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Background: Advancements in genomic technologies are rapidly evolving, with the potential to transform laboratory diagnostics by enabling high-throughput analysis of complex biological data, such as microbiome data. Large Language Models (LLMs) have shown significant promise in extracting actionable insights from vast datasets, but their application in generating microbiome findings reports with clinical interpretations and lifestyle recommendations has not been explored yet. Methods: This article introduces an innovative framework that utilizes LLMs to automate the generation of findings reports in the context of microbiome diagnostics. The proposed model integrates LLMs within an event-driven, workflow-based architecture, designed to enhance scalability and adaptability in clinical laboratory environments. Special focus is given to aligning the model with clinical standards and regulatory guidelines such as the In-Vitro Diagnostic Regulation (IVDR) and the guidelines published by the High-Level Expert Group on Artificial Intelligence (HLEG AI). The implementation of this model was demonstrated through a prototype called "MicroFlow". Results: The implementation of MicroFlow indicates the viability of automating findings report generation using LLMs. Initial evaluation by laboratory expert users indicated that the integration of LLMs is promising, with the generated reports being plausible and useful, although further testing on real-world data is necessary to assess the model's accuracy and reliability. Conclusions: This work presents a potential approach for using LLMs to support the generation of findings reports in microbiome diagnostics. While the initial results seem promising, further evaluation and refinement are needed to ensure the model's effectiveness and adherence to clinical standards. Future efforts will focus on improvements based on feedback from laboratory experts and comprehensive testing on real patient data. [ABSTRACT FROM AUTHOR]

Pediatric SARS‐CoV‐2 infection is often mild or asymptomatic and the immune responses of children are understudied compared to adults. Here, we present and evaluate the performance of a two‐panel (16‐ and 17 parameter) flow cytometry‐based approach for immune phenotypic analysis of cryopreserved PBMC samples from children after SARS‐CoV‐2 infection. The panels were optimized based on previous SARS‐CoV‐2 related studies for the pediatric immune system. PBMC samples from seven SARS‐CoV‐2 seropositive children from early 2020 and five age‐matched healthy controls were stained for analysis of T‐cells (panel T), B and innate immune cells (panel B). Performance of the panels was evaluated in two parallel approaches, namely classical manual gating of known subpopulations and unbiased clustering using the R‐based algorithm PhenoGraph. Using manual gating we clearly identified 14 predefined subpopulations of interest for panel T and 19 populations in panel B in low‐volume pediatric samples. PhenoGraph found 18 clusters within the T‐cell panel and 21 clusters within the innate and B‐cell panel that could be unmistakably annotated. Combining the data of the two panels and analysis approaches, we found expected differentially abundant clusters in SARS‐CoV‐2 seropositive children compared to healthy controls, underscoring the value of these two panels for the analysis of immune response to SARS‐CoV‐2. We established a two‐panel flow cytometry approach that can be used with limited amounts of cryopreserved pediatric samples. Our workflow allowed for a rapid, comprehensive, and robust pediatric immune phenotyping with comparable performance in manual gating and unbiased clustering. These panels may be adapted for large multi‐center cohort studies to investigate the pediatric immune response to emerging virus variants in the ongoing and future pandemics. [ABSTRACT FROM AUTHOR]

Background & Aims: Little is known about the composition of intrahepatic immune cells and their contribution to the pathogenesis of primary sclerosing cholangitis (PSC). Herein, we aimed to create an atlas of intrahepatic T cells and thereby perform an in-depth characterization of T cells in inflamed human liver., Methods: Different single-cell RNA sequencing methods were combined with in silico analyses on intrahepatic and peripheral T cells from patients with PSC (n = 11) and healthy donors (HDs, n = 4). Multi-parameter flow cytometry and functional in vitro experiments were conducted on samples from patients with PSC (n = 24), controls with other liver diseases and HDs., Results: We identified a population of intrahepatic naive-like CD4 + T cells, which was present in all liver diseases tested, but particularly expanded in PSC. This population had a transcriptome and T cell receptor repertoire similar to circulating naive T cells but expressed a set of genes associated with tissue residency. Their periductal location supported the concept of tissue-resident naive-like T cells in livers of patients with PSC. Trajectory inference suggested that these cells had the developmental propensity to acquire a T helper 17 (T H 17) polarization state. Functional and chromatin accessibility experiments revealed that circulating naive T cells in patients with PSC were predisposed to polarize towards T H 17 cells., Conclusion: We report the first atlas of intrahepatic T cells in PSC, which led to the identification of a previously unrecognized population of tissue-resident naive-like T cells in the inflamed human liver and to the finding that naive CD4 + T cells in PSC harbour the propensity to develop into T H 17 cells., Lay Summary: The composition of intrahepatic immune cells in primary sclerosing cholangitis (PSC) and their contribution to disease pathogenesis is widely unknown. We analysed intrahepatic T cells and identified a previously uncharacterized population of liver-resident CD4 + T cells which are expanded in the livers of patients with PSC compared to healthy liver tissue and other liver diseases. These cells are likely to contribute to the pathogenesis of PSC and could be targeted in novel therapeutic approaches., Competing Interests: Conflict of interest The authors declare no conflict of interest. Please refer to the accompanying ICMJE disclosure forms for further details., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

The recruitment and retention of Natural Killer (NK) cells in the liver are thought to play an important role during hepatotropic infections and liver cirrhosis. The aims of this study were to determine differences between liver-derived and peripheral blood-derived NK cells in the context of liver inflammation and cirrhosis. We conducted a prospective dual-center cross-sectional study in patients undergoing liver transplantation or tumor-free liver resections, in which both liver tissue and peripheral blood samples were obtained from each consenting study participants. Intrahepatic lymphocytes and PBMCs were stained, fixed and analyzed by flow cytometry. Our results showed that, within cirrhotic liver samples, intrahepatic NK cells were particularly enriched for CD49a+ NK cells when compared to tumor-free liver resection samples. CD49a+ liver-derived NK cells included populations of cells expressing CD25, CD34 and CXCR3. Moreover, CD49a+CD25+ liver-derived NK cells exhibited high proliferative capacity in vitro in response to low doses of IL-2. Our study identified a specific subset of CD49a+CD25+ NK cells in cirrhotic livers bearing functional features of proliferation.