Psychiatric disorders are not uncommon among severely obese patients who present for bariatric surgery. This paper (1) reviews the results of the published studies using the structured interviews to assess psychopathology in bariatric surgery candidates; (2) compares the prevalence rates of psychiatric disorders across these studies with the data from other population samples; and (3) assesses whether sociodemographic variables appear to affect these prevalence rates. We searched online resources, PubMed, PsychINFO and reference lists of all the relevant articles to provide an overview of evidence so far and highlight some details in the assessment and comparisons of different samples in different countries. The prevalence estimates in the non- treatment obese group did not appear to differ substantially from the general population group in the US or the Italian population samples, although they were relatively higher for the German population. However, the rates of psychopathology in the bariatric surgery candidates were considerably higher than the other two population groups in all the samples. Overall, the most common category of lifetime Axis I disorders in all the studies was affective disorders, with anxiety disorders being the most common category of current Axis I disorders. Certain demographic characteristics are also associated with higher rates of psychopathology, such as, female gender, low socioeconomic status, higher BMI. Overall, methodological and sociodemographic differences make these studies difficult to compare and these differences should be taken into account when interpreting the results.

Summary Hyperinsulinemic hypoglycemia with neuroglycopenia is an increasingly recognized complication of Roux-en-Y gastric bypass (RYGB) due to the changes in gut hormonal milieu. Physicians should be aware of this complication to ensure timely and effective treatment of post-RYGB patients, who present to them with hypoglycemic symptoms. Possible causes of hypoglycemia in these patients include late dumping syndrome, nesidioblastosis and rarely insulinoma. Systematic evaluation including history, biochemical analysis, and diagnostic testing might help in distinguishing among these diagnoses. Continuous glucose monitoring is also a valuable tool, revealing the episodes in the natural environment and can also be used to monitor treatment success. Treatment should begin with strict low carbohydrate diet, followed by medication therapy. Therapy with diazoxide, acarbose, calcium channel blockers and octreotide have been proven to be beneficial, but the response apparently is highly variable. When other treatment options fail, surgical options can be considered.

Background Artificial intelligence (AI) is no longer a futuristic concept; it is increasingly being integrated into health care. As studies on attitudes toward AI have primarily focused on physicians, there is a need to assess the perspectives of students across health care disciplines to inform future curriculum development. Objective This study aims to explore and identify gaps in the knowledge that Canadian health care students have regarding AI, capture how health care students in different fields differ in their knowledge and perspectives on AI, and present student-identified ways that AI literacy may be incorporated into the health care curriculum. Methods The survey was developed from a narrative literature review of topics in attitudinal surveys on AI. The final survey comprised 15 items, including multiple-choice questions, pick-group-rank questions, 11-point Likert scale items, slider scale questions, and narrative questions. We used snowball and convenience sampling methods by distributing an email with a description and a link to the web-based survey to representatives from 18 Canadian schools. Results A total of 2167 students across 10 different health professions from 18 universities across Canada responded to the survey. Overall, 78.77% (1707/2167) predicted that AI technology would affect their careers within the coming decade and 74.5% (1595/2167) reported a positive outlook toward the emerging role of AI in their respective fields. Attitudes toward AI varied by discipline. Students, even those opposed to AI, identified the need to incorporate a basic understanding of AI into their curricula. Conclusions We performed a nationwide survey of health care students across 10 different health professions in Canada. The findings would inform student-identified topics within AI and their preferred delivery formats, which would advance education across different health care professions.

BACKGROUND Integrative multi-omic approaches have been increasingly applied to discovery and functional studies of complex human diseases. Short-term preoperative antibiotics have been adopted to reduce site infections in colorectal cancer (CRC) resections. We hypothesize that the antibiotics will impact analysis of multi-omic datasets generated from resection samples to investigate biological CRC risk factors. AIM To assess the impact of preoperative antibiotics and other variables on integrated microbiome and human transcriptomic data generated from archived CRC resection samples. METHODS Genomic DNA (gDNA) and RNA were extracted from prospectively collected 51 pairs of frozen sporadic CRC tumor and adjacent non-tumor mucosal samples from 50 CRC patients archived at a single medical center from 2010-2020. The 16S rRNA gene sequencing (V3V4 region, paired end, 300 bp) and confirmatory quantitative polymerase chain reaction (qPCR) assays were conducted on gDNA. RNA sequencing (IPE, 125 bp) was performed on parallel tumor and non-tumor RNA samples with RNA Integrity Numbers scores ≥ 6. RESULTS PERMANOVA detected significant effects of tumor vs nontumor histology ( P = 0.002) and antibiotics ( P = 0.001) on microbial β-diversity, but CRC tumor location (left vs right), diabetes mellitus vs not diabetic and Black/African Ancestry (AA) vs not Black/AA, did not reach significance. Linear mixed models detected significant tumor vs nontumor histology*antibiotics interaction terms for 14 genus level taxa. QPCR confirmed increased Fusobacterium abundance in tumor vs nontumor groups, and detected significantly reduced bacterial load in the (+)antibiotics group. Principal coordinate analysis of the transcriptomic data showed a clear separation between tumor and nontumor samples. Differentially expressed genes obtained from separate analyses of tumor and nontumor samples, are presented for the antibiotics, CRC location, diabetes and Black/AA race groups. CONCLUSION Recent adoption of additional preoperative antibiotics as standard of care, has a measurable impact on -omics analysis of resected specimens. This study still confirmed increased Fusobacterium nucleatum in tumor.