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.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

3CL protease (3CLpro) of SARS-CoV-2 is a pivotal enzyme required in coronavirus replication and transcription. Its highly conserved structure and the absence of homologous proteins in the host make it an ideal target for broad-spectrum anti-coronavirus drug development. In this work, we systematically investigated and compared the binding modes and dynamic properties of the four stereoisomers of a pyridyl-urea diyne ester (PyDU) molecule with two chiral centers within the 3CLpro active site. Through molecular docking, MD simulations, MM/GBSA binding free-energy calculations, and DCCM analysis, all four stereoisomers were stabilized primarily by hydrophobic packing. Among them, the (R,S) isomer exhibited the best overall performance, including docking score, binding free-energy components, and key residue interactions. The (R,S) and (S,R) isomers also enhanced the cooperative motions around the binding pocket, while the (R,S) isomer further modulated the flexibility of domain III, which may influence 3CLpro dimerization. Conversely, the (S,S) isomer exhibited the weakest affinity due to insufficient hydrophobic contact. By innovatively integrating chirality, binding energy and protein dynamical features, we revealed the dual role of chirality in modulating affinity and dynamic responses, which provides a theoretical basis for the chiral-guided design of coronavirus inhibitors.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective To investigate the mechanism of Ginkgo biloba extracts(GB)in the treatment of cerebral ischemia-reperfusion(CIR)injury based on network pharmacology and animal experiments.Methods The intersection targets of CIR and GB were obtained from TCMSP,GeneCards and other databases.Cytoscape software and Metascape database were used to analyze and map the related targets.The model of transient middle cerebral arterial occlusion(t-MCAO)was constructed in mice by suture method,and the effects of GB on the neurological function of mice after t-MCAO were observed by the neurological deficit score and Morris water maze test.HE staining was used to observe the pathological structural changes of neuron in the hippocampus of mice,and Western blot was used to verify the signal pathways screened by network pharmacology.Results Network pharmacology predicted that GB contained 33 active ingredients,and 116 potential targets of GB in treatment of CIR included Caspase3,Bax,etc.In addition,GB may play a protective role through signaling pathways such as PI3K-Akt and AMPK.Animal experiments showed that GB treatment could significantly improve the neural function and learning spatial memory ability of mice,alleviate the brain histopathological injury,and activate p-Akt/Akt signaling pathway.Conclusion GB has the characteristics of multi-target and multi-pathways therapy for CIR,which may reduce neuronal apoptosis by activating the p-Akt/Akt signaling pathway.

Objective:Using ecological niche width and situation model,the operation and management of public Traditional Chinese Medicine(TCM)hospitals in 16 cities in Shandong Province were evaluated to put forward countermeasures.Methods:The relevant index data of public TCM hospitals in 16 cities in Shandong Province from 2019 to 2022 were collected to analyze the development status.The ecological niche width model and niche situation model were applied to evaluate the operation and management of public TCM hospitals in 16 cities in Shandong.Results:The top three public TCM hospitals in terms of average ecological niche width were City G,City P and City F.The ecological niche situation value of public TCM hospitals in City K,City A and City J ranked the top three.Conclusion:The dimensions of operation management structure of public TCM hospitals in Shandong need to be enhanced and the development of operation management space needs to be balanced.It is feasible to evaluate operation management by using ecological niche width and situation model.It is suggested to improve the allocation efficiency of health personnel,facilities,funds and other resources;promote the spatial balanced development of operation management;promote the application of ecological niche width and situation model in the field of medicine and health management.

Objective:To investigate the effect of medical community homogenization management(MCHM)on self-care ability,heart function,vascular endothelial function and quality of life in patients with chronic heart failure(CHF).Methods:This randomized controlled study enrolled 110 CHF patients admitted in Panzhihua Central Hos-pital between April 2021 and April 2023.They were divided into intervention group(n=55)and routine group(n=55).The control group received routine management,while intervention group received additional MCHM,both groups were intervened for 3 months.Self-care ability,heart function,vascular endothelial function,quality of life and incidence of adverse events were compared between two groups.Results:Compared with patients in control group,those in intervention group had significant higher total score of self-care of heart failure index(SCHFI)[(82.30±2.98)points vs.(59.46±3.19)points],stroke volume(SV)[(73.30±2.31)ml vs.(54.66±1.96)ml],left ventricular ejection fraction(LVEF)[(58.25±2.90)％ vs.(52.41±2.52)％],early diastolic peak flow velocity/late diastolic peak flow velocity(E/A)[(1.95±0.18)vs.(1.30±0.16)]and the level of nitric oxide(NO)[(106.70±4.44)μmol/L vs.(82.36±4.66)μmol/L](P＜0.001 all),and significant lower left ventricular end-diastolic diameter(LVEDd)[(49.79±1.58)mm vs.(56.49±2.17)mm],endothelin-1(ET-1)[(36.66±2.65)ng/L vs.(46.88±2.66)ng/L],Minnesota living with heart failure questionnaire(MLHFQ)total score[(36.12±3.23)points vs.(54.67±3.35)points](P＜0.001 all).Patients in intervention group had significant lower incidence of adverse events comparing to those in control group(7.27％ vs.25.45％,P=0.010).Conclu-sion:Medical community homogenization management could significantly improve self-care ability,heart func-tion,vascular endothelial function and quality of life with good safety in CHF patients.

Objective:To investigate the current status of life stress and hypertension among couples of childbearing age across diverse economic regions in China, and to explore relevant influencing factors.Methods:This study was a cross-sectional study, with subjects from the “Research on the standardized system of comprehensive prevention and control of birth defects based on preconception-prenatal-postnatal whole chain”. From February to May 2021, urban and rural couples of childbearing age (18-49 years old) from Beijing, Henan, and Gansu provinces were enrolled, representing the eastern, central, and western regions of China, respectively. The detection rate, cognition and control of hypertension in the general population, as well as the detection rate of hypertension in different genders and regions were analyzed. Subjects were divided into hypertensive group and non-hypertensive group based on whether their blood pressure was≥140/90 mmHg (1 mmHg=0.133 kPa), and the general clinical data of the two groups were compared. Subjects were also divided into prehypertension and hypertension group and normal blood pressure group based on whether their blood pressure was≥130/80 mmHg, and the general clinical data of the two groups were compared, with subgroup analyses conducted by gender. Multifactorial logistic regression model was applied to identify factors associated with prehypertension and hypertension in both males and females.Results:A total of 1 942 couples of childbearing age, comprising 3 884 individuals, aged (29.8±5.2) years were enrolled, with 1 942 males (50.0%). The overall hypertension detection rate was 6.3% (246/3 884), with a detection rate of 10.5% (203/1 942) in males and 2.2% (43/1 942) in females. The hypertension detection rates in Beijing, Henan, and Gansu were 6.2% (92/1 482), 11.6% (139/1 200), and 1.2% (15/1 202), respectively. The overall detection rate of prehypertension and hypertension was 40.5% (1 574/3 884). Multifactorial logistic regression analysis showed that life pressure factors had no effect on female blood pressure levels ( P>0.05), while a significant or high level of life/work pressure was a risk factor for prehypertension and hypertension in males ( OR=2.30, 95% CI 1.06-4.99, P<0.05). Conclusion:The detection rate of prehypertension and hypertension among young couples of childbearing age in China is high, with poor awareness and control of hypertension. There are sex differences in the relationship between life pressure and blood pressure levels. Comprehensive consideration of individual living environments and mental health factors is crucial in blood pressure management. Measures to reduce life stress and enhance mental resilience should be implemented to address this public health issue.

Objective:To analyze the genetic characteristics of the VWF gene c.7332G＞A nonsense mutation and explore its molecular pathogenesis.Methods:Phenotypic diagnosis of the proband was performed using VWF:Ag,VWF:RCo,FⅧ:C and multimeric analysis.The probands were genotyped by NGS whole-exome sequencing,and the sequencing results were validated by sanger sequencing.The family members were genotyped by Sanger sequencing.The VWF gene c.7332G＞A nonsense mutant plasmid was constructed.After transfection,the function of VWF gene c.7332G＞A mutant plasmid was verified at cell level in vitro.The mRNA level was detected by qRT-PCR,and the expression level of protein was detected by Western blot,the function of multimerization was verified by the multimeric analysis.Results:VWF:Ag and VWF:RCo were all less than 3％in the proband,and the multimeric analysis showed multimer deficiency.The proband was diagnosed as type 3 VWD.The homozygous nonsense mutation of VWF gene c.7332G＞A was detected by gene sequencing.The VWF mRNA level of the mutant plasmid was decreased,and the VWF protein expression in the cell supernatant was decreased,the mutant protein was truncated and the function of VWF multimerization was impaired.Conclusion:A homozygous mutation in exon 43 of VWF gene,c.7332G＞A,was responsible for the probands type 3 VWD in the proband.The mutation caused a decrease in the relative level of VWF mRNA and protein,and impaired the function of VWF multimerization.