Colorectal inflammatory cancer transformation poses a major risk to patients with colitis.Patients with chronic intestinal inflammation have an approximately 2-3 fold increased risk of developing colorectal cancer(CRC).Unfortunately,there is currently no effective intervention available.Huangqin decoction(HQD),a well-known traditional Chinese medicine(TCM)formula,is frequently clinically prescribed for treating patients with colitis,and its active ingredients have effective antitumour efficacy.Nonetheless,the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear.A strategy integrating metagenomic,lipidomic,and messenger RNA(mRNA)sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome,metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation.Our study revealed that HQD suppressed colorectal inflammatory cancer transformation,which was associated with enhanced in-testinal barrier function,decreased the inflammatory response,and regulation of the gut microbiome.Notably,cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis.Moreover,gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism,especially the remodeling of arachidonic acid metabolism,which was associated with the amelioration of pathological transformation.Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase(ALOX12)were affected by HQD treatment,and no obvious protective effect of HQD was observed in Alox12-/-mice,which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation.In summary,multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory CRC.

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Objective:To investigate the relationship between serum tumor markers and the severity of silicosis.Methods:In April 2024, A cluster sampling was conducted on the pulmonary rehabilitation centers in Jiangsu Province. A retrospective analysis was carried out on 629 patients who received follow-up physical examinations for pneumoconiosis from April to November 2023 at the selected rehabilitation centers. 281 healthy volunteers who underwent occupational health examinations at our institution were selected as the blank control group, and 384 dust exposed workers from a coal mining enterprise were selected as the dust exposed control group. Detect the levels of peripheral bloodtumor markers carcinoembryonic antigen CEA, carbohydrate antigen CA199, and neuron-specific enolase NSE in specimens. Measure the patient's forced vital capacity (FVC), forced expiratory volume in one second (FEV 1), and lactate acid dehydrogenase (LDH) levels in the blood. The Jonckheere-Terpstra test, a non-parametric test for ordered independent samples, was used to compare the expression levels of tumor markers among multiple groups. Spearman's rank correlation analysis was adopted to explore the correlations between serum tumor markers and the staging of pneumoconiosis as well as lung function parameters. Results:Among the 629 patients with pneumoconiosis, 454 were in stage Ⅰ, 150 were in stage Ⅱ, 25 were in stage Ⅲ. There were significant differences in serum CEA, CA199 and NSE levels among patients with different periods of pneumoconiosis, blank control group and dust-exposed control group ( P<0.001). Serum CEA, CA199 and NSE levels were positively correlated with pneumoconiosis stage ( P<0.05). There is a negative correlation between serum CA199 levels and FEV 1% in patients with pneumoconiosis ( r=-0.082, P<0.05). The serum CA199 level was positively correlated with LDH in patients with pneumoconiosis ( r=0.108, P<0.05) .The serum NSE level of pneumoconiosis patients was negatively correlated with FVC% ( r=-0.079, P<0.05) .There is a positive correlation between serum NSE levels and LDH in patients with pneumoconiosis ( r=0.435, P<0.05) . Conclusion:The serum CA199 and NSE of pneumoconiosis patients are directly related to the severity and stage of the disease, which have practical significance in judging the treatment effect of pneumoconiosis patients and monitoring the development of the disease.

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

PURPOSE: To analyze risk factors for severe trauma and establish a nomogram for early risk prediction, to improve the early identification of severe trauma. METHODS: This study was conducted on the patients treated in 81 trauma treatment institutions in Gansu province from 2020 to 2022. Patients were grouped by year, with 5364 patients from 2020 to 2021 as the training set and 1094 newly admitted patients in 2020 as the external validation set. Based on the injury severity score (ISS), patients in the training set were classified into 2 subgroups of the severe trauma group (n = 478, ISS scores ≥25) and the non-severe trauma group (n = 4886, ISS scores <25). Univariate and binary logistic regression analyses were employed to identify independent risk factors for severe trauma. Subsequently, a predictive model was developed using the R software environment. Furthermore, the model was subjected to internal and external validation via the Hosmer-Lemeshow test and receiver operating characteristic curve analysis. RESULTS: In total, 6458 trauma patients were included in this study. Initially, this study identified several independent risk factors for severe trauma, including multiple traumatic injuries (polytrauma), external hemorrhage, elevated shock index, elevated respiratory rate, decreased peripheral oxygen saturation, and decreased Glasgow coma scale score (all p < 0.05). For internal validation, the area under the receiver operating characteristic curve was 0.914, with the sensitivity and specificity of 88.4% and 87.6%, respectively; while for external validation, the area under the receiver operating characteristic curve was 0.936, with the sensitivity and specificity of 84.6% and 93.7%, respectively. In addition, a good model fitting was observed through the Hosmer-Lemeshow test and calibration curve analysis (p > 0.05). CONCLUSION This study establishes a nomogram for early risk prediction of severe trauma, which is suitable for primary healthcare institutions in underdeveloped western China. It facilitates early triage and quantitative assessment of trauma severity by clinicians prior to clinical interventions.
Humans ; Nomograms ; Male ; Female ; Wounds and Injuries/diagnosis* ; Risk Factors ; Middle Aged ; Adult ; Injury Severity Score ; Risk Assessment ; ROC Curve ; Aged ; Logistic Models ; China ; Glasgow Coma Scale

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

AIM To investigate the effects of Polygonum cuspidatum and polydatin on lipid deposition in adipose tissue of high-fat diet-induced obese mice.METHODS Forty male C57BL/6J mice were randomly assigned to either a control group(10 mice)fed standard chow or a diet-induced obesity(DIO)group(30 mice)fed a high-fat diet for 8 weeks.The successful mouse models were randomly assigned to the model group,the polydatin group(250 mg/kg)and the P.cuspidatum group(4.5 g/kg),with 8 mice in each group,to resume their high-fat diet during the following 8 weeks corresponding drug administration by gavage.Weekly body weight measurements were recorded for all mice.Serum TG,TC and LDL levels were quantified post-treatment.Histopathological assessment of adipose tissue was performed using HE staining.The mRNA expressions of AMPK,SREBP-1c and FAS in adipose tissue were analyzed by RT-qPCR.The protein expressions of p-AMPK,SREBP-1c and FAS in adipose tissue was detected by Western blot.RESULTS Compared to the control group,the model group displayed significantly higher body weight,inguinal fat weight and epididymal fat weight(P＜0.05);elevated serum TG,TC and LDL levels(P＜0.05);markedly enlarged volumes of inguinal and epididymal adipocytes(P＜0.01);reduced p-AMPK protein expression in inguinal adipose tissue(P＜0.01);and upregulated mRNA and protein expressions of SREBP-1c and FAS(P＜0.05,P＜0.01).Compared to the model group,both the P.cuspidatum group and polygonin group exhibited significantly reduced body weight and inguinal fat weight(P＜0.05);decreased serum TG and TC levels(P＜0.05);reduced inguinal adipocyte size(P＜0.01);elevated p-AMPK protein expression in inguinal adipose tissue(P＜0.01);and downregulated mRNA and protein expressions of SREBP-1c and FAS(P＜0.05,P＜0.01).CONCLUSION P.cuspidatum and polydatin significantly increases p-AMPK expression while decreasing SREBP-1c and FAS levels in adipose tissue.This regulatory effect likely contributes to reduction of body weight in obese mice through suppression of lipogenesis.

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

Colorectal inflammatory cancer transformation poses a major risk to patients with colitis. Patients with chronic intestinal inflammation have an approximately 2-3 folds increased risk of developing colorectal cancer (CRC). Unfortunately, there is currently no effective intervention available. Huangqin decoction (HQD), a well-known traditional Chinese medicine (TCM) formula, is frequently clinically prescribed for treating patients with colitis, and its active ingredients have effective antitumour efficacy. Nonetheless, the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear. A strategy integrating metagenomic, lipidomic, and messenger RNA (mRNA) sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome, metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation. Our study revealed that HQD suppressed colorectal inflammatory cancer transformation, which was associated with enhanced intestinal barrier function, decreased the inflammatory response, and regulation of the gut microbiome. Notably, cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis. Moreover, gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism, especially the remodeling of arachidonic acid metabolism, which was associated with the amelioration of pathological transformation. Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase (ALOX12) were affected by HQD treatment, and no obvious protective effect of HQD was observed in Alox 12 ^-/- mice, which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation. In summary, multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory CRC.

Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the "therapeutic module" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.