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 technical process and clinical application of laparoscopic combined upper midline incision minimally invasive liver transplantation. Methods A retrospective analysis was conducted on 30 cases of laparoscopic combined upper midline incision minimally invasive liver transplantation. The cases were divided into cirrhosis group (15 cases) and liver failure group (15 cases) based on the primary disease. The surgical and postoperative conditions of the two groups were compared. Results All patients successfully underwent laparoscopic "clockwise" liver resection, with no cases of passive conversion to open surgery or intolerance to pneumoperitoneum. In 6 cases, the right lobe was relatively large, and the right hepatic ligaments could not be completely mobilized. One case required an additional reverse "L" incision during open surgery. All patients successfully completed the liver transplantation, with no major intraoperative bleeding, cardiovascular events, or other occurrences in the 30 patients. The model for end-stage liver disease (MELD) score in the cirrhosis group was lower than that in the liver failure group (P<0.001). There were no statistically significant differences between the two groups in terms of age, surgical time, blood loss, anhepatic phase, or cold ischemia time (all P>0.05). During the perioperative period, there was 1 case of hepatic artery embolism, 1 case of portal vein anastomotic stenosis, no complications of hepatic vein and inferior vena cava, and 3 cases of biliary anastomotic stenosis, all of which occurred in the liver failure group. Conclusions In strictly selected cases, the minimally invasive liver transplantation technique combining laparoscopic hepatectomy with upper midline incision for graft implantation has the advantages of smaller incisions, less bleeding, relatively easier operation, and faster postoperative recovery, which is worthy of clinical promotion and application.

Objective To establish the phylogenic relationships among genus Botrychium,and to develop better molecular markers,along with to gain better understanding of cytonuclear coordination patterns of RuBisCO enzyme,the current article sampled two species(e.g.Botrychium ternatum(Thunb.)Sw.and Botrychium virginianum(L.)Sw.),and applied sequencing approaches for the data mining.Methods The assembly results of chloroplast(cp)genomes from B.ternatum and B.virginianum were determined via de novo hybrid assemble approach with the help of short reads(Illumina)and long reads(PacBio and Nanopore).Then the phylogenic relationships of 18 fern species were reconstructed based on the protein coding sequences from the cp genome and the rbcS gene,which were fished out of the RNA-seq data from SRA database,respectively.Then the adaptive selection and co-evolutionary analysis were employed to investigate the evolutionary trajectories of rbcL(cp genome)and rbcS(nuclear genome)genes.Results The full length of cp genome in the two genus Botrychium species were determined as 139 063 bp(NC_060644)and 139 372 bp(OR609363).Then 92 SSR sites and 78 SSR sites were identified in the current two cp genomes,respectively.The collinearity analysis showed high relevant relationship between the current two species,and significant relationship within both species among the inverted repeats regions.The adaptation and coevolution investigations illustrated the following results:①Coevolution network exists between RBCL and RBCS subunits from the fern RuBisCO enzyme.②Positively selected sites were significantly detected among both rbcL and rbcS genes.③Two coevolutionary pair sites from the two genes(e.g.site 11 in RBCL and site 106 in RBCS)were significantly positively selected,which may demonstrate a molecular pattern for the fern species fine-tuning the RuBisCO enzyme during the long earth history via the cytonuclear coordination.Conclusion Our current research shed a new light on the phylogenetic relationship of the genus Botrychium among the fern backbone-tree and provided amount of cpSSR sites with the potential as molecular markers for further population study on B.ternatum and B.virginianum.Moreover,our adaptation and coevolution investigations on rbcL and rbcS genes might indicate that the underlying cytonuclear coordination between the organelle and nuclear in cell of fern species for fine-tuning the key photosynthesis enzyme RuBisCO to gain better fitness according to the changing environment of earth during the geologic time-scale.

Objective To explore research hotspots and future development trends in radioactive iodine refractory differentiated thyroid carcinoma (RAIR-DTC) treatment from 2004 to 2024. Methods Literature on RAIR-DTC treatment published from January 2004 to May 2024 was retrieved from the Web of Science (WOS) database. CiteSpace, VOSviewer, and Microsoft Office Excel were used for visual analysis of publication volume, countries, institutions, authors, keywords, and co-citation networks. Results A total of 677 articles were included in the analysis. National and institutional co-occurrence analysis revealed that the United States, along with the MD Anderson Cancer Center at the University of Texas, was the most productive and influential in this field. Author and citation co-occurrence analysis highlighted the substantial contributions of Schlumberger M and Brose MS to the field. The exploration of high-frequency keywords and keyword clustering indicated tyrosine kinase inhibitors and disease prognostic factors were current research hotspots. Keyword burst analysis suggested that future research trends would focus on optimizing clinical benefits through reliable data provided from high-quality clinical trials and achieving personalized, precise treatment management. Conclusion Targeted drugs hold remarkable potential for RAIR-DTC treatment, and emphasizing predictive factors for disease prognosis offers valuable guidance for medical practice.

Objective West Nile virus(WNV)is one of the most common mosquito-borne zoonotic viruses worldwide,with unique transmission dynamics and varied hosts.Lots of ecological and host factors have been reported to influence the host adaptation and transmission of WNVs,however,general genomic features of WNVs are less focused,except for some exact host-specific genotypes at molecular level.Artificial intelligence that analyzes genome composition characteristics currently shows significant advantages in identifying and predicting viral host adaptability.This research aimed to establish a convolutional neural network(CNN)model to predict the host adaptability of WNVs based on general genomic features.Methods Presently available WNV gene sequences were embedded for their genomic features with an embedding approach of dinucleotide composition representation(DCR).And DCR-based distribution difference of WNV samples among various hosts was performed with unsupervised learning methods.Then a classification model was built with a convolutional neural network(CNN)framework based on genomic DCR to evaluate the adaptation of the WNVs from birds,mammals and mosquitos.Additionally,host-specific amino acids in WNV proteins were inferred via Bayes method.Results DCR features could effectively distinguish host-specific WNVs.The trained CNN model predicted accurately mammalian susceptible WNVs from avian susceptible WNVs,however,much less accurately for mosquito/mammalian WNVs.Such predicted host adaptation was interpreted as host specified significance of biased amino acid distribution on the bayes-inferred sites in WNV proteins,implying a possible high significance of these sites for WNV adaptive phenotypes.Conclusions Genomic compositional features of WNVs are host-specific,and such genomic bias facilitates predicting the adaptation of WNVs to avian or mammalian hosts via deep learning methods.DCR-based decomposition is helpful to recognize the high risk of infecting mammals of WNVs.The present study provides a general knowledge of genomic features contributing to host adaptation to WNVs.

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.

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:To retrospectively analyze the results of auditory examination,vestibular function examination and laboratory examination of 63 patients diagnosed as vestibular neuritis.Methods:A total of 63 patients diagnosed with vestibular neuritis hospitalized in the Department of Otolaryngology, Head and Neck Surgery of the Third Affiliated Hospital of Sun Yat-sen University, from October 2012 to December 2022 were recruited. All patients met the diagnostic criteria for the 2022 Bárány association vestibular neuritis. Clinical data and the results of pure tone audiometry, electrocochleogram, video electronystagmogram, caloric test, cervical vestibuloevoked myogenic potential（cVEMP）, ocular vestibuloevoked myogenic potential（oVEMP）, video head impulse test（vHIT） was collected.A total of 63 age-and sex-matched healthy subjects in the physical examination center were randomly selected as the control group. The differences of blood indexs and lipid metabolism indexes between the two groups were compared. Results:In patients with vestibular neuritis, 50 out of 63 patients presented normal threshold in pure tone audiometry, 8 out of 63 patients had bilateral high-frequency sensorineural hearing loss and 5 out of 63 patients had unilateral mild high-frequency sensorineural hearing loss, 56 out of 63 cases completed the electrocochleogram, of which 3 cases had a binaural-SP/AP amplitude ratio≥0.4, 5 cases had monaural amplitude ratio ≥0.4. Fifty-five out of 63 patients completed the caloric test with CP values greater than 30% in all. The ratio of patients completed cVEMP, oVEMP and vHIT were 46 cases, 22 cases and 30 cases, respectively. 17 out of 63 cases completed all the four vestibular function tests. According to these tests, 49 patients could determine the extent of injury，including 27 cases with unilateral superior vestibular nerve injury, 21 cases with unilateral superior and inferior vestibular nerve injury and 1 case with unilateral inferior vestibular nerve injury. There were significant differences in neutrophil value（P<0.001）, lymphocyte value（P<0.005）, neutrophil/lymphocyte ratio（P<0.001） and apolipoprotein A1（P<0.001） between patient group and control group. Inflammatory markers were risk factors for patients with vestibular neuritis. The OR values of neutrophil value and blood neutrophil/lymphocyte ratio were 1.81（1.38-2.37, P<0.001） and 2.11（1.41-3.16, P<0.001）, respectively. Apolipoprotein A1 was a protective factor for patients with vestibular neuritis, and the OR value was 0.004（0.001-0.042, P<0.001）. Conclusion:Electrocochleogram could be used in vestibular neuritis patients with normal pure tone threshold to test whether there is hidden hearing loss in these patients. Neutrophil value, lymphocyte value, neutrophil/lymphocyte ratio and apolipoprotein A1 were correlated with vestibular neuritis. The Neutrophil value and neutrophil/lymphocyte ratio were risk factors for morbidity.
Humans ; Vestibular Neuronitis/physiopathology* ; Retrospective Studies ; Female ; Male ; Audiometry, Pure-Tone ; Hearing Loss, Sensorineural/physiopathology* ; Middle Aged ; Adult ; Vestibular Function Tests ; Vestibular Evoked Myogenic Potentials ; Aged

Pediatric vertigo presents with complex etiologies, and its clinical diagnosis and management can be challenging due to children's limited ability to describe their symptoms. Recurrent vertigo episodes in children, who are at a critical stage of development, can readily lead to emotional disorders in both the children themselves and their guardians. This article reports a case of benign paroxysmal vertigo of childhood（BPVC） in a child who sought care from multiple providers. The child was found to have a patent foramen ovale（PFO） and mild emotional disorder. By analyzing challenges encountered during the diagnostic and management process in this case of recurrent pediatric vertigo, this study provides practical guidance for rational selection of diagnostic techniques and the comprehensive assessment of disease status in pediatric vertigo/dizziness.
Child ; Humans ; Affective Symptoms/complications* ; Foramen Ovale, Patent/complications* ; Vertigo/complications*