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.

Objective:To investigate the risk factors for adverse outcomes in elderly patients with nonvalvular atrial fibrilla-tion(AF)after percutaneous left atrial appendage closure(LAAC)combined with radiofrequency ablation(RFA).Meth-ods:A total of 199 elderly AF patients who admitted in Department of Cardiology,Yuhuangding Hospital between Jan 1st,2019 and Aug 17th,2023 and underwent LAAC combined RFA were enrolled.The patients were divided into case group(n=78)and control group(n=121)according to presence of atrial arrhythmia and/or cerebral infarction(CI)within one year after operation.Baseline clinical data,laboratory indexes and color Doppler ultrasound indexes were compared be-tween the two groups,and multivariate Logistic regression was used to analyze the risk factors for postoperative atrial ar-rhythmia and/or CI.Receiver operating characteristic(ROC)curve was constructed to analyze the predictive efficacy of risk factors for atrial arrhythmia and/or CI after operation.Results:Univariate analysis indicated that compared with pa-tients in control group,those in case group had significant higher proportions of preoperative persistent atrial fibrillation(52.60％ vs.37.20％),old myocardial infarction(OMI)(11.50％vs.1.70％)and left atrial diameter(LAD)[(45.47±6.90)mm vs.(43.34±6.64)mm](P＜0.05 or＜0.01).Multivariate Logistic regression analysis indicated history of OMI(OR=8.736,95％CI 1.772～43.069,P=0.008)and LAD(OR=1.053,95％CI 1.006～1.102,P=0.027)were independent risk factors of adverse outcomes in elderly AF patients after LAAC+RFA.ROC analysis indicated that predic-tive efficacy of combined detection of OMI and LAD(AUC=0.663,95％CI 0.593～0.728)for adverse outcomes within 1 year in elderly AF patients after LAAC+RFA was significantly better than those of OMI(AUC=0.549,95％CI 0.477～0.620)and LAD(AUC=0.602,95％CI 0.531～0.671)alone(Z=3.045,2.312,P=0.002,0.021).Conclusion:His-tory of old myocardial infarction and left atrial diameter are independent risk factors for atrial arrhythmia and/or cerebral infarction within 1 year after percutaneous left atrial appendage closure combined with radiofrequency ablation in elderly patients with atrial fibrillation,and the combination has good predictive performance.

Objective:To investigate the risk factors for adverse outcomes in elderly patients with nonvalvular atrial fibrilla-tion(AF)after percutaneous left atrial appendage closure(LAAC)combined with radiofrequency ablation(RFA).Meth-ods:A total of 199 elderly AF patients who admitted in Department of Cardiology,Yuhuangding Hospital between Jan 1st,2019 and Aug 17th,2023 and underwent LAAC combined RFA were enrolled.The patients were divided into case group(n=78)and control group(n=121)according to presence of atrial arrhythmia and/or cerebral infarction(CI)within one year after operation.Baseline clinical data,laboratory indexes and color Doppler ultrasound indexes were compared be-tween the two groups,and multivariate Logistic regression was used to analyze the risk factors for postoperative atrial ar-rhythmia and/or CI.Receiver operating characteristic(ROC)curve was constructed to analyze the predictive efficacy of risk factors for atrial arrhythmia and/or CI after operation.Results:Univariate analysis indicated that compared with pa-tients in control group,those in case group had significant higher proportions of preoperative persistent atrial fibrillation(52.60％ vs.37.20％),old myocardial infarction(OMI)(11.50％vs.1.70％)and left atrial diameter(LAD)[(45.47±6.90)mm vs.(43.34±6.64)mm](P＜0.05 or＜0.01).Multivariate Logistic regression analysis indicated history of OMI(OR=8.736,95％CI 1.772～43.069,P=0.008)and LAD(OR=1.053,95％CI 1.006～1.102,P=0.027)were independent risk factors of adverse outcomes in elderly AF patients after LAAC+RFA.ROC analysis indicated that predic-tive efficacy of combined detection of OMI and LAD(AUC=0.663,95％CI 0.593～0.728)for adverse outcomes within 1 year in elderly AF patients after LAAC+RFA was significantly better than those of OMI(AUC=0.549,95％CI 0.477～0.620)and LAD(AUC=0.602,95％CI 0.531～0.671)alone(Z=3.045,2.312,P=0.002,0.021).Conclusion:His-tory of old myocardial infarction and left atrial diameter are independent risk factors for atrial arrhythmia and/or cerebral infarction within 1 year after percutaneous left atrial appendage closure combined with radiofrequency ablation in elderly patients with atrial fibrillation,and the combination has good predictive performance.

OBJECTIVE To design and synthesize rifamycin S derivatives and load them into milk exosomes to evaluate their in vitro antimicrobial activity.METHODS Rifamycin S derivatives were synthe-sized and characterized by mass spectrometry and NMR.Using the dilution assay method,the inhibitory activity of each rifamycin S derivatives molecule against Staphylococcus aureus and Pseudomonas aerugi-nosa was determined,and the IC50 was calculated.Derivatives molecules with excellent antimicrobial activity were selected and loaded into milk exosomes using the ultrasonication method,resulting in the preparation of milk exosome-loaded rifamycin S derivatives.The antimicrobial activity against Staphylo-coccus aureus was determined using the dilution assay method.The inhibitory effect of the exosome-loaded rifamycin S derivatives on Staphylococcus aureus residing within macrophages was detected using the plate colony counting method.RESULTS Three rifamycin S derivatives were successfully designed and synthesized,which demonstrated superior antimicrobial activity against Staphylococcus aureus(the parent compound's antimicrobial activity is merely from 1/20 to 1/80 of that of the three rifamycin S derivatives)and Pseudomonas aeruginosa(the parent compound's antimicrobial activity is only 1/14 and 1/9 of that of compound 1 and compound 3)compared to the parent compound.The loading of milk exosomes with the rifamycin S derivatives compound 3 was successfully achieved,with a loading efficiency of 10.9％.The antimicrobial activity of the compound after exosome loading was significantly enhanced against Staphylococcus aureus in vitro and against Staphylococcus aureus residing within macrophages(P＜0.01).CONCLUSION The designed and synthesized derivatives of rifamycin S possess stronger anti-microbial activity,and their antibacterial efficacy against both extracellular and intracellular bacteria can be further enhanced after loading into exosomes.

Objective To evaluate the efficacy and safety of high-power,short-duration radiofrequency catheter ablation for the treatment of persistent atrial fibrillation.Methods This retrospective study included 392 patients diagnosed with persistent atrial fibrillation who underwent catheter radiofrequency ablation at Suzhou Kowloon Hospital,Shanghai Jiao Tong University School of Medicine,from January 2019 to December 2023.Of these,256 patients were treated with high-power,short-duration ablation,and 136 patients with low-power,long-duration ablation.The following parameters were compared:radiofrequency ablation time,total procedure time,single-circle pulmonary vein isolation rate,immediate procedural success rate,number of ablation points,and perioperative complications(including pericardial tamponade,pseudoaneurysm,arteriovenous fistula,stroke,etc.).Follow-up assessments were conducted at 3,6,and 12 months post-surgery to evaluate the 12-month sinus rhythm maintenance rate.Results The ablation time in the high-power group was significantly shorter than that in the low-power group[(14.6±2.3)min vs.(30.3±4.2)min,P＜0.001],as was the total procedure time[(113.8±24.8)min vs.(128.5±26.7)min,P=0.001].There were no significant differences between the two groups in terms of pulmonary vein isolation rate(97.7％vs.94.9％,P=0.823),number of ablation points[(71.2±8.0)vs.(74.3±14.3),P=0.168],or perioperative complications(3.1％vs.4.4％,P=0.571).Regarding the maintenance rate of sinus rhythm at 12 months post-operation,the high-power group showed a higher rate than the low-power group,but no statistically significant difference was observed(82.8％vs.79.4％,P=0.399).Conclusions High-power,short-duration radiofrequency catheter ablation can improve procedural efficiency in the treatment of persistent atrial fibrillation.Its efficacy and safety are similar to those of the low-power,long-duration technique.

To investigate the prevalence of influenza D virus(IDV)in cattle and swine populations in Jilin Province,China,277 nasopharyngeal swabs were collected from livestock exhibiting influ-enza-like symptoms for IDV detection.Virus isolation was performed using swine testicular(ST)cells for PCR-positive samples,followed by comprehensive analyses including whole-genome se-quencing,phylogenetic analysis,electron microscopic observation of viral morphology,and glycosy-lation site prediction.Two IDV strains were successfully isolated from bovine samples,designated as D/bovine/China/JL22/2024(JL22)and D/bovine/China/JL34/2024(JL34).These strains were demonstrated to have specific hemagglutination activity against turkey red blood cells,while no he-magglutination to chicken,rabbit,or guinea pig erythrocytes.Virus-inoculated ST cells exhibited distinct cytopathic effects(CPE)within 48 h,with a hemagglutination titer of 4 log2 in the culture supernatant.Phylogenetic analysis of the hemagglutinin-esterase-fusion(HEF)gene indicated that these strains were most closely related to the Japanese isolate D/Yamagata2019,belonging to the YAMA2019 lineage.Genomic sequence analysis showed the absence of genetic reassortment in these isolates.In this study,two IDV strains were successfully isolated and characterized,which provides preliminary insights into their genomic sequences and biological properties.The findings confirm the presence of IDV in bovine populations in Jilin Province and provide the fundamental data for future epidemiological surveillance and control strategies of IDV.

To investigate the prevalence of influenza D virus(IDV)in cattle and swine populations in Jilin Province,China,277 nasopharyngeal swabs were collected from livestock exhibiting influ-enza-like symptoms for IDV detection.Virus isolation was performed using swine testicular(ST)cells for PCR-positive samples,followed by comprehensive analyses including whole-genome se-quencing,phylogenetic analysis,electron microscopic observation of viral morphology,and glycosy-lation site prediction.Two IDV strains were successfully isolated from bovine samples,designated as D/bovine/China/JL22/2024(JL22)and D/bovine/China/JL34/2024(JL34).These strains were demonstrated to have specific hemagglutination activity against turkey red blood cells,while no he-magglutination to chicken,rabbit,or guinea pig erythrocytes.Virus-inoculated ST cells exhibited distinct cytopathic effects(CPE)within 48 h,with a hemagglutination titer of 4 log2 in the culture supernatant.Phylogenetic analysis of the hemagglutinin-esterase-fusion(HEF)gene indicated that these strains were most closely related to the Japanese isolate D/Yamagata2019,belonging to the YAMA2019 lineage.Genomic sequence analysis showed the absence of genetic reassortment in these isolates.In this study,two IDV strains were successfully isolated and characterized,which provides preliminary insights into their genomic sequences and biological properties.The findings confirm the presence of IDV in bovine populations in Jilin Province and provide the fundamental data for future epidemiological surveillance and control strategies of IDV.

Objective:Non-targeted metabolomics based on ultra-performance liquid chromatography mass spectrometry(UPLC-MS)platform was used to study the metabolic characteristics of multiple myeloma(MM)patients,and explore potential new metabolic mechanisms affecting the occurrence and development of MM.Methods:The study enrolled 42 MM patients,including 21 newly diagnosed(ND)patients and 21 relapsed patients(RP),and 21 age-sex matched healthy controls(HC)as subjects.UPLC-MS analysis platform was used to detect small molecule metabolites in serum of the subjects.Principal component analysis(PCA),orthogonal partial least-squared discriminant analysis(OPLS-DA)and 200 random permutations were used to analyze the differences of metabolic profiles among groups.Identification of differential metabolites was completed in the Human Metabolome Database(HMDB)and abnormal metabolic pathway analysis was performed using the KEGG database.Results:The metabolic profiles of MM patients and healthy controls were significantly separated in both PCA and OPLS-DA models,while the metabolic profiles of newly diagnosed and relapsed MM patients were significantly separated only in OPLS-DA model.In ND vs HC,RP vs HC and RP vs ND cohorts,19,24 and 18 differential metabolites were identified respectively,mainly sphingolipids,glycerophospholipids and fatty acyl amino acids.The metabolic pathway abnormalities in newly diagnosed and relapsed MM patients were mainly manifested in sphingolipid metabolism and glycerophospholipid metabolism compared to healthy controls.Compared with newly diagnosed MM patients,relapsed MM patients were mainly manifested in sphingolipid metabolism and ether-lipid metabolism.Conclusion:The metabolic profiles of MM patients are significantly different from those of healthy people.Relapsed MM patients and newly diagnosed MM patients have similar metabolic profiles,but there are still some differences.Glycerophospholipid metabolism,sphingolipid meta-bolism and ether-lipid metabolism may play important biological roles in the occurrence and development of MM.