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Pregnant women in sub-Saharan Africa have high rates of maternal morbidity. There is interest in the impact of the vaginal microbiome on maternal health, including HIV and sexually transmitted infection (STI) acquisition. We characterized the vaginal microbiota of South African women ≥ 18 years with and without HIV in a longitudinal cohort over two visits during pregnancy and one visit postpartum. At each visit, we obtained HIV testing and self-collected vaginal swabs for point-of-care testing for STIs and microbiota sequencing. We categorized microbial communities and evaluated changes over pregnancy and associations with HIV status and STI diagnosis. Across 242 women (mean age 29, 44% living with HIV, 33% diagnosed with STIs), we identified four main community state types (CSTs): two lactobacillus-dominant CSTs (dominated by Lactobacillus crispatus and Lactobacillus iners respectively) and two diverse, non-lactobacillus-dominant CSTs (one dominated by Gardnerella vaginalis and one by diverse facultative anaerobes). From the first antenatal visit to the third trimester (24-36 weeks gestation), 60% of women in the Gardnerella-dominant CST shifted to lactobacillus-dominant CSTs. From the third trimester to postpartum (mean 17 days post-delivery), 80% of women in lactobacillus-dominant CSTs shifted to non-lactobacillus-dominant CSTs with a large proportion in the facultative anaerobe-dominant CST. Microbial composition differed by STI diagnosis (PERMANOVA R2 = 0.002, p = 0.004), and women diagnosed with an STI were more likely to be categorized as L. iners-dominant or Gardnerella-dominant CSTs. Overall, we found a shift toward lactobacillus dominance during pregnancy and the emergence of a distinct, highly diverse anaerobe-dominant microbiota profile in the postpartum period.

Amebic liver abscesses should be considered in adult males with a liver abscess and a history of travel to endemic areas. Effective treatment includes metronidazole, followed by paromomycin.

African women have more diverse vaginal microbiota than women of European descent, and there is interest in the impact of this diversity on maternal health, including HIV and STI acquisition. We characterized the vaginal microbiota in a cohort of women ≥ 18 years with and without HIV in a longitudinal cohort over two visits during pregnancy and one visit postpartum. At each visit we obtained HIV testing and self-collected vaginal swabs for point of care testing for STIs and microbiome sequencing. We categorized microbial communities and evaluated changes over pregnancy and associations with HIV status and STI diagnosis. Across 242 women (mean age 29, 44% living with HIV, 33% diagnosed with STIs), we identified four main community state types (CSTs): two lactobacillus-dominant CSTs (dominated by Lactobacillus crispatus and Lactobacillus iners respectively) and two diverse, non-lactobacillus-dominant CSTs (one dominated by Gardnerella vaginalis and one by other facultative anaerobes). From first antenatal visit to third trimester (24-36 weeks gestation), 60% of women in the Gardnerella -dominant CST shifted to L actobacillus -dominant CSTs. From third trimester to postpartum (mean 17 days post-delivery), 80% of women in Lactobacillus -dominant CSTs shifted to non-lactobacillus-dominant CSTs with a large proportion in the facultative anaerobe-dominant CST. Microbial composition differed by STI diagnosis (PERMANOVA R 2  = 0.002, p = 0.004), and women diagnosed with an STI were more likely to be categorized with L. iners -dominant or Gardnerella -dominant CSTs. Overall we found a shift toward lactobacillus dominance during pregnancy, and the emergence of a distinct, highly diverse anaerobe-dominant microbiome population in the postpartum period.

Despite providing valuable intellectual labor to universities, graduate students experience oppression based on social class (e.g., underpaid labor, student debt, barriers to unionizing), which is compounded for graduate students who hold minoritized statuses (i.e., students of color, sexual minoritized students). Minimal research has focused on graduate student academic persistence and performance in this context. Critical consciousness (CC) has been shown to improve the development of political agency that enables socially oppressed students to persist against systemic barriers. The current study adopts a structural equation modeling (SEM) path model that integrates CC and social cognitive career theory (SCCT) with a racially and ethnically diverse and low-income sample of graduate students (N = 159) to better understand how CC is involved in promoting academic performance and graduate student persistence. Analyses involved examining direct and indirect effects models. Results supported the fit of the model among graduate students, and suggested that higher critical activism predicted higher political self-efficacy, while greater critical reflection predicted greater political outcome expectations, which in turn predicted higher intent to persist and academic performance. These results suggest that integrating CC and SCCT is appropriate for understanding how to improve academic outcomes for low-income graduate students. Results suggest that the model integrating critical consciousness and SCCT is appropriate in predicting outcomes for students who face oppression based on socioeconomic status, including students holding other minoritized identities based on race and ethnicity. Implications for future research and practice aiming to promote equity in graduate education are discussed.

BACKGROUND AND AIMS: The host receptor for severe acute respiratory syndrome coronavirus 2, angiotensin-converting enzyme 2 (ACE2), is highly expressed in small bowel (SB). Our aim was to identify factors influencing intestinal ACE2 expression in Crohns disease (CD), ulcerative colitis (UC), and non-inflammatory bowel disease (IBD) controls. METHODS: Using bulk RNA sequencing or microarray transcriptomics from tissue samples (4 SB and 2 colonic cohorts; n = 495; n = 387 UC; n = 94 non-IBD), we analyzed the relationship between ACE2 with demographics and disease activity and prognosis. We examined the outcome of anti-tumor necrosis factor and anti-interleukin-12/interleukin-23 treatment on SB and colonic ACE2 expression in 3 clinical trials. Univariate and multivariate regression models were fitted. RESULTS: ACE2 levels were consistently reduced in SB CD and elevated in colonic UC compared with non-IBD controls. Elevated SB ACE2 was also associated with demographic features (age and elevated body mass index) associated with poor coronavirus disease 2019 outcomes. Within CD, SB ACE2 was reduced in patients subsequently developing complicated disease. Within UC, colonic ACE2 was elevated in active disease and in patients subsequently requiring anti-tumor necrosis factor rescue therapy. SB and colonic ACE2 expression in active CD and UC were restored by anti-cytokine therapy, most notably in responders. CONCLUSIONS: Reduced SB but elevated colonic ACE2 levels in IBD are associated with inflammation and severe disease, but normalized after anti-cytokine therapy, suggesting compartmentalization of ACE2-related biology in SB and colonic inflammation. The restoration of ACE2 expression with anti-cytokine therapy might be important in the context of severe acute respiratory syndrome coronavirus 2 infection and potentially explain reports of reduced morbidity from coronavirus disease 2019 in IBD patients treated with anti-cytokines.

BackgroundCrowdsourcing method is an excellent tool for developing tailored interventions to improve sexual health. We evaluated the implementation of an innovation contest for sexual health promotion in China.MethodsWe organized an innovation contest over three months in 2014 for Chinese individuals

Background and Aims Histological disease activity in inflammatory bowel disease [IBD] is associated with clinical outcomes and is an important endpoint in drug development. We developed deep learning models for automating histological assessments in IBD. Methods Histology images of intestinal mucosa from phase 2 and phase 3 clinical trials in Crohn's disease [CD] and ulcerative colitis [UC] were used to train artificial intelligence [AI] models to predict the Global Histology Activity Score [GHAS] for CD and Geboes histopathology score for UC. Three AI methods were compared. AI models were evaluated on held-back testing sets, and model predictions were compared against an expert central reader and five independent pathologists. Results The model based on multiple instance learning and the attention mechanism [SA-AbMILP] demonstrated the best performance among competing models. AI-modelled GHAS and Geboes subgrades matched central readings with moderate to substantial agreement, with accuracies ranging from 65% to 89%. Furthermore, the model was able to distinguish the presence and absence of pathology across four selected histological features, with accuracies for colon in both CD and UC ranging from 87% to 94% and for CD ileum ranging from 76% to 83%. For both CD and UC and across anatomical compartments [ileum and colon] in CD, comparable accuracies against central readings were found between the model-assigned scores and scores by an independent set of pathologists. Conclusions Deep learning models based upon GHAS and Geboes scoring systems were effective at distinguishing between the presence and absence of IBD microscopic disease activity. [ABSTRACT FROM AUTHOR]