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 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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To analyze the clinical and ultrasonic features of breast invasive ductal carcinoma in young women patients,and improve the accuracy of ultrasonic diagnosis of breast invasive ductal carcinoma in young patients.Methods:A retrospective study was conducted on patients with invasive ductal carcinoma who underwent surgery in the Second Hospital of Shandong University from December 2015 to June 2023,with complete clinical data,preopera-tive ultrasonography and postoperative pathology.All patients were divided into two groups:young group(≤35 year-old)and control group(>35 year-old).Univariate t-test and multivariate Logistic regression analyses were used to assess the factors.Results:There was a statistical difference between the young group and the control group in the accuracy of ultrasound diagnosis(young group 81%vs control group 94%,χ2=13.082,P=0.001).Compared with the control group,the young group had a shorter disease history,a higher proportion of multiple masses,posterior echo changes and hypo-vascular lesions(P<0.05).However,there was no statistical difference in family history of breast cancer,other cancer family history,clinical symptoms,size,lesion classification,palpation,location,aspect ratio,focus echo,shape,edge per-formance,bright ring sign,calcification characteristics,ER,PR,HER-2 and Ki67(P>0.05).Conclusion:The incidence rate of young breast IDC is low,while the misdiagnosis rate of ultrasound is relatively high.More attention should be paid when the patient has a short history,multiple masses,changes in the posterior echo and less lesion blood supply.

Objective:To investigate the effects of individual versus connected microdroplet culture modes in time-lapse (TL) incubators on embryo development parameters and pregnancy outcomes in patients undergoing whole embryo culture to blastocyst stage.Methods:Using a retrospective cohort study, clinical data from 3 507 fresh blastocyst transfer cycles were analyzed. These cycles involved patients who underwent assisted reproductive technology treatment with whole embryo culture to blastocyst stage at the Reproductive Medical Center of Northwest Women's and Children's Hospital between January 2019 and December 2023. Based on different culture modes, patients were divided into two groups, connected group ( n=2 446, using connected microdroplet culture) and individual group ( n=1 061, using individual microdroplet culture). Baseline characteristics, embryo development parameters, pregnancy outcomes, and neonatal outcomes were compared between the two groups. Generalized linear models (GLM) were used to adjust for confounding factors and analyze the effect of culture mode. Results:Embryo development assessment showed the day 3 (D3) high-quality embryo rate in the connected group [60.12% (12 136/20 187)] was significantly lower than that in the individual group [63.62% (4 705/7 395), P<0.001], whereas the high-quality blastocyst formation rate [34.93% (7 052/20 187)] and the available blastocyst formation rate [56.07% (11 319/20 187)] were both significantly higher than those in the individual group [33.08% (2 446/7 395), P=0.004; 51.45% (3 805/7 395), P<0.001], with statistically significant differences. The implantation rate [67.40% (1 774/2 632)], the clinical pregnancy rate [70.20% (1 717/2 446)], and the live birth rate [60.66% (1 469/2 446)] in the connected group were all significantly higher than those in the individual group [63.40% (724/1 142), P=0.017; 66.73% (708/1 061), P=0.041; 55.89% (593/1 061), P=0.021], with statistically significant differences. Neonatal outcomes showed no statistically significant difference between the two groups (all P>0.05). After adjusting for confounding factors using GLM, connected culture was an independent influencing factor for D3 high-quality embryo rate (a MD=-0.017, 95% CI: -0.034-0.000, P=0.046), high-quality blastocyst formation rate (a MD=-0.020, 95% CI: 0.002-0.037, P=0.026), available blastocyst formation rate (a MD=0.032, 95% CI: 0.015-0.048, P<0.001), live birth rate (a OR=1.182, 95% CI: 1.006-1.388, P=0.042). However, it had no effect on D3 available embryo rate, clinical pregnancy rate, or early miscarriage rate (all P>0.05). Conclusion:In TL incubator systems, individual and connected microdroplet culture modes exert different effects at various stages of embryo development. Individual microdroplet culture can significantly enhance cleavage-stage embryo quality, whereas the connected microdroplet culture was more beneficial for enhancing the blastocyst formation rate and quality, ultimately improving the live birth rate without increasing neonatal risks.

Objective:To construct an integrated management model for early screening and diagnosis of PCa based on the In-novative Care for Chronic Conditions Framework(ICCC)and the 1+1 contract-based tiered diagnosis and treatment system(TDTS)in China.Methods:Based on the 1+1 contract-based TDTS platform,we conducted PCa screening for the male residents aged 60 years and above during health check-ups in Pujin Community Health Center from January 1,2023 to December 31,2023.For those with abnormal total prostate-specific antigen(tPSA)≥4 μg/L,we promptly referred them to higher-level hospitals for further diagno-sis and treatment via the two-way referral green channel platform and information sharing service using the 1+1 contract model.We further analyzed the relevant data on screening and diagnosis.Results:A total of 4 080 males aged 71.39±5.059 years received PCa screening from January to December 2023.PSA screening was performed in 43.96％of the male residents,revealing 654 cases of PSA abnormality,with a PSA positivity rate of 16.03％,which was higher than that found in the previous large-scale PCa screenings in other regions of China.Among the males with PSA abnormality,292(44.65％)expressed their willingness for medical referral,while the others did not seek further medical attention for reasons of being asymptomatic,low awareness of the disease,no accompany for medical visits,and concerns about further costs of diagnosis and treatment.Prostate biopsy was recommended to 154 cases after further examinations,which was accepted by 92(59.74％).Fifty-eight cases were diagnosed with Pa,and thedetection rate reached 63.04％.Conclusion:The integrated management model for PSA examination-based early screening and diagnosis of PCa using the 1+1 contract-based TDTS platform is plays a significant role in enhancing peoples awareness and knowledge of PCa and improving the early detection rate of the malignancy.

Objective To investigate the efficacy of varying doses of methylprednisolone(MP)on mice with acute exacerbations of chronic obstructive pulmonary disease(AECOPD)induced with influenza A virus(IAV).Methods Mouse model of COPD was established using LPS combined with smoking for 12 weeks,and then these COPD mice were treated with administration of 40 μL IAV via nasal drip to establish a AECOPD model.A total of 15 AECOPD mice were randomly divided into low-,medium-and high-dose MP groups,oseltamivir group and blank group.The body weight and survival time were monitored within 10 d after IAV infection.On days 1,3,and 5 post-treatment,lung function was assessed using whole-body plethysmography(WBP),inflammatory factors in bronchoalveolar lavage fluid(BALF)were quantified with ELISA,viral titers in BALF were determined using plaque assays,and colony-forming units were evaluated with blood agar plates.Immunofluorescence analysis:① Pulmonary immunofluorescence assay:Mice were randomly categorized into(n=4):LPS 1-day group,LPS 3-day group,and LPS+MP treatment group.All groups received an initial dose of LPS via atomization;subsequently,the LPS+MP treatment group received a single gavage dose of MP.Lung tissues were harvested from the 1-day LPS group on 1 d post-treatment,and from the 3-day LPS and LPS+MP groups on 3 d for immunofluorescence staining.② Cellular immunofluorescence assay:Mouse bone marrow neutrophils were classified into blank control(no intervention),LPS stimulation(LPS group),MP intervention with LPS stimulation(LPS+MP group),and MP intervention alone(MP group).The above cells were collected in 4 h after corresponding interventions for subsequent cellular immunofluorescence analysis.Results ①The medium-dose MP group demonstrated the most significant improvement in survival rate,weight recovery,and lung function when compared to other groups(P＜0.05).② Treatment of medium-dose MP obviously reduced the levels of IL-6 and neutrophil extracellular traps(NETs)(P＜0.05),while,elevated inflammatory factors and NETs were observed in the high-dose MP group on day 5 post-treatment.③ Notable decline in the lung injury score was found in the medium-dose MP group than the other groups(P＜0.05).④The high-dose MP group exhibited substantial bacterial proliferation and delayed viral clearance since day 5 after treatment.Conclusion Medium-dose MP shows best efficacy in treatment of IAV-induced AECOPD,and the dose neither delays viral clearance nor increases the risk of bacterial infection following viral infection.

The rapid and non-destructive detection of constituent content of fresh tea leaves shows an important reference value for quality identification of tea.Visible near infrared(Vis-NIR)spectroscopy has been used for qualitative and quantitative analysis of chemical components in plant samples with the advantages such as simple,rapid and non-destructive detection.In this study,residual attention convolutional neural network(RACNN)was used to predict the internal constituent content of fresh tea leaves.Firstly,the reflectance spectral data of the samples in the Vis-NIR band range and the constituent contents of gallic acid(GA),gallocatechin(GC),epigallocatechin(EGC),and epigallocatechin gallate(ECG)in fresh tea leaves were collected.Based on the preprocessing of the spectral data,the contents of the four components were predicted using a partial least squares regression(PLSR)model,and the optimal preprocessing was determined.Subsequently,the characteristic bands were extracted using the random forest(RF)algorithm.Finally,the performances of PLSR,convolutional neural network(CNN)and RACNN models were compared.The results showed that for GA,the RACNN model worked best with a validation set coefficient of determination(R2)of 0.946 and a root mean square error of the prediction set(RMSEP)of 1.173;for GC,the RACNN model works best with a validation set R2 of 0.928 and RMSEP of 6.081;for EGC,the RACNN model works best with a validation set R2 of 0.891 and a RMSEP of 15.197;for ECG,the RACNN model worked best with a validation set R2 of 0.878 and a RMSEP of 7.837.The RACNN model established by Vis-NIR spectroscopy combined with chemometrics could realize the accurate detection of the contents of components in fresh tea.

Digital polymerase chain reaction(dPCR)enables absolute quantitative detection of nucleic acid samples.Since the quantitative upper and lower limits of detectable samples mainly depend on the volume and number of single droplets,the abundance of the sample to be tested,the volume of single droplets,and the number of droplets need to be adapted.For samples with unknown abundance,repeated adjustment of droplet size is not allowed.In this study,a one-step double-volume droplet generation method was proposed,and a double-volume droplet microfluidic chip was developed to verify the quantitative detection capability of the chip using a duck-derived kit.The results showed that the droplets with different volumes had different quantitative capabilities.Large-volume droplets had higher reliability for low-abundance sample concentrations,while small-volume droplets had advantages in detecting high-abundance sample concentrations.The double-volume droplets produced by the double-volume droplet microfluidic chip proposed in this study greatly improved the reliability of quantitative capabilities,and had broad application prospects in detection of precious nucleic acid samples with unknown abundance in the field of microfluidic PCR.