Objective To investigate the diversity and composition of gut fungi microbiota in patients with polycystic kidney disease(PKD)and its correlation with clinical indicators.Methods A total of 44 PKD patients,44 patients with non-polycystic chronic kidney disease(NPCKD)and 22 healthy controls(HC)admitted to our hospital from February 2023 to February 2024 were recruited.ITS1 DNA sequencing was applied to analyze the gut fungal composition.Bioinformatics analysis was used to compare the diversity and structural differences of fungi among the 3 groups.Pearson correlation analysis was performed to analyze the relationship between gut fungi and clinical indicators.Results There were no significant differences in baseline characteristics(gender,age,body mass index,etc.)among the 3 groups,but statistical differences were seen in terms of serum indicators(such as serum creatinine,blood urea nitrogen,uric acid,estimated glomerular filtration rate,etc.)(P<0.01).Alpha diversity analysis showed no significant difference was seen between the PKD and HC groups,but the PKD group had significant differences to the NPCKD group(P<0.01).Beta diversity analysis revealed significant differences among the 3 groups and in pairwise comparisons(P=0.001).Fungi composition analysis found that the abundance of Candida was significantly higher in the PKD group than the other 2 groups(P<0.01),while the abundances of Aspergillus and Cladosporium were significantly lower in the PKD group than the HC group(P<0.05).Linear discriminant analysis(LEFSe)indicated that Candida was significantly enriched,while Aspergillus and Cladosporium were significantly reduced in the PKD group.Correlation analysis revealed that the abundance of Cladosporium was negatively correlated with cyst diameter and immunoglobulin light chain Kappa/Lambda ratio in the PKD group(P<0.05),while the abundance of Candida was positively correlated with liver/kidney cyst diameter(P<0.01).Conclusion PKD patients exhibit characteristic changes in gut fungi diversity and composition.The abundances of Cladosporium and Candida are closely associated with clinical indicators of PKD patients.

Objective To compare the gut fungal composition between gout patients and healthy individuals through high-throughput sequencing of ribosomal DNA internal transcribed spacer 1(ITS1).Methods Gout patients and healthy volunteers who visited our hospital from January 2023 to December 2024 were enrolled in this study.Then based on established medical guidelines,the gout patients were categorized into 3 groups:Group H(asymptomatic hyperuricemia,n=14),Group G(acute gouty arthritis,n=14),and Group I(intercritical period of gouty arthritis,n=15),and the healthy individuals were assigned into Group N(n=9).Fecal samples were collected from all the participants to undergo ITS1 sequencing analysis.The differences in diversity and composition of gut mycobiome,and FunGuild-derived fungal functions and nutritional status were compared among the 4 groups,and the correlation between the gut mycobiome and clinical indicators was analyzed.Results There were no significant differences in baseline features such as gender,age,glomerular filtration rate(GFR),and levels of serum creatinine(SCr)and serum urea among Group N and other gout groups,but obvious differences were observed in body mass index(BMI),erythrocyte sedimentation rate,and levels of C-reactive protein(CRP),serum uric acid(SUA),and IL-1β and IL-6(P<0.05).In terms of gut fungal diversity,ITS1 analysis showed there were no statistical differences in α-diversity or the principal coordinate analysis(PCoA)of β-diversity among the groups.However,as gout progressed,significant changes were observed in β-diversity indices,indicating a shift in the gut fungal community composition with disease advancement(P<0.05).The phyla Ascomycota,Basidiomycota,and Mucoromycotina were the dominant fungal phyla in all groups.Compared with the other 3 gout groups,the abundance of Pichia was significantly increased in Group N(P<0.05),that of Saccharomyces was in Group H(P<0.05),and that of Starmerella was in Group G(P<0.05).Correlation analysis between the gut mycobiome and clinical indices indicated that the relative abundance of Starmerella was significantly positively correlated with IL-1β(P<0.01)and IL-6(P<0.05).The relative abundance of Pichia was significantly positively correlated with IL-1β and IL-6 levels(P<0.05),and negatively correlated with serum urea level(P<0.05),and the relative abundance of Saccharomyces was negatively correlated with IL-1β and IL-6 levels(P<0.05).Conclusion There exist significant alterations in both the diversity and composition of gut fungi among patients with gout at various stages.Notably,the fluctuations in the relative abundance of Starmerella,Pichia and Saccharomyces appear to correlate with key clinical indicators.

Objective To analyze the diversity and composition of gut microbiota in individuals with circadian rhythm disruption and their correlation with cognition.Methods Night shift workers and regular shift workers were subjected from our hospital during August 2022 and October 2024.The participants with circadian rhythm disorders were assigned into an experimental group(n=24),and those with normal circadian rhythms were into a control group(n=24).Their height,weight,age,gender,body mass index(BMI)and fresh fecal samples were collected,and Montreal Cognitive Assessment(MoCA)and Mini-Mental State Examination(MMSE)were used to evaluate their mental status.Metagenomics,Alpha and Beta diversity analyses,Linear Discriminant Analysis Effect Size(LEfSe),and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis were employed to investigate the diversity and function characteristics of gut microbiota in the participants.Results There were no statistical differences between the 2 groups in baseline data,such as height,weight,gender,age,and BMI(P>0.05).Alpha diversity analysis indicated that no statistical differences were observed in the ACE,Chao1,Shannon,or Simpson indices between the 2 groups,while beta diversity analysis revealed significant differences(P<0.01),suggesting different structure of gut microbiota between them.In the experimental group,the abundance of Faecalibacterium prausnitzii and Agathobacter rectalis was decreased,while that of Escherichia coli and Phocaeicola vulgaratus was increased,with significant differences when compared with the control group(P<0.05).Additionally,KEGG functional analysis showed that the experimental group had obviously higher expression levels in Th17 cell differentiation and the IL-17 signaling pathway than the control group(P<0.05).Agathobacter rectalis and Faecalibacterium prausnitzii were positively correlated with MoCA score and MMSE score(P<0.05,P<0.01).Agathobacter rectalis was negatively correlated with the IL-17 signaling pathway and Th17 cell differentiation.Conclusion Individuals with circadian rhythm disorders have significant changes in the structure and function of gut microbiota when compared to those with normal circadian rhythms.Agathobacter rectalis may be involved in the regulation of the IL-17 signaling pathway and differentiation of Th17 cells,thereby possibly impacting the increases of cognitive score related to circadian rhythm disorders.

OBJECTIVE To construct a remotely contactless intelligent sleep monitoring system(RCISMS),which could be used to assist the titration of Mandibular advancement device(MAD)for the patients of obstructive sleep apnea-hypopnea syndrome(OSAHS),and to verify the effectiveness of the system.METHODS RCISMS was constructed by multidisciplinary medical-engineering cooperation of clinical medicine,biosensing technology,and artificial intelligence;And the diagnostic and therapeutic efficacy evaluation of RCISMS was improved through clinical comparative tests.From December 2023 to May 2024,A total of 176 patients who would receive polysomnography(PSG)evaluation were prospectively collected in the Department of Otolaryngology,Beijing Jishuitan Hospital,Capital Medical University.All the patients met the inclusion criteria and underwent synchronized sleep monitoring using RCISMS and PSG.Through repeatedly comparison with the'gold standard'PSG,the intelligent algorithm of Apnea-hypopnea index(AHI)which is the diagnosis and efficacy of OSAHS was improved in RCISMS.The consistency and correlation of the results between RCISMS and PSG were statistically analyzed.RESULTS RCISMS can continuously monitor the patient's natural sleep in a remote,non-direct contact way,and can upload data in real time,analyze and diagnose intelligently,and the results can be distributed to the doctor and the patient simultaneously.Among the parameters monitored by RCISMS,the AHI,lowest peripheral oxygen saturation(LSpO2),mean peripheral oxygen saturation(MSpO?),sleep efficiency,and the proportion of light sleep stage showed strong correlation with the corresponding PSG parameters(all P<0.05).The LSpO2 and the proportion of light sleep stage showed no statistically significant differences between the two monitoring methods.The consistency test between RCISMS and PSG for AHI classification yielded a Kappa value of 0.627(P<0.001),indicating moderate agreement.The efficacy evaluation of RCISMS for MAD treatment assessment demonstrated 73.8%sensitivity and 100%specificity for OSAHS detection,which helped to precisely identify patients who had achieved full recovery at the endpoint of MAD titration.RCISMS demonstrated sensitivities of 73.8%,84.8%,and 92.7%for detecting mild,moderate,and severe OSAHS respectively,with corresponding specificities of 78.4%,91.6%,and 95.9%.This system can objectively reflect therapeutic changes during MAD titration.CONCLUSION This study established the RCISMS,which provided a novel titration procedure for the MAD titration of OSAHS patients,and might potentially overcome existing limitations in current clinical MAD titration procedures.

Objective To analyze the characteristics of methadone-related poisoning cases and provide a reference for forensic identification.Methods A total of 71 cases of methadone-related poisoning re-ported from 1998 to 2023 in China and 26 cases of methadone-related deaths reported from 2013 to 2018 in Italy were retrieved from databases including PubMed,Wanfang and CNKI.The general infor-mation,forensic pathological and toxicological characteristics were analyzed.Results Among the 71 methadone-related poisoning cases in China,there were 54 cases(76.06%)of poisoning without death and 17 cases(23.94%)of death from poisoning.There were 54 male cases(76.06%),and 51 cases(71.83%)aged 19 to 39 years old.There were 35 cases(49.30%)of poisoning caused by methadone alone,and 32 cases(45.07%)were poisoning caused by methadone combined with other substances or drugs including heroin and benzodiazepines.Most of the poisoned showed coma,respiratory depres-sion and miosis.Signs of asphyxia were often found by autopsy.The mass concentration of methadone detected in the blood of 6 deceased ranged from 0.112 to 3.000 mg/L.Among the 26 methadone-related deaths in Italy,22 cases were male(84.62%).There were 6 cases(23.08%)caused by methadone alone,and 20 cases(76.92%)died from methadone combined with other substances or drugs.The mass concentration of methadone in blood ranged from 0.181 to 4.059 mg/L.Conclusion The propor-tions of poisoning cases caused by methadone alone and methadone combined with other substances or drugs are comparable in China.The majority of deceased caused by methadone poisoning shows typi-cal triad of coma,respiratory depression and miosis,which helps forensic experts determine the cause of death related to methadone.Additionally,it is necessary to increase the routine testing of the con-centration of methadone and its combined substances or drugs in deceased,and collect data for the in-terpretation of the results of related cases.

Objective: To explore the risk of endometrial polyp (EP) based on lipid metabolism and vaginal micro- ecology combined with uterine volume line drawing model. Methods: 143 EP patients treated by hysteroscopic sur- gery were selected as the experimental group , and 113 healthy women were selected as the control group at the same time. The data were randomly divided into training set and validation set according to the ratio of 7 : 3. The clinical data of the two groups were collected and recorded , and t/χ2 test , LASSO regression and multifactorial lo- gistic regression analysis were used to screen the independent risk factors , construct the prediction model , and draw the column line graph. The performance of the model was evaluated by applying subject operating characteristic (ROC) curves , calibration curves , Hosmer-Lemeshow test and clinical decision-making (DCA) curves. Results: Multifactorial logistic regression analysis showed that total cholesterol ( TC) , low-density lipoprotein cholesterol (LDL-C) , vaginal microecological balance , and uterine volume were independent risk factors for the development of EP. ROC curve analysis showed that the AUC values of the training and validation sets of the column line graph model were 0. 935 and 0. 887 , respectively , and its sensitivity and specificity were 90. 21% , 83. 46% and 86. 29% , 80. 66% respectively , The Hosmer-Lemeshow test showed that the model fits well ( training set : χ2 = 2. 261 , P = 0. 840 ; validation set : χ2 = 4. 837 , P = 0. 441) and the calibration curves of the training and validation sets were close to the ideal curves , which indicated that the model had good prediction accuracy; the analysis of DCA curves of the training and validation sets both showed that the column-line graph model had a good clinical benefit rate in predicting EP. Conclusion TC , LDL-C , vaginal microecological balance and uterine volume are independent risk factors for EP , and the column-line diagram model constructed by the model has high clinical ben- efit , calibration and accuracy in predicting the risk of EP.

[Objective] To analyse and predict the tendencies of using erythrocyte blood in Changsha based on the autoregressive integrated moving average (ARIMA) model, long short-term memory (LSTM) and ARIMA-LSTM combination model, so as to provide reliable basis for designing a feasible and effective blood inventory management strategy. [Methods] The data of erythrocyte usage from hospitals in Changsha between January 2012 and December 2023 were collected, and ARIMA model, LSTM model and ARIMA-LSTM combination model were established. The actual erythrocyte consumption from January to May 2024 were used to assess and verify the prediction effect of the models. The extrapolation prediction accuracy of the models were tested using two evaluation indicators: mean absolute percentage error (MAPE) and root mean square error (RMSE), and then the prediction performance of the model was compared. [Results] The RMSE of LSTM model, optimal model ARIMA(1,1,1)(1,1,1)12 and ARIMA-LSTM combination model were respectively 5 206.66, 3 096.43 and 2 745.75, and the MAPE were 18.78%,11.54% and 9.76% respectively, which indicated that the ARIMA-LSTM combination model was more accurate than the ARIMA model and LSTM model, and the prediction results was basically consistent with the actual situation. [Conclusion] The ARIMA-LSTM model can better predict the clinical erythrocyte consumption in Changsha in the short term.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

With the growing emphasis on maternal and child oral health, the significance of managing oral health across preconception, pregnancy, and infancy stages has become increasingly apparent. Oral health challenges extend beyond affecting maternal well-being, exerting profound influences on fetal and neonatal oral development as well as immune system maturation. This expert consensus paper, developed using a modified Delphi method, reviews current research and provides recommendations on maternal and child oral health management. It underscores the critical role of comprehensive oral assessments prior to conception, diligent oral health management throughout pregnancy, and meticulous oral hygiene practices during infancy. Effective strategies should be seamlessly integrated across the life course, encompassing preconception oral assessments, systematic dental care during pregnancy, and routine infant oral hygiene. Collaborative efforts among pediatric dentists, maternal and child health workers, and obstetricians are crucial to improving outcomes and fostering clinical research, contributing to evidence-based health management strategies.
Humans ; Pregnancy ; Female ; Infant ; Consensus ; Mouth Diseases/therapy* ; Pregnancy Complications/therapy* ; Oral Health ; Infant, Newborn ; Delphi Technique ; Oral Hygiene

ObjectiveTo learn the density and seasonal variation of adult mosquitoes in Pudong New Area of Shanghai, and to explore the influence of meteorological factors on the density of adult mosquitoes. MethodsFrom April to November in 2017‒2021, adult mosquito density in Pudong New Area was monitored every ten days a time by using CO₂ trapping light method. Meteorological data were collected during the same time, and Pearson correlation analysis and multiple linear regression model were used to investigate the correlation between adult mosquito density and meteorological factors. ResultsThe seasonal variation of adult mosquito density showed a single-peak pattern, with the peak of 7.09 mosquitoes·(set·time)^-1 in July. The adult mosquito density was positively correlated with the monthly average temperature, monthly maximum temperature, monthly minimum temperature, and monthly average relative humidity (r=0.813, 0.793, 0.820, 0.617, all P<0.05), but negatively correlated with monthly average air pressure (r=-0.738, P<0.05). The regression equation of the adult mosquito density and monthly minimum temperature in Pudong New Area of Shanghai was Y=0.066 X₃-0.884, with a corrected R² of 0.673, indicating a good model fitting. ConclusionThe overall seasonal variation of adult mosquito density in Pudong New Area showed a single-peak pattern. The density of adult mosquitoes was correlated with the monthly average temperature, monthly maximum temperature, monthly minimum temperature, monthly average relative humidity, and monthly average air pressure, and linearly correlated with monthly minimum temperature.