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 analyze the characteristics of injury surveillance cases among the elderly in Ningbo City, Zhejiang Province from 2014 to 2023, so as to provide the basis for formulating targeted injury intervention measures. Methods: Injury surveillance cases aged ≥60 years were collected from seven injury sentinel hospitals in Ningbo City through the Zhejiang Provincial Chronic Disease Surveillance Information Management System from 2014 to 2023. Population distribution, temporal distribution, injury circumstances, and clinical characteristics were described. Results: A total of 67 259 injury surveillance cases among the elderly were reported in Ningbo City from 2014 to 2023, including 32 159 males (47.81%) and 35 100 females (52.19%). The median age was 68.00 (interquartile range, 14.00) years. The three months with a higher number of cases were December (6 271 cases, 9.32%), August (6 226 cases, 9.26%) and October (6 221 cases, 9.25%). The primary causes of injury were falls (25 276 cases, 37.58%), stabs (12 250 cases, 18.21%), and sprains (11 815 cases, 17.57%). The injury occurred mainly in homes (44 975 cases, 66.87%) and streets/urban areas (16 174 cases, 24.05%). The predominant activities at the time of injury were leisure activities (28 801 cases, 42.82%) and household chores (23 647 cases, 35.16%). The proportions of falls as the cause of injury and injuries occurring at home among females and people aged 80 years and above were relatively high. The predominant sites of injury were upper limbs (23 354 cases, 34.72%) and lower limbs (20 343 cases, 30.25%). The predominant nature of injury were soft tissue injuries (43 345 cases, 64.44%) and bone and joint injuries (22 042 cases, 32.77%). Injuries were primarily mild and moderate in severity, with 46 391 cases (68.97%) and 20 205 cases (30.04%), respectively. The proportion of bone and joint injuries, moderate in injuries among females and people aged 80 years and above was relatively high. Conclusions The main causes of injury surveillance cases among the elderly in Ningbo City from 2014 to 2023 were falls and stabs, and the injuries occurred mainly in homes and streets/urban areas. Female and elderly people have a higher risk of injury.

Osteosarcoma (OS) is the most prevalent primary malignant bone tumor affecting children and adolescents. Despite ongoing research efforts, the 5-year survival rate has remained stagnant for many years, highlighting the critical need for novel drug development to enhance current treatment protocols. Ziyuglycoside II (ZYG II), a triterpenoid saponin extracted from S. officinalis, has recently demonstrated antitumor properties. This study evaluates the antitumor effect of ZYG II on osteosarcoma and elucidates its mechanism of action through the co-regulation of p53 and estrogen-related receptor gamma (ESRRG), which inhibits disease progression. The research employs in vitro experiments using multiple established osteosarcoma cell lines, as well as in vivo studies utilizing a nude mouse model of orthotopic xenograft osteosarcoma. Additionally, ESRRG shRNA was used to construct stable ESRRG-reducing OS cell lines to investigate the molecular mechanism by which ZYG II exerts its anti-osteosarcoma effects through the co-regulation of ESRRG and p53. Results indicate that ZYG II administration led to decreased OS cell viability and reduced tumor volumes. Furthermore, cell cycles were arrested at the G₀/G₁ phase, while the proportion of apoptotic cells increased. Expression of p53, ESRRG, p21, Bax, Cleaved Caspase-9, and Cleaved Caspase-3 proteins increased, while expression of CDK4, Cyclin D1, and Bcl-2 proteins decreased. Multiple ZYG II and ESRRG docking patterns were simulated through molecular docking. Comparing the pharmacodynamic response of ZYG II to OS cell lines with reduced ESRRG and normal expression demonstrated that ZYG II inhibits osteosarcoma progression, induces cell cycle arrest, and promotes cell apoptosis through the coordination of p53 and ESRRG. In conclusion, ZYG II inhibits osteosarcoma progression, leads to cell cycle arrest, and promotes cell apoptosis through synergistic regulation of p53 and ESRRG.
Osteosarcoma/physiopathology* ; Tumor Suppressor Protein p53/genetics* ; Humans ; Animals ; Saponins/chemistry* ; Bone Neoplasms/physiopathology* ; Signal Transduction/drug effects* ; Cell Line, Tumor ; Mice, Nude ; Mice ; Apoptosis/drug effects* ; Receptors, Estrogen/genetics* ; Mice, Inbred BALB C ; Female ; Male ; Xenograft Model Antitumor Assays

Objective To analyze the characteristics of HIV-1 pretreatment drug resistance(PDR)and molecular transmission networks in Yubei District,Chongqing,providing evidence for targeted interventions.Methods Using a cross-sectional design,plasma samples were collected from HIV/AIDS patients receiving antiretroviral therapy(ART)in Yubei District from January 2022 to December 2023.Pol gene fragments were extracted and amplified for HIV-1 genotyping and drug resistance analysis.Molecular transmission networks were constructed based on genetic distance calculations.Results Among 478 HIV-1 pol sequences,eight geno-types were identified:with CRF07_BC(60.4%,289/478),CRF08_BC(15.5%,74/478),CRF01_AE(11.7%,56/478),and CRF85_BC(5.9%,28/478).The overall PDR rate was 6.3%(30/478),with resistance to nucleoside reverse transcriptase inhibitors(NRTIs)and non-nucleoside reverse transcriptase inhibitors(NNRTIs)at 1.7%(8/478)and 5.2%(25/478),respectively.No protease inhibitor(PI)resistance was de-tected.The molecular network included 177 cases(37.0%network entry rate),forming 53 clusters with 198 connections.Cluster sizes ranged from 2 to 17 nodes,and 75.3%(149/198)of connections were associated with five subdistricts/towns:Shuanglonghu Street,Huixing Street,Luoqi Town,Gulu Town,and Baoshenghu Street.Conclusion HIV-1 genotypes in Yubei District exhibit diversity and complexity,with moderate PDR prevalence.Regional clustering of transmission networks suggests the need for enhanced molecular surveil-lance and targeted interventions based on analytical findings.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

Investigating the correlation between micronucleus formation and male infertility has the potential to improve clinical diagnosis and deepen our understanding of pathological progression. Our study enrolled 2252 male patients whose semen was analyzed from March 2023 to July 2023. Their clinical data, including semen parameters and age, were also collected. Genetic analysis was used to determine whether the sex chromosome involved in male infertility was abnormal (including the increase, deletion, and translocation of the X and Y chromosomes), and subsequent semen analysis was conducted for clinical grouping purposes. The participants were categorized into five groups: normozoospermia, asthenozoospermia, oligozoospermia, oligoasthenozoospermia, and azoospermia. Patients were randomly selected for further study; 41 patients with normozoospermia were included in the control group and 117 patients with non-normozoospermia were included in the study group according to the proportions of all enrolled patients. Cytokinesis-block micronucleus (CBMN) screening was conducted through peripheral blood. Statistical analysis was used to determine the differences in micronuclei (MNi) among the groups and the relationships between MNi and clinical data. There was a significant increase in MNi in infertile men, including those with azoospermia, compared with normozoospermic patients, but there was no significant difference between the genetic and nongenetic groups in azoospermic men. The presence of MNi was associated with sperm concentration, progressive sperm motility, immotile spermatozoa, malformed spermatozoa, total sperm count, and total sperm motility. This study underscores the potential utility of MNi as a diagnostic tool and highlights the need for further research to elucidate the underlying mechanisms of male infertility.
Humans ; Male ; Infertility, Male/genetics* ; Adult ; Micronucleus Tests ; Semen Analysis ; Oligospermia/genetics* ; Azoospermia/genetics* ; Chromosome Aberrations ; Sperm Count ; Micronuclei, Chromosome-Defective ; Middle Aged

OBJECTIVE: To illustrate the role of dehydrocorydaline (DHC) in chronic constriction injury (CCI)-induced neuropathic pain and the underlying mechanism. METHODS: C57BL/6J mice were randomly divided into 3 groups by using a random number table, including sham group (sham operation), CCI group [intrathecal injection of 10% dimethyl sulfoxide (DMSO)], and CCI+DHC group (intrathecal injection of DHC), 8 mice in each group. A CCI mouse model was conducted to induce neuropathic pain through ligating the right common sciatic nerve. On day 14 after CCI modeling or sham operation, mice were intrathecal injected with 5 µL of 10% DMSO or 10 mg/kg DHC (5 µL) into the 5th to 6th lumbar intervertebral space (L5-L6). Pregnant ICR mice were sacrificed for isolating primary spinal neurons on day 14 of embryo development for in vitro experiment. Pain behaviors were evaluated by measuring the paw withdrawal mechanical threshold (PWMT) of mice. Immunofluorescence was used to observe the activation of astrocytes and microglia in mouse spinal cord. Protein expressions of inducible nitric oxide synthase (iNOS), tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), phosphorylation of N-methyl-D-aspartate receptor subunit 2B (p-NR2B), and NR2B in the spinal cord or primary spinal neurons were detected by Western blot. RESULTS: In CCI-induced neuropathic pain model, mice presented significantly decreased PWMT, activation of glial cells, overexpressions of iNOS, TNF-α, IL-6, and higher p-NR2B/NR2B ratio in the spinal cord (P<0.05 or P<0.01), which were all reversed by a single intrathecal injection of DHC (P<0.05 or P<0.01). The p-NR2B/NR2B ratio in primary spinal neurons were also inhibited after DHC treatment (P<0.05). CONCLUSION An intrathecal injection of DHC relieved CCI-induced neuropathic pain in mice by inhibiting the neuroinflammation and neuron hyperactivity.
Animals ; Neuralgia/etiology* ; Mice, Inbred C57BL ; Analgesics/pharmacology* ; Neuroinflammatory Diseases/pathology* ; Constriction ; Male ; Receptors, N-Methyl-D-Aspartate/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; Mice, Inbred ICR ; Microglia/pathology* ; Spinal Cord/drug effects* ; Female ; Mice ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Constriction, Pathologic/complications* ; Interleukin-6/metabolism* ; Astrocytes/metabolism* ; Chronic Disease ; Neurons/metabolism*

Objective:Traditional salivary gland surgery involves incisions in the visible facial and cervical regions, leaving postoperative scars that affect cosmesis. This study aims to investigate the clinical efficacy, safety, and application value of robot-assisted endoscopic resection of benign submandibular and parotid gland lesions via a postauricular approach, while clarifying its advantageous differences compared with endoscopic surgery. Methods:Clinical data of 23 patients who underwent robot-assisted endoscopic surgery via a postauricular approach（11 parotid gland cases and 12 submandibular gland cases） from January 2017 to February 2025 were retrospectively analyzed. Meanwhile, A matched control group of patients who received postauricular endoscopic surgery during the same period was selected as the control group in a 1∶1 ratio（11 parotid gland cases and 12 submandibular gland cases）. Indicators such as operation time, intraoperative blood loss, complications, and postoperative aesthetic satisfaction scores（Numeric Satisfaction Scale, NSS） were collected and compared between the two groups. The inclusion criteria were limited to benign lesions of the parotid superficial lobe（diameter ≤5 cm, without deep lobe involvement） and benign submandibular gland lesions（diameter ≤4 cm, without extension through the mylohyoid muscle）. Results:All robot-assisted surgeries were successfully completed without conversion to open surgery. In the robot group, there were 7 male patients（mean age 39.5 years） and 16 female patients（mean age 35.9 years）. For parotid gland surgeries, the mean operation time was （114.00±38.35） minutes. For submandibular gland surgeries, the mean operation time was（140.00±30.75） minutes.Temporary facial paralysis occurred in 0 of patients after robotic submandibular gland surgery （vs.8% in the endoscopic group） and 18% after robotic parotid gland surgery （vs.27 % in the endoscopic group）,all of which resolved within 1 month, with no occurrence of salivary fistula or infection. Patients had high aesthetic satisfaction（NSS scores: 8.90±1.20 for parotid surgeries and 9.00±0.70 for submandibular surgeries）. No tumor recurrence was observed during the 8-77 month follow-up period. Conclusion:Robot-assisted endoscopic salivary gland surgery via a postauricular approach is safe and feasible. With three-dimensional high-definition visualization and precise mechanical manipulation, it outperforms traditional endoscopic surgery in reducing blood loss, lowering the risk of nerve injury, and achieving long-term cosmetic outcomes. It is particularly suitable for young patients and cases with benign lesions of the parotid superficial lobe or submandibular gland that have high aesthetic demands. However, this surgical approach is not suitable for deep parotid lobe tumors, and its long-term efficacy requires verification through large-sample studies.
Humans ; Robotic Surgical Procedures/methods* ; Retrospective Studies ; Endoscopy/methods* ; Submandibular Gland/surgery* ; Parotid Gland/surgery* ; Female ; Male ; Operative Time ; Salivary Glands/surgery* ; Adult ; Middle Aged

Photodynamic immunotherapy is a promising strategy for cancer treatment. However, the dysfunctional tumor vasculature results in tumor hypoxia and the low efficiency of drug delivery, which in turn restricts the anticancer effect of photodynamic immunotherapy. In this study, we designed photosensitive lipid nanoparticles. The synthesized PFBT@Rox Lip nanoparticles could produce type I/II reactive oxygen species (ROS) by electron or energy transfer through PFBT under light irradiation. Moreover, this nanosystem could alleviate tumor hypoxia and promote vascular normalization through Roxadustat. Upon irradiation with white light, the ROS produced by PFBT@Rox Lip nanoparticles in situ dysregulated calcium homeostasis and triggered endoplasmic reticulum stress, which further promoted the release of damage-associated molecular patterns, enhanced antigen presentation, and stimulated an effective adaptive immune response, ultimately priming the tumor microenvironment (TME) together with the hypoxia alleviation and vessel normalization by Roxadustat. Indeed, in vivo results indicated that PFBT@Rox Lip nanoparticles promoted M1 polarization of tumor-associated macrophages, recruited more natural killer cells, and augmented infiltration of T cells, thereby leading to efficient photodynamic immunotherapy and potentiating the anti-primary and metastatic tumor efficacy of PD-1 antibody. Collectively, photodynamic immunotherapy with PFBT@Rox Lip nanoparticles efficiently program TME through the induction of immunogenicity and oxygenation, and effectively suppress tumor growth through immunogenic cell death and enhanced anti-tumor immunity.