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.

Ventricular assist devices(VADs)have emerged as a pivotal therapeutic option for end-stage heart failure,undergoing significant technological advancements from pneumatic membrane pumps to continuous-flow centrifugal pumps.This review provides a detailed overview of several VAD models,including HeartMate Ⅲ,EVAHEART 2,and Heart Con.The initial generation of VADs established a foundation for subsequent developments,despite the occurrence of frequent complications.The second generation of VADs demonstrated a notable improvement in patient prognosis but carried the risk of ventricular collapse.The third generation of VADs represents a further reduction in size,incorporating magnetic levitation technology to enhance durability and blood compatibility.In the future,the development of VADs will focus on better emulating the physiological function of the native heart,improving pulsatility,and extending device longevity.As technology advances,VADs are expected to offer heart failure patients with a greater range of treatment options and a higher quality of life.

Following extensive interdisciplinary research and development over several years,mechanical circulatory support devices(MCSD),including ventricular assist device(VAD)and total artificial heart(TAH),are now established as vital treatment options for patients with advanced heart failure.These devices have proven to be crucial in assisting or replacing a failing heart,offering patients a new lease of life and improving their quality of life.Currently,mechanical circulatory support(MCS)has become a well-recognised,long-term treatment option for patients who are unable to undergo heart transplantation due to donor organ shortages or contraindications.Given their continuous availability independent of donor organ limitations,these devices are poised to play an increasingly vital role in the future of medicine.This article aims to summarize the evolution,clinical applications,categorization,and potential complications of MCSD.

OBJECTIVE To systematically analyse the research status and hotspots of Jiegeng decoction from the perspective of bibliometrics,and to provide theoretical references for its clinical application and in-depth research.METHODS We searched the relevant literature in the databases of China Knowledge Network(CNKI),Wanfang and VIP up to March 2025,and used NoteExpress for de-duplication and screening,combined with Excel,CiteSpace,and VOSviewer to analyse the dimensions of trend of issuance,country/institution cooperation,author network,and keywords.The dimensions of publication trend,country/institution collaboration,author network and keywords were visualised and analysed by combining Excel,CiteSpace and VOSviewer.RESULTS A total of 597 Chi-nese articles were included.The number of variable publications was characterised by a four-stage evolution,with the core research in-stitutions focusing on TCM colleges and affiliated hospitals,and less cross-country collaboration.Literature focused on the effects of Jiegeng decoction on"cough","treatment"and"chronic pharyngitis".Emerging keywords indicated that"mechanism of action","therapeutic effect","medication pattern"and"antiviral"were emerging hot topics in recent years.CONCLUSION The study of Jiegeng decoction is shifting from single disease treatment to multi-target system regulation.In the future,it is necessary to strengthen the interdisciplinary integration,deepen the research on the immunomodulatory mechanism of Jiegeng decoction in respiratory viral in-fections,build the"chemical component-biological effect"related quality control system,deepen the combination of network pharma-cology and real-world research,and provide a new paradigm for the modernisation of classical prescriptions.

Objective:To investigate the clinical characteristics of patients with multiple myeloma(MM)complicated by bone lesions and the risk factors associated with bone lesions.Methods:The clinical data of 294 newly diagnosed MM patients in Gansu Provincial Hospital from January 2017 to June 2021 were retrospectively analyzed.The patients were divided into the bone lesion group(154 cases)and the non-bone lesions group(140 cases)based on the presence of absence of bone lesions at diagnosis.The general data and laboratory parameters were compared between the two groups.The risk factors for bone lesions in MM patients were analyzed by logistic regression analysis,and the characteristic(ROC)curves were plotted to assess the predictive value of each risk factor for the occurrence of bone lesions in MM patients.Results:Compared to the non-bone lesion group,the bone lesion group had significantly higher serum calcium levels and significantly greater proportions of patients with Durie-Salmon(DS)stage Ⅲ,and bone pain(all P＜0.05).Logistic regression analysis showed that elevated serum calcium(OR=5.135,95％CI:1.931-13.653,P=0.001),DS stage Ⅲ(OR=1.841,95％CI:1.019-3.328,P=0.043),and bone pain(OR=8.208,95％CI:4.761-14.151,P＜0.001)were independent risk factors for bone lesions in MM patients.ROC curve analysis showed that serum calcium(AUC=0.619,95％CI:0.555-0.683,P＜0.001)and bone pain(AUC=0.743,95％CI:0.692-0.793,P＜0.001)had predictive value for bone lesions in MM patients.Conclusion:MM patients have a high incidence of bone lesions,and active monitoring and management of risk factors may improve treatment outcomes and prognosis.

BACKGROUND:The Twin-block orthodontic appliance is commonly used for the correction of Class Ⅱ malocclusion.Its mechanism of action in stimulating mandibular growth has been confirmed in many studies,but its impact on maxillary growth is not very clear. OBJECTIVE:By establishing a finite element model to analyze the stress distribution of the maxillary complex,surrounding bone sutures,and maxillary dentition in patients with Class Ⅱ malocclusion wearing Twin-block orthodontic appliances. METHODS:One patient with Class Ⅱ malocclusion who underwent orthodontic treatment at Qingdao Hospital/Qingdao Municipal Hospital of Shandong Rehabilitation University was selected.The bite force data of the patient when wearing the Twin-block orthodontic appliance was measured,and CBCT data were collected.A finite element model was established,including the maxillary complex,peripheral sutures,Twin-block orthodontic appliance,and maxillary dentition.ABAQUS software was used to simulate the stress distribution in the maxilla and maxillary dentition when the patient was wearing the Twin-block appliance. RESULTS AND CONCLUSION:The equivalent stress on the maxillary anterior teeth was significantly smaller than that on the posterior teeth,and the maximum equivalent stress on both sides of the teeth were 4.797 5 Mpa and 8.716 1 Mpa,respectively,which were located at the first premolar.The maximum displacements were presented at the maxillary incisors on both sides of the teeth,which were 0.080 5 mm and 0.081 0 mm,respectively.The maximum equivalent stress on the bone suture was 1.284 Mpa,which was mainly concentrated in the pterygopalatine suture and the frontal-maxillary suture on both sides,and there was almost no difference in the force of the rest of bone sutures;the maximum displacement of the bone suture was 0.07 mm,with the pterygopalatine suture having the largest displacement,followed by the frontal-maxillary suture.The maximal equivalent stress on the maxillary complex was 27.18 Mpa,which was mainly concentrated on both sides of the anterior pyriform foramen of the maxilla,around the nasofrontal suture and around the pterygopalatine suture at the posterior part of the jaws.The maximal displacement of the maxilla was 0.07 mm,which was mainly concentrated on the maxillary alveolar bone.All these findings show that the occlusal force acts on the maxillary complex through the Twin-block appliance,resulting in clockwise rotation of the maxilla and steepening of the dentition plane.Measures should be taken to compensate for this tendency,for example,by considering maxillary molar elongation and intrusion in the process of occlusion,which are not only able to flatten the occlusal plane,but facilitate the mandibular protraction,thereby further improving Class Ⅱ malocclusion orthodontic treatment.

Atherosclerosis(AS)is a multifactorial disease,in which mitochondrial dysfunction of macrophages plays a key role.Mitochondrial dysfunction of macrophages affects polarization direction of macrophages and leads to severe inflammatory reac-tions,is a potential therapeutic target for AS.This article mainly reviews the latest research progress on role of macrophage mitochon-drial dysfunction in occurrence and development of AS,as well as treatment methods for improving macrophage mitochondrial function.

OBJECTIVE: To explore clinical efficacy of vancomycin-loaded antibiotic bone cement combined with induced membrane grafting for the treatment of diabetic foot ulcers(DFU). METHODS: Totally 68 DFU patients treated with bone cement combined with induced membrane grafting from November 2019 to November 2021 were retrospectively analyzed, including 37 males and 31 females, aged from 51 to 79 years old with an average of (63.63±7.85) years old;47 patients on the right side and 21 patients on the left side;28 patients with grade 2, 31 patients with were grade 3, and 9 patients with grade 4 according to Wagner's grades;the diameter of the wound ranged from 20.40 to 96.99 mm with an average of (59.67±23.26) mm. The time of wound healing, the number of operations, the survival of postoperative skin grafting, the number of postoperative recurrence and the rate of amputation were observed. RESULTS: All 68 patients were followed up for 12 to 18 months with an average of (15.06±2.12) months. The wound healing time ranged from 42 to 65 d with an average of (51.50±7.24) d, the numbers of operation ranged from 2 to 3 with an average of (2.25±0.44) times. All skin grafts were survived well after operation, without recurrence and amputation cases. CONCLUSION Vancomycin-containing antibiotic bone cement combined with induced membrane grafting is effective in treating DFU, and the operation is simple and reliable.
Humans ; Male ; Female ; Middle Aged ; Vancomycin/therapeutic use* ; Bone Cements/therapeutic use* ; Aged ; Diabetic Foot/therapy* ; Skin Transplantation ; Anti-Bacterial Agents/therapeutic use* ; Retrospective Studies ; Wound Healing/drug effects*