Objective To analyze survival outcomes and influencing factors among patients with colorectal cancer in Yunnan Province. Methods Clinical data were retrospectively collected from 4 892 patients with colorectal cancer. Survival data were obtained through follow-up. Overall survival (OS) was calculated by using the Kaplan-Meier method. Univariate analysis was performed by applying the log-rank test. Meanwhile, multivariate analysis employed the Cox proportional hazards regression model. Results The 1-, 3-, 5-, and 10-year OS rates for the entire cohort were 91.90%, 74.40%, 64.40%, and 28.70%, respectively. Univariate analysis revealed that age, ethnicity, region, differentiation grade, TNM stage, clinical stage, metastatic status, histological type, and treatment modality (chemotherapy, radiotherapy, and surgery) were associated with patient prognosis (all P<0.05). Multivariate analysis identified age (HR=1.250), region (HR=1.262), differentiation grade (HR=0.761), clinical stage (HR=3.128), and treatment modality (chemotherapy, HR=0.644; radiotherapy, HR=1.605; surgery, HR=0.384) as independent factors affecting survival prognosis in patients with colorectal cancer (all P<0.001). Conclusion Age, region, clinical stage, and treatment modality are independent factors influencing survival among patients with colorectal cancer in Yunnan Province. In clinical practice, these factors should be integrated to develop individualized prevention and treatment strategies, thereby improving patient outcomes.

Thyroid diseases are common clinical endocrine disorders， and their pathogenesis is generally considered to be closely related to genetic predisposition factors， immune system disorders， hormone levels， etc. Xiaoyaosan is widely used in the treatment of various thyroid diseases with excellent effects. This study summarized the relevant literature on the treatment of thyroid diseases with modified Xiaoyaosan prescriptions and their active ingredients from aspects such as theoretical analysis， clinical research， and mechanism research. Theoretical analysis revealed that Xiaoyaosan could not only disperse stagnated liver qi but also replenish deficient spleen Qi， which was consistent with the etiology and pathogenesis of thyroid diseases. Clinical studies found that Xiaoyaosan and its modified prescriptions could be widely used in the treatment of multiple thyroid diseases， such as hyperthyroidism， Hashimoto's thyroiditis， and thyroid nodules. Both the use of modified Xiaoyaosan alone and in combination with medications such as methimazole， propylthiouracil， and euthyrox could effectively improve patients' clinical symptoms. In the mechanism research， this study discovered that the whole formula of Xiaoyaosan and its modified prescriptions could inhibit inflammatory reactions， regulate immune balance， and delay liver damage during the treatment of thyroid diseases. The research on Xiaoyaosan for treating thyroid diseases mainly focused on thyroid cancer， autoimmune thyroiditis， hyperthyroidism， and hypothyroidism. The mechanisms of action mainly involved promoting cell apoptosis， inhibiting cell proliferation and migration， arresting the cell cycle， and regulating thyroid hormone levels. In conclusion， this study systematically combs and summarizes the research status of Xiaoyaosan in treating thyroid diseases through literature retrieval， aiming to provide new perspectives and new ideas for the prevention and treatment of thyroid diseases with traditional Chinese medicine.

ObjectiveBased on the theory of "gut-prostate" axis， this study explored the effects and mechanisms of Zishen Tongguan formula and Cinnamomi Cortex in the formula in treating rats with chronic non-bacterial prostatitis（CNP） by detecting the levels of inflammatory factors， and the composition and structure of intestinal flora in CNP rats. MethodsEight out of 42 SD rats were randomly selected as the normal group， and the remaining rats were injected with carrageenan to prepare the CNP model. After successful modeling， 32 rats were randomly divided into the model group， Ningmitai capsule group（0.50 g·kg^-1）， Zishen Tongguan formula group（2.00 g·kg^-1）， and the Phellodendri Chinensis Cortex-Anemarrhenae Rhizoma pair group（PCC-AR group， 2.00 g·kg^-1）， with 8 rats in each group. The administered groups were given the corresponding medicinal solution by gavage， and the normal and model groups were intragastrically administered with an equal volume of normal saline， once a day for 14 consecutive days. The prostate tissues of rats were collected and subjected to hematoxylin-eosin（HE） staining and Masson staining to observe the pathological changes of the tissues in each group. Enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of related inflammatory factors in rat serum， and 16S rDNA sequencing was used to analyze the abundance and diversity changes of gut microbiota before and after administration， and species difference analysis was performed. ResultsAll the administered groups could alleviate the inflammatory symptoms of CNP rats， increase the expression levels of anti-inflammatory factors and decrease the expression levels of pro-inflammatory factors， with the most sIgnificant effect observed in the Zishen Tongguan formula group. Compared with the normal group， the expression levels of interleukin（IL）-8， hypersensitive C-reactive protein（hs-CRP）， immunoglobulin（Ig）M， secretory IgA （sIgA）， and inducible nitric oxide synthase（iNOS） were sIgnificantly increased in the model group（P<0.01）. Compared with the model group， the expression levels of the above inflammatory factors in all administered groups were significantly reduced（P<0.01）. When compared with the PCC-AR group， the Zishen Tongguan formula group showed a significant decrease in transforming growth factor（TGF）-β₁ expression level（P<0.05） and a significant increase in IgM expression level（P<0.01）. The results of gut microbiota analysis showed that， compared with the PCC-AR group， at the order level， the Zishen Tongguan formula group significantly reduced the relative abundance of conditional pathogens such as Bacteroidales， Acidaminococcales， Rhodospirillales， Clostridiales， and Elusimicrobiales（P<0.01）. And at the genus level， the Zishen Tongguan formula group significantly decreased the relative abundance of pathogenic microbiota such as Lachnospira and Bacteroides（P<0.01） and significantly increased the relative abundances of beneficial microbiota such as Ruminococcus and Lactobacillus（P<0.01）. ConclusionZishen Tongguan formula can reduce the level of harmful intestinal bacteria， increase the level of beneficial intestinal bacteria， down-regulate the expression of serum inflammatory factors， and the small amount of Cinnamomi Cortex in the formula may play a key role in the treatment of CNP with this formula.

ObjectiveBased on the theory of "gut-prostate" axis， this study explored the effects and mechanisms of Zishen Tongguan formula and Cinnamomi Cortex in the formula in treating rats with chronic non-bacterial prostatitis（CNP） by detecting the levels of inflammatory factors， and the composition and structure of intestinal flora in CNP rats. MethodsEight out of 42 SD rats were randomly selected as the normal group， and the remaining rats were injected with carrageenan to prepare the CNP model. After successful modeling， 32 rats were randomly divided into the model group， Ningmitai capsule group（0.50 g·kg^-1）， Zishen Tongguan formula group（2.00 g·kg^-1）， and the Phellodendri Chinensis Cortex-Anemarrhenae Rhizoma pair group（PCC-AR group， 2.00 g·kg^-1）， with 8 rats in each group. The administered groups were given the corresponding medicinal solution by gavage， and the normal and model groups were intragastrically administered with an equal volume of normal saline， once a day for 14 consecutive days. The prostate tissues of rats were collected and subjected to hematoxylin-eosin（HE） staining and Masson staining to observe the pathological changes of the tissues in each group. Enzyme-linked immunosorbent assay（ELISA） was used to detect the levels of related inflammatory factors in rat serum， and 16S rDNA sequencing was used to analyze the abundance and diversity changes of gut microbiota before and after administration， and species difference analysis was performed. ResultsAll the administered groups could alleviate the inflammatory symptoms of CNP rats， increase the expression levels of anti-inflammatory factors and decrease the expression levels of pro-inflammatory factors， with the most sIgnificant effect observed in the Zishen Tongguan formula group. Compared with the normal group， the expression levels of interleukin（IL）-8， hypersensitive C-reactive protein（hs-CRP）， immunoglobulin（Ig）M， secretory IgA （sIgA）， and inducible nitric oxide synthase（iNOS） were sIgnificantly increased in the model group（P<0.01）. Compared with the model group， the expression levels of the above inflammatory factors in all administered groups were significantly reduced（P<0.01）. When compared with the PCC-AR group， the Zishen Tongguan formula group showed a significant decrease in transforming growth factor（TGF）-β₁ expression level（P<0.05） and a significant increase in IgM expression level（P<0.01）. The results of gut microbiota analysis showed that， compared with the PCC-AR group， at the order level， the Zishen Tongguan formula group significantly reduced the relative abundance of conditional pathogens such as Bacteroidales， Acidaminococcales， Rhodospirillales， Clostridiales， and Elusimicrobiales（P<0.01）. And at the genus level， the Zishen Tongguan formula group significantly decreased the relative abundance of pathogenic microbiota such as Lachnospira and Bacteroides（P<0.01） and significantly increased the relative abundances of beneficial microbiota such as Ruminococcus and Lactobacillus（P<0.01）. ConclusionZishen Tongguan formula can reduce the level of harmful intestinal bacteria， increase the level of beneficial intestinal bacteria， down-regulate the expression of serum inflammatory factors， and the small amount of Cinnamomi Cortex in the formula may play a key role in the treatment of CNP with this formula.

ObjectiveTo investigate the risk factors for pyogenic liver abscess （PLA） comorbid with sepsis by analyzing clinical features， and to construct a predictive model. MethodsA retrospective analysis was performed for 489 patients who were hospitalized and diagnosed with PLA in The Affiliated Hospital of Xuzhou Medical University from January 2019 to December 2023， and according to the presence or absence of sepsis， they were divided into sepsis group with 306 patients and non-sepsis group with 183 patients. Related data were collected， including general information， laboratory markers， and outcome measures. The patients were further divided into a training set of 342 patients and a validation set of 147 patients at a ratio of 7∶3， and the training set was used for screening of variables and construction of a predictive model， while the validation set was used to test the performance of the model. An LASSO regression analysis was used for the screening of variables， and a multivariate Logistic regression analysis was used to construct the predictive model and plot a nomogram. The calibration curve， the receiver operating characteristic （ROC） curve， and the decision curve analysis were used for the validation of the model， and internal validation was performed for assessment. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical variables between groups. ResultsThere were significant differences between the sepsis group and the non-sepsis group in pulse rate， mean arterial pressure， duration pf symptoms， comorbidity of liver cirrhosis or malignant tumor， leukocyte count， neutrophil count， lymphocyte count， platelet count （PLT）， activated partial thromboplastin time， fibrinogen， C-reactive protein， aspartate aminotransferase， alanine aminotransferase， albumin， total bilirubin （TBil）， creatinine， potassium， and prognostic nutritional index （PNI） （all P<0.05）. In the training set， the LASSO regression analysis identified four predictive factors of pulse rate， PLT， TBil and PNI， and the multivariate Logistic regression analysis showed that pulse rate （odds ratio ［OR］=1.033， 95% confidence interval ［CI］： 1.006‍ ‍—‍ ‍1.061， P=0.018）， PLT （OR=0.981， 95%CI： 0.975‍ ‍—‍ ‍0.987， P<0.001）， TBil （OR=1.086， 95%CI： 1.053‍ ‍—‍ ‍1.125， P<0.001）， and PNI （OR=0.935， 95%CI： 0.882‍ ‍—‍ ‍0.988， P=0.019） were independent influencing factors for the risk of sepsis in patients with PLA. The model constructed based on these factors showed a good predictive ability， with an area under the ROC curve of 0.948 （95%CI： 0.923‍ ‍—‍ ‍0.973） in the training set and 0.912 （95%CI： 0.848‍ ‍—‍ ‍0.976） in the validation set. The decision curve analysis showed that the model has a good net benefit within the range of 0.3‍ ‍—‍ ‍0.9 for threshold probability. ConclusionThe nomogram prediction model constructed based on pulse rate， PLT， TBil， and PNI has a certain clinical value and can well predict the risk of sepsis in patients with PLA.

Objective: To explore the influencing factors for sarcopenia among elderly male patients with type 2 diabetes (T2DM), so as to provide the basis for the early prevention and treatment of sarcopenia. Methods: Male T2DM patients aged 60 and above admitted to Hangzhou First People's Hospital from January to December 2024 were selected as the study subjects. Demographic data, T2DM complications, and blood biochemical parameters were collected. Physical activity levels were assessed using the Chinese version of the International Physical Activity Questionnaire. The diagnosis of sarcopenia was made according to the diagnostic procedures and criteria established by the Asian Working Group for Sarcopenia in 2019. Factors affecting sarcopenia among elderly male patients with T2DM were analyzed using multivariable logistic regression model. Results: A total of 455 elderly male patients with T2DM were surveyed, with a mean age of (71.80±9.55) years. The predominant physical activity level was moderate with 226 cases accounting for 49.67%. The disease course of T2DM was mainly from 10-<20 years, with 229 cases accounting for 50.33%. There were 140 cases of T2DM complications, accounting for 30.77%. A total of 138 cases of sarcopenia were detected, with a prevalence of 30.33%. Multivariable logistic regression analysis showed that age (OR=1.077, 95%CI: 1.003~1.156), body mass index (<18.5kg/m2, OR=11.056, 95%CI: 3.343~36.547; 18.5~<25.0 kg/m2, OR=2.633, 95%CI: 1.420~4.881), physical activity level (low, OR=2.469, 95%CI: 1.421~4.292), chronic obstructive pulmonary disease (yes, OR=1.871, 95%CI: 1.091~3.206), T2DM complications (yes, OR=3.015, 95%CI: 1.516~6.001), glycated hemoglobin (≥7%, OR=2.822, 95%CI: 1.423~5.590) and albumin (OR=0.810, 95%CI: 0.662~0.991) were factors affecting sarcopenia among elderly male patients with T2DM (P<0.05). Conclusion Advanced age, body mass index <25.0 kg/m2, low physical activity level, chronic obstructive pulmonary disease, T2DM complications, high glycated hemoglobin and low albumin are associated with a higher risk of sarcopenia in elderly male patients with T2DM.

Objective:To investigate the factors influencing the delayed onset of intrapartum fever following epidural labor analgesia and their impact on maternal and neonatal outcomes.Methods:Select parturients who experienced intrapartum fever following labor analgesia(T≥38.0℃,age≥18 years,singleton pregnancy,ASA classification Ⅱ)between January 1,2021,and December 31,2023.Group them based on the median time of intra-partum fever onset after labor analgesia:those with onset times less than the median were classified as the ear-ly-onset fever group,and those with onset times greater than the median were classified as the late-onset fever group.Using univariate and multivariate Logistic regression analysis to explore factors influencing the delay in in-trapartum fever onset and the pregnancy outcomes of the mothers and newborns in both groups.Results:A total of 253 parturients were included,and the time range of onset of intrapartum fever following epidural labor analgesi-a was 1.83-28.42 hours,with a median fever onset time of 8.00 hours.There were 126 cases in the early-onset group and 127 in the late-onset group.Multivariate Logistic regression analysis indicated that primiparous women,artificial membrane rupture,and neonatal birth weight were independent risk factors for delayed fever onset(OR＞1,P＜0.05),whereas the administration of oxytocin prior to labor analgesia was found to be a protective factor(OR＜1,P＜0.05).The late-onset group exhibited higher levels of white blood cells(WBC),C-reactive pro-tein,longer hospital stays,higher hospitalization costs,greater diagnosis rates of chorioamnionitis,higher NICU ad-mission rates,as well as a higher incidence of neonatal pneumonia,for newborns compared to the early-onset group(P＜0.05).Conclusions:Primiparous women,artificial membrane rupture,and higher neonatal birth weight may be associated with delayed onset of intrapartum fever,while oxytocin administration prior to labor analgesia may offer some protective benefit.The later the onset of intrapartum fever,the worse the clinical outcomes for both mother and infants.

Objective::To examine the impact of hypertensive disorders of pregnancy (HDP) on offspring metabolomics.Methods::We searched five databases: PubMed, Ovid Embase, MEDLINE, Web of Science, and China National Knowledge Infrastructure, and included studies that reported metabolomics among human offspring born to HDP-complicated pregnancies.Results::Database search yielded 4054 articles, and after full-text screening, ten observational studies met inclusion criteria. Half of the studies had a sample size of less than 100 and were all observational studies in preeclampsia (PE) and gestational hypertension.Neonates were the most focused group in all included studies. Offspring born to HDP-complicated pregnancies exhibited statistically significant variations in blood metabolomics compared to their counterparts, characterized by amino acids, lipids, carnitine, and others (e.g., 1α,25-(OH) 2-D). Most studies reported a significant increase in differential metabolites of offspring born to HDP-complicated pregnancies. Four studies ( n = 1109) measured lipids-related metabolites, and all consistently showed that offspring born to PE-complicated pregnancies had significantly higher concentrations than non-PE exposed offspring. Conclusion::The existing evidence suggests an intergenerational effect of HDP on offspring metabolomics. Long-term follow-up studies are needed to advance the health effects of related adverse health outcomes and inform the prevention of offspring’s health.

Objective To quantitatively evaluate the structure and content of the long-term care insurance(LTCI)policy in China's deeply aging areas.Methods Using the Policy Modeling Consistency(PMC)index model indicator design method,a LTCI policy evalua-tion index system was constructed,consisting of nine primary indicators and 34 secondary indicators.A total of 123 provincial-level LTCI policies issued in deeply aging regions of China between June 1,2014,and October 1,2024 were analyzed.High-frequency word extraction was performed using ROSTCM 6.0,and a social network diagram of LTCI policies was created.The policy structure and content were quantitatively evaluated and ana-lyzed based on the established policy evaluation index system.Results The main content of LTCI policies in deeply aging areas of China covered services,institutions and assessment.The highest policy score was 7.28,and the lowest was 2.20,with an average score of 5.00.There were 25 perfect policies,63 excellent policies,28 good policies and seven qualified policies.In the dimension of policy content,the indexes of five primary indicators of policy evaluation,policy target groups,policy nature,policy perspective and policy tools were 0.60 or more;while the indexes of four primary indicators of policy content,incentives and constraints,policy timeliness,and policy level were 0.50 or less.Conclusion LTCI policies issued in China's deeply aging areas provide comprehensive coverage in aspects such as poli-cy evaluation,policy target groups and policy nature,and need to be improved in policy tool selection and the construction of incentive and constraint mechanisms.

Objective:To establish a rapid quantitative model of sodium chloride content in Halitum of traditional Chinese medicine by using X-ray diffraction technology and machine learning algorithm.Methods:The data of X-ray diffraction patterns of 90 batches of Halitum samples were collected,and the rapid prediction models of X-ray diffraction were constructed by using partial least squares(PLS),support vector regression(SVR)long short-term memory(LSTM)according to the reference values determined by the content determination method of Halitum in the Chinese Pharmacopoeia 2020 edition.Results:The data preprocessed by multivariate scatter correction(MSC)and selected by competitive adaptive reweighted sampling(CARS)were better in PLS model and LSTM model.The data pretreated by standard normal transformation(SNV)and selected by CARS feature variable perform well in SVR.Conclusion:The three models show good prediction potential,which shows that the combination of X-ray diffraction technology and machine learning algorithm is feasible for accurate prediction of the content of Halitum in traditional Chinese medicine.