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Spawn aging poses a substantial challenge to the Agaricus bisporus industry. This study focuses on the role of mitochondrial dysfunction in the aging process of A. bisporus spawn. We conducted a comprehensive comparative transcriptome analysis to elucidate the molecular mechanisms underlying A. bisporus spawn aging. A total of 1620 genes with significant expression changes between the normal and aged spawn were identified, including 917 up-regulated genes and 703 down-regulated genes. Our results revealed a notable down-regulation of genes involved in carbohydrate metabolism, mitochondrial energy metabolism, reactive oxygen species (ROS) scavenging, repair mechanisms for oxidative stress-induced damage, fatty acid β-oxidation, and amino acid degradation in aged A. bisporus spawn. Additionally, we observed a decreased expression of genes involved in critical signal transduction pathways associated with mitochondrial function in aged mycelium as well as genes responsible for maintaining mitochondrial stability. The up-regulated genes in aged spawn mainly affect mitochondrial fission and programmed cell death, impacting mitochondrial function. Overall, the present study first provides evidence for the pivotal role of mitochondrial dysfunction in the aging process of A. bisporus spawn and contributes to the development of targeted strategies to enhance mitochondrial function, mitigate spawn aging, and improve the yield and quality of A. bisporus cultivation. [ABSTRACT FROM AUTHOR]

The Insulated Gate Bipolar Transistor (IGBT) is the key power device in the rod control power cabinet of nuclear power plants; its reliable operation is of great significance for ensuring the safe and economical operation of the nuclear power plants. Therefore, it is necessary to conduct fault prediction research on IGBT to achieve better condition-based maintenance and improve its operational reliability. However, power cabinets often operate under multiple, complex working conditions, so predicting IGBT faults from single working condition data usually has limitations and low accuracy. Its failure probability has an important relationship with the actual operating conditions of the cabinet. In order to improve the reliability and maintainability of the control power cabinet in nuclear power plants, this paper takes IGBTs in the rod control power cabinet as the object and makes full use of the data of IGBTs under multiple working conditions to carry out research on the cross-condition fault prediction of IGBTs under multiple-source working conditions. A transfer learning (TL) model based on a bidirectional time convolutional network (BiTCN) combined with attention was proposed to solve the problem of low accuracy of cross-operating fault prediction in a multi-source domain. Firstly, an IGBT fault simulation model was built to collect the life cycle state data of the module under different working conditions. Then, after pre-processing such as removing outliers, kernel principal component analysis (KPCA) was used to integrate all source domain data, obtain source domain characterization data, and train the BiTCN-attention model. Finally, the BiTCN-attention model trained in the source domain was transferred, and the model was fine-tuned according to the target domain data. Simulation results show that the accuracy of the proposed BiTCN-attention transfer learning prediction method can reach more than 99%, which is significantly better than that of the recurrent neural network transfer learning (RNN-TL) model, long short-term memory network transfer learning (LSTM-TL) model, gated cyclic unit transfer learning (GRU-TL) model, and time convolutional network transfer learning (TCN-TL) model. This method can not only reduce the inconsistency of fault characteristic values caused by changes in working conditions but also accurately predict the degradation trend when only early fault data are available, providing an effective solution for IGBT fault prediction across working conditions in multi-source domains. [ABSTRACT FROM AUTHOR]

Agaricus bisporus, belonging to the genus Agaricus and the family Agaricaceae, is a popular commercially cultivated mushroom with rich nutritional and medical values. Cultivation of A. bisporus requires superior cultivars. Understanding the differences between wild and cultivated accession at the genetic level is crucial for mining loci and genes associated with cultivation-related traits, informing future breeding directions. Additionally, the identification of loci and genes associated with important agronomic traits (e.g., yield and quality) facilitates mushroom molecular breeding. In this study, we conducted sequencing of 200 strains of A. bisporus and analyzed genomic variations. Population structure and genetic relationships were investigated for 200 strains. Selection signs and genes were also obtained after selection sweep analysis. Thirteen candidate genes in the selective elimination regions had significantly different expression patterns at the fruit body stage. Moreover, six genes were identified for the esterase isozyme type through a combination of GWAS and RNA data. This study provides insight into environmental adaptation at the genetic base, providing valuable genetic resources for button mushroom molecular breeding to improve environmental adaptation, quality, or yield. [ABSTRACT FROM AUTHOR]

Background: Parental Educational Attainment and children's 24-h behaviors significantly influenced children's hyperactivity symptoms. This study aimed to examine the mediating role of children's 24-h behavior changes due to the COVID-19 pandemic between Parental Educational Attainment and children's hyperactivity index. It also aimed to investigate the associations between Children's Physical Activity, digital media use, sleep, and hyperactivity index between two clusters of Parental Educational Attainments. The goal was to provide targeted behavioral optimization recommendations for caregivers to reduce the risk of children's hyperactivity. Methods: The study was a collaborative extension of the International iPreschooler Surveillance Study Among Asians and otheRs project and the Chinese Children and Adolescent Sports Health Promotion Action Project. The Parent-Surveillance of Digital Media in Childhood Questionnaire® and the Abbreviated Rating Scales from the Conners Parent Symptom Questionnaire were used to measure Parental Educational Attainment, children's behavior changes during the COVID-19 pandemic, and hyperactivity indexes. A total of 11,190 parents of 6-to-12-year-old children completed the online surveys in mainland China. A structural equation model was established by using Smart-PLS, and the linear regression model, and isotemporal substitution models were established by using a Compositional Data Analysis package with R program to achieve the research objectives. Results: Changes in children's 24-h behaviors due to the COVID-19 pandemic had a significant mediation effect on the negative associations between Parental Educational Attainment and children's hyperactivity index (β = 0.018, T = 4.521, p < 0.001) with a total effect (β = −0.046, T = 4.521, p < 0.001) and a direct effect (β = −0.064, T = 6.330, p < 0.001). Children's Digital Media use was significantly and negatively associated with hyperactivity index among all children. Reallocated time from digital media use to both sleep and physical activity decreased the hyperactivity index, and vice-versa. For parents without tertiary education (R2 = 0.09, p < 0.001), sleep was significantly and negatively associated with the hyperactivity index (βilr-CSL = −0.06, p < 0.001); for parents with tertiary education (R2 = 0.07, p < 0.001), physical activity was significantly and negatively associated with the hyperactivity index (βilr-CPA = −0.05, p < 0.001), and sleep was significantly and positively associated with the hyperactivity index (βilr-CSL = 0.03, p < 0.001). A significant increase in the hyperactivity index was detected when physical activity time was reallocated to sleep, with a significant decrease in the opposite direction. Conclusions: Parental Educational Attainment and children's 24-h behaviors directly influenced children's hyperactivity index. However, a purposeful and targeted optimization of children's 24-h behaviors—namely, physical activity, digital media use, and sleep—could assist parents with different educational attainments to reduce their children's hyperactivity index and mitigate the risk of hyperactivity. [ABSTRACT FROM AUTHOR]

Outbreaks of wet bubble disease (WBD) caused by Mycogone perniciosa are increasing across the world and seriously affecting the yield of Agaricus bisporus. However, highly WBD-resistant strains are rare. Here, we tested 28 A. bisporus strains for WBD resistance by inoculating M. perniciosa spore suspension on casing soil, and assessed genetic diversity of these strains using 17 new simple sequence repeat (SSR) markers developed in this study. We found that 10 wild strains originating from the Tibetan Plateau in China were highly WBD-resistant strains, and 13 cultivated strains from six countries were highly susceptible strains. A total of 88 alleles were detected in these 28 strains, and the observed number of alleles per locus ranged from 2 to 8. Cluster and genetic structure analysis results revealed the wild resources from China have a relatively high level of genetic diversity and occur at low level of gene flow and introgression with cultivated strains. Moreover, the wild strains from China potentially have the consensus ancestral genotypes different from the cultivated strains and evolved independently. Therefore, the highly WBD-resistant wild strains from China and newly developed SSR markers could be used as novel sources for WBD-resistant breeding and quantitative trait locus (QTL) mapping of WBD-resistant gene of A. bisporus., Competing Interests: The authors declare no conflict of interest.