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This study evaluates the level of knowledge and the influencing factors related to the U = U (undetectable = untransmittable) concept among residents of Henan Province, China, using an online questionnaire. Among 700 participants whose responses met the inclusion criteria—namely, completion time between 90 and 600 s, consistent answers, and IP addresses located in Henan Province—only 29.86% had a basic understanding of U = U. Many participants held misconceptions, such as believing that individuals who achieve U = U status can discontinue medication or are completely cured of HIV. Descriptive statistics and multivariate logistic regression were used to analyze the data. Multivariate analysis revealed that knowledge of U = U was significantly associated with age, education level, medical background, and sexual orientation. Younger participants, those with higher education, and those with medical training exhibited a better understanding of U = U. These findings highlight the urgent need for targeted health education initiatives, especially for older and less-educated populations, to improve awareness and reduce misinformation.

Background Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause multiple organ damage in the whole body. Our aim was to use machine learning (ML) to build an independent polysomnography (PSG) model to analyze risk factors and predict OSAHS. Materials and methods Clinical data of 2064 snoring patients who underwent physical examination in the Health Management Center of the First Affiliated Hospital of Shanxi Medical University from July 2018 to July 2023 were retrospectively collected, involving 24 characteristic variables. Then they were randomly divided into training group and verification group according to the ratio of 7:3. By analyzing the importance of these features, it was concluded that LDL-C, Cr, common carotid artery plaque, A1c and BMI made major contributions to OSAHS. Moreover, five kinds of machine learning algorithm models such as logistic regression, support vector machine, Boosting, Random Forest and MLP were further established, and cross validation was used to adjust the model hyperparameters to determine the final prediction model. We compared the accuracy, Precision, Recall rate, F1-score and AUC indexes of the model, and finally obtained that MLP was the optimal model with an accuracy of 85.80%, Precision of 0.89, Recall of 0.75, F1-score of 0.82, and AUC of 0.938. Conclusion We established the risk prediction model of OSAHS using ML method, and proved that the MLP model performed best among the five ML models. This predictive model helps to identify patients with OSAHS and provide early, personalized diagnosis and treatment options.

Pediatric infections are often closely linked to infections in families, schools, and communities, illustrating the importance of developing a holistic model of pediatric respiratory infection prevention. Research purposes were to construct a new preventive model for pediatric respiratory infection prevention and to clarify the relationships among impact factors in this model. Research method was a cross-sectional survey. A structured questionnaire was used to measure model variables, including “parental prevention measures (PPM),” “concern about pediatric vaccination (CPV),” “school precautionary measures (SPM),” and “children’s self-protection practices (CSPP).” Structural equation modeling analysis was performed to test four proposed hypotheses and identify the relationships among these variables. Research participants were 2420 parents with one or more 3-16-year-old children. Results identified five paths in research model. (1) “Parental prevention measures, PPM” directly affects “concerns about pediatric vaccination, CPV” [direct effect: 0.354], “school precautionary measures, SPM” [direct effect: 0.354], and “children’s self-protection practices, CSPP” [direct effect: 0.354]. (2) PPM affects CPV through the mediating effect of SPM (indirect effect: 0.04), resulting in a total effect of 0.394. (3) PPM affects CSPP through the mediating effect of SPM (indirect effect: 0.3), resulting in a total effect of 0.655. All these effects were statistically significant. Results strongly suggested that coordinating prevention strategies between families and schoolteachers is most effective in equipping children with the knowledge and behaviors to avoid infectious disease. Results confirmed that the newly constructed model for preventing pediatric respiratory infection was well fitted as a double mediation model. Further studies are needed to pursue the family-school health education model in the prevention of pediatric infectious disease. Key words: Parental prevention measures; Concern about pediatric vaccination; School precautionary measures; Children’s self-protection practices; Pediatric Respiratory Infection.

Potassium‐ion batteries (PIBs) have garnered significant attention as a promising alternative to commercial lithium‐ion batteries (LIBs) due to abundant and cost‐efficient potassium reserves. However, the large size of potassium ions and the resulting sluggish reaction kinetics present major obstacles to the widespread use of PIBs. Herein, we present a simple method to ingeniously encapsulate SnS2 nanoparticles within sulfurized polyacrylonitrile (SPAN) fibers (SnS2@SPAN) for serving as a high‐performance PIB anode. The large interlayer spacing of SnS2 provides a fast transport channel for potassium ions during charge–discharge cycles, while the one‐dimensional SPAN skeleton offers massive binding sites and shortens the diffusion path for potassium ions, facilitating faster reaction kinetics. Additionally, the excellent ductility of SPAN can effectively accommodate the large volume changes that occur in SnS2 upon potassium‐ion insertion, thereby enhancing the cyclic stability of SnS2. Benefiting from the above advantages, the SnS2@SPAN composites exhibit impressive cyclability over 500 cycles at 4 A g−1, with a capacity retention rate close to 100%. This study provides an effective approach for stabilizing high‐capacity PIB anode materials with large volume variations. A long‐lifespan potassium‐ion battery (PIB) anode, namely, SnS2@sulfurized polyacrylonitrile (SPAN) composite, is prepared by encapsulating ultrasmall SnS2 nanocrystals in SPAN fibers via coaxial electrospinning and vulcanization, which exhibits 117.5 mAh g−1 over 500 cycles at 4 A g−1. This work provides a reliable approach to enhance the structural stability and battery performance of high‐capacity anode materials for PIBs.

Recurrent seizures lead to self-reconstruction of the central nervous system, which is termed the neuroplasticity of epilepsy. While preclinical studies implicate neuroinflammation and oxidative stress in epilepsy-associated neuroplasticity, in vivo molecular-level evidence in humans is lacking. We used astrocyte-derived extracellular vesicles (ADEVs) and neuron-derived extracellular vesicles (NDEVs) as brain-derived biomarkers to explore biomarkers of neuroplasticity, neuroinflammation, and oxidative stress. A total of 50 patients in the epilepsy group (EP) and 25 matched healthy controls (HC) were recruited for this study. Plasma ADEVs and NDEVs were isolated and confirmed, and the levels of the EV marker CD81, the neuroplasticity marker brain-derived neurotrophic factor (BDNF), and the neuroinflammation marker tumor necrosis factor α (TNF-α) in ADEVs, as well as the markers of oxidative stress, superoxide dismutase 1 (SOD1) and malondialdehyde (MDA), in NDEVs were measured. BDNF levels in ADEVs and SOD1 levels in NDEVs from EP were significantly lower than those in HC, whereas TNF-α levels in ADEVs and MDA levels in NDEVs were significantly increased, and the results remained stable after normalization by CD81. Spearman correlation analysis revealed that BDNF levels in ADEVs were negatively correlated with TNF-α levels in ADEVs and MDA levels in NDEVs and positively correlated with SOD1 levels in NDEVs. The innovative use of ADEVs and NDEVs as brain-derived biomarkers in this study provides in vivo evidence that epilepsy may result in impaired neuroplasticity and may be associated with increased neuroinflammation and oxidative stress.

Background Drought severely limits crop growth and yield. Highland barley ( Hordeum vulgare L.), a naturally stress-tolerant crop, serves as an ideal model for investigating the molecular and physiological mechanisms underlying plant drought adaptation. Results In this study, two highland barley varieties, Xi-La 22 (XL22) and Zang-Qing 17 (ZQ17), with different degrees of drought tolerance, were used to investigate the mechanism of drought tolerance in highland barley. Compared with XL22, ZQ17 exhibited significant reductions in the biomass and root/shoot ratio, and the increase in ion leakage and malondialdehyde content under drought stress. Natural drought experiment further confirmed that ZQ17 had a higher fatality rate and water loss rate than XL22, indicating that XL22 had higher drought tolerance. Drought induced significant increase in H 2 O 2 and O 2 . − levels in both barley varieties, especially in ZQ17. Moreover, compared with XL22, more distribution of H 2 O 2 in chloroplasts of ZQ17 might lead to greater degradation of photosynthetic protein complexes (PSI, PSII, LHCII trimers), thereby reducing photosynthetic capacity. The activities of glutathione reductase and glutathione peroxidase and content of reduced glutathione and ascorbate acid were markedly higher in XL22 compared with ZQ17 under drought stress. RNA-seq results showed many genes related to reactive oxygen species (ROS) scavenging, osmotic adjustment (LEA, HSP, aquaporins), hormone signaling and transcription factors (TFs) were specifically up-regulated in XL22. Weighted gene co-expression network analysis (WGCNA) further identified key modules and clarified core hub genes in XL22, mainly including genes in bZIP, AP2/ERF, bHLH transcription factor (TF) families and ABA signaling pathway, which help maintain high ROS scavenging capacity, root/shoot ratio and photosynthetic performance. Conclusion This study reveals that drought-tolerant highland barley maintains antioxidant activity, photosynthetic complex integrity, hormone signaling, and drought-responsive TF activation, providing insights for barley germplasm screening.

Iron (Fe) is an essential micronutrient for plants. Due to the low Fe bioavailability in cultivated soils, Fe deficiency is a widespread agricultural problem. In this study, we present the functional characterization of a petunia (Petunia hybrida) basic-helix-loop-helix transcription factor PhbHLH121 in response to Fe shortage. Real-time PCR revealed that the expression of PhbHLH121 in petunia roots and shoots was downregulated under Fe-limited conditions. CRISPR/Cas9-edited phbhlh121 mutant plants were generated to investigate the functions of PhbHLH121 in petunia. Loss-of-function of PhbHLH121 enhanced petunia tolerance to Fe deficiency. Further investigations revealed that the expression level of several structural genes involved in Fe uptake in petunia, such as IRT1 and FRO2, was higher in phbhlh121 mutants compared to that in wild-type under Fe-limited conditions, and the expression level of several genes involved in Fe storage and Fe transport, such as VTL2, FERs and ZIF1, was lower in phbhlh121 mutants compared to that in wild-type under Fe-deficient conditions. Yeast one-hybrid assays revealed that PhbHLH121 binds to the G-box element in the promoter of genes involved in Fe homeostasis. Yeast two-hybrid assays revealed that PhbHLH121 interacts with petunia bHLH IVc proteins. Taken together, PhbHLH121 plays an important role in the Fe deficiency response in petunia.

Aim To explore the influence of emotional intelligence and organisational commitment (OC) on clinical nurses' turnover intention (TI) and to provide intervention strategies to reduce the turnover rate of nursing staff and maintain the stability of the nursing team. Design A cross‐sectional descriptive study was conducted with nurses (n = 452) in a tertiary hospital in Kaifeng City, Henan Province, China. Methods The project was conducted in July 2023. The data were collected using the organisational commitment scale, Wong and Law emotional intelligence scale and turnover intention scale. Results The emotional intelligence score of clinical nurses was (3.07 ± 0.68), organisational commitment scale was (3.04 ± 0.68), and turnover intention scale was (2.70 ± 0.58). Organisational commitment scale and emotional intelligence scores are negatively correlated with turnover intention; the mediating effect of emotional intelligence in organisational commitment and turnover intention scale of clinical nurses is −0.406, and the mediating effect accounts for 49.9%. Public Contribution Nurses' organisational commitment can directly predict turnover intention, and emotional intelligence plays a role in mediating the relationship between nurses' organisational commitment and turnover intention. This research makes a substantial contribution to the public and healthcare sector. The findings provide valuable insights for healthcare administrators, policy‐makers and educators, offering evidence‐based strategies to improve nurse retention and enhance the quality of patient care. It is important to note that the research upholds the highest standards of integrity, with a meticulous review process and a dedicated effort to maintain data quality.

Powdery mildew (PM), triggered by Oidium neolycopersici , represents a significant threat and a major concern for the productivity of tomato plants ( Solanum lycopersicum L.). The presence of susceptibility (S) genes in plants facilitates pathogen proliferation and their dysfunction can lead to a recessively inherited broad-spectrum and durable type of resistance. Past studies have demonstrated that disrupting the function of DND1 (Defense No Death 1) increases plant resilience against various pathogens, such as powdery mildew (PM), but this comes at the cost of negatively affecting the overall health and vigor of the plant. To investigate the possibility of minimizing the adverse effects of the dnd 1 mutation while boosting disease resistance, a CRISPR-Cas9 construct with four single guide RNAs targeting three exons of SlDND1 (Solyc02g088560.4.1) was designed and introduced into the tomato variety Moneymaker (MM) through Agrobacterium tumefaciens -mediated transformation. Three T 1 lines (named E1, E3 and E4) were crossed with MM and then selfed to produce T F2 families. All the T F2 plants in homozygous state dnd1/dnd1 , showed reduced PM symptoms compared to the heterozygous ( DND1/dnd1 ) and wild type ( DND1/DND1) ones. Two full knock-out (KO) mutant events (E1 and E4) encoding truncated DND1 proteins, exhibited clear dwarfness and auto-necrosis phenotypes, while mutant event E3 harbouring deletions of 3 amino acids, showed normal growth in height with less auto-necrotic spots. Analysis of the 3D structures of both the reference and the mutant proteins revealed significant conformational alterations in the protein derived from E3, potentially impacting its function. A dnd1/dnd1 TF2 line (TV181848-9, E3) underwent whole-genome sequencing using Illumina technology, which confirmed the absence of off-target mutations in selected genomic areas. Additionally, no traces of the Cas9 gene were detected, indicating its elimination through segregation. Our findings confirm the role of DND1 as an S-gene in tomato because impairment of this gene leads to a notable reduction in susceptibility to O. neolycopersici . Moreover, we provide, for the first time, a dnd1 mutant allele (E3) that exhibits fitness advantages in comparison with previously reported dnd1 mutant alleles, indicating a possible way to breed with dnd1 mutants.

The 28th United Nations Climate Change Conference, held in the United Arab Emirates at the end of November 2023, stated that climate action cannot be delayed and the financing and investment situation for adapting to climate change needs a qualitative leap. Vigorously developing green finance is one of the important ways to achieve this goal. The core question of this paper is: Can green finance policies promote enterprises’ environmental investment? This article uses the formal implementation of the “Green Credit Guidelines” in 2012 as a quasi-natural experiment, bases on the micro data of A-share listed companies from 2004 to 2020, and adopts the difference-indifferences propensity score matching method (PSM-DID) to explore the role of green credit policy in guiding corporate environmental protection investment from multiple dimensions. The research shows that the implementation of the “Green Credit Guidelines” has promoted corporate environmental protection investment to a certain extent, and the conclusion still holds after a series of robustness tests. Heterogeneity tests found that the impact of green credit policy on corporate environmental protection investment varies significantly among different ownership enterprises and enterprises in different regions. Further research shows that the Green Credit Guidelines are regulated by macro and meso factors. From the perspective of mechanism, this paper finds out the mechanism of promoting enterprises’ environmental protection investment at the micro level. At the macro level, economic policy uncertainty and monetary policy tightening affect the degree of corporate environmental protection investment. At the meso level, the government’s attention to environmental protection determines the behavior of local enterprises, which in turn affects the attitude of enterprises towards environmental protection investment activities. At the micro level, the implementation of green credit on the one hand exacerbates the problem of corporate financing constraints, making companies have incentives to invest in environmental protection to alleviate this problem. On the other hand, it will also promote changes in innovation and capital factors in enterprises, directly increasing corporate environmental protection investment. This paper is helpful for the theoretical circle and management departments, so as to provide reference for the government to issue relevant policies.