ObjectiveTo investigate the trends in diabetes mortality and potential years of life lost (PYLL) among residents of Huangpu District, Shanghai from 1993 to 2021, to analyze the long-term trends of diabetic patients with different characteristics and to provide a reference for scientific prevention and control of diabetes in aging urban areas. MethodsDiabetes mortality data were obtained from the Huangpu District cause of death registration records in the Shanghai death cause registration system. Indicators such as crude mortality rate, standardized mortality rate, potential years of life lost (PYLL), average years of life lost (AYLL), annual percentage change (APC), and average annual percentage change (AAPC) were used to analyze diabetes-related mortality and life loss. Statistical analyses were performed using software SPSS 21.0 and Joinpoint 5.0.2. ResultsFrom 1993 to 2021, the average annual crude mortality rate of diabetes in Huangpu District was 46.56/100 000, and the average annual standardized mortality rate was 20.44/100 000. The crude mortality rate and standardized mortality rate of diabetes for female residents were higher than those for males. The crude mortality rate showed an overall increasing trend [AAPC=2.81% (95%CI: 0.20%‒5.49%), P<0.05], while the increase in standardized mortality rate significantly slowed [AAPC=0.15% (95%CI: -2.27%‒2.63%)], P<0.05]. The mortality rate rose rapidly in the 70‒74 years age group and peaked in the 85‒ years age group (607.69/100 000). Diabetes accounted for a cumulative PYLL of22 741 person-years, with an average annual AYLL of 1.88 years and an average annual potential years of life lost rate (PYLLR) of 0.82‰. Male residents had higher PYLL, AYLL, and PYLLR than females. ConclusionDiabetes mortality rates in Huangpu District have increased year by year, resulting in significant life loss. However, the age-standardized mortality rate increase has markedly slowed. Efforts should focus on elderly diabetic patients aged ≥70 years, by leveraging platforms such as community-based chronic disease health support centers, efforts should be made to enhance diabetes screening service for middle-aged and elderly residents. Consequently, elderly diabetic patients’ awareness of diabetes and responce to related complications is improved, which would be conducive to controling the progression of complications and reducing the mortolity risk of diabetes.

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.

ObjectiveTo investigate the pathogenic spectrum and epidemiological characteristics of diarrheal disease in Fengxian District of Shanghai, and to provide scientific basis for the prevention and control of diarrheal diseases. MethodsBasic information of the initial adult cases visited diarrheal disease surveillance sentinel hospital in Fengxian District, Shanghai, was collected from August 2013 to 2023, and fecal samples were collected at 1∶5 sampling intervals to isolate and identify 5 kinds of diarrheagenic Escherichia coli (DEC), Salmonella (SAL), Vibrio parahaemolyticus, Campylobacter, Vibrio cholerae, Shigella and Yersinia enterocolitica (YE). Simultaneously, nucleic acid detection was performed for 3 kinds of rotavirus, 2 kinds of norovirus, intestinal adenovirus, astrovirus and sapovirus. ResultsA total of 1 861 cases of newly diagnosed diarrheal disease were reported, with the peak in July to August. Additionally, 704 surveillance samples were detected, with a total positive detection rate of 50.57%. The detection rates of bacterial, viral and mixed infection were 25.14%, 21.02% and 4.40%, respectively. Among the pathogens detected, DEC accounted for the highest (17.61%, 124/704), followed by norovirus (16.48%, 116/704), rotavirus (6.39%, 45/704), SAL (5.97%, 42/704) and Campylobacter (3.84%, 27/704). DEC detected were mainly enteroaggregative Escherichia coli and enterotoxigenic Escherichia coli, with no detection of Vibrio cholerae, Shigella and YE. The highest total pathogen detection rate was observed from June to September, and the detection peaks of norovirus were from March to June and from October to December, whereas that of DEC was from June to October. The detection rate of rotavirus peaked from January to February, but which was not detected between 2020‒2023. The SAL positive rate peak was in September, whereas that of Campylobacter was from July to September. ConclusionThe main pathogens detected in Fengxian District from 2013‒2019 are DEC, norovirus, rotavirus, SAL and Campylobacter. Different pathogens have different detection peaks, with bacteria predominating in summer and viruses in winter and spring. Prevention and control measures should be carried out according to the epidemiological characteristics of different seasons.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective To clarify the risk factors of diaphragmatic dysfunction (DD) after cardiac surgery with extracorporeal circulation. Methods A retrospective analysis was conducted on the data of patients who underwent cardiac surgery with extracorporeal circulation in the Department of Cardiovascular Surgery of Peking University People's Hospital from January 2023 to March 2024. Patients were divided into two groups according to the results of bedside diaphragm ultrasound: a DD group and a control group. The preoperative, intraoperative, and postoperative indicators of the patients were compared and analyzed, and independent risk factors for DD were screened using multivariate logistic regression analysis. Results A total of 281 patients were included, with 32 patients in the DD group, including 23 males and 9 females, with an average age of (64.0±13.5) years. There were 249 patients in the control group, including 189 males and 60 females, with an average age of (58.0±11.2) years. The body mass index of the DD group was lower than that of the control group [(18.4±1.5) kg/m2 vs. (21.9±1.8) kg/m2, P=0.004], and the prevalence of hypertension, chronic obstructive pulmonary disease, heart failure, and renal insufficiency was higher in the DD group (P<0.05). There was no statistical difference in intraoperative indicators (operation method, extracorporeal circulation time, aortic clamping time, and intraoperative nasopharyngeal temperature) between the two groups (P>0.05). In terms of postoperative aspects, the peak postoperative blood glucose in the DD group was significantly higher than that in the control group (P=0.001), and the proportion of patients requiring continuous renal replacement therapy was significantly higher than that in the control group (P=0.001). The postoperative reintubation rate, tracheotomy rate, mechanical ventilation time, and intensive care unit stay time in the DD group were higher or longer than those in the control group (P<0.05). Multivariate logistic regression analysis showed that low body mass index [OR=0.72, 95%CI (0.41, 0.88), P=0.011], preoperative dialysis [OR=2.51, 95%CI (1.89, 4.14), P=0.027], low left ventricular ejection fraction [OR=0.88, 95%CI (0.71, 0.93), P=0.046], and postoperative hyperglycemia [OR=3.27, 95%CI (2.58, 5.32), P=0.009] were independent risk factors for DD. Conclusion The incidence of DD is relatively high after cardiac surgery, and low body mass index, preoperative renal insufficiency requiring dialysis, low left ventricular ejection fraction, and postoperative hyperglycemia are risk factors for DD.

Background Long-term exposure to ambient fine particulate matter (PM_2.5) may increase the risk of diabetes, and a healthy diet can effectively control fasting blood glucose levels. However, it is unclear whether dietary factors have a moderating effect on the risk of diabetes associated with atmospheric PM_2.5 exposure. Objective To investigate the association between long-term exposure to PM_2.5 and diabetes in rural areas of Ningxia, and potential interaction of long-term exposure to atmospheric PM_2.5 and diet on diabetes. Methods The study subjects were selected from the baseline survey data of the China Northwest Cohort-Ningxia (CNC-NX) , a natural population cohort. A total of 13917 subjects were included, excluding participants with missing covariate information. We utilized the annual average ambient PM_2.5 concentration from 2014 to 2018 as the long-term exposure level. Logistic regression and multiple linear regression were employed to analyze the associations of long-term atmospheric PM_2.5 exposure with diabetes and fasting blood glucose levels. Stratification by frequency of vegetable consumption, frequency of fruit consumption, and salty taste was used to examine moderating effects on the diabetes risk associated with atmospheric PM_2.5 exposure. Results The mean age of the 13917 subjects was (56.8±10.0) years, and the prevalence of diabetes was 9.8%. Between 2014 and 2018, the average annual concentration of PM_2.5 was (38.10±4.67) μg·m⁻³. The risk (OR) of diabetes was 1.018 (95%CI: 1.005, 1.032) and the fasting blood glucose was increased by 0.011 (95%CI: 0.004, 0.017) mmol·L⁻¹ for each 1 μg·m⁻³ increase in PM_2.5 concentration. Compared to those who consumed vegetables < 1 time per week, individuals who consume vegetables 1-3 times per week and ≥4 times per week had a reduced risk of developing diabetes by 27.1% (OR=0.729, 95%CI: 0.594, 0.893) and 16.8% (OR=0.832, 95%CI: 0.715, 0.971) respectively. Similarly, when compared to those who consumed fruits <1 time per week, individuals who consumed fruits 1-3 times per week and ≥4 times per week exhibited a reduced risk of diabetes by 16.4% (OR=0.836, 95%CI: 0.702, 0.998) and 18.2% (OR=0.818, 95%CI: 0.700, 0.959) respectively. Fasting blood glucose decreased by 0.202 (95%CI: -0.304, -0.101) mmol·L⁻¹ in participants who ate vegetables 1-3 times per week. The effect of salty taste on diabetes and fasting blood glucose was not significant. The results of stratified analysis by dietary factors and PM_2.5 concentration showed that the risks of diabetes were increased in the low PM_2.5 pollution-low vegetable intake frequency group and the high PM_2.5 pollution-low vegetable intake frequency group compared with the low PM_2.5 pollution-high vegetable intake frequency group, with OR values of 3.987 (95%CI: 2.943, 5.371) and 1.433 (95%CI: 1.143, 1.796) respectively. The risk of diabetes was 50.1% higher in participants with high PM_2.5 pollution and low fruit intake frequency than in participants with low PM_2.5 pollution and high fruit intake frequency (OR=1.501, 95%CI: 1.171, 1.926). No interaction was found between salty taste and PM_2.5 on diabetes. Conclusion Long-term exposure to ambient PM_2.5 is associated with an increased fasting blood glucose and an elevated risk of diabetes in rural Ningxia population. Increasing the frequency of weekly consumption of vegetables or fruits may have a certain protective effect against diabetes occurrence, as well as a moderating effect on diabetes and fasting blood glucose levels associated with long-term exposure to atmospheric PM_2.5.

Objective To analyze the clinical outcomes of early invasive fungal disease(IFD)in patients after allogenetic hematopoietic stem cell transplantation(allo-HCST)with metagenomic next-generation sequencing(mNGS).Methods A retrospective analysis was conducted on patients undergoing allo-HCST in our Bone Marrow Transplantation Center between July 2021 and October 2022.These patients experienced one of the following conditions within 100 d after transplantation:① Patients with persistent fever and negative blood culture after empiric antimicrobial therapy for 72 h or longer;② Hyperpyrexia of unknown origin occurred again after effective anti-infection in the past;③ Symptoms in lower respiratory tract associated with lung lesions on CT scan,and empiric anti-infective therapy was ineffective.Peripheral blood or bronchoscopic alveolar lavage fluid were tested with mNGS,and overall survival(OS)and non-relapse mortality(NRM)were analyzed.Results There were 60 patients enrolled in this study.For the peripheral blood samples of 47 cases and bronchoalveolar lavage fluid samples of 13 cases,mNGS found that 19 cases were negative to pathogens,30 cases were non-fungal positive,and 11 case were fungal positive,including 3 cases of aspergillus,5 cases of mucor,2 cases of Candida tropicalis,and 1 case of Trichosporon asahii.Of the 11 patients with fungal positive,8 achieved complete remission after antifungal therapy according to the mNGS results.The 1-year OS and NRM of the 60 patients were 70.0％(95％CI:64.1％～75.9％)and 20.0％(95％CI:11.9％～32.5％),respectively,while those of the fungal infection patients were 54.5％(95％CI:49.5％～69.5％)and 36.4％(95％ CI:15.5％～70.3％),respectively.No significant differences were seen in 1-year OS(P=0.487)and 1-year NRM(P=0.358)among the negative,fungal infection and non-fungal infection patients,neither OS(P=0.238)and NRM(P=0.154)between the fungal infection and the non-fungal infection patients.Conclusion mNGS can rapidly diagnose the early IFD after allo-HSCT,which is helpful for timely and effective treatment and improves the prognosis of patients.

Objective·To analyze the clinicopathologic characteristics,gene mutation profile,and prognostic factors of thyroid diffuse large B-cell lymphoma(DLBCL).Methods·From November 2003 to December 2021,a total of 66 patients with thyroid DLBCL[23 cases(34.8%)with primary thyroid DLBCL,and 43 cases(65.2%)with secondary thyroid DLBCL]admitted to Ruijin Hospital,Shanghai Jiao Tong University School of Medicine were retrospectively analyzed for their clinicopathological data,survival and prognostic factors.Gene mutation profiles were evaluated by targeted sequencing(55 lymphoma-related genes)in 40 patients.Results·Compared to primary thyroid DLBCL,secondary thyroid DLBCL had advanced ratio of Ann Arbor stage Ⅲ?Ⅳ(P=0.000),elevated serum lactate dehydrogenase(LDH)(P=0.043),number of affected extranodal involvement≥2(P=0.000),non-germinal center B cell(non-GCB)(P=0.030),BCL-2/MYC double expression(DE)(P=0.026),and international prognostic index(IPI)3?5-scores(P=0.000).The proportion of patients who underwent thyroid surgery(P=0.012)was lower than that of patients with primary thyroid DLBCL.The complete remission(CR)rate in primary thyroid DLBCL patients was higher than that in secondary thyroid DLBCL patients(P=0.039).Fifty-five patients(83%)received rituximab combined with cyclophosphamide,doxorubicin,vincristine,and prednisone(R-CHOP)-based first-line regimen.The estimated 5-year progression free survival(PFS)rate of primary thyroid DLBCL patients was 95.0%,higher than the 49.7%of the secondary patients(P=0.010).Univariate analysis showed that Ann Arbor Ⅲ?Ⅳ(HR=4.411,95%CI 1.373?14.170),elevated LDH(HR=5.500,95%CI 1.519?19.911),non-GCB(HR= 5.291,95%CI 1.667?16.788),and DE(HR=6.178,95%CI 1.813?21.058)were adverse prognostic factors of PFS in patients with thyroid DLBCL.Ann Arbor Ⅲ?Ⅳ(HR=7.088,95%CI 0.827?60.717),elevated LDH(HR=6.982,95%CI 0.809?60.266),and DE(HR=18.079,95%CI 1.837?177.923)were adverse prognostic factors of overall survival(OS).Multivariate analysis showed that Ann Arbor Ⅲ?Ⅳ(HR=4.693,95%CI 1.218?18.081)and elevated LDH(HR=5.058,95%CI 1.166?21.941)were independent adverse prognostic factors of PFS in patients with thyroid DLBCL.Targeted sequencing data showed mutation frequency>20%in TET2(n=14,35%),KMT2D(n=13,32%),TP53(n=11,28%),GNA13(n=10,25%),KMT2C(n=9,22%),and TP53 were adverse prognostic factors of PFS in patients with thyroid DLBCL(P=0.000).Conclusion·Patients with primary thyroid DLBCL have better PFS and OS than those with secondary thyroid DLBCL.Ann Arbor Ⅲ?Ⅳ,elevated LDH,non-GCB,and DE(MYC and BCL2)are adverse prognostic factors in thyroid DLBCL.TET2,KMT2D,TP53,GNA13,and KMT2C are commonly highly mutated genes in thyroid DLBCL,and the prognosis of patients with TP53 mutations is poor.

In the field of dental aesthetics,digital aesthetic design plays a crucial role in helping dentists to predict treatment outcomes vis-ually,as well as in enhancing the consistency of knowledge and understanding of aesthetic goals between dentists and patients.It serves as the foundation for achieving ideal aesthetic effects.However,there is no clear standard for this digital process currently in China and abroad.Many dentists lack of systematic understanding of how to carry out digital aesthetic design for treatment.To establish standardized processes for dental aesthetic design and to improve the homogeneity of treatment outcomes,Chinese Society of Digital Dental Industry(CSD-DI)convened domestic experts in related field to compile this consensus.This article elaborates on the key aspects of digital aesthetic data collection,integration steps,and the digital aesthetic design process.It also formulates a decision tree for dental aesthetics at macro level and outlines corresponding workflows for various clinical scenarios,serving as a reference for clinicians.

Objective To evaluate the effects of high-fat diet on the pharmacokinetics of metronidazole in Chinese healthy adult subjects.Methods This program is designed according to a single-center,randomized,open,single-dose trial.Forty-seven healthy subjects were assigned to receive single dose of metronidazole tablets 200 mg in either fasting and high-fat diet state,and blood samples were taken at different time points,respectively.The concentrations of metronidazole in plasma were determined by high performance liquid chromatography-mass spectromentry.Results The main pharmacokinetic parameters of metronidazole in fasting state and high-fat diet state were as follows:Cmax were(4 799.13±1 195.32)and(4 044.17±773.98)ng·mL-1;tmax were 1.00 and 2.25 h;t1/2 were(9.11±1.73)and(9.37±1.79)h;AUC0_t were(5.59±1.19)x 104 and(5.51±1.18)x 104 ng·mL-1·h;AUC0_∞ were(5.79±1.33)x 104 and(5.74±1.32)× 104 ng·mL-1·h.Compared to the fasting state,the tmaxof the drug taken after a high fat diet was delayed by 1.25 h(P＜0.01),Cmax,AUC0_t,AUC0-∞ were less or decreased in different degrees,but the effects were small(all P＞0.05).Conclusion High-fat diet has little effects on the pharmacokinetic parameters of metronidazole,which does not significantly change the degree of drug absorption,but can significantly delay the time to peak.