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.

Liumotang comes from the Yuan dynasty's Effective Prescription Handed Down for Generations of Physicians. It is composed of six medicinal materials： Arecae Semen， Aquilariae Lignum Resinatum， Aucklandiae Radix， Linderae Radix， Rhei Radix et Rhizoma， and Aurantii Fructus. It is a classical formula for treating abdominal pain due to Qi stagnation and constipation accompanied by heat. This study systematically collated the records of Liumotang in ancient medical books and modern clinical literature and conducted in-depth analysis and textual research on its formula source， main diseases， composition， dosage， medical books， container capacity， processing， preparation method， usage， drug basis， formula meaning， and other key information， so as to provide a powerful reference for the development and clinical application of compound preparations of the classical formula Liumotang. The results show that Liumotang was first seen in Effective Prescription Handed Down for Generations of Physicians， and many medical books of the past dynasties have imitated this. In terms of drug basis， the dried and mature seeds of the palm plant Areca catechu， resin-containing wood of the Daphneaceae plant Aquilaria sinensis， the dried roots of the Asteraceae plant woody Aucklandia lappa， the dried tuber root of the Lauraceae plant Lindera aggregata， the dried roots and rhizomes of the knotweed plant， R. palmatum， R.tangutikum， and R. officinale， and the dried and unripe fruits of the citrus genus C. aurantium and its cultivated varieties from the family Rutaceae were selected. In terms of dosage， through the textual research on bowls in the Ming and Qing dynasties， combined with the conversion of medicines and bowl capacity in the Qing dynasty， it was estimated that the dosage of each drug in the Yuan dynasty was 10.86 g. In the Ming and Qing dynasties， the dosage of drugs was mostly equal， but the dosage of drugs was somewhat different. In terms of processing， preparation method， and usage， in the medical books of the past dynasties， the processing of drugs has slightly changed， but raw drugs are used in all preparations. The preparation method and usage did not change much during the Yuan， Ming， and Qing dynasties， except for certain differences in dosage. In terms of syndrome， Liumotang was first used to treat abdominal pain due to Qi stagnation and constipation accompanied by heat. Medical books of the past dynasties often omit the symptoms of heat. In modern clinical practice， Liumotang is mainly used in the digestive system and urinary system diseases and is mostly used to treat constipation-predominant irritable bowel syndrome， biliary reflux gastritis， functional constipation， slow transit constipation， and other diseases， with no adverse reactions found yet. The above results provide a reliable scientific basis for the development and clinical treatment of Liumotang compound preparations.

OBJECTIVE To investigate the effects of Tripterygium wilfordii multiglycoside （TWM） on renal injury in diabetic nephropathy （DN） rats through tumor protein p53/microRNA-214 （miR-214）/UNC-51-like kinase 1 （ULK1） axis. METHODS Male SD rats were randomly divided into normal group （n＝6） and modeling group （n＝28）； the modeling group was fed with high fat and high glucose plus intraperitoneal injection of streptozotocin to establish DN model. The modeled rats were randomly divided into model group， valsartan group [8.33 mg/（kg·d）] and TWM group[6.25 mg/（kg·d）]， with 8 rats in each group. Rats in each group were gavaged with the corresponding medication or normal saline， once a day， for 6 consecutive weeks. After the last medication， liver and renal function indexes [24 h urinary total protein （24 h-UTP）， blood urea nitrogen （BUN）， serum creatinine （SCr）， albumin （ALB）， alanine transaminase （ALT）]， blood lipid indexes （triglycerides， total cholesterol） and blood glucose index （fasting blood glucose） in urine/blood sample of rats were detected in each group. Renal pathologic change was observed， protein and mRNA expressions of p53， ULK1， Beclin-1 and microtubule-associated protein 1 light chain 3 （LC3）， and expression of miR-214 in renal tissue were also determined. RESULTS Compared with the normal group， the renal tubular epithelium of rats in the model group showed obvious edema， cell swelling， accompanied by lymphocyte infiltration； the levels of 24h-UTP， BUN， SCr， ALT and glycolipid indexes， the expressions of p53 protein and mRNA， as well as the expression of miR-214 in rats in the model group and administration groups were significantly increased or up-regulated， while ALB level， LC3-Ⅱ/LC3-Ⅰ， the expressions of LC3 mRNA， the expressions of ULK1， Beclin-1 protein and mRNA were significantly decreased or down-regulated （P＜0.01）. Compared with the model group， the histopathological damage of the kidney in rats was improved in administration groups； the levels of 24 h-UTP， BUN， SCr， ALT and glycolipid indexes， the expressions of p53 protein and mRNA， as well as the expression of miR-214 were all significantly decreased or down-regulated， while ALB level， LC3-Ⅱ/LC3-Ⅰ， the expressions of LC3 mRNA， the expressions of ULK1 and Beclin-1 protein and mRNA were significantly increased or up-regulated （P＜0.01）. CONCLUSIONS TG can alleviate renal damage in DN rats， and improve their liver and renal function， as well as glucose and lipid levels. These effects may be related to the regulation of the p53/miR-214/ULK1 axis and the restoration of cellular autophagy.

PURPOSE: Deep vein thrombosis (DVT) of the left and right lower extremities was treated in the same way, but the left and right extremities received different levels of attention. This study aimed to investigate the differences between the right and left lower extremity deep vein thrombosis (LEDVT). METHODS: Clinical characteristics of LEDVT patients from July 2020 to June 2022 were retrospectively analyzed to compare the incidence of LEDVT on different limbs, demographics, predisposing factors, and anatomical characteristics. The exclusion criteria were bilateral LEDVT and recurrent thrombosis. Measured data was analyzed using independent samples t-test or Mann-Whitney test. Count data were analyzed by Chi-square test. A p < 0.05 was considered a statistically significant difference. RESULTS: There were 478 patients included in this study and the ratio of left to right LEDVT on the left and right limbs was 3.16:1 (363:115). Left LEDVT predominantly affected female, with the major aged > 50 years (50 - 60 years: 16.80%; > 60 years: 57.30%). The primary predisposing factor was iliac vein compression syndrome, with iliofemoral thrombosis being the main type. Male patients with LEDVT on the right limb were predominant and the age of onset was usually ≤ 60 years (52.17%). The main predisposing factor was recent surgery or trauma (< 30 days) and femoropopliteal thrombosis was the main type. In more detail, the left iliac vein was compressed mainly in the proximal segment, and the right iliac vein was compressed mainly in the intermediate and distal segments. Recent surgery or trauma to the locomotor system and genitourinary system often induced LEDVT. CONCLUSION The incidence of LEDVT on the left is significantly higher than that on the right. LEDVT on different sides has different characteristics, which is crucial for prevention and diagnosis in the relevant population so there are also differences in treatment of the affected limbs.
Humans ; Venous Thrombosis/etiology* ; Male ; Female ; Middle Aged ; Lower Extremity/blood supply* ; Retrospective Studies ; Adult ; Aged ; Age Factors ; Sex Factors ; Risk Factors ; Acute Disease ; Incidence ; Aged, 80 and over ; Young Adult ; Adolescent

Objective To analyze the factors affecting the prevalence of hyperuricemia(HUA)in an island troop.Methods A total of 1 113 soldiers stationed on an island from December 2021 to December 2022 were selected as research objects by cluster sampling.Their lifestyle and health information were collected.Physical examination and laboratory detection were conducted.Multivariate logistic regression was used to analyze the influencing factors of HUA.Results The prevalence rate of HUA was 21.02%(234/1 113).There were significant differences in the body mass index(BMI),waist-to-hip ratio,triglyceride,alanine aminotransferase,and creatinine between the soldiers with hyperuricemia and the soldiers with normal blood uric acid(P<0.05).Multivariate logistic regression analysis showed that BMI≥24(OR=1.49,95%CI:1.09-2.05),abnormal liver function(OR=2.26,95%CI:1.31-3.92),and dyslipidemia(OR=1.46,95%CI:1.01-2.12)were positively correlated with hyperuricemia;age>30 years old(OR=0.59,95%CI:0.37-0.93)and exercise time>1 h per week(OR=0.46,95%CI:0.22-0.97)were negatively correlated with HUA.Conclusion The prevalence rate of hyperuricemia is at a high level in an island troop.BMI≥24,age≤30 years old,exercise time≤1 h per week,abnormal liver function,and dyslipidemia are the risk factors for HUA.Prevention and control measures should be taken as early as possible for the soldiers with these risk factors.

Objective To observe the clinical efficacy of mind-regulating and meridians-dredging acupuncture combined with rehabilitation training in treating limb dysfunction in recovery period of cerebral infarction(CI).Methods A total of 110 cases of patients with limb dysfunction in recovery period of CI were randomly divided into observation group and control group,55 cases in each group,the control group was given routine rehabilitation training,and the observation group was treated with mind-regulating and meridians-dredging acupuncture on the basis of intervention of the control group,the course of treatment covered two consecutive weeks.After two weeks of treatment,the clinical efficacy of the two groups was evaluated,and the changes of scores of traditional Chinese medicine(TCM)syndrome,Fugl-Meyer Assessment(FMA),Berg Balance Scale(BBS)and Modified Barthel Index(MBI)before and after treatment of patients in the two groups were observed.The changes of electromyographic signal before and after treatment were compared between the two groups.And the safety and the occurrence of adverse reactions in the two groups were evaluated.Results(1)The total effective rate was 98.18%(54/55)in the observation group and 87.27%(48/55)in the control group.The efficacy of the observation group was superior to that of the control group,the difference being statistically significant(P<0.05).(2)After treatment,the TCM syndrome scores of patients in the two groups were significantly improved(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,with a statistically significant difference(P<0.05).(3)After treatment,the FMA scores of patients in the two groups improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(4)After treatment,the BBS scores and MBI scores of the patients in the two groups improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(5)After treatment,the root mean square value(RMS)of biceps brachii muscle elbow flexion and triceps brachii muscle elbow extention of the two groups of patients improved significantly(P<0.05),and the improvement in the observation group was significantly superior to that in the control group,the difference being statistically significant(P<0.05).(6)During the treatment,there were no obvious adverse reactions occurred in both groups.Conclusion Mind-regulating and meridians-dredging acupuncture combined with rehabilitation training in treating limb dysfunction in recovery period of CI can significantly improve the motor ability of patients,and adjust the electromyographic signals of the affected limbs,with high safety.

To understand the background of Escherichia coli(E.coli)carried by artificially bred sika deer and the biological characteristics of the isolated strains,such as drug resistance and pathogenicity,in April 2024,we collected 184 fresh deer fecal samples from four deer farms in Luxiang Township,Shuangyang District,Changchun City,Jilin Province,for isolation and cultivation of E.coli.The isolates were tested for drug resistance and biochemical identification with a BD PhoenixTM-100 Automated Microbiology System.The virulence genes were detected with PCR,and the strains were molecularly typed with ERIC-PCR.A total of 165 E.coli strains were isolated from 184 samples of deer feces,with an isolation rate of 89.67%.Twenty strains had a drug resistance phenotype,and the drug resistance rate was 12.12%;these strains included 15 strains of multi-drug resistant bacteria and 11 strains of ESBL-producing bacteria.Virulence gene detection indicated that the sika deer isolates carried multiple diarrhea-associated virulence genes,such as EAST-1(12.12%),eae(1.21%),stx1(7.88%),stx2(7.27%),and STa(1.82%).ERIC-PCR demonstrated that the isolates showed high polymorphism.The ESBL-producing E.coli carried by sika deer are likely to spread drug resistance in the community and livestock population.Some isolates carried multiple diarrhea-associated virulence genes,thus posing a human transmission risk.Therefore,monitoring of drug resistance and virulence genes must be strengthened,and antibiotics must be used reasonably during the breeding process to avoid excessive use and misuse.

To understand the background of Escherichia coli(E.coli)carried by artificially bred sika deer and the biological characteristics of the isolated strains,such as drug resistance and pathogenicity,in April 2024,we collected 184 fresh deer fecal samples from four deer farms in Luxiang Township,Shuangyang District,Changchun City,Jilin Province,for isolation and cultivation of E.coli.The isolates were tested for drug resistance and biochemical identification with a BD PhoenixTM-100 Automated Microbiology System.The virulence genes were detected with PCR,and the strains were molecularly typed with ERIC-PCR.A total of 165 E.coli strains were isolated from 184 samples of deer feces,with an isolation rate of 89.67%.Twenty strains had a drug resistance phenotype,and the drug resistance rate was 12.12%;these strains included 15 strains of multi-drug resistant bacteria and 11 strains of ESBL-producing bacteria.Virulence gene detection indicated that the sika deer isolates carried multiple diarrhea-associated virulence genes,such as EAST-1(12.12%),eae(1.21%),stx1(7.88%),stx2(7.27%),and STa(1.82%).ERIC-PCR demonstrated that the isolates showed high polymorphism.The ESBL-producing E.coli carried by sika deer are likely to spread drug resistance in the community and livestock population.Some isolates carried multiple diarrhea-associated virulence genes,thus posing a human transmission risk.Therefore,monitoring of drug resistance and virulence genes must be strengthened,and antibiotics must be used reasonably during the breeding process to avoid excessive use and misuse.