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Formal thought disorder (FTD) is a clinical key factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, the relationship between FTD symptom dimensions and patterns of regional brain volume loss in schizophrenia remains to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles by enrolling a large multi-site cohort acquired by the ENIGMA Schizophrenia Working Group (752 schizophrenia patients and 1256 controls), to unravel the neuroanatomy of FTD in schizophrenia and using virtual histology tools on implicated brain regions to investigate the cellular basis. Based on the findings of previous clinical and neuroimaging studies, we decided to separately explore positive, negative and total formal thought disorder. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but positive and negative FTD demonstrated a dissociation: negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD also showed associations with microglial cell types. These results provide an important step towards linking FTD to brain structural changes and their cellular underpinnings, providing an avenue for a better mechanistic understanding of this syndrome.

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenias alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

BACKGROUND: Reducing treatment burden is a priority for people with cystic fibrosis, whose health has benefited from using new modulators that substantially increase CFTR protein function. The SIMPLIFY study aimed to assess the effects of discontinuing nebulised hypertonic saline or dornase alfa in individuals using the CFTR modulator elexacaftor plus tezacaftor plus ivacaftor (ETI). METHODS: The SIMPLIFY study included two parallel, multicentre, open-label, randomised, controlled, non-inferiority trials at 80 participating clinics across the USA in the Cystic Fibrosis Therapeutics Development Network. We included individuals with cystic fibrosis aged 12-17 years with percent predicted FEV1 (ppFEV1) of 70% or more, or those aged 18 years or older with ppFEV1 of 60% or more, if they had been taking ETI and either (or both) mucoactive therapies (≥3% hypertonic saline or dornase alfa) for at least 90 days before screening. Participants on both hypertonic saline and dornase alfa were randomly assigned to one of the two trials, and those on a single therapy were assigned to the applicable trial. All participants were then randomly assigned 1:1 to continue or discontinue therapy for 6 weeks using permuted blocks of varying size, stratified by baseline ppFEV1 (week 0; ≥90% or

Hirschsprung’s disease (HSCR, incidence 1/5000 live births) is caused by the failure of neural crest-derived precursors to migrate, survive, proliferate, or differentiate during the embryonic development of the Enteric Nervous System (ENS), which could be disrupted by many factors, including inflammatory processes. The NF-κB family controls several biological processes, including inflammation, neurogenesis, and cell migration. With the aim of studying the potential role of NF-κB in HSCR, we have analyzed the expression of the NF-κB main subunits and other NF-κB-related genes by RT-qPCR in HSCR tissue samples (sub-divided into ganglionic and aganglionic segments). We found decreased gene expression of the NF-κB main subunit RELA but also of NFKBIA, TNFA, TFGBR2, and ERBB3 in the pathologic distal aganglionic segments compared to the proximal ganglionic segments. Moreover, we could also confirm the lower protein expression of RelA/p65 in the aganglionic distal segments by immunofluorescence staining. Further, we show that the expression of RelA/p65 protein in the proximal segments concurs with lymphocyte infiltration in the bowel tissue, indicating a pro-inflammatory activation of p65 in the proximal ganglionic HSCR tissue in the patients analyzed. All in all, our findings suggest that the modulation of NF-κB signaling in the neuro-enteric system does obviously contribute to the pathological effects of HSCR.

Abstract Background Antibiotic-loaded polymethylmethacrylate (PMMA) bone cement spacers provide high local antibiotic concentrations and patient mobility during the interim period of two-stage revision for periprosthetic joint infection (PJI). This study compares mechanical characteristics of six dual antibiotic-loaded bone cement (dALBC) preparations made from three different PMMA bone cements. The study`s main objective was to determine the effect of time and antibiotic concentration on mechanical strength of dALBCs frequently used for spacer fabrication in the setting of two-stage revision for PJI. Methods A total of 84 dual antibiotic-loaded bone cement specimens made of either Copal spacem, Copal G + V or Palacos R + G were fabricated. Each specimen contained 0.5 g of gentamicin and either 2 g (low concentration) or 4 g (high concentration) of vancomycin powder per 40 g bone cement. The bending strength was determined at two different timepoints, 24 h and six weeks after spacer fabrication, using the four-point bending test. Results Preparations made from Copal G + V showed the highest bending strength after incubation for 24 h with a mean of 57.6 ± 1.2 MPa (low concentration) and 50.4 ± 4.4 MPa (high concentration). After incubation for six weeks the bending strength had decreased in all six preparations and Palacos R + G showed the highest bending strength in the high concentration group (39.4 ± 1.6 MPa). All low concentration preparations showed superior mechanical strength compared to their high concentration (4 g of vancomycin) counterpart. This difference was statistically significant for Copal spacem and Copal G + V (both p

Background: Amphibians are experiencing substantial declines attributed to emerging pathogens. Efforts to understand what drives patterns of pathogen prevalence and differential responses among species are challenging because numerous factors related to the host, pathogen, and their shared environment can influence infection dynamics. Furthermore, sampling across broad taxonomic and geographic scales to evaluate these factors poses logistical challenges, and interpreting the roles of multiple potentially correlated variables is difficult with traditional statistical approaches. In this study, we leverage frozen tissues stored in natural history collections and machine learning techniques to characterize infection dynamics of three generalist pathogens known to cause mortality in frogs. Methods: We selected 12 widespread and abundant focal taxa within three ecologically distinct, co-distributed host families (Bufonidae, Hylidae, and Ranidae) and sampled them across the eastern two-thirds of the United States of America. We screened and quantified infection loads via quantitative PCR for three major pathogens: the fungal pathogen Batrachochytrium dendrobatidis (Bd), double-stranded viruses in the lineage Ranavirus (Rv), and the alveolate parasite currently referred to as Amphibian Perkinsea (Pr). We then built balanced random forests (RF) models to predict infection status and intensity based on host taxonomy, age, sex, geography, and environmental variables and to assess relative variable importance across pathogens. Lastly, we used one-way analyses to determine directional relationships and significance of identified predictors. Results: We found approximately 20% of individuals were infected with at least one pathogen (231 single infections and 25 coinfections). The most prevalent pathogen across all taxonomic groups was Bd (16.9%; 95% CI [14.9–19%]), followed by Rv (4.38%; 95% CI [3.35–5.7%]) and Pr (1.06%; 95% CI [0.618–1.82%]). The highest prevalence and intensity were found in the family Ranidae, which represented 74.3% of all infections, including the majority of Rv infection points, and had significantly higher Bd intensities compared to Bufonidae and Hylidae. Host species and environmental variables related to temperature were key predictors identified in RF models, with differences in importance among pathogens and host families. For Bd and Rv, infected individuals were associated with higher latitudes and cooler, more stable temperatures, while Pr showed trends in the opposite direction. We found no significant differences between sexes, but juvenile frogs had higher Rv prevalence and Bd infection intensity compared to adults. Overall, our study highlights the use of machine learning techniques and a broad sampling strategy for identifying important factors related to infection in multi-host, multi-pathogen systems. [ABSTRACT FROM AUTHOR]

Migratory amphibians require movements to complete their biphasic life cycle, often across altered landscapes fragmented by roadways, which can have severe consequences on their populations. To manage this threat, transportation agencies have begun to implement exclusion fencing to separate natural areas from the roadway to prevent wildlife-vehicle collisions. Although fences are an effective conservation tool, the tendency of animals to access the road by circumventing the fence ends, known as the fence-end effect, threatens to jeopardize management efforts to reduce road associated mortality. One strategy to lessen the impacts of the fence-end effect is to construct fence-end treatments to block amphibian movement and guide the animals to safe crossing locations. By using experimental fence arenas, we examined how nine amphibian species responded to two alternative fence-end structures: horizontal v-shape and perpendicular fence-end treatments. Using a generalized linear model framework, we found both fence-end treatments to be an effective strategy to reduce the impacts of the fence-end effect, with our predictor variable, fence-end treatment, explaining most of the variation in amphibian response. Structure effectiveness also started to improve by 20% with each 7°C increase in temperature, however, this was not significant. Despite these promising findings, we also found for each additional 312 s an amphibians spent attempting to navigate around the experimental fence resulted in a 25% decline in structure effectiveness, suggesting longer fences are not an adequate protection measure to combat the fence-end effect for amphibians. In addition, Anaxyrus americanus was not found to differ in their response, performing equally well to both experimental fence-end treatments. In contrast, Rana spp., Pseudacris crucifer, and Notopthalmus viridescens showed a greater response to the horizontal v-shape fence-end treatment compared to the perpendicular fence-end treatment. Variation in response for Ambystoma spp. could not be detected due to a small sample size; however, no individuals responded positively to the perpendicular fence-end treatment. Guidelines for amphibian fences should continue to incorporate fence-end treatments into the design and implementation to mitigate for the fence-end effect, and preferably angle the fence-ends inward in the horizontal v-shape pattern with the fence ends diagonal to the road for migratory amphibians.