OBJECTIVE To systematically analyze the trends in the volume and value of out-licensing deals by Chinese biopharmaceutical companies over the past two decades， and to quantitatively identify factors associated with deal value， thereby providing an evidence base for policymakers and corporate managers. METHODS Based on the PharnexCloud database， information on out-licensing deals disclosed by Chinese biopharmaceutical companies between January 1， 2005 and December 31， 2025 was collected， and executed deals with disclosed specific financial terms were included for analysis. Descriptive statistical analyses of deal value， product characteristics and deal characteristics were performed using Stata SE 18.0； with the natural logarithm of deal value as the dependent variable， stepwise multiple regression models were constructed to examine the associations of product and deal characteristics with deal value. RESULTS A total of 210 out-licensing deals were included， with a cumulative deal value of approximately 214.151 billion dollars and a mean deal value of 1.020 billion dollars . The trading market expanded rapidly from 2020 onward， with the annual deal value reaching a record 95.687 billion dollars in 2025. Multiple regression analysis showed that the deal value of products at the drug discovery stage was significantly lower than that at the preclinical stage [regression coefficient （ β ） ＝－1.995， 95% confidence interval （CI）： －3.256 to －0.734， P ＜0.05 ] ； the deal value of oncology products was significantly higher than that of other therapeutic areas （ β ＝0.828， 95%CI： 0.224 to 1.431， P ＜0.05）； global licensing （ β ＝1.690， 95%CI： 1.107 to 2.273， P ＜0.05） and co-development arrangements （ β ＝0.849， 95%CI： 0.084 to 1.615， P ＜0.05） were significantly associated with higher deal value. CONCLUSIONS Out-licensing deals by Chinese biopharmaceutical companies have achieved significant growth in both volume and value over the past two decades. Oncology products， global licensing， and co-development arrangements are significantly and positively associated with higher deal value.

Occupational disease diagnostician (ODD) is the core technology professional who is responsible for occupational disease diagnosis and identification and the main inspection work for occupational medical examination. The implementation of regular assessment management for ODDs is a key component of standardized workforce management, which facilitates dynamic evaluation of professional competence, regulation of medical practice, and assurance of medical safety. Since January 2025, Guangdong Province has implemented regular assessment management for ODDs within its administrative region. The assessment adopts an integrated model consisting of three components including professional competency evaluation, performance appraisal, and professional ethics evaluation, with each assessment cycle lasting three years. ODDs who passed all three components are classified as qualified ODD, whereas those who failed to pass any one of the three components result in an unqualified assessment outcome. In the implementation of ODD regular assessment management, Guangdong Province has emphasized integrating assessment with quality evaluation, strengthening full-cycle supervision of ODDs′ professional conduct, optimizing assessment strategies for special groups of ODDs, and reinforcing the primary management responsibility of medical institutions. Meanwhile, ODDs′ professional competence, service quality, and professional integrity have been continuously promoted by adopting human-computer interactive assessments, information-based assessment management, and "elimination" mechanism.

OBJECTIVE Identify the incentive and constraint factors of artificial intelligence （AI） application in the pharmaceutical field， and promote the application of AI in the field of pharmacy. METHODS Based on the technology acceptance model （TAM）， technology-organization-environment （TOE） framework， and diffusion of innovation theory （DOI）， a TAM-TOE-DOI integrated framework was constructed through a four-stage research process of “theoretical review → dimension mapping → mechanism integration → proposition development”. Combining the analytical pathways of the above three theories in AI application in pharmacy with the integration mechanisms and core propositions of the TAM-TOE-DOI， literature review and deductive reasoning were employed to systematically identify the incentive and constraint factors of AI application in pharmacy from three levels：micro （TAM）， meso （TOE）， and macro （DOI）， and to propose optimization strategies. RESULTS & CONCLUSIONS At the micro level， the efficiency transformation and quality improvement brought by AI technology were the main incentive factors for perceived usefulness， while technological complexity and algorithmic opacity were the main constraint factors for perceived ease of use. At the meso level， the completeness of technological infrastructure， the strength of top management support and innovation climate， as well as external institutional pressure and competitive driving forces were the core incentive factors， whereas scarcity of organizational resources and talent shortage were the main constraint factors. At the macro level， relative advantage and observability were typical incentive factors， while technological complexity was a typical constraint factor. China’s health administration， medical insurance authorities， and other relevant departments should coordinate efforts at the macro， meso， and micro levels to advance AI application in pharmacy： optimizing human-computer interaction and implementing tiered training programs at the micro level； reinforcing organizational support systems and capacity building at the meso level； dismantling data barriers and building social trust at the macro level. Differentiated implementation pathways should be developed for medical institutions at different tiers.

Oral cancer is a common inflammation-associated malignant tumor of the head and neck.In recent years,the role of the tumor microenvironment in the progression of oral cancer has received increasing attention.In the microenvironment of solid tumors,including or-al cancer,tumor-associated macrophages(TAMs)are among the most common type of immune cell and are closely associated with the poor prognosis of more than 80%of human malignant tumors.An increasing body of evidence indicates that TAMs play important roles in the oc-currence and progression of oral cancer.On the basis of the most recent research progress,both domestic and international,we systematic-ally reviewed the phenotypic characteristics,clinicopathological correlations,and molecular regulatory mechanisms of TAMs in the microen-vironment of oral squamous cell carcinoma(OSCC).In particular,we focus on the key signaling pathways promoting tumorigenesis and de-velopment and immune escape mechanisms,with the aim of constructing a systematic theoretical framework for developing therapeutic strategies targeting TAMs and providing a scientific basis for clinical translational research.

Objective:To evaluate effectiveness of finerenone in patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) in the real world, and to analyze the associated factors of renal function progression during treatment.Methods:It was a single-center retrospective study. The patients diagnosed with T2DM and CKD who received finerenone treatment for 3 months in Beijing Anzhen Hospital, Capital Medical University between April 1 and October 1, 2023 were included. The clinical data before and after finerenone treatment were collected. Based on urinary albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR), the patients were divided into different groups, and the differences of clinical data before and after treatment were compared respectively. Logistic regression models was used to analyze the correlated factors of renal function changes during the treatment.Results:A total of 151 patients were included with age of 63 (54, 70) years, and 103 males accounted for 68.2%. UACR level after 3 months of finerenone treatment was significantly lower than those before treatment ( Z=-5.051, P<0.001), whereas there was no statistically significant change in eGFR ( P>0.05). Both patients with baseline eGFR ≥60 ml·min -1·(1.73 m 2) -1 ( Z=-4.543, P<0.001) and those with baseline eGFR <60 ml·min -1·(1.73 m 2) -1 ( Z=-2.610, P=0.009) showed significant reductions in UACR after treatment. Both patients with baseline UACR ≥300 mg/g ( Z=-4.681, P<0.001) and those with baseline UACR <300 mg/g ( Z=-1.979, P=0.048) exhibited significantly lower UACR levels after treatment. The percentage reduction in UACR was greater in patients with baseline UACR ≥300 mg/g than in those with baseline UACR <300 mg/g ( Z=-2.102, P=0.036).After 3 months of finerenone therapy, serum potassium level was slightly higher than baseline, but the difference was not statistically significant ( P>0.05).The incidence of hyperkalemia after treatment was higher than baseline in patients with baseline eGFR <60 ml·min -1·(1.73 m 2) -1 ( χ 2=2.558 , P=0.039). During the treatment, 74 patients (49.0%) experienced renal function progression. Multivariate logistic regression analysis identified increased baseline serum albumin <45 g/L was an independent correlated factor of renal function progression during finerenone therapy ( OR=1.934, 95% CI 1.157-3.231, P=0.012). Conclusions:UACR in patients with T2DM and CKD can be reduced significantly after short-term treatment of finerenone. Increased baseline serum albumin level <45 g/L is independently associated with renal function progression during finerenone therapy.

Objective:To develop and validate a deep learning-based multimodal model integrating clinical and radiomic features for predicting acute kidney injury（AKI）risk after partial nephrectomy.Methods:A retrospective analysis was conducted on 416 patients who underwent partial nephrectomy at Zhongshan Hospital，Fudan University from January 2023 to January 2025. The cohort included 100 AKI patients［defined by a ≥ 25% reduction in postoperative evaluated glomerular filtration rate（eGFR）within 48 hours sustained for >24 hours］and 316 non-AKI patients（1∶3 ratio，randomly matched with 16 additional cases for redundancy）. Clinical and radiomic features were extracted from preoperative contrast-enhanced CT scans using PyRadiomics. Demographics included 259 males and 158 females，with a median age of 57（49，65）years，body mass index of（24.1 ± 3.3）kg/m2，preoperative eGFR of（88.5 ± 18.3）ml/（min·1.73 m2），postoperative eGFR（48-hour）of（76.0 ± 21.9）ml/（min·1.73 m2），Zhongshan Score（ZSscore）of 7.34 ± 2.01，and R.E.N.A.L. score of 7.50 ± 1.71. All tumors were T 1a stage. Patients were divided into training（n = 312）and test（n = 104）sets（3∶1 ratio）. A clinical model was constructed via multivariate logistic regression，while radiomic and combined（clinical + radiomic）models utilized an artificial neural network（ANN）with 1 input layer，5 hidden layers，1 output layer，and 10 5 training epochs. Model performance was evaluated by using receiver operating characteristic（ROC）curves and area under the curve（AUC），and was compared to the Martini model. Feature contributions were interpreted via SHapley Additive exPlanations（SHAP）. Results:In the test set，the results of multivariate logistic regression showed that patient’s weight，preoperative eGFR，R.E.N.A.L. score，surgical approach，and operation time were risk factors for AKI（ P < 0.05）. The AUC of the clinical feature prediction model constructed based on the above factors was 0.852（95% CI 0.775?0.929）. In the test set，the AUC of the Martini model was 0.725（95% CI 0.565?0.791）. The radiomic model，trained on 1 315 imaging features，achieved an AUC of 0.898（95% CI 0.804?0.993）with 94.2%（98/104）accuracy. The combined clinical and radiomic model，integrating 1 315 radiomic features and clinical features，demonstrated superior performance with an AUC of 0.946（95% CI 0.887?1.000）and 96.2%（100/104）accuracy，outperforming both the clinical model（ P = 0.03）and the Martini model（ P < 0.01）. SHAP analysis identified the top five predictors in the combined model：ZSscore（SHAP value：0.78），long-run low gray-level emphasis（SHAP value：0.61），run-length non-uniformity（SHAP value：0.58），size-zone non-uniformity（SHAP value：0.46），and gray-level co-occurrence matrix joint energy（SHAP value：0.36）. Conclusions:The deep learning-based multimodal model integrating clinical and radiomic features accurately predicts AKI risk after partial nephrectomy，offering a novel strategy for preoperative risk stratification and personalized intervention.

Objective:To investigate the correlation between serum growth differentiation factor 15 (GDF15) and the clinicopathological characteristics of patients with IgA nephropathy (IgAN), and further explore the relationship of GDF15 with the cardiac and renal prognosis of IgAN patients.Methods:It was a single-center retrospective cohort study. From January 2018 to December 2022, the relevant data were collected from patients who were diagnosed with primary IgAN at the Department of Nephrology, Beijing Anzhen Hospital Affiliated to Capital Medical University, and regularly followed up for at least 1 year. Serum samples were collected at admission and the baseline level of serum GDF15 was measured. Based on the median GDF15 level, IgAN patients were categorized into high-level GDF15 group and low-level GDF15 group, and their clinicopathological characteristics were compared. A multiple linear regression model was then constructed to identify independent factors associated with serum GDF15 level based on these comparisons. Subsequently, Kaplan-Meier survival analysis was performed to investigate the association between serum GDF15 level and the cardiorenal prognosis of IgAN patients.Results:A total of 104 IgAN patients were included in this study. The serum GDF15 level in these IgAN patients was 825.60 (556.84, 1 428.15) ng/L. Serum GDF15 level was positively correlated with 24 h urinary protein ( r=0.405, P<0.001), negatively correlated with estimated glomerular filtration rate (eGFR)( r=-0.606, P<0.001). The serum levels of GDF15 in patients with tubular atrophy or interstitial fibrosis (overall comparison among T0, T1, and T2, H=21.866, P<0.001), crescentic lesions (overall comparison among C0, C1, and C2, H=13.787, P=0.001), or intrarenal arteriolar lesions (overall comparison among none, mild, and moderate-to-severe, H=9.856, P=0.007) were significantly different. Compared with IgAN patients without tubular atrophy or interstitial fibrosis, those with Oxford classification T1 ( Z=-17.326, P=0.042) or T2 ( Z=-42.933, P<0.001) had higher serum GDF15 levels. Compared with IgAN patients without crescentic lesions, those with Oxford classification C2 had higher serum GDF15 levels ( Z=-45.929, P=0.001). Compared with IgAN patients without intrarenal arteriolar lesions, those with moderate-to-severe arteriolar sclerosis had higher serum GDF15 levels ( Z=-26.686, P=0.005). The median GDF15 was used as the cut-off value to divide IgAN patients into a high-level GDF15 group (≥825.60 ng/L, n=52) and a low-level GDF15 group (<825.60 ng/L, n=52). Compared to low-level GDF15 group, IgAN patients in high-level GDF15 group presented with a higher proportion of diabetes mellitus ( χ 2=9.420, P=0.002) and cardiovascular disease ( χ 2=7.792, P=0.005), a higher level of systolic blood pressure ( Z=-2.266, P=0.023), body mass index ( Z=-2.183, P=0.031), 24 h urinary protein ( Z=-3.485, P<0.001), blood total cholesterol ( Z=-2.002, P=0.045) and left ventricular mass index ( Z=-2.649, P=0.008), and a lower level of blood albumin ( Z=-3.053, P=0.002) and eGFR ( Z=6.480, P<0.001). Multiple linear regression analysis showed that serum GDF15 level was independently associated with systolic blood pressure (regression coefficient B=29.453, 95% CI 14.139–44.767, P<0.001), blood albumin ( B=-81.412, 95% CI -113.084–-49.740, P<0.001) and eGFR ( B=-9.797, 95% CI -17.554–-2.040, P=0.014). Moreover, IgAN patients in high-level GDF15 group exhibited significantly poorer cardiac and renal prognosis compared to low-level GDF15 group ( χ 2=9.955, P=0.002). Conclusion:High serum GDF15 level correlates with disease severity in IgAN, and high serum GDF15 level may suggest a poorer cardiorenal prognosis in IgAN patients.

Rehabilitation is an effective measure to improve the quality of life for cancer patients,and strong rehabilitation motivation is an important influencing factor for patients' compliance with rehabilitation.This paper mainly reviews the concepts,assessment tools,influencing factors,and intervention strategies of rehabilitation motivation in cancer patients,with the aim of providing references for medical staff to improve the level of rehabilitation compliance in cancer patients and develop targeted rehabilitation management strategies.

Objective:This study aimed to identify potential prognostic and biotherapeutic targets for oral squamous cell carcinoma(OSCC)by investigating the regulatory effects of M1/M2 macrophages on OSCC progression and their underlying mechanisms.Methods:The ef-fects of M1/M2 macrophages on the proliferation,migration,invasion,and apoptosis of SCC-15 cells were examined.Immunohistochemical staining was used to detect the expression of CD68 and M2 macrophage marker proteins in human OSCC tissue microarrays,and their cor-relations with clinicopathological features were analyzed.Results:M1 macrophages promoted apoptosis of SCC-15 cells while inhibiting their proliferation,migration,and invasion.In contrast,M2 macrophages exhibited the opposite effects.The infiltration density of tumor-associ-ated macrophages(TAMs)in OSCC tissues was significantly positively correlated(P<0.05)with lymph node metastasis.Conclusions:M1 mac-rophages suppress OSCC progression,whereas M2 macrophages promote it.

Objective To systematically evaluate the rehabilitation effect of immersive virtual reality technology for patients with peripheral vestibular dysfunction,and to provide theoretical basis and practical guidance for the design of efficient rehabilitation training programs.Methods PubMed,Embase,Cochrane Library,Web of Science,CINAHL,CNKI,Wanfang Database,VIP Database,and China Biomedical Literature Database were searched for randomized controlled trials on the intervention effect of immersive virtual reality technology in patients with peripheral vestibular dysfunction from inception to February 2025.RevMan5.4 software was used to perform meta-analysis of the literature that met the quality standards.Results A total of 10 papers with 491 patients with peripheral vestibular dysfunction were included.Meta-analysis showed that immersive virtual reality technology improved vertigo symptoms in patients with peripheral vestibular dysfunction compared with conventional vestibular rehabilitation care[SMD=-1.41,95％CI(-1.58,-0.70),P＜0.001],and subgroup analysis showed that the frequency of intervention was＜5 times/week[SMD=-1.31,95％CI=(-1.96,-0.66),P＜0.001],single intervention duration＜30 min[SMD=-1.45,95％CI=(-2.21,-0.70),P＜0.001],and intervention period≤7 weeks[SMD=-1.49,95％CI(-2.04,-0.94),P＜0.001]were more significant.Immersive virtual reality technology reduced the risk of falls[MD=4.66,95％CI(3.84,5.48),P＜0.001],and improved anxiety and depression[SMD=2.65,95％CI(1.98,3.33),P＜0.001].Conclusion Immer-sive virtual reality technology improves vertigo symptoms,reduces the risk of falls,and improves anxiety and depres-sion symptoms in patients with peripheral vestibular dysfunction,in which the intervention period of ≤7 weeks,＜5 training sessions per week,and each training session of＜30 min are better for improving vertigo symptoms in patients with peripheral vestibular dysfunction.