Multimodal Sensing for Depression Risk Detection: Integrating Audio, Video, and Text Data.

Depression is a major psychological disorder with a growing impact worldwide. Traditional methods for detecting the risk of depression, predominantly reliant on psychiatric evaluations and self-assessment questionnaires, are often criticized for their inefficiency and lack of objectivity. Advancements in deep learning have paved the way for innovations in depression risk detection methods that fuse multimodal data. This paper introduces a novel framework, the Audio, Video, and Text Fusion-Three Branch Network (AVTF-TBN), designed to amalgamate auditory, visual, and textual cues for a comprehensive analysis of depression risk. Our approach encompasses three dedicated branches-Audio Branch, Video Branch, and Text Branch-each responsible for extracting salient features from the corresponding modality. These features are subsequently fused through a multimodal fusion (MMF) module, yielding a robust feature vector that feeds into a predictive modeling layer. To further our research, we devised an emotion elicitation paradigm based on two distinct tasks-reading and interviewing-implemented to gather a rich, sensor-based depression risk detection dataset. The sensory equipment, such as cameras, captures subtle facial expressions and vocal characteristics essential for our analysis. The research thoroughly investigates the data generated by varying emotional stimuli and evaluates the contribution of different tasks to emotion evocation. During the experiment, the AVTF-TBN model has the best performance when the data from the two tasks are simultaneously used for detection, where the F1 Score is 0.78, Precision is 0.76, and Recall is 0.81. Our experimental results confirm the validity of the paradigm and demonstrate the efficacy of the AVTF-TBN model in detecting depression risk, showcasing the crucial role of sensor-based data in mental health detection.

Association Between Myopia and Pupil Diameter in Preschoolers: Evidence from a Machine Learning Approach Based on a Real-World Large-Scale Dataset.

INTRODUCTION: Previous studies have explored the connections between various ocular biological parameters with myopia. Our previous study also found that pupil data can predict the myopic progression during the interventions for myopia. However, studies exploring the association between pupil diameter and myopia in preschoolers with myopia were lacking. Hence this study was aimed to investigate the association between pupil diameter and myopia in preschoolers with myopia based on a real-world, large-scale dataset. METHODS: Data containing 650,671 preschoolers were collected from a total of 1943 kindergartens in Shenzhen, China. Refraction and pupil parameters were collected. After data filtering, the occurrence of myopia and its association with age, gender, pupil diameter, and other variables, were analyzed. Random forest (RF) and eXtreme gradient boosting (XGBoost) were selected from seven machine learning algorithms to build the model. The mean decrease accuracy (MDA), mean decrease Gini (MDG), and gain feature importance (GFI) techniques were employed to quantify the importance of pupil diameter and other features. RESULTS: After the assessments, 51,325 valid records with complete pupil data were included, and 3468 (6.76%) were identified as myopia based on the calculated cycloplegic refraction. Preschoolers with myopia presented reduced pupil diameter and greater variation (5.00 ± 0.99 mm) compared to non-myopic preschoolers (6.22 ± 0.67 mm). A nonlinear relationship was found according to the scatterplots between pupil diameter and refraction (R2 = 0.14). Especially preschoolers with myopia had reduced pupil diameter compared to emmetropic preschoolers, but hyperope did not experience additional pupil enlargement. After adjusting for other covariates, this relationship is still consistent (P < 0.001). XGBoost and RF algorithms presented the highest performance and validated the importance of pupil diameter in myopia. CONCLUSIONS: Based on a real-world large-scale dataset, the current study illuminated that preschoolers with myopia had a reduced pupil diameter compared to emmetropic preschoolers with a nonlinear pattern. Machine learning algorithms visualized and validated the pivotal role of pupil diameter in myopia. TRIAL REGISTRATION: chictr.org Identifier: ChiCTR2200057391.

Multimodal and hemispheric graph-theoretical brain network predictors of learning efficacy for frontal alpha asymmetry neurofeedback.

EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09939-x.

Unveiling convergent and divergent intrinsic brain network alternations in depressed adolescents engaged in non-suicidal self-injurious behaviors with and without suicide attempts.

AIMS: Limited understanding exists regarding the neurobiological mechanisms underlying non-suicidal self-injury (NSSI) and suicide attempts (SA) in depressed adolescents. The maturation of brain network is crucial during adolescence, yet the abnormal alternations in depressed adolescents with NSSI or NSSI+SA remain poorly understood. METHODS: Resting-state functional magnetic resonance imaging data were collected from 114 depressed adolescents, classified into three groups: clinical control (non-self-harm), NSSI only, and NSSI+SA based on self-harm history. The alternations of resting-state functional connectivity (RSFC) were identified through support vector machine-based classification. RESULTS: Convergent alterations in NSSI and NSSI+SA predominantly centered on the inter-network RSFC between the Limbic network and the three core neurocognitive networks (SalVAttn, Control, and Default networks). Divergent alterations in the NSSI+SA group primarily focused on the Visual, Limbic, and Subcortical networks. Additionally, the severity of depressive symptoms only showed a significant correlation with altered RSFCs between Limbic and DorsAttn or Visual networks, strengthening the fact that increased depression severity alone does not fully explain observed FC alternations in the NSSI+SA group. CONCLUSION: Convergent alterations suggest a shared neurobiological mechanism along the self-destructiveness continuum. Divergent alterations may indicate biomarkers differentiating risk for SA, informing neurobiologically guided interventions.

Biochar-derived dissolved organic matter enhanced the release of residual ciprofloxacin from the soil solid phase.

Biochar has been utilized to reduce ciprofloxacin (CIP) residues in soil. However, little is known about the effect of biochar-derived dissolved organic matter (DOM) on residual CIP transformation. Thus, we analyzed the residual soil CIP as influenced by biochar generated from rice straw (RS3 and RS6), pig manure (PM3 and PM6), and cockroach shell (CS3 and CS6) at 300 °C and 600 °C. The three-dimensional excitation-emission matrix (3D-EEM), parallel factor analysis (PARAFAC) and two-dimensional correlation spectral analysis (2D-COS) were used to describe the potential variation in the DOM-CIP interaction. Compared with CK, biochar amendment increased the water-soluble CIP content by 160.7% (RS3), 55.2% (RS6), 534.1% (PM3), 277.5% (PM6), 1160.6% (CS3) and 703.9% (CS6), indicating that the biochar feedstock controlled the soil CIP release. The content of water-soluble CIP was positively correlated with the content of dissolved organic carbon (r = 0.922, p < 0.01) and dissolved organic nitrogen (r = 0.898, p < 0.01), suggesting that the major influence of the water-soluble CIP increase was DOM. The fluorescence quenching experiment showed that the interaction between DOM and CIP triggered static quenching and the creation of a DOM complex. The mean log K of protein-like material (4.977) was higher than that of terrestrial humus-like material (3.491), suggesting that the protein-like material complexed CIP was more stable than the humus-like material. Compared with pyrolysis at 300 °C, pyrolysis at 600 °C decreased the stability of the complex of protein-like material and CIP by 0.44 (RS), 1.689 (PM) and 0.548 (CS). This result suggested that the influence of temperature change was more profound on PM biochar-derived DOM than on RS and CS. These insights are essential for understanding CIP transportation in soil and controlling CIP contamination with biochar.

State-Dependent tACS Effects Reveal the Potential Causal Role of Prestimulus Alpha Traveling Waves in Visual Contrast Detection.

The intricate relationship between prestimulus alpha oscillations and visual contrast detection variability has been the focus of numerous studies. However, the causal impact of prestimulus alpha traveling waves on visual contrast detection remains largely unexplored. In our research, we sought to discern the causal link between prestimulus alpha traveling waves and visual contrast detection across different levels of mental fatigue. Using electroencephalography alongside a visual detection task with 30 healthy adults (13 females; 17 males), we identified a robust negative correlation between prestimulus alpha forward traveling waves (FTWs) and visual contrast threshold (VCT). Inspired by this correlation, we utilized 45/-45° phase-shifted transcranial alternating current stimulation (tACS) in a sham-controlled, double-blind, within-subject experiment with 33 healthy adults (23 females; 10 males) to directly modulate these alpha traveling waves. After the application of 45° phase-shifted tACS, we observed a substantial decrease in FTW and an increase in backward traveling waves, along with a concurrent increase in VCT, compared with the sham condition. These changes were particularly pronounced under a low fatigue state. The findings of state-dependent tACS effects reveal the potential causal role of prestimulus alpha traveling waves in visual contrast detection. Moreover, our study highlights the potential of 45/-45° phase-shifted tACS in cognitive modulation and therapeutic applications.

Association between body stature with ocular biometrics and refraction among Chinese preschoolers.

PURPOSE: To evaluate the association of body stature with ocular biometrics and refraction in preschool children. METHODS: A cross-sectional, school-based study was conducted in Shenzhen, China. Preschool children aged 3 to 6 from 10 randomly-selected kindergartens were recruited. Ocular biometric parameters, including axial length (AL), anterior chamber depth (ACD), vitreous chamber depth (VCD), corneal radius curvature (CR), axial length to corneal radius ratio (AL-to-CR ratio) and lens thickness (LT) were measured using non-contact partial-coherence laser interferometry. Cycloplegic refractions were obtained by a desktop autorefractor. Body height and weight were measured using standard procedures. The association between body stature and ocular biometrics were analyzed with univariable and multivariable regression model. RESULTS: A total of 373 preschoolers were included. AL, ACD, VCD, CR, and AL-to-CR ratio, were positively associated with height and weight (p < 0.05), whereas LT was negatively associated with height and weight (p < 0.01). No association was observed between stature and central cornea thickness and refraction. After adjusted for age and gender in a multivariable regression model, AL had positive associations with height (p < 0.01) and weight (p < 0.01). However, refraction had no significant association with stature parameters. CONCLUSION: Taller and heavier preschoolers had eyes with longer AL, deeper vitreous chamber, and flatter cornea. The significant associations between body stature and ocular biometric parameters reveal the driving influence of body development on the growth of eyeballs in preschoolers.

Visual impairment burden in retinopathy of prematurity: trends, inequalities, and improvement gaps.

Retinopathy of prematurity (ROP) is an important cause of avoidable childhood visual impairment, and the increase in number and survival of premature infants may inflate its burden globally. We aimed to comprehensively assess the trends and inequalities in the burden of ROP-related visual impairment and to identify improvement gaps to facilitate appropriate actions in neonatal care systems. We obtained ROP data from the Global Burden of Disease 2019 study. We employed joinpoint regression analysis to assess the trends of the burden of ROP-related visual impairment, measured by age-standardised prevalence rates, health equity analysis methods to evaluate cross-country burden inequalities, and data envelopment and stochastic frontier analyses to identify improvement gaps based on the development status, i.e., sociodemographic index (SDI). Between 1990 and 2019, the age-standardised prevalence rates of ROP-related visual impairment significantly increased worldwide (average annual percentage change: 0.23 [95% confidence interval, 0.21-0.26] among males and 0.26 [0.25-0.27] among females), primarily in developed regions. Although significant SDI-related cross-country inequalities were identified, these reduced over time (slope index of inequality: -57.74 [-66.22 to -49.25] in 1990 to -29.68 [-38.39 to -20.97] in 2019; health concentration index: -0.11 [-0.13 to -0.09] in 1990 to -0.07 [-0.09 to -0.06] in 2019). Notably, some less-developed countries exhibited superior performance despite limited resources, whereas others with a higher SDI delivered lagging performance.  Conclusion: The global burden of ROP-related visual impairment has steadily increased between 1990 and 2019, with disproportionate burden concentration among less-developed countries, requiring appropriate preventive and intervention measures. What is Known: • Retinopathy of prematurity (ROP) is an important cause of avoidable childhood visual impairment. • The prevalence of ROP is anticipated to increase due to the growing number of extremely premature infants. What is New: • The prevalence of ROP-related visual impairment has increased worldwide, primarily in developed regions, with declining but persisting cross-country inequalities. • The increasing burden of ROP-related visual impairment should be considered as part of global and national health agendas, requiring interventions with proven efficacy.

Dynamic reconfiguration of brain coactivation states that underlying working memory correlates with cognitive decline in clinically unimpaired older adults.

Impairments in working memory (WM) are evident in both clinically diagnosed patients with mild cognitive decline and older adults at risk, as indicated by lower scores on neuropsychological tests. Examining the WM-related neural signatures in at-risk older adults becomes essential for timely intervention. WM functioning relies on dynamic brain activities, particularly within the frontoparietal system. However, it remains unclear whether the cognitive decline would be reflected in the decreased dynamic reconfiguration of brain coactivation states during WM tasks. We enrolled 47 older adults and assessed their cognitive function using the Montreal Cognitive Assessment. The temporal dynamics of brain coactivations during a WM task were investigated through graph-based time-frame modularity analysis. Four primary recurring states emerged: two task-positive states with positive activity in the frontoparietal system (dorsal attention and central executive); two task-negative states with positive activity in the default mode network accompanied by negative activity in the frontoparietal networks. Heightened WM load was associated with increased flexibility of the frontoparietal networks, but the cognitive decline was correlated with reduced capacity for neuroplastic changes in response to increased task demands. These findings advance our understanding of aberrant brain reconfiguration linked to cognitive decline, potentially aiding early identification of at-risk individuals.

Insight into the fracture energy dissipation mechanism in elastomer composites via sacrificial bonds and fillers.

Most tough elastomer composites are reinforced by introducing sacrificial structures and fillers. Understanding the contribution of fillers and sacrificial bonds in elastomer composites to the energy dissipation is critical for the design of high-toughness materials. However, the energy dissipation mechanism in elastomer composites remains elusive. In this study, using a tearing test and time-temperature superposition, we investigate the effect of fillers and sacrificial bonds on the energy dissipation of elastomer composites consisting of poly(lipoic acid)/silver-coated Al fillers. We found that the fillers and sacrificial bonds mutually enhance both the intrinsic fracture energy and the bulk energy dissipation, and moreover the sacrificial bonds play a more important role in enhancing fracture toughness than the fillers. It is unreasonable to rely solely on the loss factor for bulk energy dissipation. The addition of sacrificial bonds results in a chain segment experiencing greater binding force compared to the addition of fillers. This suggests that the chain segment consumes more energy during its movement. By calculating the length of the Kuhn chain segment and the Kuhn number, it is evident that the addition of sacrificial bonds results in a greater binding force for the chain segment than the addition of fillers, and this enhanced binding force increases the energy consumption during the motion of the chain segment.

Disrupted morphological brain network organization in subjective cognitive decline and mild cognitive impairment.

We aim to investigate the alterations in gray matter for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) from the perspective of the human connectome. High-resolution T1-weighted images were acquired from 54 patients with SCD, 95 patients with MCI, and 65 healthy controls (HC). Morphological brain networks (MBN) were constructed using similarities in the distribution of gray matter volumes between regions. The strength of morphological connections and topographic metrics derived from the graph-theoretical analysis were compared. Furthermore, we assessed the relationship between the observed morphological abnormalities and disease severity. According to the results, we found a significantly decreased morphological connection between the somatomotor network and ventral attention network in SCD compared to HC and MCI compared to SCD. The graph-theoretic analysis illustrated disruptions in the whole network organization, where the normalized shortest path increased and the global efficiency (Eg) decreased in MCI compared to SCD. In addition, Montreal Cognitive Assessment scores of SCD patients had a significantly negative correlation with Eg. The primary limitations of the present study include the cross-sectional design, no enrolled AD patients, no assessment of amyloidosis, and the need for more comprehensive neuropsychological tests. Our findings indicate the abnormalities of morphological networks at early stages in the AD continuum, which could be interpreted as compensatory changes to retain a normal level of cognitive function. The present study could provide new insight into the mechanism of AD.

Altered cortical and subcortical morphometric features and asymmetries in the subjective cognitive decline and mild cognitive impairment.

Introduction: This study aimed to evaluate morphological changes in cortical and subcortical regions and their asymmetrical differences in individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). These morphological changes may provide valuable insights into the early diagnosis and treatment of Alzheimer's disease (AD). Methods: We conducted structural MRI scans on a cohort comprising 62 SCD patients, 97 MCI patients, and 70 age-, sex-, and years of education-matched healthy controls (HC). Using Freesurfer, we quantified surface area, thickness, the local gyrification index (LGI) of cortical regions, and the volume of subcortical nuclei. Asymmetry measures were also calculated. Additionally, we explored the correlation between morphological changes and clinical variables related to cognitive decline. Results: Compared to HC, patients with MCI exhibited predominantly left-sided surface morphological changes in various brain regions, including the transverse temporal gyrus, superior temporal gyrus, insula, and pars opercularis. SCD patients showed relatively minor surface morphological changes, primarily in the insula and pars triangularis. Furthermore, MCI patients demonstrated reduced volumes in the anterior-superior region of the right hypothalamus, the fimbria of the bilateral hippocampus, and the anterior region of the left thalamus. These observed morphological changes were significantly associated with clinical ratings of cognitive decline. Conclusion: The findings of this study suggest that cortical and subcortical morphometric changes may contribute to cognitive impairment in MCI, while compensatory mechanisms may be at play in SCD to preserve cognitive function. These insights have the potential to aid in the early diagnosis and treatment of AD.

Cauchy non-convex sparse feature selection method for the high-dimensional small-sample problem in motor imagery EEG decoding.

Introduction: The time, frequency, and space information of electroencephalogram (EEG) signals is crucial for motor imagery decoding. However, these temporal-frequency-spatial features are high-dimensional small-sample data, which poses significant challenges for motor imagery decoding. Sparse regularization is an effective method for addressing this issue. However, the most commonly employed sparse regularization models in motor imagery decoding, such as the least absolute shrinkage and selection operator (LASSO), is a biased estimation method and leads to the loss of target feature information. Methods: In this paper, we propose a non-convex sparse regularization model that employs the Cauchy function. By designing a proximal gradient algorithm, our proposed model achieves closer-to-unbiased estimation than existing sparse models. Therefore, it can learn more accurate, discriminative, and effective feature information. Additionally, the proposed method can perform feature selection and classification simultaneously, without requiring additional classifiers. Results: We conducted experiments on two publicly available motor imagery EEG datasets. The proposed method achieved an average classification accuracy of 82.98% and 64.45% in subject-dependent and subject-independent decoding assessment methods, respectively. Conclusion: The experimental results show that the proposed method can significantly improve the performance of motor imagery decoding, with better classification performance than existing feature selection and deep learning methods. Furthermore, the proposed model shows better generalization capability, with parameter consistency over different datasets and robust classification across different training sample sizes. Compared with existing sparse regularization methods, the proposed method converges faster, and with shorter model training time.

Executive functions in non-suicidal self-injury comorbid first-episode and drug-naïve depression among adolescents.

Executive functions(EFs) may be associated with the emergence of non-suicidal self-injury(NSSI) due to their role as behavior controllers. EFs includes three core cognitive processes: inhibitory control, working memory, and cognitive flexibility(i.e. the ability to selectively alter cognitive strategies to generate appropriate behavior in the changing environment). This study aimed to systematically explore the three core EFs in depressed adolescents with NSSI. The data was obtained from the baseline data of the Chinese adolescent depression Cohort. The adolescents underwent cognitive assessments to yield domain-specific scores in EFs using the Digit Span Backward test(DSB), the Stroop Color-word interference test- color-word condition(Stroop-CW), and the Wisconsin Card Sorting tests(WCST). The significant differences in WCST scores were found between the NSSI group and the non-NSSI group. NSSI frequency was moderately positively correlated with total errors and negatively correlated with the number of categories completed. The number of categories completed in the "≥200″ NSSI frequency group was significantly lower than that in the "≤10″ NSSI group. The current findings suggested that depressed adolescents who had engaged in NSSI have poorer cognitive flexibility performance compared to adolescents without NSSI. As the frequency of NSSI increased, cognitive flexibility might become worse. These results provide evidence of a connection between executive dysfunctions and NSSI in depressed adolescents.

Frontal-occipital phase synchronization predicts occipital alpha power in perceptual decision-making.

Numerous studies of perceptual decision-making have shown that lower prestimulus alpha power leads to a higher hit rate in visual detection, which is believed to correlate with the top-down control. However, whether frontal-occipital phase synchronization underlying the top-down control could impact the occipital alpha power that directly affects the perceptual performance remains unclear. In this study, we used analyses of the general linear mixed model (GLMM) and event-related potentials (ERPs) to show that the prestimulus alpha power over the occipital area directly affected visual perception. Using both the univariate and multivariate methods, we found that low-frequency (4-30 Hz) frontal-occipital phase synchronization predicted the prestimulus alpha power over the occipital area. Overall, our results suggested that frontal-occipital phase synchronization could predict occipital alpha power that directly affects perceptual decision-making. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09862-7.

Association of shift work and dietary inflammatory potential with all-cause death among us hypertensive population: national health and nutrition examination study, 2005-2010.

BACKGROUND & AIMS: The individual effect of working schedule on survival in the hypertensive population has not been adequately studied. Shiftworkers are also prone to unhealthy lifestyles like pro-inflammatory diet. Therefore, we assessed the effect of shift work and its joint association with dietary inflammatory potential on mortality risk among the large US nationally representative sample of adult hypertensive population. METHODS: Data were from a nationally representative prospective cohort among US hypertensive population (n = 3680; weighted population, 54,192,988). The participants were linked to the 2019 public-access linked mortality archives. The working schedule were self-reported using the Occupation Questionnaire Section. Dietary inflammatory index (DII) scores were equally calculated using the 24-hour dietary recall (24 h) interviews. Multivariable Cox proportional hazards regression models were used to estimate hazard ratio and 95% confidence intervals (95%CI) for survival of hypertension individuals by work schedule and dietary inflammatory potential. The joint effect of work schedule and dietary inflammatory potential was then examined. RESULTS: Among the 3680 hypertension individuals (39.89% female [n = 1479] and 71.42% white [n = 1707]; weighted mean [SE] age, 47.35 [0.32] years), 592 individuals reported shift work status. 474 (10.76%) reported shift work status with pro-inflammatory dietary pattern (DII scores > 0). 118 (3.06%) reported shift work status with anti-inflammatory dietary pattern (DII scores < 0). 646 (19.64%) reported a non-shift working schedule with anti-inflammatory dietary pattern, while 2442 (66.54%) reported non-shift working schedule with pro-inflammatory dietary pattern. After a median follow-up of 11.67 years (140 months), 317 deaths (cardiovascular diseases (CVD), 65; cancer, 104) were registered. Cox regression analysis showed that shift work was associated with higher risk of all-cause mortality (hazard ratio [HR], 1.48; 95% CI, 1.07-2.06) compared with non-shift workers. In the joint analysis, shift work status combined with pro-inflammatory dietary pattern was associated with the highest all-cause mortality risk. Moreover, adopting the anti-inflammatory diet significantly attenuates the deleterious effect of shift work on mortality risk. CONCLUSIONS: In this large representative sample of adults with hypertension in the U.S., the combination of shift work status with pro-inflammatory dietary pattern was highly prevalent and was associated with the highest risks of death from all causes.

Transcriptome and physiological determination reveal the effects of selenite on the growth and selenium metabolism in mung bean sprouts.

Selenium (Se) biofortification of crops has been studied to substantially improve the Se content in human dietary food intake. In the present study, Vigna radiata (mung bean) seeds were soaked in different concentrations of sodium selenite (Na2SeO3). Low concentration of selenite is conducive to seed germination and growth, and can increase the fresh weight (FW) and dry weight (DW) of sprouts. The concentration of Na2SeO3 lower than 50 mg/kg resulted in noticeable elongation in the stem and marginal elongation in root. Mung bean seeds soaked with 80 mg/kg Na2SeO3 accounted for 93.77% of organic Se after growing for about 5 days. Transcriptome data revealed that Se treatment enhances starch and sugar metabolism, along with the up-regulation of ribosomal protein and DNA synthesis related genes. Further analysis indicated that the mung bean seeds absorbed Na2SeO3 through PHT1.1 and NIP2. Se (IV) was transformed into Se (VI) and transported to stems, leaves and roots through cotyledons during the germination of bean sprouts. SULTR3;3 may play an important role in the transit process. Se (VI) or Se (IV) transported to the leaves was catalytically transformed into SeCys through SiR and CS, and SeCys is further converted to MeSeCys through SMT. Most SeCys were transformed into SeHCys through CBL, transported to plastids, and finally transformed into SeMet through Met Synthase.

Morphological and Physiological Indicators and Transcriptome Analyses Reveal the Mechanism of Selenium Multilevel Mitigation of Cadmium Damage in Brassica juncea.

Cadmium (Cd) is a common agricultural soil pollutant, which does serious harm to the environment and the human body. In this study, Brassica juncea was treated with different concentrations of CdCl2 and Na2SeO3. Then, physiological indexes and transcriptome were measured to reveal the mechanisms by which Se reduces the inhibition and toxicity of Cd in B. juncea. The results showed that Se alleviated the inhibitive Cd effects on seedling biomass, root length, and chlorophyll, and promoted the adsorption of Cd by pectin and lignin in the root cell wall (CW). Se also alleviated the oxidative stress induced by Cd, and reduced the content of MDA in cells. As a result, SeCys and SeMet alleviated the transport of Cd to the shoots. Transcriptome data showed that the bivalent cation transporter MPP and ABCC subfamily participated in the separation of Cd in vacuoles, CAL1 was related to the chelation of Cd in the cytoplasm of cells, and ZIP transporter 4 reduced the transport of Cd to the shoots. These results indicated that Se alleviated the damage of Cd in plants and decreased its transport to the shoots by improving the antioxidant system, enhancing the ability of the CW to adsorb Cd, reducing the activity of Cd transporters, and chelating Cd.

A brain-wide genome-wide association study of candidate quantitative trait loci associated with structural and functional phenotypes of pain sensitivity.

Individual pain sensitivity is modulated by the brain's structural and functional features, but its heritability remains unclear. This paper conducted a brain-wide genome-wide association study (GWAS) to explore the genetic bases of neuroimage phenotypes of pain sensitivity. In total, 432 normal participants were divided into high and low pain sensitivity groups according to the laser quantitative test threshold. Then, the brain's gray matter density (GMD) features correlated with pain sensitivity were identified. Next, GWAS was performed on each GMD phenotype using quality-controlled genotypes. Based on the heatmap and hierarchical clustering results, the right insula was identified for further refined analysis in terms of subregions GMD and resting-state functional connectivity (rs-FC) phenotypes. The results indicate that the right insula GMD in the high sensitivity group is significantly lower than that in the low sensitivity group. Also, the TT/TC group at locus rs187974 has lower right insula GMD than the CC group. Further, loci at gene CYP2D6 may lead to a variation of rs-FC between the right insula and left putamen. In conclusion, our study suggests that the right insula and multiple candidate loci may be importantly involved in pain sensitivity modulation, which may guide the future development of precision pain therapeutics.

Gender-specific prevalence and trend of heart failure in China from 1990 to 2019.

AIMS: Heart failure (HF) is one of the leading causes of the global burden of disability and mortality. However, the comprehensive epidemic status of HF in China is unclear. Notably, the gender-specific survey for HF prevalence is lacking. The present study aimed to analyse the gender-specific prevalence and temporal trend of HF in China and explore the attributable aetiology and risk factors. METHODS AND RESULTS: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 was used to evaluate the age-standardized prevalence and years lived with disability of HF in China by gender. The temporal trend of HF and attributable risk factors were analysed by Joinpoint regression models from 1990 to 2019. The total age-standardized prevalence rate of HF steadily decreased over the past two decades from 1079.4 to 1032.8 per 100 000 individuals. Since 2017, the prevalence trend of HF has significantly increased [annual percentage change (APC) of 2.72 for females and 0.61 for males, P < 0.05]. In 2019, the age-standardized rate of HF prevalence in females surpassed that of males, and hypertensive heart disease was the leading cause of HF for females (42.65% of cases) and males (41.19% of cases). From 2017 to 2019, high systolic pressure contributed to most cases of HF-related hypertensive heart disease, with an APC of 2.68 for females and 0.48 for males (P < 0.05). CONCLUSIONS: Although HF prevalence has steadily decreased over the past two decades, an increasing trend has occurred since 2017, especially for females. The leading cause of HF was hypertensive heart disease. Metabolic risks, particularly high systolic pressure, consistently contribute to the prevalence of heart diseases leading to HF. Promoting HF screening and controlling metabolic risks at the population level are imperative. Gender differences in HF prevalence should be considered.