Background Allergic rhinitis (AR) symptoms exhibit prominent 24‐hour variations associated with the biological clock. Although endogenous glucocorticoids synchronize circadian oscillator in the nasal mucosa, the precise mechanism of AR remains unclear. Therefore, using a mouse model, we investigated the association between circadian‐clock genes and AR symptoms at various time‐points. Methods Based on the rhythmic secretion of corticosterone levels, we chose 2 time‐points, ZT4 (10:00 AM) and ZT16 (10:00 PM), to observe dynamic changes of nasal symptoms, immunologic responses, and circadian‐clock gene period (Per) expressions. Results In the AR group, nasal symptom scores at ZT4 were significantly higher than at ZT16, with a greater increase in eosinophils, mast cells, and total immunoglobulin E levels at ZT4. The scores had a negative correlation with fluctuation of corticosterone levels. T‐helper 1 (Th1) cell counts and interferon‐γ levels decreased significantly at ZT4 compared with ZT16 in the AR group, whereas Th2 cells; Th17 cells; and interleukin (IL)‐4, ‐13, and ‐17A levels increased significantly at ZT4 compared with ZT16. Furthermore, Per2 gene expression levels were attenuated at ZT4 and elevated at ZT16, but correlated negatively with Th2 and Th17 responses associated with Gata3 and Rorγt expression levels that were enhanced at ZT4 and reduced at ZT16 in the AR group. Conclusion Our results suggest that the Per2 gene may influence diurnal variations of AR symptom severity, partially through its possible anti‐inflammatory effect on the circadian regulation of GATA3 and RORγt levels in immune cells. This further demonstrates the neural‐immune‐endocrinal mechanism of circadian rhythm in AR and sheds new light on chronotherapeutic approaches to AR.

Background Chronic jet lag (CJL)‐induced circadian rhythm disruption (CRD) is positively correlated with an increased risk of allergic diseases. However, little is known about the mechanism involved in allergic rhinitis (AR). Methods Aberrant light/dark cycles‐induced CRD mice were randomly divided into negative control (NC) group, AR group, CRD+NC group, and CRD+AR group (n = 8/group). After ovalbumin (OVA) challenge, nasal symptom scores were recorded. The expression of Occludin and ZO‐1 in both nasal mucosa and lung tissues was detected by reverse transcription–quantitative polymerase chain reaction (RT‐PCR) and immunohistochemical staining. The level of OVA–specific immunoglobulin E (sIgE) and T‐helper (Th)‐related cytokines in the plasma was measured by enzyme‐linked immunosorbent assay (ELISA), and the proportion of Th1, Th2, Th17, and regulatory T cell (Treg) in splenocytes was evaluated by flow cytometry. Results The nasal symptom score in the CRD+AR group was significantly higher than those in the AR group with respect to eosinophil infiltration, mast cell degranulation, and goblet cell hyperplasia. The expression of ZO‐1 and Occludin in the nasal mucosa and lung tissues in the CRD+AR group were significantly lower than those in the AR group. Furthermore, Th2 and Th17 cell counts from splenocytes and OVA‐sIgE, interleukin 4 (IL‐4), IL‐6, IL‐13, and IL‐17A levels in plasma were significantly increased in the CRD+AR group than in the AR group, whereas Th1 and Treg cell count and interferon γ (IFN‐γ) level were significantly decreased in the CRD+AR group. Conclusion CRD experimentally mimicked CJL in human activities, could exacerbate local and systemic allergic reactions in AR mice, partially through decreasing Occludin and ZO‐1 level in the respiratory mucosa and increasing Th2‐like immune response in splenocytes.

Background Mounting evidence indicates that the gut microbiome (GMB) plays an essential role in kidney stone (KS) formation. In this study, we conducted a systematic review and meta-analysis to compare the composition of gut microbiota in kidney stone patients and healthy individuals, and further understand the role of gut microbiota in nephrolithiasis. Results Six databases were searched to find taxonomy-based comparison studies on the GMB until September 2022. Meta-analyses were performed using RevMan 5.3 to estimate the overall relative abundance of gut microbiota in KS patients and healthy subjects. Eight studies were included with 356 nephrolithiasis patients and 347 healthy subjects. The meta-analysis suggested that KS patients had a higher abundance of Bacteroides (35.11% vs 21.25%, Z = 3.56, P = 0.0004) and Escherichia_Shigella (4.39% vs 1.78%, Z = 3.23, P = 0.001), and a lower abundance of Prevotella_9 (8.41% vs 10.65%, Z = 4.49, P < 0.00001). Qualitative analysis revealed that beta-diversity was different between the two groups (P < 0.05); Ten taxa (Bacteroides, Phascolarctobacterium, Faecalibacterium, Flavobacterium, Akkermansia, Lactobacillus, Escherichia coli, Rhodobacter and Gordonia) helped the detection of kidney stones (P < 0.05); Genes or protein families of the GMB involved in oxalate degradation, glycan synthesis, and energy metabolism were altered in patients (P < 0.05). Conclusions There is a characteristic gut microbiota dysbiosis in kidney stone patients. Individualized therapies like microbial supplementation, probiotic or synbiotic preparations and adjusted diet patterns based on individual gut microbial characteristics of patients may be more effective in preventing stone formation and recurrence.

Backgroud:To assess the diagnostic performance of transient elastography (TE) in detecting the presence and size of esophageal varices (EV) in cirrhotic patients.Methods:We searched PubMed, Web of Science, Wiley Online Library, Science Direct, China National Knowledge Infrastructure, WeiPu, WanFang database, and Baidu Scholar to identify studies that evaluated the diagnostic accuracy of TE in liver stiffness measurement, compared with esophagogastroduodenoscopy (EGD), for the detection of the presence and degree of EV in cirrhosis.Results:We included 32 studies in the presence of any EV (grade 1–3; n = 4082), 27 studies on substantial EV (grade 2–3; n = 5221) and 5 studies on large EV (grade 3). The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were 0.8 (95% CI, 0.78–0.86), 0.68 (95% CI, 0.62–0.74), and 10 (95% CI, 7–14) for any EV; 0.81 (95% CI, 0.77–0.85), 0.72 (95% CI, 0.66–0.77), and 11 (95% CI, 8–15) for substantial EV; and 0.92 (95% CI, 0.83–0.96), 0.78 (95% CI, 0.70–0.85), and 40 (95% CI, 15–107) for large EV. Subgroup analysis revealed that the heterogeneity among studies on any EV could potentially be explained by study location, proportion of Child A, and time interval between TE and EGD; for substantial EV, the proportion of Child A, etiology of cirrhosis, and the time interval between TE and EGD were important heterogeneity factors. Publication bias was found among studies evaluating diagnostic performance of TE for any EV.Conclusion:TE is a good tool for detecting the presence and degree of EV; however, in determination of the liver stiffness cutoff values means that TE is only cautiously used in clinical practice.