Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

Objective To predict the radiation impact of discharging wastewater containing uranium within the specified limit generated during the normal operation of a new production line at a nuclear fuel plant on the receiving water body and its downstream, and to provide a reference for the management of radioactive liquid effluent discharge from nuclear facilities. Methods Based on the technical guidelines for environmental impact assessment, literature on radiation environmental impact assessment, and data collected from on-site investigations, appropriate hydrological parameters and prediction models were selected to analyze and predict the variation pattern of radioactive nuclide uranium along the receiving water body and the radiation exposure of nearby residents. Results The maximum increase in uranium concentration in the receiving water body and its downstream caused by the discharge of uranium-containing wastewater was 1.14 μg/L. The maximum predicted concentration was 2.75 μg/L after adding the background data of the water body. The resulting maximum individual annual effective dose for the public was 1.49 × 10⁻⁴ mSv/a. Conclusion The maximum predicted uranium concentration in the receiving water body and its downstream is lower than the uranium concentration limit of 30 μg/L specified in the Standards for Drinking Water Quality (GB 5749-2022). The maximum individual annual effective dose for the public is much lower than the control value of 0.2 mSv/a specified in the Radiation Protection Regulations for Uranium Processing and Fuel and Fuel Manufacturing Facilities (EJ 1056-2018). The radiation impact is acceptable.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Objective To study the chemical constituents of Fallopia aubertii L.Henry Holub. Methods The chemical constituents of Fallopia aubertii L.Henry Holub. were separated and purified by online two-dimensional preparative liquid chromatography and identified by physical and chemical constants and spectral analysis. The inhibitory activities on xanthine oxidase were determined by ultraviolet spectrophotometry. Results Ten compounds were isolated from the extract of Fallopia aubertii L.Henry Holub, including isotachioside（1）, 3,4,5-trimethoxyphenyl-（6'-O-galloyl）-O-β-D-Glucopyranoside（2）, 1-hydroxy-,4,5-1-O-[6'-O-（4''-carboxy-1'',3'',5'trihydrotrimethoxyphenylxy）-phenyl]-β-D-glucopyranoside（3）, myricetrin（4）, myricetin（5）, rutin（6）, quercetin-3-O-β-D-galactoside（7）, quercetin-3-O-β-D-glucopyranoside（8）, lyciumideA（9）, and N-trans-Feruloyltyramine（10）. The inhibitory activity test results showed that the IC₅₀ of compound 5 was 15.92 μmol/L, and the IC₅₀ of compound 6 was 87.36 μmol/L. Conclusion Compounds 1,2,3,4 and 8 were isolated from Medicago polymorpha for the first time. Compounds 5 and 6 had xanthine oxidase inhibitory activity.

OBJECTIVE To analyze the chemical constituents and components absorbed into plasma of the extract of Ardisia crenata and to elucidate its possible pharmacodynamic material basis. METHODS Overall， 12 rats were randomly assigned to the blank group （n＝6） and A. crenata group （n＝6） by the paired comparison method. The drug was administered once daily in the morning and afternoon for three days. Serum samples were prepared from serum after redosing on 4th day. The UPLC-QE-HF-MS/ MS was used to analyze and identify the chemical constituents in A. crenata extract and serum samples. Compound Discoverer 3.0 was employed for retention time correction， peak identification， and peak extraction. According to the secondary mass spectrometry information， the Thermo mzCloud online and Thermo mzVault local databases， referring to the relevant literature and control quality spectrum information were used to preliminarily identify the chemical constituents and components absorbed into plasma of A. crenata. RESULTS A total of 34 compounds were identified from the extract of A. crenata， mainly coumarins， flavonoids， organic acids， amino acids， including bergenin， quercetin， gallic acid， L-pyroglutamic acid， etc. Besides， 5 components absorbed into plasma were identified from serum samples: L-pyroglutamic acid， syringic acid， bergenin， cinnabar root saponin A， and mycophenolic acid. CONCLUSIONS L-pyroglutamic acid， syringic acid， bergenin， cinnabar root saponin A， and mycophenolic acid may act as the pharmacodynamic material basis of A. crenata.

Objective To evaluate the effects of high-fat diet on the pharmacokinetics of metronidazole in Chinese healthy adult subjects.Methods This program is designed according to a single-center,randomized,open,single-dose trial.Forty-seven healthy subjects were assigned to receive single dose of metronidazole tablets 200 mg in either fasting and high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of metronidazole in plasma were determined by high performance liquid chromatography-mass spectromentry.Results The main pharmacokinetic parameters of metronidazole in fasting state and high-fat diet state were as follows:Cmax were(4 799.13±1 195.32)and(4 044.17±773.98)ng·mL-1;tmax were 1.00 and 2.25 h;t1/2 were(9.11±1.73)and(9.37±1.79)h;AUC0_t were(5.59±1.19)x 104 and(5.51±1.18)x 104 ng·mL-1·h;AUC0_∞ were(5.79±1.33)x 104 and(5.74±1.32)× 104 ng·mL-1·h.Compared to the fasting state,the tmaxof the drug taken after a high fat diet was delayed by 1.25 h(P＜0.01),Cmax,AUC0_t,AUC0-∞ were less or decreased in different degrees,but the effects were small(all P＞0.05).Conclusion High-fat diet has little effects on the pharmacokinetic parameters of metronidazole,which does not significantly change the degree of drug absorption,but can significantly delay the time to peak.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

Objective To evaluate the characteristics of the mass balance and pharmacokinetics of[14 C]birociclib in Chinese male healthy volunteers after a single oral administration.Methods This study used a 14 C labeled method to investigate the mass balance and biological transformation of birociclib in human.Subjects were given a single oral dose of 360 mg/50 pCi of[14 C]birociclib suspension after meals.The blood,urine,and fecal samples were collected at specified time points/intervals after administration.The radiation levels of 14 C labeled birociclib-related compounds in the blood,plasma,urine,and feces were analyzed using liquid scintillation counting.In addition,a combination of high-performance liquid chromatography and on-line/off-line isotope detectors was used to obtain radioactive isotope metabolite spectra of plasma,urine,and fecal samples,and high-resolution mass spectrometry was used to identify the main metabolites.Results A total of 6 healthy male subjects were enrolled in this study.The median peak time of radioactive components in plasma was 5.00 h and the average terminal elimination half-life was 43.70 h after administration.The radioactive components were basically excreted and cleared from the body within 288.00 hours after administration,and average cumulative recovery rate of radioactive drugs was(94.10±8.19)％.The radioactive drugs were mainly excreted through feces,accounting for(84.60±7.10)％of the dose of radioactive drugs administered.Urine was the secondary excretory pathway,accounting for 9.41％of the dose of radioactive drugs administered.Metabolic analysis indicated that the prototype drug was the main radioactive components in plasma samples.The main metabolites in plasma were RM4(XZP-5286),RM6(XZP-3584),and RM7(XZP-5736).The drugs were mainly cleared from the body in the form of prototype drugs and metabolites.In addition to prototype drugs,a total of 9 metabolites were identified and analyzed in plasma,urine,and fecal samples,all of which were phase 1 metabolites.The main metabolic and clearance pathways of drugs in the body were deethylation,diisopropylat ion,oxidation,etc.Conclusion After a single oral administration of[14C]birociclib suspension to healthy subjects,it was mainly cleared from the body in the form of prototype drugs and metabolites,with feces as the main excretory pathway and urine as the secondary excretory pathway.Drugs mainly undergo metabolic reactions in the body,such as deethylation,diisopropylation,and oxidation.The subjects were well tolerance after administration.