ObjectiveTo dynamically observe and evaluate the damage to the pulmonary air-blood barrier in mice during the inflammatory cancer transformation process of ulcerative colitis （UC） based on the "lung-intestine correlation" theory. MethodsSixty-five C57BL/6 mice were divided into a normal group （n=25） and a model group （n=40） using a random number table. Azoxymethane/dextran sodium sulfate （DSS） method was used to establish a mouse model of UC inflammation cancer transformation in the modeling group. According to the tissue collection time points at 5， 8， 11， 13， and 15 weeks， the normal group mice were randomly divided into the normal 5w， 8w， 11w， 13w， and 15w groups. The model group mice， 10 mice of which died after the first cycle of DSS administration， were randomly divided into model 5w， 8w， 11w， 13w， and 15w groups. During the experiment， the general condition of the mice was observed daily， and their body weight was measured weekly. At the corresponding tissue collection time points， the colon length of each group was measured. Histopathology of mouse lung and colon tissues was examined using HE staining. Immunofluorescence was used to detect changes in the positive expression of tight junction protein （ZO-1）， vascular endothelial cadherin （VE-cadherin）， and cytoskeletal protein （F-actin） in lung and colon tissues. RT-PCR was used to detect the mRNA expression of apoptosis regulatory proteins B-cell lymphoma-2 （Bcl-2）， BCL2-associated X protein （Bax）， and Cysteine aspartic acid protease-3 （Caspase-3） in lung tissues. Western Blot was employed to measure protein levels of ZO-1， VE-cadherin， and F-actin in lung tissues. ResultsCompared to the normal group at the same time point， the mice in the model group at each time point generally had poorer conditions， with weight loss and shortened colon length （P＜0.05 or P＜0.01）. In the model 5w group， there was significant inflammatory cell infiltration in the colon tissue； in the model 8w group， there was mild atypical hyperplasia； in the model 11w group， the crypt structure was disordered， and moderate to severe atypical hyperplasia occurred； in the model 13w and 15w groups， tumors appeared. Pulmonary interstitial lesions， inflammation， vasculitis， and fibrosis were observed at all stages of UC inflammation cancer transformation. The protein levels of ZO-1， VE-cadherin， and F-actin， as well as Bcl-2 mRNA expression in lung tissue decreased during the acute inflammatory recovery period， atypical hyperplasia period， and canceration period， while the expressions of Bax and Caspase-3 mRNA increased； the expressions of ZO-1， VE-cadherin， and F-actin proteins in colon tissue decreased during the acute inflammatory recovery period， atypical hyperplasia period， and canceration period （P＜0.01 or P＜0.05）. Compared to the model 5w group， the ZO-1 and F-actin protein levels and Bcl-2 mRNA expression in lung tissue in the other model groups increased in the atypical hyperplasia period and canceration period， while the expressions of Bax and Caspase-3 mRNA decreased； the expression of ZO-1 protein in colon tissue increased in the canceration period， and the expression of VE-cadherin protein decreased in the atypical hyperplasia period （P＜0.01 or P＜0.05）. ConclusionIn the process of "inflammatory response-atypical hyperplasia-carcinogenesis" in UC inflammatory cancer transformation mice， there were damage to air-blood barrier.

ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Health economics evidence plays an important role in linking clinical value evidence with health resource allocation decisions in the development of clinical practice guidelines. It can not only effectively balance clinical effectiveness and economic feasibility but also avoid forming "idealized" recommendations that are detached from the affordability of the healthcare system or the burden-bearing capacity of patients. To promote guideline developers to use health economics evidence more standardizedly and fully, this paper conducts an in-depth analysis of the current application status, existing challenges, access channels, and application processes of health economics evidence in current guidelines, and on this basis, puts forward considerations and suggestions for strengthening and standardizing the application of health economics evidence in China's clinical practice guidelines.

Background/Aims: Cholangiocarcinoma (CCA) is a primary malignant neoplasm with an extremely poor prognosis. While combined chemoradiotherapy has been demonstrated to delay CCA progression to a certain extent, the absence of specific molecular biomarkers or targets significantly hinders the diagnosis and treatment of CCA. Methods: Through cross-analysis of proteomics and ADMA modificationomics, we identified DDX1 overexpressed in CCA with elevated R602-ADMA modifications. HPLC-MS/MS identified PRMT1 as the methyltransferase and USP10 as the deubiquitinating enzyme for DDX1. Immunofluorescence and nuclear-cytoplasmic partitioning experiments confirmed DDX1’s nuclear localization. GO and KEGG analyses clarify the biological functions of DDX1 in response to hypoxia. RNA-seq transcriptomics analyzed key pathways influenced by DDX1. A hydrodynamic in situ CCA mouse model was established to validate the chemopreventive effects of the PRMT1-specific inhibitor GSK715 on CCA development. Results: DDX1 promotes CCA progression both in vivo and in vitro and can be inhibited by GSK715. Mechanistically, PRMT1 mediates ADMA modification at position R602 of DDX1. This modification promotes DDX1 nuclear localization by recruiting USP10 to deubiquitinate DDX1, while simultaneously inhibiting PRMT1 degradation. DDX1 promotes the transcription of PRMT1 and USP10 by binding to the mRNA 3’UTR region, establishing a positive feedback regulatory pathway. This mechanism promotes the occurrence and development of CCA and can serve as a target for the inhibitor GSK715 to suppress CCA progression. Conclusions Our study identified DDX1-R602-ADMA modification as a novel ADMA modification in CCA. It further confirmed its pivotal role in CCA progression. Targeting the USP10-PRMT1-DDX1 axis may represent a significant therapeutic approach for CCA.

ObjectiveTo develop and preliminarily validate a prediction model for brace treatment failure risk in patients with adolescent idiopathic scoliosis (AIS), based on information obtained before brace treatment and during initial brace fitting. MethodsA total of 191 patients with AIS who initiated thoracolumbosacral orthosis treatment at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from March, 2015 to August, 2024 and had determinable outcomes were retrospectively included. Patients were divided according to a prespecified scheme into a training set (n = 133) and a validation set (n = 58). Brace treatment failure was defined as progression of the major-curve Cobb angle by ≥ 5° from baseline during follow-up or at brace weaning, or a final major-curve Cobb angle > 45°. Logistic regression, random forest, support vector machine with radial basis function kernel, and extreme gradient boosting (XGBoost) models were developed using routinely available clinical and radiographic variables before brace treatment and during initial brace fitting. Stratified five-fold cross-validation was used for hyperparameter tuning in the training set. Model performance was evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AUPRC), Brier score, calibration curves, and decision curve analysis (DCA). SHapley Additive exPlanations (SHAP) was used to interpret the main explanatory model. ResultsIn cross-validation of the training set, both random forest and XGBoost showed good discriminative performance, with cross-validation-AUC values of 0.871 and 0.880, respectively. In the validation set, the AUC values of random forest and XGBoost were 0.888 and 0.899, the AUPRC values were 0.678 and 0.830, and the Brier scores were 0.086 and 0.076, respectively. Random forest was selected as the primary model for interpretation, with a calibration intercept of 0.091 and a calibration slope of 0.995. SHAP analysis indicated that the in-brace correction rate and the major-curve Cobb angle measured in the brace contributed most to the model predictions. ConclusionThe random forest model developed using routinely available pretreatment and initial-fitting variables shows preliminary predictive value for brace treatment failure risk in AIS, and may provide quantitative support for follow-up scheduling, brace-fit reassessment and early adherence-oriented management.

Objective: To analyze the demographic evolution of China over the forthcoming decade (2026-2035) and to systematically evaluate its potential implications for voluntary blood donation practices and the equilibrium of clinical blood supply and demand. Methods: Leveraging comprehensive blood collection and utilization data from 2021 to 2025 at the national, provincial (Shandong), and municipal (Zibo) levels, we identified and examined critical determinants influencing blood management systems. The DeepSeek-V3.2 large language model was deployed to project future population age structures, and to generate quantitative estimates for hospitalization volumes, clinical blood requirements, available blood supply, and donation frequencies for the target years 2030 and 2035, thereby furnishing an evidence base for strategic planning and priority-setting. Results: DeepSeek-derived projections indicate that the proportion of China's population aged 60 years and above will surpass 27% (370 million/1 380 million) by 2030 and exceed 30% (400 million/1 350 million) by 2035, signaling a marked acceleration in population aging. This demographic shift is projected to reduce the proportion of the national population eligible to donate blood from 59.2% (835 million out of 1.41 billion) to 52% (710 million out of 1.36 billion), while the demand for blood is expected to increase by 87.8% relative to 2024, rising from 26.927 million units to 50.56 million units. Sustaining blood supply-demand balance will necessitate progressive annual increases in donation rates. Under prevailing policy frameworks, the required blood donation rate among the eligible population in Shandong Province would need to rise by 122.57% by 2035 [from 20.07‰ (1.1641 million person-times/58 million people) to 44.67‰ (2.189 million person-times/49 million people)] to potentially satisfy projected clinical requirements. Conclusion: By integrating DeepSeek-V3.2, AI predictive models, and blood donation incentive measures, it is possible to monitor population demographics, forecast clinical blood demand, manage blood supplies, and ensure the long-term sustainability of clinical blood availability. It must be acknowledged, however, that the present analysis is constrained by a limited data foundation (comprising only five annual observation points); accordingly, the projections should be interpreted as directional trend indicators or methodological illustrations rather than definitive quantitative forecasts.

ObjectiveJunctophilin-2 (JPH2) is an essential structural protein that maintains junctional membrane complexes (JMCs) in cardiomyocytes by tethering the plasma membrane to the sarcoplasmic reticulum, thereby facilitating excitation-contraction (E-C) coupling. Mutations in JPH2 have been associated with hypertrophic cardiomyopathy (HCM), but the molecular mechanisms governing its membrane-binding properties and the functional relevance of its membrane occupation and recognition nexus (MORN) repeat motifs remain incompletely understood. This study aimed to elucidate the structural basis of JPH2 membrane association and its implications for HCM pathogenesis. MethodsA recombinant N-terminal fragment of mouse JPH2 (residues1-440), encompassing the MORN repeats and an adjacent helical region, was purified under near-physiological buffer conditions.X-ray crystallography was employed to determine the structure of the JPH2 MORN-Helix domain. Sequence conservation analysis across species and junctophilin isoforms was performed to assess the evolutionary conservation of key structural features. Functional membrane-binding assays were conducted using liposome co-sedimentation and cell-based localization studies in COS7 and HeLa cells. In addition, site-directed mutagenesis targeting positively charged residues and known HCM-associated mutations, including R347C, was used to evaluate their effects on membrane interaction and subcellular localization. ResultsThe crystal structure of the mouse JPH2 MORN-Helix domain was resolved at 2.6 Å, revealing a compact, elongated architecture consisting of multiple tandem MORN motifs arranged in a curved configuration, forming a continuous hydrophobic core stabilized by alternating aromatic residues. A C-terminal α-helix further reinforced structural integrity. Conservation analysis identified the inner groove of the MORN array as a highly conserved surface, suggesting its role as a protein-binding interface. A flexible linker segment enriched in positively charged residues, located adjacent to the MORN motifs, was found to mediate direct electrostatic interactions with negatively charged phospholipid membranes. Functional assays demonstrated that mutation of these basic residues impaired membrane association, while the HCM-linked R347C mutation completely abolished membrane localization in cellular assays, despite preserving the overall MORN-Helix fold in structural modeling. ConclusionThis study provides structural insight into the membrane-binding mechanism of the cardiomyocyte-specific protein JPH2, highlighting the dual roles of its MORN-Helix domain in membrane anchoring and protein interactions. The findings clarify the structural basis for membrane targeting via a positively charged linker and demonstrate that disruption of this interaction—such as that caused by the R347C mutation—likely contributes to HCM pathogenesis. These results not only enhance current understanding of JPH2 function in cardiac E-C coupling but also offer a structural framework for future investigations into the assembly and regulation of JMCs in both physiological and disease contexts.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To investigate the factors influencing global longitudinal strain(GLS)measured by cardiac magnetic resonance(CMR)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods Clinical data of 315 hospitalized patients diagnosed with acute STEMI who underwent percutaneous coronary intervention(PCI)at the First Medical Center of Chinese PLA General Hospital from June 2016 to September 2021 were retrospectively collected.After analyzing CMR images of all patients,GLS and other strain parameters were obtained,and then the patients were divided into two groups according to the median GLS.In order to balance gender and age differences,1:1 propensity score matching was performed,and 206 patients were eventually included:GLS>-11.3%group(indicating severe GLS impairment,n=103)and GLS≤-11.3%group(n=103).Baseline characteristics,laboratory indicators,coronary angiographic parameters,electrocardiogram(ECG)features,and CMR parameters were compared between the two groups.Variables showing significant differences were analyzed for their correlation with GLS.Multivariate logistic regression and multiple stepwise linear regression analyses were performed to identify factors associated with GLS impairment.Results Compared with GLS≤-11.3%group,GLS>-11.3%group had significantly higher peak levels of creatine kinase-MB(CK-MB)and troponin T(TnT)(P<0.001).A higher proportion of patients in GLS>-11.3%group had the left anterior descending artery(LAD)as the culprit vessel,while a lower proportion had the right coronary artery(RCA)as the culprit vessel(P<0.001).Additionally,GLS>-11.3%group had longer QRS duration(P<0.001)and a higher incidence of pathological Q waves(P=0.001).Regarding CMR parameters,GLS>-11.3%group exhibited larger global circumferential strain(GCS),infarct size(IS),and left ventricular end-systolic volume(LVESV),as well as lower global radial strain(GRS)and left ventricular ejection fraction(LVEF)(P<0.001).Multivariate logistic regression indicated that peak TnT(OR=1.092,P=0.001),LAD culprit vessel(OR=3.744,P<0.001),and QRS duration(OR=1.026,P<0.001)were significantly associated with severely impaired GLS.Multiple stepwise linear regression analysis showed that the logarithmic value of peak TnT,LAD as the culprit vessel,and the square root of QRS duration were linearly correlated with GLS values(adjusted R2=0.301,P<0.001),and these independent variables explained 30.1%of the variation in GLS.Conclusion Elevated peak TnT,prolonged QRS duration,and LAD as the culprit vessel are significantly associated with severe GLS impairment in STEMI patients,indicating more severe myocardial infarction and worse left ventricular function.