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High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment. Intratumoural heterogeneity in high-grade serous ovarian carcinoma (HGSOC) remains to be explored. Here, the authors perform spatial transcriptomics and reveal a high degree of subclonal heterogeneity in HGSOC.

Abstract INTRODUCTION Bariatric surgery is an effective treatment for obesity and aids in enhancing metabolic health. However, it has been observed that there's a heightened occurrence of Ulcerative Colitis (UC), especially following Roux-en-Y gastric bypass surgery. This study aims to ascertain whether racial differences influence the risk of developing Ulcerative Colitis in patients who have undergone bariatric surgery. Illuminating this relationship is key to improving patient outcomes and refining care following surgery. METHODS Our retrospective analysis reviewed patients who underwent bariatric surgery at our facility between 2009 and 2022. We collected data concerning comorbidities, insurance statuses, types of surgical procedures, colonoscopy, pathology reports, and baseline characteristics, employing ICD and CPT codes. We monitored patients who manifested Ulcerative colitis (UC) after surgery until 2023, categorizing them by gender, race, and the time elapsed. To balance baseline characteristics, we used propensity score matching. Patients with a history of UC before surgery were omitted from the study. We utilized Kaplan-Meier survival analysis and Cox proportional hazards models to determine the timing of UC onset across different racial groups. We applied odds ratios to discern independent factors impacting the study's outcomes. RESULTS Between 2009 and 2022, our facility performed 960 bariatric surgeries. Of these procedures, 24 patients (or 0.02%) were diagnosed with UC, typically identified around 80±14.2 months post-surgery. The mean age of the participants was approximately 46±11.8 years, and females constituted 54.2% of the cohort. When examining racial breakdowns, 38.39% were African Americans, 24.4% were whites, 21% were Asians, and 16.21% were Hispanics. Notably, Hispanic patients manifested UC within a considerably shorter duration than other racial groups (Breslow: 11.836, p=0.022). Additionally, a heightened risk of UC was observed among individuals from the lowest income bracket (OR: 3.15, P=0.041), emphasizing the influence of socioeconomic status on health outcomes. DISCUSSION This research contributes to bridging the knowledge deficit regarding the influence of race on the occurrence of UC following bariatric surgery. Our retrospective examination of 960 surgeries from 2009 to 2022 indicated a 0.02% incidence of UC, usually identified approximately 45 months after surgery. Importantly, Hispanic patients experienced the onset of UC in a notably shorter period compared to other racial groups, with those in lower income brackets encountering elevated risk levels. Continued studies in this domain can facilitate the development of interventions to diminish these risks, thereby improving health outcomes for a broad spectrum of patient demographics.

Powder-based additive manufacturing (PAM) is a potential fabrication approach in advancing state-of-the-art research to produce intricate components with high precision and accuracy in near-net form. In PAM, the raw materials are used in powder form, deposited on the surface layer by layer, and fused to produce the final product. PAM composite fabrication for biomedical implants, aircraft structure panels, and automotive brake rotary components is gaining popularity. In PAM composite fabrication, the aluminium cast alloy is widely preferred as a metal matrix for its unique properties, and different reinforcements are employed in the form of oxides, carbides, and nitrides. However, for enhancing the mechanical properties, the carbide form is predominantly considered. This comprehensive study focuses on contemporary research and reveals the effect of metal carbide’s (MCs) addition to the aluminium matrix processed through various PAM processes, challenges involved, and potential scopes to advance the research.

BackgroundThe impact of race on fatty liver disease outcomes in post-bariatric surgery patients is a vital yet understudied area of research. Racial and ethnic differences in genetic, metabolic, and lifestyle factors have been observed to influence disease progression and response to treatment. Notably, certain racial groups may exhibit a higher propensity for developing fatty liver disease post-surgery, impacting prognosis and management strategies. Understanding these racial disparities can significantly enhance personalized care, improving liver health outcomes for all post-bariatric surgery patientsMethodsOur study conducted a retrospective analysis of patients undergoing bariatric surgery at our institution from 2009–2022. We gathered extensive data, including comorbidities, insurance, pre-and post-surgery Fibrosis scores, pathology reports, and baseline characteristics using ICD and CPT codes. A 20% Fibrosis score improvement was marked as positive, with duration calculated from surgery day. Propensity score matching allowed baseline characteristic comparison. We used Kaplan Meier estimations to determine the improvement of liver cirrhosis among races and the Odds ratio to identify factors independently influencing the outcomeResultsOur hospital conducted 960 bariatric surgeries from 2009–2022. Among these, 165 patients (17%) with pre and post-surgery fibrosis scores were studied. Fibrosis scores improved in 81 patients (8.1%), averaging 40.59±20.76 months post-surgery. The average age was 50.29±12.17, with females constituting 52%. The racially diverse cohort included 30.3% African American, 24.8% White, 48% Asian, and 17.5% Hispanic. Asians (29%) took the longest to show liver cirrhosis improvement (log-rank Mantel cox: 17.651, p< 0.01). Patients with higher education demonstrated faster cirrhosis improvement (OR:1.23, P=0.015)ConclusionOur study reveals racial disparities in post-bariatric surgery fatty liver disease outcomes. Among 165 analyzed patients, 8.1% saw improved fibrosis scores post-surgery, with Asians taking the longest to show cirrhosis improvement. Additionally, higher education patients improved more quickly, suggesting a socioeconomic influence on health outcomes. These insights call for further research on genetic, metabolic, and lifestyle influences to enhance personalized care strategiesAbstract P363 Figure 1Abstract P363 Figure 2

IntroductionArtificial Intelligence (AI) has significantly revolutionized healthcare, particularly in diagnosing and treating Irritable Bowel Syndrome (IBS) and various digestive ailments. Vital AI resources, like ChatGPT and Google Bard, can decode endoscopic images, scrutinize various samples, ease administrative tasks, and aid in evaluating medical images and automating devices. These AI solutions have remarkably improved the handling of digestive diseases by personalizing treatments and predicting unfavorable responses. Incorporating these advanced AI methodologies enables patients to make informed decisions by considering personalized treatment options.MethodsThis study aimed to assess the accuracy of two prevalently utilized chatbots, ChatGPT, and Google BARD, in addressing inquiries associated with medical management. Both bots were assigned a set of questions to respond to, and their answers were rated on a 1–10 Likert scale, where 1 represented high accuracy. To maintain an unbiased evaluation, the responses from each bot were reviewed by two independent assessors. The intention behind this investigation was to shed light on the capabilities of these chatbots by methodically evaluating their effectiveness and reliability in terms of accuracy. The deployment of two reviewers and the application of the Likert scale methodology served to reduce potential biases, validating the results.ResultsOur research contrasted the effectiveness of ChatGPT and Google BARD in the realm of medical management. ChatGPT exhibited predominant proficiency, securing 59% accuracy compared to 27% by Google BARD (p = 0.041), and 51% against 24% in the trustworthiness of medical information (p = 0.011). This study emphasizes the crucial significance of precision and dependability in developing IBS chatbots. Although ChatGPT displayed notable outcomes, indicating its potential as a reliable source, it also accentuated the urgent requirement for continual exploration and progress in this field.DiscussionAI has markedly restructured healthcare, especially in diagnosing and handling IBD. ChatGPT and Google Bard are essential AI instruments capable of interpreting medical imagery, examining samples, and refining tasks. Our study scrutinized these chatbots’ accuracy and reliability within the medical management domain. ChatGPT outperformed Google Bard, achieving 59% in accuracy and 51% in the reliability of information. Although ChatGPT demonstrates considerable promise as a dependable AI tool in IBS management, the findings also highlight the ongoing need for research and development in this sector.Abstract P310 Figure 1

IntroductionArtificial Intelligence (AI) has significantly revolutionized healthcare, particularly in gastroenterology, enhancing diagnosis and treatment of digestive diseases. Key AI applications like ChatGPT and Google Bard interpret endoscopic images, analyze various samples, streamline administrative tasks, and aid in medical image evaluation and device automation. By personalizing treatments and predicting side effects, they have significantly improved digestive disorder management. The incorporation of these AI tools enables patients to make informed decisions by assessing tailored treatment options.MethodsThe research aimed to assess the accuracy of two prevalent Chat Bots - Chat GPT and Google BARD, - in answering medical management. Each bot was given a set of questions, with responses rated on a 1–10 Likert scale, where 1 represented high accuracy. Two impartial evaluators scrutinized each bot’s responses to maintain objective judgment. This study intended to shed light on these Chat Bots’ abilities through a systematic performance assessment in terms of accuracy and reliability. The use of two evaluators and the Likert scale method contributed to reducing potential bias, hence validating the resultsResultsOur research contrasted the effectiveness of Chat GPT and Google BARD in the realm of medical management. Chat GPT excelled, scoring 61% in accuracy compared to Google BARD’s 29% (p = 0.022) and 38% vs.19% in medical information reliability (p = 0.012). This study emphasizes the critical role of accuracy, and dependability, in developing gastrointestinal-oriented chatbots. While Chat GPT displayed impressive performance, indicating its potential as a reliable tool, it also underscored the necessity for continued research and development in this field.DiscussionAI has notably transformed healthcare, especially in gastroenterology, facilitating diagnosis and disease management. ChatGPT and Google Bard are pivotal AI applications that interpret medical images, analyze samples, and streamline tasks. Our study assessed these chatbots’ accuracy and reliability in medical management. ChatGPT outperformed Google Bard, achieving 61% accuracy and 38% information reliability. Despite ChatGPT’s promising potential as a dependable AI tool in gastroenterology, the findings also emphasize the ongoing need for research and development in this field.Abstract P303 Figure 1Abstract P303 Figure 2

IntroductionGastrointestinal stromal tumors (GISTs) occur along the GI tract, from the esophagus to anus, and occasionally in omentum, mesentery, and peritoneum. They represent 1–2% of primary GI cancers. Rates differ by ethnicity and race in the US, with higher prevalence among African Americans, Asian/Pacific Islanders, Whites, and American Indians. This study explores GIST incidence trends by location, ethnicity, and race in the US.MethodsOur study involved a retrospective analysis of GIST patients admitted to our hospital between 2009 and 2022. We collected data on comorbidities, insurance status, surgical procedures, colonoscopy reports, and baseline characteristics. Patients with GIST were classified based on sex, race, and tumor location. We utilized a direct method to calculate the expected number of gastric cancer cases in each specific group, using the standard population as a reference. Incidence trends over time were assessed using Joinpoint Regression, with the natural logarithm of annual standardized incidence rates as the dependent variable and the year (2009–2022) as the independent variable.ResultsThe study included a total of 259 patients diagnosed with GIST. Out of these, 101 or 38.9% were female. The incidence rate of the disease showed an upward trend in Afro-American and White populations between 2009–2014 and 2015–2022, with an Annual Percentage Change in Incidence (APCC) of 1.1 (95% Confidence Interval or CI: -0.3, 1.5) and 0.9 (95% CI: 0.3, 1) respectively. On the contrary, a decrease in incidence was observed in the Asian population during the same periods, with an APCC of -1.9 (95% CI: -2.1, -1.1). The incidence rates of GISTs in Afro-Americans and Whites paralleled each other according to the pairwise comparison test, whereas no such patterns were detected among the other groups.DiscussionOur research revealed a rising trend in the occurrence of GIST in both Afro-American and White populations, while the incidence within the Asian populations demonstrated a declining pattern. Similar rates of GIST were observed in Afro-Americans and Whites, yet differences were apparent in the rest of the groups. This shift in GIST incidence could suggest a modification in underlying causes. To further investigate these patterns, there’s a need for more extensive studies focusing on these cohorts.Abstract O42 Figure 1Gist incidence trend from 2009–2020.

Electrochromes are emerging materials for enabling sustainable energy devices such as smart windows and low power‐consuming displays along with automotive mirrors. This is owing to their electrochemical activity that results in unique optical transmission, modulating with applied potential. The molecular design rules of electrochromes are well established, consisting of electroactive components such as viologens, rhodamines, and transition metal complexes. While molecular electrochromes offer the advantage of establishing accurate structure/property relationships for tuning the optical transmission contingent on molecular structure, their physisorption on the electrodes limits the performance of electrochromic devices. Indeed, molecular electrochromes suffer from poor performance compared to their polymer counterparts in operating electrochromic devices. This perspective presents approaches to overcome these challenges. Focus is given to various strategies of covalently attaching molecular electrochromes to the device electrode for improving key electrochromic properties of contrast ratio and coloration efficiency. These operating device metrics are improved compared with the physisorption of molecular electrochromes via noncovalent interactions. The overarching goal is to provide useful insight that can be leveraged for the rational design of molecular electrochromes for their covalent attachment to electrodes toward matching device metrics of their polymer counterparts. The covalent attachment of molecular electrochromes to the conductive surface is an emerging approach for improving the performance of electrochromic devices. The perspective outlook surveys different functionalizations for covalently bonding molecular electrochromes toward enhancing the device metrics consisting of color switching with applied potential and coloration efficiency, among others, by framing improvements against their physisorbed counterparts.