In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

OBJECTIVE: To investigate the genetic causal relationship of leukocyte telomere length (LTL) with prostatitis, orchitis and epididymitis by two-sample Mendelian randomization (MR). METHODS: Using LTL as the exposure factor and prostatitis, orchitis and epididymitis as outcome factors, we mined the Database of Genome-Wide Association Studies (GWAS). Then, we analyzed the causal relationship of LTL with prostatitis, orchitis and epididymitis by Mendelian randomization using inverse variance weighting (IVW) as the main method and weighted median and MR-Egger regression as auxiliary methods, determined the horizontal multiplicity by MR-Egger intercept test, and conducted sensitivity analysis using the leaving-one-out method. RESULTS: A total of 121 related single nucleotide polymorphisms (SNPs) were identified in this study. IVW showed LTL to be a risk factor for prostatitis (OR = 1.383, 95% CI: 1.044－1.832, P = 0.024), and for orchitis and epididymitis as well (OR = 1.770, 95% CI: 1.275－2.456, P = 0.000 6). CONCLUSION Genetic evidence from Mendelian randomized analysis indicates that shortening of LTL reduces the risk of prostatitis, orchitis and epididymitis.
Humans ; Male ; Mendelian Randomization Analysis ; Epididymitis/genetics* ; Prostatitis/genetics* ; Polymorphism, Single Nucleotide ; Leukocytes ; Orchitis/genetics* ; Genome-Wide Association Study ; Telomere ; Risk Factors

OBJECTIVE: To investigate the effect of acupuncture on advanced cancer patients by meta-analysis. METHODS: Nine databases (the Cochrane Central Register of Controlled Trials, MEDLINE, Web of Science, Embase, China National Knowledge Infrastructure, the Cumulative Index to Nursing and Allied Health Literature, Chinese Biomedical Literature Database, China Science and Technology Journal Database, and WanFang Data) were searched for randomized controlled trials (RCTs) on acupuncture in advanced cancer patients published from inception to February 13, 2023 and updated to June 1, 2023. Primary outcomes were quality of life (QOL), while secondary outcomes were pain, fatigue, and adverse events (side effects). Data synthesis was performed using RevMan V.5.3 to calculate pooled effect sizes. RoB-2 was used for the risk of bias, and the quality of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool. RESULTS: Totally 17 RCTs involving 1,178 participants were included, 15 of which were pooled for meta-analysis. Most studies demonstrated some concern for the overall risk of bias. The pooled data indicated that acupuncture was associated with improved QOL [mean difference (MD)=6.67, 95% confidence interval (CI): 5.09 to 8.26], pain (MD=-1.18, 95% CI -2.28 to -0.08), and adverse events (risk ratio=0.30, 95% CI: 0.26 to 0.57) compared with control groups. Fatigue outcome was not included. Heterogeneity was substantial, and GRADE evidence was very low for both QOL and pain. CONCLUSIONS Acupuncture could benefit patients with advanced cancer and is considered safe compared with usual care. However, the evidence regarding QOL and pain outcomes requires further validation. It is crucial to encourage the development of high-quality studies to strengthen this evidence. (Registry No. CRD42023423539).
Humans ; Acupuncture Therapy ; Neoplasms/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Treatment Outcome

Ursodeoxycholic acid (UDCA) is a naturally occurring, low-toxicity, and hydrophilic bile acid (BA) in the human body that is converted by intestinal flora using primary BA. Solute carrier family 7 member 11 (SLC7A11) functions to uptake extracellular cystine in exchange for glutamate, and is highly expressed in a variety of human cancers. Retroperitoneal liposarcoma (RLPS) refers to liposarcoma originating from the retroperitoneal area. Lipidomics analysis revealed that UDCA was one of the most significantly downregulated metabolites in sera of RLPS patients compared with healthy subjects. The augmentation of UDCA concentration (≥25 μg/mL) demonstrated a suppressive effect on the proliferation of liposarcoma cells. [¹⁵N₂]-cystine and [¹³C₅]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione (GSH) synthesis. Mechanistically, UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis, leading to reactive oxygen species (ROS) accumulation and mitochondrial oxidative damage. Furthermore, UDCA can promote the anti-cancer effects of ferroptosis inducers (Erastin, RSL3), the murine double minute 2 (MDM2) inhibitors (Nutlin 3a, RG7112), cyclin dependent kinase 4 (CDK4) inhibitor (Abemaciclib), and glutaminase inhibitor (CB839). Together, UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity, and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA. More importantly, in combination with other antitumor chemotherapy or physiotherapy treatments, UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

ObjectiveTo investigate the significance of different non-treatment thresholds or upper limits of normal （ULN） of alanine aminotransferase （ALT） in evaluating significant liver pathological injury in patients with chronic hepatitis B virus （HBV） infection， and to provide guidance for clinical diagnosis and treatment. MethodsThis study was conducted among 733 patients with chronic HBV infection who were hospitalized in Ningbo No. 2 Hospital from January 2015 to December 2023 and underwent liver biopsy and histopathological examination， and all patients had a persistent ALT level of ≤40 U/L and positive HBV DNA （>30 IU/mL）. According to the treatment threshold or ULN of ALT， the patients were divided into group 1 with 575 patients （≤35 U/L for male patients， ≤25 U/L for female patients）， group 2 with 430 patients （≤30 U/L for male patients， ≤19 U/L for female patients）， group 3 with 443 patients （≤27 U/L for male patients， ≤24 U/L for female patients）， group 4 with 446 patients （≤25 U/L）， group 5 with 158 patients （>35 U/L for male patients， >25 U/L for female patients）， and group 6 with 145 patients （>30 — ≤35 U/L for male patients， >19 — ≤25 U/L for female patients）. Groups 2， 5， and 6 were compared to analyze the severity of liver pathological injury in patients with different ALT levels and the constituent ratio of patients with significant liver pathological injury， and groups 1， 2， 3， and 4 were compared to investigate the value of different ULN or non-treatment thresholds of ALT in determining liver inflammation grade （G）， liver fibrosis stage （S）， and the treatment indication based on liver pathology. The independent-samples t test was used for comparison of normally distributed continuous data between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test or the Tambane’s test was used for further comparison between two groups； the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups and further comparison between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； a Ridit analysis was used for comparison of ranked data. A multivariate Logistic regression analysis （forward stepwise） was performed with whether liver pathology met the treatment indication （≥G2 and/or ≥S2） as the dependent variable and related factors with a significant impact on the dependent variable （P <0.05） as the independent variable. The receiver operating characteristic （ROC） curve was plotted， and the area under the ROC curve （AUC）， as well as sensitivity， specificity， positive predictive value， negative predictive value， positive likelihood ratio， and negative likelihood ratio， was used to assess the diagnostic value of different non-treatment thresholds of ALT. ResultsAmong the 733 patients， 259 （35.33%） had ≥G2 liver inflammation， 211 （28.79%） had ≥S2 liver fibrosis， and 306 （41.75%） had treatment indication （≥G2 and/or ≥S2）. There was a significant difference in liver inflammation grade （G0 — G4） between groups 2， 5， and 6 （χ²=22.869， P <0.001）， and there were also significant differences in the constituent ratios of patients with ≥G2 or ≥G3 liver inflammation between the three groups （χ²=21.742 and 14.921， P<0.001 and P=0.001）. There was a significant difference in liver fibrosis stage （S0 — S4） between groups 2， 5， and 6 （χ²=16.565， P<0.001）， and there were also significant differences in the constituent ratios of patients with ≥S2， ≥S3 or S4 liver fibrosis between the three groups （χ²=13.264， 13.050， and 6.260， P=0.001， 0.001， and 0.044）. There were significant differences between groups 2， 5， and 6 in the constituent ratios of patients with or without treatment indication based on liver pathology （χ²=20.728， P<0.001）. There were significant differences between groups 2， 5， and 6 in the constituent ratio of male patients （χ²=24.836， P<0.05）， age （F=5.710， P<0.05）， ALT （F=473.193， P<0.05）， aspartate aminotransferase （AST） （F=107.774， P<0.05）， ALT/AST ratio （F=40.167， P<0.05）， γ-glutamyl transpeptidase （GGT） （H=15.463， P<0.05）， aspartate aminotransferase-to-platelet ratio index （APRI） （H=63.024， P<0.05）， and LIF-5 （5 indicators for liver inflammation and fibrosis） （H=46.397， P<0.05）. In groups 1 — 4， compared with the patients without treatment indication， the patients with treatment indication had a significantly lower constituent ratio of patients with positive HBeAg， significantly lower levels of platelet count （PLT） and HBV DNA， and significantly higher age， ALT， AST， GGT， APRI， FIB-4， and LIF-5 （all P<0.05）. The Logistic regression analysis showed that age （odds ratio ［OR］=1.044， 95% confidence interval ［CI］： 1.025 — 1.063， P<0.001）， GGT （OR=1.022， 95%CI： 1.007 — 1.038， P=0.003）， and HBV DNA （OR=0.839， 95%CI： 0.765 — 0.919， P<0.001） were influencing factors for treatment indication based on liver pathology in group 1； HBeAg （OR=1.978， 95%CI： 1.269 — 3.082， P=0.003）， age （OR=1.048， 95%CI： 1.025 — 1.071， P<0.001）， GGT （OR=1.016， 95%CI： 1.001 — 1.031， P=0.041）， and PLT （OR=0.995， 95%CI： 0.991 — 1.000， P=0.049） were influencing factors in group 2； age （OR=1.040， 95%CI： 1.014 — 1.066， P=0.002）， ALT （OR=1.047， 95%CI： 1.005 — 1.092， P=0.029）， HBV DNA （OR=0.817， 95%CI： 0.736 — 0.907， P<0.001）， and LIF-5 （OR=7.382， 95%CI： 1.151 — 47.330， P=0.035） were influencing factors in group 3； age （OR=1.054， 95%CI： 1.031 — 1.077， P<0.001）， ALT （OR=1.061， 95%CI： 1.016 — 1.107， P=0.008）， and HBV DNA （OR=0.825， 95%CI： 0.743 — 0.917， P<0.001） were influencing factors in group 4. The diagnostic performance for identifying ≥G2 liver inflammation， ≥S2 liver fibrosis， and treatment indication in groups 1 — 4 had an AUC of >0.7； group 1 showed the lowest sensitivity （28.76%） and the highest specificity， positive predictive value， positive likelihood ratio， and negative likelihood ratio in judging treatment indication； group 2 had the highest sensitivity and negative predictive value and the lowest negative likelihood ratio； groups 3 and 4 had similar diagnostic indicators. ConclusionIn patients with chronic HBV infection and a persistently low ALT level， the severity of liver histopathological injury and the constituent ratio of significant liver histopathological injury decrease with the reduction in ALT level. A higher non-treatment threshold or ULN of ALT can help to identify the patients requiring treatment （with a higher specificity）， while a lower non-treatment threshold or ULN of ALT can help to identify the patients who do not require treatment （with a higher sensitivity）.

Objective To investigate the effects of Simo decoction on duodenal microinflammation and NOD-like receptor thermal protein domain associated protein 3(NLRP3)/cysteinyl aspartate-specific proteinase-1(Caspase-1)/gasdermin D(GSDMD)signaling pathway in rats with functional dyspepsia(FD).Methods The FD model was established by multifactorial method.SD rats were randomly divided into normal group,model group(FD model),positive control group(gavage administration of 0.305 mg·kg-1 mosapride injection)and experimental-H,-M,-L groups(gavage administration of 5.62,2.81,1.40 g·kg-1 Simo decoction).Small intestinal advancement rate and gastric emptying rate was determined;the levels of interleukin(IL)-1 β and IL-18 in serum were determined by enzyme linked immunosorbent assay(ELISA);the protein expression of NLRP3 and GSDMD in duodenal tissue was detected by Western blotting.Results The gastric emptying rates of normal,model,positive control and experimental-H,-M,-Lgroupswere(58.34±5.72)％,(29.16±8.37)％,(48.77±6.10)％,(48.35±6.04)％,(48.20±3.49)％and(39.24±4.20)％;the small intestinal propulsion rates were(82.01±7.55)％,(41.95±9.53)％,(64.61±10.18)％,(75.04±9.76)％,(60.58±7.13)％and(45.89±7.40)％;serum IL-1 β expression were(12.86±0.88),(43.73±4.60),(18.84±0.86),(24.61±1.57),(19.14±0.77)and(29.04±0.72)pg·mL-1;IL-18 expressions were(95.00±3.74),(170.60±8.78),(108.50±3.05),(118.90±3.45),(99.90±8.70)and(141.00±3.71)pg·mL-1;the relative expression levels of NLRP3 proteins were 0.32±0.02,0.84±0.05,0.42±0.03,0.48±0.02,0.61±0.04 and 0.62±0.05;the relative expression levels of GSDMD proteins were 0.34±0.05,0.93±0.06,0.35±0.03,0.52±0.02,0.53±0.06 and 0.55±0.05,respectively.Compared with the normal group,the above indexes in the model group have statistical significance;compared with the model group,the above indexes in the experimental-H group and the positive control group also have statistical significance(P＜0.01 or P＜0.05).Conclusion Simo decoction can effectively improve the general condition and duodenal microinflammation in FD rats,and the mechanism may be related to the inhibition of duodenal NLRP3/Caspase-1/GSDMD signaling pathway.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective To predict the risk of in-hospital death in patients with chronic heart failure(CHF)complicated by lung infections using interpretable machine learning.Methods The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database.According to the pathogen type,the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups,and their risks of in-hospital death were compared using Kaplan-Meier survival curves.Univariate analysis and LASSO regression were used to select the features for constructing LR,AdaBoost,XGBoost,and LightGBM models,and their performance was compared in terms of accuracy,precision,F1 value,and AUC.External validation of the models was performed using the data from eICU-CRD database.SHAP algorithm was applied for interpretive analysis of XGBoost model.Results Among the 4 constructed models,the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set.In the external test set,the XGBoost model had an AUC of 0.691(95%CI:0.654-0.720)in bacterial pneumonia group and an AUC of 0.725(95%CI:0.577-0.782)in non-bacterial pneumonia group,and showed better predictive ability and stability than the other models.Conclusion The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections.The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.

Objective To predict the risk of in-hospital death in patients with chronic heart failure(CHF)complicated by lung infections using interpretable machine learning.Methods The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database.According to the pathogen type,the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups,and their risks of in-hospital death were compared using Kaplan-Meier survival curves.Univariate analysis and LASSO regression were used to select the features for constructing LR,AdaBoost,XGBoost,and LightGBM models,and their performance was compared in terms of accuracy,precision,F1 value,and AUC.External validation of the models was performed using the data from eICU-CRD database.SHAP algorithm was applied for interpretive analysis of XGBoost model.Results Among the 4 constructed models,the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set.In the external test set,the XGBoost model had an AUC of 0.691(95%CI:0.654-0.720)in bacterial pneumonia group and an AUC of 0.725(95%CI:0.577-0.782)in non-bacterial pneumonia group,and showed better predictive ability and stability than the other models.Conclusion The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections.The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.