Objective To summarize the liver biopsy and clinical features of patients with liver injury of unknown origin,and to investigate the value of ultrasound-guided percutaneous liver biopsy in the diagnosis of liver injury of unknown origin.Methods A retrospective analysis was performed for the clinical data and ultrasound-guided percutaneous liver biopsy results of 94 patients with liver injury of unknown origin who were admitted to Zhongshan Hospital,Xiamen University,from January 2018 to February 2023.According to the proportion of the patients with different final diagnoses,the patients were divided into autoimmune liver disease(AILD)group,metabolic associated fatty liver disease(MAFLD)group,drug-induced liver injury(DILI)group,alcoholic liver disease(ALD)group,and unknown group.An analysis of variance was used for comparison of normally distributed continuous data between multiple groups,and the Bonferroni analysis or the Dunnett'T3 test was used for further comparison between two groups;the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups;the Fisher's exact test was used for comparison of categorical data between multiple groups.Results All 94 patients with liver injury of unknown origin underwent ultrasound-guided percutaneous liver biopsy after admission,among whom 90 patients(95.7%)had a confirmed diagnosis based on liver biopsy and clinical features.There were 43 patients(45.7%)with AILD,21(22.3%)with MAFLD,15(16.0%)with DILI,6(6.4%)with ALD,1(1.1%)with AILD and MAFLD,1(1.1%)with hemochromatosis,1(1.1%)with Budd-Chiari syndrome,1(1.1%)with congenital hepatic fibrosis,and 1(1.1%)with idiopathic portal hypertension,while 4 patients(4.3%)still had an unknown etiology after liver biopsy.There were significant differences between the patients with top five diagnoses in age(F=4.457,P<0.05),body mass index(BMI)(F=3.245,P<0.05),aspartate aminotransferase(AST)(H=11.128,P<0.05),gamma-glutamyl transpeptidase(GGT)(H=24.789,P<0.05),alkaline phosphatase(ALP)(H=26.013,P<0.05),IgG(H=19.099,P<0.05),IgM(H=21.263,P<0.05),AMA-M2 positive rate(P<0.05),and ANA positive rate(P<0.05).Compared with the MAFLD group,the AILD group had significantly higher age,AST,GGT,and ALP and a significantly lower BMI;compared with the MAFLD group and the DILI group,the AILD group had significant increases in IgG and IgM;the AILD group had significant increases in the positive rates of AMA-M2 and ANA compared with the other four groups.Conclusion AILD,MAFLD,and DILI are the most common causes in patients with liver injury of unknown origin.Ultrasound-guided percutaneous liver biopsy plays an important role in determining the cause of liver injury of unknown origin,but it is still needed to make a comprehensive analysis based on clinical history,different types of liver injury,laboratory markers,and imaging data.

Ferroptosis is a new programmed cell death dependent on iron ions.Ferroptosis can be induced by endogenous or exogenous pathways,and cells exhibit specific cell morphological signs and are regulated by a variety of molecular mechanisms.In recent years,more and more studies have shown that ferroptosis plays an important role in the treatment of cancer.This article summarizes the mechanism of ferroptosis in bladder cancer and the regulation of cancer cells,as well as the role of ferroptosis-related factors,non-coding RNA regulation,N6-methyladenosine(m6A),amino acid metabolism and autophagy dependent ferroptosis in the growth and proliferation of bladder cancer,with a view to provide new strategies for the treatment of bladder cancer.

Endodontic diseases are a kind of chronic infectious oral disease.Common endodontic treatment concepts are based on the removal of inflamed or necrotic pulp tissue and the replacement by gutta-percha.However,it is very essential for endodontic treatment to debride the root canal system and prevent the root canal system from bacterial reinfection after root canal therapy(RCT).Recent research,encompassing bacterial etiology and advanced imaging techniques,contributes to our understanding of the root canal system's anatomy intricacies and the technique sensitivity of RCT.Success in RCT hinges on factors like patients,infection severity,root canal anatomy,and treatment techniques.Therefore,improving disease management is a key issue to combat endodontic diseases and cure periapical lesions.The clinical difficulty assessment system of RCT is established based on patient conditions,tooth conditions,root canal configuration,and root canal needing retreatment,and emphasizes pre-treatment risk assessment for optimal outcomes.The findings suggest that the presence of risk factors may correlate with the challenge of achieving the high standard required for RCT.These insights contribute not only to improve education but also aid practitioners in treatment planning and referral decision-making within the field of endodontics.

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment.However,irrigant selection or irrigation procedures are far from clear.The vapor lock effect in the apical region has yet to be solved,impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.Additionally,ambiguous clinical indications for root canal medication and non-standardized dressing protocols must be clarified.Inappropriate intracanal medication may present side effects and jeopardize the therapeutic outcomes.Indeed,clinicians have been aware of these concerns for years.Based on the current evidence of studies,this article reviews the properties of various irrigants and intracanal medicaments and elucidates their effectiveness and interactions.The evolution of different kinetic irrigation methods,their effects,limitations,the paradigm shift,current indications,and effective operational procedures regarding intracanal medication are also discussed.This expert consensus aims to establish the clinical operation guidelines for root canal irrigation and a position statement on intracanal medication,thus facilitating a better understanding of infection control,standardizing clinical practice,and ultimately improving the success of endodontic therapy.

The dental operative microscope has been widely employed in the field of dentistry, particularly in endodontics and operative dentistry, resulting in significant advancements in the effectiveness of root canal therapy, endodontic surgery, and dental restoration. However, the improper use of this microscope continues to be common in clinical settings, primarily due to operators' insufficient understanding and proficiency in both the features and established operating procedures of this equipment. In October 2019, Professor Jingping Liang, Vice Chairman of the Society of Cariology and Endodontology, Chinese Stomatological Association, organized a consensus meeting with Chinese experts in endodontics and operative dentistry. The objective of this meeting was to establish a standard operation procedure for the dental operative microscope. Subsequently, a consensus was reached and officially issued. Over the span of about four years, the content of this consensus has been further developed and improved through practical experience.
Humans ; Dentistry, Operative ; Consensus ; Endodontics ; Root Canal Therapy ; Dental Care

Digital guided therapy (DGT) has been advocated as a contemporary computer-aided technique for treating endodontic diseases in recent decades. The concept of DGT for endodontic diseases is categorized into static guided endodontics (SGE), necessitating a meticulously designed template, and dynamic guided endodontics (DGE), which utilizes an optical triangulation tracking system. Based on cone-beam computed tomography (CBCT) images superimposed with or without oral scan (OS) data, a virtual template is crafted through software and subsequently translated into a 3-dimensional (3D) printing for SGE, while the system guides the drilling path with a real-time navigation in DGE. DGT was reported to resolve a series of challenging endodontic cases, including teeth with pulp obliteration, teeth with anatomical abnormalities, teeth requiring retreatment, posterior teeth needing endodontic microsurgery, and tooth autotransplantation. Case reports and basic researches all demonstrate that DGT stand as a precise, time-saving, and minimally invasive approach in contrast to conventional freehand method. This expert consensus mainly introduces the case selection, general workflow, evaluation, and impact factor of DGT, which could provide an alternative working strategy in endodontic treatment.
Humans ; Consensus ; Endodontics/methods* ; Tooth ; Printing, Three-Dimensional ; Dental Care ; Cone-Beam Computed Tomography ; Root Canal Therapy

Osteoporosis (OP) is a systemic skeletal disease that primarily affects the elderly population, which greatly increases the risk of fractures. Here we report that Kindlin-2 expression in adipose tissue increases during aging and high-fat diet fed and is accompanied by decreased bone mass. Kindlin-2 specific deletion (K2KO) controlled by Adipoq-Cre mice or adipose tissue-targeting AAV (AAV-Rec2-CasRx-sgK2) significantly increases bone mass. Mechanistically, Kindlin-2 promotes peroxisome proliferator-activated receptor gamma (PPARγ) activation and downstream fatty acid binding protein 4 (FABP4) expression through stabilizing fatty acid synthase (FAS), and increased FABP4 inhibits insulin expression and decreases bone mass. Kindlin-2 inhibition results in accelerated FAS degradation, decreased PPARγ activation and FABP4 expression, and therefore increased insulin expression and bone mass. Interestingly, we find that FABP4 is increased while insulin is decreased in serum of OP patients. Increased FABP4 expression through PPARγ activation by rosiglitazone reverses the high bone mass phenotype of K2KO mice. Inhibition of FAS by C75 phenocopies the high bone mass phenotype of K2KO mice. Collectively, our study establishes a novel Kindlin-2/FAS/PPARγ/FABP4/insulin axis in adipose tissue modulating bone mass and strongly indicates that FAS and Kindlin-2 are new potential targets and C75 or AAV-Rec2-CasRx-sgK2 treatment are potential strategies for OP treatment.

Objective: Analyzing the characteristics of consonant errors in children with functional dysarthria in different age groups and the effect of speech training provides a reference for clinical treatment. Methods : This study followed medical ethics, and informed consent has been obtained from patients. Speech data from 388 patients with functional dysarthria were retrospectively studied. They were divided into two groups at the age of 6, namely, the preschool group (4-6 years old) of 226 patients and the school age group (6-13 years old, including 6 years old) of 162 patients. The characteristics of consonant pronunciation errors from four aspects were analyzed: average number of errors, pronunciation location, pronunciation method, and error type. One-on-one speech training was conducted, with a training frequency of once a week and once for 30 minutes. The training method was carried out in the order of phoneme training, syllable training, vocabulary training, sentence training, and short text and conversation training. The effects of speech training in the two groups were compared. Results: Analysis by pronunciation location: both age groups had the highest frequency of errors in tongue tip posterior sounds; the school age group had the lowest error frequency for labiodental consonants, and the preschool group had the lowest error frequency for bilabial consonants. According to the analysis of pronunciation mode, both age groups had the highest error frequency of aspirated affricate and the lowest error frequency of nasal sound. Analysis by error type: both age groups are mainly characterized by substitution and omission. Compared with the preschool group, most consonants of patients in the school group tend to improve in terms of pronunciation location, pronunciation mode, and error types. Compared with the preschool group, the two types of errors-palatalization and lateralization-increased in frequency in the school group, but the trend of increased lateralization was not statistically significant. After 6.7 and 5.5 sessions of speech training, the pronunciation of the preschool group and the school-age group significantly improved; the cure rate of the school-age group was 84.9% (118/139), and that of the preschool group was 77.1% (91/118). There was no statistically significant difference in the cure rate between the two groups. Conclusion Functional dysarthria may improve with age, but it may not completely self-heal. Children of different age groups can achieve good treatment results through scientific and reasonable speech training.

Purpose To explore the artificial intelligence(AI)-assisted diagnosis system of thyroid cancer based on deep transfer learning and evaluate its clinical application value.Methods The HE sections of 682 cases thyroid disease patients(including benign lesions,papillary carcinoma,follicular carci-noma,medullary carcinoma and undifferentiated carcinoma)in the Pathology Department of the Renmin Hospital of Wuhan Uni-versity were collected,scanned into digital sections,divided into training sets and internal test sets according to the ratio of 8 ∶ 2,and the training sets were labeled at the pixel level by patholo-gists.The thyroid cancer classification model was established u-sing VGG image classification algorithm model.In the process of model training,the parameters of the breast cancer region recog-nition model were taken as the initial values,and the parameters of the thyroid cancer region recognition model were optimized through the transfer learning strategy.Then the test set and 633 intraoperative frozen HE section images of thyroid disease in Jianli County People's Hospital,Jingzhou City,Hubei Province wereused as the external test set to evaluate the performance of the established AI-assisted diagnostic model.Results In the internal test set,without the use of the breast cancer region rec-ognition model transfer learning,the accuracy of the AI-assisted diagnosis model was 0.882,and the area under the Receiver op-erating characteristic(AUC)valuewas0.938;However,inthe use of the Transfer learning model,the accuracy of the AI-assis-ted diagnosis model for was 0.926,and the AUC value was 0.956.In the external test set,the accuracy of the zero learning model was 0.872,the AUC value was 0.915,and the accuracy of the Transfer learning model was 0.905,the AUC value was 0.930.Conclusion The AI-assisted diagnosis method for thy-roid cancer established in this study has good accuracy and gen-eralization.With the continuous development of pathological AI research,transfer learning can help improve the performance and generalization ability of the model,and improve the accura-cy of the diagnostic model.

Objective:To explore the risk factors for depression in patients with cognitive impairment and construct a prediction model to preliminarily validate the predictive performance of the model, aiming to provide medical and nursing staff with a screening tool for high-risk groups.Methods:From January 2020 to December 2021, convenience sampling was used to select 1 130 patients with cognitive impairment admitted to the Affiliated Brain Hospital of Nanjing Medical University as the research subject. The research subjects were divided into a modeling group ( n=791) and a validation group ( n=339) at a ratio of 7∶3. The influencing factors of depression in patients with cognitive impairment were determined using binomial Logistic regression and a risk prediction model was established. The predictive performance of the prediction model was tested using the receiver operating characteristic (ROC) curve. Results:The incidence of depression in 1 130 patients with cognitive impairment was 51.3% (580/1 130). Binomial Logistic regression analysis showed that the influencing factors for depression in patients included age, Activities of Daily Living Scale score, Hamilton Anxiety Scale score, Pittsburgh Sleep Quality Index score, and Lewy Body Composite Risk score ( P<0.05). In the modeling group, the area under the ROC curve was 0.921, the Youden index was 0.716, the sensitivity was 0.834, the specificity was 0.882, and the prediction accuracy was 0.858. In the validation group, the area under the ROC curve was 0.896, the Youden index was 0.651, the sensitivity was 0.824, the specificity was 0.827, and the prediction accuracy was 0.825. Conclusions:The depression risk prediction model can effectively predict the risk of depression in patients with cognitive impairment, and can provide a screening tool for high-risk groups for medical and nursing staff.