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 explore the independent risk factors of allogeneic blood transfusion during perioperative period of cytoreductive surgery in patients with ovarian cancer, and to construct a predictive model to facilitate clinical risk assessment and optimize perioperative blood management. Methods: Clinical data of 156 patients who underwent cytoreductive surgery for ovarian cancer in our hospital from January 2020 to December 2025 were retrospectively collected. The patients were divided into transfusion group (n=51) and non-transfusion group (n=105) according to whether they received allogeneic blood transfusion during perioperative period. The 1∶1 propensity score matching (PSM) was used to correct the confounding factors. Independent sample t test or Mann-Whitney U test was used for measurement data, and chisquare test was used for enumeration data. Variables with P<0.05 in univariate analysis were included in binary logistic regression for multivariate analysis to determine independent risk factors. A nomogram model for perioperative allogeneic blood transfusion risk prediction was constructed based on independent risk factors. Bootstrap method (100 samples) was used for internal calibration verification. ROC curve was used to evaluate the discrimination efficiency, and decision curve analysis (DCA) was used to evaluate the clinical net benefit of the model. Results: After propensity matching, the baseline data of the two groups were balanced and comparable. Multivariate logistic regression analysis showed that preoperative prothrombin time (PT) (OR=2.666, 95%CI 1.249~5.693, P=0.011), preoperative hemoglobin (Hb) (OR=0.953, 95%CI 0.923~0.984, P=0.003), intraoperative blood loss (OR=1.004, 95%CI 1.001-1.006, P=0.004), preoperative anemia grade (OR=3.052, 95%CI 1.007-9.252, P=0.049) were independent influencing factors of perioperative allogeneic blood transfusion. The nomogram model based on the above four factors was significant (LR χ =58.617, P<0.001), and the internal calibration curve showed that the predicted probability of the model was in good agreement with the actual probability (mean absolute error=0.042). The area under the ROC curve (AUC) was 0.890, indicating good discrimination efficiency. DCA showed that the clinical net benefit of the model was better than that of the unified transfusion/non-transfusion strategy in the 0-0.45 risk threshold range. Conclusion: Intraoperative blood loss, preoperative PT, preoperative Hb and preoperative anemia grade are independent risk factors for perioperative allogeneic blood transfusion in patients undergoing cytoreductive surgery for ovarian cancer. The nomogram model based on the above factors has good predictive efficacy and clinical hierarchical decision-making value, which can provide reference for clinical implementation of individualized blood management for high-risk patients and reduction of unnecessary blood transfusion rate.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

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 analyze the relationship between different degrees of cerebral venous sinus stenosis and the trans-stenotic pressure gradient using a 3D-printed hemodynamic simulation system for cerebral venous sinuses.Methods Based on the double elastic cavity model,a complete morphological model of the superior sagittal sinus,transverse sinus,and sigmoid sinuses was constructed using 3D printing technology.An in vitro hemodynamic simulation system incorporating pulsatile blood flow was established to simulate the hemodynamic environment of cerebral venous sinus stenosis.Using this system,both unilateral dominant drainage and bilateral balanced drainage were simulated.The degree of stenosis and the pressure upstream and downstream of the stenosis were measured.The pressure difference and pressure ratio were calculated to analyze the correlation between stenosis degree and the trans-stenotic pressure gradient.Results In the unilateral dominant drainage model,as the stenosis severity increased,the upstream pressure increased,whereas the downstream pressure remained relatively stable,leading to an increased pressure gradient between the two ends.The regression equation for stenosis degree(X)and pressure gradient(pressure difference ΔP)was:YΔP=1.962X-1.417(R=0.867,R2=0.753,P<0.001).In the bilateral balanced drainage model of cerebral venous sinuses,when the stenosis degree on one side of the model increased,the pressure gradient between the two ends changed slightly and eventually reached a stable state.The regression equation between X and ΔP was:YΔP=0.62X+1.047(R=0.98,R2=0.96,P<0.001).Conclusions Stenosis in cerebral venous sinuses with unilateral dominant drainage has a more significant impact on the pressure gradient,while unilateral stenosis in bilateral cerebral venous sinuses with balanced drainage has a smaller impact on the pressure gradient.This result suggests that for bilateral venous sinus stenosis,stent implantation can be prioritized in one side of the cerebral venous sinuses.

Objective To observe the value of MRI radiomics model for predicting postoperative prognosis of moderate carpal tunnel syndrome(CTS).Methods A total of 126 patients with moderate CTS who underwent endoscopic release and fat-suppressed proton density weighted imaging(PDWI)before operation were retrospectively enrolled.The patients were divided into good prognosis group(n=80)and poor prognosis group(n=46)based on postoperative functional evaluation,also randomly divided into training set and validation set at a ratio of 7∶3.Volume of interest(VOI)of the median nerve was obtained through delineating ROI of the affected wrist on fat suppressed PDWI.Radiomics features were extracted,and those associated with postoperative prognosis of CTS were screened in training set.Clinical prediction model,radiomics model and combined model of these two were established,and the predictive efficacy of the models were evaluated and compared according to the area under the curve(AUC)of receiver operating characteristic(ROC)curve.Results Patients in poor prognosis group were older than in good prognosis group(P＜0.05).A clinical model was constructed based on age.The radiomics model was constructed based on 6 radiomics features associated with postoperative prognosis of CTS,with predictive efficacy(AUC=0.872)higher than that of clinical model(AUC=0.604,P＜0.05)but not significantly different with that of the combined model(AUC=0.905,P＞0.05).Conclusion MRI radiomics model could be used to effectively predict postoperative prognosis of moderate CTS.

Objective To explore the level of energy balance related protein antibody,adropin,and its correlation with collateral circulation status in elderly patients with AMI.Methods A total of 193 elderly AMI patients admitted to our department from February 2022 to February 2024 were enrolled,and based on their collateral circulation status,they were divided into a good circulation group(121 cases)and a poor circulation group(72 cases).The level of adropin was determined.Multivariate logistic regression analysis was employed to determine the influencing factors of poor collateral circulation in elderly AMI patients.Results The poor circulation group had significantly larger proportion of hypertension,higher fasting blood glucose(FBG),and larger red blood cell distribution width(RDW),but lower adropin level and mean platelet volume(MPV)when com-pared with the good circulation group(P＜0.05,P＜0.01).Multivariate logistic regression analy-sis showed that adropin,FBG,RDW,MPV,and hypertension were all influencing factors for poor collateral circulation in elderly AMI patients(P＜0.05,P＜0.01).The AUC value of adropin,FBG,RDW,MPV,and hypertension was 0.810,0.762,0.761,0.715 and 0.563,respectively in pre-dicting poor collateral circulation.Among them,adropin level had the highest predictive value(P＜0.01).Conclusion The decrease in adropin level in elderly AMI patients is closely associated with poor collateral circulation,and it is a predictive factor for collateral circulation.

Objective:To investigate the risk factors for dural tears in patients with thoracolumbar burst fracture (TLBF) and their predictive efficacy.Methods:A retrospective cohort study was conducted to analyze the clinical data of 135 TLBF patients admitted to Tianjin Fifth Central Hospital from March 2020 to February 2025, including 83 males and 52 females, aged 16-65 years [41(31, 50)years]. Among them, 31 patients had thoracic fracture and 104 lumbar fracture. The patients were divided into dural tear group ( n=82) and dural intact group ( n=53) based on the presence of dural tear. The following data of the two groups were collected including gender, age, underlying diseases, body mass index (BMI), bone density T-score, cause of injury, AO fracture classification, distribution of injured vertebrae, vertical laminar fracture (VLF) classification, radiological parameters (pedicle spacing, vertebral canal area, sagittal diameter of the vertebral canal, vertebral compression rate), and American Spinal Injury Association (ASIA) impairment scale. Univariate analysis and multivariate Logistic regression analysis were conducted to assess and identify the independent risk factors for dural tears in TLBF patients. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the predictive efficacy of each independent risk factor. Results:Univariate analysis showed statistically significant differences in VLF classification, pedicle spacing, vertebral canal area, sagittal diameter of the vertebral canal, vertebral compression rate, and ASIA impairment scale between the two groups ( P<0.05). Multivariate Logistic regression analysis revealed that VLF classification ( OR=4.16, 95% CI 1.03, 11.46, P<0.05), pedicle spacing ( OR=1.08, 95% CI 0.81, 1.16, P<0.05), and ASIA impairment scale ( OR=3.06, 95% CI 2.00, 8.48, P<0.01) were significantly associated with dural tears in TLBF patients. ROC curve analysis showed that VLF classification (AUC=0.86, 95% CI 0.62, 0.95), pedicle spacing (AUC=0.86, 95% CI 0.77, 1.00), and ASIA impairment scale (AUC=0.76, 95% CI 0.74, 0.97) had relatively high predictive efficacy for dural tear. The combination of VLF classification and pedicle spacing had the highest predictive efficacy (AUC=0.89, 95% CI 0.78, 1.01). Conclusions:VLF classification, pedicle spacing, and ASIA impairment scale are independent risk factors for dural tears in TLBF patients. VLF classification and pedicle spacing have relatively high independent predictive efficacy and their combination can further improve the predictive efficacy.

Objective: To investigate if high glucose (HG) exacerbates Porphyromonas gingivalis (P.g) lipopolysaccharide (LPS)-induced inflammatory response in human gingival fibroblasts (HGFs) and to explore the underlying mechanisms. To provide a basis for the mechanism of diabetes aggravating periodontitis. Methods: HGFs were divided into four groups: the control group (basal medium), the LPS group (treated with 5 μg/mL P.g-LPS for 24 h), the HG group (treated with 25 mmol/L glucose for 24 h), and the HG+LPS group (treated with 25 mmol/L glucose + 5 μg/mL P.g-LPS for 24 h). After culturing for 24 h in the respective media, the cells were harvested for experiments. Intracellular reactive oxygen species (ROS) and mitochondrial reactive oxygen species (mtROS) were detected using 2 ', 7' - dichlorodihydrofluorescein diacetate (DCFH-DA) and MitoSOX Red staining, respectively. Fluorescence intensity was analyzed by confocal fluorescence microscopy and directly measured in cell suspension. Immunofluorescence was used to detect changes in mitochondrial DNA (mtDNA) content of HGFs. Real-time fluorescence quantitative PCR was used to detect the content of mtDNA in cytoplasm and cell supernatant. Protein expression of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway was assessed by western blot, while mRNA expression levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6) were detected by PCR. Results: Compared to the control group, both the LPS group and the HG group exhibited a significant increase in ROS and mtROS, with a more pronounced elevation in the HG+LPS group, demonstrating a synergistic effect (ROS: F = 396.5, P < 0.001; mtROS: F = 29.38, P < 0.001, CI < 1). The cytoplasmic mtDNA content was significantly elevated in the LPS group, with a more marked increase in the HG+LPS group (F = 27.85, P < 0.001). The supernatant mtDNA levels were significantly higher in both the LPS and HG groups, with a more pronounced elevation in the HG+LPS group (F = 15.26, P < 0.001). The phosphorylated proteins p-STING, p-TBK1, and p-P65 in the cGAS-STING pathway showed varying degrees of activation in the LPS and HG groups, reaching the highest levels in the HG+LPS group (p-STING: F = 52.67, P < 0.001; p-TBK1: F = 15.67, P = 0.001; p-P65: F = 9.83, P = 0.005), while p-IRF3 showed no significant differences among the groups (P = 0.072). Pro-inflammatory cytokine TNF-α was significantly higher in the HG+LPS group compared to the control group (F = 15.05, P < 0.001), and IL-1β increased in both the LPS and HG groups, with a more pronounced rise in the HG+LPS group (F = 30.98, P < 0.001). IL-6 showed no significant differences among the groups (P = 0.847). Conclusion High glucose and LPS act synergistically to enhance oxidative stress, accompanied by increased mtDNA release, which activates the cGAS-STING pathway, thereby amplifying the inflammatory response in HGFs.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires