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 investigate the distribution characteristics of Oncomelania hupensis snails in Yunnan Province fol-lowing interruption of schistosomiasis transmission, so as to provide the evidence for assessing the risk of schistosomiasis transmission and scientifically formulating the schistosomiasis surveillance program. Methods According to the requirements of the National Schistosomiasis Surveillance Scheme (2020 Edition), O. hupensis snail surveillance data were collected from 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province from 2020 to 2024, including area of snail survey, area of snail habitats, area of re-emerging snail habitats, number of frames surveyed, number of frames with O. hupensis snails, number of O. hupensis snails captured, and number of living snails, and the occurrence of frames with snails and mean density of living snails were calculated. Changes in snail status over the 5-year period from 2020 to 2024 and the differences in snail distributions specified by epidemic intensity, environmental type, and vegetation type were analyzed. Results The areas of snail survey increased from 1 727.96 hm² in 2020 to 3 894.45 hm² in 2024 (peak) across 18 schistosomiasis-endemic counties (cities, districts) in Yunnan Province during the period from 2020 through 2024. The areas of snail habitats increased from 70.36 hm² in 2020 to a peak in 2023 (172.04 hm²), followed by a reduction to 132.36 hm² in 2024, and the areas of re-emerging snail habitats increased from 42.71 hm² in 2020 to a peak in 2022 (78.43 hm²), followed by a reduction to 40.21 hm² in 2024. The occurrence of frames with snails and mean density of living snails increased from 1.24% (3 025/244 404) and (0.033 2 ± 0.038 7) snails/0.1 m² in 2020 to peaks at 2.03% (6 231/307 563) and (0.066 9 ± 0.068 4) snails/0.1 m² in 2023, followed by reductions to 1.04% (5 829/559 941) and (0.032 6 ± 0.057 7) snails/0.1 m² in 2024, respectively. There was a significant difference in the occurrence of frames with snails over the 5-year study period (χ² = 1 962.95, P < 0.05), and the occurrence of frames with snails reduced by 48.71% in 2024 relative to in 2023 (χ² = 1 411.05, P < 0.005); however, there was no significant difference in the mean density of living snails over the 5 years (H = 5.310, P > 0.05). There were significant differences in the occurrence of frames with snails (χ² = 481.27, P < 0.05) and mean density of living snails (H = 6.872, P < 0.05) in schistosomiasis-endemic areas with different epidemic intensities. The occurrence of frames with snails (χ² = 25.32 and 38.70, both P values < 0.017) and mean density of living snails (Z = 28.55 and 49.96, both P values < 0.017) were higher in schistosomiasis transmission-interrupted and eliminated areas with snails than in schistosomiasis-eliminated areas without snails, and the occurrence of frames with snails (χ² = 453.54, P < 0.017) and mean density of living snails (Z = −56.97, P < 0.017) were higher in schistosomiasis-eliminated areas with snails than in schistosomiasis transmission-interrupted areas with snails. O. hupensis snails were mainly distributed in paddy fields, dry farmlands and ditches; however, the occurrence of frames with snails (13.40%, 424/3 164) and mean density of living snails [(0.252 8 ± 0.158 7) snails/0.1 m²] were higher in ponds/weirs than in other types of environments (both P values < 0.05). Rice, dry farmland crops and weeds were main vegetations in which O. hupensis snails were distributed, and the occurrence of frames with snails (2.29%, 7 111/310 140) and mean density of living snails [(0.072 3 ± 0.018 9) snails/0.1 m²] were higher in weeds than in other types of environments (both P values < 0.05). Conclusions O. hupensis snails have been effectively controlled in Yunnan Province following implementation of integrated schistosomiasis control measures; however, there are still risk factors for schistosomiasis transmission, including reduced attention to schistosomiasis control and snail re-emergence. Improved control efforts and surveillance system construction and timely identification of risk factors of snail status and timely management are recommended to ensure the achievement of the target of schistosomiasis elimination as scheduled.

Objective To investigate the prevalence of Schistosoma japonicum infections in wild murines in schistosomiasisendemic areas of Yunnan Province, so as to provide the evidence for improving the schistosomiasis surveillance and early warning capability and implementing precise interventions in the province. Methods A total of 56 natural villages were sampled from 14 schistosomiasis-endemic counties (cities, districts) in Yunnan Province as surveillance sites from 2024 to 2025. Wild murines were captured using traps at night and characterized for species. Liver samples were collected from wild murines, S. japonicum eggs and miracidia were simultaneously detected using liver tissue compression microscopy, liver tissue homogenate microscopy, and liver tissue homogenate hatching. In addition, stool samples were collected from wild murine rectum, with S. japonicum eggs detected using a modified Kato-Katz thick smear technique and S. japonicum miracidia detected using the hatching test with nylon gauzes. Results A total of 15 577 valid murine traps were recovered, and 891 wild murines belonging to 16 species were captured, with a capture rate of 5.72%(891/15 577). The captured wild murines were predominantly districted in paddy fields, dry lands, ditches, ponds and marshlands, with Apodemus chevrieri, Rattus norvegicus, Crocidura attenuata, R. rattus sladeni, R. flavipectus, and Eothenomys miletus as dominant species. No S. japonicum eggs or miradicia were in laboratory; however, other parasites were identified in 25 wild murines. The prevalence rates of Schistosoma sinensis, Capillaria hepatica and Hymenolepis nana were 2.24% (20/891), 0.90% (8/891) and 0.56% (5/891), and the prevalence of S. sinensis and C. hepatica co-infection was 0.90% (8/891), respectively. Conclusions S. sinensis, C. hepatica and H. nana are predominant parasite species in wild murines in schistosomiasis-endemic areas of Yunan Province. No S. japonicum infection was detected during the study period; however, there is still a risk of wild murines as a potential source of infection for schistosomiasis transmission. Continuous intensified surveillance of S. japonicum infections in wild murines is a critical programme in schistosomiasis surveillance and early warning in Yunnan Province.

Objective: To examine the association of physical activity with cognitive function and mental health among primary school students based on latent subgroup identification and dose response modeling, and to clarify cognitive-psychological profiles and the protective role of physical exercise, so as to provide evidence based support for physical exercise promoting mental health among primary school students. Methods: A study was conducted among 546 primary school students aged 8-12 years old from a primary school in Shanghai from March to June 2025. Physical fitness indicators, including vital capacity, 50 m sprint, sit and reach, and 1 min rope skipping were measured. Physical exercise was assessed by using the Physical Activity Rating Scale-3 (PARS-3), and mental health was assessed by using the Revised Child Anxiety and Depression Scale, 47-item version (RCADS-47). Cognitive function was assessed by using Stroop, N-back, and task-switching tasks. Latent profile analysis (LPA) was performed for cognitive-psychological health of primary school students based on seven cognitive indicators and six psychological indicators. Multivariable Logistic regression, trend test, and restricted cubic spline (RCS) analysis were used to examine associations between physical exercise and psychological highrisk status. Results: Five cognitive psychological health subgroups were identified:high symptom and impaired cognition group ( n =40, 7.3%), low cognition and low symptom group ( n =108, 19.8% ), and high cognition and high symptom group ( n =110, 20.2%), cognitive advantage and psychologically healthy group ( n = 272, 49.8%), and extremely high symptom and cognitively vulnerable group ( n =16, 2.9%). Among them, the high symptom and impaired-cognition group and extremely high symptom and cognitively vulnerable group were classified as psychologically high risk types. Significant differences were observed across subgroups in psychological symptoms, cognitive function, some physical fitness indicators and physical exercise level, except for body weight, body mass index, and sit and reach ( F =2.64-297.53, all P < 0.05). The results of the multivariate Logistic regression analysis indicated that high level sports, including high total volume of physical exercise, single session duration >30 min, high intensity, and frequency ≥3 times/week, was associated with lower psychological high risk status ( OR =0.20, 0.36, 0.33, 0.40, all P <0.05). Trend analysis showed that total volume of physical exercise and single session exercise duration were negatively associated with psychological high risk status among primary school students ( OR =0.98, 0.79, both P trend <0.05). RCS analysis showed no statistically significant overall or nonlinear association between total volume of physical exercise and psychological high risk status ( χ 2=2.92, 0.01, both P >0.05). Conclusions Cognitive-psychological health among primary school students is heterogeneous. Physical exercise is associated with psychological health improvement and may show a threshold effect, with total volume of physical exercise and single session exercise duration being the key dimensions.

Objective To explore the application value of wide awake local anesthesia no tourniquet(WALANT)technique in outpatient surgery for locking of metacarpophalangeal joint with extension lag.Methods The clinical data of 6 patients with locking of meta-carpophalangeal joint with extension lag in Danyang People's Hospital from January 2019 to October 2023 were retrospectively analyzed.The patients were received outpatient surgery under the WALLANT technique for release,and lidocaine mixed solution containing 1∶100 000 epinephrine was injected into the proximal midpoint of the volar projection of the metacarpophalangeal joint.The joint was exposed with a volar or dorsal finger web incision to determine the unrestricted structure,and the collateral ligament and paralateral collateral ligament with high tension were cut off.The intraoperative blood loss,postoperative incision healing and complications were recorded.Visual analogue scale(VAS)was used to evaluate the intraoperative pain,and the range of motion of metacarpophalangeal joint and total active movement(TAM)of finger joint were observed during postoperative follow-up.Results The incision of patients were healed successfully in the first phase after surgery,without wound necrosis.The anesthesia effects of patients were all satisfied and the operation was successfully completed.The VAS score was less than 3 points and there was only a small amount of bleeding during the operation.The recovery of joint flexion and extension movements could be observed during the operation,and the TAM score after the operation was 20 points.No significant change was found on the range of motion of metacarpophalangeal joint or TAM of finger joint between the injured finger and the corresponding healthy finger(P>0.05).Conclusion WALANT technique for locking of metacarpophalangeal joint with extension lag surgery has good anesthesia effect,less bleeding in the incision,and clear vision of the surgery.It can avoid vascular and nerve injuries,observe the recovery of joint activities during the operation and relieve pain of patients,which is conducive to outpatient surgery and saving medical and social resources at the same time.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective:To apply statistical process control (SPC) techniques to the quality assurance of non-normal radiotherapy plans through Johnson transformation, establishing patient-specific tolerance and action limits based on treatment sites and dose/distance assessment criteria, thereby enhancing the intensity-modulated radiation therapy (IMRT) verification accuracy and dose delivery precision.Methods:In this study, 951 gamma analysis data of patient-specific quality assurance (PSQA) executed on the Halcyon accelerator platform were selected and categorized into six groups based on treatment sites, including brain (102 cases), head and neck (100 cases), breast (229 cases), lung (154 cases), esophagus (223 cases), and pelvic (143 cases) groups. The six groups of data were statistically analyzed through Anderson-Darling normality tests ( α = 0.05) using Minitab 21 software. Non-normal data were transformed into normal data through Johnson transformation and then were used to establish treatment site-specific tolerance and action limits, which were compared with the Shewhart control charts based on normal distributions. Results:The PSQA result of the six groups all exhibited non-normal distributions ( P < 0.05). Through Johnson transformation, the tolerance and action limits for the head and neck, breast, lung, esophagus, and pelvic areas under the 3%/2 mm criterion ranged from 95.13% to 96.16% and 94.19% to 95.91%, respectively. In contrast, the tolerance and action limits ranged from 91.15% to 94.86% and 89.94% to 94.78% under the 2%/2 mm criterion. Directly applying Shewhart control charts without normality assumptions yielded higher tolerance limits compared to the application of Johnson transformation, increasing the false positive rate in the non-normal PSQA process. Conclusions:Applying the SPC techniques directly to a non-normal process can lead to an increased false alarm rate and wrong process interpretation. The SPC techniques combined with Johnson transformation enable more effective monitoring of a non-normal PSQA process, facilitating timely identification of potential factors that may lead to an out-of-control process based on the treatment site-specific limits.

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.

The abnormal accumulation of neutrophil extracellular traps （NETs） can promote the initiation and progression of pancreatic cancer， which is considered a potential therapeutic target for this disease. The Miraculous Pivot·Inquiry About Statement （《灵枢·口问》） have recorded the concept of "defensive qi stagnation". Based on the recognition that the function of defensive qi is similar to the immune function of neutrophils， and combining traditional Chinese medicine theory with clinical practice， it is proposed that the abnormal accumulation of NETs may be a pathological product of "defensive qi stagnation"， with the spleen being the critical site of pathology. Further exploring the application strategy of cleaning spleen and restoring defensive qi method in pancreatic cancer treatment， it is proposed to employ three approaches such as dredging method to eliminate spleen stagnation and inhibit pancreatic cancer proliferation， cleaning method to remove spleen dampness and suppress the inflammatory micro-environment， and tonifying method to strengthen Weiqi and to improve the immune microenvironment， which aims to provide new insights for the clinical treatment of pancreatic cancer with traditional Chinese medicine.