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 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.

The pre-hospitalization service is an important initiative for medical institutions to implement the national reform of the medical security system. In 2018, Zhejiang province proposed the " most run once reform", requiring the establishment of an admission preparation center to carry out pre-hospitalization services. In June 2021, a certain maternal and child health hospital conducted a process reengineering for the pre admission process of the admission preparation center by applying the combined process analysis and failure mode and effects analysis, high-risk points of the hospitalization process were screened, the job value and job functions of each sector were sorted out, and the sector for improvement sector was evaluated, to launch an independent information system, establish a one click automatic import of pre hospital medical orders function, and remove on-site billing physicians from various specialties for improvement measures. The steps of the process had been optimized, inlcuding issuing pre hospital medical orders, waiting for pre-hospitalization, pre-hospitalization, and so on. The completeness rate of pre hospital medical orders, average waiting days before hospitalization, and patient satisfaction scores of pre hospitalization centers had changed from 91%, 2.99 days, and 93.46 points before process reengineering to 92%, 2.44 days, and 95.80 points after reengineering, respectively. This practice had achieved dual improvements in pre admission service quality and efficiency, so as to provide a reference for China′s medical institutions to carry out safe and efficient pre admission services.

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.

Objective:To determine the expression of transmembrane protein 45A (TMEM45A) in keloid tissues and fibroblasts, and to evaluate its effect on extracellular matrix (ECM) synthesis by keloid-derived fibroblasts (KFs) .Methods:Samples of surgically excised keloid and normal foreskin tissues were collected from the Department of Dermatology and Department of Urology of Yanbian University Hospital from January 2019 to December 2020, and TMEM45A protein expression was determined in keloid tissues and KFs by Western blot analysis. KFs were divided into TMEM45A-specific small interfering RNA (siRNA) group and control siRNA group to be transfected with the TMEM45A-specific siRNA and control siRNA respectively. Then, Western blot analysis was performed to evaluate the effects of down-regulation of the TMEM45A gene on the expression of myofibroblast marker protein (α-smooth muscle actin) and ECM-related proteins.Results:Compared with normal skin tissues (1.00 ± 0.11) and fibroblasts (1.00 ± 0.20), TMEM45A expression levels significantly decreased in keloid tissues (0.26 ± 0.05) and KFs (0.41 ± 0.09), respectively ( t = 10.76, 4.75, P < 0.001, = 0.009, respectively). The expression levels of α-smooth muscle actin, ECM-related type Ⅰ collagen, type Ⅲ collagen, and fibronectin were significantly higher in the TMEM45A-specific siRNA group than in the control siRNA group ( t = -5.98, -4.57, -4.90, -7.19, P = 0.004, 0.010, 0.008, 0.002, respectively) . Conclusion:Lowly expressed TMEM45A in keloids may play an important role in the pathogenesis of keloids by promoting ECM synthesis.

ObjectiveTo compare the differences in clinical characteristics between kidney deficiency and stasis obstruction syndrome and damp-heat stasis obstruction syndrome in patients with ankylosing spondylitis （AS）， thereby providing reference for clinical differentiation and treatment. MethodsThe clinical data of 2339 patients with AS were collected， including 1075 cases of kidney deficiency and stasis obstruction syndrome and 1264 cases of damp-heat stasis obstruction syndrome. The basic information including age， gender， course of disease， history of ophthalmia， family history and human leukocyte antigen B27 （HLA-B27） positive history， Bath ankylosing spondylitis disease activity index （BASDAI） score， Bath ankylosing spondylitis functional index （BASFI） score， Bath ankylosing spondylitis measurement index （BASMI） score， Depression Anxiety Stress Scale 21 （DASS-21） score， single symptom score in terms of spinal pain， peripheral joint pain， tendon tenderness， morning stiffness degree and morning stiffness time， patient-reported outcomes including patient global assessment （PGA） score， chronic disease therapy function-fatigue scale （FACIT-F） score and night pain visual analog scale （VAS） score， laboratory indicators including serum C-reactive protein （CRP） and erythrocyte sedimentation rate （ESR）， and CT grading of sacroiliitis were measured and compared between groups. ResultsPatients with kidney deficiency and stasis obstruction syndrome were older and had a longer course of disease （P＜0.01）. The BASDAI， BASFI and BASMI scores of the patients with kidney deficiency and stasis obstruction syndrome were 3.84±1.79， 2.78±2.00 and 3.42±2.36， respectively， while those in patients with damp-heat stasis obstruction syndrome were 4.30±1.99， 3.43±2.12， and 2.92±1.76. The BASDAI score， BASFI score， PGA score， FACIT-F score， spinal pain score， peripheral arthralgia score， tendon tenderness score， morning stiffness degree score， depression score， anxiety score， and stress score in patients with damp-heat stasis obstruction syndrome were all higher than those with kidney deficiency and stasis obstruction syndrome， with longer duration of morning stiffness and higher CRP （P＜0.05 or P＜0.01）. BASMI score and night pain VAS score were more higher in patients with kidney deficiency and stasis obstruction syndrome （P＜0.01）. There was no significant difference in the ESR level and CT grading of the sacroiliac joint between the two groups （P＞0.05）. ConclusionAS patients with kidney deficiency and stasis obstruction syndrome have poorer spinal mobility， while those with damp-heat stasis obstruction syndrome have higher disease activity， poorer physical function， and are more prone to adverse psychological reactions.

ObjectiveTo construct a quantitative differentiation model of traditional Chinese medicine （TCM） syndromes by taking primary osteoporosis （POP） with kidney yang deficiency syndrome as an example， and to provide methodological reference for the standardization of syndrome differentiation. MethodsHigh-frequency clinical features of POP were screened by descriptive statistical analysis， and strong association features of POP were obtained by association rule algorithm. On this basis， a latent structure （latent tree） model was established through latent structure analysis， and the implicit and explicit variables （features） related to POP with kidney yang deficiency syndrome were comprehensively clustered， and the clustering results were interpreted by the indexes of mutual information and cumulative information coverage， to explore the primary and secondary symptoms， and to deduce the categories of POP with kidney yang deficiency syndrome based on the probability of the features appearing in the various latent categories. Based on the categories， the clinical feature scores and identification thresholds were calculated， and the syndrome differentiation model of POP with kidney yang deficiency was initially constructed by combining the comprehensive judgment rules. Finally， the results of TCM professionals' judgment were used as the gold standard to further evaluate the effectiveness of the model in assisting the syndrome differentiation. ResultsThe 32 features strongly associated with POP were obtained， and the Bayes information critedon score of the further constructed latent tree model was -15291.93. Based on the mutual information and the cumulative information coverage， the main symptoms of POP with kidney yang deficiency syndrome were bone weakness， fatigue， pale tongue， clear urine， frequent nocturnal urination， cold limbs， thin pulse， white coating， and secondary symptoms were weakness， loss of libido， loose stool， frequent urination， lumbar and knee weakness， and fear of cold. From the probability of the occurrence of each clinical feature in different latent categories of POP with kidney yang deficiency syndrome， the state was introduced as S0 category （none/mild kidney yang syndrome）/ S1 category （moderate kidney yang syndrome）/ S2 category （severe kidney yang syndrome）. Optimizing the preliminary rules of state identification and refining the state of S1 category， the results showed that among 970 patients with POP， there were 520 patients having no/mild kidney yang deficiency syndrome， 224 patients with moderate to mild kidney yang deficiency syndrome， 81 patients with moderate to severe kidney yang deficiency syndrome， and 145 patients with severe kidney yang deficiency syndrome. During the evaluation and validation process， the correct rate of the model assessment index was 0.8835， while the sensitivity was 0.7181， and the specificity was 0.9437. ConclusionCombined with the latent structure analysis of the association rule， the syndrome differentiation model for POP with kidney yang deficiency could be constructed， and the model shows a good quantitative identification effect， which can provide methodological supports for clinicians to improve the efficiency and accuracy of TCM diagnosis.