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.

INTRODUCTION: Cancer patients attending emergency departments (EDs) often present with acute symptoms and are frequently admitted. This study aimed to characterise the profile of oncology patients who were discharged from the ED. METHODS: This was a retrospective audit of patients with cancer-related diagnoses who presented to the ED at the Singapore General Hospital (SGH) over a 6-month period from 1 October 2018 to 31 March 2019 and were directly discharged from the ED. Data was extracted from the hospital's electronic medical record system. RESULTS: Of the 492 participants included in the study, the majority were triaged as Priority 2 (61.4%), while 30.7% were triaged as Priority 3, 6.9% as Priority 1 and 1.0% as Priority 4. There was no statistical difference between the National Early Warning scores across the different triage categories in these patients. The most common complaint was (44.3%), followed by genitourinary symptoms (19.5%) and those related to devices, catheters or stomas (17.3%). More investigations of all types were done for patients being managed in Priority 1 (57.6%) than in the other triage categories (40.1% for Priority 2, 23.2% for Priority 3 and 12.0% for Priority 4). Treatment procedures carried out were mainly symptomatic (analgesics, antiemetics, proton pump inhibitors) for 79.8% of the patients. There were no significant differences in the proportion of patients requiring various treatment modalities among the triage categories. CONCLUSION Selected oncological patients may potentially be managed in an ambulatory setting.
Humans ; Emergency Service, Hospital/statistics & numerical data* ; Retrospective Studies ; Female ; Neoplasms/diagnosis* ; Male ; Singapore ; Patient Discharge/statistics & numerical data* ; Middle Aged ; Aged ; Triage ; Adult ; Emergencies ; Aged, 80 and over

INTRODUCTION: Adverse childhood experiences (ACEs) are associated with significant long-term impacts, yet few interventions specifically target ACE exposure, especially in Asian populations. Anchor, Singapore's first home visitation programme, addresses maltreat-ment among preschool children. This study evaluated Anchor's impact on children's developmental and behavioural outcomes. METHOD: We conducted a prospective evaluation of children under 4 years assessed for maltreatment from November 2019 to July 2023. Developmental and behavioural progress was measured every 6 months using the Ages and Stages Questionnaires (ASQ-3) and ASQ:Social-Emotional (ASQ:SE-2), and annually using the Child Behaviour Checklist (CBCL). RESULTS: The results of 125 children (mean age 20.0 months, 48% female) were analysed. The mean length of stay in programme was 21.2 (7.3) months. At baseline, 92 (73.6%) children were at risk of develop-mental delay and 25 (31.7%) children aged ≥18 months had behavioural concerns. The programme was associated with significant improvements in gross motor (P=0.002) and fine motor (P=0.001) domains of the ASQ-3 and internalising problem scale (P=0.001) of the CBCL. CONCLUSION Anchor effectively enhances develop-mental and behavioural outcomes for children exposed to maltreatment. Targeted early intervention through such programmes can mitigate adverse impacts, optimising developmental trajectories and potentially reducing the long-term clinical and economic burdens associated with ACEs.
Humans ; Female ; Male ; Child Abuse/therapy* ; Child, Preschool ; Singapore ; House Calls ; Infant ; Prospective Studies ; Child Development ; Developmental Disabilities/epidemiology* ; Program Evaluation ; Child Behavior Disorders ; Child Behavior

This study aimed to investigate the effects of acupuncture on dynamic changes in Ca²⁺, Na⁺, and H₂O₂ flux following eccentric exercise-induced muscle injury. The total of 324 healthy male Wistar rats were randomly divided into 6 groups: control group (C), eccentric exercise group (E), eccentric exercise with acupuncture group (EA), EA with TRP channel blocker group (EAT), EA with NOX2 blocker group (EAN) and EA with placebo group (EAP). Gastrocnemius muscles were subject to lengthening contractions with percutaneous electrical stimulation, followed by immediate pretreatment with blocking agents. After 30 min, acupuncture needling was administered to the gastrocnemius muscle, and real-time dynamic changes of Ca²⁺, Na⁺ and H₂O₂ flux were measured with non-invasive micro-test technique during the needle retention period, immediately, 3 h, 6 h, and 24 h post-extraction respectively. Results showed that compared with the E group, acupuncture significantly increased net Ca²⁺ efflux (P < 0.05), extended the period of net Na⁺ influx, and significantly decreased net H₂O₂ efflux (P < 0.05). However, these effects were significantly attenuated in the EAT and EAN groups, where excessive net H₂O₂ efflux was observed (P < 0.001). These findings indicate that acupuncture regulates the dynamic changes of Ca²⁺, Na⁺ and H₂O₂ flux by activating the TRP channels and interacting with NOX2 activity following eccentric exercise-induced skeletal muscle injury.
Animals ; Muscle, Skeletal/metabolism* ; Rats, Wistar ; Rats ; Male ; Calcium/metabolism* ; Hydrogen Peroxide/metabolism* ; Physical Conditioning, Animal ; Sodium/metabolism* ; Acupuncture Therapy ; NADPH Oxidase 2

Peroxisome proliferator-activated receptor γ coactivator 1 α (PGC-1α) is a core member of the PGC-1 family and serves as a transcriptional coactivator, playing a crucial regulatory role in various diseases. Mitochondria, the main site of cellular energy metabolism, are essential for maintaining cell growth and function. Their function is regulated by various transcription factors and coactivators. PGC-1α regulates the biogenesis, dynamics, energy metabolism, calcium homeostasis, and autophagy processes of mitochondria by interacting with multiple nuclear transcription factors, thereby exerting significant effects on mitochondrial function. This review explores the biological functions of PGC-1α and its regulatory effects and related mechanisms on mitochondria, providing important information for our in-depth understanding of the role of PGC-1α in cellular metabolism. The potential role of PGC-1α in metabolic diseases, cardiovascular diseases, and neurodegenerative diseases was also discussed, providing a theoretical basis for the development of new treatment strategies.
Humans ; Mitochondria/metabolism* ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha/physiology* ; Animals ; Energy Metabolism/physiology* ; Neurodegenerative Diseases/physiopathology* ; Autophagy/physiology* ; Transcription Factors/physiology* ; Metabolic Diseases/physiopathology* ; Cardiovascular Diseases/physiopathology*

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C

Asthma is a chronic inflammatory disease involving multiple inflammatory cells and cytokines. Its pathogenesis is complex, involving various cells and cytokines. Traditional Chinese medicine(TCM) theory suggests that the pathogenesis of asthma is closely related to the dysfunction of internal organs such as the lungs, spleen, and kidneys. In contrast, modern immunological studies have revealed the central role of T helper 1(Th1)/T helper 2(Th2) and T helper 17(Th17)/regulatory T(Treg) cellular immune imbalance in the pathogenesis of asthma. Th1/Th2 imbalance is manifested as hyperfunction of Th2 cells, which promotes the synthesis of immunoglobulin E(IgE) and the activation of eosinophil granulocytes, leading to airway hyperresponsiveness and inflammation.Meanwhile, Th17/Treg imbalance exacerbates the inflammatory response in the airways, further contributing to asthma pathology.Currently, therapeutic strategies for asthma are actively exploring potential targets for regulating the balance of Th1/Th2 and Th17/Treg immune responses. These targets include cytokines, transcription factors, key proteins, and non-coding RNAs. Precisely regulating the expression and function of these targets can effectively modulate the activation and differentiation of immune cells. In recent years,traditional Chinese medicine active ingredients have shown unique potential and prospects in the field of asthma treatment. Based on this, the present study systematically summarizes the efficacy and specific mechanisms of TCM active ingredients in treating asthma by regulating Th1/Th2 and Th17/Treg immune balance through literature review and analysis. These active ingredients, including flavonoids, terpenoids, polysaccharides, alkaloids, and phenolic acids, exert their effects through various mechanisms, such as inhibiting the activation of inflammatory cells, reducing the release of cytokines, and promoting the normal differentiation of immune cells. This study aims to provide a solid foundation for the widespread application and in-depth development of TCM in asthma treatment and to offer new ideas for clinical research and drug development of asthma.
Asthma/genetics* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Th2 Cells/drug effects* ; Th17 Cells/drug effects* ; T-Lymphocytes, Regulatory/drug effects* ; Th1 Cells/drug effects* ; Animals ; Cytokines/immunology* ; Medicine, Chinese Traditional