The structure of intestinal tissue is complex. In vitro simulation of intestinal structure and function is important for studying intestinal development and diseases. Recently, organoids have been successfully constructed and they have come to play an important role in biomedical research. Organoids are miniaturized three-dimensional (3D) organs, derived from stem cells, which mimic the structure, cell types, and physiological functions of an organ, making them robust models for biomedical research. Intestinal organoids are 3D micro-organs derived from intestinal stem cells or pluripotent stem cells that can successfully simulate the complex structure and function of the intestine, thereby providing a valuable platform for intestinal development and disease research. In this article, we review the latest progress in the construction and application of intestinal organoids.
Organoids/cytology* ; Intestines/physiology* ; Humans ; Animals ; Pluripotent Stem Cells

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objectives: This study evaluates the efficacy of a new temporomandibular joint (TMJ) capsule suspension technique for stabilizing the TMJ after free fibular flap reconstruction of the mandibular condyle. Patients and Methods: Patients undergoing the TMJ capsule suspension technique during free fibular flap reconstruction after mandibulectomy with condylectomy (study group; n=9) were compared with a control group (n=9). Mandibular movement trajectory and surface electromyographic signals of bilateral masseters were recorded. The neocondyle–disc relationship was examined with magnetic resonance imaging (MRI) at 6 months after surgery. Results: Maximal mouth opening and bilateral marginal movement distances were comparable between the two groups (P>0.05). The asymmetry index of the condyle path length was significantly higher in controls (P=0.02). Bilateral mouth opening trajectories were symmetric in 7 patients and deviated to the affected side in 2 patients in the study group; they deviated to the affected side in all controls. The mean electromyographic values of the masseter on the affected side in resting, maximum bite, and chewing states were comparable between the two groups (P=0.13, P=0.65, and P=0.82, respectively). On MRI at 6 months, the thicknesses of the anterior, medial, and posterior bands and TMJ disc length were similar on the affected and normal sides in the study group (P=0.57, P=0.13, P=0.48, and P=0.87, respectively). Conclusion The proposed TMJ capsule suspension technique could improve postoperative TMJ structure and function after fibular free flap reconstruction following mandibulectomy with condylectomy.

Objectives: This study evaluates the efficacy of a new temporomandibular joint (TMJ) capsule suspension technique for stabilizing the TMJ after free fibular flap reconstruction of the mandibular condyle. Patients and Methods: Patients undergoing the TMJ capsule suspension technique during free fibular flap reconstruction after mandibulectomy with condylectomy (study group; n=9) were compared with a control group (n=9). Mandibular movement trajectory and surface electromyographic signals of bilateral masseters were recorded. The neocondyle–disc relationship was examined with magnetic resonance imaging (MRI) at 6 months after surgery. Results: Maximal mouth opening and bilateral marginal movement distances were comparable between the two groups (P>0.05). The asymmetry index of the condyle path length was significantly higher in controls (P=0.02). Bilateral mouth opening trajectories were symmetric in 7 patients and deviated to the affected side in 2 patients in the study group; they deviated to the affected side in all controls. The mean electromyographic values of the masseter on the affected side in resting, maximum bite, and chewing states were comparable between the two groups (P=0.13, P=0.65, and P=0.82, respectively). On MRI at 6 months, the thicknesses of the anterior, medial, and posterior bands and TMJ disc length were similar on the affected and normal sides in the study group (P=0.57, P=0.13, P=0.48, and P=0.87, respectively). Conclusion The proposed TMJ capsule suspension technique could improve postoperative TMJ structure and function after fibular free flap reconstruction following mandibulectomy with condylectomy.

Objectives: This study evaluates the efficacy of a new temporomandibular joint (TMJ) capsule suspension technique for stabilizing the TMJ after free fibular flap reconstruction of the mandibular condyle. Patients and Methods: Patients undergoing the TMJ capsule suspension technique during free fibular flap reconstruction after mandibulectomy with condylectomy (study group; n=9) were compared with a control group (n=9). Mandibular movement trajectory and surface electromyographic signals of bilateral masseters were recorded. The neocondyle–disc relationship was examined with magnetic resonance imaging (MRI) at 6 months after surgery. Results: Maximal mouth opening and bilateral marginal movement distances were comparable between the two groups (P>0.05). The asymmetry index of the condyle path length was significantly higher in controls (P=0.02). Bilateral mouth opening trajectories were symmetric in 7 patients and deviated to the affected side in 2 patients in the study group; they deviated to the affected side in all controls. The mean electromyographic values of the masseter on the affected side in resting, maximum bite, and chewing states were comparable between the two groups (P=0.13, P=0.65, and P=0.82, respectively). On MRI at 6 months, the thicknesses of the anterior, medial, and posterior bands and TMJ disc length were similar on the affected and normal sides in the study group (P=0.57, P=0.13, P=0.48, and P=0.87, respectively). Conclusion The proposed TMJ capsule suspension technique could improve postoperative TMJ structure and function after fibular free flap reconstruction following mandibulectomy with condylectomy.

Objective To analyze the pathogenic characteristics and drug sensitivity of candidaemia,and construct a short-term mortality risk prediction scoring model.Methods The clinical data of patients with candidaemia admitted to the 909 Hospital of Joint Logistics Support Force from January 2011 to December 2020 were retrospectively analyzed,and the composition of pathogen composition,drug sensitivity test results and incidence of hospitalized patients were analyzed.324 cases of candidaemia were randomly divided into modeling group(190 cases)and validation group(134 cases),and the risk factors were screened by binary logistic regression.According to the odds ratio(OR)score,the 30 day mortality risk prediction scoring model was constructed,and the predictive performance of the model was verified both in modeling and validation groups.Results 356 strains of Candida including 126 strains of C.albicans(35.39%),79 strains of C.tropicalis(22.19%),74 strains of C.parapsilosis(20.79%),48 strains of C.glabrata(13.48%),14 strains of C.guilliermondii(3.93%),8 strains of C.krusei(2.25%),and 7 strains of other Candida(1.97%)were detected in 336 patients with candidemia.The incidence of candidaemia among hospitalized patients increased from 0.20 ‰ in 2011 to 0.48 ‰ in 2020.The resistance rate of candida to amphotericin B was significantly lower than that of fluconazole,voriconazole and itraconazole(P＜0.05).Among the 324 cases included in the model,95 patients died in 30 days after diagnosis,and the mortality rate was 29.32%.The proportion of males,fever,and parenteral nutrition in modeling group was significantly higher than that in validation group(P＜0.05),while the proportion of chronic lung disease and surgical history within one month were lower than those in validation group(P＜0.05).Logistic regression analysis showed that chronic renal failure,mechanical ventilation,severe neutropenia,failure to receive anti-fungal treatment within 72 hours,and APACHE Ⅱ≥20 were risk factors for short-term death of candidaemia,the OR values were 3.179,1.970,2.979,2.080,and 2.399,and the risk scores were 6,4,6,4,and 5,respectively.The area under the curve(AUC)of the risk scoring model for modeling group was 0.792(95%CI 0.721-0.862),and the result of Hosmer-Lemeshow(H-L)test was P=0.305;The AUC of validation group was 0.796(95%CI 0.735-0.898),and the H-L test result was P=0.329.A risk score≤8 indicated a low risk group for short-term mortality,a score of 9-15 indicated a medium risk group,and a score≥16 indicated a high risk group.Conclusions The incidence of candidemia in hospitalized patients is increasing and the mortality is high.The risk prediction score model can effectively predict the short-term prognosis and facilitate the early identification of the prognosis.

Objective Gallstone disease(GSD)is one of the common digestive tract diseases with a high worldwide prevalence.The effects of GSD on patients include but are not limited to the symptoms of nausea,vomiting,and biliary colic directly caused by GSD.In addition,there is mounting evidence from cohort studies connecting GSD to other conditions,such as cardiovascular diseases,biliary tract cancer,and colorectal cancer.Early identification of patients at a high risk of GSD may help improve the prevention and control of the disease.A series of studies have attempted to establish prediction models for GSD,but these models could not be fully applied in the general population due to incomplete prediction factors,small sample sizes,and limitations in external validation.It is crucial to design a universally applicable GSD risk prediction model for the general population and to take individualized intervention measures to prevent the occurrence of GSD.This study aims to conduct a multicenter investigation involving more than 90 000 people to construct and validate a complete and simplified GSD risk prediction model.Methods A total of 123 634 participants were included in the study between January 2015 and December 2020,of whom 43 929 were from the First Affiliated Hospital of Chongqing Medical University(Chongqing,China),11 907 were from the First People's Hospital of Jining City(Shandong,China),1 538 were from the Tianjin Medical University Cancer Institute and Hospital(Tianjin,China),and 66 260 were from the People's Hospital of Kaizhou District(Chongqing,China).After excluding patients with incomplete clinical medical data,35 976 patients from the First Affiliated Hospital of Chongqing Medical University were divided into a training data set(n=28 781,80% )and a validation data set(n=7 195,20% ).Logistic regression analyses were performed to investigate the relevant risk factors of GSD,and a complete risk prediction model was constructed.Factors with high scores,mainly according to the nomograms of the complete model,were retained to simplify the model.In the validation data set,the diagnostic accuracy and clinical performance of these models were validated using the calibration curve,area under the curve(AUC)of the receiver operating characteristic curve,and decision curve analysis(DCA).Moreover,the diagnostic accuracy of these two models was validated in three other hospitals.Finally,we established an online website for using the prediction model(The complete model is accessible at https://wenqianyu.shinyapps.io/Completemodel/,while the simplified model is accessible at https://wenqianyu.shinyapps.io/Simplified/).Results After excluding patients with incomplete clinical medical data,a total of 96 426 participants were finally included in this study(35 876 from the First Affiliated Hospital of the Chongqing Medical University,9 289 from the First People's Hospital of Jining City,1 522 from the Tianjin Medical University Cancer Institute,and 49 639 from the People's Hospital of Kaizhou District).Female sex,advanced age,higher body mass index,fasting plasma glucose,uric acid,total bilirubin,gamma-glutamyl transpeptidase,and fatty liver disease were positively associated with risks for GSD.Furthermore,gallbladder polyps,total cholesterol,high-density lipoprotein cholesterol,low-density lipoprotein cholesterol,and aspartate aminotransferase were negatively correlated to risks for GSD.According to the nomograms of the complete model,a simplified model including sex,age,body mass index,gallbladder polyps,and fatty liver disease was constructed.All the calibration curves exhibited good consistency between the predicted and observed probabilities.In addition,DCA indicated that both the complete model and the simplified model showed better net benefits than treat-all and treat-none.Based on the calibration plots,DCA,and AUCs of the complete model(AUC in the internal validation data set=74.1%[95% CI:72.9%-75.3%],AUC in Shandong=71.7%[95% CI:70.6%-72.8%],AUC in Tianjin=75.3%[95% CI:72.7%-77.9%],and AUC in Kaizhou=72.9%[95% CI:72.5%-73.3%])and the simplified model(AUC in the internal validation data set=73.7%[95% CI:72.5%-75.0%],AUC in Shandong=71.5%[95% CI:70.4%-72.5%],AUC in Tianjin=75.4%[95% CI:72.9%-78.0%],and AUC in Kaizhou=72.4%[95% CI:72.0%-72.8%]),we concluded that the complete and simplified risk prediction models for GSD exhibited excellent performance.Moreover,we detected no significant differences between the performance of the two models(P>0.05).We also established two online websites based on the results of this study for GSD risk prediction.Conclusions This study innovatively used the data from 96 426 patients from four hospitals to establish a GSD risk prediction model and to perform risk prediction analyses of internal and external validation data sets in four cohorts.A simplified model of GSD risk prediction,which included the variables of sex,age,body mass index,gallbladder polyps,and fatty liver disease,also exhibited good discrimination and clinical performance.Nonetheless,further studies are needed to explore the role of low-density lipoprotein cholesterol and aspartate aminotransferase in gallstone formation.Although the validation results of the complete model were better than those of the simplified model to a certain extent,the difference was not significant even in large samples.Compared with the complete model,the simplified model uses fewer variables and yields similar prediction and clinical impact.Hence,we recommend the application of the simplified model to improve the efficiency of screening high-risk groups in practice.The use of the simplified model is conducive to enhancing the self-awareness of prevention and control in the general population and early intervention for GSD.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly common liver disease worldwide. MAFLD is diagnosed based on the presence of steatosis on images, histological findings, or serum marker levels as well as the presence of at least one of the three metabolic features: overweight/obesity, type 2 diabetes mellitus, and metabolic risk factors. MAFLD is not only a liver disease but also a factor contributing to or related to cardiovascular diseases (CVD), which is the major etiology responsible for morbidity and mortality in patients with MAFLD. Hence, understanding the association between MAFLD and CVD, surveillance and risk stratification of MAFLD in patients with CVD, and assessment of the current status of MAFLD management are urgent requirements for both hepatologists and cardiologists. This Taiwan position statement reviews the literature and provides suggestions regarding the epidemiology, etiology, risk factors, risk stratification, nonpharmacological interventions, and potential drug treatments of MAFLD, focusing on its association with CVD.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.