Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

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.

With the rapid development of deep learning(DL)technology,its potential applications in the medical field have become increasingly prominent.As a refractory disease,osteonecrosis of the femoral head(ONFH)has certain limitations in traditional diagnostic and therapeutic approaches.The application of DL technology is expected to overcome these limitations and improve diagnosis and treatment outcomes.At present,the applications of DL models-including enhancing image clarity,improving diagnostic accuracy and efficiency,conducting prognostic evaluations,optimizing preoperative planning,assisting intraoperative imaging,and customizing personalized treatment plans-have fully demonstrated their tremendous potential in the diagnosis and treatment of ONFH.This review summarizes the current application status of DL in ONFH diagnosis and treatment,aiming to provide references and insights for future related research.

Objective:To evaluate the clinical equivalence between a domestic calcipotriol/betamethasone dipropionate ointment and the originator product in the treatment of stable plaque psoriasis.Methods:A multicenter, randomized, double-blind, three-arm, parallel-group, active- and placebo-controlled study was conducted, and 449 patients aged 18 - 65 years with stable plaque psoriasis were enrolled from 25 hospitals (such as the First Affiliated Hospital of China Medical University). Eligible patients had a baseline physician's global assessment (PGA) score of ≥ 3 points, baseline body surface area (BSA) involvement of 5% - 30%, and a target lesion psoriasis area and severity index (TL-PASI) for plaque elevation of ≥ 3 points. Participants were randomly assigned in a 2:2:1 ratio to the test group ( n = 179), reference group ( n = 180), and placebo group ( n = 90), and applied the domestic calcipotriol/betamethasone dipropionate ointment, originator product, and ointment base respectively, once daily in the evening for 4 weeks. Efficacy and safety were assessed at weeks 1, 2, and 4. The primary efficacy endpoints were the treatment success rates and clinical success rates in each group at week 4. The per-protocol set (PPS) was used for the primary efficacy analysis, and the intention-to-treat (ITT) set for supplementary efficacy analysis. Equivalence between the test and reference preparations was tested using the Cochran-Mantel-Haenszel method adjusted for randomization strata. Superiority of the test and reference preparations over the placebo was also tested. Measurement data were compared among the 3 groups using analysis of variance or non-parametric tests, while treatment success rates, clinical success rates, and incidence rates of adverse reactions were compared using the chi-square test. Results:The ITT, PPS, and safety sets included 447, 420, and 448 patients, respectively. In the ITT set, patients were aged 43.6 ± 12.8 years, including 320 (71.6%) males and 127 (28.4%) females, and the disease duration was 11.21 ± 9.05 years; 316 (70.7%) had a PGA score of 3 points and 131 (29.3%) had a PGA score of 4 - 5 points. No significant differences in the baseline characteristics (including age, sex, disease duration and disease severity) were observed among the 3 groups (all P > 0.05). Based on the PPS analysis, the treatment success rates were 57.9% (99/171) in the test group, 50.3% (86/171) in the reference group, and 7.7% (6/78) in the placebo group, and the clinical success rates were 57.9% (99/171), 50.3% (86/171), and 10.3% (8/78), respectively; both the test and reference groups were superior to the placebo group in both treatment and clinical success rates (all P < 0.001) ; the rate differences for treatment success (90% confidence interval [ CI]: -1.3% - 16.4%) and clinical success (90% CI: -1.3% - 16.3%) between the test and reference groups were entirely within the pre-defined equivalence margin (-20% - 20%). Subgroup analyses by baseline PGA scores: for patients with a baseline PGA score of 3 points, the treatment success rates in the test, reference, and placebo groups were 60.8% (73/120), 52.1% (62/119), and 11.1% (6/54), respectively, and the corresponding clinical success rates were 61.7% (74/120), 53.8% (64/119), and 13% (7/54), respectively; the test and reference groups did not differ significantly in treatment or clinical success rates (both P > 0.05), but both showed higher success rates than the placebo group (all P < 0.001) ; the results of statistical comparisons among the 3 groups in patients with a baseline PGA score of 4 - 5 points were consistent with those observed in patients with a baseline PGA score of 3 points. The percentage reductions in PGA and TL-PASI scores from baseline to weeks 1, 2, and 4 showed significant differences among the 3 groups, which were significantly higher in the test and reference groups than in the placebo group (all P < 0.001), but did not differ between the test and reference groups (all P > 0.05). The primary adverse reactions were local skin reactions, such as pruritus, pain, and erythema. The incidence rates of adverse reactions were 8.9% (16/179) in the test group, 7.3% (13/179) in the reference group, and 7.8% (7/90) in the placebo group, with no significant difference among the 3 groups ( P > 0.05) . Conclusions:The domestic calcipotriol/betamethasone dipropionate ointment demonstrated clinical equivalence to the originator product in the treatment of stable plaque psoriasis, and the two agents exhibited comparable efficacy for patients with varying degrees of disease severity, and were comparable in the speed and degree of clinical improvement, with similar favorable safety profiles.

Alzheimer's disease (AD) is the major form of dementia in the elderly and is closely related to the toxic effects of microglia sustained activation. In AD, sustained microglial activation triggers impaired synaptic pruning, neuroinflammation, neurotoxicity, and cognitive deficits. Accumulating evidence has demonstrated that aberrant expression of deubiquitinating enzymes is associated with regulating microglia function. Here, we use RNA sequencing to identify a deubiquitinase YOD1 as a regulator of microglial function and AD pathology. Further study showed that YOD1 knockout significantly improved the migration, phagocytosis, and inflammatory response of microglia, thereby improving the cognitive impairment of AD model mice. Through LC-MS/MS analysis combined with Co-IP, we found that Myosin heavy chain 9 (MYH9), a key regulator maintaining microglia homeostasis, is an interacting protein of YOD1. Mechanistically, YOD1 binds to MYH9 and maintains its stability by removing the K48 ubiquitin chain from MYH9, thereby mediating the microglia polarization signaling pathway to mediate microglia homeostasis. Taken together, our study reveals a specific role of microglial YOD1 in mediating microglia homeostasis and AD pathology, which provides a potential strategy for targeting microglia to treat AD.

ObjectiveThe aim of this study was to investigate the prophylactic effects of caloric restriction (CR) on lipopolysaccharide (LPS)-induced septic cardiomyopathy (SCM) and to elucidate the mechanisms underlying the cardioprotective actions of CR. This research aims to provide innovative strategies and theoretical support for the prevention of SCM. MethodsA total of forty-eight 8-week-old male C57BL/6 mice, weighing between 20-25 g, were randomly assigned to 4 distinct groups, each consisting of 12 mice. The groups were designated as follows: CON (control), LPS, CR, and CR+LPS. Prior to the initiation of the CR protocol, the CR and CR+LPS groups underwent a 2-week acclimatization period during which individual food consumption was measured. The initial week of CR intervention was set at 80% of the baseline intake, followed by a reduction to 60% for the subsequent 5 weeks. After 6-week CR intervention, all 4 groups received an intraperitoneal injection of either normal saline or LPS (10 mg/kg). Twelve hours post-injection, heart function was assessed, and subsequently, heart and blood samples were collected. Serum inflammatory markers were quantified using enzyme-linked immunosorbent assay (ELISA). The serum myocardial enzyme spectrum was analyzed using an automated biochemical instrument. Myocardial tissue sections underwent hematoxylin and eosin (HE) staining and immunofluorescence (IF) staining. Western blot analysis was used to detect the expression of protein in myocardial tissue, including inflammatory markers (TNF-α, IL-9, IL-18), oxidative stress markers (iNOS, SOD2), pro-apoptotic markers (Bax/Bcl-2 ratio, CASP3), and SIRT3/SIRT6. ResultsTwelve hours after LPS injection, there was a significant decrease in ejection fraction (EF) and fractional shortening (FS) ratios, along with a notable increase in left ventricular end-systolic diameter (LVESD). Morphological and serum indicators (AST, LDH, CK, and CK-MB) indicated that LPS injection could induce myocardial structural disorders and myocardial injury. Furthermore, 6-week CR effectively prevented the myocardial injury. LPS injection also significantly increased the circulating inflammatory levels (IL-1β, TNF-α) in mice. IF and Western blot analyses revealed that LPS injection significantly up-regulating the expression of inflammatory-related proteins (TNF-α, IL-9, IL-18), oxidative stress-related proteins (iNOS, SOD2) and apoptotic proteins (Bax/Bcl-2 ratio, CASP3) in myocardial tissue. 6-week CR intervention significantly reduced circulating inflammatory levels and downregulated the expression of inflammatory, oxidative stress-related proteins and pro-apoptotic level in myocardial tissue. Additionally, LPS injection significantly downregulated the expression of SIRT3 and SIRT6 proteins in myocardial tissue, and CR intervention could restore the expression of SIRT3 proteins. ConclusionA 6-week CR could prevent LPS-induced septic cardiomyopathy, including cardiac function decline, myocardial structural damage, inflammation, oxidative stress, and apoptosis. The mechanism may be associated with the regulation of SIRT3 expression in myocardial tissue.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

Objective:To evaluate the clinical equivalence between a domestic calcipotriol/betamethasone dipropionate ointment and the originator product in the treatment of stable plaque psoriasis.Methods:A multicenter, randomized, double-blind, three-arm, parallel-group, active- and placebo-controlled study was conducted, and 449 patients aged 18 - 65 years with stable plaque psoriasis were enrolled from 25 hospitals (such as the First Affiliated Hospital of China Medical University). Eligible patients had a baseline physician's global assessment (PGA) score of ≥ 3 points, baseline body surface area (BSA) involvement of 5% - 30%, and a target lesion psoriasis area and severity index (TL-PASI) for plaque elevation of ≥ 3 points. Participants were randomly assigned in a 2:2:1 ratio to the test group ( n = 179), reference group ( n = 180), and placebo group ( n = 90), and applied the domestic calcipotriol/betamethasone dipropionate ointment, originator product, and ointment base respectively, once daily in the evening for 4 weeks. Efficacy and safety were assessed at weeks 1, 2, and 4. The primary efficacy endpoints were the treatment success rates and clinical success rates in each group at week 4. The per-protocol set (PPS) was used for the primary efficacy analysis, and the intention-to-treat (ITT) set for supplementary efficacy analysis. Equivalence between the test and reference preparations was tested using the Cochran-Mantel-Haenszel method adjusted for randomization strata. Superiority of the test and reference preparations over the placebo was also tested. Measurement data were compared among the 3 groups using analysis of variance or non-parametric tests, while treatment success rates, clinical success rates, and incidence rates of adverse reactions were compared using the chi-square test. Results:The ITT, PPS, and safety sets included 447, 420, and 448 patients, respectively. In the ITT set, patients were aged 43.6 ± 12.8 years, including 320 (71.6%) males and 127 (28.4%) females, and the disease duration was 11.21 ± 9.05 years; 316 (70.7%) had a PGA score of 3 points and 131 (29.3%) had a PGA score of 4 - 5 points. No significant differences in the baseline characteristics (including age, sex, disease duration and disease severity) were observed among the 3 groups (all P > 0.05). Based on the PPS analysis, the treatment success rates were 57.9% (99/171) in the test group, 50.3% (86/171) in the reference group, and 7.7% (6/78) in the placebo group, and the clinical success rates were 57.9% (99/171), 50.3% (86/171), and 10.3% (8/78), respectively; both the test and reference groups were superior to the placebo group in both treatment and clinical success rates (all P < 0.001) ; the rate differences for treatment success (90% confidence interval [ CI]: -1.3% - 16.4%) and clinical success (90% CI: -1.3% - 16.3%) between the test and reference groups were entirely within the pre-defined equivalence margin (-20% - 20%). Subgroup analyses by baseline PGA scores: for patients with a baseline PGA score of 3 points, the treatment success rates in the test, reference, and placebo groups were 60.8% (73/120), 52.1% (62/119), and 11.1% (6/54), respectively, and the corresponding clinical success rates were 61.7% (74/120), 53.8% (64/119), and 13% (7/54), respectively; the test and reference groups did not differ significantly in treatment or clinical success rates (both P > 0.05), but both showed higher success rates than the placebo group (all P < 0.001) ; the results of statistical comparisons among the 3 groups in patients with a baseline PGA score of 4 - 5 points were consistent with those observed in patients with a baseline PGA score of 3 points. The percentage reductions in PGA and TL-PASI scores from baseline to weeks 1, 2, and 4 showed significant differences among the 3 groups, which were significantly higher in the test and reference groups than in the placebo group (all P < 0.001), but did not differ between the test and reference groups (all P > 0.05). The primary adverse reactions were local skin reactions, such as pruritus, pain, and erythema. The incidence rates of adverse reactions were 8.9% (16/179) in the test group, 7.3% (13/179) in the reference group, and 7.8% (7/90) in the placebo group, with no significant difference among the 3 groups ( P > 0.05) . Conclusions:The domestic calcipotriol/betamethasone dipropionate ointment demonstrated clinical equivalence to the originator product in the treatment of stable plaque psoriasis, and the two agents exhibited comparable efficacy for patients with varying degrees of disease severity, and were comparable in the speed and degree of clinical improvement, with similar favorable safety profiles.