Predicting the potential deterioration of Barrett's esophagus based on gut microbiota: a Mendelian randomization analysis.

Esophageal adenocarcinoma (EAC) is one of the most malignant tumors in the digestive system. To make thing worse, the scarcity of treatment options is disheartening. However, if detected early, there is a possibility of reversing the condition. Unfortunately, there is still a lack of relevant early screening methods. Considering that Barrett's esophagus (BE), a precursor lesion of EAC, has been confirmed as the only known precursor of EAC. Analyzing which BE cases will progress to EAC and understanding the processes and mechanisms involved is of great significance for early screening of such patients. Considering the significant alterations in the gut microbiota of patients with BE and its potential role in the progression to EAC, this study aims to analyze the relationship between BE, EAC, and GM to identify potential diagnostic biomarkers and therapeutic targets. This study utilized comprehensive statistical data on gut microbiota from a large-scale genome-wide association meta-analysis conducted by the MiBioGen consortium (n = 18,340). Subsequently, we selected a set of single nucleotide polymorphisms (SNPs) that fell below the genome-wide significance threshold (1 × 10-5) as instrumental variables. To investigate the causal relationship between gut microbiota and BE and EAC, we employed various MR analysis methods, including Inverse Variance Weighting (IVW), MR-Egger regression, weighted median (WM), and weighted mean. Additionally, we assessed the level of pleiotropy, heterogeneity, and stability of genetic variations through MR-Egger intercept test, MR-PRESSO, Cochran's Q test, and "leave-one-out" sensitivity analysis. Furthermore, we conducted reverse MR analysis to identify the causal relationships between gut microbiota and BE and EAC. The results from the Inverse Variance-Weighted (IVW) analysis indicate that Alistipes (P = 4.86 × 10-2), Lactobacillus (P = 2.11 × 10-2), Prevotella 7 (P = 4.28 × 10-2), and RuminococcaceaeUCG004 (P = 4.34 × 10-2) are risk factors for Barrett's esophagus (BE), while Flavonifractor (P = 8.81 × 10-3) and RuminococcaceaeUCG004 (P = 4.99 × 10-2) are risk factors for esophageal adenocarcinoma (EAC). On the other hand, certain gut microbiota genera appear to have a protective effect against both BE and EAC. These include Eubacterium (nodatum group) (P = 4.51 × 10-2), Holdemania (P = 1.22 × 10-2), and Lactococcus (P = 3.39 × 10-2) in the BE cohort, as well as Eubacterium (hallii group) (P = 4.07 × 10-2) and Actinomyces (P = 3.62 × 10-3) in the EAC cohort. According to the results of reverse MR analysis, no significant causal effects of BE and EAC on gut microbiota were observed. Furthermore, no significant heterogeneity or pleiotropy was detected in the instrumental variables. We have established a causal relationship between the gut microbiota and BE and EAC. This study holds profound significance for screening BE patients who may be at risk of deterioration, as it can provide them with timely medical interventions to reverse the condition.

The efficacy and safety of fexuprazan in treating erosive esophagitis: a phase III, randomized, double-blind, multicenter study.

BACKGROUND AND AIM: Fexuprazan is a novel potassium-competitive acid blocker (P-CAB). This study aimed to explore the noninferior efficacy and safety of fexuprazan to esomeprazole in treating erosive esophagitis (EE). METHODS: This was a phase III, randomized, double-blind multicenter study. Patients with endoscopically confirmed EE were randomized to receive fexuprazan 40 mg or esomeprazole 40 mg once a daily for 4-8 weeks. The healing rates of EE, symptom response, GERD-health-related quality life (GERD-HRQL), and treatment-emergent adverse events (TEAEs) were compared between fexuprazan group and esomeprazole group. RESULTS: A total of 332 subjects were included in full analysis set (FAS) and 311 in per-protocol set (PPS). The healing rates of fexuprazan and esomeprazole groups at 8 weeks were 88.5% (146/165) and 89.0% (145/163), respectively, in FAS and 97.3% (145/149) and 97.9% (143/146), respectively, in PPS. Noninferiority of fexuprazan compared with esomeprazole according to EE healing rates at 8 weeks was demonstrated in both FAS and PPS analysis. No significant difference was found between groups in EE healing rates at 4 weeks, symptom responses, and changes of GERD-HRQL. The incidence of drug-related AEs was 19.4% (32/165) in fexuprazan arm and 19.6% (32/163) in esomeprazole arm. CONCLUSION: This study demonstrated noninferior efficacy of fexuprazan to esomeprazole in treating EE. The incidence of TEAEs was similar between fexuprazan and esomeprazole. Trial registration number NCT05813561.

Potential biomarkers for immune monitoring after renal transplantation.

Renal transplantation represents the foremost efficacious approach for ameliorating end-stage renal disease. Despite the current state of advanced renal transplantation techniques and the established postoperative immunosuppression strategy, a subset of patients continues to experience immune rejection during both the early and late postoperative phases, ultimately leading to graft loss. Consequently, the identification of immunobiomarkers capable of predicting the onset of immune rejection becomes imperative in order to facilitate early intervention strategies and enhance long-term prognoses. Upon reviewing the pertinent literature, we identified several indicators that could potentially serve as immune biomarkers to varying extents. These include the T1/T2 ratio, Treg/Th17 ratio, IL-10/TNF-α ratio, IL-33, IL-34, IL-6, IL-4, other cytokines, and NOX2/4.

Fluorescence spectroscopic profiling of urine samples for predicting kidney transplant rejection.

Rejection is the primary factor affecting the functionality of a kidney post-transplant, where its prompt prediction of risk significantly influences therapeutic strategies and clinical outcomes. Current graft health assessment methods, including serum creatinine measurements and transplant kidney puncture biopsies, possess considerable limitations. In contrast, urine serves as a direct indicator of the graft's degenerative stage and provides a more accurate measure than peripheral blood analysis, given its non-invasive collection of kidney-specific metabolite. This research entailed collecting fluorescent fingerprint data from 120 urine samples of post-renal transplant patients using hyperspectral imaging, followed by the development of a learning model to detect various forms of immunological rejection. The model successfully identified multiple rejection types with an average diagnostic accuracy of 95.56 %.Beyond proposing an innovative approach for predicting the risk of complications post-kidney transplantation, this study heralds the potential introduction of a non-invasive, rapid, and accurate supplementary method for risk assessment in clinical practice.