiencing suicidal ideations. Gender-affirming hormone therapy has been shown to significantly reduce depressive symptoms and suicidal ideations in transgender and gender diverse youth, and studies in animal models suggest improvement in hepatic steatosis in response to estrogen. A multidisciplinary meeting with Gender Health, Psychiatry, and Hepatology appropriately weighed the benefits of life-saving hormone therapy and the possibility of an improvement in her comorbid liver condition with the risk of further liver damage from estrogen therapy. The teams and the patient agreed to start estradiol with subsequent resolution of laboratory and radiographic evidence of MASH.

BackgroundFecal microbiota transplantation (FMT) is increasingly used for gastrointestinal and extra-gastrointestinal diseases in veterinary medicine. However, its effects on immune responses and possible adverse events have not been systematically investigated.Hypothesis/objectivesDetermine the short-term safety profile and changes in the peripheral immune system after a single FMT administration in healthy dogs.AnimalsTen client-owned, clinically healthy dogs as FMT recipients, and 2 client-owned clinically healthy dogs as FMT donors.MethodsProspective non-randomized clinical trial. A single rectal enema of 5 g/kg was given to clinically healthy canine recipients. During the 28 days after FMT administration, owners self-reported adverse events and fecal scores. On Days 0 (baseline), 1, 4, 10, and 28 after FMT, fecal and blood samples were collected. The canine fecal dysbiosis index (DI) was calculated using qPCR.ResultsNo significant changes were found in the following variables: CBC, serum biochemistry, C-reactive protein, serum cytokines (interleukins [IL]-2, -6, -8, tumor necrosis factor [TNF]-α), peripheral leukocytes (B cells, T cells, cluster of differentiation [CD]4+ T cells, CD8+ T cells, T regulatory cells), and the canine DI. Mild vomiting (n = 3), diarrhea (n = 4), decreased activity (n = 2), and inappetence (n = 1) were reported, and resolved without intervention.Conclusions and clinical importanceFecal microbiota transplantation did not significantly alter the evaluated variables and recipients experienced minimal adverse events associated with FMT administration. Fecal microbiota transplantation was not associated with serious adverse events, changes in peripheral immunologic variables, or the canine DI in the short-term.

Abstract Introduction Ultrasound is important in heart diagnostics, yet implementing effective cardiac ultrasound requires training. While current strategies incorporate digital learning and ultrasound simulators, the effectiveness of these simulators for learning remains uncertain. This study evaluates the effectiveness of simulator-based versus human-based training in Focused Assessed with Transthoracic Echocardiography (FATE). Materials and methods This single-centre, prospective, randomised controlled study was conducted during an extracurricular FATE workshop (approximately 420 min) for third-year medical students. Participants were randomly assigned to the study group (training solely on simulators) or the control group (training on human subjects). Both groups completed a theory test and a self-assessment questionnaire before the course (T1) and at the end of the training (T2). At T2, all participants also completed two Direct Observation of Procedural Skills (DOPS) tests—one on the simulator (DOPSSim) and one on humans (DOPSHuman). Results Data from 128 participants were analysed (n = 63 study group; n = 65 control group). Both groups exhibited increased competency between the T1 and T2 self-assessments and theory tests (p

Bovine respiratory disease (BRD) is the leading cause of mortality and antimicrobial drug (AMD) use in weaned dairy heifers. Limited information is available regarding antimicrobial resistance (AMR) in respiratory bacteria in this population. This study determined AMR gene presence in 326 respiratory isolates (Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni) from weaned dairy heifers using whole genome sequencing. Concordance between AMR genotype and phenotype was determined. Twenty-six AMR genes for 8 broad classes of AMD were identified. The most prevalent, medically important AMD classes used in calf rearing, to which these genes predict AMR among study isolates were tetracycline (95%), aminoglycoside (94%), sulfonamide (94%), beta-lactam (77%), phenicol (50%), and macrolide (44%). The co-occurrence of AMR genes within an isolate was common; the largest cluster of gene co-occurrence encodes AMR to phenicol, macrolide, elfamycin, β-lactam (cephalosporin, penam cephamycin), aminoglycoside, tetracycline, and sulfonamide class AMD. Concordance between genotype and phenotype varied (Matthews Correlation Coefficient ranged from -0.57 to 1) by bacterial species, gene, and AMD tested, and was particularly poor for fluoroquinolones (no AMR genes detected) and ceftiofur (no phenotypic AMR classified while AMR genes present). These findings suggest a high genetic potential for AMR in weaned dairy heifers; preventing BRD and decreasing AMD reliance may be important in this population.

Chronic enteropathies (CE) are common disorders in cats and the differentiation between the two main underlying diseases, inflammatory bowel disease (IBD) and low-grade intestinal T-cell lymphoma (LGITL), can be challenging. Characterization of the serum metabolome could provide further information on alterations of disease-associated metabolic pathways and may identify diagnostic or therapeutic targets. Unbiased metabolomics analysis of serum from 28 cats with CE (14 cats with IBD, 14 cats with LGITL) and 14 healthy controls identified 1,007 named metabolites, of which 129 were significantly different in cats with CE compared to healthy controls at baseline. Random Forest analysis revealed a predictive accuracy of 90% for differentiating controls from cats with chronic enteropathy. Metabolic pathways found to be significantly altered included phospholipids, amino acids, thiamine, and tryptophan metabolism. Several metabolites were found to be significantly different between cats with IBD versus LGITL, including several sphingolipids, phosphatidylcholine 40:7, uridine, pinitol, 3,4-dihydroxybenzoic acid, and glucuronic acid. However, random forest analysis revealed a poor group predictive accuracy of 60% for the differentiation of IBD from LGITL. Of 129 compounds found to be significantly different between healthy cats and cats with CE at baseline, 58 remained different following treatment.

Feline chronic gingivostomatitis (FCGS) is a debilitating inflammatory oral mucosal disease with a multifactorial etiology. The clinical diagnosis of FCGS is made based on inspection of severe inflammatory lesions and histological confirmation rather than a molecular diagnostic outcome. This gap limits the ability to provide an early diagnosis. In this report, we seek to provide additional diagnostic tools using genomics to aid in providing clinically relevant information. The use of in-depth diagnostic tools, like transcriptomics of diseased tissues, to diagnose FCGS and stratify patients into predictive treatment response groups would dramatically improve both clinical decisions and patient outcomes. In this study, we addressed the gap in diagnostic options using transcriptomic analysis of caudal oral mucosal swab specimens coupled to detailed medical record linkage of FCGS-affected cats undergoing tooth extractions and in some cases administration of mesenchymal stromal cells (MSCs). To better identify markers of disease and potential response to treatment, the transcriptomes of FCGS-afflicted cats were compared to those of healthy cats and those with chronic periodontitis to clearly establish diagnostic biomarker signal transduction connections. Phosphatidylinositol 3-kinase/Ak strain transforming (PI3K/AKT) and stress-activated protein kinases/Jun N-terminal kinase (SAP/JNK) signaling pathways were significantly differentially regulated in FCGS-afflicted cats. Activation of these pathways also differed in the treatment response groups. In conjunction, the enzymes Caspase 4 (CASP4), matrix metalloproteinase-8 (MMP8), and prostaglandin-endoperoxide synthase 2 (PTGS2) were identified as potential biomarkers for the prediction of treatment response outcomes. The observations in the case study support the use of transcriptomics of FCGS patients to contribute to improved molecular diagnostics for the diagnosis and treatment of FCGS.

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Abstract Amyotrophic lateral sclerosis (ALS) lacks a specific biomarker, but is defined by relatively selective toxicity to motor neurons (MN). As others have highlighted, this offers an opportunity to develop a sensitive and specific biomarker based on detection of DNA released from dying MN within accessible biofluids. Here we have performed whole genome bisulfite sequencing (WGBS) of iPSC-derived MN from neurologically normal individuals. By comparing MN methylation with an atlas of tissue methylation we have derived a MN-specific signature of hypomethylated genomic regions, which accords with genes important for MN function. Through simulation we have optimised the selection of regions for biomarker detection in plasma and CSF cell-free DNA (cfDNA). However, we show that MN-derived DNA is not detectable via WGBS in plasma cfDNA. In support of our experimental finding, we show theoretically that the relative sparsity of lower MN sets a limit on the proportion of plasma cfDNA derived from MN which is below the threshold for detection via WGBS. Our findings are important for the ongoing development of ALS biomarkers. The MN-specific hypomethylated genomic regions we have derived could be usefully combined with more sensitive detection methods and perhaps with study of CSF instead of plasma. Indeed we demonstrate that neuronal-derived DNA is detectable in CSF. Our work is relevant for all diseases featuring death of rare cell-types.

Carbon dioxide (CO2) and methane (CH4) are the most important anthropogenic greenhouse gases and the main drivers of climate change. Monitoring their concentrations from space helps detect and quantify anthropogenic emissions, supporting the mitigation efforts urgently needed to meet the primary objective of the Paris Agreement, adopted at the 21st Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC) in 2015, to limit the global average temperature increase to well below 2 °C above pre-industrial levels. In addition, satellite observations can be used to quantify natural sources and sinks, improving our understanding of the carbon cycle. Advancing these goals is one key motivation for the European Copernicus CO2 monitoring mission CO2M. The necessary accuracy and precision requirements for the measured quantities XCO2 and XCH4 (the column-averaged dry-air mole fractions of CO2 and CH4) are demanding. According to the CO2M mission requirements, the spatial and temporal variability of the systematic errors (or spatio-temporal systematic errors) of XCO2 and XCH4 must not exceed 0.5 ppm and 5 ppb, respectively. The stochastic errors due to instrument noise must not exceed 0.7 ppm for XCO2 and 10 ppb for XCH4. Conventional so-called full-physics algorithms for retrieving XCO2 and/or XCH4 from satellite-based measurements of reflected solar radiation are typically computationally intensive and still usually require empirical bias corrections based on supervised machine learning methods. Here we present the retrieval algorithm Neural networks for Remote sensing of Greenhouse gases from CO2M (NRG-CO2M), which derives XCO2 and XCH4 from CO2M radiance measurements with minimal computational effort using artificial neural networks (ANNs). In addition, NRG-CO2M also provides estimates of both the noise-driven uncertainties and the averaging kernels of XCO2 and XCH4 for each sounding. Since CO2M will not be launched until 2026, our study exploits simulated measurements over land surfaces from a comprehensive observing system simulation experiment (OSSE) that includes realistic meteorology, aerosols, surface bidirectional reflectance distribution function (BRDF), solar-induced chlorophyll fluorescence (SIF), and CO2 and CH4 concentrations. We created a novel hybrid learning approach that combines advantages of simulation-based and measurement-based training data to ensure coverage of a wide range of XCO2 and XCH4 values, making the training data representative of future concentrations as well. The algorithm's postprocessing is designed to achieve a high data yield of about 80 % of all cloud-free soundings. The spatio-temporal systematic errors of XCO2 and XCH4 are 0.44 ppm and 2.45 ppb, respectively. The average single sounding precision is 0.41 ppm for XCO2 and 2.74 ppb for XCH4. Therefore, the presented retrieval method has the potential to meet the demanding CO2M mission requirements for XCO2 and XCH4. While the presented results are a solid proof of concept, the actual achievable quality can only be determined once NRG-CO2M is trained on real data, where it is confronted, e.g., with unknown instrument effects and systematic errors in the training truth.

Enzyme replacement therapy (ERT) is the only approved disease-modifying treatment modality for Pompe disease, a rare, inherited metabolic disorder caused by a deficiency in the acid α-glucosidase (GAA) enzyme that catabolizes lysosomal glycogen. First-generation recombinant human GAA (rhGAA) ERT (alglucosidase alfa) can slow the progressive muscle degeneration characteristic of the disease. Still, most patients experience diminished efficacy over time, possibly because of poor uptake into target tissues. Next-generation ERTs aim to address this problem by increasing bis-phosphorylated high mannose (bis-M6P) N-glycans on rhGAA as these moieties have sufficiently high receptor binding affinity at the resultant low interstitial enzyme concentrations after dosing to drive uptake by the cation-independent mannose 6-phosphate receptor on target cells. However, some approaches introduce bis-M6P onto rhGAA via non-natural linkages that cannot be hydrolyzed by natural human enzymes and thus inhibit the endolysosomal glycan trimming necessary for complete enzyme activation after cell uptake. Furthermore, all rhGAA ERTs face potential inactivation during intravenous delivery (and subsequent non-productive clearance) as GAA is an acid hydrolase that is rapidly denatured in the near-neutral pH of the blood. One new therapy, cipaglucosidase alfa plus miglustat, is hypothesized to address these challenges by combining an enzyme enriched with naturally occurring bis-M6P N-glycans with a small-molecule stabilizer. Here, we investigate this hypothesis by analyzing published and new data related to the mechanism of action of the enzyme and stabilizer molecule. Based on an extensive collection of in vitro, preclinical, and clinical data, we conclude that cipaglucosidase alfa plus miglustat successfully addresses each of these challenges to offer meaningful advantages in terms of pharmacokinetic exposure, target-cell uptake, endolysosomal processing, and clinical benefit.

Food-producing animals such as dairy cattle are potential reservoirs of antimicrobial resistance (AMR), with multidrug-resistant (MDR) organisms such as Escherichia coli observed in higher frequency in young calves compared to older cattle. In this study, we characterized the genomes of enteric MDR E. coli from pre-weaned dairy calves with and without diarrhea and evaluated the influence of host-level factors on genomic composition. Whole genome sequence comparative analysis of E. coli (n = 43) revealed substantial genomic diversity that primarily clustered by sequence type and was minimally driven by calf diarrheal disease status (healthy, diarrheic, or recovered), antimicrobial exposure, and dietary zinc supplementation. Diverse AMR genes (ARGs)-including extended-spectrum beta-lactamase genes and quinolone resistance determinants-were identified (n = 40), with unique sets of ARGs co-occurring in gene clusters with large AMR plasmids IncA/C2 and IncFIB(AP001918). Zinc supplementation was not significantly associated with the selection of individual ARGs in E. coli, however analysis of ARG and metal resistance gene pairs identified positive associations between certain aminoglycoside, beta-lactam, sulfonamide, and trimethoprim ARGs with acid, tellurium and mercury resistance genes. Although E. coli in this study lacked the typical virulence factors of diarrheagenic strains, virulence genes overlapping with those in major pathotypes were identified. Among the 103 virulence genes detected, the highest abundance and diversity of genes corresponded to iron acquisition (siderophores and heme uptake). Our findings indicate that the host-level factors evaluated in this study were not key drivers of genomic variability, but that certain accessory genes in enteric MDR E. coli may be enriched. Collectively, this work provides insight into the genomic diversity and host-microbe interface of MDR E. coli from pre-weaned dairy calves.

PurposeWe evaluated the impact of partial volume correction (PVC) methods on the quantification of longitudinal [18F]GTP1 tau positron-emission tomography (PET) in Alzheimer's disease and the suitability of describing the tau pathology burden temporal trajectories using linear mixed-effects models (LMEM).MethodsWe applied van Cittert iterative deconvolution (VC), 2-compartment, and 3-compartment, and the geometric transfer matrix plus region-based voxelwise methods to data acquired in an Alzheimer's disease natural history study over 18 months at a single imaging site. We determined the optimal PVC method by comparing the standardized uptake value ratio change (%ΔSUVR) between diagnostic and tau burden-level groups and the longitudinal repeatability derived from the LMEM. The performance of LMEM analysis for calculating %ΔSUVR was evaluated in a natural history study and in a multisite clinical trial of semorinemab in prodromal to mild Alzheimer's disease by comparing results to traditional per-visit estimates.ResultsThe VC, 2-compartment, and 3-compartment PVC methods had similar performance, whereas region-based voxelwise overcorrected regions with a higher tau burden. The lowest within-subject variability and acceptable group separation scores were observed without PVC. The LMEM-derived %ΔSUVR values were similar to the per-visit estimates with lower variability.ConclusionThe results indicate that the tested PVC methods do not offer a clear advantage or improvement over non-PVC images for the quantification of longitudinal [18F]GTP1 PET data. LMEM offers a robust framework for the longitudinal tau PET quantification with low longitudinal test-retest variability.Clinical trial registrationNCT02640092 and NCT03289143.

BACKGROUND: The goal of this study was to assess the microbial ecology and diversity present in the uterus of post-partum dairy cows with and without metritis from 24 commercial California dairy farms using shotgun metagenomics. A set subset of 95 intrauterine swab samples, taken from a larger selection of 307 individual cow samples previously collected, were examined for α and β diversity and differential abundance associated with metritis. Cows within 21 days post-partum were categorized into one of three clinical groups during sample collection: control (CT, n = 32), defined as cows with either no vaginal discharge or a clear, non-purulent mucus vaginal discharge; metritis (MET, n = 33), defined as a cow with watery, red or brown colored, and fetid vaginal discharge; and purulent discharge cows (PUS, n = 31), defined as a non-fetid purulent or mucopurulent vaginal discharge. RESULTS: All three clinical groups (CT, MET, and PUS) were highly diverse, with the top 12 most abundant genera accounting for 10.3%, 8.8%, and 10.1% of mean relative abundance, respectively. The α diversity indices revealed a lower diversity from samples collected from MET and PUS when compared to CT cows. PERMANOVA statistical testing revealed a significant difference (P adjusted