Collaborative Cross mice have diverse phenotypic responses to infection with Methicillin-resistant Staphylococcus aureus USA300.

Staphylococcus aureus (S. aureus) is an opportunistic pathogen causing diseases ranging from mild skin infections to life threatening conditions, including endocarditis, pneumonia, and sepsis. To identify host genes modulating this host-pathogen interaction, we infected 25 Collaborative Cross (CC) mouse strains with methicillin-resistant S. aureus (MRSA) and monitored disease progression for seven days using a surgically implanted telemetry system. CC strains varied widely in their response to intravenous MRSA infection. We identified eight 'susceptible' CC strains with high bacterial load, tissue damage, and reduced survival. Among the surviving strains, six with minimal colonization were classified as 'resistant', while the remaining six tolerated higher organ colonization ('tolerant'). The kidney was the most heavily colonized organ, but liver, spleen and lung colonization were better correlated with reduced survival. Resistant strains had higher pre-infection circulating neutrophils and lower post-infection tissue damage compared to susceptible and tolerant strains. We identified four CC strains with sexual dimorphism: all females survived the study period while all males met our euthanasia criteria earlier. In these CC strains, males had more baseline circulating monocytes and red blood cells. We identified several CC strains that may be useful as new models for endocarditis, myocarditis, pneumonia, and resistance to MRSA infection. Quantitative Trait Locus (QTL) analysis identified two significant loci, on Chromosomes 18 and 3, involved in early susceptibility and late survival after infection. We prioritized Npc1 and Ifi44l genes as the strongest candidates influencing survival using variant analysis and mRNA expression data from kidneys within these intervals.

An algorithm for computing Schubert varieties of best fit with applications.

We propose the geometric framework of the Schubert variety as a tool for representing a collection of subspaces of a fixed vector space. Specifically, given a collection of l-dimensional subspaces V1, …, Vr of ℝn, represented as the column spaces of matrices X1, …, Xr, we seek to determine a representative matrix K∈ℝn×k such that each subspace Vi intersects (or comes close to intersecting) the span of the columns of K in at least c dimensions. We formulate a non-convex optimization problem to determine such a K along with associated sets of vectors {ai} and {bi} used to express linear combinations of the columns of the Xi that are close to linear combinations of the columns of K. Further, we present a mechanism for integrating this representation into an artificial neural network architecture as a computational unit (which we refer to as an abstract node). The representative matrix K can be learned in situ, or sequentially, as part of a learning problem. Additionally, the matrix K can be employed as a change of coordinates in the learning problem. The set of all l-dimensional subspaces of ℝn that intersects the span of the columns of K in at least c dimensions is an example of a Schubert subvariety of the Grassmannian GR(l, n). When it is not possible to find a Schubert variety passing through a collection of points on GR(l, n), the goal of the non-convex optimization problem is to find the Schubert variety of best fit, i.e., the Schubert variety that comes as close as possible to the points. This may be viewed as an analog of finding a subspace of best fit to data in a vector space. The approach we take is well-suited to the modeling of collections of sets of data either as a stand-alone Schubert variety of best fit (SVBF), or in the processing workflow of a deep neural network. We present applications to some classification problems on sets of data to illustrate the behavior of the method.

Locally linear attributes of ReLU neural networks.

A ReLU neural network functions as a continuous piecewise linear map from an input space to an output space. The weights in the neural network determine a partitioning of the input space into convex polytopes, where each polytope is associated with a distinct affine mapping. The structure of this partitioning, together with the affine map attached to each polytope, can be analyzed to investigate the behavior of the associated neural network. We investigate simple problems to build intuition on how these regions act and both how they can potentially be reduced in number and how similar structures occur across different networks. To validate these intuitions, we apply them to networks trained on MNIST to demonstrate similarity between those networks and the potential for them to be reduced in complexity.

Integrating geometries of ReLU feedforward neural networks.

This paper investigates the integration of multiple geometries present within a ReLU-based neural network. A ReLU neural network determines a piecewise affine linear continuous map, M, from an input space ℝm to an output space ℝn. The piecewise behavior corresponds to a polyhedral decomposition of ℝm. Each polyhedron in the decomposition can be labeled with a binary vector (whose length equals the number of ReLU nodes in the network) and with an affine linear function (which agrees with M when restricted to points in the polyhedron). We develop a toolbox that calculates the binary vector for a polyhedra containing a given data point with respect to a given ReLU FFNN. We utilize this binary vector to derive bounding facets for the corresponding polyhedron, extraction of "active" bits within the binary vector, enumeration of neighboring binary vectors, and visualization of the polyhedral decomposition (Python code is available at https://github.com/cglrtrgy/GoL_Toolbox). Polyhedra in the polyhedral decomposition of ℝm are neighbors if they share a facet. Binary vectors for neighboring polyhedra differ in exactly 1 bit. Using the toolbox, we analyze the Hamming distance between the binary vectors for polyhedra containing points from adversarial/nonadversarial datasets revealing distinct geometric properties. A bisection method is employed to identify sample points with a Hamming distance of 1 along the shortest Euclidean distance path, facilitating the analysis of local geometric interplay between Euclidean geometry and the polyhedral decomposition along the path. Additionally, we study the distribution of Chebyshev centers and related radii across different polyhedra, shedding light on the polyhedral shape, size, clustering, and aiding in the understanding of decision boundaries.

Nurture outpaces nature: fostering with an attentive mother alters social dominance in a mouse model of stress sensitivity.

Maternal care is critical for epigenetic programming during postnatal brain development. Stress is recognized as a critical factor that may affect maternal behavior, yet owing to high heterogeneity in stress response, its impact varies among individuals. We aimed here to understand the connection between inborn stress vulnerability, maternal care, and early epigenetic programming using mouse populations that exhibit opposite poles of the behavioral spectrum (social dominance [Dom] and submissiveness [Sub]) and differential response to stress. In contrast to stress-resilient Dom dams, stress-vulnerable Sub dams exhibit significantly lower maternal attachment, serum oxytocin, and colonic Lactobacillus reuteri populations. Sub offspring showed a reduced hippocampal expression of key methylation genes at postnatal day (PND) 7 and a lack of developmentally-dependent increase in 5-methylcytosine (5-mC) at PND 21. In addition, Sub pups exhibit significant hypermethylation of gene promoters connected with glutamatergic synapses and behavioral responses. We were able to reverse the submissive endophenotype through cross-fostering Sub pups with Dom dams (Sub/D). Thus, Sub/D pups exhibited elevated hippocampal expression of DNMT3A at PND 7 and increased 5-mC levels at PND 21. Furthermore, adult Sub/D offspring exhibited increased sociability, social dominance, and hippocampal glutamate and monoamine levels resembling the neurochemical profile of Dom mice. We postulate that maternal inborn stress vulnerability governs epigenetic patterning sculpted by maternal care and intestinal microbiome diversity during early developmental stages and shapes the array of gene expression patterns that may dictate neuronal architecture with a long-lasting impact on stress sensitivity and the social behavior of offspring.

A Poly-D-lysine-Coated Coralline Matrix Promotes Hippocampal Neural Precursor Cells' Differentiation into GFAP-Positive Astrocytes.

A major goal of regenerative medicine of the central nervous system is to accelerate the regeneration of nerve tissue, where astrocytes, despite their positive and negative roles, play a critical role. Thus, scaffolds capable of producing astrocytes from neural precursor cells (NPCs) are most desirable. Our study shows that NPCs are converted into reactive astrocytes upon cultivation on coralline-derived calcium carbonate coated with poly-D-lysine (PDL-CS). As shown via nuclei staining, the adhesion of neurospheres containing hundreds of hippocampal neural cells to PDL-CS resulted in disaggregation of the cell cluster as well as the radial migration of dozens of cells away from the neurosphere core. Migrating cells per neurosphere averaged 100 on PDL-CS, significantly higher than on uncoated CS (28), PDL-coated glass (65), or uncoated glass (20). After 3 days of culture on PDL-CS, cell migration plateaued and remained stable for four more days. In addition, NPCs expressing nestin underwent continuous morphological changes from round to spiky, extending and elongating their processes, resembling activated astrocytes. The extension of the process increased continuously during the maturation of the culture and doubled after 7 days compared to day 1, whereas bifurcation increased by twofold during the first 3 days before plateauing. In addition, nestin positive cells' shape, measured through the opposite circularity level correlation, decreased approximately twofold after three days, indicating spiky transformation. Moreover, nestin-positive cells co-expressing GFAP increased by 2.2 from day 1 to 7, reaching 40% of the NPC population on day 7. In this way, PDL-CS promotes NPC differentiation into reactive astrocytes, which could accelerate the repair of neural tissue.

SARS-CoV-2 wastewater monitoring in rural and small metropolitan communities in Central Michigan.

Central Michigan University (CMU) participated in a state-wide SARS-CoV-2 wastewater monitoring program throughout the 2021-2022 academic year. Wastewater samples were collected weekly from ten on-campus sites and nine off-campus wastewater treatment plants servicing small metropolitan and rural communities. SARS-CoV-2 genome copies were quantified using droplet digital PCR. Case data reported by Central Michigan District Health Department and CMU were collected and compared with wastewater data. During the delta wave, wastewater detection and on-campus case reports increased rapidly with the start of the academic semester and peaked quickly, compared with a more gradual and prolonged increase in detection and case reports off-campus. During the omicron wave, transmission dynamics were similar on-campus and off-campus. Normalization of on-campus and off-campus wastewater data with pepper mild mottle virus gene expression suggested lower SARS-CoV-2 shedding per person in on-campus compared to off-campus samples during the delta wave, but no difference in virus shedding during the omicron wave. We discuss the possibility that a higher on-campus vaccination rate may have reduced virus shedding per person during the delta wave, but that this effect was lost with the omicron variant. This study suggests that wastewater monitoring is effective in rural and small metropolitan communities when used in conjunction with case reports to understand regional transmission dynamics and the impact of public health policies at a public university on virus shedding in the community.

Using machine learning to determine the time of exposure to infection by a respiratory pathogen.

Given an infected host, estimating the time that has elapsed since initial exposure to the pathogen is an important problem in public health. In this paper we use longitudinal gene expression data from human challenge studies of viral respiratory illnesses for building predictive models to estimate the time elapsed since onset of respiratory infection. We apply sparsity driven machine learning to this time-stamped gene expression data to model the time of exposure by a pathogen and subsequent infection accompanied by the onset of the host immune response. These predictive models exploit the fact that the host gene expression profile evolves in time and its characteristic temporal signature can be effectively modeled using a small number of features. Predicting the time of exposure to infection to be in first 48 h after exposure produces BSR in the range of 80-90% on sequestered test data. A variety of machine learning experiments provide evidence that models developed on one virus can be used to predict exposure time for other viruses, e.g., H1N1, H3N2, and HRV. The interferon [Formula: see text] signaling pathway appears to play a central role in keeping time from onset of infection. Successful prediction of the time of exposure to a pathogen has potential ramifications for patient treatment and contact tracing.

Modeling of adaptive immunity uncovers disease tolerance mechanisms.

When an organism is challenged with a pathogen a cascade of events unfolds. The innate immune system rapidly mounts a preliminary nonspecific defense, while the acquired immune system slowly develops microbe-killing specialists. These responses cause inflammation, and along with the pathogen cause direct and indirect tissue damage, which anti-inflammatory mediators seek to temper. This interplay of systems is credited for maintaining homeostasis but may produce unexpected results such as disease tolerance. Tolerance is characterized by the persistence of pathogen and damage mitigation, where the relevant mechanisms are poorly understood. In this work we develop an ordinary differential equations model of the immune response to infection in order to identify key components in tolerance. Bifurcation analysis uncovers health, immune- and pathogen-mediated death clinical outcomes dependent on pathogen growth rate. We demonstrate that decreasing the inflammatory response to damage and increasing the strength of the immune system gives rise to a region in which limit cycles, or periodic solutions, are the only biological trajectories. We then describe areas of parameter space corresponding to disease tolerance by varying immune cell decay, pathogen removal, and lymphocyte proliferation rates.

Module representatives for refining gene co-expression modules.

This paper concerns the identification of gene co-expression modules in transcriptomics data, i.e. collections of genes which are highly co-expressed and potentially linked to a biological mechanism. Weighted gene co-expression network analysis (WGCNA) is a widely used method for module detection based on the computation of eigengenes, the weights of the first principal component for the module gene expression matrix. This eigengene has been used as a centroid in ak-means algorithm to improve module memberships. In this paper, we present four new module representatives: the eigengene subspace, flag mean, flag median and module expression vector. The eigengene subspace, flag mean and flag median are subspace module representatives which capture more variance of the gene expression within a module. The module expression vector is a weighted centroid of the module which leverages the structure of the module gene co-expression network. We use these module representatives in Linde-Buzo-Gray clustering algorithms to refine WGCNA module membership. We evaluate these methodologies on two transcriptomics data sets. We find that most of our module refinement techniques improve upon the WGCNA modules by two statistics: (1) module classification between phenotype and (2) module biological significance according to Gene Ontology terms.

The British Society for Sexual Medicine Guidelines on Male Adult Testosterone Deficiency, with Statements for Practice.

Testosterone deficiency (TD) is an increasingly common problem with significant health implications, but its diagnosis and management can be challenging. A multi-disciplinary panel from BSSM reviewed the available literature on TD and provide evidence-based statements for clinical practice. Evidence was derived from Medline, EMBASE and Cochrane searches on hypogonadism, testosterone therapy (T Therapy) and cardiovascular safety from May 2017 to September 2022. This revealed 1,714 articles, including 52 clinical trials and 32 placebo-controlled randomised controlled trials. A total of twenty-five statements are provided, relating to five key areas: screening, diagnosis, initiating T Therapy, benefits and risks of T Therapy, and follow-up. Seven statements are supported by level 1 evidence, eight by level 2, five by level 3, and five by level 4. Recent studies have demonstrated that low levels of testosterone in men are associated with increased risk of incident type 2 diabetes mellitus, worse outcomes in chronic kidney disease and COVID 19 infection with increased all-cause mortality, along with significant quality of life implications. These guidelines should help practitioners to effectively diagnose and manage primary and age-related TD.

Pathway expression analysis.

This paper introduces a pathway expression framework as an approach for constructing derived biomarkers. The pathway expression framework incorporates the biological connections of genes leading to a biologically relevant model. Using this framework, we distinguish between shedding subjects post-infection and all subjects pre-infection in human blood transcriptomic samples challenged with various respiratory viruses: H1N1, H3N2, HRV (Human Rhinoviruses), and RSV (Respiratory Syncytial Virus). Additionally, pathway expression data is used for selecting discriminatory pathways from these experiments. The classification results and selected pathways are benchmarked against standard gene expression based classification and pathway ranking methodologies. We find that using the pathway expression data along with selected pathways, which have minimal overlap with high ranking pathways found by traditional methods, improves classification rates across experiments.

Guidelines for Sexual Health Care for Prostate Cancer Patients: Recommendations of an International Panel.

BACKGROUND: Patients with prostate cancer suffer significant sexual dysfunction after treatment which negatively affects them and their partners psychologically, and strain their relationships. AIM: We convened an international panel with the aim of developing guidelines that will inform clinicians, patients and partners about the impact of prostate cancer therapies (PCT) on patients' and partners' sexual health, their relationships, and about biopsychosocial rehabilitation in prostate cancer (PC) survivorship. METHODS: The guidelines panel included international expert researchers and clinicians, and a guideline methodologist. A systematic review of the literature, using the Ovid MEDLINE, Scopus, CINAHL, PsychINFO, LGBT Life, and Embase databases was conducted (1995-2022) according to the Cochrane Handbook for Systematic Reviews of Interventions. Study selection was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Each statement was assigned an evidence strength (A-C) and a recommendation level (strong, moderate, conditional) based on benefit/risk assessment, according to the nomenclature of the American Urological Association (AUA). Data synthesis included meta-analyses of studies deemed of sufficient quality (3), using A Measurement Tool to Assess Systematic Reviews (AMSTAR). OUTCOMES: Guidelines for sexual health care for patients with prostate cancer were developed, based on available evidence and the expertise of the international panel. RESULTS: The guidelines account for patients' cultural, ethnic, and racial diversity. They attend to the unique needs of individuals with diverse sexual orientations and gender identities. The guidelines are based on literature review, a theoretical model of sexual recovery after PCT, and 6 principles that promote clinician-initiated discussion of realistic expectations of sexual outcomes and mitigation of sexual side-effects through biopsychosocial rehabilitation. Forty-seven statements address the psychosexual, relationship, and functional domains in addition to statements on lifestyle modification, assessment, provider education, and systemic challenges to providing sexual health care in PC survivorship. CLINICAL IMPLICATIONS: The guidelines provide clinicians with a comprehensive approach to sexual health care for patients with prostate cancer. STRENGTHS & LIMITATIONS: The strength of the study is the comprehensive evaluation of existing evidence on sexual dysfunction and rehabilitation in prostate cancer that can, along with available expert knowledge, best undergird clinical practice. Limitation is the variation in the evidence supporting interventions and the lack of research on issues facing patients with prostate cancer in low and middle-income countries. CONCLUSION: The guidelines document the distressing sexual sequelae of PCT, provide evidence-based recommendations for sexual rehabilitation and outline areas for future research. Wittmann D, Mehta A, McCaughan E, et al. Guidelines for Sexual Health Care for Prostate Cancer Patients: Recommendations of an International Panel. J Sex Med 2022;19:1655-1669.

An accurate wearable hydration sensor: Real-world evaluation of practical use.

A wearable body hydration sensor employing photoplethysmographic and galvanic biosensors was field evaluated using 240 human participants with equal numbers of men and women volunteers. Monitoring of water mass loss due to perspiration was performed by medical balance measurements following one of two different treadmill physical exercise regimens over 90 minutes in 15-minute intervals with intervening 10-minute rest periods. Participants wore two different models of the dehydration body monitor device mated to commercially-available smartwatches (Samsung Gear S2 and Samsung Gear Fit2). Device output was recorded by Bluetooth wireless link to a standard smartphone in 20-second blocks. Comparison of the devices with the standard measurement method (change in body mass measured by medical balance) indicated very close agreement between changes in body water mass and device output (percent normalized mean root square error averaged approximately 2% for all participants). Bland-Altman analyses of method agreement indicated that <5% of participant values fell outside of the 95% confidence interval limits of agreement and all measured value differences were normally distributed around the line of equality. The results of this first-ever field trial of a practical, wearable hydration monitor suggests that this device will be a reliable tool to aid in geriatric hydration monitoring and physical training scenarios.

Elucidating Mechanisms of Tolerance to Salmonella Typhimurium across Long-Term Infections Using the Collaborative Cross.

Understanding the molecular mechanisms underlying resistance and tolerance to pathogen infection may present the opportunity to develop novel interventions. Resistance is the absence of clinical disease with a low pathogen burden, while tolerance is minimal clinical disease with a high pathogen burden. Salmonella is a worldwide health concern. We studied 18 strains of collaborative cross mice that survive acute Salmonella Typhimurium (STm) infections. We infected these strains orally and monitored them for 3 weeks. Five strains cleared STm (resistant), six strains maintained a bacterial load and survived (tolerant), while seven strains survived >7 days but succumbed to infection within the study period and were called "delayed susceptible." Tolerant strains were colonized in the Peyer's patches, mesenteric lymph node, spleen, and liver, while resistant strains had significantly reduced bacterial colonization. Tolerant strains had lower preinfection core body temperatures and had disrupted circadian patterns of body temperature postinfection sooner than other strains. Tolerant strains had higher circulating total white blood cells than resistant strains, driven by increased numbers of neutrophils. Tolerant strains had more severe tissue damage and higher circulating levels of monocyte chemoattractant protein 1 (MCP-1) and interferon gamma (IFN-γ), but lower levels of epithelial neutrophil-activating protein 78 (ENA-78) than resistant strains. Quantitative trait locus (QTL) analysis revealed one significant association and six suggestive associations. Gene expression analysis identified 22 genes that are differentially regulated in tolerant versus resistant animals that overlapped these QTLs. Fibrinogen genes (Fga, Fgb, and Fgg) were found across the QTL, RNA, and top canonical pathways, making them the best candidate genes for differentiating tolerance and resistance. IMPORTANCE To survive a bacterial infection, an infected host can display resistance or tolerance. Resistance is indicated by a decrease in pathogen load, while for tolerance a high pathogen load is accompanied by minimal disease. We infected genetically diverse mice with Salmonella Typhimurium for 21 days and discovered new phenotypes for disease outcome (delayed susceptible, tolerant, and resistant). Tolerant strains showed the lowest preinfection core body temperatures and the most rapid disruption in circadian patterns of body temperature postinfection. Tolerant strains had higher circulating neutrophils and higher circulating levels of MCP-1 and IFN-γ, but lower levels of ENA-78 than did resistant strains, in addition to more severe tissue damage. QTL analysis revealed multiple associated regions, and gene expression analysis identified 22 genes that are differentially regulated in tolerant versus resistant animals in these regions. Fibrinogen genes (Fga, Fgb, and Fgg) were found across the QTL, RNA, and the top canonical pathways, suggesting a role in tolerance.

Genetic background influences survival of infections with Salmonella enterica serovar Typhimurium in the Collaborative Cross.

Salmonella infections typically cause self-limiting gastroenteritis, but in some individuals these bacteria can spread systemically and cause disseminated disease. Salmonella Typhimurium (STm), which causes severe systemic disease in most inbred mice, has been used as a model for disseminated disease. To screen for new infection phenotypes across a range of host genetics, we orally infected 32 Collaborative Cross (CC) mouse strains with STm and monitored their disease progression for seven days by telemetry. Our data revealed a broad range of phenotypes across CC strains in many parameters including survival, bacterial colonization, tissue damage, complete blood counts (CBC), and serum cytokines. Eighteen CC strains survived to day 7, while fourteen susceptible strains succumbed to infection before day 7. Several CC strains had sex differences in survival and colonization. Surviving strains had lower pre-infection baseline temperatures and were less active during their daily active period. Core body temperature disruptions were detected earlier after STm infection than activity disruptions, making temperature a better detector of illness. All CC strains had STm in spleen and liver, but susceptible strains were more highly colonized. Tissue damage was weakly negatively correlated to survival. We identified loci associated with survival on Chromosomes (Chr) 1, 2, 4, 7. Polymorphisms in Ncf2 and Slc11a1, known to reduce survival in mice after STm infections, are located in the Chr 1 interval, and the Chr 7 association overlaps with a previously identified QTL peak called Ses2. We identified two new genetic regions on Chr 2 and 4 associated with susceptibility to STm infection. Our data reveal the diversity of responses to STm infection across a range of host genetics and identified new candidate regions for survival of STm infection.

Antidepressant-like effects of a chlorogenic acid- and cynarine-enriched fraction from Dittrichia viscosa root extract.

Dittrichia viscosa is a perennial Mediterranean plant used in traditional medicine for "calming purposes", pointing at a possible antidepressant activity of the plant. We conducted chromatographic and bioassay-guided fractionation of D. viscosa root extract to isolate a specific fraction (fraction "K") with antidepressant-like characteristics in vivo and strong antioxidant properties in vitro. A single dose of "K" reduced immobility time in the forced swim test with a mouse model possessing a depressive-like phenotype. Neurochemical profiling for 5-hydroxytryptamine (5-HT) and its primary metabolite, 5-hydroxyindoleacetic acid (5-HIAA), in prefrontal cortex and hippocampus of "K"-treated mice showed reduction in 5-HIAA, indicative of either serotonin uptake transporter or monoamine oxidase-A inhibition, as well as slight increases in 5-HT content. These neurochemical alterations, as well as the behavioral changes observed, were comparable to the effects of paroxetine. "K" also protected PC12 cells in a H2O2 cytotoxicity assay, thus demonstrating antioxidant properties, yet paroxetine augmented oxidative damage and cell death. Identification of the main compounds in "K" by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) indicated that chlorogenic acid and cynarine comprised 87% of the total components. D. viscosa root extract appears to produce antidepressant and cytoprotective effects and may serve as an attractive alternative to standard therapies for depression.