Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

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 To compare the risk of pneumonitis and interstitial lung disease （ILD） associated with different antibody-drug conjugates （ADC） in the treatment of breast cancer. METHODS CNKI， VIP， PubMed， Embase and other Chinese and English databases， and ClinicalTrials.gov were searched from the inception to June 15， 2025. Randomized controlled trials （RCT） about pneumonitis and ILD associated with ADC （T-DM1， T-DXd， SG， Dato-DXd， SHR-A1811，ARX788， and T-Duo） in the treatment of breast cancer were included. After literature screening， data extraction， and quality assessment， a network meta-analysis was conducted using Stata 17.0 software， and the surface under the cumulative ranking curve（SUCRA） of all interventions were ranked. RESULTS A total of 19 RCTs involving 10 556 patients were included. The overall incidence of pneumonitis with ARX788 and T-DXd was significantly higher than that with T-DM1， T-DM1 plus TPC（T-DM1combined with pertuzumab or atezolizumab）， TPC（treatment of primary care）， and SG （ P ＜0.05）， for grade 1-2 pneumonitis， ARX788 and T-DXd showed significantly higher incidence than T-DM1， T-DM1 plus TPC， and TPC （ P ＜0.05）. For both indicators， ARX788 and T-Duo were ranked as the top two by SUCRA. For the incidence of grade ≥3 pneumonitis， T-DXd and T-DM1 were significantly higher than SG （ P ＜0.05）， T-Duo and Dato-DXd were ranked as the top two by SUCRA. For overall incidence of ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， TPC， and SG （ P ＜0.05）， for the incidence of grade 1-2 ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， and TPC （ P ＜0.05）， for the incidence of grade ≥3 ILD， ARX788 was significantly higher than TPC （ P ＜0.05）. For three indicators above， ARX788 and T-DXd combined with pertuzumab were ranked as the top two by SUCRA. CONCLUSIONS Compared with other ADCs， ARX788 and T-Duo are associated with a higher risk of pneumonitis and ILD in patients with breast cancer.

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

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.

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*