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 explore the strategy of blood management in patients with massive transfusion in the frigid plateau region. [Methods] The treatment process of a patient with liver rupture in the frigid plateau region was analyzed, and the blood management strategy of the frigid plateau region was discussed in combination with the difficulties of blood transfusion and literature review. [Results] The preoperative complete blood count (CBC) test results of the patient were as follows: RBC 3.14×10¹²/L, Hb 10⁶ g/L, HCT 30.40%, PLT 115.00×10⁹/L; coagulation function: PT 18.9 s, FiB 1.31 g/L, DD > 6 μg/mL, FDP 25.86 μg/mL; ultrasound examination and imaging manifestations suggested liver contusion and laceration / intraparenchymal hematoma, splenic contusion and laceration, and massive blood accumulation in the abdominal cavity; it was estimated that the patient's blood loss was ≥ 2 000 mL, and massive blood transfusion was required during the operation; red blood cell components were timely transfused during the operation, and the blood component transfusion was guided according to the patient's CBC and coagulation function test results, providing strong support and guarantee for the successful treatment of the patient. The patient recovered well after the operation, and the CBC test results were as follows: RBC 4.32×10¹²/L, Hb 144 g/L, HCT 39.50%, PLT 329.00×10⁹/L; coagulation function: APTT 29.3 s, PT 12.1 s, FiB 2.728 g/L, DD>6 μg/mL, FDP 25.86 μg/mL. The patient was discharged after 20 days, and regular follow-up reexamination showed no abnormal results. [Conclusion] Individualized blood management strategy should comprehensively consider the patient’s clinical symptoms, the degree of hemoglobin decline, dynamic coagulation test results and existing treatment conditions. Efficient and reasonable patient blood management strategies can effectively improve the clinical outcomes of massive transfusion patients in the frigid plateau region.

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

Objective:To evaluate the efficacy and safety of once-daily tacrolimus extended-release capsules (OD-TAC) in pediatric liver transplant recipients after conversion from twice-daily tacrolimus (TD-TAC).Methods:A retrospective analysis was performed on pediatric liver transplant recipients at Tianjin First Center Hospital between January 2014 and December 2020 who were converted from TD-TAC to OD-TAC with a follow-up of at least 12 months. After conversion, all patients received OD-TAC monotherapy. The daily dose conversion ratio from TD-TAC to OD-TAC ranged from 2∶1 to 1∶2. Clinical data including demographics, tacrolimus dosage, trough concentrations, liver function, and adverse events were collected. Continuous variables with normal distribution were expressed as Mean±SD and compared using independent-samples t-test or ANOVA; non-normally distributed variables were expressed as median ( Q1, Q3) and compared using Mann-Whitney U or Kruskal-Wallis H tests. Categorical variables were expressed as frequency and percentage, and compared using χ 2 test or Fisher's exact test. P<0.05 was considered statistically significant. Results:A total of 290 children were enrolled, including 140 males (48.3%) and 150 females (51.7%). The median age at transplantation was 7.34 (6.03, 12.34) months, and the median time to conversion was 36 (29, 48) months post-transplant. Tacrolimus daily doses at 3, 6, and 12 months after conversion were slightly higher than before conversion, but without statistical significance (all P>0.05). Trough tacrolimus levels at 6 and 12 months after conversion were 2.34±1.02 μg/L and 2.23±1.07 μg/L, respectively, both lower than pre-conversion (2.77±1.43 μg/L), with statistical significance ( P=0.02 and P<0.01). Serum creatinine levels at 6 and 12 months post-conversion were 2.63±0.63 mmol/L and 2.76±0.68 mmol/L, respectively, both higher than before conversion (2.57±1.90 mmol/L, P<0.05). Triglyceride level at 12 months post-conversion was 0.87±0.25 mmol/L, significantly lower than pre-conversion (1.05±0.55 mmol/L, P<0.05). Two patients developed transient bilirubin elevation at 3 months, and another two developed transient triglyceride elevation at 6 months; all recovered without intervention. No new-onset diabetes was observed during follow-up. Thirteen patients experienced acute rejection. One patient (0.3%) died three years after conversion due to hepatic venous outflow obstruction, while all others survived. Conclusion:In pediatric liver transplant recipients, OD-TAC provides comparable efficacy and safety to TD-TAC.

Objective:To evaluate the efficacy and safety of once-daily tacrolimus extended-release capsules (OD-TAC) in pediatric liver transplant recipients after conversion from twice-daily tacrolimus (TD-TAC).Methods:A retrospective analysis was performed on pediatric liver transplant recipients at Tianjin First Center Hospital between January 2014 and December 2020 who were converted from TD-TAC to OD-TAC with a follow-up of at least 12 months. After conversion, all patients received OD-TAC monotherapy. The daily dose conversion ratio from TD-TAC to OD-TAC ranged from 2∶1 to 1∶2. Clinical data including demographics, tacrolimus dosage, trough concentrations, liver function, and adverse events were collected. Continuous variables with normal distribution were expressed as Mean±SD and compared using independent-samples t-test or ANOVA; non-normally distributed variables were expressed as median ( Q1, Q3) and compared using Mann-Whitney U or Kruskal-Wallis H tests. Categorical variables were expressed as frequency and percentage, and compared using χ 2 test or Fisher's exact test. P<0.05 was considered statistically significant. Results:A total of 290 children were enrolled, including 140 males (48.3%) and 150 females (51.7%). The median age at transplantation was 7.34 (6.03, 12.34) months, and the median time to conversion was 36 (29, 48) months post-transplant. Tacrolimus daily doses at 3, 6, and 12 months after conversion were slightly higher than before conversion, but without statistical significance (all P>0.05). Trough tacrolimus levels at 6 and 12 months after conversion were 2.34±1.02 μg/L and 2.23±1.07 μg/L, respectively, both lower than pre-conversion (2.77±1.43 μg/L), with statistical significance ( P=0.02 and P<0.01). Serum creatinine levels at 6 and 12 months post-conversion were 2.63±0.63 mmol/L and 2.76±0.68 mmol/L, respectively, both higher than before conversion (2.57±1.90 mmol/L, P<0.05). Triglyceride level at 12 months post-conversion was 0.87±0.25 mmol/L, significantly lower than pre-conversion (1.05±0.55 mmol/L, P<0.05). Two patients developed transient bilirubin elevation at 3 months, and another two developed transient triglyceride elevation at 6 months; all recovered without intervention. No new-onset diabetes was observed during follow-up. Thirteen patients experienced acute rejection. One patient (0.3%) died three years after conversion due to hepatic venous outflow obstruction, while all others survived. Conclusion:In pediatric liver transplant recipients, OD-TAC provides comparable efficacy and safety to TD-TAC.

Objective To analyze the spatiotemporal distribution characteristics of respiratory bacterial infections in Sanmenxia City from 2012 to 2022, and explore key areas for respiratory infection prevention and control. Methods Respiratory bacterial infection cases admitted to our hospital from 2012 to 2022 was collected, use OpenGeoDal software for spatial autocorrelation analysis, and SaTScan software for spatiotemporal scanning analysis. Results From 2012 to 2022, 8762 cases of respiratory bacterial infection were reported in Sanmenxia , with an average annual incidence of 173.47/100 000 and a standardized incidence of 132.63/100 000，and the overall incidence showed a downward trend (χ²=48.093，P<0.01). The incidence of respiratory tract bacterial infection has gender characteristics,the incidence of respiratory tract bacterial infection is the highest among people aged 50 years and above (P<0.05). There was no global spatial autocorrelation, and local autocorrelation results showed that the "high-high" clustering area was mainly located in Yima City. The spatiotemporal scanning results showed that the first level aggregation area was located in Yima City, with a time span of 2020-2022 and a radiation radius of 4.57 km (LLR=40.19, RR=3.27, P<0.001). Conclusion The overall trend of respiratory bacterial infections in Sanmenxia City is decreasing, and Yima City is a ^“high- high^” gathering area, which is a key region to prevention and control.

Objective:To construct an analytic method aimed at the characteristics of the commonly method of supplementing and pouring of acupuncture based on the analysis and modeling of ultrasound images around acupoint region in the process of acupuncture.Methods:A total of 7 healthy subjects who underwent physical examination in Beijing Zhongguancun Hospital from June,2022 to June,2023 were selected,and their Kongzui acupoints were acupunctured by 10 acupuncturists with associate senior title as 4 kinds of acupuncture manipulations included reinforcing by twisting and rotating(RFTR),reducing by twisting and rotating(RDTR),reinforcing by lifting and thrusting(RFLT),and reducing by lifting and thrusting(RDLT).The B-ultrasound diagnostic device was used to collect the images of muscle and fascial tissue below the acupoint,so as to construct the model of images.The definition of virtual acupuncture point was adopted to study the regulation of perturbation of subcutaneous tissue that was caused after the skin was acupunctured by needle.The change regulation of the virtual acupuncture point of muscle bundle below skin at Zuikong acupoint of subjects was analyzed.Results:The difference value of average absolution value between peak and trough of the trajectory of virtual acupuncture point of twisting and rotating was 0.066±0.045,and the average value of amplitude of this method was less than that(0.428±0.276)of lifting and thrusting method,and the twisting and rotating method was uniform and symmetrical,and there was difference between two kinds of acupuncture methods.The characteristics of computer graphics was used to qualify the work effect of lifting and thrusting,and reinforcing and reducing,which showed the heavy insertion and light lifting of RFLT,and showed heavy lifting and light insertion of RDLT,thus distinguished the two methods[(RFLT)and(RDLT)].Conclusions:The ultrasound imaging and computer graphics can be used to analyze the regularity of the common"reinforcing and reducing"method of acupuncture and moxibustion.

Objective To evaluate the clinical application of automatic coagulation detection assembly line in high-throughput specimen detection.Methods The relevant information of sodium citrate anticoagulation samples in Zhongshan Hospital Affiliated to Fudan University from June to August 2021 was collected,inclu-ding sample collection time,receiving time,instrument sucking time,test completion time,and whether it pas-sed autoverification or not.The sample pretreatment time,testing time and turnaround time(TAT)of the au-tomatic coagulation detection assembly line were compared before and after installation,and the detection speed of the automatic coagulation detection assembly line was evaluated.Results The automatic coagulation detection line was expected to detect 650-900 samples per hour.The increase in the number of turbidimetric tests would slow down the detection speed of the instrument.Automatic coagulation detection assembly line test specimen to clinic and ward of pretreatment time and testing time were shorter than single detection,the differences were statistically significant(P＜0.05).The automatic coagulation detection assembly line could shorten TAT(P＜0.05).After the application of automatic coagulation detection assembly line,the autoveri-fication rate was 25.6％.Conclusion The automatic coagulation detection assembly line is suitable for high-throughput specimen detection in laboratory.Compared with stand-alone coagulation detection,the automatic coagulation detection assembly line could shorten TAT and testing time,and help to reduce the work pressure of laboratory personnel.