Brain Age Estimation from Overnight Sleep Electroencephalography with Multi-Flow Sequence Learning.

Purpose: This study aims to improve brain age estimation by developing a novel deep learning model utilizing overnight electroencephalography (EEG) data. Methods: We address limitations in current brain age prediction methods by proposing a model trained and evaluated on multiple cohort data, covering a broad age range. The model employs a one-dimensional Swin Transformer to efficiently extract complex patterns from sleep EEG signals and a convolutional neural network with attentional mechanisms to summarize sleep structural features. A multi-flow learning-based framework attentively merges these two features, employing sleep structural information to direct and augment the EEG features. A post-prediction model is designed to integrate the age-related features throughout the night. Furthermore, we propose a DecadeCE loss function to address the problem of an uneven age distribution. Results: We utilized 18,767 polysomnograms (PSGs) from 13,616 subjects to develop and evaluate the proposed model. The model achieves a mean absolute error (MAE) of 4.19 and a correlation of 0.97 on the mixed-cohort test set, and an MAE of 6.18 years and a correlation of 0.78 on an independent test set. Our brain age estimation work reduced the error by more than 1 year compared to other studies that also used EEG, achieving the level of neuroimaging. The estimated brain age index demonstrated longitudinal sensitivity and exhibited a significant increase of 1.27 years in individuals with psychiatric or neurological disorders relative to healthy individuals. Conclusion: The multi-flow deep learning model proposed in this study, based on overnight EEG, represents a more accurate approach for estimating brain age. The utilization of overnight sleep EEG for the prediction of brain age is both cost-effective and adept at capturing dynamic changes. These findings demonstrate the potential of EEG in predicting brain age, presenting a noninvasive and accessible method for assessing brain aging.

[Recent advances in protein precipitation-based methods for drug-target screening].

Drug targets are biological macromolecules that bind drug molecules in vivo. Therefore, the system-wide identification of drug targets plays a vital role in fully understanding the mechanism of drug action, efficacy, and side effects. The unbiased screening of drug targets may accelerate the process of drug discovery and candidate screening. Mass spectrometry is a key tool for large-scale protein identification and accurate quantification owing to its high acquisition speed, resolution, and sensitivity. Mass spectrometry-based proteomics has been widely used for drug-target screening. It can systematically identify the protein-target landscape of a drug and elucidate drug-protein interactions. Commonly used drug-target characterization methods, such as labeling-based affinity enrichment, require the chemical derivatization of drug molecules, which is not only time-consuming but may also affect the affinity of the drug towards its targets. Furthermore, the spatial effects of the derivatization groups may block interactions between the drug and its targets. Considering the disadvantages of affinity-enrichment methods, strategies that do not require chemical derivatization have received widespread attention. Proteins may undergo denaturation, unfolding, and precipitation under different conditions such as high temperatures, extreme pH, denaturants, and mechanical stress. Binding to small-molecule drugs may alter the folding balance of target proteins. The conformational stability of target proteins can be stabilized by binding with drugs, and protein-drug complexes are more resistant than free proteins to the precipitation induced by different conditions. Based on this mechanism, various large-scale drug-target identification methods using protein precipitation have been developed by combining proteomics and mass spectrometry analysis, including thermal proteome profiling and solvent-, mechanical stress-, and pH-induced protein precipitation. These methods have been successfully applied to the characterization of small-molecule drug targets. In this review, we describe the protein precipitation-based methods used for the high-throughput discovery of drug targets and elucidation of the interactions between drugs and proteins in the past decade. We also summarize the characteristics of each method and discuss their application potential in drug-efficacy evaluation and drug discovery.

Suppression of P53 Pathway is an Important Factor Inducing Acute Graft-versus-Host Disease Through T Cell Activation Based on Bioinformatics Analysis.

Purpose: Acute graft-versus-host disease (aGVHD) poses a significant impediment to achieving a more favourable therapeutic outcome in allogeneic hematopoietic stem cell transplantation (allo-HSCT). The tumour suppressor p53 plays a pivotal role in preventing aGVHD development. However, whether P53 pathway which contains p53 family members and other related genes participates in aGVHD development remains an unsolved question. Patients and Methods: Transcriptomic data was obtained from Gene Expression Omnibus (GEO) database. Gene set enrichment analysis was applied to determine the enrichment degree of signaling pathways. CIBERSORT and ssGSVA were used to evaluate immune cell compositions. Univariate and multivariate logistic regression analysis were performed to examine the independent diagnostic variables. qRT-PCR was utilized to validate the genes expression levels in our cohort. Results: A total number of 102 patients (42 aGVHD patients vs 60 non-aGVHD patients) were obtained after integrating two datasets in GEO database (GSE73809 and GSE4624). P53 pathway was remarkably suppressed in T cells from aGVHD patients and negatively associated with activated T cells as well as T cells activation related signaling pathways, including T-cell receptor (TCR), mTORC1, MYC and E2F target pathways. A risk model for aGVHD built by four genes (DDIT3, FBXW7, TPRKB and TOB1) in P53 pathway, exhibiting high differentiate and predictive value. DDIT3 and FBXW7 mRNA expression levels significantly decreased in peripheral blood mononuclear cells (PBMCs) from aGVHD patients compared with non-aGVHD group in our patient cohort, consisting with bioinformatics analysis. Conclusion: P53 pathway plays a potential role in impeding T cell activation through suppressing its related signaling pathways, thereby preventing aGVHD development. P53 pathway may emerge as a promising therapeutic target in aGVHD treatment.

Evaluating the Usability of mHealth Apps: An Evaluation Model Based on Task Analysis Methods and Eye Movement Data.

Advancements in information technology have facilitated the emergence of mHealth apps as crucial tools for health management and chronic disease prevention. This research work focuses on mHealth apps for the management of diabetes by patients on their own. Given that China has the highest number of diabetes patients in the world, with 141 million people and a prevalence rate of 12.8% (mentioned in the Global Overview of Diabetes), the development of a usability research methodology to assess and validate the user-friendliness of apps is necessary. This study describes a usability evaluation model that combines task analysis methods and eye movement data. A blood glucose recording application was designed to be evaluated. The evaluation was designed based on the model, and the feasibility of the model was demonstrated by comparing the usability of the blood glucose logging application before and after a prototype modification based on the improvement suggestions derived from the evaluation. Tests showed that an improvement plan based on error logs and post-task questionnaires for task analysis improves interaction usability by about 24%, in addition to an improvement plan based on eye movement data analysis for hotspot movement acceleration that improves information access usability by about 15%. The results demonstrate that this study presents a usability evaluation model for mHealth apps that enables the effective evaluation of the usability of mHealth apps.

ABE-ultramax for high-efficiency biallelic adenine base editing in zebrafish.

Advancements in CRISPR technology, particularly the development of base editors, revolutionize genetic variant research. When combined with model organisms like zebrafish, base editors significantly accelerate and refine in vivo analysis of genetic variations. However, base editors are restricted by protospacer adjacent motif (PAM) sequences and specific editing windows, hindering their applicability to a broad spectrum of genetic variants. Additionally, base editors can introduce unintended mutations and often exhibit reduced efficiency in living organisms compared to cultured cell lines. Here, we engineer a suite of adenine base editors (ABEs) called ABE-Ultramax (Umax), demonstrating high editing efficiency and low rates of insertions and deletions (indels) in zebrafish. The ABE-Umax suite of editors includes ABEs with shifted, narrowed, or broadened editing windows, reduced bystander mutation frequency, and highly flexible PAM sequence requirements. These advancements have the potential to address previous challenges in disease modeling and advance gene therapy applications.

Heterologous expression and characterization of two delta glutathione S-transferases genes involved in imidacloprid metabolism in Grapholita molesta.

Glutathione S-transferases (GSTs) are multifunctional enzymes, and insect GSTs play a pivotal role in the metabolism of insecticides. Grapholita molesta is a worldwide pest that causes substantial economic losses to the fruit industry. However, it remains unclear how imidacloprid, a commonly used insecticide in orchards, is metabolized by G. molesta. In the present study, the synergist diethyl maleate (DEM), which inhibits the GST activity, exhibited a 22-fold synergistic ratio against imidacloprid. Two new GST genes, GmGSTD2 (OR096251) and GmGSTD3 (OR096252), were identified and successfully cloned, showing the highest expression in the Malpighian tubes. Knockdown of GmGSTD2 and GmGSTD3 by RNA interference, increased the mortality of G. molesta from 28% to 47% following imidacloprid treatment. Both recombinant GmGSTD2 and GmGSTD3 proteins exhibited 1-chloro-2,4-dinitrobenzene (CDNB) activity and could be inhibited by imidacloprid in vitro, with maximum inhibition was 60% for GmGSTD2 and 80% for GmGSTD3. These results suggested that GSTs participate in the metabolism of imidacloprid with GmGSTD2 and GmGSTD3 playing key roles in this process.

Reconstructing high-resolution gridded precipitation data in the southwest China highland canyon area using an improved (MGWR) downscaling method.

High-spatiotemporal-resolution rainfall data are vital for investigating local terrestrial water cycles. Although remote-sensing satellite retrieval of precipitation products effectively reproduces spatial patterns of rainfall, it suffers from low spatial resolution. To overcome such limitations, a two-step downscaling approach is proposed here. First, 80 % of the meteorological-station data is utilized to calibrate the original Global Precipitation Measurement (GPM) data, enhancing the correlation between GPM and station data. Subsequently, utilizing elevation, slope, aspect, the normalized difference vegetation index (NDVI), wind direction, water vapor, and land surface temperature, as well as slope and aspect correction factors, as independent variables, multiscale geographically weighted regression (MGWR) and temporal lag MGWR (TL-MGWR) models were constructed. Through the aforementioned steps, downscaled monthly and daily precipitation data for the geographic region under investigation in 2022 at a spatial resolution of 0.01° were obtained. Our findings indicate that selectively employing suitable MGWR or TL-MGWR models on a monthly basis can effectively downscale monthly GPM rainfall data. The downscaled (original) monthly precipitation data exhibited a correlation of 0.94 (0.768), with a mean absolute error (MAE) of 16.233 mm/month, root-mean-square error (RMSE) of 27.106 mm/month, and bias of -0.043. Similar enhancement was likewise noted in daily precipitation, displaying a correlation coefficient of 0.863 (0.318) for downscaled (original) data, and a RMSE of 3.209 mm/day, MAE of 1.082 mm/day, and bias of -0.06. The downscaled results show a correlation increase of 0.172 monthly and 0.545 daily, with MAE reductions of 18.43 mm/month and 1.658 mm/day, RMSE reductions of 26.172 mm/month and 4.183 mm/day, and bias reductions of 82.7 % and 56.8 %. In summary, the data after downscaling, both for monthly and daily datasets, was markedly improved in accuracy. The proposed downscaling method is applicable for reconstructing high-resolution grid data in the complex terrain of the southwest China highland canyon area.

High-performance Piezoelectric Two-dimensional Covalent Organic Frameworks.

Organic piezoelectric nanogenerators (PENGs) are attractive in harvesting mechanical energy for various self-powering systems. However, their practical applications are severely restricted by their low output open circuit voltage. To address this issue, herein, we prepared two two-dimensional (2D) covalent organic frameworks (COFs, CityU-13 and CityU-14), functionalized with fluorinated alkyl chains for PENGs. The piezoelectricity of both COFs was evidenced by switchable polarization, characteristic butterfly amplitude loops, phase hysteresis loops, conspicuous surface potentials and high piezoelectric coefficient value (d33). The PENGs fabricated with COFs displayed highest output open circuit voltages (60 V for CityU-13 and 50 V for CityU-14) and delivered satisfactory short circuit current with an excellent stability of over 600 seconds. The superior open circuit voltages of CityU-13 and CityU-14 rank in top 1 and 2 among all reported organic materials-based PENGs.

Reversible modulation of superconductivity in thin-film NbSe2 via plasmon coupling.

In recent years, lightwave has stood out as an ultrafast, non-contact control knob for developing compact superconducting circuitry. However, the modulation efficiency is limited by the low photoresponse of superconductors. Plasmons, with the advantages of strong light-matter interaction, present a promising route to overcome the limitations. Here we achieve effective modulation of superconductivity in thin-film NbSe2 via near-field coupling to plasmons in gold nanoparticles. Upon resonant plasmon excitation, the superconductivity of NbSe2 is substantially suppressed. The modulation factor exceeds 40% at a photon flux of 9.36 × 1013 s-1mm-2, and the effect is significantly diminished for thicker NbSe2 samples. Our observations can be theoretically interpreted by invoking the non-equilibrium electron distribution in NbSe2 driven by the plasmon-associated evanescent field. Finally, a reversible plasmon-driven superconducting switch is realized in this system. These findings highlight plasmonic tailoring of quantum states as an innovative strategy for superconducting electronics.

Pancreatic cancer mortality trends attributable to high fasting blood sugar over the period 1990-2019 and projections up to 2040.

Background: Pancreatic cancer (PC) is a prevalent malignancy within the digestive system, with diabetes recognized as one of its well-established risk factors. Methods: Data on PC mortality attributed to high fasting blood sugar were retrieved from the Global Burden of Disease (GBD) study 2019 online database. To assess the temporal trends of PC burden attributable to high fasting plasma glucose (HFPG), estimated annual percentage changes (EAPCs) for age-standardized death rates (ASDRs) between 1990 and 2019 were determined using a generalized linear model. Furthermore, a Bayesian age-period-cohort (BAPC) model using the integrated nested Laplacian approximation algorithm was employed to project the disease burden over the next 20 years. Results: Globally, the crude death number of PC attributable to HFPG almost tripled (from 13,065.7 in 1990 to 48,358.5 in 2019) from 1990 to 2019, and the ASDR increased from 0.36/100,000 to 0.61/100,000 with an EAPC of 2.04 (95% CI 1.91-2.16). The population aged ≥70 years accounted for nearly 60% of total deaths in 2019 and experienced a more significant increase, with the death number increasing approximately fourfold and the ASDR increasing annually by 2.65%. In regions with different sociodemographic indexes (SDIs), the highest disease burden was observed in the high-SDI region, whereas more pronounced increasing trends in ASDR were observed in the low to middle-SDI, low-SDI, and middle-SDI regions. Additionally, a significantly negative association was found between EAPCs and ASDRs of PC attributable to HFPG from 1990 to 2019. Moreover, the BAPC model predicts that ASDR and age-standardized disability-adjusted life-years (DALYs) rate for PC attributed to HFPG was projected to increase obviously for men and women from 2019 to 2040. Conclusions: The burden of PC attributed to HFPG has increased globally over the past three decades, with the elderly population and high-SDI regions carrying a relatively greater disease burden, but more adverse trends observed in low-SDI areas. Furthermore, the burden is projected to continue increasing over the next 20 years. Hence, more tailored prevention methodologies should be established to mitigate this increasing trend.

Association between enlarged perivascular spaces in basal ganglia and cerebral perfusion in elderly people.

Background and objective: Enlarged perivascular spaces in basal ganglia (BG-EPVS) are considered an imaging marker of cerebral small vessel disease (CSVD), but its pathogenesis and pathophysiological process remain unclear. While decreased cerebral perfusion is linked to other CSVD markers, the relationship between BG-EPVS and cerebral perfusion remains ambiguous. This study aimed to explore this association. Methods: Elderly individuals with severe BG-EPVS (n = 77) and age/sex-matched controls (n = 89) underwent head CT perfusion imaging. The cerebral perfusion parameters including mean transit time (MTT), time to maximum (TMAX), cerebral blood flow (CBF), and cerebral blood volume (CBV) were quantitatively measured by symmetric regions of interest plotted in the basal ganglia region. Point-biserial correlation and logistics regression analysis were performed to investigate the association between BG-EPVS and cerebral perfusion. Results: There were no significant differences in MTT, TMAX, or CBF between BG-EPVS group and control group. CBV was significantly lower in the BG-EPVS group (p = 0.035). Point-biserial correlation analysis showed a negative correlation between BG-EPVS and CBV (r = -0.198, p = 0.011). BG-EPVS group and control group as the dependent variable, binary logistics regression analysis showed that CBV was not an independent risk factor for severe BG-EPVS (p = 0.448). All enrolled patients were divided into four groups according to the interquartile interval of CBV. The ordered logistic regression analysis showed severe BG-EPVS was an independent risk factor for decreased CBV after adjusting for confounding factors (OR = 2.142, 95%CI: 1.211-3.788, p = 0.009). Conclusion: Severe BG-EPVS is an independent risk factor for decreased CBV in the elderly, however, the formation of BG-EPVS is not solely dependent on changes in CBV in this region. This finding provides information about the pathophysiological consequence caused by severe BG-EPVS.

Unveiling the fast adsorption and desorption of heavy metals on/off nanoplastics by real-time in-situ potentiometric sensing.

Nanoplastics (<1 µm) can serve as a transport vector of environmental pollutants (e.g., heavy metals) and change their toxicities and bioavailabilities. Up to date the behaviors of adsorption and desorption heavy metals on/off nanoplastics are largely unknown. Herein, polymeric membrane potentiometric ion sensors are proposed for in-situ assessment of the real-time kinetics of heavy metal adsorption and desorption on/off nanoplastics. Results show that nanoplastics can adsorb and release heavy metals in a fast manner, indicating their superior ability in transferring heavy metals. The adsorption behaviors are closely related to the characteristics of nanoplastics and background electrolytes. Particle aggregation and increases in salinity and acidity suppress the adsorption of heavy metals on nanoplastics. The desorption efficiencies of different heavy metals are Pb2+ (31 %) < Cu2+ (40 %) < Cd2+ (97 %). Our proposed method is applicable for the detection of the plastic pollutants with size <100 nm and of the samples with high salinities (e.g., seawater). This work would provide new insights into the assessment of environmental risks posed by nanoplastics and heavy metals.

Mediation effect of sleep time on the association between outdoor activity and myopia in Chinese children and adolescents: a cross-sectional study.

BACKGROUND: This study aimed to assess the association between outdoor activity and myopia among children and adolescents and investigate whether sleep time could mediate this relationship. METHODS: This cross-sectional study was performed on students aged 4-16 years in China, from August 2021 to January 2022. Outdoor activity was assessed by the Assessment Questionnaire of Exposure to Sunlight Activities for Students (AQESAS). Binary logistic regression combined with the mediation analysis was used to analyze the association of AQESAS with myopia and the mediating effect of sleep time on this relationship. RESULTS: The prevalence of myopia was 53.51% (N = 1609). Multivariate logistic regression analysis showed that more sleep time (OR = 0.794, 95%CI: 0.707-0.893) and a higher score of AQESAS (OR = 0.989, 95%CI: 0.981-0.996) were significantly associated with a decreased risk of myopia. Mediation analysis revealed that sleep time plays a mediating role in the association between outdoor activity and myopia (ACME = -0.0006, P < 0.001), and the mediation proportion was 19.7%. CONCLUSION: Outdoor activity affects myopia directly and indirectly through sleep time. The result suggested that children may be able to reduce the risk of myopia by promoting sleep through increased awareness of outdoor activity and exposure to sunlight.

Wafer-Scale Patterning Integration of Chiral 3D Perovskite Single Crystals toward High-Performance Full-Stokes Polarimeter.

Chiral three-dimensional (3D) perovskites exhibit exceptional optoelectronic characteristics and inherent chiroptical activity, which may overcome the limitations of low-dimensional chiral optoelectronic devices and achieve superior performance. The integrated chip of high-performance arbitrary polarized light detection is one of the aims of chiral optoelectronic devices and may be achieved by chiral 3D perovskites. Herein, we first fabricate the wafer-scale integrated full-Stokes polarimeter by the synergy of unprecedented chiral 3D perovskites (R/S-PyEA)Pb2Br6 and one-step capillary-bridge assembly technology. Compared with the chiral low-dimensional perovskites, chiral 3D perovskites present smaller exciton binding energies of 57.3 meV and excellent circular dichroism (CD) absorption properties, yielding excellent circularly polarized light (CPL) photodetectors with an ultrahigh responsivity of 86.7 A W-1, an unprecedented detectivity exceeding 4.84 × 1013 Jones, a high anisotropy factor of 0.42, and high-fidelity CPL imaging with 256 pixels. Moreover, the anisotropic crystal structure also enables chiral 3D perovskites to have a large linear-polarization response with a polarized ratio of 1.52. The combination of linear-polarization and circular-polarization discrimination capabilities guarantees the achievement of a full-Stokes polarimeter. Our study provides new research insights for the large-scale patterning wafer integration of high-performance chiroptical devices.

EVIDENCE FOR AUDITORY STIMULUS-SPECIFIC ADAPTATION BUT NOT DEVIANCE DETECTION IN LARVAL ZEBRAFISH BRAINS.

Animals receive a constant stream of sensory input, and detecting changes in this sensory landscape is critical to their survival. One signature of change detection in humans is the auditory mismatch negativity (MMN), a neural response to unexpected stimuli that deviate from a predictable sequence. This process requires the auditory system to adapt to specific repeated stimuli while remaining sensitive to novel input (stimulus-specific adaptation). MMN was originally described in humans, and equivalent responses have been found in other mammals and birds, but it is not known to what extent this deviance detection circuitry is evolutionarily conserved. Here we present the first evidence for stimulus-specific adaptation in the brain of a teleost fish, using whole-brain calcium imaging of larval zebrafish at single-neuron resolution with selective plane illumination microscopy. We found frequency-specific responses across the brain with variable response amplitudes for frequencies of the same volume, and created a loudness curve to model this effect. We presented an auditory 'oddball' stimulus in an otherwise predictable train of pure tone stimuli, and did not find a population of neurons with specific responses to deviant tones that were not otherwise explained by stimulus-specific adaptation. Further, we observed no deviance responses to an unexpected omission of a sound in a repetitive sequence of white noise bursts. These findings extend the known scope of auditory adaptation and deviance responses across the evolutionary tree, and lay groundwork for future studies to describe the circuitry underlying auditory adaptation at the level of individual neurons.

A prospective study on maternal periodontal diseases and neonatal adverse outcomes.

OBJECTIVE: It is evident that periodontitis is linked to various adverse pregnancy outcomes. This prospective study explored the potential link of maternal periodontal diseases to neonatal adverse outcomes. MATERIALS AND METHODS: A total of 193 generally healthy females in their third trimester (34-36 weeks) of pregnancy were enrolled. All subjects received full-mouth periodontal assessment, and the periodontal inflamed surface area (PISA) was calculated. Demographic data, lifestyles and anthropometric measurements of the neonates (e.g., body length and head circumference) were recorded. Herein, small-for-gestational age (SGA) referred to gender- and age-adjusted birth weight below the 10th percentile in line with the standard reference. Multivariable logistic regression analysis and restricted cubic spline were performed for examining the association of periodontal parameters with SGA.  Results: There were 8.3% (16/193) of neonates with SGA. Significantly positive correlation existed between the percentage of tooth sites with increased probing depth and an elevated risk of SGA (OR: 1.052; P < 0.05). Yet, the PISA was positively associated with the risk of SGA (OR: 1.002; P < 0.05) as well. No significant link occurred between maternal periodontal status and other neonatal outcome measures. CONCLUSION: Within the limitations of this study, the findings suggest that there could be a link between maternal periodontal diseases and neonatal adverse outcomes like SGA. Further investigation is required to clarify the current findings and potential implications for promoting maternal oral/periodontal health and newborn health.

Knowledge, attitudes, and practices (KAPs) regarding tick-borne rickettsial disease among medical staff in endemic areas of China.

Tick-borne rickettsial disease (TBRD) is a perilous acute infection that often eludes diagnosis in its early stages. The triad of knowledge, attitudes, and practices (KAPs) among medical professionals is key to reducing missed diagnosis rates. Therefore, a meticulous evaluation of KAPs is imperative. This study aimed to delve into the understanding of TBRD and explore the beliefs and practices related to personal prevention methods among individuals in Lu'an, a hotspot for TBRD. During the summer months of 2023, convenience sampling was employed by circulating a confidential questionnaire to 1,206 participants in the endemic regions of China. This questionnaire painted a comprehensive picture of the participants' sociodemographic profiles and their KAPs levels vis-à-vis TBRD. The findings revealed that participants scored a mere 55.78% in knowledge, while their attitudes and practices garnered impressive scores of 90.09% and 90.83%, respectively. Upon further analysis using multiple linear regression, several intriguing patterns emerged. Male participants, employed in the Infectious Disease Department, held vice-senior or higher titles, or had prior medical training demonstrated superior knowledge scores. On the other hand, medical personnel who were younger than 30, possessed graduate degrees or higher qualifications, and had training excelled in attitudes and practices. Notably, when employing the Boston Consulting Group (BCG) matrix, a significant distribution of medical personnel was observed across the four quadrants. Specifically, 37.43%, 13.19%, 19.61%, and 29.77% fell into the first, second, third, and fourth quadrants. This survey underscores the commendable attitudes and practices of medical staff towards TBRD in endemic regions of China. However, their knowledge level remains wanting and demands urgent improvement.

Epidemiological exploration of the impact of bluetooth headset usage on thyroid nodules using Shapley additive explanations method.

With an increasing prevalence of thyroid nodules globally, this study investigates the potential correlation between the use of Bluetooth headsets and the incidence of thyroid nodules, considering the cumulative effects of non-ionizing radiation (NIR) emitted by these devices. In this study, we analyzed 600 valid questionnaires from the WenJuanXing platform using Propensity Score Matching (PSM) and the XGBOOST model, supplemented by SHAP analysis, to assess the risk of thyroid nodules. PSM was utilized to balance baseline characteristic differences, thereby reducing bias. The XGBOOST model was then employed to predict risk factors, with model efficacy measured by the area under the Receiver Operating Characteristic (ROC) curve (AUC). SHAP analysis helped quantify and explain the impact of each feature on the prediction outcomes, identifying key risk factors. Initially, 600 valid questionnaires from the WenJuanXing platform underwent PSM processing, resulting in a matched dataset of 96 cases for modeling analysis. The AUC value of the XGBOOST model reached 0.95, demonstrating high accuracy in differentiating thyroid nodule risks. SHAP analysis revealed age and daily Bluetooth headset usage duration as the two most significant factors affecting thyroid nodule risk. Specifically, longer daily usage durations of Bluetooth headsets were strongly linked to an increased risk of developing thyroid nodules, as indicated by the SHAP analysis outcomes. Our study highlighted a significant impact relationship between prolonged Bluetooth headset use and increased thyroid nodule risk, emphasizing the importance of considering health impacts in the use of modern technology, especially for devices like Bluetooth headsets that are frequently used daily. Through precise model predictions and variable importance analysis, our research provides a scientific basis for the formulation of public health policies and personal health habit choices, suggesting that attention should be paid to the duration of Bluetooth headset use in daily life to reduce the potential risk of thyroid nodules. Future research should further investigate the biological mechanisms of this relationship and consider additional potential influencing factors to offer more comprehensive health guidance and preventive measures.

Micro/nano-plastics impacts in cardiovascular systems across species.

The widespread presence of microplastics and nanoplastics (MPs/NPs) in the environment has become a critical public health issue due to their potential to infiltrate and affect various biological systems. Our review is crucial as it consolidates current data and provides a comprehensive analysis of the cardiovascular impacts of MPs/NPs across species, highlighting significant implications for human health. By synthesizing findings from studies on aquatic and terrestrial organisms, including humans, this review offers insights into the ubiquity of MPs/NPs and their pathophysiological roles in cardiovascular systems. We demonstrated that exposure to MPs/NPs is linked to various cardiovascular ailments such as thrombogenesis, vascular damage, and cardiac impairments in model organisms, which likely extrapolate to humans. Our review critically evaluated methods for detecting MPs/NPs in biological tissues, assessing their toxicity, and understanding their behaviour within the vasculature. These findings emphasise the urgent need for targeted public health strategies and enhanced regulatory measures to mitigate the impacts of MP/NP pollution. Furthermore, the review underlined the necessity of advancing research methodologies to explore long-term effects and potential intergenerational consequences of MP/NP exposure. By mapping out the intricate links between environmental exposure and cardiovascular risks, our work served as a pivotal reference for future research and policymaking aimed at curbing the burgeoning threat of plastic pollution.

Neuro-cardiac-guided transcranial magnetic stimulation: Unveiling the modulatory effects of low-frequency and high-frequency stimulation on heart rate.

Transcranial magnetic stimulation (TMS) is pivotal in the field of major depressive disorder treatment. Due to its unsatisfied response rate, an increasing number of researchers have turned their attention towards optimizing TMS site localization. Since the influence of TMS in reducing heart rate (HR) offers insights into its regulatory impact on the autonomic nervous system, a novel approach, called neurocardiac-guided TMS (NCG-TMS), has been proposed to pinpoint the brain region eliciting the maximal individual reduction in HR as a personalized optimal stimulation target. The present study intends to systematically explore the effects of stimulation frequency, left and right hemispheres, stimulation positions, and individual differences on HR modulation using the NCG-TMS method. In experiment 1, low-frequency TMS was administered to 30 subjects, and it was found that low-frequency NCG-TMS significantly downregulated HR, with more significant effects in the right hemisphere than in the left hemisphere and the prefrontal cortex than in other brain areas. In experiment 2, high-frequency NCG-TMS stimulation was administered to 30 subjects, showing that high-frequency NCG-TMS also downregulated HR and had the greatest modulatory effect in the right prefrontal region. Simultaneously, both experiments revealed sizeable individual variability in the optimal stimulation site, which in turn validated the feasibility of the NCG-TMS method. In conclusion, the present experiments independently replicated the effect of NCG-TMS, provided an effect of high-/low-frequency TMS stimulation to downregulate HR, and identified a right lateralization of the HR modulation effect.