AIM:To investigate the associations of triglyceride glucose(TyG)index, triglyceride glucose-body mass index(TyG-BMI), and homeostatic model assessment of insulin resistance(HOMA-IR)with diabetic retinopathy(DR), and to evaluate their diagnostic value.METHODS: This study was a single-center retrospective study. Patients with type 2 diabetes mellitus(T2DM)who were hospitalized in the endocrinology department of 3201 Hospital from January 1, 2023 to March 1, 2025 were included. According to the diagnostic criteria for DR, participants were classified into DR group and non-DR(NDR)group. Then the association of TyG index, TyG-BMI, and HOMA-IR index with DR of the two groups of patients were alalyzed.RESULTS:A total of 969 patients with T2DM were enrolled in this study, including 816 patients in the DR group. Among DR group, 271 were males(33.2%)and 545 were females(66.8%), with a mean age of 56.78±11.88 years. The NDR group consisted of 153 patients, including 41 males(26.8%)and 112 females(73.2%), with a mean age of 59.40±10.52 years. Statistically significant differences were observed between the DR group and the NDR group in terms of age, BMI, TyG index, TyG-BMI, HOMA-IR index, fasting blood glucose(FBG), 2-h postprandial blood glucose(2 hPBG), fasting insulin(FINS), 2-h postprandial insulin(2 hPINS), fasting C-peptide(FCP), 2-h postprandial C-peptide(2 hPCP), total cholesterol(CHO), triglyceride(TG), low-density lipoprotein(LDL-C), blood urea nitrogen(BUN), uric acid(UA), direct bilirubin(DBIL), glycated hemoglobin(HbA1c), milligrams per total protein(M-TP), microalbuminuria(MALB), urinary albumin to creatinine ratio(UACR), 24-hour urine protein, white blood cell(WBC), neutrophil(N), and platelets(PLT; all P<0.05), while no significant differences were found in the remaining indicators(all P>0.05). In multivariable Logistic regression, both TyG index(aOR=198.65, 95% CI: 66.73-591.41, P<0.001)and TyG-BMI(aOR=1.03, 95% CI: 1.02-1.04, P<0.001)remained independently positive associated with DR. Quartile analysis indicated a progressive increase in DR risk with ascending quartiles of TyG index and TyG-BMI(all Ptrend<0.001). In contrast, HOMA-IR was not significantly associated with DR. Restricted cubic spline analysis, fully adjusted for confounders, showed a nonlinear upward trend in DR risk with increasing TyG index(Pnonlinearity<0.001), whereas TyG-BMI exhibited a U-shaped association(Pnonlinearity<0.05). No significant association was found between HOMA-IR and DR after propensity score matching. Receiver operating characteristic(ROC)curve demonstrated area under curve(AUC)values of 0.870(95% CI: 0.839-0.901)for TyG index, 0.710(95% CI: 0.665-0.755)for TyG-BMI, and 0.657(95% CI: 0.608-0.706)for HOMA-IR.CONCLUSION:The TyG index and TyG-BMI are risk factors for DR. A dose-dependent increase in DR risk was associated with elevated TyG index values. TyG-BMI exhibited an inverted U-shaped relationship with DR risk. The TyG index had better diagnostic efficiency for DR compared to both TyG-BMI and HOMA-IR index.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVE: To investigate the regulatory effects of two traditional mineral medicines (TMMs), Gypsum Fibrosum (Shigao, GF) and Terra Flava Usta (Zaoxintu, TFU), on gut-beneficial bacteria in mice, and preliminarily explore their mechanisms of action. METHODS: Mice were randomly divided into 3 groups (n=10 per group): the control group (standard diet), the GF group (diet supplemented with 2% GF), and the TFU group (diet supplemented with 2% TFU). After 4-week intervention, 16S rRNA gene sequencing was used to analyze the changes in the gut microbiota (GM). Scanning electron microscopy, in combination with coumarin A tetramethyl rhodamine conjugate and Hoechst stainings, was used to observe the bacteria and biofilm formation. RESULTS: Principal coordinate analysis revealed that GF and TFU significantly altered the GM composition in mice. Further analysis revealed that GF and TFU affected different types of gut bacteria, suggesting that different TMMs may selectively modulate specific bacterial populations. For certain bacteria, such as Faecalibaculum and Ileibacterium, both GF and TFU exhibited growth-promoting effects, implying that they may be sensitive to TMMs and that different TMMs can increase their abundance through their respective mechanisms. Notably, Lactobacillus reuteri, a widely recognized and used probiotic, was significantly enriched in the GF group. Random forest analysis identified Ileibacterium valens as a potential indicator bacterium for TMMs' impact on GM. Further mechanistic studies showed that gut bacteria formed biofilm structures on the TFU surface. CONCLUSIONS This study provides new insights into the interaction between TMMs and GM. As safe and effective natural clays, GF and TFU hold promise as potential candidates for prebiotic development.
Animals ; Gastrointestinal Microbiome/drug effects* ; Bacteria/growth & development* ; Mice ; Biofilms/drug effects* ; Male ; RNA, Ribosomal, 16S/genetics*

Disruption of the intestinal mucosal barrier caused by gut dysbiosis and metabolic imbalance is the underlying pathology of inflammatory bowel disease (IBD). Traditional Chinese medicine Wuji Wan (WJW) is commonly used to treat digestive system disorders and showed therapeutic potential for IBD. In this interdisciplinary study, we aim to investigate the pharmacological effects of WJW against experimental colitis by combining functional metabolomics and gut-microbiota sequencing techniques. Treatment with WJW altered the profile of the intestinal microbiota and notably increased the abundance of Lactobacillus, thereby facilitating the conversion of tryptophan into indole-3-acetic acid (IAA) and indoleacrylic acid (IA). These indole derivatives activated the aryl hydrocarbon receptor (AhR) pathway, which reduced colonic inflammation and restored the expression of intestinal barrier proteins. Interestingly, the beneficial effects of WJW on gut barrier function improvement and tryptophan metabolism were disappeared in the absence of gut microbiota. Finally, pre-treatment with the AhR antagonist CH-223191 confirmed the essential role of IAA-mediated AhR activation in the therapeutic effects of WJW. Overall, WJW enhanced intestinal barrier function and reduced colonic inflammation in a murine colitis model by modulating Lactobacillus-IAA-AhR signaling pathway. This study provides novel insights into colitis pathogenesis and presents an effective therapeutic and preventive approach against IBD.

Cannabidiol (CBD), a non-psychoactive cannabinoid, shows great promise in treating methamphetamine (METH) addiction. Nonetheless, the molecular target and the mechanism through which CBD treats METH addiction remain unexplored. Herein, CBD was shown to counteract METH-induced locomotor sensitization and conditioned place preference. Additionally, CBD mitigated the adverse effects of METH, such as cristae loss, a decline in ATP content, and a reduction in membrane potential. Employing an activity-based protein profiling approach, a target fishing strategy was used to uncover CBD's direct target. ATP5A1, a subunit of ATP synthase, was identified and validated as a CBD target. Moreover, CBD demonstrated the ability to ameliorate METH-induced ubiquitination of ATP5A1 via the D376 residue, thereby reversing the METH-induced reduction of ATP5A1 and promoting the assembly of ATP synthase. Pharmacological inhibition of the ATP efflux channel pannexin 1, blockade of ATP hydrolysis by a CD39 inhibitor, and blocking the adenosine A1 receptor (A1R) all attenuated the therapeutic benefits of CBD in mitigating METH-induced behavioral sensitization and CPP. Moreover, the RNA interference of ATP5A1 in the ventral tegmental area resulted in the reversal of CBD's therapeutic efficacy against METH addiction. Collectively, these data show that ATP5A1 is a target for CBD to inhibit METH-induced addiction behaviors through the ADO-A1R signaling pathway.

OBJECTIVE: Circadian rhythm disruption (CRD) is a risk factor that correlates with poor prognosis across multiple tumor types, including hepatocellular carcinoma (HCC). However, its mechanism remains unclear. This study aimed to define HCC subtypes based on CRD and explore their individual heterogeneity. METHODS: To quantify CRD, the HCC CRD score (HCCcrds) was developed. Using machine learning algorithms, we identified CRD module genes and defined CRD-related HCC subtypes in The Cancer Genome Atlas liver HCC cohort (n = 369), and the robustness of this method was validated. Furthermore, we used bioinformatics tools to investigate the cellular heterogeneity across these CRD subtypes. RESULTS: We defined three distinct HCC subtypes that exhibit significant heterogeneity in prognosis. The CRD-related subtype with high HCCcrds was significantly correlated with worse prognosis, higher pathological grade, and advanced clinical stages, while the CRD-related subtype with low HCCcrds had better clinical outcomes. We also identified novel biomarkers for each subtype, such as nicotinamide n-methyltransferase and myristoylated alanine-rich protein kinase C substrate-like 1. CONCLUSION We classify the HCC patients into three distinct groups based on circadian rhythm and identify their specific biomarkers. Within these groups greater HCCcrds was associated with worse prognosis. This approach has the potential to improve prediction of an individual's prognosis, guide precision treatments, and assist clinical decision making for HCC patients. Please cite this article as: Li XJ, Chang L, Mi Y, Zhang G, Zhu SS, Zhang YX, et al. Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm. J Integr Med. 2025; 23(4): 445-456.
Humans ; Carcinoma, Hepatocellular/pathology* ; Liver Neoplasms/pathology* ; Circadian Rhythm/genetics* ; Prognosis ; Male ; Female ; Biomarkers, Tumor/genetics* ; Middle Aged ; Machine Learning ; Computational Biology