Objective: To explore the characteristics of the diversity and composition of oral microbial flora with age, and to provide a reference for understanding the succession of oral microecology at different ages. Methods: Oral rinse 16S rRNA (V4 region) sequencing data from 9 021 participants 14-69 years of age in the 2009-2012 National Health and Nutrition Examination Survey (NHANES) were analyzed. Alpha diversity (Observed OTUs, Faith’s PD, Shannon Index), beta diversity (Bray-Curtis and UniFrac), and genus-level composition were examined using weighted generalized linear models (GLMs), including quadratic terms for age and adjusting for key covariates (gender, race/ethnicity, BMI, smoking status, and periodontitis severity). Results: Alpha diversity demonstrated a clear inverted U-shaped trajectory across age, peaking at 25-30 years old and declining thereafter. This trend remained consistent across sex, race, smoking, and periodontal health strata. Beta diversity analyses revealed a modest but steady age-related shift in community structure. Genus-level analyses revealed that Rothia, Prevotella_6, and Lactobacillus increased steadily with age, while Haemophilus, Porphyromonas, and Corynebacterium declined significantly. Notably, potential periodontopathogens, such as Fusobacterium and Treponema_2, peaked in early adulthood before declining with age. Conclusion Age is an important driver of oral microbial succession, and the oral microbiome exhibits dynamic changes across different life stages. Future longitudinal and multi-omic studies are warranted to elucidate the mechanisms underlying these age-related trajectories.

Objective: To understand the allocation and use of safety seats for preschool children and explore its related factors, so as to provide a scientific reference for promoting the usage of safety seats. Methods: A stratified random cluster sampling method was used to select 3 143 parents of preschool children aged 3 to 6 from six kindergartens in Shunyi District, Beijing from January 3 to 10, 2022. An online questionnaire survey was conducted to collect and evaluate the equipment and use of child safety seats in different characteristics of preschool children, as well as their scores of health beliefs. Multiple factor Logistic regression analysis was used to investigated the related factors of safety seat configuration and use. Results: The equipping rate and usage rate of safety seats for preschool children were 66.56% and 58.45%, respectively. The proportion of equipped and used safety seats for preschool children in core families (69.52%, 62.23%) were higher than that in large families (64.35%, 55.62%), only child families ( 72.39 %, 64.87%) were higher than non only child families (61.49%, 52.86%), and urban families (71.63%, 63.04%) were higher than rural families (52.31%, 45.51%) ( χ 2=9.23, 13.86; 41.72, 46.44; 101.96 ,76.97,all P <0.05) . As the educational level of parents ( χ 2 trend =154.23,98.76) and annual income of the family ( χ 2 trend =155.78,127.69) rised, the reporting rates of the equipped and used child safety seats in the family also increased(all P <0.05 ). There were statistically significant differences in the scores of different dimensions of health beliefs for the provision ( t =-20.22-18.16) and use ( t =24.32-24.17) of safety seats for preschool children(all P <0.05). After adjusting for child sex, child age, family annual income, parental education level, family type, whether the child was an only child, and place of residence，multivariate Logistic regression analysis showed that preschool children with higher perceived susceptibility score( OR =1.11, 1.08), higher self efficacy score( OR =1.23, 1.33), and higher suggestive factors score( OR =1.08, 1.12) were more likely to have and use safety seats in their families, while preschool children with higher perceived impairments score( OR =0.82, 0.80) were less likely to have and use safety seats in their families (all P <0.05). Conclusions The installation rate of child safety seats needs to be improved, and there is also a certain gap in their use after installation. Parents of preschool children should improve susceptibility and self efficacy to safety seat equipment and use, and perceptual barriers should be reduced.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

ObjectiveCell adhesion is a critical process that regulates cellular physiological functions. Quantitative characterization of adhesion dynamics is essential for elucidating the intrinsic mechanical mechanisms underlying cellular activities. Although atomic force microscopy-based single-cell force spectroscopy is widely used for single-cell adhesion measurements, it requires complex chemical modifications for preparation of live-cell probes, leading to limitations such as cumbersome operation, low throughput, and potential impacts on cell viability. Fluidic force microscopy, which combines atomic force microscopy with microfluidic probes, is a technique allowing the operation of force-controlled nanopipettes in aqueous environments. By applying negative or positive pressure via a pressure controller, a single living cell can be captured onto or released from the cantilever under physiological conditions. This procedure offers a simple workflow and high assay throughput for single-cell adhesion measurements without the need for chemical functionalization. In this study, fluidic force microscopy-based single-cell force spectroscopy was adopted to achieve long-term quantitative characterization of single-cell adhesion dynamics in a simpler and more efficient manner, comparing the dynamic differences in adhesion establishment between two cell lines with different differentiation levels. MethodsHEK 293T and hTERT RPE-1 cells were non-invasively captured on the cantilever of a fluidic force microscope via its integrated microfluidic system during 40 h of adhesion culture. Cell-substrate detachment assays were performed, and force-distance curves were recorded to extract key mechanical adhesion parameters, including adhesion force, adhesion energy, and maximum detachment distance. These measurements were combined with real-time monitoring of cell spreading area to systematically characterize the dynamic evolution of single-cell adhesion. ResultshTERT RPE-1 cells rapidly entered a stable adhesion phase within 1 h after seeding, with both area-normalized adhesion force and area-normalized adhesion energy reaching peak values. In contrast, HEK 293T cells required 4 h to achieve stable adhesion. Subsequently, the adhesion force, adhesion energy and maximum detachment distance of hTERT RPE-1 and HEK 293T cells stabilized at approximately 240 nN vs. 30 nN, 2.2 pJ vs. 0.12 pJ and 6 μm vs. 4 μm, respectively. hTERT RPE-1 cells reached the peak of area-normalized adhesion parameters earlier than HEK 293T cells, with their peak area-normalized adhesion force and area-normalized adhesion energy being substantially elevated relative to HEK 293T cells. HEK 293T cells presented stronger linear correlations among adhesion energy, maximum detachment distance and adhesion force compared with hTERT RPE-1 cells. For both cell lines, cell spreading area exhibited a weak correlation with adhesion force. Whereas the area-normalized adhesion parameters of HEK 293T cells remained relatively constant throughout the adhesion process, hTERT RPE-1 cells exhibited elevated values in the early phase, followed by a gradual decline. These results indicated distinct dynamic adhesion patterns between the two cell types, with hTERT RPE-1 cells exhibiting stronger adhesion strength and higher adhesion efficiency. ConclusionIn this study, fluidic force microscopy-based single-cell force spectroscopy was successfully applied to perform long-term in situ quantitative measurement of the adhesion dynamics in single adherent cells. The approach revealed divergent adhesion patterns between HEK 293T and hTERT RPE-1 cells, suggesting a close association between cell differentiation and adhesion behaviors. These findings provide quantitative mechanical evidence for further understanding the underlying mechanisms of cell adhesion.

Objective: To understand the current status and related factors of oral health behavior in preschool children, so as to provide scientific basis for improving parents oral health care abilities. Methods: From March 5 to 12, 2024, using a stratified cluster sampling method, an online questionnaire survey was conducted among parents of 1 381 preschool children aged 3-6 from 6 selected kindergartens of a district in Beijing. A structural equation model (SEM) was constructed based on the Theory of Planned Behavior framework to analyze the factors associated with preschool children s oral health behaviors. Results: The rates of parental assistance in brushing teeth, regular oral examination, and postprandial rinsing were 44.4%, 18.6% and 23.6%, respectively. Attitude, subjective norms were positively correlated with oral health behavior intention ( r =0.61, 0.55); attitude, perceived behavioral control, and behavioral intention were positively correlated with oral health behavior ( r =0.14, 0.13, 0.16) (all P < 0.01 ). The results of the SEM showed that attitude and subjective norms had a significant direct effect on oral health behavior intention ( β = 0.42 , 0.40), and the direct effect of perceived behavioral control on oral health behavior was statistically significant ( β =0.42) (all P <0.01). Conclusions The overall level of oral health behavior among preschool children needs to be improved. Perceived behavioral control is the most direct positive related factor of oral health behavior. In the future, intervention measures should focus on perceived behavioral control as the entry point and provide systematic intervention guidance in combination with planned behavior theory.

Objective To explore the role of DNAJC5B in immunotherapy for esophageal squamous cell carcinoma (ESCC). Methods Using the ESCC dataset from The Cancer Genome Atlas (TCGA) database, genes correlated with DNAJC5B expression were identified through Pearson correlation analysis. Subsequently, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed. Additionally, single-cell RNA sequencing (scRNA-seq) data were utilized to analyze the expression of DNAJC5B in different T-cell subsets. The prognostic value of DNAJC5B was evaluated using Kaplan-Meier survival curves, receiver operating characteristic curves, and Cox proportional hazards models. Results DNAJC5B was highly expressed in patients with advanced-stage ESCC, particularly in males. GO and KEGG analyses revealed a significant correlation between DNAJC5B expression and immune-related processes, such as the adaptive immune response and cell surface receptor signaling pathways. Single-cell analysis results indicated that DNAJC5B expression was positively correlated with immune function, with DNAJC5B predominantly accumulating in CD8+ T cells. Kaplan-Meier survival curves showed that the median survival time for patients with high DNAJC5B expression was 681 days, significantly shorter than the 1 361 days for patients with low expression (P<0.05). Furthermore, univariate and multivariate independent prognostic analyses demonstrated that DNAJC5B was an independent risk factor, with hazard ratios (HRs) of 3.577 and 4.114, respectively (both P<0.05). Conclusion DNAJC5B may play a crucial immunomodulatory role in ESCC, particularly in regulating CD8+ T-cell function and tumor immune escape. These findings support the potential of DNAJC5B as a biomarker for the treatment and prognostic assessment of ESCC.

Due to the poor ionization efficiency and the weak mass spectrometry(MS)intensity of weakly polar substances,direct analysis using the traditional electrospray ionization mass spectrometry(ESI-MS)is a big challenge.In this study,a novel rapid on-site detection method of four prohibited sex hormones in cosmetics was proposed using online derivatization strategy coupled with a miniature mass spectrometer.The target substances in the samples were extracted by a custom-made polyaniline/multi-walled carbon nanotube solid-phase microextraction(SPME)probe.The stirring speed was 200 r/min,the extraction temperature was 40℃,and the extraction time was 2 min.A pulled dual-channel θ borosilicate glass capillary emitter was used as the nano-ESI ion source.The SPME probe was inserted into the channel containing methanol in theθborosilicate glass capillary.When the spray voltage was applied,the four sex hormones were desorbed and formed spray microdroplets,which then collided with the hydroxylamine microdroplets generated from the other channel.The microdroplets of reaction product entered into the miniature mass spectrometer for direct analysis.The limits of detection(LOD)and limits of quantification(LOQ)for the four sex hormones were 10-20 ng/mL and 20-50 ng/mL,respectively.The recoveries were from 84.6%to 107.8%with the relative standard deviations(RSD)from 4.1%to 11.6%.Compared to detection without derivatization,the MS signals of the four target substances were increased by 3 to 15 times.This method was simple,rapid,highly efficient and sensitive,and suitable for on-site rapid analysis of weakly polar sex hormones in cosmetics.

Cerebral small vessel disease (CSVD) and large artery atherosclerosis (LAA) are two types of cerebrovascular diseases. Their pathogenesis is closely related, with common risk factors, but there are differences. Early detection and effective management of common risk factors, while taking into account differentiated risk factors, are of great significance for stroke prevention. This article reviews the similarities and differences in the major risk factors between CSVD and LAA.

Objective To investigate the diagnostic accuracy and clinical applicability of the Linknet-VGG16 deep learning algorithm for measuring the effective optical zone(EOZ)after corneal refractive surgery.Methods This single-center retrospective cohort study included 69 patients(69 eyes)who underwent femtosecond laser-assisted in situ kerato-mileusis(FS-LASIK)(34 eyes)or small incision lenticule extraction(SMILE)(35 eyes)at the Refractive Surgery Center of Affiliated Zhengzhou Aier Eye Hospital of Henan University from June 2023 to June 2024.Data from the right eyes of all patients were selected for statistical analysis.During the surgery,patients in the FS-LASIK group adopted the VisuMax fem-tosecond laser system combined with the Amaris 750S excimer laser system,while those in the SMILE group only used the VisuMax femtosecond laser system.A total of 276 Pentacam images were re-examined postoperatively.A Linknet segmenta-tion model based on the VGG16 encoder was constructed,and image normalization techniques were applied to accelerate model convergence.Model performance was assessed using accuracy,intersection over union(IoU),and the Dice coeffi-cient.The traditional EOZ measurement method based on corneal tangential curvature served as the reference standard.Bland-Altman analysis was conducted to evaluate consistency across all images and within each group,and the time effi-ciency of both methods was compared.Results Six representative medical image segmentation architectures(U-Net,U-Net++,DeepLabv3-ResNet50,DeepLabv3+-ResNet50,Unet-Densenet169,and Linknet-VGG16)were systematically evaluated.The Linknet-VGG16 model demonstrated superior performance over the other 5 models in pixel-level accuracy,IoU and Dice coefficient,which were 99.83％,99.48％and 99.74％,respectively.Although there was no significant differ-ence in accuracy and Dice coefficient between Linknet-VGG16 and U-Net models(whose accuracy was 99.82％and Dice coefficient was 99.72％),the inference speed of the U-Net model(62.46 ms)was 31.76％slower than that of the Linknet-VGG16 model(42.62 ms).The evaluation results of a clinically applicable comprehensive scoring model(weights:accura-cy 20％,IoU 20％,Dice coefficient 20％,speed 25％,model size 15％)showed that the Linknet-VGG16 model achieved a score of 88.01,surpassing other architectures(U-Net:86.29;DeepLabv3+-ResNet50:80.41;DeepLabv3-ResNet50:73.82;U-Net++:73.22;Unet-Densenet169:66.66).Bland-Altman analysis revealed that the mean difference of the 136 images in the FS-LASIK group was 0.01 mm[95％limits of agreement(LoA):-0.36 to 0.35 mm],with 96.3％of data points falling within the LoA.The mean difference of the 140 images in the SMILE group was-0.01 mm(95％LoA:-0.36 to 0.33 mum),with 95.7％of data points falling within the LoA.The mean difference of all 276 images was 0.00 mm(95％LoA:-0.36 to 0.34 mm),with 96.4％of data points falling within the LoA.These results indicated excellent consistency.The average measurement time per image using the traditional EOZ measurement method was 13.00 minutes,whereas the deep learning model required only 3.22 seconds.Conclusion The traditional EOZ measurement method based on corne-al tangential curvature exhibits good consistency with the fully automatic EOZ measurement method based on deep learning algorithms,achieving high image recognition accuracy.Additionally,the deep learning algorithm significantly reduces measurement time,compared with the traditional method based on corneal tangential curvature.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.