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 This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

OBJECTIVE To establish a quality control method for Jinbei oral liquid based on multi-wavelength switching high performance liquid chromatography （HPLC） fingerprint， chemical pattern recognition and multi-index content determination. METHODS A total of 15 batches of Jinbei oral liquid were used as test samples. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （ Version 2012 ） was adopted to establish multi-wavelength switching HPLC fingerprints， followed by chromatographic peak identification and similarity evaluation. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were applied to conduct chemical pattern recognition on the 15 batches of samples. The multi-wavelength switching HPLC method was used to simultaneously determine the contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianoli c acid B and wogonoside in samples. RESULTS A total of 25 common peaks were calibrated in the fingerprints of 15 batches of Jinbei oral liquid， among which 7 common peaks were unambiguously identified. The similarity of all samples was higher than 0.960. Chemical pattern recognition results showed that samples S1-S8 were clustered into group 1， and samples S9-S15 were clustered into group 2. Baicalin， wogonoside， neochlorogenic acid， chlorogenic acid and salvianolic acid B were identified as the differential quality markers. The average contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianolic acid B and wogonoside in 15 batches of Jinbei oral liquid were 0.213 7， 0.085 3， 0.104 9， 0.287 3， 0.420 1， 0.062 1， 0.176 0 mg/mL， respectively. CONCLUSIONS The established quality control method for Jinbei oral liquid combining multi-wavelength switching HPLC fingerprint， chemical pattern recognition and multi-index content determination is stable and reliable， which can provide a reference for the formulation of quality standards of this preparation.

ObjectiveTo explore the mechanisms of Qingchang Wenzhong Decoction （清肠温中方， QWD） in treating ulcerative colitis （UC）. MethodsA total of 100 male C57BL/6J mice were assigned to a pseudo-germ-free group （n=45） and a conventional group （n=55） using a random number table. Pseudo-germ-free model was established by giving antibiotic treatment and subsequently subjected to acute UC induction. After the model was successfully established， the 45 pseudo-germ-free acute UC mice were randomly allocated to a pseudo-germ-free model group， a pseudo-germ-free QWD group， and a pseudo-germ-free mesalazine group， with 15 mice in each group. The 55 conventional mice were randomly divided into a normal control group （n=10）， as well as a conventional model group， a conventional QWD group， and a conventional mesalazine group， with 15 mice in each group. Except for the normal control group， acute UC models were established in all other groups. Mice in the control group received no intervention. From day 32 of the experiment， mice in the pseudo-germ-free QWD group and the conventional QWD group were administered with QWD granules at a dose of 9.71 g/（kg·d） by gavage with deionized water， while those in the pseudo-germ-free mesalazine group and the conventional mesalazine group were given mesalazine enteric-coated tablets at a dose of 151.67 mg/（kg·d） by gavage. Mice in the remaining groups received an equal volume of deionized water once daily for 7 consecutive days. On day 25 of the experiment， six mice were randomly selected from both the pseudo-germ-free group and the conventional group to measure body weight， and fecal samples were collected for 16S rDNA sequencing to compare differences in gut microbiota， including operational taxonomic units （OTUs）， Shannon index， Observed_species index， and phylogenetic diversity （PD whole tree）. On day 39， body weight was measured in all groups， and the disease activity index （DAI） was evaluated. Colon length and colon wet weight were recorded. Histopathological changes in colonic tissues were assessed by hematoxylin and eosin （HE） staining， and histological injury scores were determined. In addition， the expression levels of mucopolysaccharides and mucin 2 （MUC2） in colonic tissues were measured. ResultsOn day 25， there was no significant difference in body weight between the pseudo-germ-free group and the conventional microbiota group （P＞0.05）. Compared to the conventional microbiota group， the pseudo-germ-free group showed significantly reduced OTUs， Shannon index， Observed_species index， and PD whole tree （P＜0.01）. On day 39， compared to the normal control group， mice in the conventional model group showed a significant decrease in the body weight and an increase in DAI， along with increased colon wet weight， shortened colon length， markedly elevated histopathological scores， and reduced expression of mucopolysaccharides and MUC2 （P＜0.01）. In contrast， no significant differences were observed in these parameters in the pseudo-germ-free model group （P＞0.05）. Compared to the conventional model group， the conventional QWD group showed significant improvement in all measured parameters， whereas the conventional mesalazine group showed reductions only in DAI scores and colon wet weight （P＜0.01）. No statistically significant differences were observed among the pseudo-germ-free model group， the pseudo-germ-free QWD group， and the pseudo-germ-free mesalazine group （P＞0.05）. ConclusionQWD may promote the reconstruction of the intestinal mucus barrier by regulating the intestinal flora， thereby exerting a therapeutic effect on acute UC.

ObjectiveTo explore the mechanisms of Qingchang Wenzhong Decoction （清肠温中方， QWD） in treating ulcerative colitis （UC）. MethodsA total of 100 male C57BL/6J mice were assigned to a pseudo-germ-free group （n=45） and a conventional group （n=55） using a random number table. Pseudo-germ-free model was established by giving antibiotic treatment and subsequently subjected to acute UC induction. After the model was successfully established， the 45 pseudo-germ-free acute UC mice were randomly allocated to a pseudo-germ-free model group， a pseudo-germ-free QWD group， and a pseudo-germ-free mesalazine group， with 15 mice in each group. The 55 conventional mice were randomly divided into a normal control group （n=10）， as well as a conventional model group， a conventional QWD group， and a conventional mesalazine group， with 15 mice in each group. Except for the normal control group， acute UC models were established in all other groups. Mice in the control group received no intervention. From day 32 of the experiment， mice in the pseudo-germ-free QWD group and the conventional QWD group were administered with QWD granules at a dose of 9.71 g/（kg·d） by gavage with deionized water， while those in the pseudo-germ-free mesalazine group and the conventional mesalazine group were given mesalazine enteric-coated tablets at a dose of 151.67 mg/（kg·d） by gavage. Mice in the remaining groups received an equal volume of deionized water once daily for 7 consecutive days. On day 25 of the experiment， six mice were randomly selected from both the pseudo-germ-free group and the conventional group to measure body weight， and fecal samples were collected for 16S rDNA sequencing to compare differences in gut microbiota， including operational taxonomic units （OTUs）， Shannon index， Observed_species index， and phylogenetic diversity （PD whole tree）. On day 39， body weight was measured in all groups， and the disease activity index （DAI） was evaluated. Colon length and colon wet weight were recorded. Histopathological changes in colonic tissues were assessed by hematoxylin and eosin （HE） staining， and histological injury scores were determined. In addition， the expression levels of mucopolysaccharides and mucin 2 （MUC2） in colonic tissues were measured. ResultsOn day 25， there was no significant difference in body weight between the pseudo-germ-free group and the conventional microbiota group （P＞0.05）. Compared to the conventional microbiota group， the pseudo-germ-free group showed significantly reduced OTUs， Shannon index， Observed_species index， and PD whole tree （P＜0.01）. On day 39， compared to the normal control group， mice in the conventional model group showed a significant decrease in the body weight and an increase in DAI， along with increased colon wet weight， shortened colon length， markedly elevated histopathological scores， and reduced expression of mucopolysaccharides and MUC2 （P＜0.01）. In contrast， no significant differences were observed in these parameters in the pseudo-germ-free model group （P＞0.05）. Compared to the conventional model group， the conventional QWD group showed significant improvement in all measured parameters， whereas the conventional mesalazine group showed reductions only in DAI scores and colon wet weight （P＜0.01）. No statistically significant differences were observed among the pseudo-germ-free model group， the pseudo-germ-free QWD group， and the pseudo-germ-free mesalazine group （P＞0.05）. ConclusionQWD may promote the reconstruction of the intestinal mucus barrier by regulating the intestinal flora， thereby exerting a therapeutic effect on acute UC.

OBJECTIVE To establish a quality control method for Jinbei oral liquid based on multi-wavelength switching high performance liquid chromatography （HPLC） fingerprint， chemical pattern recognition and multi-index content determination. METHODS A total of 15 batches of Jinbei oral liquid were used as test samples. The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （ Version 2012 ） was adopted to establish multi-wavelength switching HPLC fingerprints， followed by chromatographic peak identification and similarity evaluation. Cluster analysis， principal component analysis and orthogonal partial least squares-discriminant analysis were applied to conduct chemical pattern recognition on the 15 batches of samples. The multi-wavelength switching HPLC method was used to simultaneously determine the contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianoli c acid B and wogonoside in samples. RESULTS A total of 25 common peaks were calibrated in the fingerprints of 15 batches of Jinbei oral liquid， among which 7 common peaks were unambiguously identified. The similarity of all samples was higher than 0.960. Chemical pattern recognition results showed that samples S1-S8 were clustered into group 1， and samples S9-S15 were clustered into group 2. Baicalin， wogonoside， neochlorogenic acid， chlorogenic acid and salvianolic acid B were identified as the differential quality markers. The average contents of neochlorogenic acid， chlorogenic acid， cryptochlorogenic acid， forsythoside A， baicalin， salvianolic acid B and wogonoside in 15 batches of Jinbei oral liquid were 0.213 7， 0.085 3， 0.104 9， 0.287 3， 0.420 1， 0.062 1， 0.176 0 mg/mL， respectively. CONCLUSIONS The established quality control method for Jinbei oral liquid combining multi-wavelength switching HPLC fingerprint， chemical pattern recognition and multi-index content determination is stable and reliable， which can provide a reference for the formulation of quality standards of this preparation.

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets