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.

To study the therapeutic effect and mechanisms of ethyl syringate(MD) on ulcerative colitis(UC), the MTT assay was used to detect the proliferation inhibition of RAW264.7 cells and HT-29 cells by different concentrations of MD(50, 100, 200, 400 μmol·L~(-1)). UC cell models were constructed by inducing RAW264.7 cells and HT-29 cells with lipopolysaccharide(LPS) and tumor necrosis factor-α(TNF-α). An animal model was established by inducing mice with 2.5% dextran sulfate sodium(DSS) to verify the therapeutic effect of MD on UC. A control group, a model group(LPS or TNF-α), and groups treated with different concentrations of MD(50, 100, 200, 400 μmol·L~(-1)) were set up in this study. Nitric oxide(NO) levels were measured using a NO detection kit. Intracellular reactive oxygen species(ROS) levels were assessed using a laser confocal microscope and ROS kit. Enzyme-linked immunosorbent assay(ELISA) was used to detect changes in the levels of interleukin-6(IL-6), TNF-α, interferon-γ(INF-γ), interleukin-10(IL-10), and myeloperoxidase(MPO) in cells and animal tissues. Western blot was used to detect the expression levels of phosphorylated Janus kinase 2(p-JAK2), Janus kinase 2(JAK2), phosphorylated signal transducer and activator of transcription 3(p-STAT3), signal transducer and activator of transcription 3(STAT3), zonula occludens-1(ZO-1), occludin, and claudin-1 in cells and animal tissues. The results showed that MD can improve the inflammatory response by inhibiting the production of NO and ROS and regulating the expression of inflammatory factors. It significantly reduced the disease activity index(DAI) in mice, improved the shortening of the colon, and repaired intestinal epithelial damage by inhibiting the activation of the JAK2/STAT3 pathway, thereby exerting anti-UC activity.
Animals ; Colitis, Ulcerative/chemically induced* ; Janus Kinase 2/genetics* ; STAT3 Transcription Factor/genetics* ; Mice ; Humans ; Signal Transduction/drug effects* ; Male ; RAW 264.7 Cells ; Reactive Oxygen Species/metabolism* ; Nitric Oxide/metabolism* ; HT29 Cells ; Salicylates/administration & dosage* ; Protective Agents/administration & dosage*

With the rise of data-intensive research, data literacy has become a critical capability for improving scientific data quality and achieving artificial intelligence (AI) readiness. In the biomedical domain, data are characterized by high complexity and privacy sensitivity, calling for robust and systematic data management skills. This paper reviews current trends in scientific data governance and the evolving policy landscape, highlighting persistent challenges such as inconsistent standards, semantic misalignment, and limited awareness of compliance. These issues are largely rooted in the lack of structured training and practical support for researchers. In response, this study builds on existing data literacy frameworks and integrates the specific demands of biomedical research to propose a comprehensive, lifecycle-oriented data literacy competency model with an emphasis on ethics and regulatory awareness. Furthermore, it outlines a tiered training strategy tailored to different research stages-undergraduate, graduate, and professional, offering theoretical foundations and practical pathways for universities and research institutions to advance data literacy education.
Artificial Intelligence ; Humans ; Biomedical Research

OBJECTIVE: To explore the feasibility and effectiveness of repairing surgical defect in pharyngo-laryngeal malignant tumor with free rectus femoris flap. METHODS: The clinical data of 34 patients with surgical defects in pharyngo-laryngeal malignant tumor who met the selection criteria between July 2014 and August 2024 were retrospectively analyzed. There were 25 males and 9 females, aged 25-82 years, with a median age of 54 years. The disease duration ranged from 2 months to 2 years, with a median of 7 months. The tumor locations included the oropharynx, hypopharynx, cervical esophagus, and larynx. Pathological types included squamous cell carcinoma (29 cases), myoepithelial carcinoma (2 cases), adenoid cystic carcinoma (1 case), and diffuse large B-cell lymphoma (2 cases). TNM staging: 16 cases of T ₄N ₁M ₀, 3 cases of T ₄N ₂M ₀, 3 cases of T ₄N ₀M ₀, 10 cases of T ₃N ₁M ₀, and 2 cases of T ₃N ₀M ₀. The 2017 American Joint Committee on Cancer (AJCC) staging was stage Ⅲ in 2 cases and stage Ⅳ in 32 cases. The blood supply of the proximal rectus femoris muscle was observed by enhanced CT of the lower limb vessels before operation, and the surgical defects ranged from 3.0 cm×2.0 cm to 12.0 cm×8.5 cm. The blood supply and perforators of rectus femoris muscle were explored during operation, and the free rectus femoris flap pedicled with the direct vascular stem of rectus femoris muscle was used to repair the defect. For the patients with pharyngeal fistula or obvious neck swelling after operation, the blood supply of the flap was analyzed by vascular enhanced CT to determine the corresponding strategies of nutritional support, anti-infection, dressing change and drainage. Radiotherapy and chemotherapy were supplemented in 27 patients with lymph node metastasis after operation. RESULTS: All the 34 patients were followed up 1-10 years, with an average of 3 years. The flap was found to be necrotic by fibrolaryngoscopy at 1 week after operation in 2 cases, and the incision healed after dressing change and nutritional support, and no reoperation was performed. The flap was in good condition at 1 week after operation in 4 cases, and the signs of gradual necrosis of the flap were found within 1 month after operation, of which 2 cases were healed after dressing change, 1 case was removed the necrotic tissue by reoperation, and 1 case was healed after pectoralis major myocutaneous flap was used to repair the pharyngeal tissue defect. The flaps survived in 28 cases, including 4 cases of pharyngeal fistula, which healed by dressing change. Twenty-two cases achieved satisfactory results in swallowing or phonation. Two patients with total laryngectomy and voice reconstruction underwent reoperation to seal the voice tube because of postoperative aspiration. During the follow-up, 1 case had tracheal stomal recurrence, 2 cases had bone metastasis, and 1 case had bone and lung metastasis. CONCLUSION The free rectus femoris flap has good flexibility, the volume of the flap is easy to adjust, and the incision of the donor site is concealed, which is expected to become a new choice for the repair of the surgical defect in pharyngo-laryngeal malignant tumor.
Humans ; Male ; Middle Aged ; Female ; Aged ; Adult ; Plastic Surgery Procedures/methods* ; Retrospective Studies ; Laryngeal Neoplasms/pathology* ; Aged, 80 and over ; Pharyngeal Neoplasms/pathology* ; Free Tissue Flaps/blood supply* ; Quadriceps Muscle/transplantation* ; Surgical Wound/surgery* ; Treatment Outcome

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.

Objective To establish a performance verification scheme for the metagenomic next-generation sequencing(mNGS)DNA workflow.Methods Reference materials and clinical samples were used for conducting experiments.The mNGS detection results were evaluated in terms of limit of detection(LOD),repeatability,robustness,anti-interference ability,specificity and accuracy,as well as the patterns of library construction and the performance of sequencers.Results All species in the reference materials were stably detected,and the LOD of mNGS was 5.0E+02 CFU/mL(copies/mL).The repeatability was 100％and the within-batch(coefficient of variation)CV ranged from 8.53％to 38.73％.The linear correlation coefficient|r|＞0.9 was found between the input pathogenic microorganism concentration and the read count.Meanwhile,the experimental robustness was found to be good.The results of the anti-interference test showed that the higher concentration of human DNA inputted,the fewer pathogenic microorganism read counts detected by mNGS.Meanwhile,the read counts of related species presented a proportional relationship with the corresponding pathogenic microorganisms concentration inputted,which meant the validation of the cross-interference test had been passed.Furthermore,the detection result of D0 was negative.The accuracy of clinical samples testing was 90.9％(10/11).In addition,the library quality control results obtained by the automatic liquid handling workstation and manually operation were all acceptable.The performance of the three Illumina sequencers met or were better than the factory standards.Conclusion The clinical laboratory performance verification scheme for mNGS detection was established,which included the design for reference materials,comparison of different patterns for library construction,and performance evaluation of the sequencers.More importantly,the performance verification scheme can be used to evaluate and ensure the quality of mNGS DNA workflow detection process.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.