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.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Background: Aspiration pneumonia (AP), which can be caused by gastric content inhalation into the lower airways, causes acute lung injury (ALI) through complex mechanisms, including inflammation, oxidative stress, and apoptosis. Here, we evaluated the efficacy of exosomes derived from human placental mesenchymal stem cells (hpMSCs) in mitigating ALI in a murine model of AP. We also investigated the role of hsa-let-7i-5p, the most abundant miRNA in hpMSC-derived exosomes, in this respect. Methods: Adult male C57BL/6 mouse AP models were administered hpMSC-derived exosomes (APExo group) or phosphate-buffered saline (AP group) intra-tracheally. After 48 h, the mice were euthanized and evaluated. The effects of hsa-let-7i-5p were assessed by specific inhibition or overexpression. Results: Compared with the APExo group, the AP group exhibited significantly greater ALI, as evidenced by histological damage, increased lung injury scores, impaired lung function, increased leukocyte infiltration, and elevated tissue edema (all P < 0.05). The untreated AP group also showed more inflammation, characterized by nuclear factor-κB upregulation, macrophage M1 polarization, and cytokine level elevation (tumor necrosis factor-α, interleukin-1β, and interleukin-6), as well as increased oxidation and activation of the apoptosis pathway (all P < 0.05). Notably, the therapeutic effects of hpMSC-derived exosomes were compromised by specific inhibition of hsa-let-7i-5p. Furthermore, engineered exosomes derived from genetically modified RAW264.7 overexpressing hsa-let-7i-5p demonstrated therapeutic effects against AP similar to those obtained with hpMSC-derived exosomes. Conclusions In a murine AP model, intra-tracheal administration of hpMSC-derived exosomes has ALI-mitigating effects, involving inflammation, oxidation, and apoptosis modulation, with hsa-let-7i-5p playing a pivotal mediating role.

ObjectiveTo analyze the epidemiological and clinical characteristics of pertussis in Taizhou City, Zhejiang Province, 2024, and to provide a scientific basis for formulating local prevention and control strategies. MethodsCase data and population data were obtained from the China Disease Prevention and Control Information System. Epidemiological case investigation data were collected from the Zhejiang Vaccine Clinical Research and Application Effectiveness Evaluation System and the Immunization Service Information System. Descriptive epidemiological methods were used to analyze the temporal, spatial and demographic distributions, and SaTScan 9.7 software was applied for spatiotemporal cluster scanning. ResultsIn 2024, a total of 3 090 pertussis cases were reported in Taizhou City, with no deaths. The number of reported cases increased significantly compared with those in previous years, and the peak occurred in April. Spatiotemporal scanning identified three clusters: a most likely cluster centered around Tantou Town in Tiantai County, covering 16 streets/towns, a second most likely cluster centered around Taiping Subdistrict in Wenling City, covering 11 streets/towns, and a third most likely cluster centered around Ganjiang Town in Yuhuan City, covering 6 streets/towns. The three clusters together accounted for 31.04% of the total scanned cases.The majority of cases were in the 6‒10 years age group (55.02%), and students accounted for the highest proportion by occupation (44.17%). Among 2 929 epidemiological investigation cases, the most common clinical manifestations were cough (97.58%) and aggravated nocturnal cough (52.10%), while typical symptoms (including paroxysmal spasmodic cough and post-tussive vomiting, etc.) were less frequent. Among the cases, 82.49% had completed the full 4-dose vaccination schedule, and their complication rate (10.47%) was lower than that of the unvaccinated group (20.56%). ConclusionThe number of reported pertussis cases surged in Taizhou City in 2024, showing significant spatiotemporal clustering, with school‑aged children being the high‑risk group. Vaccination could reduce the risk of complications. It is recommended to further enhance surveillance sensitivity, with a focus on strengthening immunization strategies for high-risk groups such as school-aged children aged 6‒10 years, and to reinforce targeted protection for infants under 1 year old who have not completed primary vaccination, along with their families. In addition, prevention and control resources should be deployed in advance for the cluster areas identified through spatiotemporal analysis and for the spring peak season,to interrupt local transmission chains.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Objective To investigate the occurrence status quo and influencing factors of low muscle mass(LMM)among young and middle-aged health examination population.Methods The young and middle-aged people undergoing the body composition analysis in this hospital from January to December 2023 were selected as the study subjects.The general data,body composition indices and biochemical indicators were col-lected.The body composition analysis was performed by the bioelectrical impedance analysis(BIA).LMM was diagnosed based on the skeletal muscle index.The univariate and multivariate logistic regression were used to analyze the influencing factors of LMN occurrence in the young and middle-aged health examination population.The receiver operating characteristic(ROC)curve and the area under the curve(AUC)were em-ployed to evaluate the predictive value of each indicator.Results A total of 2 351 people undergoing the phys-ical examination were included,aged 18-49 years old,366(15.57％)cases of LMM were detected out.The skeletal muscle index,sex,age,age group distribution,body mass index(BMI),body fat percentage(BFP),body fat percentage grade,visceral fat area(VFA),AST/ALT,Hb,serum creatinine,blood uric acid,HbA1c,fasting blood glucose,TC,LDL-C,HDL-C,TG and triglyceride-glucose index(TyG)had statistical differences between the LMM group and normal group(P＜0.05).Multivariate logistic regression revealed that the sex(OR=2.606,95％CI:1.755-3.870),BMI(OR=0.579,95％CI:0.538-0.623),BFP(OR=5.885,95％CI:4.176-8.292)and VFA(OR=0.955,95％CI:0.944-0.967)were the influencing factors for the LMM oc-currence in the young and middle-aged people undergoing the physical examination(P＜0.001).The ROC a-nalysis showed the AUC values of the sex,BMI,BFP and VFA for predicting LMM were 0.580,0.821,0.636 and 0.715 respectively,in which the predictive value of BMI was highest.Conclusion The population of fe-male,low BMI,high BFP and low VFA maybe the high-risk groups for LMM.The health management for the above-mentioned groups needs to be strengthened.

Objective To study the protective effects and mechanism of sacubitril(Sac)/valsartan(Val)on cardiomyocytes of rabbits with heart failure induced by doxorubicin(DOX).Methods Thirty New Zealand rabbits were selected to establish DOX-induced heart failure rabbit model.Twenty-five rabbits with successful modeling were randomly assigned to model group(DOX group,n=9),DOX+Val group(n=8),and DOX+Sac/Val group(n=8);and another 8 New Zealand rabbits were selected as blank group.The DOX+Val group was gavaged with 4.65 mg/kg Val suspension each time,the DOX+Sac/Val group was gavaged with 9.3 mg/kg Sac/Val suspension each time,and the blank group and DOX group were gavaged with equal volume of distilled water each time.Each group was gavaged twice a day for 8 weeks.After 8 weeks of administration,echocardiography was used to measure left ventricular end-diastolic diameter(LVDD),left ventricular end-systolic diameter(LVSD),left ventricular ejection fraction(LVEF),and left ventricular fractional shortening(LVFS).The heart mass index(HMI)and left ventricular mass index(LVMI)were calculated.The pathological morphology and myocardial fibrosis of myocardial tissue were observed by hematoxylin-eosin(H-E)and Masson staining.The ultrastructure of cardiomyocytes was observed by transmission electron microscope.Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling(TUNEL)staining was used to observe cardiomyocytes apoptosis and apoptosis rate was calculated.Enzyme-linked immunosorbent assay(ELISA)was used to detect the levels of N-terminal pro-brain natriuretic peptide(NT-proBNP),high-sensitivity cardiac troponin I(Hs-cTNI),angiotensin Ⅱ(Ang Ⅱ),aldosterone(ALD),atrial natriuretic peptide(ANP),brain natriuretic peptide(BNP),cyclic guanosine monophosphate(cGMP),and protein kinase G(PKG)in serum.Quantitative polymerase chain reaction(qPCR)was used to detect the expression of natriuretic peptide receptor A(NPR-A),cGMP-specific phosphodiesterase 5A(PDE5A[cGMP]),PKG,B-cell lymphoma 2(Bcl-2),Bcl-2 associated X protein(Bax),and cysteine aspartate protease 3(caspase 3)mRNA in myocardial tissue.Western blotting was used to detect the expression of phosphorylated cAMP response element-binding protein(p-CREB),phosphorylated Bcl-2 related death promoting factor(p-Bad),Bcl-2,Bax,and caspase 3 proteins in myocardial tissue.Results Compared with the blank group,the LVDD and LVSD in the DOX group were increased(both P<0.01),the LVEF and LVFS were decreased(both P<0.01)and the HMI and LVMI were increased(both P<0.01);the apoptosis and apoptosis rate of cardiomyocytes were increased(P<0.01);the levels of NT-proBNP,Hs-cTNI,Ang Ⅱ,ALD,ANP,BNP,cGMP and PKG and the expression of NPR-A,PDE5A(cGMP),PKG,p-CREB,Bax and caspase 3 were all increased(all P<0.01),while the expression of Bcl-2 was decreased(P<0.01),and the expression of p-Bad had no significant difference(P>0.05).Compared with the DOX group,the LVDD and LVSD of the DOX+Sac/Val group and DOX+Val group were decreased(all P<0.01),the LVEF and LVFS were increased(all P<0.01)and the HMI and the LVMI were decreased(all P<0.01);the apoptosis and apoptosis rate of cardiomyocytes were decreased(all P<0.01);the levels of NT-proBNP,Hs-cTNI,Ang Ⅱ,ALD,ANP,BNP,cGMP and PKG and the expression of NPR-A,PDE5A(cGMP),PKG,Bax and caspase 3 were all decreased(all P<0.01),while the expression of Bcl-2 was increased(P<0.01);and the expression of p-CREB and p-Bad was increased in the DOX+Sac/Val group(both P<0.01),but there was no significant difference in the DOX+Val group(both P>0.05).Compared with the DOX+Val group,the DOX+Sac/Val group showed a decrease in all indicators except for LVEF,LVFS,NPR-A,ANP,BNP,cGMP,PDE5A(cGMP),PKG,p-CREB,p-Bad,and Bcl-2,which were all elevated(all P<0.05).Myocardial pathology and transmission electron microscopy showed that Sac/Val effectively protected cardiomyocytes,reduced cardiomyocytes apoptosis and myocardial fibrosis,and these effects were significantly better than those of Val.Conclusion Sac/Val can effectively reduce cardiomyocytes apoptosis,improve cardiac function and reduce myocardial fibrosis in rabbits with heart failure,and these effects are superior to Val.Its mechanism may be related to activating the NPR-A/cGMP/PKG signaling pathway and inhibiting renin-angiotensin-aldosterone system.