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.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

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.

A scoping review was performed to systematically search and summarize the clinical research in the treatment of dysmenorrhea with oral Chinese patent medicines. The oral Chinese patent medicines for treating dysmenorrhea in three major drug lists, guidelines, and textbooks were screened, and the relevant clinical trials were retrieved from eight Chinese and English databases. The key information of the included trials was extracted and visually analyzed. A total of 50 Chinese patent medicines were included, among which oral Chinese patent medicines for the dysmenorrhea patients with the syndrome of Qi stagnation and blood stasis accounted for the highest proportion, and the average daily cost varied greatly among Chinese patent medicines. A total of 150 articles were included, involving 22 Chinese patent medicines, among which Guizhi Fuling Capsules/Pills, Sanjie Zhentong Capsules, and Dan'e Fukang Soft Extract were the most frequently studied. These articles mainly reported randomized controlled trial(RCT), which mainly focused on the comparison of the intervention effect between Chinese patent medicines combined with western medicine and western medicine alone, and the sample size was generally 51-100 cases. The high-frequency outcome indicators belonged to nine domains such as effective rate, adverse reactions, and laboratory examinations. This study showed that oral Chinese patent medicines had advantages in the treatment of dysmenorrhea, and the annual number of related clinical trials showed an overall growing trend. However, there were still problems such as insufficient safety information and vague description of traditional Chinese medicine(TCM) syndromes types in the instructions of Chinese patent medicines. The available clinical research had shortcomings such as uneven distribution of Chinese patent medicines, limited research scale, poor methodological rigor, and insufficient standardization of outcome indicators. In the future, it is necessary to deepen the development of high-quality clinical research and improve the contents of the instructions to ensure the effectiveness and safety of the clinical application of oral Chinese patent medicines in the treatment of dysmenorrhea.
Dysmenorrhea/drug therapy* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Female ; Administration, Oral ; Nonprescription Drugs/administration & dosage*

This study aims to investigate the antipyretic effects and mechanisms of ethanol extracts from Arisaematis Rhizoma fermented with bile from different sources on a rat model of fever induced by a dry-yeast suspension. The rat model of fever was established by subcutaneous injection of 20% dry-yeast suspension into the rat back. The levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6) in the serum, as well as prostaglandin E_2(PGE_2) and cyclic adenosine monophosphate(cAMP) in the hypothalamus, were determined by ELISA. Metabolomics analysis was then performed on serum and hypothalamus samples based on UPLC-Q-TOF MS to explore the potential biomarkers and metabolic pathways. The results showed that the body temperatures of rats significantly rose 4 h after modeling. After oral administration of high-dose ethanol extracts of Arisaematis Rhizoma fermented with bovine bile(NCH) and porcine bile(ZCH), the body temperatures of rats declined(P<0.05), and the NCH group showed better antipyretic effect than the ZCH group. Additionally, compared with the model group, the NCH and ZCH groups showed lowered levels of IL-1β, IL-6, TNF-α, PGE_2, and cAMP(P<0.01). The results of serum and hypothalamus metabolomics analysis indicated that both NCH and ZCH exerted antipyretic effects by regulating phenylalanine metabolism, sphingolipid metabolism, arachidonic acid metabolism, and steroid hormone biosynthesis. Collectively, both NCH and ZCH can play an obvious antipyretic role in the rat model of dry yeast-induced fever, and the underlying mechanism might be closely associated with inhibiting inflammation and regulating metabolic disorders. Moreover, NCH demonstrates better antipyretic effect.
Animals ; Rats ; Male ; Fermentation ; Rats, Sprague-Dawley ; Rhizome/metabolism* ; Drugs, Chinese Herbal/chemistry* ; Bile/chemistry* ; Antipyretics/chemistry* ; Fever/metabolism* ; Cattle ; Swine ; Tumor Necrosis Factor-alpha/metabolism* ; Ethanol/chemistry* ; Interleukin-6/blood* ; Interleukin-1beta/blood*

Based on the high-fat diet-induced hyperlipidemia rat model, this study aimed to evaluate the lipid-lowering effect of Arisaema Cum Bile and explore its mechanisms, providing experimental evidence for its clinical application. Biochemical analysis was used to detect serum levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-C), triglycerides(TG), and total cholesterol(TC) to assess the lipid-lowering activity of Arisaema Cum Bile. Additionally, 16S rDNA sequencing and metabolomics techniques were employed to jointly elucidate the lipid-lowering mechanisms of Arisaema Cum Bile. The experimental results showed that high-dose Arisaema Cum Bile(PBA-H) significantly reduced serum ALT, AST, LDL-C, TG, and TC levels(P<0.01), and significantly increased HDL-C levels(P<0.01). The effect was similar to that of fenofibrate, with no significant difference. Furthermore, Arisaema Cum Bile significantly alleviated hepatocyte ballooning and mitigated fatty degeneration in liver tissues. As indicated by 16S rDNA sequencing results, PBA-H significantly enhanced both alpha and beta diversity of the gut microbiota in the model rats, notably increasing the relative abundance of Akkermansia and Subdoligranulum species(P<0.01). Liver metabolomics analysis revealed that PBA-H primarily regulated pathways involved in arachidonic acid metabolism, vitamin B_6 metabolism, and steroid biosynthesis. In summary, Arisaema Cum Bile significantly improved abnormal blood lipid levels and liver pathology induced by a high-fat diet, regulated hepatic metabolic disorders, and improved the abundance and structural composition of gut microbiota, thereby exerting its lipid-lowering effect. The findings of this study provide experimental evidence for the clinical application of Arisaema Cum Bile and the treatment of hyperlipidemia.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Metabolomics ; Hyperlipidemias/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Hypolipidemic Agents/pharmacology* ; Liver/metabolism* ; Humans ; Alanine Transaminase/metabolism* ; Triglycerides/metabolism* ; Aspartate Aminotransferases/metabolism*

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.