To analyze the disease burden of acute lymphoid leukemia(ALL) and its changing trends in China and globally from 1990 to 2021, aiming to provide a theoretical basis for disease prevention, treatment, and policy formulation.

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.

ObjectiveTo explore the listed varieties and prescription characteristics of Chinese patent medicines for stroke in China， explore the medication rules of Chinese medicine for stroke， and provide guidance for further clinical research and development of Chinese patent medicines. MethodsExcel 2021 and the Ancient and Modern Medical Record Cloud Platform （V2.3.5） were used to systematically mine and analyze the varieties and prescriptions of Chinese patent medicines for stroke in China. ResultsA total of 244 Chinese patent medicines （two for different dosage forms of the same prescription）， 1 736 approval documents for Chinese patent medicines， 792 manufacturers， and 83 varieties of protected Chinese patent medicines were finally included in the database. The top three dosage forms were capsules （75）， pills （53）， and tablets （42）. There were 28 Chinese patent medicines for stroke in the National Essential Drug Catalogue （2018）， 129 in the National Essential Medical Insurance， Industrial Injury Insurance and Maternity Insurance Drug Catalogue （2023）， and 4 in the National Non-prescription Drug Catalogue. Among the 138 prescriptions screened out， Chinese patent medicines mainly treated stroke patients with the syndrome of Qi deficiency and blood stasis. The top three most frequent medicinal herbs were Chuanxiong Rhizoma （63）， Pheretima （47）， and Salviae Miltiorrhizae Radix et Rhizoma （47）. The medicinal herbs used were mainly warm， pungent， with the meridian tropism to the liver meridian. The correlation analysis showed that the herb pair with the highest support was Astragali Radix-Chuanxiong Rhizoma， and that with the highest confidence was Carthami Flos-Chuanxiong Rhizoma. Five herb combinations were identified based on the cluster analysis. ConclusionThe Chinese patent medicines for stroke mainly treat patients with the syndrome of Qi deficiency and blood stasis. The medicinal herbs used in the prescriptions mainly have the functions of activating blood and resolving stasis， extinguishing wind and stopping convulsions. Drug compatibility usually focuses on activating blood and resolving stasis， as well as expelling phlegm and opening orifices. This review of the varieties and prescription characteristics of Chinese patent medicines for stroke helps optimize clinical decision-making， guide drug research and development， promote medical research and scientific progress， and provide more effective support and guarantee for the treatment of stroke patients.

[Objective] To explore the feasibility of using whole blood as a source of NK cells for allogeneic CAR NK cell therapy and activated NK cell reinfusion therapy, and initially construct a technical system for the separation and purification of NK cells from whole blood. [Methods] All peripheral blood mononuclear cells (PBMCs) were enriched from 400 mL of whole blood by manual separation and machine separation, respectively. The erythrocyte loss rate, PBMCs number, NK cell purity of the two methods were compared. NK cells were sorted from PBMCs by three separation and enrichment methods as immunomagnetic bead negative selection method, platelet lysate culture expansion and PERCOLL density gradient separation method, and the purity and yield of NK cells, the activity of NK cells and the tumor-killing ability of the three separation and enrichment methods were compared. [Results] The proportion of NK cells in the lymphocyte population was higher in the manual separation method than in the machine separation method[(13.16±5.16)% vs (8.56±3.92)%, P<0.05]; the number PBMCs was lower in the manual separation method than in the machine separation method[(4.09±1.80)×10⁸vs (6.49±2.16)×10⁸, P<0.05], and there was no difference in the red blood cell loss between the two methods (P>0.05). The purity of NK cells isolated and enriched from PBMCs by manual separation method using immunomagnetic was (96.77±2.31)%; the yield was (56.27±10.47)%; the inhibition of tumor proliferation was (38.67±14.05)%; and the tumor killing rate was (19.90±8.05)%. The purity of NK cells isolated and enriched from PBMCs by manual separation method using platelet lysis culture expansion method was the highest at day 7, which was (54.84±15.80)%; the cell expansion multiple could reach 16.92±6.28 at day 7; the in vitro tumor killing rate of NK cells was (15.83±5.5)%; the tumor inhibition rate was (44.33±13.5)%; and there was no difference in the toxicity and activity of NK cells between the two methods (P>0.05). The purity of NK cells isolated and enriched by PERCOLL density gradient separation method was (15.83±5.82)%, and the yield was (14±6.25)%, which was significantly lower than the other two methods. [Conclusion] PBMCs isolated from whole blood by manual separation and NK cells enriched by negative selection with immunomagnetic beads have the potential to provide NK cell materials for CAR-NK cell therapy, and NK cells enriched by platelet lysate-conditioned medium have the potential to provide NK cells for large-scale NK cell activation reinfusion therapy.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

Laparoscopic subtotal cholecystectomy (LSC) has been a safe and viable alternative to conversion to laparotomy in cases of severe cholecystitis. The objective of this study is to determine the utility of intraoperative choledochoscopy in LSC for the exploration of the gallbladder, cyst duct, and subsequent stone clearance of the cystic duct in cases of severe cholecystitis. A total of 72 patients diagnosed with severe cholecystitis received choledochoscopy-assisted laparoscopic subtotal cholecystectomy (CALSC). A choledochoscopy was performed to explore the gallbladder cavity and/or cystic duct, and to extract stones using a range of techniques. The clinical records, including the operative records and outcomes, were subjected to analysis. No LSC was converted to open surgery, and no bile duct or vascular injuries were sustained. All stones within the cystic duct were removed by a combination of techniques, including high-frequency needle knife electrotomy, basket, and electrohydraulic lithotripsy. A follow-up examination revealed the absence of residual bile duct stones, with the exception of one common bile duct stone, which was extracted via endoscopic retrograde cholangiopancreatography. In certain special cases, CALSC may prove to be an efficacious treatment for the management of severe cholecystitis. This technique allows for optimal comprehension of the situation within the gallbladder cavity and cystic duct, facilitating the removal of stones from the cystic duct and reducing the residue of the non-functional gallbladder remnant.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: The contraction behaviors of cardiomyocytes (CMs), especially contraction synchrony, are crucial factors reflecting their maturity and response to drugs. A wider field of view helps to observe more pronounced synchrony differences, but the accompanied greater computational load, requiring more computing power or longer computational time. METHODS: We proposed a method that directly correlates variations in optical field brightness with cardiac tissue contraction status (CVB method), based on principles from physics and photometry, for rapid video analysis in wide field of view to obtain contraction parameters, such as period and contraction propagation direction and speed. RESULTS: Through video analysis of human induced pluripotent stem cell (hiPSC)-derived CMs labeled with green fluorescent protein (GFP) cultured on aligned and random nanofiber scaffolds, the CVB method was demonstrated to obtain contraction parameters and quantify the direction and speed of contraction within regions of interest (ROIs) in wide field of view. The CVB method required less computation time compared to one of the contour tracking methods, the LucasKanade (LK) optical flow method, and provided better stability and accuracy in the results. CONCLUSION This method has a smaller computational load, is less affected by motion blur and out-of-focus conditions, and provides a potential tool for accurate and rapid analysis of cardiac tissue contraction synchrony in wide field of view without the need for more powerful hardware.

BACKGROUND: Over 65 million people have long COVID. Evidence for using Chinese herbal medicine (CHM) to treat long COVID is growing. A systematic review of evidence for guiding clinical decision is warranted. OBJECTIVE: To examine the effects and safety of CHM in alleviating the severity of dyspnea, fatigue, exercise intolerance, depression, anxiety and insomnia in long COVID adults based on registered randomized clinical trials (RCT). SEARCH STRATEGY: World Health Organization International Clinical Trials Registry Platform and Chinese Clinical Trial Registry were searched for registered trial protocols from database inception to February 10, 2023. English (PubMed, Embase, AMED and CINAHL) and Chinese databases (CNKI, Wanfang Data and CQVIP) were then searched to identify relevant publications from December 2019 through April 6, 2023. INCLUSION CRITERIA: Registered RCTs that compared the effects of Chinese herbal medicines or Chinese herbal formulas against a control treatment (i.e., the placebo or usual care) in adults with persistent symptoms of long COVID. The primary outcome of dyspnea, and secondary outcomes of fatigue, exercise intolerance, depression, anxiety and insomnia were measured using validated tools at the end of the treatment. DATA EXTRACTION AND ANALYSIS: Data were extracted, and eligible RCTs were evaluated using version 2 of the Cochrane risk-of-bias tool for randomized trials and Grading of Recommendations, Assessment, Development and Evaluations independently by two researchers. Effect sizes were estimated by random-effects modelling and mean difference (MD). Heterogeneity between trials was quantified by I². RESULTS: Among the 38 registered clinical trials we identified, seven RCTs (1,519 patients) were included in the systematic review. One RCT had a low overall risk of bias. Compared to the control, CHM reduces dyspnea on the Borg Dyspnea Scale score (MD = -0.2, 95% confidence interval [CI] = -0.65 to 0.25) with moderate certainty, and reduces fatigue on the Borg Scale (MD = -0.48, 95% CI = -0.74 to -0.22) with low certainty. CHM clinically reduces depression on Hamilton Depression Rating Scale score (MD = -6.00, 95% CI = -7.56 to -4.44) and anxiety on Hamilton Anxiety Rating Scale score (MD = -6.10, 95% CI = -7.67 to -4.53), and reduces insomnia on the Insomnia Severity Index (MD = -4.86, 95% CI = -12.50 to 2.79) with moderate certainty. Meta-analysis of two RCTs (517 patients) showed that CHM clinically improves exercise intolerance by increasing 6-minute walking distance (MD = -15.92, 95% CI = -10.20 to 42.05) with substantial heterogeneity (I² = 68%) and low certainty. CONCLUSION CHM is associated with a post-treatment clinical reduction in depression and anxiety in long COVID adults, compared to the control, but it does not have a strong treatment effect on dyspnea and insomnia. Effects of CHM on exercise intolerance and fatigue are uncertain, and the safety of using CHM remains questionable. Please cite this article as: Tsang MS, Zhou IW, Zhang AL, Xue CC. Chinese herbal medicine for dyspnea and persistent symptoms of long COVID: A systematic review and meta-analysis of randomized controlled trials. J Integr Med. 2025; 23(2): 126-137.
Humans ; Dyspnea/etiology* ; Drugs, Chinese Herbal/therapeutic use* ; Randomized Controlled Trials as Topic ; COVID-19/complications* ; Fatigue/drug therapy* ; SARS-CoV-2 ; Anxiety/drug therapy* ; Depression/drug therapy* ; Sleep Initiation and Maintenance Disorders/drug therapy* ; Betacoronavirus