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ABSTRACT Objectives We report the use of intra‐operative endoscopy, termed here ‘surgically‐assisted endoscopy’. The procedure spares a gastrotomy, therefore, shortening anaesthetic time, minimising potential complications and resulting in a quicker and less painful recovery. Methods Four dogs and one cat requiring surgical celiotomy for various conditions were treated. In all animals, a gastrointestinal foreign body (FB) was located at surgery. During the surgery, with the patient still in dorsal recumbency and the abdomen still open, in lieu of gastrotomy, the animals had their FBs removed via endoscopy, sparing a gastrotomy procedure and its potential complications. Results In all five cases, a gastrotomy was avoided and the FBs were successfully extracted using the endoscope. Only one minor complication was seen intra‐operatively and none at short‐term follow‐up. Clinical Significance Although prognosis after gastrotomy is considered excellent, potential complications still exist and include haemorrhage, intra‐operative spillage, peritonitis and post‐operative dehiscence. Alternatively, endoscopy negates many of those possible complications and shortens anaesthesia time. In many cases of gastric FBs, or where intestinal FBs can be safely manipulated into the stomach, surgically assisted endoscopy could be considered a viable and potentially preferred option to gastrotomy.

Background and Objective: Depression is a substantial public health issue, with global ramifications. While initial literature reviews explored the intersection between artificial intelligence (AI) and mental health, they have not yet critically assessed the specific contributions of Large Language Models (LLMs) in this domain. The objective of this systematic review was to examine the usefulness of LLMs in diagnosing and managing depression, as well as to investigate their incorporation into clinical practice., Methods: This review was based on a thorough search of the PubMed, Embase, Web of Science, and Scopus databases for the period January 2018 through March 2024. The search used PROSPERO and adhered to PRISMA guidelines. Original research articles, preprints, and conference papers were included, while non-English and non-research publications were excluded. Data extraction was standardized, and the risk of bias was evaluated using the ROBINS-I, QUADAS-2, and PROBAST tools., Results: Our review included 34 studies that focused on the application of LLMs in detecting and classifying depression through clinical data and social media texts. LLMs such as RoBERTa and BERT demonstrated high effectiveness, particularly in early detection and symptom classification. Nevertheless, the integration of LLMs into clinical practice is in its nascent stage, with ongoing concerns about data privacy and ethical implications., Conclusion: LLMs exhibit significant potential for transforming strategies for diagnosing and treating depression. Nonetheless, full integration of LLMs into clinical practice requires rigorous testing, ethical considerations, and enhanced privacy measures to ensure their safe and effective use., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest regarding the publication of this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The human microbiome exerts profound influence over various biological processes within the body. Unlike many host determinants, it represents a readily accessible target for manipulation to promote health benefits. However, existing commercial microbiome-directed products often exhibit low efficacy. Advancements in technology are paving the way for the development of novel microbiome therapeutics, across a wide range of indications. In this narrative review, we provide an overview of state-of-the-art technologies in late-stage development, examining their advantages and limitations. By covering a spectrum, from fecal-derived products to live biotherapeutics, phage therapy, and synthetic biology, we illuminate the path toward the future of microbiome therapeutics., Competing Interests: Declarations. Funding: This review was not supported by any funding agency. Conflict of interest: M.P., I.K., D.S., D.B.H., and H.B.-Y. have no conflicts to declare. Ethics approval: Not applicable. Informed consent: Not applicable. Data availability: Not applicable. Author contributions: M.P., I.K., D.S., D.B.H., and H.B.-Y. all contributed to the review. All authors approved the final version of the article, including the authorship list., (© 2025. The Author(s).)

Introduction and Hypothesis: Pelvic organ prolapse (POP) surgery has evolved toward minimally invasive techniques. Laparoscopic sacrohysteropexy (LSHP) is associated with reduced morbidity and lower mesh exposure risks. This study evaluates the long-term outcomes of LSHP using the SERATEX ® SlimSling ® mesh for isolated uterine prolapse., Methods: A retrospective case series was conducted on patients who underwent LSHP with SERATEX ® SlimSling ® mesh for apical prolapse with uterine preservation between 2014 and 2020. Data were extracted from medical records, including demographics, intraoperative details, and postoperative outcomes. Modified POP-Q measurements (Ba, Bp, C, D) were recorded. Patients were assessed perioperatively and at multiple postoperative intervals, with follow-up via telephone interviews by a urogynecologist. Statistical analysis included descriptive statistics and univariate analysis, with a p value of less than 0.05 considered significant., Results: Twenty-five women underwent LSHP with a mean age of 46 years. Most patients had isolated apical prolapse without other symptoms. Intraoperatively, 75% had concomitant cervical shortening, 10% had anterior colporrhaphy, and 30% had mid urethral sling, with a mean surgery duration of 112 min and no postoperative complications. Median follow-up was 66 months. Three patients (12%) experienced prolapse recurrence, mainly cystocele with two requiring reoperations. Four patients conceived and delivered post-procedure, all via cesarean section. At the long-term telephone interview, 76.2% were very happy with the surgery, 14.3% happy, and 9.5% unhappy., Conclusions: LSHP with the SERATEX ® SlimSling ® mesh for isolated uterine prolapse demonstrates a fair safety profile, durable outcomes, high patient satisfaction, and favorable pregnancy outcomes. This procedure offers a viable, minimally invasive option for uterine preservation., Competing Interests: Declarations. Ethical Approval: Ethical approval was obtained from the Clinical Research Ethics Committee of Ziv Medical Center in accordance to Helsinki guidelines. All data were anonymized, and patient consent was waived owing to the retrospective nature of the study. Conflict of Interest: The authors declare that they have no conflict of interest., (© 2025. The International Urogynecological Association.)

Large language models (LLMs) offer promising possibilities in mental health, yet their ability to assess disorders and recommend treatments remains underexplored. This quantitative cross-sectional study evaluated four LLMs (Gemini (Gemini 2.0 Flash Experimental), Claude (Claude 3.5 Sonnet), ChatGPT-3.5, and ChatGPT-4) using text vignettes representing conditions such as depression, suicidal ideation, early and chronic schizophrenia, social phobia, and PTSD. Each model's diagnostic accuracy, treatment recommendations, and predicted outcomes were compared with norms established by mental health professionals. Findings indicated that for certain conditions, including depression and PTSD, models like ChatGPT-4 achieved higher diagnostic accuracy compared to human professionals. However, in more complex cases, such as early schizophrenia, LLM performance varied, with ChatGPT-4 achieving only 55% accuracy, while other LLMs and professionals performed better. LLMs tended to suggest a broader range of proactive treatments, whereas professionals recommended more targeted psychiatric consultations and specific medications. In terms of outcome predictions, professionals were generally more optimistic regarding full recovery, especially with treatment, while LLMs predicted lower full recovery rates and higher partial recovery rates, particularly in untreated cases. While LLMs recommend a broader treatment range, their conservative recovery predictions, particularly for complex conditions, highlight the need for professional oversight. LLMs provide valuable support in diagnostics and treatment planning but cannot replace professional discretion.

Depression poses significant challenges to global healthcare systems and impacts the quality of life of individuals and their family members. Recent advancements in artificial intelligence (AI) have had a transformative impact on the diagnosis and treatment of depression. These innovations have the potential to significantly enhance clinical decision-making processes and improve patient outcomes in healthcare settings. AI-powered tools can analyze extensive patient data-including medical records, genetic information, and behavioral patterns-to identify early warning signs of depression, thereby enhancing diagnostic accuracy. By recognizing subtle indicators that traditional assessments may overlook, these tools enable healthcare providers to make timely and precise diagnostic decisions that are crucial in preventing the onset or escalation of depressive episodes. In terms of treatment, AI algorithms can assist in personalizing therapeutic interventions by predicting the effectiveness of various approaches for individual patients based on their unique characteristics and medical history. This includes recommending tailored treatment plans that consider the patient's specific symptoms. Such personalized strategies aim to optimize therapeutic outcomes and improve the overall efficiency of healthcare. This theoretical review uniquely synthesizes current evidence on AI applications in primary care depression management, offering a comprehensive analysis of both diagnostic and treatment personalization capabilities. Alongside these advancements, we also address the conflicting findings in the field and the presence of biases that necessitate important limitations.

Propagation of membrane tension mediates mechanical signal transduction along surfaces of live cells and sets the time scale of mechanical equilibration of cell membranes. Recent studies in several cell types and under different conditions revealed a strikingly wide variation range of the tension propagation speeds including extremely low ones. The latter suggests a possibility of long-living inhomogeneities of membrane tension crucially affecting mechano-sensitive membrane processes. Here, we propose, analyze theoretically, and support experimentally a mechanism of tension propagation in membranes crumpled by the contractile cortical cytoskeleton. The tension spreading is mediated by the membrane flow between the crumples. We predict the pace of the tension propagation to be controlled by the intra-cellular pressure and the degree of the membrane crumpling. We provide experimental support for the suggested mechanism by monitoring the rate of tension propagation in cells exposed to external media of different osmolarities., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)