Objective To investigate the clinical prognostic value of the prognostic nutritional index (PNI) in patients with renal cell carcinoma (RCC) undergoing partial nephrectomy.Methods A retrospective analysis was conducted on the clinical data of RCC patients who underwent partial nephrectomy at our hospital during 2020 and 2024.The optimal cutoff value of PNI was determined based on the maximum Youden index from the receiver operating characteristic (ROC) curve.The clinicopathological characteristics, overall survival (OS), and progression-free survival (PFS) between patients with different PNI levels were compared.Cox regression analysis was used to explore the independent prognostic factors for RCC patients. Results Based on the ROC curve, the optimal cutoff value corresponding to the maximum Youden index was calculated to be 46.675, at which point the sensitivity was 65.3% and the specificity was 62.2%.Of the 815 patients included in the study, 293 (36.0%) patients had a PNI＜46.675.Cox regression analysis confirmed that preoperative PNI, tumor diameter, ISUP classification, and ECOG score were independent risk factors for postoperative OS in patients with RCC who underwent PN (P＜0.05).In addition, preoperative PNI, tumor diameter, ISUP classification and ECOG score were independent risk factors for postoperative PFS (P＜0.05).After covariates in the multivariable Cox regression model were adjusted, patients in the low PNI group demonstrated significantly shorter overall survival (HR=2.392, P＜0.001) and significantly poorer progression-free survival (HR=2.076, P＜0.001) compared to those in the high PNI group.Conclusion Preoperative PNI has significant clinical value in evaluating the prognosis of RCC patients undergoing partial nephrectomy.An elevated preoperative PNI is associated with a better prognosis.

ObjectiveTo investigate the clinical features of tumor-induced acute pancreatitis （TIAP）， to construct and validate a predictive model for TIAP， and to provide help for early identification in clinical practice. MethodsA retrospective analysis was performed for the clinical data of 3 051 patients with acute pancreatitis （AP） who were admitted to The First Affiliated Hospital of Xinjiang Medical University from January 2020 to January 2026， among whom there were 72 patients with TIAP. To reduce class imbalance， 216 patients with non-tumor-related AP （2 979 patients） were randomly selected as conventional group using sex-stratified sampling， resulting in a cohort of 288 patients， and this cohort was randomly divided into a training set with 201 patients and a test set with 87 patients at a ratio of 7∶3. The two groups were compared in terms of general information and laboratory markers. 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 data between two groups. Recursive feature elimination and least absolute shrinkage and selection operator regression were used for screening of characteristic variables， and five machine learning models were constructed， i.e.， logistic regression model， random forest model， support vector machine model， extreme gradient boosting model， and light gradient boosting machine model. The receiver operating characteristic curve and the precision-recall curve were used to assess model performance； the calibration curve was used to assess goodness of fit； decision curve analysis was used to evaluate clinical applicability and practicality； Shapley additive explanations were used to assess model interpretability. ResultsIn the training set of 201 patients， there were 52 patients （25.9%） in the TIAP group， and in the test set of 87 patients， there were 20 patients （23.0%） in the TIAP group. Compared with the conventional group， the TIAP group had a significantly higher proportion of patients with pancreatic duct dilatation （χ²=79.474， P<0.05）， a significantly higher age （Z=-5.838， P<0.05）， and significantly lower levels of white blood cell count （Z=5.630， P<0.05）， amylase （Z=2.606， P<0.05）， hemoglobin （Z=5.038， P<0.05）， and neutrophil percentage （Z=5.269， P<0.05）， as well as a lower level of direct bilirubin （Z=0.936， P>0.05）. The five machine learning models constructed based on these seven variables had a certain predictive ability， among which the logistic regression model had the best performance in the test set， with an area under the curve of 0.893 （95% confidence interval： 0.821 — 0.953）， an average precision of 0.654 in the precision-recall curve， good calibration， and good clinical benefits based on the decision curve analysis. ConclusionThe predictive model for TIAP based on pancreatic duct dilatation， age， white blood cell count， amylase， hemoglobin， neutrophil percentage， and direct bilirubin shows good predictive performance and can provide important guidance for the early diagnosis of TIAP.

The Huangdi Neijing proposes the " using bitter herbs to nourish or purge" theory to guide clinical prescription and formulation of herbal remedies based on the physiological characteristics and functions of the five zang viscera, along with the properties and flavors of medicinal herbs. This study explored diabetic kidney disease pathogenesis and treatment based on the " using bitter herbs to nourish or purge" theory. Kidney dryness is a key pathological factor in diabetic kidney disease, and the disharmony of kidney dryness is an essential aspect of its pathogenesis. Strengthening is the primary therapeutic principle, and kidney dryness is a persistent factor throughout the occurrence and progression of diabetic kidney disease. In the early stage, the pathogenesis involves heat-consuming qi and injuring yin, leading to kidney dryness. In the middle stage, the pathogenesis manifests as qi deficiency and blood stasis in the collaterals, resulting in turbidity owing to kidney dryness. In the late stage, the pathogenesis involves yin and yang deficiency, with kidney dryness and disharmony. This study proposes the staging-based treatment based on the " need for firmness" characteristic of the kidney. The aim is to provide new insights for clinical diagnosis and treatment in traditional Chinese medicine by rationally using pungent, bitter, and salty medicinal herbs to nourish and moisturize the kidney. This approach seeks to promote precise syndrome differentiation and personalized treatment for different stages of diabetic kidney disease, thereby enhancing clinical efficacy.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

ObjectiveTo study the effects of applying different microbial fertilizers on the growth and rhizosphere soil environment of Codonopsis pilosula and provide a theoretical basis for ecological cultivation of this medicinal plant. MethodsSeven groups were designed， including CK （no application of microbial fertilizer）， T1 （Trichoderma longibrachiatum fertilizer）， T2 （Bacillus subtilis fertilizer）， T3 （Trichoderma viride fertilizer）， T4 （compound microbial fertilizer）， T5 （C. pilosula stems and leaves fermented with compound microbial fertilizer）， and T6 （Scutellaria baicalensis stems and leaves fermented with T. viride fertilizer）. The physiological indicators， yield， and quality of C. pilosula and the physicochemical properties， enzyme activities， and microbial diversity in the rhizosphere soil of different fertilizer treatments were measured. ResultsGroup T1 showed slight decreases in soluble protein content （SPC） and superoxide dismutase （SOD）. Groups T2-T6 showed increases in physiological indicators such as proline （Pro）， soluble solids content （SSC）， SPC， catalase （CAT）， and peroxidase （POD） and a decrease in malondialdehyde （MDA） in C. pilosula leaves. All the fertilizer treatments increased the yield of C. pilosula and the total polysaccharide content in the roots. T1， T2， T3， T4， and T5 increased the total flavonoid content in the roots. Meanwhile， T4 increased the total saponin content in the roots. All the fertilizer treatments reduced the pH and increased the electric conductivity （EC）， soil organic matter （SOM）， and alkaline nitrogen （AN） in the soil. T2 and T5 increased the available phosphorus （AP）， and T3， T4， T5， and T6 increased the available potassium （AK） in the soil. All the fertilizer treatments increased the activities of urease， sucrase， and CAT in the soil. Except that T1 decreased the bacterial diversity in the soil， other fertilizer treatments significantly increased bacterial and fungal diversity in the soil. Different fertilizer treatments significantly affected the composition of bacterial and fungal communities in the soil. At the phylum level， the dominant bacterial phyla included Proteobacteria， Acidobacteriota， and Bacteroideta， and the dominant fungal phyla were Ascomycota， Mortierellomycota， and unclassified_fungi in the rhizosphere soil of C. pilosula after bacterial fertilizer treatment. At the genus level， unclassified Gemmatimonadaceae， Sphingomonas， and unclassified Vicinamibacteraceae were the dominant bacterial genera， while unidentified， unclassified Fungi， and unclassified Sordariomycetes were the dominant fungal genera in the rhizosphere soil. The results of redundancy analysis indicated that the main physicochemical factors affecting changes of microbial communities in the rhizosphere soil of C. pilosula were pH， EC， AK， AN， AP， and soil organic matter （SOM） in the soil. The correlation heatmap showed that Bryobacter had significantly positive correlations with EC， AK， and AN. There was a significantly negative correlation between Fusarium and SOM. In summary， applying an appropriate amount of microbial fertilizer can promote the growth and improve the rhizosphere soil environment of C. pilosula. ConclusionThe compound microbial fertilizer and the C. pilosula stems and leaves fermented with compound microbial fertilizer can improve the soil nutrients， growth， development， yield， and quality of C. pilosula， and thus they can be applied to the artificial cultivation of C. pilosula.

Objective To analyze the ecological suitability of Codonopsis pilosula;To provide theoretical reference for expanding the planting scale of Codonopsis pilosula in Shanxi Province.Methods Information on the distribution of Codonopsis pilosula samples through the fourth survey of TCM resources in Shanxi Province and literature review;the MaxEnt model and ArcGIS 10.8 geographic information system software were used to analyze the ecological factors affecting the distribution of Codonopsis Radix in Shanxi Province,and the suitable distribution areas of Codonopsis pilosula in Shanxi Province were predicted.Results The predicted distribution areas of Codonopsis pilosula in Shanxi Province by the model were highly consistent with the actual distribution area;the AUC of the training set was 0.945,indicating good prediction results.The predominant ecological factors(contributing)impacting the distribution of Codonopsis pilosula included vegetation type(31.1%),the standard deviation of seasonal temperature fluctuations(25.0%),slope(8.3%),mean January precipitation(5.3%),mean May precipitation(5.0%),and elevation(4.9%)etc.The optimal vegetation types conducive to the proliferation of Codonopsis pilosula were identified as temperate deciduous shrubs,temperate grasslands,temperate coniferous forests,and temperate deciduous broad-leaved forests.The standard deviation of seasonal temperature change was within the range of 92 to 108,the slope gradient was from 14° to 30°,mean January precipitation was of 4 to 6.8 mm,mean May precipitation was of 33.5 to 58 mm,and elevation ranged from 1 100 to 2 800 meters.Codonopsis pilosula was mainly distributed in Lucheng,Qinxian and Qinyuan counties in the eastern part of Taiyue Mountain in Changzhi City;Pu County,Fenxi County,Fenyang City of Lyuliang City in the Lyuliang Mountain Range and Yushe County of Jinzhong City in the northern part of Taiyue Mountain.The most suitable area in Shanxi Province was 14 109.67 km2,the suitable area encompassed 22 837.62 km2,the relatively suitable area covered 41 982.96 km2,while the unsuitable area extended over 77 769.75 km2.Conclusion The geographical distribution data of Codonopsis pilosula resources in Shanxi Province may serve as a basis for further examination of regional zoning,with the establishment of wild cultivation bases for Codonopsis pilosula in proximity to various mountain ranges,such as the Taihang Mountains.Moreover,the artificial cultivation conditions can be modified in accordance with the optimal growth environment of Codonopsis pilosula,thereby optimizing the management of Codonopsis resources.

Diabetic kidney disease(DKD)is one of the serious complications of diabetes.Ferroptosis causes pathological damage and is involved in the progression of DKD.How to inhibit ferroptosis and delay DKD is a new academic hotspot.The author's team further enriched and proposed the core pathogenesis theory of"internal heat induced disease"on the basis of the traditional DKD"yin deficiency and dryness-heat"theory,and explained the general development law of DKD.In this article,"internal heat"and"Zhengjia"in the theory of DKD"internal heat induced diseases"are used as the starting point to explore the relationship of the main pathological damage of ferroptosis such as activating inflammatory response,enhancing oxidative stress,promoting fibrosis and so on with the internal mechanism of the theory of"internal heat induced diseases",further explained the scientific connotation of DKD"internal heat induced diseases",in order to provide ideas and theoretical basis for the TCM prevention and treatment of DKD.

Biometric recognition technology has developed rapidly and highly integrated with clinical diagnostics,phenotypic genomics,genomics,and big data analytics,facilitating not only precise personal identification but also demonstrating significant potential in health maintenance,particularly for military personnel.Global research has increasingly focused on uncovering the complex associations between biometric traits and key health determinants,such as disease susceptibility,psychological states,and physiological functions,to further harness biometrics in proactive health management.This paper provided a comprehensive overview of the latest progress and emerging applications of biometric technology in healthcare and military medicine,aiming to offer a scientific reference supporting the strategic development of biometrics research,its application promotion,and population-wide health management enhancement.

Objective To identify candidate compounds that activate thermogenesis during cold exposure by integrating the Library of Integrated Network-Based Cellular Signatures(LINCS)with RNA expression profiles specific to cold-induced thermogenesis.Methods Gene expression profiles of interscapular brown adipose tissue(BAT)and inguinal white adipose tissue(iWAT)were generated from 8-week-old C57BL/6J mice which were housed at 5 ℃ or room temperature(23 ℃)for 7 days.The gene expression signatures of the cold-induced BAT and iWAT were compared to the LINCS dataset to predict potential candidates for testing in a cold challenge model that was intended to assess thermogenesis activation.The pharmacological potential of the identified compounds was evaluated in a cold-exposed mouse model.The core body temperature and infrared thermal imaging were collected to monitor physiological responses during cold exposure.Additionally,hematoxylin and eosin(HE)staining was used to assess morphological changes of fat cells of BAT,iWAT,and epididymal white adipose tissue(eWAT).Results The transcriptomic signatures related to cold-induced thermogenesis were obtained and the top 20 candidate compounds were identified by comparison with the LINCS dataset.Mice treated with withaferin A(WA)during the cold challenge exhibited elevated rectal temperatures and smaller adipocyte sizes compared to controls.Conclusion Our drug repurposing strategy,which connects transcriptional profiles with LINCS data,identifies potential compounds.WA enhances thermogenesis and metabolic activity in adipose tissue,which helps maintain body temperature,and improves cold tolerance during exposure to low temperatures.