Objective: To investigate the efficacy and safety of intelligent temperature-pressure-controlled flexible ureteroscopy combined with negative-pressure suction sheath lithotripsy in the treatment of upper urinary tract stones ≤2.5 cm. Methods: The clinical data of 225 patients with ≤2.5 cm upper urinary tract stones treated with this surgical method in our department during Aug. 2023 and Jul. 2024 were retrospectively analyzed. The patients were divided into the dual-control group (n=36) and conventional group (n=189) according to whether or not the intelligent temperature and pressure control device was used during operation. In the dual-control group，the intraoperative temperature and pressure in the renal pelvis were monitored and controlled in real time by the temperature and pressure sensors distributed at the end of the ureteral soft lens. The perioperative parameters，stone-removal rate，complication rate and renal function were compared between the two groups. Results: All operations were successfully completed in both groups. The postoperative procalcitonin (PCT) level [(22.75±5.85) ng/L vs. (29.08±6.60) ng/L，P=0.001]，difference in the white blood cell (WBC) level [(0.24±2.12)×10 cells/L vs. (1.19±2.17)×10 cells/L，P=0.016]，incidence of fever (2.8% vs. 16.9%，P=0.028) and overall complication rate (5.6% vs. 19.6%，P=0.042) were significantly lower in the dual-control group than in the conventional group，while the stone-clearance rate was slightly higher (88.9% vs. 82.5%，P=0.346)，with no significant difference. Conclusion: For upper urinary tract stones ≤2.5 cm，intelligent temperature-pressure-controlled ureteroscopy combined with negative-pressure suction sheath lithotripsy has a satisfactory stone-removal rate and a low rate of complications，which is worthy of clinical promotion.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.

Objective : To investigate the effects of branched-chain amino acid(BCAA) on the differentiation of 3T3-L1 preadipocytes and its potential mechanism. Methods : 3T3-L1 preadipocytes were divided into the Control, differentiation medium(DM), low-concentration BCAA, and high-concentration BCAA groups. A CCK-8 assay was utilized to evaluate pre-adipocyte survival under various BCAA concentrations. Oil-red O staining was used to observe the formation of lipid droplets in adipocytes. Intracellular triglyceride(TG) and total cholesterol(TC) were detected by enzymatic method. RT-qPCR and Western blot were used to detect the mRNA and protein expression of Stat3 and adipocyte differentiation-related genes. Results : CCK-8 results showed that the viability of 3T3-L1 cells was not affected when the BCAA concentration was ≤ 10 mmol/L. Compared with the DM group, the low-concentration BCAA groups(0.5 and 1.0 mmol/L) had significantly larger intracellular lipid droplets, increased number of lipid droplets, and elevated levels of the intracellular TC(0.88vs0.68 mmol/g; 0.83vs0.68 mmol/g,P<0.01) and TG(0.77vs0.40 mmol/g; 0.62vs0.40 mmol/g,P<0.01). Nevertheless, the cell differentiation in the high-concentration group(5.0 and 10.0 mmol/L) significantly decreased compared with that in the DM group. Further, levels of PPARγ, C/EBPα, Adiponectin, and FABP4 mRNA and protein expression significantly increased in the low-concentration group, but significantly decreased in the high-concentration group than that in the DM group(P<0.01). In addition, low concentrations of BCAA promoted stat3 phosphorylation, while high concentrations inhibited its phosphorylation(P<0.01). Conclusion BCAA have a dual role in regulating the differentiation of preadipocytes through Stat3, i.e. low concentrations of BCAA induce cell differentiation by promoting Stat3 phosphorylation; whereas high concentrations of BCAA inhibit Stat3 phosphorylation and cell differentiation.

ObjectiveTo investigate the identification of kidney Yang deficiency syndrome of patients with osteoporosis（OP）， and to form the clinical syndrome identification rules of traditional Chinese medicine（TCM）. MethodBasic information， etiology， clinical symptoms and other characteristics of 982 OP patients were included， and statistical tests were used to screen the variables associated with kidney Yang deficiency syndrome. Taking the decision tree as the base model， bootstrap aggregation algorithm（Bagging algorithm） was utilized to establish the classification model of kidney Yang deficiency syndrome in OP， generating numerous rules and removing redundancy. Combining least absolute shrinkage and selection operator（LASSO） regression to screen key rules and integrate them to construct an identification model， achieving the identification of kidney Yang deficiency syndrome in OP patients. ResultEighteen key identification rules were screened out， and of these， where 11 rules with regression coefficients>0 correlated positively with the kidney Yang deficiency syndrome， the rule with the highest coefficient was chilliness（present）&feverish sensation over the palm and sole（absent）. The other 7 rules with regression coefficients<0 correlated negatively with the syndrome， the rule with the lowest coefficient was reddish tongue（present）&diarrhea（absent）&deficiency of endowment（absent）. According to the regression coefficients of each key rule， variables with importance>0.2 were ranked as chilliness， reddish tongue， feverish sensation over the palm and sole， cold limbs， clear urine， diarrhea， deficiency of endowment， prolonged illness. The results of the partial dependence analysis of the identification model showed that compared to OP patients without chilliness， those with chilliness（present） had a 0.266 8 higher probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identification of the syndrome. Similarly， compared to OP patients without reddish tongue， those with reddish tongue had a 0.141 9 lower probability of being identified as having kidney Yang deficiency syndrome， indicating that this variable had the highest impact on identifying non-kidney Yang deficiency syndrome. The accuracy， sensitivity， specificity and area under receiver operating characteristic curve（AUC） of the established kidney Yang deficiency syndrome identification model in the test set were 0.865 9， 0.853 7， 0.872 0 and 0.931 5， respectively. ConclusionA precise identification model of OP kidney Yang deficiency syndrome is conducted basing on the rule ensemble method of Bagging combining LASSO regression， and the screened key rules can explain the identification process of kidney Yang deficiency syndrome. In this research， according to the regression coefficients of rules， the importance and partial dependence of variables， combined with the thinking of TCM， the influence of patient characteristics on the identification of syndromes is described， so as to reveal the primary and secondary syndromes of identification and assist the clinical identification of kidney Yang deficiency syndrome.

A 3-year-old male patient was diagnosed with neurofibromatosis type 1(NF1) for two years. The patient has multiple neurofibromas in retroperitoneum, lumbococcygeal paravertebral, lumbosacral spinal canal, and foramina. Due to retroperitoneal mass compression, the child suffered from urological complications such as hydronephrosis, ureterdilation, neurogenic bladder, etc., which seriously affected the urination function and resulted in multiple surgical treatments. Currently, the patient has been treated with mitogen activates extracelluar signal-regulated kinases(MEK) inhibitor selumetinib targeted therapy, and has voluntarily urinated, and his general state is better than before medication. The diagnosis and treatment of this case reflects the importance of multidisciplinary collaboration in the diagnosis and treatment of rare diseases.

【Objective】 To establish a nomogram model for predicting the risk of positive prostate biopsy in MRI-negative patients, and to perform the internal validation. 【Methods】 We retrospectively analyzed the clinical data of 197 MRI-negative patients who underwent prostate biopsy at our hospital, analyzed the independent predictors of positive prostate biopsy with univariate and multivariate logistic regression analysis, constructed the nomogram model and conducted internal validation. 【Results】 Multivariate logistic regression analysis showed age (P=0.003), digital rectal examination (DRE)(P=0.005), total prostate-specific antigen (tPSA) (P=0.001) and prostate volume (PV)(P<0.001) were independent risk factors of MRI-negative but prostate biopsy-positive results. The nomogram model based on all variables was established. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.862, which was greater than that of tPSA (AUC=0.739), PV(AUC=0.711) and DRE(AUC=0.666) (all P<0.05). The average absolute error of the model was 1.1% after 500 internal resampling, indicating that the prediction of positive prostate biopsy was consistent with the actual situation. 【Conclusion】 The age, DRE, tPSA and PV were independent predictors of positive prostate biopsy in MRI-negative patients. The nomogram model has a good prediction performance.

Objective:To explore the independent influencing factors of Gleason group upgrading (GGU)after radical prostatectomy (RP) of localized prostate cancer based on 2014 International Society of Urologic Pathology (ISUP)grouping system, then establish an effective prediction model.Methods:The study included 48567 patients with localized prostate cancer who underwent radical prostatectomy from the surveillance, epidemiology and end results (SEER) database. The age was (61.1±7.0) years, including 39 014 cases (80.3%), 7 063 cases (14.5%), 2 331 cases (4.8%), and 159 cases (0.3%) of White, Black, Asian or Pacific Islander, American Indian/Alaska Native. PSA<4 ng/ml, 4-10 ng/ml, 11-19 ng/ml, ≥20 ng/ml were 6 545 cases (13.5%), 35 007 cases (72.1%), 5 578 cases (11.5%), 1 437 cases (3.0%) respectively. Percent positive cores (PPC)≥33% were 24 743 cases (50.9%). Gleason group of biopsy specimen: G1 18 971cases (39.1%), G2 18 446 cases (38.0%), G3 7 093 cases (14.6%), G4 4 057 cases (8.4%). Simple random sampling was assigned to the cases, divided them into training cohort and internal validation cohort according to the ratio of 7∶3. 67 patients with localized prostate cancer who treated in The Second Affiliated Hospital of Zhengzhou University during January 2017 to December 2021 were set as external validation cohort. All these cases were Asian with Chinese nationality, age(66.4±10.3) years. PSA<4 ng/ml, 4-10 ng/ml, 11-19 ng/ml, ≥20 ng/ml were 13 cases (19.4%), 32 cases (47.8%)16 cases (23.9%), 6 cases (9.0%) respectively. PPC≥33% were 38 cases (56.7%). Gleason group of biopsy specimen: G1 18 cases (26.9%), G2 23cases (34.3%), G3 12 cases (17.9%), G4 14 cases (20.9%). The independent predictors of GGU were analyzed by logistic regression analysis, and the nomogram for predicting GGU were established. Then, the performance of nomograms was internally and externally validated via area under curve (AUC) and the calibration curve.Results:There were 8 716 cases (25.6%), 3 677 cases (25.2%) and 24 cases (35.8%) with GGU in the training group, internal validation group and external validation group, respectively. Logistic regression showed Gleason group of biopsy specimen (G2: OR=0.164, P<0.01; G3: OR=0.073, P<0.01; G4: OR=0.087, P<0.01), PSA (4-10 ng/ml: OR=1.550, P<0.01; 11-19 ng/ml: OR=2.084, P<0.01; ≥20 ng/ml: OR=2.664, P<0.01), age (60-69 years: OR=1.292, P<0.01; ≥70 years: OR=1.550, P<0.01), PPC (≥33%: OR=1.334, P<0.01) and race (Asian or Pacific Islander: OR=1.266, P<0.01) were independent influencing factors for GGU. The predicting model, was established according to Gleason group of biopsy specimen, PSA, age and PPC. The AUC of the model in the training cohort, the internal validation cohort and the external validation cohort were 0.759, 0.757 and 0.747 respectively. The calibration curves of the three cohorts were close to the ideal line and showed good consistency. Conclusions:Gleason group of biopsy specimen, PSA, age, PPC and race are independent influencing factors for GGU after RP of localized prostate cancer. G. P.A.P. model can effectively predict the risk of GGU after RP of localized prostate cancer.

Optimizing pre-hospitalized services is a powerful measure for hospitals to improve patient experience. In June 2022, a certain maternal and child health hospital had carried out a value chain management for pre-hospitalized patient communication based on patient needs. The Kano model and value chain theory were used to analyze the patient demand attributes, clarify the value-added activities of pre-hospitalized patient communication value chain, and implement value-added activities, including carrying out the GLTC doctor-patient communication model, optimizing the information management system of the admission preparation center, establishing a hospital preparation group management platform, and introducing the " Zhejiang Nursing" platform, to achieve the added value of key value chains in patient communication, improve the quality of pre-hospitalized services, and improve patient experience. After one year of practice, the pre-hospitalized patient management indexes, including the unregistration rate after issuing the hospitalization certificate, the cancellation rate after registration, and the average length of stay had decreased from 9%, 3%, and 4.65 days before practice (June 2021 to May 2022) to 6%, 1%, and 4.13 days after practice (June 2022 to May 2023), respectively. As well as the timely completion rate of pre-hospital inspection and the average satisfaction rate of pre-hospitalized patients had increased from 93% and 94% to 98% and 97%, respectively. The practice had achieved good application effects, so as to provide references for improving the level of pre-hospitalized services and improving the patient experiences in medical institutions in our country.