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Background The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are the most commonly used scales to detect mild cognitive impairment (MCI) in population-based epidemiologic studies. However, their comparison on which is best suited to assess cognition is scarce in samples from multiple regions of China. Methods We conducted a cross-sectional analysis of 4923 adults aged ≥55 years from the Community-based Cohort Study on Nervous System Diseases. Objective cognition was assessed by Chinese versions of MMSE and MoCA, and total score and subscores of cognitive domains were calculated for each. Education-specific cutoffs of total score were used to diagnose MCI. Demographic and health-related characteristics were collected by questionnaires. Correlation and agreement for MCI between MMSE and MoCA were analyzed; group differences in cognition were evaluated; and multiple logistic regression model was used to clarify risk factors for MCI. Results The overall MCI prevalence was 28.6% for MMSE and 36.2% for MoCA. MMSE had good correlation with MoCA (Spearman correlation coefficient = 0.8374, p  < 0.0001) and moderate agreement for detecting MCI with Kappa value of 0.5973 ( p  < 0.0001). Ceiling effect for MCI was less frequent using MoCA versus MMSE according to the distribution of total score. Percentage of relative standard deviation, the measure of inter-individual variance, for MoCA (26.9%) was greater than for MMSE (19.0%) overall ( p  < 0.0001). Increasing age (MMSE: OR = 2.073 for ≥75 years; MoCA: OR = 1.869 for≥75 years), female (OR = 1.280 for MMSE; OR = 1.163 for MoCA), living in county town (OR = 1.386 and 1.862 for MMSE and MoCA, respectively) or village (OR = 2.579 and 2.721 for MMSE and MoCA, respectively), smoking (OR = 1.373 and 1.288 for MMSE and MoCA, respectively), hypertension (MMSE: OR = 1.278; MoCA: OR = 1.208) and depression (MMSE: OR = 1.465; MoCA: OR = 1.350) were independently associated with greater likelihood of MCI compared to corresponding reference group in both scales (all p  < 0.05). Conclusions MoCA is a better measure of cognitive function due to lack of ceiling effect and with good detection of cognitive heterogeneity. MCI prevalence is higher using MoCA compared to MMSE. Both tools identify concordantly modifiable factors for MCI, which provide important evidence for establishing intervention measures.

The aim of this study was to examine sex disparity in metabolic syndrome prevalence and its risk factors among Chinese adults. Using the 2010-2012 China National Nutrition and Health Survey (CNNHS), a nationally representative cross-sectional study on nutrition and non-communicable chronic diseases, a total of 98,042 participants aged 18 years and older were included in the analysis. Dietary information was collected with a food frequency questionnaire (FFQ). Metabolic syndrome was defined according to the updated NCEP ATP III criteria. A multivariable logistic regression model was performed to examine the associations between sociodemographic and dietary factors with metabolic syndrome prevalence, and the results are presented using odd ratios (ORs) and 95% confidence intervals (CIs). The overall standardized prevalence of metabolic syndrome was 24.2% (24.6% in men and 23.8% in women). The metabolic syndrome prevalence was positively associated with age in men and women. The prevalence of metabolic syndrome was negatively associated with the physical activity level among men and inversely associated with the education level among women (P for trend < 0.01). Frequent consumption of fungi and algae was an underlying risk factor for metabolic syndrome in men, whereas frequent consumption of nuts and pork was associated with a decreased prevalence of metabolic syndrome in women. The prevalence of metabolic syndrome in men was not different from that in women. There are sex-specific associations between multiple risk factors and metabolic syndrome.

Since the Opening of China, the country’s economy has continuously and rapidly improved. Various economic, educational, and health policies have been implemented to shape the development of society, which may have greatly affected the Chinese diet and related malnutrition issues. The objective of the present review was to comprehensively review long-term trends in dietary intakes, nutrition status, and subsequent health challenges among Chinese adults. The data sources were mainly the 1982, 1992, 2002, and 2010–2012 China National Nutrition Surveys (CNNS) and reports and the 1989–2015 China Health and Nutrition Survey (CHNS). Over decades, there have been significant changes in the dietary structure of Chinese adults, characterized as decreased intake of cereals and vegetables and increased intake of animal foods with pork dominating. Intakes of eggs, fish, and dairy has reminded at a low level, with only a small increase over time. Consumption of cooking oil and salt was substantively far above the recommendations. A great proportion of fat-to-energy intake and “hidden hunger” was still prominent. Despite nutrition deficiency, there have been some modest improvements in related diseases, but overweight and obesity has become a prominent issue, with the prevalence in adults increasing from 16.4% and 3.6% in 1982 to 30.1% and 11.9% in 2012, respectively. In conclusion, this review sheds light on some salient problems with nutrition and malnutrition status in China, especially the dual challenges of undernutrition and overnutrition. Dynamic monitoring of nutritional characteristics in China should be strengthened, and effective strategies to improve nutrition need to be targeted at the national, societal, family, and individual levels.

Neurofibromatosis type 1 (NF1), the most common tumor predisposition syndrome, occurs when NF1 gene variants result in loss of neurofibromin, a negative regulator of RAS activity. Plexiform neurofibromas (PN) are peripheral nerve sheath tumors that develop in patients with NF1 and are associated with substantial morbidity and for which, until recently, the only treatment was surgical resection. However, surgery carries several risks and a proportion of PN are considered inoperable. Understanding the genetic underpinnings of PN led to the investigation of targeted therapies as medical treatment options, and the MEK1/2 inhibitor selumetinib has shown promising efficacy in pediatric patients with NF1 and symptomatic, inoperable PN. In a phase I/II trial, most children (approximately 70%) achieved reduction in tumor volume accompanied by improvements in patient-reported outcomes (decreased tumor-related pain and improvements in quality of life, strength, and range of motion). Selumetinib is currently the only licensed medical therapy indicated for use in pediatric patients with symptomatic, inoperable NF1-PN, with approval based on the results of this pivotal clinical study. Several other MEK inhibitors (binimetinib, mirdametinib, trametinib) and the tyrosine kinase inhibitor cabozantinib are also being investigated as medical therapies for NF1-PN. Careful consideration of multiple aspects of both disease and treatments is vital to reduce morbidity and improve outcomes in patients with this complex and heterogeneous disease, and clinicians should be fully aware of the risks and benefits of available treatments. There is no single treatment pathway for patients with NF1-PN; surgery, watchful waiting, and/or medical treatment are options. Treatment should be individualized based on recommendations from a multidisciplinary team, considering the size and location of PN, effects on adjacent tissues, and patient and family preferences. This review outlines the treatment strategies currently available for patients with NF1-PN and the evidence supporting the use of MEK inhibitors, and discusses key considerations in clinical decision-making.

Ferroelectric tunnel junctions (FTJs) have recently attracted considerable interest as a promising candidate for applications in the next-generation non-volatile memory technology. In this work, using an ultrathin (3 nm) ferroelectric Sm 0.1 Bi 0.9 FeO 3 layer as the tunnelling barrier and a semiconducting Nb-doped SrTiO 3 single crystal as the bottom electrode, we achieve a tunnelling electroresistance as large as 10 5 . Furthermore, the FTJ memory states could be modulated by light illumination, which is accompanied by a hysteretic photovoltaic effect. These complimentary effects are attributed to the bias- and light-induced modulation of the tunnel barrier, both in height and width, at the semiconductor/ferroelectric interface. Overall, the highly tunable tunnelling electroresistance and the correlated photovoltaic functionalities provide a new route for producing and non-destructively sensing multiple non-volatile electronic states in such FTJs. Tunnelling electroresistance is the variation of resistance of a thin-film junction with the polarization state of its ferroelectric tunnel barrier. Here the authors demonstrate a large light-modulated tunnelling electroresistance and a hysteretic photovoltaic effect in a complex oxide heterostructure.

The fields of photovoltaics, photodetection and light emission have seen tremendous activity in recent years with the advent of hybrid organic-inorganic perovskites. Yet, there have been far fewer reports of perovskite-based field-effect transistors. The lateral and interfacial transport requirements of transistors make them particularly vulnerable to surface contamination and defects rife in polycrystalline films and bulk single crystals. Here, we demonstrate a spatially-confined inverse temperature crystallization strategy which synthesizes micrometre-thin single crystals of methylammonium lead halide perovskites MAPbX 3 (X = Cl, Br, I) with sub-nanometer surface roughness and very low surface contamination. These benefit the integration of MAPbX 3 crystals into ambipolar transistors and yield record, room-temperature field-effect mobility up to 4.7 and 1.5 cm 2  V −1  s −1 in p and n channel devices respectively, with 10 4 to 10 5 on-off ratio and low turn-on voltages. This work paves the way for integrating hybrid perovskite crystals into printed, flexible and transparent electronics. The methylammonium lead halide perovskites have shown excellent optoelectronic properties but the field-effect transistors are much less studied. Here Yu et al. synthesize micrometer-thin crystals of perovskites with low surface contamination and make ambipolar transistor devices with high mobilities.

NOx is one of the main sources of pollutants for motor vehicles. Nowadays, many diesel vehicle manufacturers may use emission-cheating equipment to make the vehicles meet compliance standards during emission tests, but the emissions will exceed the standards during actual driving. In order to strengthen the supervision of diesel vehicles for emission monitoring, this article intends to establish a model that can predict the transient emission characteristics of heavy-duty diesel vehicles and provide a solution for remote online monitoring of diesel vehicles. This paper refers to the heavy-duty vehicle National VI emission regulations and uses vehicle-mounted portable emission testing equipment (PEMS) to conduct actual road emission tests on a certain country’s VI heavy-duty diesel vehicles. Then, it proposes a new feature engineering processing method that uses gray correlation analysis and principal component analysis to eliminate invalid data and reduce the dimensionality of the aligned data, which facilitates the rapid convergence of the model during the training process. Then, a double-hidden-layer BP (Back propagation) neural network was established, and the improved gray wolf algorithm was used to optimize the threshold and weight of the neural network, and a heavy-duty diesel vehicle NOx emission prediction model was obtained. Through the training of the network, the root mean square error (RMSE) of the improved model on the test set between the predicted value and the true value is 1.9144 (mg/s), and the coefficient of determination (R2) is 0.87024. Compared with single-hidden-layer network and double-hidden-layer BP neural network models, the accuracy of the model has been improved. The model can well predict the actual road NOx emissions of heavy-duty diesel vehicles.

Background The Perceived Stress Scale (PSS) is a globally used and self-report scale measuring perceived stress. Three versions of PSS (PSS-14, PSS-10 and PSS-4) are available which comprise 14, 10 and 4 items respectively. However, the Chinese version of the PSS has not yet been validated in a large community-based general population. The aims of this study were to evaluate the psychometric properties of the Chinese PSS in a large community-based general population and to compare the appropriateness of the three versions of PSS. Methods A total of 9507 adults with at least a junior high school education and completed PSS-14 from the China Health and Nutrition Survey were involved in this study. The internal consistency reliability of PSS was assessed using Cronbach’s alpha coefficient and confirmatory factor analysis was employed to test the construct validity. Modification index was used for model extension and the critical ratio was used for model restriction. Results The internal consistency coefficients were satisfactory for PSS-14 and PSS-10, but not for PSS-4. The corresponding Cronbach’s alpha were 0.830, 0.754 and 0.473 respectively. A 2-factor structure was confirmed for the PSS-14 and PSS-10, and all items’ standardized factor loadings exceeded 0.4 for either negative or positive factors. Given that item 12 loaded on both negative and positive factors for PSS-14 and the goodness of fit for PSS-14 was not acceptable, PSS-13 (PSS-14 excluding item 12) was studied. The construct validities of PSS-13 and PSS-10 were satisfactory, but the goodness of fit for PSS-10 were better than that for PSS-13. Conclusions PSS-13 (PSS-14 excluding item 12) and PSS-10 have satisfactory psychometric properties. PSS-10 are more applicable to measure the perceived stress than PSS-13 in a large community-based general population in China.

Demodulating Orthogonal Frequency Division Multiplexing (OFDM) signals in complex wireless environments remains a fundamental challenge, especially when traditional receiver designs rely on explicit channel estimation under adverse conditions such as low signal-to-noise ratio (SNR) or carrier frequency offset (CFO). Motivated by practical challenges in decoding DroneID—a proprietary OFDM-like signaling format used by DJI drones with a nonstandard frame structure—we present TranSIC-Net, a Transformer-based end-to-end neural network that unifies channel estimation and symbol detection within a single architecture. Unlike conventional methods that treat these steps separately, TranSIC-Net implicitly learns channel dynamics from pilot patterns and exploits the attention mechanism to capture inter-subcarrier correlations. While initially developed to tackle the unique structure of DroneID, the model demonstrates strong generalizability: with minimal adaptation, it can be applied to a wide range of OFDM systems. Extensive evaluations on both synthetic OFDM waveforms and real-world unmanned aerial vehicle (UAV) signals show that TranSIC-Net consistently outperforms least-squares plus zero-forcing (LS+ZF) and leading deep learning baselines such as ProEsNet in terms of bit error rate (BER), estimation accuracy, and robustness—highlighting its effectiveness and flexibility in practical wireless communication scenarios.

Background N6-methyladenosine (m 6 A) modification is the most common chemical modification in mammalian mRNAs, and it plays important roles by regulating several cellular processes. Previous studies report that m 6 A is implicated in modulating tumorigenesis and progression. However, dysregulation of m 6 A modification and effect of m 6 A demethylase fat-mass and obesity-associated protein (FTO) on glucose metabolism has not been fully elucidated in papillary thyroid cancer (PTC). Methods Quantitative real-time PCR (qRT-PCR), western blotting and immunohistochemistry were performed to explore the expression profile of FTO in PTC tissues and adjacent non-cancerous thyroid tissues. Effects of FTO on PTC glycolysis and growth were investigated through in vitro and in vivo experiments. Mechanism of FTO-mediated m 6 A modification was explored through transcriptome-sequencing (RNA-seq), methylated RNA immunoprecipitation sequencing (MeRIP-seq), MeRIP-qPCR, luciferase reporter assays, RNA stability assay and RNA immunoprecipitation assay. Results FTO expression was significantly downregulated in PTC tissues. Functional analysis showed that FTO inhibited PTC glycolysis and growth. Further analyses were conducted to explore FTO-mediated m 6 A modification profile in PTC cells and Apolipoprotein E (APOE) was identified as the target gene for FTO-mediated m 6 A modification using RNA-seq and MeRIP-seq. FTO knockdown significantly increased APOE mRNA m 6 A modification and upregulated its expression. FTO-mediated m 6 A modification of APOE mRNA was recognized and stabilized by the m 6 A reader IGF2BP2. The findings showed that APOE also promoted tumor growth through glycolysis in PTC. Analysis showed that FTO/APOE axis inhibits PTC glycolysis by modulating IL-6/JAK2/STAT3 signaling pathway. Conclusion FTO acts as a tumor suppressor to inhibit tumor glycolysis in PTC. The findings of the current study showed that FTO inhibited expression of APOE through IGF2BP2-mediated m 6 A modification and may inhibit glycolytic metabolism in PTC by modulating IL-6/JAK2/STAT3 signaling pathway, thus abrogating tumor growth.