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Maternal immune activation (MIA) is strongly associated with an increased risk of developing mental illness in adulthood, which often co-occurs with alcohol misuse. The current study aimed to begin to determine whether MIA, combined with adolescent alcohol exposure (AE), could be used as a model with which we could study the neurobiological mechanisms behind such co-occurring disorders. Pregnant Sprague-Dawley rats were treated with polyI:C or saline on gestational day 15. Half of the offspring were given continuous access to alcohol during adolescence, leading to four experimental groups: controls, MIA, AE, and Dual (MIA + AE). We then evaluated whether MIA and/or AE alter: (1) alcohol consumption; (2) locomotor behavior; and (3) cortical-striatal-hippocampal local field potentials (LFPs) in adult offspring. Dual rats, particularly females, drank significantly more alcohol in adulthood compared to all other groups. MIA led to reduced locomotor behavior in males only. Using machine learning to build predictive models from LFPs, we were able to differentiate Dual rats from control rats and AE rats in both sexes, and Dual rats from MIA rats in females. These data suggest that Dual “hits” (MIA + AE) increases substance use behavior and disrupts activity in reward-related circuits, and that this may be a valuable heuristic model we can use to study the neurobiological underpinnings of co-occurring disorders. Our future work aims to extend these findings to other addictive substances to enhance the translational relevance of this model, as well as determine whether amelioration of these circuit disruptions can reduce substance use behavior.

Resident microbiota activate regulatory cells that modulate intestinal inflammation and promote and maintain intestinal homeostasis. IL-10 is a key mediator of immune regulatory function. Our studies described the functional importance and mechanisms by which gut microbiota and specific microbial components influenced the development of intestinal IL-10-producing B cells. We used fecal transplant to germ-free (GF) Il10+/EGFP reporter and Il10-/- mice to demonstrate that microbiota from specific pathogen-free mice primarily stimulated IL-10-producing colon-specific B cells and T regulatory-1 cells in ex-GF mice. IL-10 in turn down-regulated microbiota-activated mucosal inflammatory cytokines. TLR2/9 ligands and enteric bacterial lysates preferentially induced IL-10 production and regulatory capacity of intestinal B cells. Analysis of Il10+/EGFP mice crossed with additional gene-deficient strains and B cell co-transfer studies demonstrated that microbiota-induced IL-10-producing intestinal B cells ameliorated chronic T cell-mediated colitis in a TLR2, MyD88 and PI3K-dependent fashion. In vitro studies implicated PI3Kp110δ and AKT downstream signaling. These studies demonstrated that resident enteric bacteria activated intestinal IL-10-producing B cells through TLR2, MyD88 and PI3K pathways. These B cells reduced colonic T cell activation and maintained mucosal homeostasis in response to intestinal microbiota.

This study examined associations between the composition and diversity of the intestinal microbiota and measures of depression, anxiety, eating disorder psychopathology, stress, and personality in a group of healthy adult females. Female participants (n = 91) ages 19-50 years with BMI 18.5-25 kg/m2 were recruited from central North Carolina between July 2014 and March 2015. Participants provided a single fecal sample and completed an online psychiatric questionnaire that included five measures: (i) Beck Anxiety Inventory; (ii) Beck Depression Inventory-II; (iii) Eating Disorder Examination-Questionnaire; (iv) Perceived Stress Scale; and (v) Mini International Personality Item Pool. Bacterial composition and diversity were characterized by Illumina sequencing of the 16S rRNA gene, and associations were examined using Kendall's tau-b correlation coefficient, in conjunction with Benjamini and Hochberg's False Discovery Rate procedure. We found no significant associations between microbial markers of gut composition and diversity and scores on psychiatric measures of anxiety, depression, eating-related thoughts and behaviors, stress, or personality in a large cohort of healthy adult females. This study was the first specifically to examine associations between the intestinal microbiota and psychiatric measures in healthy females, and based on 16S rRNA taxonomic abundances and diversity measures, our results do not suggest a strong role for the enteric microbe-gut-brain axis in normal variation on responses to psychiatric measures in this population. However, the role of the intestinal microbiota in the pathophysiology of psychiatric illness may be limited to more severe psychopathology.

The vast majority of people with cystic fibrosis (CF) are now eligible for CF transmembrane regulator (CFTR) modulator therapy. The remaining individuals with CF harbor premature termination codons (PTCs) or rare CFTR variants with limited treatment options. Although the clinical modulator response can be reliably predicted using primary airway epithelial cells, primary cells carrying rare CFTR variants are scarce. To overcome this obstacle, cell lines can be created by overexpression of mouse Bmi-1 and human TERT (hTERT). Using this approach, we developed 2 non-CF and 6 CF airway epithelial cell lines, 3 of which were homozygous for the W1282X PTC variant. The Bmi-1/hTERT cell lines recapitulated primary cell morphology and ion transport function. The 2 F508del-CFTR cell lines responded robustly to CFTR modulators, which was mirrored in the parent primary cells and in the cell donors' clinical response. Cereblon E3 ligase modulators targeting eukaryotic release factor 3a (eRF3a) rescued W1282X-CFTR function to approximately 20% of WT levels and, when paired with G418, rescued G542XCFTR function to approximately 50% of WT levels. Intriguingly, eRF3a degraders also diminished epithelial sodium channel (ENaC) function. These studies demonstrate that Bmi-1/hTERT cell lines faithfully mirrored primary cell responses to CFTR modulators and illustrate a therapeutic approach to rescue CFTR nonsense mutations.

Chemical manipulation of estrogen receptor alpha ligand binding domain structural mobility tunes receptor lifetime and influences breast cancer therapeutic activities. Selective estrogen receptor modulators (SERMs) extend estrogen receptor alpha (ERα) cellular lifetime/accumulation. They are antagonists in the breast but agonists in the uterine epithelium and/or in bone. Selective estrogen receptor degraders/downregulators (SERDs) reduce ERα cellular lifetime/accumulation and are pure antagonists. Activating somatic ESR1 mutations Y537S and D538G enable resistance to first-line endocrine therapies. SERDs have shown significant activities in ESR1 mutant setting while few SERMs have been studied. To understand whether chemical manipulation of ERα cellular lifetime and accumulation influences antagonistic activity, we studied a series of methylpyrollidine lasofoxifene (Laso) derivatives that maintained the drug’s antagonistic activities while uniquely tuning ERα cellular accumulation. These molecules were examined alongside a panel of antiestrogens in live cell assays of ERα cellular accumulation, lifetime, SUMOylation, and transcriptional antagonism. High-resolution x-ray crystal structures of WT and Y537S ERα ligand binding domain in complex with the methylated Laso derivatives or representative SERMs and SERDs show that molecules that favor a highly buried helix 12 antagonist conformation achieve the greatest transcriptional suppression activities in breast cancer cells harboring WT/Y537S ESR1 . Together these results show that chemical reduction of ERα cellular lifetime is not necessarily the most crucial parameter for transcriptional antagonism in ESR1 mutated breast cancer cells. Importantly, our studies show how small chemical differences within a scaffold series can provide compounds with similar antagonistic activities, but with greatly different effects of the cellular lifetime of the ERα, which is crucial for achieving desired SERM or SERD profiles.

I argue that machine learning (ML) models used in science function as highly idealized toy models. If we treat ML models as a type of highly idealized toy model, then we can deploy standard representational and epistemic strategies from the toy model literature to explain why ML models can still provide epistemic success despite their lack of similarity to their targets.

Under what conditions does machine learning (ML) model opacity inhibit the possibility of explaining and understanding phenomena? In this article, I argue that nonepistemic values give shape to the ML opacity problem even if we keep researcher interests fixed. Treating ML models as an instance of doing model-based science to explain and understand phenomena reveals that there is (i) an external opacity problem, where the presence of inductive risk imposes higher standards on externally validating models, and (ii) an internal opacity problem, where greater inductive risk demands a higher level of transparency regarding the inferences the model makes.

Transplanting human gut microbiotas into germ-free (GF) mice is a popular approach to disentangle cause-and-effect relationships between enteric microbes and disease. Algorithm development has enabled sequence variant (SV) identification from 16S rRNA gene sequence data. SV analyses can identify which donor taxa colonize recipient GF mice, and how SV abundance in humans is replicated in these mice. Fecal microbiotas from 8 human subjects were used to generate 77 slurries, which were transplanted into 153 GF mice. Strong correlations between fecal and slurry microbial communities were observed; however, only 42.15 ± 9.95% of SVs successfully transferred from the donor to the corresponding recipient mouse. Firmicutes had a particularly low transfer rate and SV abundance was poorly correlated between donor and recipient pairs. Our study confirms human fecal microbiotas colonize formerly GF mice, but the engrafted community only partially resembles the input human communities. Our findings emphasize the importance of reporting a standardized transfer rate and merit the exploration of other animal models or in silico tools to understand the relationships between human gut microbiotas and disease.

BackgroundThe aim of the study was to investigate the role of the gut microbiota in weight regain or suboptimal weight loss following Roux-en-Y gastric bypass (RYGB).Materials and MethodsThe gut microbiota composition in post-RYGB patients who experienced successful weight loss (SWL, n = 6), post-RYGB patients who experienced poor weight loss (PWL, n = 6), and non-surgical controls (NSC, n = 6) who were age- and BMI-matched to the SWL group (NSC, n = 6) were characterized through 16S rRNA gene sequencing. To further investigate the impact of the gut microbiota on weight profile, human fecal samples were transplanted into antibiotic-treated mice.ResultsOrders of Micrococcales and Lactobacillales were enriched in SWL and PWL groups compared to the NSC group. No significant difference was observed in the gut microbiota composition between PWL and SWL patients. However, transfer of the gut microbiota from human patients into antibiotic-treated mice resulted in significantly greater weight gain in PWL recipient mice compared to SWL recipient mice. A few genera that were effectively transferred from humans to mice were associated with weight gain in mice. Among them, Barnesiella was significantly higher in PWL recipient mice compared to SWL and NSC recipient mice.ConclusionThese results indicate that the gut microbiota are at least functionally, if not compositionally, different between PWL and SWL patients. Some taxa may contribute to weight gain after surgery. Future studies will need to determine the molecular mechanisms behind the effects of the gut bacteria on weight regain after RYGB.

Transgender and gender-diverse (TGD) individuals are at risk for discrimination and inequities across legal, social, and medical contexts. Population-level resources have rarely been used for TGD health research and, therefore, data is lacking about prevalences of a wide range of clinical conditions among TGD populations. To leverage the Utah Population Database's demographic, vital, and health records and examine population-level diagnostic prevalences in TGD individuals and an age-matched general cohort. 6,664 TGD individuals were identified using ICD codes for gender incongruence between 1995 and 2021; 64,124 age-matched individuals comprised the control cohort. Using Phecodes to collapse ICD codes, this study examined differences in the prevalence of medical, mental health, and neurodevelopmental clinical phenotypes in TGD and control cohorts using modified Poisson regression models. Affiliated healthcare systems within the state of Utah. We evaluated adjusted prevalence ratios of identified Phecodes. The TGD cohort showed broadly higher documented prevalences of medical, mental health, and neurodevelopmental conditions compared to controls. Medical diagnoses more common in the TGD cohort included sleep disorders and chronic pain. Disparities in diagnoses such as \"other endocrine disorders\" and \"need for hormone replacement therapy\" likely reflect gender-affirming treatments. Mental health conditions including mood, depression, anxiety, and personality disorders were significantly more prevalent in the TGD cohort. This study highlights diagnostic disparities for TGD individuals across multiple clinical categories. Our findings may be driven by: 1) discrimination and over-medicalization of TGD individuals, 2) differences in accessing and interacting with the healthcare system, and 3) variation in the true incidence of medical and mental health outcomes in the TGD vs control cohorts.