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.

Purpose To evaluate the efficacy of ultra-high field 5.0T MRI combined with histogram analysis for diagnosing prostate cancer and benign prostatic hyperplasia.Materials and Methods This retrospective analysis included data from 63 patients with prostatic diseases at the Chongqing University Three Gorges Hospital from January to May 2024,comprising 31 cases of prostate cancer and 32 cases of benign prostatic hyperplasia.MRI sequences included T2WI,T1WI,diffusion-weighted imaging,intravoxel incoherent motion and T2 mapping.Histogram data of apparent diffusion coefficient,true diffusion coefficient,pseudo-diffusion coefficient,perfusion fraction and T2 relaxation time were calculated,and diagnostic efficacy was assessed using the area under the receiver operating characteristic curve.Results In prostate cancer,the 10th percentile,the 90th percentile,mean,median,and minimum values of histogram parameters from apparent diffusion coefficient,true diffusion coefficient,pseudo-diffusion coefficient,perfusion fraction and T2 mapping were significantly lower than those of benign prostatic hyperplasia(Z=-6.036--3.368,all P<0.05).Notably,the combined model of apparent diffusion coefficient,intravoxel incoherent motion and T2 mapping parameters achieved an the area under the curve of 0.987,with sensitivity and specificity of 96.77%and 96.87%,respectively.Conclusion This study confirms that 5.0T MRI histogram analysis technique demonstrates significant diagnostic efficacy in differentiating prostate cancer from benign prostatic hyperplasia.

Purpose To evaluate the efficacy of ultra-high field 5.0T MRI combined with histogram analysis for diagnosing prostate cancer and benign prostatic hyperplasia.Materials and Methods This retrospective analysis included data from 63 patients with prostatic diseases at the Chongqing University Three Gorges Hospital from January to May 2024,comprising 31 cases of prostate cancer and 32 cases of benign prostatic hyperplasia.MRI sequences included T2WI,T1WI,diffusion-weighted imaging,intravoxel incoherent motion and T2 mapping.Histogram data of apparent diffusion coefficient,true diffusion coefficient,pseudo-diffusion coefficient,perfusion fraction and T2 relaxation time were calculated,and diagnostic efficacy was assessed using the area under the receiver operating characteristic curve.Results In prostate cancer,the 10th percentile,the 90th percentile,mean,median,and minimum values of histogram parameters from apparent diffusion coefficient,true diffusion coefficient,pseudo-diffusion coefficient,perfusion fraction and T2 mapping were significantly lower than those of benign prostatic hyperplasia(Z=-6.036--3.368,all P<0.05).Notably,the combined model of apparent diffusion coefficient,intravoxel incoherent motion and T2 mapping parameters achieved an the area under the curve of 0.987,with sensitivity and specificity of 96.77%and 96.87%,respectively.Conclusion This study confirms that 5.0T MRI histogram analysis technique demonstrates significant diagnostic efficacy in differentiating prostate cancer from benign prostatic hyperplasia.

Sarcopenia is an age-related skeletal muscle degenerative disease.Physiologically aging mice are the most commonly used animal model for studying sarcopenia.As sarcopenia is characterized by decreased skeletal muscle mass and reduced muscle strength,exercise performance as a reflection of muscle function is widely used to evaluate sarcopenia.Methods of evaluating the motor function of sarcopenia mouse models are generally designed based on muscle endurance,muscle strength,coordination,and balance.The method include tests such as treadmill exhaustion,voluntary wheel use,grip strength,horse grid,bars and balance beam tests.By collating recent publications,we have systematically summarized the method used for evaluating motor function,including the tests'principles,procedures,evaluation indexes,advantages,and disadvantages.We then propose an operational program for evaluating the sarcopenia phenotype,which will be of help to researchers wishing to choose evaluation method appropriate to their specific research purposes.Further innovative technology for assessing motor function that could be instructive in the evaluation of skeletal muscle function and diagnosis of sarcopenia is summarized.

Objective Five chloroplast(cp)genomes from members of genus Polygonatum were assembled by hybrid assembly technique,and their intraspecic and interspecific differences were analyzed by comparative genomic method.Codon usage patterns and influencing factors were determined,and the cp genome data were applied to understand the phylogenomic relationships in the entire genus Polygonatum along with the available data.Methods In this study,the chloroplast genomes of 5 species of genus Polygonatum were assembled using Unicycler software.Sequence alignment,collinearity analysis,boundary analysis and other methods were used to evaluate the interspecific differences of these five species.Nucleotide polymorphism analysis was used to discover the high-variation sites of the five species and their related species,predict the distribution of different long repeat sequences and SSRs,and then analyze the use bias of Polygonatum code.Finally,phylogenetic tree was constructed with the coding sequences of other 47 genus Polygonatum and their closely related species to explore their phylogenetic relationships in this study.Results ①Chloroplast genomes of 155 408-155 623 bp were assembled from five species of Polygonatum.A total of 132-133 genes were annotated,and 369 long repeats and 1553 simple repeats were detected.②The contraction and expansion of chloroplast genomes in 8 species were not obvious at the IRs boundary,and the size and distribution of individual genes at the LSC-IRs-SSC boundary,such as ndhF gene and ycf1 gene,were slightly different.No interspecific or intraspecific rearrangement was observed in 8 species.③ The high-variation regions of the 8 chloroplast genomes are mainly located in two single-copy regions,the duplicate copy region is relatively conserved,and the coding region is more conserved than the non-coding region.High nucleotide polymorphic loci rps16-trnQ,trnS-trnG,trnTUGU-trnL,ndhF-rpl32 and rpl32-trnL are located in the single copy region and most of them are gene spacer regions.④ The codon preference results showed that the codon preference of the five species was similar and mainly affected by selection pressure,and the third base of the codon played A dominant role and mainly ended in A/U.RSCU clustering heat map shows that PK and PZ,PCB and PS have close relationship.⑤ Phylogenetic trees divided 52 species into five branches:Ⅰ,Ⅱ,Ⅲ,ⅣandⅤ.PS,PK,PCB,PCZ and PZ were divided into ⅣandⅤbranches,among which PK and PZ were most closely related,while PCZ was more distant than the other four,was divided into the Ⅴbranch alone.Conclusion This study provided a reference for the phylogenetic research and molecular marker development of the medicinal plants of the Polygonum genus.

EGFR-mutant non-small cell lung cancer (NSCLC) is a common type of lung cancer, with EGFR tyrosine kinase inhibitors (EGFR-TKIs) being the standard first-line treatment. However, most patients with NSCLC eventually develop resistance to EGFR-TKIs. Studies on the mechanism underlying EGFR-TKI resistance have driven the development of personalized and precision medicine. Current strategies to address resistance include targeted therapy, immunotherapy, and novel drug treatments. Selecting the appropriate personalized treatment plan is crucial for improving the survival rate and quality of life of patients with EGFR-mutant NSCLC. Thus, this study provides a brief review of the current status and future perspectives in the treatment of EGFR-mutant NSCLC after progression on EGFR-TKI therapy.

Background: Developing and validating a modified parameter, the SYS-G angle (the angle between the lower endplate of the C2 and the upper endplate of C7 vertebrae), as a feasible substitute for the C2–C7 Cobb method in assessing cervical sagittal alignment and exploring its reference range through a large-scale retrospective study. Methods: The visibility of the C6, C7 upper, and C7 lower endplates was graded and compared. Baseline data such as height, weight, body mass index (BMI), age, and sex were analyzed for their impact on the visibility of the C7 lower endplate. Values of C2-6 Cobb angle, SYS-G angle, and C2-7 Cobb angle were measured. The intra- and interobserver reliability, differences, and efficacy of evaluation on cervical lordosis of the parameters were compared, and the correlations among the parameters were analyzed. Furthermore, reference ranges for the SYS-G angle were established based on lateral cervical spine x-rays of 825 asymptomatic Chinese adults across different age groups and sexes. Results: The visibility of the C7 lower endplates was significantly reduced compared to the C6 lower and C7 upper endplates.Age, weight, BMI, and male sex were identified as factors negatively influencing the visibility of the C7 lower endplate. Both intraobserver and interobserver reliability demonstrated excellence for all tested parameters. The linear regression model unveiled a stronger association of the SYS-G angle with the C2-7 Cobb angle compared to the C2-6 Cobb angle. Furthermore, the SYS-G angle exhibited excellent efficacy in evaluating cervical lordosis. Age displayed a positive correlation with the SYS-G angle, and across every age bracket from 20 to 69 years, men exhibited a higher mean SYS-G angle compared to women. Conclusions The visibility of the C7 lower endplate diminishes with increasing age, weight, BMI, and male sex. In cases where the C7 lower endplate is unclear, the SYS-G angle emerges as a reliable method for estimating cervical sagittal morphology. Reference ranges for the SYS-G angle were established across various age groups and sexes among asymptomatic Chinese adults, offering a valuable resource to guide therapeutic interventions for cervical spine disorders and deformities.

Background: Developing and validating a modified parameter, the SYS-G angle (the angle between the lower endplate of the C2 and the upper endplate of C7 vertebrae), as a feasible substitute for the C2–C7 Cobb method in assessing cervical sagittal alignment and exploring its reference range through a large-scale retrospective study. Methods: The visibility of the C6, C7 upper, and C7 lower endplates was graded and compared. Baseline data such as height, weight, body mass index (BMI), age, and sex were analyzed for their impact on the visibility of the C7 lower endplate. Values of C2-6 Cobb angle, SYS-G angle, and C2-7 Cobb angle were measured. The intra- and interobserver reliability, differences, and efficacy of evaluation on cervical lordosis of the parameters were compared, and the correlations among the parameters were analyzed. Furthermore, reference ranges for the SYS-G angle were established based on lateral cervical spine x-rays of 825 asymptomatic Chinese adults across different age groups and sexes. Results: The visibility of the C7 lower endplates was significantly reduced compared to the C6 lower and C7 upper endplates.Age, weight, BMI, and male sex were identified as factors negatively influencing the visibility of the C7 lower endplate. Both intraobserver and interobserver reliability demonstrated excellence for all tested parameters. The linear regression model unveiled a stronger association of the SYS-G angle with the C2-7 Cobb angle compared to the C2-6 Cobb angle. Furthermore, the SYS-G angle exhibited excellent efficacy in evaluating cervical lordosis. Age displayed a positive correlation with the SYS-G angle, and across every age bracket from 20 to 69 years, men exhibited a higher mean SYS-G angle compared to women. Conclusions The visibility of the C7 lower endplate diminishes with increasing age, weight, BMI, and male sex. In cases where the C7 lower endplate is unclear, the SYS-G angle emerges as a reliable method for estimating cervical sagittal morphology. Reference ranges for the SYS-G angle were established across various age groups and sexes among asymptomatic Chinese adults, offering a valuable resource to guide therapeutic interventions for cervical spine disorders and deformities.

Background: Developing and validating a modified parameter, the SYS-G angle (the angle between the lower endplate of the C2 and the upper endplate of C7 vertebrae), as a feasible substitute for the C2–C7 Cobb method in assessing cervical sagittal alignment and exploring its reference range through a large-scale retrospective study. Methods: The visibility of the C6, C7 upper, and C7 lower endplates was graded and compared. Baseline data such as height, weight, body mass index (BMI), age, and sex were analyzed for their impact on the visibility of the C7 lower endplate. Values of C2-6 Cobb angle, SYS-G angle, and C2-7 Cobb angle were measured. The intra- and interobserver reliability, differences, and efficacy of evaluation on cervical lordosis of the parameters were compared, and the correlations among the parameters were analyzed. Furthermore, reference ranges for the SYS-G angle were established based on lateral cervical spine x-rays of 825 asymptomatic Chinese adults across different age groups and sexes. Results: The visibility of the C7 lower endplates was significantly reduced compared to the C6 lower and C7 upper endplates.Age, weight, BMI, and male sex were identified as factors negatively influencing the visibility of the C7 lower endplate. Both intraobserver and interobserver reliability demonstrated excellence for all tested parameters. The linear regression model unveiled a stronger association of the SYS-G angle with the C2-7 Cobb angle compared to the C2-6 Cobb angle. Furthermore, the SYS-G angle exhibited excellent efficacy in evaluating cervical lordosis. Age displayed a positive correlation with the SYS-G angle, and across every age bracket from 20 to 69 years, men exhibited a higher mean SYS-G angle compared to women. Conclusions The visibility of the C7 lower endplate diminishes with increasing age, weight, BMI, and male sex. In cases where the C7 lower endplate is unclear, the SYS-G angle emerges as a reliable method for estimating cervical sagittal morphology. Reference ranges for the SYS-G angle were established across various age groups and sexes among asymptomatic Chinese adults, offering a valuable resource to guide therapeutic interventions for cervical spine disorders and deformities.