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[This corrects the article DOI: 10.1371/journal.pone.0290267.].

In addition to affecting people’s bodily and mental health, the Covid-19 epidemic has also altered the emotional and mental well-being of many workers. Especially in the realm of institutions and privately held enterprises, which encountered a plethora of constraints due to the peculiar circumstances of the epidemic. It was thus anticipated that the present study would use a group method of data handling (GMDH) neural network for analyzing the relationship of demographic factors, Coronavirus, resilience, and the burnout in startups. The test methodology was quantitative. The research examined 384 startup directors and representatives, which is a sizable proportion of the limitless community. The BRCS, the MBI-GS, and custom-made assessments of stress due to the Coronavirus were all used to collect data. Cronbach’s alpha confirmed the polls’ dependability, and an expert panel confirmed the surveys’ authenticity. The GMDH neural network’s inherent potential for self-organization was used to choose the most useful properties automatically. The trained network has a three-layered topology with 4, 3, and 2 neurons in each of the hidden layers. The GMDH network has significantly reduced the computational load by using just 7 parameters of marital status, stress of covid-19, job experience, professional efficiency, gender, age, and resilience for burnout categorization. After comparing the neural network’s output with the acquired data, it was determined that the constructed network accurately classified all of the information. Among the achievements of this research, high accuracy in predicting job burnout, checking the performance of neural network in determining job burnout and introducing effective characteristics in determination of this parameter can be mentioned.

Observations and model simulations reveal that El Niño generates stronger westerly anomalies than the easterlies induced by La Niña. Here we show that this asymmetry arises from the nonlinear sensitivity of atmospheric convection to total sea surface temperature (SST) in the tropical Pacific. Convection–SST sensitivity increases within 25.5–28.75°C, where small warm anomalies trigger disproportionately stronger convection anomalies, inducing intrinsic asymmetry in the atmospheric response to ENSO. Using observations, CMIP6 simulations, and Gill‐type atmospheric model experiments, we show that stronger convection–SST sensitivity enhances low‐level wind asymmetry. Gill‐type model sensitivity experiments further illustrate a monotonic increase in wind asymmetry with stronger convection–SST sensitivity prescribed therein. These results identify nonlinear convection–SST coupling as the bridge linking ENSO SST anomalies to asymmetric atmospheric responses, underscoring the importance of coupled models realistically capturing the observed convection–SST sensitivity for improved ENSO simulations..

1,3,5-triazine derivatives, also called s-triazines, are a series of containing-nitrogen heterocyclic compounds that play an important role in anticancer drug design and development. To date, three s-triazine derivatives, including altretamine, gedatolisib, and enasidenib, have already been approved for refractory ovarian cancer, metastatic breast cancer, and leukemia therapy, respectively, demonstrating that the s-triazine core is a useful scaffold for the discovery of novel anticancer drugs. In this review, we mainly focus on s-triazines targeting topoisomerases, tyrosine kinases, phosphoinositide 3-kinases, NADP+-dependent isocitrate dehydrogenases, and cyclin-dependent kinases in diverse signaling pathways, which have been extensively studied. The medicinal chemistry of s-triazine derivatives as anticancer agents was summarized, including discovery, structure optimization, and biological applications. This review will provide a reference to inspire new and original discoveries.

We propose a scheme for the quantum metrology of the Schwinger effect and the dynamics of Gaussian interference power (GIP). The ongoing reliability of the estimation strategy for the probe state prepared in particle–particle modes is demonstrated. Although the GIP sensitively depends on the strength of the external electric field and the transverse momentum, the advantage of quantum parameter estimation is still maintained even in the limit of an infinite electric field and zero transverse momentum. It is shown that the entanglement between the particle–particle modes provides a guarantee for obtaining higher precision for the black-box estimation. In contrast, for the probe state prepared in particle–antiparticle modes, the advantage of quantum parameter estimation can also be ensured even though there is no entanglement in the probe state. Put differently, some non-entanglement quantum correlations play the role of quantum resources in the estimation for particle–antiparticle modes.

Heart failure (HF) remains a significant global health concern with limited effective treatments available. C1q/TNF‐related protein 6 (CTRP6) is a member of the CTRP family analogous to adiponectin and its role in HF pathogenesis remains unclear. Here, we investigated the impact of CTRP6 on HF progression. To mimic heart failure with reduced ejection fraction (HFrEF), we used isoproterenol injection in mice and administered adenovirus vectors expressing CTRP6 (Ad‐CTRP6) via tail vein injection. We assessed cardiac function through echocardiography and histology. CTRP6's effects on hypertrophy, fibrosis, apoptosis, oxidative stress and mitochondrial function were analysed. Downstream pathways (phosphorylated AMP‐activated protein kinase (p‐AMPK), sirtuin 1 (SIRT1) and peroxisome proliferator‐activated receptor γ coactivator 1‐α (PGC‐1α) were studied in heart tissues. In vitro, isoproterenol‐stimulated H9c2 cardiomyocytes were treated with CTRP6 to examine viability, apoptosis, F‐actin and signalling proteins. Compound C was used to assess AMPK involvement. CTRP6 expression was lower in the plasma of HF patients. In an isoproterenol‐induced HFrEF mouse model, adenovirus‐mediated overexpression of CTRP6 ameliorated cardiac dysfunction and reduced cardiomyocyte apoptosis, oxidative stress, inflammation and myocardial injury markers. Mechanistically, CTRP6 activation of the AMPK/SIRT1/PGC‐1α signalling pathway restored mitochondrial homeostasis, evidenced by reduced mitochondrial reactive oxygen species levels, increased ATP content, and enhanced mitochondrial complex I/III activities in cardiac tissues. In vitro studies using isoproterenol‐stimulated H9c2 cardiomyocytes corroborated these findings, demonstrating that CTRP6 upregulation attenuated hypertrophy, apoptosis, oxidative stress and mitochondrial dysfunction. Furthermore, these effects were partially reversed by the AMPK inhibitor Compound C, implicating the involvement of the AMPK pathway in CTRP6‐mediated cardioprotection. CTRP6 alleviates HF progression through the AMPK/SIRT1/PGC‐1α signalling pathway. What is the central question of this study? What are the role and mechanisms of C1q/tumour necrosis factor‐related protein‐6 (CTRP6) in heart failure (HF) progression and its potential cardioprotective effects? What is the main finding and its importance? CTRP6 alleviates HF progression through the activation of the AMPK/SIRT1/PGC‐1α signalling pathway, reducing oxidative stress, inflammation and mitochondrial dysfunction. This may enable development of novel therapeutic strategies for HF management.

Cytosine base editors (CBEs) and adenine base editors (ABEs) enable precise C-to-T and A-to-G edits. Recently, ABE8e, derived from TadA-8e, enhances A-to-G edits in mammalian cells and plants. Interestingly, TadA-8e can also be evolved to confer C-to-T editing. This study compares engineered CBEs derived from TadA-8e in rice and tomato cells, identifying TadCBEa, TadCBEd, and TadCBEd_V106W as efficient CBEs with high purity and a narrow editing window. A dual base editor, TadDE, promotes simultaneous C-to-T and A-to-G editing. Multiplexed base editing with TadCBEa and TadDE is demonstrated in transgenic rice, with no off-target effects detected by whole genome and transcriptome sequencing, indicating high specificity. Finally, two crop engineering applications using TadDE are shown: introducing herbicide resistance alleles in OsALS and creating synonymous mutations in OsSPL14 to resist OsMIR156 -mediated degradation. Together, this study presents TadA-8e derived CBEs and a dual base editor as valuable additions to the plant editing toolbox. Base editors are a powerful but underexplored tool for genetic engineering and directed evolution of plants. Here, the authors investigate the editing efficiency and specificity of TadA-8e-derived cytosine base editors and dual base editor TadDE in rice and tomato.

Background MYB transcription factors are widely distributed in the plant kingdom and play key roles in regulatory networks governing plant metabolism and biochemical and physiological processes. Results Here, we first determined the R2R3-MYB genes in five Euphorbiaceae genomes. The three Trp (W) residues from the first MYB domain (R2) were absolutely conserved, whereas the first W residue from the second MYB domain (R3) was preferentially mutated. The R2R3-MYBs were clustered into 48 functional subfamilies, of which 34 had both R2R3-MYBs of Euphorbiaceae species and AtMYBs, and four contained only Euphorbiaceae R2R3-MYBs. The whole-genome duplication (WGD) and/or segmental duplication (SD) played key roles in the expansion of the R2R3-MYB family. Unlike paralogous R2R3-MYB family members, orthologous R2R3-MYB members contained a higher selective pressure and were subject to a constrained evolutionary rate. VfMYB36 was specifically expressed in fruit, and its trend was consistent with the change in oil content, indicating that it might be involved in oil biosynthesis. Overexpression experiments showed that VfMYB36 could significantly provide linolenic acid (C18:3) content, which eventually led to a significant increase in oil content. Conclusion Our study first provides insight into understanding the evolution and expression of R2R3-MYBs in Euphorbiaceae species, and also provides a target for the production of biomass diesel and a convenient way for breeding germplasm resources with high linolenic acid content in the future.

Purpose Both off-topic discussions and exchanges of social support are important to the success of online health support groups. Analyzing their relationship could enhance our understanding of the nature of helpful interactions in online cancer support groups and ways promoting their success. Methods A total of 15,284 messages were collected and analyzed from an online support group for rectal cancer. Two coders coded and categorized the messages into 211 threads using directed content analysis and a social support classification system. The relationship between off-topic discussions and social support was explored using the quadratic assignment procedure. Results There are 91 threads of off-topic discussions, 83 threads of informational support, 22 threads of emotional support, seven threads of tangible support, five threads of network support, and three threads of esteem support. More of the off-topic discussions are associated with more emotional and tangible support. Both off-topic discussions and informational support are mutually influenced by the mediating role of emotional support. In addition, off-topic discussions and network support are mutually influenced by the mediating role of emotional and tangible support, and off-topic discussions and esteem support are mutually influenced by the mediating role of tangible support. Conclusions Off-topic discussions directly or indirectly promote different types of social support in an online rectal cancer support group.

Making timely assessments of disease progression in patients with COVID-19 could help offer the best personalized treatment. The purpose of this study was to explore an effective model to predict the outcome of patients with COVID-19. We retrospectively included 188 patients (124 in the training set and 64 in the test set) diagnosed with COVID-19. Patients were divided into aggravation and improvement groups according to the disease progression. Three kinds of models were established, including the radiomics, clinical, and combined model. Receiver operating characteristic curves, decision curves, and Delong’s test were used to evaluate and compare the models. Our analysis showed that all the established prediction models had good predictive performance in predicting the progress and outcome of COVID-19.