Hepatolenticular degeneration is a rare disease,and the number of cases of primary liver cancer occurring on the basis of liver cirrhosis caused by hepatolenticular degeneration is very small.This paper reports a case of hepatolenticular degeneration with primary liver cancer,and then reviews and summarizes current cases of this disease both domestically and internationally.
Humans ; Hepatolenticular Degeneration/complications* ; Liver Neoplasms/complications*

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.

Objective To investigate the value of first platelet count(PLT)to respiratory rate(RR)ratio(PLT/RR)on admission in the diagnosis and prognosis of secondary sepsis in pneumonia patients.Methods A total of 100 patients with pneumonia admitted to the First Affiliated Hospital of Army Medical University from May 2023 to August 2024 were selected as subjects.According to the presence or absence of pneumonia sepsis,they were divided into sepsis group(63 cases)and non-sepsis group(37 cases).The secondary sepsis in pneumonia pa-tients were followed up continuously for 30 d.According to the survival situation,they were divided into sur-vival group(54 cases)and death group(9 cases).PLT in peripheral blood was measured,vital signs were col-lected on the first day of admission,and PLT/RR was calculated.The receiver operating characteristic curve was used to evaluate the predictive value of PLT,RR and PLT/RR for secondary sepsis in pneumonia pa-tients.The systemic inflammatory response syndrome(SIRS)score,modified early warning score(MEWS)and quick sequential organ failure assessment(qSOFA)score on admission were calculated,and the clinical predictive value of SIRS score,MEWS and qSOFA score was compared.Results PLT and PLT/RR in sepsis group were lower than those in non-sepsis group(P<0.000 1),RR was higher than that in non-sepsis group(P<0.01).The area under the curve(AUC,95%CI)of PLT,RR and PLT/RR were 0.858(0.785-0.931),0.693(0.589-0.796)and 0.902(0.843-0.962),respectively.The optimal cut-off values were 146.5×109/L,20.5 per minute and 8.075,respectively.The specificity were 8.1%,83.8%and 2.7%,respec-tively.The sensitivity was 33.3%,50.8%and 30.2%,respectively.Compared with the non-sepsis group,the sepsis group had a significantly higher SIRS score(P<0.001),a significantly lower MEWS(P<0.000 1),and no significant difference in qSOFA score between the two groups(P>0.05).The AUC(95%CI)of SIRS score,MEWS and qSOFA score in predicting secondary sepsis in pneumonia patients were 0.717(0.616-0.818),0.748(0.650-0.846)and 0.505(0.389-0.622),respectively.The optimal cut-off values were 4.5,2.5 and 1.5 points,respectively.The specificity were 91.9%,2.7%and 100.0%,respectively.The sensitivity was 42.9%,33.3%and 6.3%,respectively.PLT and PLT/RR in death group were lower than those in sur-vival group(P<0.05),RR was higher than that in survival group(P<0.05).Secondary sepsis in pneumonia patients were followed up for 30 d,Kaplan-Meier survival curve showed that patients with PLT≤138.5×109/L had a lower 30 d survival rate(P=0.007 8).Patients with RR>24.5 per minute had a lower 30 d sur-vival rate(P=0.016 1).Patients with PLT/RR≤6.375 had a lower 30 d survival rate(P=0.002 3).Conclu-sion PLT/RR can be used as a biological index to predict secondary sepsis in pneumonia patients,which is better than SIRS score,MEWS and qSOFA score,and the prognosis of secondary sepsis in pneumonia patients with low PLT/RR is worse.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

The incidence rate of kidney diseases in China has always remained high.At present,the clinical treat-ment mainly focuses on symptomatic treatment to delay the progression of the disease,and there is a lack of eco-nomical and effective treatment methods.MicroRNA plays an important regulatory role in the occurrence and devel-opment of diseases.This study aims to explore the role and regulatory mechanism of miR-142a-3p in adriamycin(ADR)-induced renal tubular epithelial cell(TCMK-1)injury,with a focus on its potential as a therapeutic target for ADR nephropathy.First,cell viability was assessed using the CCK-8 kit,and a mouse renal tubular epithelial cell model induced by ADR was established.Subsequently,alterations in miR-142a-3p and its target gene ATG16L1 mRNA levels were quantified using RT-qPCR.Western blotting was used to detect the protein levels of autophagy marker proteins and pyroptosis marker proteins.Monodansylcadaverin(MDC)staining was performed and the autophagy of cells was detected by flow cytometry.The results showed that the relative expression of miR-142a-3p in TCMK-1 cells induced by ADR was increased and the relative expression of its target gene ATG16L1 was decreased(P＜0.0001).Western blotting results showed that the levels of p62(P＜0.001)and pyroptosis-related proteins(P＜0.001)were increased,while the protein levels of autophagy-related proteins were decreased(P＜0.05).The flow cytometry results showed that there was no difference in the mean fluorescence intensity of autoph-agosomes between the ADR group and the autophagosome inhibitor group(3-MA group)(P＞0.05),indicating that after ADR induction,cell autophagy was inhibited and pyroptosis was enhanced.When the expression of miR-142a-3p was inhibited by transfecting miR-142a-3p inhibitor,the relative expression level of the target gene ATG16L1 was restored(P＜0.001).Western blotting showed that the protein level of p62(P＜0.01)and pyropto-sis-related proteins(P＜0.01)were decreased,and the protein level of autophagy-related proteins was restored(P＜0.001).Flow cytometry results further indicated that cell autophagy was restored(P＜0.0001).In conclusion,ADR targets A TG1 6L1 through miR-142a-3p to reduce the autophagy level of TCMK-1,and simultaneously activates GSDMD-mediated pyroptosis.

Premenstrual dysphoric disorder (PMDD) is considered a severe form of premenstrual syndrome (PMS). As a key brain region involved in emotional regulation and stress responses, the amygdala has been implicated in the pathogenesis of PMS/PMDD. The amygdala is composed of multiple subregions, each playing distinct roles in emotion, memory, and stress responses, and forms complex brain areas. Summarizing the interconnections among amygdala, subregions and their connectivity with external areas, and exploringt the neuroimaging characteristics of the amygdala, as well as changes in its neural circuits and brain networks in these patients, will help provide a theoretical foundation for targeted modulation of amygdala function in the treatment of PMS/PMDD.
Humans ; Amygdala/diagnostic imaging* ; Female ; Premenstrual Dysphoric Disorder/pathology* ; Premenstrual Syndrome/pathology* ; Emotions/physiology* ; Magnetic Resonance Imaging

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Instrument separation is a critical complication during root canal therapy, impacting treatment success and long-term tooth preservation. The etiology of instrument separation is multifactorial, involving the intricate anatomy of the root canal system, instrument-related factors, and instrumentation techniques. Instrument separation can hinder thorough cleaning, shaping, and obturation of the root canal, posing challenges to successful treatment outcomes. Although retrieval of separated instrument is often feasible, it carries risks including perforation, excessive removal of tooth structure and root fractures. Effective management of separated instruments requires a comprehensive understanding of the contributing factors, meticulous preoperative assessment, and precise evaluation of the retrieval difficulty. The application of appropriate retrieval techniques is essential to minimize complications and optimize clinical outcomes. The current manuscript provides a framework for understanding the causes, risk factors, and clinical management principles of instrument separation. By integrating effective strategies, endodontists can enhance decision-making, improve endodontic treatment success and ensure the preservation of natural dentition.
Humans ; Root Canal Therapy/adverse effects* ; Consensus ; Root Canal Preparation/adverse effects*