N-Acetyltransferase 10 represses Uqcr11 and Uqcrb independently of ac4C modification to promote heart regeneration.

Translational control is crucial for protein production in various biological contexts. Here, we use Ribo-seq and RNA-seq to show that genes related to oxidative phosphorylation are translationally downregulated during heart regeneration. We find that Nat10 regulates the expression of Uqcr11 and Uqcrb mRNAs in mouse and human cardiomyocytes. In mice, overexpression of Nat10 in cardiomyocytes promotes cardiac regeneration and improves cardiac function after injury. Conversely, treating neonatal mice with Remodelin-a Nat10 pharmacological inhibitor-or genetically removing Nat10 from their cardiomyocytes both inhibit heart regeneration. Mechanistically, Nat10 suppresses the expression of Uqcr11 and Uqcrb independently of its ac4C enzyme activity. This suppression weakens mitochondrial respiration and enhances the glycolytic capacity of the cardiomyocytes, leading to metabolic reprogramming. We also observe that the expression of Nat10 is downregulated in the cardiomyocytes of P7 male pig hearts compared to P1 controls. The levels of Nat10 are also lower in female human failing hearts than non-failing hearts. We further identify the specific binding regions of Nat10, and validate the pro-proliferative effects of Nat10 in cardiomyocytes derived from human embryonic stem cells. Our findings indicate that Nat10 is an epigenetic regulator during heart regeneration and could potentially become a clinical target.

DNA barcoding, identification, and validation of the pufferfish (Order: Tetraodontiformes) in China coastal waters.

The order Tetraodontiformes are one of the most unique groups of teleostean fish, exhibiting highly derived and greatly diversified phenotypes. It is a difficult task for both professionals and nonprofessionals to accurately identify these species only according to morphological characteristics. DNA barcoding can identify species at the molecular level to overcome the limitations of morphological classification. In this study, we collected 616 specimens of pufferfish from the coastal waters of China. According to the morphological characteristics, they were preliminarily identified as 50 species. Further analysis using DNA barcodes identified these specimens as 46 species, belonging to 23 genera, 6 families. According to the species classification results of DNA barcoding, the three species identified by morphology as Takifugu pseudommus, Takifugu chinensis, and Takifugu rubripes should be the same species. Similarly, Lagocephalus wheeleri is the synonym of Lagocephalus spadiceus. Another important discovery of DNA barcoding analysis is that there are closer interspecific genetic distances within the genus Takifugu. If T. rubripes, T. pseudommus, and T. chinensis are taken as one species, the average interspecific to intraspecific genetic distance ratio of Takifugu is only 6.21 times, which does not reach the DNA barcoding threshold of more than 10 times proposed previously. Although the interspecific genetic distance in the genus Takifugu is relatively small, each species can be clustered into independent clades in the NJ tree. In conclusion, this study not only found that there are synonymous phenomena in the order Tetraodontiformes but also provided molecular evidence for the valid species names of Takifugu rubripes and Lagocephalus Spadiceus. The results can provide reliable DNA barcoding information for the identification of pufferfish species, help solve the problem of classification confusion in this order, and provide technical support for the identification of the original components of related commodities on the aquatic product market.

Effects of PM2.5 and high-fat diet interaction on blood glucose metabolism in adolescent male Wistar rats: A serum metabolomics analysis based on ultra-high performance liquid chromatography/mass spectrometry.

Fine particulate matter (PM2.5) and high-fat diet (HFD) are known to contribute to blood glucose metabolic disorders. However, limited research has investigated the combined impact of PM2.5 and HFD on blood glucose metabolism. This study aimed to explore the joint effects of PM2.5 and HFD on blood glucose metabolism in rats using serum metabolomics and to identify involved metabolites and metabolic pathways. The 32 male Wistar rats were exposed to filtered air (FA) or PM2.5 (real-world inhaled, concentrated PM2.5, 8 times the ambient level, ranging from 131.42 to 773.44 µg/m3) and fed normal diet (ND) or HFD for 8 weeks. The rats were divided into four groups (n = 8/group): ND-FA, ND-PM2.5, HFD-FA and HFD-PM2.5 groups. Blood samples were collected to determine fasting glucose (FBG), plasma insulin and glucose tolerance test and HOMA Insulin Resistance (HOMA-IR) index was calculated. Finally, the serum metabolism of rats was analyzed by ultra-high performance liquid chromatography/mass spectrometry (UHPLC-MS). Then we constructed the partial least squares discriminant analysis (PLS-DA) model to screen the differential metabolites, and performed pathway analysis to screen the main metabolic pathways. Results showed that combined effect of PM2.5 and HFD caused changes in glucose tolerance, increased FBG levels and HOMA-IR in rats and there were interactions between PM2.5 and HFD in FBG and insulin. By metabonomic analysis, the serum differential metabolites pregnenolone and progesterone, which involved in steroid hormone biosynthesis, were two different metabolites in the ND groups. In the HFD groups, the serum differential metabolites were L-tyrosine and phosphorylcholine, which involved in glycerophospholipid metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. When PM2.5 and HFD coexist, they may lead to more severe and complex effects on glucose metabolism by affecting lipid metabolism and amino acid metabolism. Therefore, reducing PM2.5 exposure and controlling dietary structure are important measures for preventing and reducing glucose metabolism disorders.

The relationship between ratings of perceived exertion (RPE) and relative strength for a fatiguing dynamic upper extremity task: A consideration of multiple cycles and conditions.

The goal of this study was to evaluate the relationship between ratings of perceived exertion (RPE) and relative strength with respect to baseline for a fatiguing free dynamic task targeting the upper extremity, namely simulated order picking, and determine whether the relationship remains the same for different conditions (i.e., pace and weight) and with fatigue. Fourteen participants (seven males, seven females) performed four sessions that included two 45-min work periods separated by 15 min of rest. The work periods involved picking weighted bottles from shoulder height and packaging them at waist height for four combinations of bottle mass and picking rate: 2.5 kg-15 bottles per minute (bpm), 2.5 kg-10 bpm, 2.5 kg-5 bpm, and 1.5 kg-15 bpm. Participants reported their RPEs every 5 min and performed a maximum isometric shoulder flexion exertion every 9 min. Pearson product-moment correlation was used to evaluate the linear relationship between RPE and relative strength for each subject and work period. Then, the effects of condition and work period on the average relationship were assessed using a repeated-measures analysis of variance (ANOVA). For the first 45-min period, there were no significantly different correlations between RPE and relative strength across conditions (average r = -0.62 (standard deviation = 0.38); p = 0.57). There was a significant decrease in average correlation for the second work period (r = -0.39 (0.53)). These results suggest that individual subjective responses consistently increase while relative strength declines when starting from a non-fatigued state. However, correlations are weaker when re-engaging in work following incomplete recovery. Thus, starting fatigue levels should be accounted for when considering the expected relationship between RPE and relative strength.

The effect of episodic foresight on intertemporal decision-making: the role of future self-continuity and perceived control.

To investigate the mechanism of episodic foresight of different valences on intertemporal decision-making, this study examined the mediating role of future self-continuity in the influence of episodic foresight on intertemporal decision-making and the moderating role of perceived control in two experiments. The results found that (1) future self-continuity mediated the effect of episodic foresight on individuals' intertemporal decision-making; and (2) perceived control moderated the indirect effect of episodic foresight on intertemporal decision-making through future self-continuity. Under low perceived control, individuals with positive episodic foresight had stronger future self-continuity and preferred future options, while individuals with negative episodic foresight had lower future self-continuity. In contrast, under high perceived control, individuals with different episodic foresight potencies did not show significant differences in their future self-continuity levels, but all showed higher levels and tended to choose the delayed option when faced with an intertemporal choice. From the perspective of the self-cognition, this study provided new insights into the relationship between episodic foresight and intertemporal decision-making and the psychological mechanisms of intertemporal decision-making.

Functional ANOVA for Upper Extremity Fatigue Analysis during Dynamic Order Picking.

OCCUPATIONAL APPLICATIONSMusculoskeletal disorders are prevalent among warehouse workers who engage in repetitive and dynamic tasks. To prevent such injuries, it is vital to identify the factors that influence fatigue in the upper extremities during these repetitive activities. Our study reveals that task factors, namely the bottle mass and picking rate, significantly influence upper extremity fatigue. In most cases, the fatigue indicator is a functional variable, meaning that the fatigue score or measurement is a curve captured over time, which could be modeled as a function. In this study, we demonstrate that functional data analysis tools, such as functional analysis of variance (FANOVA), prove more effective than traditional methods in specifying how task factors contribute to the development of fatigue in the upper extremities. Furthermore, since there are inherent differences among workers that could affect their fatigue development process, the data heterogeneity could be tackled by employing clustering methods.

Background: Preventing musculoskeletal disorders is a paramount safety concern for industries, with order pickers in warehouses being particularly vulnerable due to their repetitive and dynamic tasks. Understanding the factors contributing to upper-extremity fatigue in such settings is crucial. Purpose: This paper investigates the impact of task-related factors on two upper-extremity fatigue indicators: ratings of perceived fatigue and relative muscle strength. Several statistical approaches were used and compared in terms of their capability in eliciting these effects. Methods: Simulated over-shoulder, order-picking lab experiments were conducted under different combinations of two bottle loads and three picking paces. Fourteen participants, evenly distributed between genders, completed the experiment. A FANOVA was executed as the principal analytical approach, considering the functional nature of the two fatigue indicators measured over the work period. To underscore the benefits of considering the whole functional curve instead of discrete variables, we also conducted repeated-measures and two-way ANOVA as benchmark analyses. Results: FANOVA outcomes affirmed that both task factors (load and pace) significantly influenced both fatigue indicators. The FANOVA method identified larger effect sizes (0.11< ηp2 < 0.19) for both task factors compared to the conventional methods (0< ηp2 < 0.11), supporting the efficacy of FANOVA in identifying the importance of these factors. Conclusions: The FANOVA approach proved effective in detecting the impact of task factors on fatigue indicators, yielding superior results compared to conventional benchmark methods. To address participant heterogeneity, functional clustering and gender-based clustering were introduced into the FANOVA framework, both effectively mitigating this challenge. Notably, FANOVA with functional clusters had superior performance compared to the one with gender clustering, suggesting functional clustering as a more suitable method in overcoming participant heterogeneity.

Classifying tasks performed by electrical line workers using a wrist-worn sensor: A data analytic approach.

Electrical line workers (ELWs) experience harsh environments, characterized by long shifts, remote operations, and potentially risky tasks. Wearables present an opportunity for unobtrusive monitoring of productivity and safety. A prerequisite to monitoring is the automated identification of the tasks being performed. Human activity recognition has been widely used for classification for activities of daily living. However, the literature is limited for electrical line maintenance/repair tasks due to task variety and complexity. We investigated how features can be engineered from a single wrist-worn accelerometer for the purpose of classifying ELW tasks. Specifically, three classifiers were investigated across three feature sets (time, frequency, and time-frequency) and two window lengths (4 and 10 seconds) to identify ten common ELW tasks. Based on data from 37 participants in a lab environment, two application scenarios were evaluated: (a) intra-subject, where individualized models were trained and deployed for each worker; and (b) inter-subject, where data was pooled to train a general model that can be deployed for new workers. Accuracies ≥ 93% were achieved for both scenarios, and increased to ≥96% with 10-second windows. Overall and class-specific feature importance were computed, and the impact of those features on the obtained predictions were explained. This work will contribute to the future risk mitigation of ELWs using wearables.

Oxidant stress-sensitive circRNA Mdc1 controls cardiomyocyte chromosome stability and cell cycle re-entry during heart regeneration.

Targeting cardiomyocyte plasticity has emerged as a new strategy for promoting heart repair after myocardial infarction. However, the precise mechanistic network underlying heart regeneration is not completely understood. As noncoding RNAs, circular RNAs (circRNAs) play essential roles in regulating cardiac physiology and pathology. The present study aimed to investigate the potential roles of circMdc1 in cardiac repair after injury and elucidate its underlying mechanisms. Here, we identified that circMdc1 levels were upregulated in postnatal mouse hearts but downregulated in the regenerative myocardium. The expression of circMdc1 in cardiomyocytes is sensitive to oxidative stress, which was attenuated by N-acetyl-cysteine. Enforced circMdc1 expression inhibited cardiomyocyte proliferation, while circMdc1 silencing led to cardiomyocyte cell cycle re-entry. In vivo, the cardiac-specific adeno-associated virus-mediated knockdown of circMdc1 promoted cardiac regeneration and heart repair accompanied by improved heart function. Conversely, circMdc1 overexpression blunted the regenerative capacity of neonatal hearts after apex resection. Moreover, circMdc1 was able to block the translation of its host gene Mdc1 specifically by binding to PABP, affecting DNA damage and the chromosome stability of cardiomyocytes. Furthermore, overexpression of Mdc1 caused damaged mouse hearts to regenerate and repair after myocardial infarction in vivo. Oxidative stress-sensitive circMdc1 plays an important role in cardiac regeneration and heart repair after injury by regulating DNA damage and chromosome stability in cardiomyocytes by blocking the translation of the host gene Mdc1.

A Review on the Modification of Cellulose and Its Applications.

The latest advancements in cellulose and its derivatives are the subject of this study. We summarize the characteristics, modifications, applications, and properties of cellulose. Here, we discuss new breakthroughs in modified cellulose that allow for enhanced control. In addition to standard approaches, improvements in different techniques employed for cellulose and its derivatives are the subject of this review. The various strategies for synthetic polymers are also discussed. The recent advancements in polymer production allow for more precise control, and make it possible to make functional celluloses with better physical qualities. For sustainability and environmental preservation, the development of cellulose green processing is the most abundant renewable substance in nature. The discovery of cellulose disintegration opens up new possibilities for sustainable techniques. Based on the review of recent scientific literature, we believe that additional chemical units of cellulose solubility should be used. This evaluation will evaluate the sustainability of biomass and processing the greenness for the long term. It appears not only crucial to dissolution, but also to the greenness of any process.

Photobiomodulation Drives MiR-136-5p Expression to Promote Injury Repair after Myocardial Infarction.

Photobiomodulation (PBM) has emerged as an alternative therapy involved in modulating a variety of biological effects. In this study, we verified whether PBM can affect cardiac physiological activity in mice through noninvasive irradiation using light-emitting diodes at a wavelength of 630 nm (LED-Red). We found that the PBM involved in regulating the repair of injured myocardium is wavelength-limited. LED-Red caused cardiomyocytes (CMs) that had exited the cell cycle to divide and proliferate again, and the cell proliferation ratio increased significantly with the accumulation of intracellular photopower. In addition, LED-Red promoted myocardial revascularization and myocardial regeneration, reduced the area of fibrosis in mice with myocardial infarction (MI), and thus improved cardiac contractile function. In regard to the mechanism, miRNA sequencing analysis showed that low-power LED-Red irradiation could induce differential changes in miRNAs in CMs. Among them, miR-136-5p was identified as a cardiac photo-sensitive miRNA and was obviously inhibited after stimulation, which produced a proliferation-promoting effect on CMs. Subsequent luciferase reporter assays confirmed the involvement of Ino80 as a binding target of miR-136-5p in the regulatory process of CM proliferation. Similarly, LED-Red irradiation elevated intracellular Ino80 expression. After knockdown of Ino80, the proliferation-promoting effect of LED-Red on CMs was inhibited. Collectively, this study demonstrates that LED-Red can promote CM proliferation by inhibiting cardiac photo-sensitive miRNA- miR-136-5p expression through targeting Ino80. The findings provided a new potential strategy for the treatment of ischemic cardiomyopathy (ICD).

A data analytic end-to-end framework for the automated quantification of ergonomic risk factors across multiple tasks using a single wearable sensor.

Existing ergonomic risk assessment tools require monitoring of multiple risk factors. To eliminate the direct observation, we investigated the effectiveness of an end-to-end framework that works with the data from a single wearable sensor. The framework is used to identify the performed task as the major contextual risk factor, and then estimate the task duration and number of repetitions as two main indicators of task intensity. For evaluation of the framework, we recruited 37 participants to complete 10 simulated work tasks in a laboratory setting. In testing, we achieved an average accuracy of 92% for task identification, 7.3% error in estimation of task duration, and 7.1% error for counting the number of task repetitions. Moreover, we showed the utility of the framework outputs in two ergonomic tools to estimate the risk of injury. Overall, we indicated the feasibility of using data from wearable sensors to automate the ergonomic risk assessment in workplaces.

Analyzing Risk of Service Failures in Heavy Haul Rail Lines: A Hybrid Approach for Imbalanced Data.

An incident in which a rail defect of size over a threshold value is noticed and the track is taken out of service is known as a service failure. This article aims at building accurate prediction models with binary outcome for risk of service failures on heavy haul rail segments. An analysis of the factors that influence the risk of a service failure is conducted and quantitative models are developed to predict locations where service failures are most likely to occur until the next inspection. To this end, data are collected from a Class I U.S. Railroads for six years from 2011 to 2016. Four prediction models (i.e., logistic regression, decision tree, multilayer perceptron, and gradient boosting classifier) are implemented and their results are compared. To account for the imbalanced classes between the normal operation and service failure, two treatments have been used including undersampling and oversampling. To improve the model performance, the parameters of each method are tuned using random search hyperparameter optimization. Later, bootstrap aggregation (or bagging) is incorporated into each method. The findings of the study show that the prediction performance is the highest when using bagging and oversampling as treatments with gradient boosting method. It was also identified that gross tonnage, presence of geometry defects, ambient temperature, segment length, and rail defect presence are the most important factors for predicting the risk of service failures. The results of this study are useful for railroads to develop effective strategies for rail inspections, preventive maintenance, and capital planning.

Light Emitting Diodes Photobiomodulation Improves Cardiac Function by Promoting ATP Synthesis in Mice With Heart Failure.

Heart failure (HF) is the common consequences of various cardiovascular diseases, often leading to severe cardiac output deficits with a high morbidity and mortality. In recent years, light emitting diodes-based therapy (LEDT) has been widely used in multiple cardiac diseases, while its modulatory effects on cardiac function with HF still remain unclear. Therefore, the objective of this study was to investigate the effects of LED-Red irradiation on cardiac function in mice with HF and to reveal its mechanisms. In this study, we constructed a mouse model of HF. We found that LED-Red (630 nm) was an effective wavelength for the treatment of HF. Meanwhile, the application of LED-Red therapy to treat HF mice improved cardiac function, ameliorate heart morphology, reduced pulmonary edema, as well as inhibited collagen deposition. Moreover, LED-Red therapy attenuated the extent of perivascular fibrosis. Besides, LED-Red irradiation promoted calcium transients in cardiomyocytes as well as upregulated ATP synthesis, which may have positive implications for contractile function in mice with HF. Collectively, we identified that LED-Red exerts beneficial effects on cardiac function in HF mice possibly by promoting the synthesis of ATP.

Investigation of Heterogeneity Sources for Occupational Task Recognition via Transfer Learning.

Human activity recognition has been extensively used for the classification of occupational tasks. Existing activity recognition approaches perform well when training and testing data follow an identical distribution. However, in the real world, this condition may be violated due to existing heterogeneities among training and testing data, which results in degradation of classification performance. This study aims to investigate the impact of four heterogeneity sources, cross-sensor, cross-subject, joint cross-sensor and cross-subject, and cross-scenario heterogeneities, on classification performance. To that end, two experiments called separate task scenario and mixed task scenario were conducted to simulate tasks of electrical line workers under various heterogeneity sources. Furthermore, a support vector machine classifier equipped with domain adaptation was used to classify the tasks and benchmarked against a standard support vector machine baseline. Our results demonstrated that the support vector machine equipped with domain adaptation outperformed the baseline for cross-sensor, joint cross-subject and cross-sensor, and cross-subject cases, while the performance of support vector machine equipped with domain adaptation was not better than that of the baseline for cross-scenario case. Therefore, it is of great importance to investigate the impact of heterogeneity sources on classification performance and if needed, leverage domain adaptation methods to improve the performance.

Quantifying the CVD-grown two-dimensional materials via image clustering.

Machine learning (ML) techniques have been recently employed to facilitate the development of novel two-dimensional (2D) materials. Among various synthesis approaches, chemical vapor deposition (CVD) has demonstrated tremendous potential in producing high-quality 2D flakes with good controllability, enabling large-scale production at a relatively low cost. Traditionally, the quality of CVD-grown samples can be manually evaluated based on optical images which is labor-intensive and time-consuming. In this paper, we explored a data-driven unsupervised quality assessment strategy based on image clustering via integrating self-organizing map (SOM) and k-means methods for optical image analysis of CVD-grown 2D materials. The high matching rate between the clustering results and material experts' labels indicated a good accuracy of the proposed clustering algorithm. The proposed unsupervised ML methodology will provide materials scientists with an effective tool kit for efficient evaluation of CVD-grown materials' quality and has a broad applicability for various material systems.

Real-World Outcomes of Revascularization Strategies in Patients With Left Ventricular Dysfunction and Three-Vessel Coronary Disease Stratified by Mitral Regurgitation.

Aims: Limited information exists regarding optimal revascularization options for patients with triple-vessel coronary artery disease (TVD), heart failure (HF), and different degrees of mitral regurgitation (MR). Thus, we aimed to compare the effect of percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) surgery in the indicated patients. Methods and Results: In the real-world prospective study, 1190 patients with multi-vessel disease and decreased left ventricular systolic function but without severe MR, who underwent PCI or CABG, were enrolled and followed-up for 4.7 ± 1.8 years. The primary endpoint was a composite of cardiovascular death and HF hospitalization. Secondary endpoints were the individual components of the primary outcome. Risk of the primary endpoint was higher in the PCI than in the CABG group (HR = 1.38, 95%CI: 1.14-1.67, and P < 0.01), particularly in patients with moderate MR (HR = 1.85, 95%CI: 1.35-2.55, and P < 0.01). In patients with no-mild MR, the risk of the primary endpoint did not differ significantly between PCI and CABG (P = 0.09). Treatment with PCI was associated with an increased risk for cardiovascular death and HF hospitalization in the moderate MR cohort, while PCI was comparable to CABG in the no-mild MR cohort. Conclusions: In this real-world study, for patients with HF and TVD, CABG was related to lower adverse outcome rates compared to PCI. Assessment of MR can aid in selecting optimal revascularization therapies and in risk stratification.

Sperm mtDNA copy number, telomere length, and seminal spermatogenic cells in relation to ambient air pollution: Results of a cross-sectional study in Jing-Jin-Ji region of China.

Evidences on the association of air pollutants and semen quality were limited and mechanism-based biomarkers were sparse. We enrolled 423 men at a fertility clinic in Shijiazhuang, China to evaluate associations between air pollutants and semen quality parameters including the conventional ones, sperm mitochondrial DNA copy number (mtDNAcn), sperm telomere length (STL) and seminal spermatogenic cells. PM2.5, PM10, CO, SO2, NO2 and O3 exposure during lag0-90, lag0-9, lag10-14 and lag70-90 days were evaluated with ordinary Kringing model. The exposure-response correlations were analyzed with multiple linear regression models. CO, PM2.5 and PM10 were adversely associated with conventional semen parameters including sperm count, motility and morphology. Besides, CO was positively associated with seminal primary spermatocyte (lag70-90, 0.49; 0.14, 0.85) and mtDNAcn (lag0-90, 0.37; 0.12, 0.62, lag10-14, 0.31; 0.12, 0.49), negatively associated with STL (lag0-9, -0.30; -0.57, -0.03). PM2.5 was positively associated with mtDNAcn (0.50; 0.24, 0.75 and 0.38; 0.02, 0.75 for lag0-90 and lag70-90) while negatively associated with STL (lag70-90, -0.49; -0.96, -0.01). PM10 and NO2 were positively associated with mtDNAcn. Our findings indicate CO and PM might impair semen quality testicularly and post-testicularly while seminal spermatogenic cell, STL and mtDNAcn change indicate necessity for more attention on these mechanisms.

A forecasting framework for predicting perceived fatigue: Using time series methods to forecast ratings of perceived exertion with features from wearable sensors.

Advancements in sensing and network technologies have increased the amount of data being collected to monitor the worker conditions. In this study, we consider the use of time series methods to forecast physical fatigue using subjective ratings of perceived exertion (RPE) and gait data from wearable sensors captured during a simulated in-lab manual material handling task (Lab Study 1) and a fatiguing squatting with intermittent walking cycle (Lab Study 2). To determine whether time series models can accurately forecast individual response and for how many time periods ahead, five models were compared: naïve method, autoregression (AR), autoregressive integrated moving average (ARIMA), vector autoregression (VAR), and the vector error correction model (VECM). For forecasts of three or more time periods ahead, the VECM model that incorporates historical RPE and wearable sensor data outperformed the other models with median mean absolute error (MAE) <1.24 and median MAE <1.22 across all participants for Lab Study 1 and Lab Study 2, respectively. These results suggest that wearable sensor data can support forecasting a worker's condition and the forecasts obtained are as good as current state-of-the-art models using multiple sensors for current time prediction.

Melatonin promotes cardiomyocyte proliferation and heart repair in mice with myocardial infarction via miR-143-3p/Yap/Ctnnd1 signaling pathway.

The neonatal heart possesses the ability to proliferate and the capacity to regenerate after injury; however, the mechanisms underlying these processes are not fully understood. Melatonin has been shown to protect the heart against myocardial injury through mitigating oxidative stress, reducing apoptosis, inhibiting mitochondrial fission, etc. In this study, we investigated whether melatonin regulated cardiomyocyte proliferation and promoted cardiac repair in mice with myocardial infarction (MI), which was induced by ligation of the left anterior descending coronary artery. We showed that melatonin administration significantly improved the cardiac functions accompanied by markedly enhanced cardiomyocyte proliferation in MI mice. In neonatal mouse cardiomyocytes, treatment with melatonin (1 µM) greatly suppressed miR-143-3p levels. Silencing of miR-143-3p stimulated cardiomyocytes to re-enter the cell cycle. On the contrary, overexpression of miR-143-3p inhibited the mitosis of cardiomyocytes and abrogated cardiomyocyte mitosis induced by exposure to melatonin. Moreover, Yap and Ctnnd1 were identified as the target genes of miR-143-3p. In cardiomyocytes, inhibition of miR-143-3p increased the protein expression of Yap and Ctnnd1. Melatonin treatment also enhanced Yap and Ctnnd1 protein levels. Furthermore, Yap siRNA and Ctnnd1 siRNA attenuated melatonin-induced cell cycle re-entry of cardiomyocytes. We showed that the effect of melatonin on cardiomyocyte proliferation and cardiac regeneration was impeded by the melatonin receptor inhibitor luzindole. Silencing miR-143-3p abrogated the inhibition of luzindole on cardiomyocyte proliferation. In addition, both MT1 and MT2 siRNA could cancel the beneficial effects of melatonin on cardiomyocyte proliferation. Collectively, the results suggest that melatonin induces cardiomyocyte proliferation and heart regeneration after MI by regulating the miR-143-3p/Yap/Ctnnd1 signaling pathway, providing a new therapeutic strategy for cardiac regeneration.

Early Departure, Early Revival: A ''Free From Care'' Account of Negative Temporal Discounting.

According to the positive temporal discounting theory and our relevant observations, when faced with future losses, people should, and do, prefer delayed negative events (e.g., deferring paying taxes, debts, or tickets), which can lead to substantial individual and societal costs. However, a counterexample has been identified and it appears to depart from the prediction of positive temporal discounting when faced with negative events. This study proposed and investigated the novel free from care account for the reverse preference. Results of five laboratory and field studies showed that students preferred an immediate negative event (i.e., an English oral exam) when "something tying one up" was imposed, in which coping with a distraction induced by such a situation could play a mediating role. In particular, the addition of "something tying one up" was found to be an effective behavioral nudge in terms of reliability and reproducibility and should be simple for potential users to follow. Specifically, the association between being tied up and undergoing a negative event immediately in the present studies mirrored the association between outgroup threat and intergroup cooperation in the Robbers Cave experiment.