The impact of Chatbot-Assisted Self Assessment (CASA) on intentions for sexual health screening in people from minoritised ethnic groups at risk of sexually transmitted infections.

Background Sexually transmitted infections (STIs) present a significant global public health issue, with disparities in STI rates often observed across ethnic groups. The study investigates the impact of Chatbot-Assisted Self Assessment (CASA) on the intentions for sexual health screening within minoritised ethnic groups (MEGs) at risk of STIs as well as the subsequent use of a chatbot for booking STI screening. Methods A simulation within-subject design was utilised to evaluate the effect of CASA on intentions for STI/HIV screening, concern about STIs, and attitudes towards STI screening. Screening intentions served as the dependent variable, while demographic and behavioural factors related to STI/HIV risk were the independent variables. ANCOVA tests were conducted to measure the impact of CASA on these perceptions. Results Involving 548 participants (54% women, 66% black, average age=30years), the study found that CASA positively influenced screening intentions t (547)=-10.3, P t (544)=-4.96, P t (543)=-4.36, P Conclusion CASA increased motivations for STI screening intentions among ethnically diverse communities. The intervention's non-judgemental nature and the chatbot's ability to emulate sexual history-taking were critical in fostering an environment conducive to behavioural intention change. The study's high acceptability indicates the potential for broader application in digital health interventions. However, the limitation of not tracking actual post-intervention behaviour warrants further investigation into CASA's real-world efficacy.

The D-HCM score, a new diagnostic tool for distinguishing hypertrophic cardiomyopathy from hypertensive cardiopathy.

AIM: The diagnosis of hypertrophic cardiomyopathy (HCM) with moderate hypertrophy is challenging. Hypertensive heart disease (HHD) is the most common differential diagnosis that mimics the LVH of HCM. The aim of this study was to compare the QRS duration in HCM and HHD to create a novel diagnostic tool to identify primary HCM. METHODS AND RESULTS: We conducted an international retrospective multicentre study enrolling patients with true HCM and HHD. A total of 547 individuals with HCM and 139 with HHD were included. The median QRS duration was significantly shorter in HCM than in HHD (88 ms [80-94] vs. 98 ms [88-108]; P < 0.01). Multivariable logistic regression identified for the novel diagnostic HCM (D-HCM) score: absence of antihypertensive drugs (+2); family history of unexplained sudden death (+2); QRS duration [<95 ms] = +1; maximum wall thickness (mm) [≥17] = +1. A cumulative QRS-HCM score ≥2 supports the diagnostic certainty of true HCM with a sensitivity of 79%, specificity of 99%, negative predictive value (NPV) of 55%, and positive predictive value (PPV) of 99%. CONCLUSION: The QRS duration in patient with HCM is significantly shorter compared with patients with HHD-related LVH. QRS duration can be used as a diagnosis marker to distinguish between HCM and HHD. The D-HCM score is a novel, simple, and accurate diagnosis tool for HCM patients with mild to moderate phenotypes.

Iron rescues glucose-mediated photosynthesis repression during lipid accumulation in the green alga Chromochloris zofingiensis.

Energy status and nutrients regulate photosynthetic protein expression. The unicellular green alga Chromochloris zofingiensis switches off photosynthesis in the presence of exogenous glucose (+Glc) in a process that depends on hexokinase (HXK1). Here, we show that this response requires that cells lack sufficient iron (-Fe). Cells grown in -Fe+Glc accumulate triacylglycerol (TAG) while losing photosynthesis and thylakoid membranes. However, cells with an iron supplement (+Fe+Glc) maintain photosynthesis and thylakoids while still accumulating TAG. Proteomic analysis shows that known photosynthetic proteins are most depleted in heterotrophy, alongside hundreds of uncharacterized, conserved proteins. Photosynthesis repression is associated with enzyme and transporter regulation that redirects iron resources to (a) respiratory instead of photosynthetic complexes and (b) a ferredoxin-dependent desaturase pathway supporting TAG accumulation rather than thylakoid lipid synthesis. Combining insights from diverse organisms from green algae to vascular plants, we show how iron and trophic constraints on metabolism aid gene discovery for photosynthesis and biofuel production.

Catalytically distinct IDH1 mutants tune phenotype severity in tumor models.

Mutations in isocitrate dehydrogenase 1 (IDH1) impart a neomorphic reaction that produces the oncometabolite D-2-hydroxyglutarate (D2HG), which can inhibit DNA and histone demethylases to drive tumorigenesis via epigenetic changes. Though heterozygous point mutations in patients primarily affect residue R132, there are myriad D2HG-producing mutants that display unique catalytic efficiency of D2HG production. Here, we show that catalytic efficiency of D2HG production is greater in IDH1 R132Q than R132H mutants, and expression of IDH1 R132Q in cellular and mouse xenograft models leads to higher D2HG concentrations in cells, tumors, and sera compared to R132H-expressing models. Reduced representation bisulfite sequencing (RRBS) analysis of xenograft tumors shows expression of IDH1 R132Q relative to R132H leads to hypermethylation patterns in pathways associated with DNA damage. Transcriptome analysis indicates that the IDH1 R132Q mutation has a more aggressive pro-tumor phenotype, with members of EGFR, Wnt, and PI3K signaling pathways differentially expressed, perhaps through non-epigenetic routes. Together, these data suggest that the catalytic efficiency of IDH1 mutants modulate D2HG levels in cellular and in vivo models, resulting in unique epigenetic and transcriptomic consequences where higher D2HG levels appear to be associated with more aggressive tumors.

Achieving health equity through conversational AI: A roadmap for design and implementation of inclusive chatbots in healthcare.

BACKGROUND: The rapid evolution of conversational and generative artificial intelligence (AI) has led to the increased deployment of AI tools in healthcare settings. While these conversational AI tools promise efficiency and expanded access to healthcare services, there are growing concerns ethically, practically and in terms of inclusivity. This study aimed to identify activities which reduce bias in conversational AI and make their designs and implementation more equitable. METHODS: A qualitative research approach was employed to develop an analytical framework based on the content analysis of 17 guidelines about AI use in clinical settings. A stakeholder consultation was subsequently conducted with a total of 33 ethnically diverse community members, AI designers, industry experts and relevant health professionals to further develop a roadmap for equitable design and implementation of conversational AI in healthcare. Framework analysis was conducted on the interview data. RESULTS: A 10-stage roadmap was developed to outline activities relevant to equitable conversational AI design and implementation phases: 1) Conception and planning, 2) Diversity and collaboration, 3) Preliminary research, 4) Co-production, 5) Safety measures, 6) Preliminary testing, 7) Healthcare integration, 8) Service evaluation and auditing, 9) Maintenance, and 10) Termination. DISCUSSION: We have made specific recommendations to increase conversational AI's equity as part of healthcare services. These emphasise the importance of a collaborative approach and the involvement of patient groups in navigating the rapid evolution of conversational AI technologies. Further research must assess the impact of recommended activities on chatbots' fairness and their ability to reduce health inequalities.

A compendium of multi-omics data illuminating host responses to lethal human virus infections.

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

Omental Preadipocytes Stimulate Matrix Remodeling and IGF Signaling to Support Ovarian Cancer Metastasis.

Ovarian cancer can metastasize to the omentum, which is associated with a complex tumor microenvironment. Omental stromal cells facilitate ovarian cancer colonization by secreting cytokines and growth factors. An improved understanding of the tumor-supportive functions of specific cell populations in the omentum could identify strategies to prevent and treat ovarian cancer metastasis. Here, we showed that omental preadipocytes enhance the tumor initiation capacity of ovarian cancer cells. Secreted factors from preadipocytes supported cancer cell viability during nutrient and isolation stress and enabled prolonged proliferation. Coculturing with preadipocytes led to the upregulation of genes involved in extracellular matrix (ECM) organization, cellular response to stress, and regulation of insulin-like growth factor (IGF) signaling in ovarian cancer cells. IGF1 induced ECM genes and increased alternative NF-κB signaling by activating RelB. Inhibiting the IGF1 receptor initially increased tumor omental adhesion but decreased the growth of established preadipocyte-induced subcutaneous tumors as well as established intraperitoneal tumors. Together, this study shows that omental preadipocytes support ovarian cancer progression, which has implications for targeting metastasis. Significance: Omental preadipocyte-mediated IGF1 signaling promotes ovarian cancer tumorigenesis and metastasis via extracellular matrix remodeling, revealing a role for preadipocytes in regulating ovarian cancer progression and highlighting potential therapeutic targets for metastatic disease.

Untargeted, tandem mass spectrometry metaproteome of Columbia River sediments.

Rivers are critical ecosystems that impact global biogeochemical cycles. Nonetheless, a mechanistic understanding of river microbial metabolisms and their influences on geochemistry is lacking. Here, we announce metaproteomes of river sediments that are paired with metagenomes and metabolites, enabling an understanding of the microbial underpinnings of river respiration.

Unusual Presentation of a Granulocytic Sarcoma.

A granulocytic sarcoma is an unusual tumor outside of bone marrow. It is composed of immature cells of the granulocytic cell line. We present a rare case of a 76-year-old male with a history of myelodysplastic syndrome who presented with a large bowel obstruction secondary to lesions at the cecum and transverse colon. He underwent exploratory laparotomy with extended right hemicolectomy. A pathological examination confirmed a granulocytic sarcoma as the cause of the obstruction.

Reduction of chemokine CXCL9 expression by omega-3 fatty acids via ADP-ribosylhydrolase ARH3 in MIN6 insulin-producing cells.

Type 1 diabetes (T1D) results from the autoimmune destruction of the insulin producing ß cells of the pancreas. Omega-3 fatty acids protect ß cells and reduce the incident of T1D. However, how omega-3 fatty acids act on ß cells is not well understood. We have shown that omega-3 fatty acids reduce pro-inflammatory cytokine-mediated ß-cell apoptosis by upregulating the expression of the ADP-ribosylhydrolase ARH3. Here, we further investigate the ß-cell protection mechanism by ARH3 by performing siRNA of its gene Adprhl2 in MIN6 insulin-producing cells followed by treatment with a cocktail of the pro-inflammatory cytokines IL-1ß + IFN-γ + TNF-α, and proteomics analysis. ARH3 regulated proteins from several pathways related to the nucleus (splicing, RNA surveillance and nucleocytoplasmic transport), mitochondria (metabolic pathways) and endoplasmic reticulum (protein folding). ARH3 also regulated the levels of cytokine-signaling proteins related to the antigen processing and presentation, and chemokine-signaling pathway. We further studied the role of ARH in regulating the chemokine CXCL9. We confirmed that ARH3 reduces the cytokine-induced expression of CXCL9 by ELISA. We also found that CXCL9 expression is regulated by omega-3 fatty acids. In conclusion, we showed that omega-3 fatty acids regulate CXCL9 expression via ARH3, which might have a role in protecting ß cells from immune attack and preventing T1D development.

Regulation of ß-cell death by ADP-ribosylhydrolase ARH3 via lipid signaling in insulitis.

BACKGROUND: Lipids are regulators of insulitis and ß-cell death in type 1 diabetes development, but the underlying mechanisms are poorly understood. Here, we investigated how the islet lipid composition and downstream signaling regulate ß-cell death. METHODS: We performed lipidomics using three models of insulitis: human islets and EndoC-ßH1 ß cells treated with the pro-inflammatory cytokines interlukine-1ß and interferon-γ, and islets from pre-diabetic non-obese mice. We also performed mass spectrometry and fluorescence imaging to determine the localization of lipids and enzyme in islets. RNAi, apoptotic assay, and qPCR were performed to determine the role of a specific factor in lipid-mediated cytokine signaling. RESULTS: Across all three models, lipidomic analyses showed a consistent increase of lysophosphatidylcholine species and phosphatidylcholines with polyunsaturated fatty acids and a reduction of triacylglycerol species. Imaging assays showed that phosphatidylcholines with polyunsaturated fatty acids and their hydrolyzing enzyme phospholipase PLA2G6 are enriched in islets. In downstream signaling, omega-3 fatty acids reduce cytokine-induced ß-cell death by improving the expression of ADP-ribosylhydrolase ARH3. The mechanism involves omega-3 fatty acid-mediated reduction of the histone methylation polycomb complex PRC2 component Suz12, upregulating the expression of Arh3, which in turn decreases cell apoptosis. CONCLUSIONS: Our data provide insights into the change of lipidomics landscape in ß cells during insulitis and identify a protective mechanism by omega-3 fatty acids. Video Abstract.

Mapping microhabitats of lignocellulose decomposition by a microbial consortium.

The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines.

The Consolidated Standards of Reporting Trials extension for Artificial Intelligence interventions (CONSORT-AI) was published in September 2020. Since its publication, several randomised controlled trials (RCTs) of AI interventions have been published but their completeness and transparency of reporting is unknown. This systematic review assesses the completeness of reporting of AI RCTs following publication of CONSORT-AI and provides a comprehensive summary of RCTs published in recent years. 65 RCTs were identified, mostly conducted in China (37%) and USA (18%). Median concordance with CONSORT-AI reporting was 90% (IQR 77-94%), although only 10 RCTs explicitly reported its use. Several items were consistently under-reported, including algorithm version, accessibility of the AI intervention or code, and references to a study protocol. Only 3 of 52 included journals explicitly endorsed or mandated CONSORT-AI. Despite a generally high concordance amongst recent AI RCTs, some AI-specific considerations remain systematically poorly reported. Further encouragement of CONSORT-AI adoption by journals and funders may enable more complete adoption of the full CONSORT-AI guidelines.

Deciphering ApoE Genotype-Driven Proteomic and Lipidomic Alterations in Alzheimer's Disease Across Distinct Brain Regions.

Alzheimer's disease (AD) is a neurodegenerative disease with a complex etiology influenced by confounding factors such as genetic polymorphisms, age, sex, and race. Traditionally, AD research has not prioritized these influences, resulting in dramatically skewed cohorts such as three times the number of Apolipoprotein E (APOE) ε4-allele carriers in AD relative to healthy cohorts. Thus, the resulting molecular changes in AD have previously been complicated by the influence of apolipoprotein E disparities. To explore how apolipoprotein E polymorphism influences AD progression, 62 post-mortem patients consisting of 33 AD and 29 controls (Ctrl) were studied to balance the number of ε4-allele carriers and facilitate a molecular comparison of the apolipoprotein E genotype. Lipid and protein perturbations were assessed across AD diagnosed brains compared to Ctrl brains, ε4 allele carriers (APOE4+ for those carrying 1 or 2 ε4s and APOE4- for non-ε4 carriers), and differences in ε3ε3 and ε3ε4 Ctrl brains across two brain regions (frontal cortex (FCX) and cerebellum (CBM)). The region-specific influences of apolipoprotein E on AD mechanisms showcased mitochondrial dysfunction and cell proteostasis at the core of AD pathophysiology in the post-mortem brains, indicating these two processes may be influenced by genotypic differences and brain morphology.

Long COVID Among Wisconsin Workers in the Workers' Compensation System: Associations With Sociodemographics, Vaccination, and Predominant Variant Period From March 1, 2020 to July 31, 2022.

OBJECTIVE: This analysis aimed to determine the likelihood of developing long COVID among Wisconsin workers while adjusting for sociodemographics, COVID-19 vaccination, industry, and occupation. METHODS: This retrospective analysis determined the odds ratios of developing long COVID among Wisconsin workers who were compensated for COVID-19 lost time during March 1, 2020 to July 31, 2022. RESULTS: A total of 234 workers (11.7%) were determined to have long COVID. Factors associated with long COVID were age ≥40 years, non-White race, infection occurrence during the initial and Omicron variant dominant periods, and the absence of COVID-19 vaccination. Workers in manufacturing and public administration were more likely to develop long COVID compared with those in health care and social assistance. CONCLUSIONS: Long COVID disproportionately affects some worker groups. This calls for more worker protection and preventative care to mitigate its impact.

Ectomycorrhizal fungi enhance pine growth by stimulating iron-dependent mechanisms with trade-offs in symbiotic performance.

Iron (Fe) is crucial for metabolic functions of living organisms. Plants access occluded Fe through interactions with rhizosphere microorganisms and symbionts. Yet, the interplay between Fe addition and plant-mycorrhizal interactions, especially the molecular mechanisms underlying mycorrhiza-assisted Fe processing in plants, remains largely unexplored. We conducted mesocosms in Pinus plants inoculated with different ectomycorrhizal fungi (EMF) Suillus species under conditions with and without Fe coatings. Meta-transcriptomic, biogeochemical, and X-ray fluorescence imaging analyses were applied to investigate early-stage mycorrhizal roots. While Fe addition promoted Pinus growth, it concurrently reduced mycorrhiza formation rate, symbiosis-related metabolites in plant roots, and aboveground plant carbon and macronutrient content. This suggested potential trade-offs between Fe-enhanced plant growth and symbiotic performance. However, the extent of this trade-off may depend on interactions between host plants and EMF species. Interestingly, dual EMF species were more effective at facilitating plant Fe uptake by inducing diverse Fe-related functions than single-EMF species. This subsequently triggered various Fe-dependent physiological and biochemical processes in Pinus roots, significantly contributing to Pinus growth. However, this resulted in a greater carbon allocation to roots, relatively reducing the aboveground plant carbon content. Our study offers critical insights into how EMF communities rebalance benefits of Fe-induced effects on symbiotic partners.

"Two Years Later I'm Still Just as Angry": A Focus Group Study of Emergency and Internal Medicine Physicians on Disrespectful Communication.

Phenomenon: Disrespectful behavior between physicians across departments can contribute to burnout, poor learning environments, and adverse patient outcomes. Approach: In this focus group study, we aimed to describe the nature and context of perceived disrespectful communication between emergency and internal medicine physicians (residents and faculty) at patient handoff. We used a constructivist approach and framework method of content analysis to conduct and analyze focus group data from 24 residents and 11 faculty members from May to December 2019 at a large academic medical center. Findings: We organized focus group results into four overarching categories related to disrespectful communication: characteristics and context (including specific phrasing that members from each department interpreted as disrespectful, effects of listener engagement/disengagement, and the tendency for communication that is not in-person to result in misunderstanding and conflict); differences across training levels (with disrespectful communication more likely when participants were at different training levels); the individual correspondent's tendency toward perceived rudeness; and negative/long-term impacts of disrespectful communication on the individual and environment (including avoidance and effects on patient care). Insights: In the context of predominantly positive descriptions of interdepartmental communication, participants described episodes of perceived disrespectful behavior that often had long-lasting, negative impacts on the quality of the learning environment and clinical work. We created a conceptual model illustrating the process and outcomes of these interactions. We make several recommendations to reduce disrespectful communication that can be applied throughout the hospital to potentially improve patient care, interdepartmental collaboration, and trainee and faculty quality of life.

Oligosaccharide production and signaling correlate with delayed flowering in an Arabidopsis genotype grown and selected in high [CO2].

Since industrialization began, atmospheric CO2 ([CO2]) has increased from 270 to 415 ppm and is projected to reach 800-1000 ppm this century. Some Arabidopsis thaliana (Arabidopsis) genotypes delayed flowering in elevated [CO2] relative to current [CO2], while others showed no change or accelerations. To predict genotype-specific flowering behaviors, we must understand the mechanisms driving flowering response to rising [CO2]. [CO2] changes alter photosynthesis and carbohydrates in plants. Plants sense carbohydrate levels, and exogenous carbohydrate application influences flowering time and flowering transcript levels. We asked how organismal changes in carbohydrates and transcription correlate with changes in flowering time under elevated [CO2]. We used a genotype (SG) of Arabidopsis that was selected for high fitness at elevated [CO2] (700 ppm). SG delays flowering under elevated [CO2] (700 ppm) relative to current [CO2] (400 ppm). We compared SG to a closely related control genotype (CG) that shows no [CO2]-induced flowering change. We compared metabolomic and transcriptomic profiles in these genotypes at current and elevated [CO2] to assess correlations with flowering in these conditions. While both genotypes altered carbohydrates in response to elevated [CO2], SG had higher levels of sucrose than CG and showed a stronger increase in glucose and fructose in elevated [CO2]. Both genotypes demonstrated transcriptional changes, with CG increasing genes related to fructose 1,6-bisphosphate breakdown, amino acid synthesis, and secondary metabolites; and SG decreasing genes related to starch and sugar metabolism, but increasing genes involved in oligosaccharide production and sugar modifications. Genes associated with flowering regulation within the photoperiod, vernalization, and meristem identity pathways were altered in these genotypes. Elevated [CO2] may alter carbohydrates to influence transcription in both genotypes and delayed flowering in SG. Changes in the oligosaccharide pool may contribute to delayed flowering in SG. This work extends the literature exploring genotypic-specific flowering responses to elevated [CO2].