Developmental pleiotropy of SDP1 from seedling to mature stages in B. napus.

Rapeseed, an important oil crop, relies on robust seedling emergence for optimal yields. Seedling emergence in the field is vulnerable to various factors, among which inadequate self-supply of energy is crucial to limiting seedling growth in early stage. SUGAR-DEPENDENT1 (SDP1) initiates triacylglycerol (TAG) degradation, yet its detailed function has not been determined in B. napus. Here, we focused on the effects of plant growth during whole growth stages and energy mobilization during seedling establishment by mutation in BnSDP1. Protein sequence alignment and haplotypic analysis revealed the conservation of SDP1 among species, with a favorable haplotype enhancing oil content. Investigation of agronomic traits indicated bnsdp1 had a minor impact on vegetative growth and no obvious developmental defects when compared with wild type (WT) across growth stages. The seed oil content was improved by 2.0-2.37% in bnsdp1 lines, with slight reductions in silique length and seed number per silique. Furthermore, bnsdp1 resulted in lower seedling emergence, characterized by a shrunken hypocotyl and poor photosynthetic capacity in the early stages. Additionally, impaired seedling growth, especially in yellow seedlings, was not fully rescued in medium supplemented with exogenous sucrose. The limited lipid turnover in bnsdp1 was accompanied by induced amino acid degradation and PPDK-dependent gluconeogenesis pathway. Analysis of the metabolites in cotyledons revealed active amino acid metabolism and suppressed lipid degradation, consistent with the RNA-seq results. Finally, we proposed strategies for applying BnSDP1 in molecular breeding. Our study provides theoretical guidance for understanding trade-off between oil accumulation and seedling energy mobilization in B. napus.

In Operando Monitoring the Stress Evolution of Silicon Anode Electrodes during Battery Operation via Optical Fiber Sensors.

Silicon (Si) anode has attracted broad attention because of its high theoretical specific capacity and low working potential. However, the severe volumetric changes of Si particles during the lithiation process cause expansion and contraction of the electrodes, which induces a repeatedly repair of solid electrolyte interphase, resulting in an excessive consuming of electrolyte and rapid capacity decay. Clearly known the deformation and stress changing at µÎµ resolution in the Si-based electrode during battery operation provides invaluable information for the battery research and development. Here, an in operando approach is developed to monitor the stress evolution of Si anode electrodes via optical fiber Bragg grating (FBG) sensors. By implanting FBG sensor at specific locations in the pouch cells with different Si anodes, the stress evolution of Si electrodes has been systematically investigated, and Δσ/areal capacity is proposed for stress assessment. The results indicate that the differences in stress evolution are nested in the morphological changes of Si particles and the evolution characteristics of electrode structures. The proposed technique provides a brand-new view for understanding the electrochemical mechanics of Si electrodes during battery operation.

Joint and interactive effects of metal mixtures on liver damage: Epidemiological evidence from repeated-measures study.

BACKGROUND: The impact of heavy metals on liver function has been examined in numerous epidemiological studies. However, these findings lack consistency and longitudinal validation. METHODS: In this study, we conducted three follow-up surveys with 426 participants from Northeast China. Blood and urine samples were collected, along with questionnaire information. Urine samples were analyzed for concentrations of four metals (chromium [Cr], cadmium [Cd], lead [Pb], and manganese [Mn]), while blood samples were used to measure five liver function indicators (alanine aminotransferase [ALT], aspartate aminotransferase [AST], albumin [ALB], globulin [GLB], and total protein [TP]). We utilized a linear mixed-effects model (LME) to explore the association between individual heavy metal exposure and liver function. Joint effects of metal mixtures were investigated using quantile g-computation and Bayesian kernel machine regression (BKMR). Furthermore, we employed BKMR and Marginal Effect models to examine the interaction effects between metals on liver function. RESULTS: The LME results demonstrated a significant association between urinary heavy metals (Cr, Cd, Pb, and Mn) and liver function markers. BKMR results indicated positive associations between heavy metal mixtures and ALT, AST, and GLB, and negative associations with ALB and TP, which were consistent with the g-comp results. Synergistic effects were observed between Cd-Cr on ALT, Mn-Cr and Cr-Pb on ALB, while an antagonistic effect was found between Mn-Pb and Mn-Cd on ALB. Additionally, synergistic effects were observed between Mn-Cr on GLB and Cd-Cr on TP. Furthermore, a three-way antagonistic effect of Mn-Pb-Cr on ALB was identified. CONCLUSION: Exposure to heavy metals (Cr, Cd, Mn, Pb) is associated with liver function markers, potentially leading to liver damage. Moreover, there are joint and interaction effects among these metals, which warrant further investigation at both the population and mechanistic levels.

Complex interplay of heavy metals and renal injury: New perspectives from longitudinal epidemiological evidence.

BACKGROUND: Epidemiological studies have reported associations between heavy metals and renal function. However, longitudinal studies are required to further validate these associations and explore the interactive effects of heavy metals on renal function and their directional influence. METHOD: This study, conducted in Northeast China from 2016 to 2021, included a four-time repeated measures design involving 384 participants (1536 observations). Urinary concentrations of chromium (Cr), cadmium (Cd), manganese (Mn), and lead (Pb) were measured, along with renal biomarkers including urinary microalbumin (umAlb), urinary albumin-to-creatinine ratio (UACR), N-acetyl-ß-D-glucosaminidase (NAG), and ß2-microglobulin (ß2-MG) levels. Estimated glomerular filtration rate (eGFR) was calculated. A Linear Mixed Effects Model (LME) examined the association between individual metal exposure and renal biomarkers. Subsequently, Quantile g-computation and Bayesian Kernel Machine Regression (BKMR) models assessed the overall effects of heavy metal mixtures. Marginal Effect models examined the directional impact of metal interactions in the BKMR on renal function. RESULT: Results indicate significant impacts of individual and combined exposures of Cr, Cd, Pb, and Mn on renal biomarkers. Metal interactions in the BKMR model were observed, with synergistic effects of Cd-Cr on NAG, umAlb, UACR; Cd-Pb on NAG, UACR; Pb-Cr on umAlb, UACR, eGFR-MDRD, eGFR-EPI; and an antagonistic effect of Mn-Pb-Cr on UACR. CONCLUSION: Both individual and combined exposures to heavy metals are associated with renal biomarkers, with significant synergistic interactions leading to renal damage. Our findings elucidate potential interactions among these metals, offering valuable insights into the mechanisms linking multiple metal exposures to renal injury.

Neurotransmitter norepinephrine regulates chromatosomes aggregation and the formation of blotches in coral trout Plectropomus leopardus.

Color changes and pattern formations can represent strategies of the utmost importance for the survival of individuals or of species. Previous studies have associated capture with the formation of blotches (areas with light color) of coral trout, but the regulatory mechanisms link the two are lacking. Here, we report that capture induced blotches formation within 4-5 seconds. The blotches disappeared after anesthesia dispersed the pigment cells and reappeared after electrical stimulation. Subsequently, combining immunofluorescence, transmission electron microscopy and chemical sympathectomy, we found blotches formation results from activation of catecholaminergic neurons below the pigment layer. Finally, the in vitro incubation and intraperitoneal injection of norepinephrine (NE) induced aggregation of chromatosomes and lightening of body color, respectively, suggesting that NE, a neurotransmitter released by catecholaminergic nerves, mediates blotches formation. Our results demonstrate that acute stress response-induced neuronal activity can drive rapid changes in body color, which enriches our knowledge of physiological adaptations in coral reef fish.

Xanthophyll esterases in association with fibrillins control the stable storage of carotenoids in yellow flowers of rapeseed (Brassica juncea).

Biosynthesis, stabilization, and storage of carotenoids are vital processes in plants that collectively contribute to the vibrant colors observed in flowers and fruits. Despite its importance, the carotenoid storage pathway remains poorly understood and lacks thorough characterization. We identified two homologous genes, BjA02.PC1 and BjB04.PC2, belonging to the esterase/lipase/thioesterase (ELT) family of acyltransferases. We showed that BjPCs in association with fibrillin gene BjFBN1b control the stable storage of carotenoids in yellow flowers of Brassica juncea. Through genetic, high-resolution mass spectrometry and transmission electron microscopy analyses, we demonstrated that both BjA02.PC1 and BjB04.PC2 can promote the accumulation of esterified xanthophylls, facilitating the formation of carotenoid-enriched plastoglobules (PGs) and ultimately producing yellow pigments in flowers. The elimination of BjPCs led to the redirection of metabolic flux from xanthophyll ester biosynthesis to lipid biosynthesis, resulting in white flowers for B. juncea. Moreover, we genetically verified the function of two fibrillin genes, BjA01.FBN1b and BjB05.FBN1b, in mediating PG formation and demonstrated that xanthophyll esters must be deposited in PGs for stable storage. These findings identified a previously unknown carotenoid storage pathway that is regulated by BjPCs and BjFBN1b, while offering unique opportunities for improving the stability, deposition, and bioavailability of carotenoids.

Association of long-term air pollution exposure with the risk of prediabetes and diabetes: Systematic perspective from inflammatory mechanisms, glucose homeostasis pathway to preventive strategies.

BACKGROUND: Limited evidence suggests the association of air pollutants with a series of diabetic cascades including inflammatory pathways, glucose homeostasis disorder, and prediabetes and diabetes. Subclinical strategies for preventing such pollutants-induced effects remain unknown. METHODS: We conducted a cross-sectional study in two typically air-polluted Chinese cities in 2018-2020. One-year average PM1, PM2.5, PM10, SO2, NO2, and O3 were calculated according to participants' residence. GAM multinomial logistic regression was performed to investigate the association of air pollutants with diabetes status. GAM and quantile g-computation were respectively performed to investigate individual and joint effects of air pollutants on glucose homeostasis markers (glucose, insulin, HbA1c, HOMA-IR, HOMA-B and HOMA-S). Complement C3 and hsCRP were analyzed as potential mediators. The ABCS criteria and hemoglobin glycation index (HGI) were examined for their potential in preventive strategy. RESULTS: Long-term air pollutants exposure was associated with the risk of prediabetes [Prevalence ratio for O3 (PR_O3) = 1.96 (95% CI: 1.24, 3.03)] and diabetes [PR_PM1 = 1.18 (95% CI: 1.05, 1.32); PR_PM2.5 = 1.08 (95% CI: 1.00, 1.16); PR_O3 = 1.35 (95% CI: 1.03, 1.74)]. PM1, PM10, SO2 or O3 exposure was associated with glucose-homeostasis disorder. For example, O3 exposure was associated with increased levels of glucose [7.67% (95% CI: 1.75, 13.92)], insulin [19.98% (95% CI: 4.53, 37.72)], HOMA-IR [34.88% (95% CI: 13.81, 59.84)], and decreased levels of HOMA-S [-25.88% (95% CI: -37.46, -12.16)]. Complement C3 and hsCRP played mediating roles in these relationships with proportion mediated ranging from 6.95% to 60.64%. Participants with HGI ≤ -0.53 were protected from the adverse effects of air pollutants. CONCLUSION: Our study provides comprehensive insights into air pollutant-associated diabetic cascade and suggests subclinical preventive strategies.

Independent, combine and interactive effects of heavy metal exposure on dyslipidemia biomarkers: A cross-sectional study in northeastern China.

Dyslipidemia is a common disease in the older population and represents a considerable disease burden worldwide. Epidemiological and experimental studies have indicated associations between heavy metal exposure and dyslipidemia; few studies have investigated the effects of heavy metal mixture and interactions between metals on dyslipidemia. We recruited 1121 participants living in heavy metal-contaminated and control areas in northeast China from a cross-sectional survey (2017-2019). Urinary metals including chromium (Cr), cadmium (Cd), lead (Pb), and manganese (Mn) and dyslipidemia biomarkers, namely triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels, were measured. The generalized linear model (GLM) was used to explore the association of a single metal with dyslipidemia biomarkers. Bayesian kernel machine regression (BKMR) and multivariable linear regression were performed to explore the overall effect of metal mixture and the interaction between metals on dyslipidemia. Heavy metal mixture was positively associated with LDL-C, TC, and TG and negatively with HDL-C. In multivariable linear regression, Pb and Cd exhibited a synergistic association with LDL-C in the participants without hyperlipemia. Mn-Cd and Pb-Cr also showed a synergistic association with increasing the level of LDL-C in subjects without hyperlipemia. Cd-Cr showed an antagonistic association with HDL-C, respectively. Cr-Mn exhibited an antagonistic association with decreased HDL-C and TG levels. No significant interaction was noted among the three metals. Our study indicated that exposure to heavy metals is associated with dyslipidemia biomarkers and the presence of potential synergistic or antagonistic interactions between the heavy metals.

Threshold effect of urinary chromium on kidney function biomarkers: Evidence from a repeated-measures study.

Chronic kidney disease (CKD) is a public health concern worldwide, and chromium exposure may be a risk factor due to its potential nephrotoxicity. However, research on the association between chromium exposure and kidney function especially the potential threshold effect of chromium exposure is limited. A repeated-measures study involving 183 adults (641 observations) was conducted from 2017 to 2021 in Jinzhou, China. Urinary albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) were measured as kidney function biomarkers. Generalized mixed models and two-piecewise linear spline mixed models were used to assess the dose-response relationship and potential threshold effect of chromium on kidney function, respectively. Temporal analysis was conducted by the latent process mixed model to depict the longitudinal change of kidney function over age. Urinary chromium was associated with CKD (odds ratio [OR] = 1.29; 95 % confidence interval [CI], 6.41, 14.06) and UACR (Percent change = 10.16 %; 95 % CI, 6.41 %, 14.06 %), and we did not find significant association between urinary chromium and eGFR (Percent change = 0.06 %; 95 % CI, -0.80 %, 0.95 %). The threshold analyses suggested the existence of threshold effects of urinary chromium, with inflection points at 2.74 µg/L for UACR and 3.95 µg/L for eGFR. Furthermore, we found that chromium exposure exhibited stronger kidney damage over age. Our study provided evidence for the threshold effects of chromium exposure on kidney function biomarkers and the heightened nephrotoxicity of chromium in older adults. More attention should be paid to the supervision of chromium exposure concentrations for preventing kidney damage, especially in older adults.

Transport model simulation prediction and environmental risk assessment of pyrethroid insecticides in urban artificial lakes caused by rainfall: A case study of Cloud Mountain Park in subhumid climate zone.

Pyrethroid insecticides are among urban parks' most widely used and harmful insecticides. The advanced prediction method is the key to studying the pollution and diffusion risk of plant conservation insecticides in parks. A two-dimensional advection-dispersion model was established for the North Lake of Cloud Mountain Park in the subhumid area of Hebei Province. The temporal and spatial distribution of lambda-cyhalothrin pollution required by plant growth in artificial lakes under different rainfall intensities and the time of water renewal after rainfall was simulated and predicted. According to the model efficiency (E: 0.98), mean absolute error (MAE: 0.016-0.064 cm), and root mean square error (RMSE: 0.014-0.041 cm), the prediction results showed that the model fits well. The results showed that the concentration of lambda-cyhalothrin in the artificial lake was positively correlated with the increase in rainfall intensity. Under the three scenarios of moderate rain, heavy rain, and rainstorm, the variation of total pollutants into the lake over time conformed to the first-order dynamic equation (R2＞0.97), and the cumulative rates were 0.013 min-1, 0.019 min-1 and 0.022 min-1, respectively. Under light rain, the accumulation rate of lambda-cyhalothrin showed a double-linear relationship, which was in accordance with the second-order kinetic equation (R2＞0.97). The rapid accumulation rate of early-stage rainfall was 0.0024 min-1, and the slow accumulation rate of late-stage rainfall was 0.0019 min-1. The human health risk assessment predicted by the simulation was lower than the hazard value (Rtgn(a-1): 9.65 E-11-1.12 E-10 a-1). However, the potential risk value to aquatic species was higher (RQ: 0.33-23.05). In addition, the increase in rainfall intensity has no significant effect on the acceleration of water renewal time. The two-dimensional dispersion model of pollutants driven by water dynamics provided relevant examples for evaluating the impact of runoff on pesticide scour in parks and supplied scientific support for improving the management of artificial lakes in urban parks.

CausalMGM: an interactive web-based causal discovery tool.

High-throughput sequencing and the availability of large online data repositories (e.g. The Cancer Genome Atlas and Trans-Omics for Precision Medicine) have the potential to revolutionize systems biology by enabling researchers to study interactions between data from different modalities (i.e. genetic, genomic, clinical, behavioral, etc.). Currently, data mining and statistical approaches are confined to identifying correlates in these datasets, but researchers are often interested in identifying cause-and-effect relationships. Causal discovery methods were developed to infer such cause-and-effect relationships from observational data. Though these algorithms have had demonstrated successes in several biomedical applications, they are difficult to use for non-experts. So, there is a need for web-based tools to make causal discovery methods accessible. Here, we present CausalMGM (http://causalmgm.org/), the first web-based causal discovery tool that enables researchers to find cause-and-effect relationships from observational data. Web-based CausalMGM consists of three data analysis tools: (i) feature selection and clustering; (ii) automated identification of cause-and-effect relationships via a graphical model; and (iii) interactive visualization of the learned causal (directed) graph. We demonstrate how CausalMGM enables an end-to-end exploratory analysis of biomedical datasets, giving researchers a clearer picture of its capabilities.

Association between urine metals and liver function biomarkers in Northeast China: A cross-sectional study.

BACKGROUND: After heavy metals enter the body, they affect a variety of organs, particularly the main metabolic organ, the liver. Moreover, people are more likely to be exposed to multiple metals than to a single metal. We explored the associations between exposure to a heavy metal mixture and liver function biomarkers. METHODS: This study involved 1171 residents living in areas with or without heavy metal exposure in northeast China. Urine concentrations of chromium (Cr), cadmium (Cd), lead (Pb), and manganese (Mn) were measured. Total protein (TP), albumin (ALB), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were used as biomarkers of liver function. A generalized linear model (GLM), quantile g-computation, and Bayesian kernel machine regression (BKMR) were used to explore the associations between the four metals and liver function. RESULTS: GLM analysis revealed that Cr level was negatively associated with TP (ß = - 0.57; 95% CI: - 0.89, - 0.26) and ALB (ß = - 0.27; 95% CI: - 0.47, - 0.07) levels, and Cd level was positively associated with AST (ß = 1.04; 95% CI: 0.43, 1.65) and ALT (ß = 0.94; 95% CI: 0.08, 1.79) levels. ALB (ß = 0.26; 95% CI: 0.10, 0.41) and ALT (ß = 0.52; 95% CI: 0.02, 1.02) levels were positively associated with urine Mn concentration. The quantile g-computation indicated that exposure to a mixture of the four metals was significantly associated with TP (ß = - 0.56; 95% CI: - 0.94, - 0.18) and ALT (ß = 0.84; 95% CI: 0.04, 1.63) levels. Among the metals, Cr had the strongest effect on TP and Cd had that on AST. The BKMR model indicated that mixed metal exposure was negatively associated with TP and ALB levels and positively associated with ALT and AST levels. CONCLUSION: Exposure to mixtures of heavy metals may influence liver function. Cr and Cd may be the largest contributors.

Negatively interactive effect of chromium and cadmium on obesity: Evidence from adults living near ferrochromium factory.

BACKGROUND: Researchers have reported that chromium (Cr) exposure may be associated with metabolism of glucose and lipids in residents living in a long-term Cr polluted area. Previous statistical analysis is mainly focused on individual chromium exposure. Furtherly, we aim to investigated the independent, combined, and interaction effects of the co-exposure of urine Cr (UCr) with cadmium (UCd), lead (UPb) and manganese (UMn) on body mass index (BMI), waist circumference, and the risk of overweight and abdominal obesity. METHOD: We enrolled 1187 participants from annual surveys between 2017 and 2019. Heavy metal concentrations in urine were standardized using covariate-adjusted urine creatinine levels. Multiple linear/logistic regression models were applied to measure the single effect of urine heavy metal concentration on the outcomes. The quantile-based g-computation (g-comp) model was used to evaluate the combined effect of metal mixture on the outcomes and to compare the contribution of each metal. Both additive and multiplicative interactions were measured for UCr with UCd, UPb, UMn on the outcomes. Analysis was performed on the overall population and stratified by smoking habit. RESULTS: For the overall study population, UCr was positively associated with BMI (p trend = 0.023) and waist circumference (p trend = 0.018). For smoking participants, the g-comp model demonstrated that the metal mixture was negatively associated with BMI, with UCr and UCd contributing the most in the positive and negative direction. A negative additive interaction was observed between UCr and UCd on BMI and abdominal obesity. We did not observe a significant interaction effect of UCr with UPb or UMn. CONCLUSION: Our study indicated that Cr and Cd exposure may be associated with BMI and waist circumference, with combined and interaction effects of the heavy metals noted. Further epidemiological and experimental researches could simultaneously consider single and complex mixed exposure to verify the findings and biological mechanisms.

Prediction of the impact of benzo[a]pyrene on shallow groundwater during natural infiltration of reclaimed water-receiving rivers: A case study of Liangshui, China.

The quality of groundwater along rivers is greatly affected by long-term infiltration from surface water, especially reclaimed water-receiving rivers. To predict the degree of influence of contaminated river water on groundwater quality, the spatiotemporal distribution and migration evolution prediction of benzo[a]pyrene (B(a)P) was monitored and simulated by Hydrus-coupled Groundwater Modeling Systems (GMS) model in terms of reclaimed water-receiving Liangshui River. The prediction results indicated the goodness-of-fit of this coupled model, according to the model efficiency (E: 0.78-0.93), the mean absolute error (MAE: 0.01-0.32 m) and the root-mean-square error (RMSE: 0.06-0.35 m). The vertical infiltration rate of B(a)P in the vadose zone was 0.102 m-1, which was only 0.73% that of water. B(a)P penetrated the 16 m depth vadose zone for 63 years owing to the attenuation function of adsorption and biodegradation, with contribution ratios of 78.4% and 19.3%, respectively. However, once B(a)P intersects with groundwater, the migration of B(a)P is dominated by horizontal migration due to downward movement along the groundwater flow direction. The migration rate of B(a)P in groundwater was 6.65 m/y in the horizontal direction, which was 2.42 and 16.22 times higher than the dispersion rate in the longitudinal and vertical directions, respectively. The spatiotemporal distribution indicated that the B(a)P concentration decreased with the crow-fly distance from river with attenuation rate constants of 1.19 × 10-4, 3.05 × 10-4, and 3.67 × 10-3 m-1 over horizontal, longitudinal, and vertical direction, respectively, which were negatively correlated with migration rate. However, the B(a)P content increased over the extension of infiltration time with an accumulation rate of 7.3 × 10-2 d-1. The migration and accumulation of B(a)P induced potential health risks to groundwater-based drinking water safety, which resulted in the groundwater safety utilization range decreasing from 450 m, 283 m, and 20.1 m-583 m, 338 m, and 28.2 m far from the river over the horizontal, longitudinal, and vertical directions, respectively, 20 years later. This study provides a numerical modeling solution for the viable spatiotemporal evolution of B(a)P in groundwater and an effective decision-making tool for the safe utilization of groundwater as drinking water.

Social media reduce users' moral sensitivity: Online shaming as a possible consequence.

In this study, we propose that social media reduce users' moral sensitivity through the mediation of the perceived moral intensity of hostile comments, which leads to behavioral consequences for online shaming. Three separate studies were conducted to explore this statement. Study 1 (N = 160) compared moral sensitivity between participants in simulated social media situations and a control group. Study 2 (N = 412) tested the mediating role of perceived moral intensity through self-rated questionnaires. Study 3 (N = 295) examined the behavioral consequences of reduced moral sensitivity on online shaming by manipulating social media and perceived moral intensity. Across these three studies with their different methodologies, we found consistent support for our prediction that social media reduce users' moral sensitivity. Also, our findings shed light on perceived moral intensity as a mediator. As expected, less perceived moral intensity and less moral sensitivity (as serial mediators) induced by social media led to a higher tendency to participate in online shaming. In addition, our research suggests that the harmful effects of social media could be restricted by improving users' perceived moral intensity in the form of reminders. These findings provide novel insights into the underlying mechanism of cyberviolence on social media and also contribute to the literature on the antecedents and consequences of moral sensitivity.

Nonvisual system-mediated body color change in fish reveals nonvisual function of Opsin 3 in skin.

Body-color changes in many poikilothermic animals can occur quickly. This color change is generally initiated by visual system, followed by neuromuscular or neuroendocrine control. We have previously showed that the ventral skin color of the large yellow croaker (Larimichthys crocea) presents golden yellow in dark environment and quickly changes to silvery white in light environment. In the present study, we found that the light-induced whitening of ventral skin color was independent of visual input. Using light-emitting diode sources of different wavelength with same luminance (150 lx) but different absolute irradiance (0.039-0.333 mW/cm2), we further found that the blue light (λmax = 480 nm, 0.107 mW/cm2) is more effectively in induction of whitening of ventral skin color in compare with other light sources. Interestingly, the result of RT-PCR showed opsin 3 transcripts expressed in xanthophores. Recombinant protein of Opsin 3 with 11-cis retinal formed functional blue-sensitive pigment, with an absorption maximum at 468 nm. The HEK293T cells transfected with Opsin 3 showed a blue light-evoked Ca2+ response. Knock-down of Opsin 3 expression blocked the light-induced xanthosomes aggregation in vitro. Moreover, the light-induced xanthosomes aggregation was mediated via Ca2+-PKC and Ca2+-CaMKII pathways, and relied on microtubules and dynein. Decrease of cAMP levels was a prerequisite for xanthosomes aggregation. Our results provide a unique organism model exhibiting light-induced quick body color change, which was independent of visual input but rather rely on non-visual function of Opsin 3 within xanthophore.

The effects of mobile phone addiction on bedtime procrastination in university students: the masking effect of physical activity and anxiety.

PURPOSE: Good sleep is one of the necessary conditions to ensure the normal performance of the physiological and psychological functions of college students. This study aimed to explore the relationship between mobile phone addiction and bedtime procrastination among Chinese college students and the mediating mechanisms of physical exercise and anxiety between the two, with a view to seek ways to prevent and intervene in college students' sleep procrastination and improve their sleep quality. METHODS: Using SPSS 29.0 analysis with Bootstrap's method, 3,800 first-year students, sophomores, and juniors were given the Mobile Phone Addiction Tendency Scale, Bedtime Procrastination Scale, Physical Activity Scale, and Anxiety Scale. The results of the analyses included mediation tests and effect analyses of anxiety and physical activity. RESULTS: The correlation analysis revealed significant positive correlations between mobile phone addiction and bedtime procrastination (r = 0.149, p < 0.01) as well as anxiety (r = 0.497, p < 0.01). Additionally, there was a significant negative correlation between mobile phone addiction and physical activity (r = -0.447, p < 0.01). Physical activity was also found to have significant negative correlations with anxiety (r = -0.506, p < 0.01) and bedtime procrastination (r = -0.424, p < 0.01). Furthermore, anxiety showed a significant positive correlation with bedtime procrastination (r = 0.334, p < 0.01). Physical activity and anxiety acted as substantial mediators between mobile phone addiction and nighttime procrastination. Both mediators had considerable masking effects, with the mediating effect amounting to 50.3% and 25.1%, respectively. Physical exercise and anxiety played a chain mediating role between mobile phone addiction and bedtime procrastination, and the masking effect was also significant, with a mediating effect size of 13.4%. CONCLUSIONS: This study reveals the special characteristics of the influencing factors and pathways of bedtime procrastination in this group of college students, providing targeted evidence for the prevention and intervention of bedtime procrastination in college students. It also has an important reference value for the effects of exercise and comprehensive intervention to improve bedtime procrastination and enhance the quality of sleep in college students.

The Effects of Short-Term Exposure to pH Reduction on the Behavioral and Physiological Parameters of Juvenile Black Rockfish (Sebastes schlegelii).

Coastal areas are subject to greater pH fluctuation and more rapid pH decline as a result of both natural and anthropogenic influences in contrast to open ocean environments. Such variations in pH have the potential to pose a threat to the survival and physiological function of offshore fishes. With the aim of evaluating the impact of short-term pH reduction on the behavioral performance and physiological response of costal fish, the black rockfish (Sebastes schlegelii), one of the principal stock-enhanced species, was examined. In the present study, juveniles of the black rockfish with a mean body length of 6.9 ± 0.3 cm and weight of 8.5 ± 0.5 g were exposed to a series of pHs, 7.0, 7.2, 7.4, 7.6, 7.8, and normal seawater (pH 8.0) for 96 h. At the predetermined time points post-exposure (i.e., 0, 12, 24, 48, and 96 h), fish movement behavior was recorded and the specimens were sampled to assess their physiological responses. The results indicate that the lowered pH environment (pH 7.0-7.8) elicited a significant increase in highly mobile behavior, a decrease in immobile behavior, and a significant rise in the metabolic levels of the black rockfish juveniles. Specifically, carbohydrate metabolism was significantly elevated in the pH 7.2 and 7.4 treatments, while lipid metabolism was significantly increased in the pH 7.0, 7.4, and 7.8 treatments. The results of the present study indicate that short-term reductions in pH could ramp up boldness and boost energy expenditure in the black rockfish juveniles, leading to an increased metabolic cost. Additionally, the present investigation revealed that the black rockfish juveniles were capable of adapting to a short-term pH reduction. The findings may provide insight into the underlying physiological mechanisms that govern fish responses to potential decreases in seawater pH in the future.

Thyroid disrupting effects of multiple metals exposure: Comprehensive investigation from the thyroid parenchyma to hormonal function in a prospective cohort study.

This study aimed to investigate the thyroid disrupting effects of multiple metals exposure with comprehensive investigation from the thyroid parenchyma to hormonal function. In this prospective cohort study of in-service staff of the Baoding Power Supply, we found that arsenic was negatively associated with total thyroxine (TT4) [ßAs = -0.075, 95% confidence interval (CI): -0.129, -0.020, Padj = 0.04]. Similarly, selenium was negatively correlated with TT4 (ßSe = -0.134, 95% CI: -0.211, -0.058, Padj < 0.01) and peripheral deiodinase activity (GT) (ßSe = -0.133, 95% CI: -0.210, -0.056, Padj = 0.01). With respect to strontium, there were positive associations of strontium with thyroid-stimulating hormone (ßSr = 0.263, 95% CI: 0.112, 0.414, Padj = 0.01), and negative associations of strontium with TT4 (ßSr = -0.099, 95% CI: -0.150, -0.048, Padj < 0.01) and GT (ßSr = -0.102, 95% CI: -0.153, -0.050, Padj < 0.01). We also observed negative associations of metal mixtures with TT4 and GT and potential interactions. Increased risks of thyroid nodule associated with aluminum, cobalt and nickel were also observed. Our findings suggest that multiple metals exposure leads to a multi-pronged assault to thyroid from the thyroid parenchyma to hormonal function. Future large-scale prospective cohort studies of general population and experimental studies were warranted.

Associations of metals and metals mixture with lipid profiles: A repeated-measures study of older adults in Beijing.

Metals inevitably and easily enter into human bodies and can induce a series of pathophysiological changes, such as oxidative stress damage and lipid peroxidation, which then may further induce dyslipidemia. However, the effects of metals and metals mixture on the lipid profiles are still unclear, especially in older adults. A three-visits repeated measurement of 201 older adults in Beijing was conducted from November 2016 to January 2018. Linear Mixed Effects models and Bayesian kernel machine regression models were used to estimate associations of eight blood metals and metals mixture with lipid profiles, including total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), Castelli risk indexes I (CRI-1), Castelli risk indexes II (CRI-2), atherogenic coefficient (AC), and non-HDL cholesterol (NHC). Cesium (Cs) was positively associated with TG (ßCs = 0.14; 95% CI: 0.02, 0.26) whereas copper (Cu) was inversely related to TG (ßCu = -0.65; 95%CI: -1.14, -0.17) in adjusted models. Manganese (Mn) was mainly related to higher HDL-C (ßMn = 0.14; 95% CI: 0.07, 0.21) whereas molybdenum showed opposite association. Metals mixture was marginally positive associated with HDL-C, among which Mn played a crucial role. Our findings suggest that the effects of single metal on lipid profiles may be counteracted in mixtures in the context of multiple metal exposures; however, future studies with large sample size are still needed to focus on the detrimental effects of single metals on lipid profiles as well as to identify key components.