Bacillus mycoides JA20-1 was screened and identified as a biocontrol bacterium with a high capacity for producing volatile organic compounds(VOCs) in the laboratory. This strain had significant inhibitory effects on various postharvest disease pathogens in crops, such as Botrytis cinerea, as well as soil-borne disease pathogens in ginseng, such as Sclerotinia ginseng. In order to accelerate its industrialization process, in this study, single-factor experiments and response surface optimization methods were used. The fermentation medium and fermentation conditions in the shake flask of strain JA20-1 were systematically optimized by using cell production volume as the response variable. Meanwhile, the biocontrol effect of JA20-1 on B. cinerea of ginseng during the storage period was evaluated by using the method of fumigation in a dry dish in vitro. The results indicated that the optimal fermentation medium formulation for strain JA20-1 was as follows: 1% yeast paste, 1% soluble starch, 0.25% K_2HPO_4·3H_2O, and 0.2% NaCl. The optimal fermentation conditions in the shake flask were vaccination size of 3%, culture volume of 50 mL in a 250 mL Erlenmeyer flask, pH of 6.2, fermentation temperature of 34 ℃, shaking speed of 180 r·min~(-1), and incubation time of 18 hours. The bacteria count in the fermentation broth under these conditions reached 2.17 × 10~8 CFU·mL~(-1), which was 6.58 times higher than before. The average control efficacy of the fermentation broth on Botrytis cinerea of ginseng under in vitro fumigation reached 61.70% and 84.04% respectively, when 20 mL and 30 mL per dish were used. The research provided theoretical support and technical foundation for the development and utilization of Bacillus mycoides JA20-1 and the biocontrol of soil-borne diseases in ginseng and postharvest diseases in crops.
Botrytis/drug effects* ; Fermentation ; Panax/microbiology* ; Plant Diseases/prevention & control* ; Volatile Organic Compounds/metabolism* ; Bacillus/physiology* ; Pest Control, Biological/methods* ; Biological Control Agents/metabolism* ; Culture Media/chemistry*

Process analytical technology(PAT) is a key means for digital transformation and upgrading of the traditional Chinese medicine(TCM) manufacturing process, serving as an important guarantee for consistent and controllable TCM product quality. Near-infrared(NIR) spectroscopy has become the core technology for measuring the TCM manufacturing process. By incorporating NIR spectroscopy into PAT and starting from the construction of a smart platform for the TCM manufacturing process, this paper systematically described the development history and innovative application of the combination of NIR spectroscopy with chemometrics in measuring the TCM manufacturing process by the research team over the past two decades. Additionally, it explored the application of a validation method based on accuracy profile(AP) in the practice of NIR spectroscopy. Furthermore, the software development progress driven by NIR spectroscopy supported by modeling technology was analyzed, and the prospect of integrating NIR spectroscopy in smart factory control platforms was exemplified with the construction practices of related platforms. By integrating with the smart platform, NIR spectroscopy could improve production efficiency and guarantee product quality. Finally, the prospect of the smart platform application in measuring the TCM manufacturing process was projected. It is believed that the software development for NIR spectroscopy and the smart manufacturing platform will provide strong technical support for TCM digitalization and industrialization.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/analysis* ; Software ; Medicine, Chinese Traditional ; Quality Control

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Objective To investigate the efficacy of an interpretable integrated learning model combining clinical indicators,CT image features and radiomics features for the differential diagnosis of lung squamous cell carcinoma and adenocarcinoma,so as to provide references for clincal treatment decisions.Methods A retrospective analysis was conducted on clinical and imaging data from 220 patients(231 lesions)with primary non-small cell lung cancer at Jiangjin Central Hospital of Chongqing(Center 1)and 83 patients(84 lesions)at Chongqing General Hospital(Center 2).In Center 1,the squamous cell carcinoma group consisted of 60 patients(60 lesions),while the adenocarcinoma group included 160 patients(171 lesions).In Center 2,the squamous cell carcinoma group comprised 18 patients(18 lesions),and the adenocarcinoma group involved 65 patients(66 lesions).The patients were categorized into squamous cell carcinoma and adenocarcinoma groups based on pathological findings.Center 1 was randomly partitioned into a training set and a validation set at a 7∶3 ratio,while Center 2 served as the independent test set.Firstly,a deep learning model,VB-Net,was used to automatically segment the tumor region on the lung window image;secondly,the SMOTE(synthetic minority oversampling technique)method was used to balance the categories in the training set and standardize the extracted features with Z-scores;thirdly,the least absolute shrinkage and selection operator(LASSO)were used to select the optimal radiomics features and calculate the radiomics score(Radscore),and univariate and multivariate logistic regression was used to screen clinical indicators and independent clinical factors for differentiating lung squamous cell carcinoma and adenocarcinoma in CT image features;finally,three ensemble learning algorithms(AdaBoost,Bagging decision tree and XGBoost)were used to combine independent clinical factors and Radscore to construct the model.The receiver operating characteristic(ROC)curve was used to evaluate the diagnostic performance of the models.SHAP technique was used to analyze the feature contribution and model decision-making process.Results Among the evaluated ensemble models,AdaBoost and Bagging decision trees demonstrated overfitting tendencies.In contrast,the XGBoost model showed the best performance,achieving AUC values of 0.939,0.887 and 0.853 in the training,validation and independent test sets,respectively.SHAP indicated that Radscore was the most important feature affecting the performance of the model.The decision diagram enabled the visualization of the diagnostic process of the model.Conclusion The interpretable integrated learning model based on clinical indicators,CT image and radiomics features is expected to non-invasively diagnose lung squamous cell carcinoma and adenocarcinoma before treatment and assist clinicians make treatment decisions as early as possible.[Chinese Medical Equipment Journal,2025,46(7):12-20]

Background and aims Cancer cachexia is prevalent in various cancers and is associated with chemotherapy toxicity. However, limited data exist on the relationship between cachexia and immune-related adverse events (irAEs). The aim of this study is to explore the correlation between cancer cachexia and irAEs and its possible mechanism. Methods A murine model of orthotopic hepatocellular carcinoma (HCC) with cachexia was developed to evaluate the impact of T-cell infiltration into multiple tumor-free organs on the occurrence of irAEs. Single-cell RNA sequencing of thymic stromal cells was performed. Additionally, patients with advanced cancers receiving anti-programmed cell death protein 1/ligand 1 (PD-1/L1) antibody treatment were followed to investigate the relationship between cachexia and irAEs. Results Inflammatory cell infiltration was observed in multiple tumor-free organs of cachexic HCC mice but not in non-cachexic controls. Immunofluorescence confirmed that the infiltrating cells included CD4+ and CD8+ T cells. Morphological assessment and hematoxylin–eosin staining revealed thymic atrophy in cachexic HCC mice. Single-cell RNA sequencing of thymic stromal cells showed a reduction in medullary thymic epithelial cells (mTECs) II and III in cachexic mice. Autoimmune regulator (Aire) downregulation was accompanied by decreased expression of tissue-restricted antigens in mTECs. T cells from cachexic HCC mice induced organ-specific inflammation and T-cell infiltration in multiple organs of tumor-free mice. Following anti-mouse PD-1 antibody treatment, the incidence of inflammation in multiple organs markedly increased in cachexic HCC mice and in tumor-free mice that had received T cells from the cachexic HCC mice. Flow cytometry and immunofluorescence analyses revealed enrichment of thymic monocytic myeloid-derived suppressor cells (M-MDSCs) in cachexic HCC mice. M-MDSCs infiltrated the thymus in cachexic mice with cancer, and they induced apoptosis of mTECs from tumor-free mice in vitro via nitric oxide production. Transfer of M-MDSCs led to inflammatory cell infiltration in multiple organs and thymic involution in tumor-free mice without affecting body weight. Sixty-four patients with advanced cancer receiving anti-PD-1/L1 therapy were enrolled. Patients who developed irAEs had higher levels of circulating M-MDSCs than those who did not. Moreover, patients with cachexia (body mass index (BMI) < 20 kg/m2 or ≥5% weight loss over the past 6 months) had elevated M-MDSC levels. Patients with both high M-MDSC levels and low BMI or weight loss ≥5% experienced more irAEs (hazard ratio: 2.333; 95% confidence interval: 1.231–4.423). Conclusions M-MDSCs in cachexic mice induced mTEC apoptosis through nitric oxide production, impairing T-cell negative selection and promoting autoimmune T-cell infiltration into tumor-free organs. Cancer cachexia-related M-MDSCs may serve as predictive biomarkers for irAEs in patients with advanced cancer. Graphical abstract

Objective To investigate the protective effect and mechanism of acellular nerve allografts(ANA)combined with electroacupuncture on spinal ganglia in rats with sciatic nerve injury(SNI).Methods Totally 50 male adult SD rats were randomly selected for this experiment.Ten rats were prepared for the ANA.Forty male SD rats were randomly divided into normal group,model group,ANA group and combinational group,with 10 rats in each group.The SNI model was established by cutting off the nerves 10 mm at the 5 mm on the inferior border of piriformis after separating the right sciatic nerves.The rats in the ANA group were bridged with ANA to the two broken ends of injured nerves.The rats in the combinational group were treated with electroacupuncture 2 days after ANA bridging,Huantiao(GB30)and Yanglingquan(GB34)were performed as the acupuncture points,each electroacupuncture lasted 15 minutes and 7 days as a course of treatment,4 courses in all.Sciatic nerve conduction velocity was measured by electrophysiology to evaluate the regeneration of damaged axons.Morphology of spinal ganglia was observed by Nissl staining.The expression of nerve growth factor(NGF)and brain-derived neurotrophic factor(BDNF)were detected by Western blotting and immunofluorescent staining.Results Compared with the normal group,the sciatic nerve conduction velocity in model group decreased significantly(P<0.01),Nissl bodies in neurons of spinal ganglia were swollen and dissolved,with incomplete structure and the number decreased dramatically(P<0.01),while the level of NGF and BDNF also decreased significantly(P<0.01).Compared with the model group,the sciatic nerve conduction velocity in ANA and combinational groups strongly increased(P<0.01),the damage of Nissl bodies in neurons of spinal ganglia reduced and the number obviously increased(P<0.01),the level of NGF and BDNF increased considerably(P<0.01).Compared with the ANA group,the sciatic nerve conduction velocity in combinational group increased significantly(P<0.01),the morphology of Nissl bodies in neurons of spinal ganglia were more regular and the number increased(P<0.01),moreover,the level of NGF also increased significantly(P<0.01).Conclusion ANA combined with electroacupuncture can enhance the sciatic nerve conduction velocity,improve the morphology of neurons in spinal ganglia and play a protective effect on spinal ganglia.The mechanism can be related to the higher expression of NGF and BDNF proteins,especially the expression of NGF protein.

As a major global public health problem, pulmonary diseases threaten human life and health while causing a huge economic burden. The messenger RNA (mRNA)-based inhalation preparation, which effectively targets pulmonary cells can overcome the problems of traditional therapy, such as high side effects, low pulmonary bioavailability, and difficulty in synthesizing target proteins in vitro, thus providing new ideas for the treatment of pulmonary diseases. However, as the lung structure is complex and mRNA has trouble entering cells, researchers have been attempting to develop a suitable nano delivery system for higher delivery efficiency. This review introduces the barriers to pulmonary delivery, discusses the recent research development of the mRNA pulmonary delivery systems, including lipid nanoparticles, polymeric nanoparticles, polypeptides and exosomes, summarizes their limitations and looks forward to the application of mRNA inhalation preparations.

ObjectiveTo investigate the mRNA expression levels of various aquaporins （AQPs） in luteinized granulosa cells from follicles of different diameters. MethodsFrom March 25， 2022 to September 23， 2022 in our reproductive medicine center， 48 women undergoing in-vitro fertilization （IVF） were enrolled and divided into the antagonist group and the agonist group according to the ovarian stimulation protocol. Follicular fluid samples were collected on the day of oocyte pick-up and granulosa cells were extracted from follicles of different diameters： small （<13 mm）， medium （13~18 mm） and large （≥18 mm）. After RNA quantification， 22 cases （66 samples） were included for analysis and mRNA expression levels of AQPs were compared among the three follicle groups. ResultsThe mRNA expression of aquaporin 2 （AQP2） in luteinized granulosa cells increased with the increase of follicle diameter （linear trend P = 0.004） and the difference was statistically significant between two groups of large and small follicles （P = 0.017）. Statistical difference was found in the antagonist group （P = 0.049 6）， but not in the agonist group （P = 0.108）. ConclusionThe mRNA level of AQP2 in luteinized granulosa cells increases with the increase of follicle diameter and its expression is related to the ovarian stimulation protocol， suggesting that AQP2 may play a role in follicle growth and follicular fluid formation， and its mRNA expression level may be regulated by follicle stimulating hormone （FSH） and luteinizing hormone （LH）.