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Acute Myocardial Infarction (AMI) has seen rising cases, particularly in younger people, leading to public health concerns. Standard treatments, like coronary artery recanalization, often don't fully repair the heart's microvasculature, risking heart failure. Advances show that Mesenchymal Stromal Cells (MSCs) transplantation improves cardiac function after AMI, but the harsh microenvironment post-AMI impacts cell survival and therapeutic results. MSCs aid heart repair via their membrane proteins and paracrine extracellular vesicles that carry microRNA-125b, which regulates multiple targets, preventing cardiomyocyte death, limiting fibroblast growth, and combating myocardial remodeling after AMI. This study introduces ultrasound-responsive phase-change bionic nanoparticles, leveraging MSCs' natural properties. These particles contain MSC membrane and microRNA-125b, with added macrophage membrane for stability. Using Ultrasound Targeted Microbubble Destruction (UTMD), this method targets the delivery of MSC membrane proteins and microRNA-125b to AMI's inflamed areas. This aims to enhance cardiac function recovery and provide precise, targeted AMI therapy.

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BACKGROUND: Older adults living in elderly caring social organizations (SOs) are prone to suffer from depression. Many studies have found correlations between environmental and quality-of-life factors and depression; however, evidence from elderly caring SOs is rare, particularly in China. METHODS: A cross-sectional study was conducted among service recipients in elderly caring SOs in Anhui and Chongqing, China. Data on demographic and health-related characteristics, living environment factors, and service quality satisfaction factors in 2171 older adults were used for analysis. The binary logistic regression model was conducted to estimate the association between living environment and service quality satisfaction factors and depression. RESULTS: Our results indicated that living environment factors in terms of exposure to suitable temperature and humidity (OR = 0.655; 95 % CI: 0.446, 0.963), green coverage >30 % (OR = 0.432; 95 % CI: 0.337, 0.553) were associated with lower odds of developing depression. Also, an opposite relationship was found in the noise factor (OR = 1.985; 95 % CI: 1.395, 2.823). Higher satisfaction with admission and discharge services, dietary services, entertainment services, and psychological support services were also found to be associated with a lower risk of depression. LIMITATIONS: A cross-sectional design precluded determining whether living environment, service quality satisfaction, and depression are causally related. Measurement of living environment factors and service quality satisfaction factors needs to be further clarified comprehensively. CONCLUSIONS: Enhancing the living environment and the quality of the services provided to seniors in the elderly caring SOs is conducive to the reduction of the likelihood of depression.

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A novel ion anchoring strategy stabilizes the perovskite phase, yielding ambient stable perovskite films and ultra-stable perovskite light-emitting diodes (PeLEDs) with an unprecedented operational half-lifetime over 37.2 years at 100 cd m-2 and exceeding 27% efficiency, marking a new stability benchmark for next-generation display and lighting applications.

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Seasonal variations in black carbon (BC) pollution characteristics during haze episodes in Benxi city, Liaoning province, were analyzed using year-long measurements of BC, carbon monoxide (CO), and PM2.5. Haze frequencies were recorded to be 0.07, 0.03 and 0.14 in spring, autumn, and winter respectively. Solid fuel contributions increased notably by 7%-8% during haze events compared to clean periods in all seasons. Transitioning from clean to haze periods led to ΔBC/ΔCO increases of 16% in spring and autumn, and 6.8% in winter, while BC/PM2.5 ratios decreased by approximately 33%, 50%, and 24% for spring, autumn, and winter respectively, likely indicating enhanced residential and industrial contributions. These further led to an increase in BC absorption capacities by factors of around 2.2 in spring and autumn, and up to 2.6 in winter during haze periods. Despite liquid fuel sources dominating BC emissions, certain haze episodes (frequency <10%) showed solid fuel contributions of up to 65%, highlighting BC pollution complexity in the region during haze. Backward trajectories analysis revealed local air masses from Liaoning province arrived consistently with the most occurrence of haze events across all seasons, while long-range air masses from Mongolian regions, though with less frequent occurrence during haze periods, significantly elevated BC loadings from solid fuel sources, particularly in spring and autumn due to biomass burning. Despite higher BC wet scavenging rates (WSR) in long-range air masses (0.072 ng m-3 ppbv-1 mm-1) compared to local air masses (0.039 ng m-3 ppbv-1 mm-1), significant BC transport persisted due to limited precipitation along transport pathways, especially during haze periods. These findings provide crucial insights for policymakers, highlighting the need for targeted haze prevention and control strategies focusing on mitigating BC emissions in Northeast China.

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Quasi-2D perovskites light-emitting diodes (PeLEDs) have achieved significant progress due to their superior optical and electronic properties. However, the blue PeLEDs still exist inefficient energy transfer and electroluminescence performance caused by mixed multidimensional phase distribution. In this work, transition metal salt (zinc bromide, ZnBr2) is introduced to modulate phase distributions by suppressing the nucleation of high n phase perovskites, which effectively shortens the energy transfer path for blue emission. Moreover, ZnBr2 also facilitates energy level matching and reduces non-radiative recombination, thus improving electroluminescence (EL) efficiency. Benefiting from these combined improvements, an efficient blue PeLEDs is obtained with a maximum external quantum efficiency (EQE) of 16.2% peaking located at 486 nm. This work provides a promising approach to tune phase distribution of quasi-2D perovskites and achieving highly efficient blue PeLEDs.

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Water eutrophication has emerged as a pressing concern for massive algal blooms, and these harmful blooms can potentially generate harmful toxins, which can detrimentally impact the aquatic environment and human health. Consequently, it is imperative to identify a safe and efficient approach to combat algal blooms to safeguard the ecological safety of water. This study aimed to investigate the procedure for extracting total flavonoids from Z. bungeanum residue and assess its antioxidant properties. The most favorable parameters for extracting total flavonoids from Z. bungeanum residue were a liquid-solid ratio (LSR) of 20 mL/g, a solvent concentration of 60%, an extraction period of 55 min, and an ultrasonic temperature of 80 °C. Meanwhile, the photosynthetic inhibitory mechanism of Z. bungeanum residue extracts against M. aeruginosa was assessed with a particular focus on the concentration-dependent toxicity effect. Z. bungeanum residue extracts damaged the oxygen-evolving complex structure, influenced energy capture and distribution, and inhibited the electron transport of PSII in M. aeruginosa. Furthermore, the enhanced capacity for ROS detoxification enables treated cells to sustain their photosynthetic activity. The findings of this study hold considerable relevance for the ecological management community and offer potential avenues for the practical utilization of resources in controlling algal blooms.

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Aging is a challenge to global development. This challenge is particularly significant for China because it has the largest elderly population worldwide. The proportion of aging population continues to increase, and solely relying on government efforts to meet the needs of the elderly is inadequate. Hence, involvement of social organizations in elderly care services is needed. Their core members exhibit higher sense of responsibility and identification with the organization than regular members, thus profoundly affecting organizational development. Based on the Social Capital Theory, this study employed a multistage stratified random sampling method to examine the social capital stock of elderly social organizations and their core members across six cities in Anhui Province, China. Chi-square tests analyzed the relationship between the core members' demographic factors and individual performance. Independent-sample t-tests assessed the relationship between social capital and individual performance. Finally, binary logistic regression models determined the factors influencing the individual performance of core members. Social networks within core members' social capital and the internal social capital of elderly caring social organizations (ESOs) affect the individual performance of core members. Therefore, organizations should provide more training opportunities for core members to expand their networks. Cultivating a shared language and vision as components of social capital can enhance organizational cohesion and operational stability.

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BACKGROUND: Predicting whether Carbapenem-Resistant Gram-Negative Bacterial (CRGNB) cause bloodstream infection when giving advice may guide the use of antibiotics because it takes 2-5 days conventionally to return the results from doctor's order. METHODS: It is a regional multi-center retrospective study in which patients with suspected bloodstream infections were divided into a positive and negative culture group. According to the positive results, patients were divided into the CRGNB group and other groups. We used the machine learning algorithm to predict whether the blood culture was positive and whether the pathogen was CRGNB once giving the order of blood culture. RESULTS: There were 952 patients with positive blood cultures, 418 patients in the CRGNB group, 534 in the non-CRGNB group, and 1422 with negative blood cultures. Mechanical ventilation, invasive catheterization, and carbapenem use history were the main high-risk factors for CRGNB bloodstream infection. The random forest model has the best prediction ability, with AUROC being 0.86, followed by the XGBoost prediction model in bloodstream infection prediction. In the CRGNB prediction model analysis, the SVM and random forest model have higher area under the receiver operating characteristic curves, which are 0.88 and 0.87, respectively. CONCLUSIONS: The machine learning algorithm can accurately predict the occurrence of ICU-acquired bloodstream infection and identify whether CRGNB causes it once giving the order of blood culture.

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Pharyngocutaneous fistula (PCF) is a major complication after total laryngectomy, with significant morbidity and mortality. Whether mechanical stapler closure of the pharynx reduces fistula rates compared to hand-sewn techniques remains unclear. We conducted an updated systematic review and meta-analysis to clarify this question. Five databases were systematically searched from inception through November 2023 for studies comparing stapler versus suture closure for fistula outcomes after laryngectomy. Odds ratios (OR) were pooled using random-effects models and fixed-effects models. Subgroup and sensitivity analyses were performed. Risk of bias was appraised using NHLBI tools. Nine studies with 803 patients were included. Mechanical closure significantly reduced fistula incidence versus suture closure (OR = 0.57, 95% CI 0.34-0.95, p = 0.03). Subgroup analysis found that stapling's protective effect varied by patient age, country/region, linear stapler size and female percentage. Stapling reduced fistula odds by 80% in the Turkey subgroup (OR = 0.20, 95% CI 0.09-0.50) but showed no benefit in other regions. Patients <60 years showed an 84% fistula reduction with stapling (OR = 0.17, 95% CI 0.06-0.45), whereas older subgroups did not. Linear stapler size of 60 mm significantly reduced fistula occurrence while 75 mm did not. There was no evidence that low female percentage mitigated stapling benefits. Mechanical stapler closure after total laryngectomy meaningfully reduces the likelihood of postoperative PCF formation compared to hand-sewn closure, especially for patients younger than 60 years old. The absolute risk reduction supports its utility to prevent this complication.

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This article aims to address the challenge of predicting the salaries of college graduates, a subject of significant practical value in the fields of human resources and career planning. Traditional prediction models often overlook diverse influencing factors and complex data distributions, limiting the accuracy and reliability of their predictions. Against this backdrop, we propose a novel prediction model that integrates maximum likelihood estimation (MLE), Jeffreys priors, Kullback-Leibler risk function, and Gaussian mixture models to optimize LSTM models in deep learning. Compared to existing research, our approach has multiple innovations: First, we successfully improve the model's predictive accuracy through the use of MLE. Second, we reduce the model's complexity and enhance its interpretability by applying Jeffreys priors. Lastly, we employ the Kullback-Leibler risk function for model selection and optimization, while the Gaussian mixture models further refine the capture of complex characteristics of salary distribution. To validate the effectiveness and robustness of our model, we conducted experiments on two different datasets. The results show significant improvements in prediction accuracy, model complexity, and risk performance. This study not only provides an efficient and reliable tool for predicting the salaries of college graduates but also offers robust theoretical and empirical foundations for future research in this field.

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Compliant strain sensors are crucial for soft robots' perception and autonomy. However, their deformable bodies and dynamic actuation pose challenges in predictive sensor manufacturing and long-term robustness. This necessitates accurate sensor modelling and well-controlled sensor structural changes under strain. Here, we present a computational sensor design featuring a programmed crack array within micro-crumples strategy. By controlling the user-defined structure, the sensing performance becomes highly tunable and can be accurately modelled by physical models. Moreover, they maintain robust responsiveness under various demanding conditions including noise interruptions (50% strain), intermittent cyclic loadings (100,000 cycles), and dynamic frequencies (0-23 Hz), satisfying soft robots of diverse scaling from macro to micro. Finally, machine intelligence is applied to a sensor-integrated origami robot, enabling robotic trajectory prediction (<4% error) and topographical altitude awareness (<10% error). This strategy holds promise for advancing soft robotic capabilities in exploration, rescue operations, and swarming behaviors in complex environments.

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BACKGROUND: Predicting the successful weaning of acute kidney injury (AKI) patients from renal replacement therapy (RRT) has emerged as a research focus, and we successfully built predictive models for RRT withdrawal in patients with severe AKI by machine learning. METHODS: This retrospective single-center study utilized data from our general intensive care unit (ICU) Database, focusing on patients diagnosed with severe AKI who underwent RRT. We evaluated RRT weaning success based on patients being free of RRT in the subsequent week and their overall survival. Multiple logistic regression (MLR) and machine learning algorithms were adopted to construct the prediction models. RESULTS: A total of 976 patients were included, with 349 patients successfully weaned off RRT. Longer RRT duration (7.0 vs. 9.6 d, p = 0.002, OR = 0.94), higher serum cystatin C levels (1.2 vs. 3.2 mg/L, p < 0.001, OR = 0.46), and the presence of septic shock (28.1% vs. 41.5%, p < 0.001, OR = 0.63) were associated with reduced likelihood of RRT weaning. Conversely, a positive furosemide stress test (FST) (60.2% vs. 40.7%, p < 0.001, OR = 2.75) and higher total urine volume 3 d before RRT withdrawal (755 vs. 125 mL/d, p < 0.001, OR = 2.12) were associated with an increased likelihood of successful weaning from RRT. Next, we demonstrated that machine learning models, especially Random Forest and XGBoost, achieving an AUROC of 0.95. The XGBoost model exhibited superior accuracy, yielding an AUROC of 0.849. CONCLUSION: High-risk factors for unsuccessful RRT weaning in severe AKI patients include prolonged RRT duration. Machine learning prediction models, when compared to models based on multivariate logistic regression using these indicators, offer distinct advantages in predictive accuracy.

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Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to analyze what knowledge humans have about verbs. Thus, several verb feature datasets have been developed in different languages such as English, Spanish, and German. However, there is still a lack of a dataset of Chinese verbs. In this study, we developed a semantic feature dataset of 1140 Chinese Mandarin verbs (CVFD) with 11 dimensions including verb familiarity, agentive subject, patient, action effector, perceptual modality, instrumentality, emotional valence, action imageability, action complexity, action intensity, and the usage scenario of action. We calculated the semantic features of each verb and the correlation between dimensions. We also compared the difference between action, mental, and other verbs and gave some examples about how to use CVFD to classify verbs according to different dimensions. Finally, we discussed the potential applications of CVFD in the fields of neuroscience, psycholinguistics, cultural differences, and artificial intelligence. All the data can be found at https://osf.io/pv29z/ .

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BACKGROUND: Diabetes has become a prominent global public health problem, which is an important cause of death, disease burden, and medical and health economic burden. Previous studies have reported that majority of persons diagnosed with diabetes later presented with psychological and mental health diseases. The study aimed to explore the mediation role of anxiety on social support and depression among diabetic patents in elderly caring social organizations (SOs). METHODS: A multi-stage stratified cluster random sampling method was used in this cross-sectional study, and a questionnaire consisting of demographic questionnaire, MSPSS, GAD-7, and CES-D-10 was utilized to gather data. SPSS 22.0 and MPLUS 7.4 were used for statistical analysis. Spearman correlation analysis was employed to investigate correlations of key variables. A generalized linear model was used to exam factors associated with depression. Finally, the mediation effect among study variables was investigated by structural equation modeling (SEM). RESULTS: The average scores of social support, anxiety, and depression were 58.41 ± 14.67, 2.95 ± 3.95, and 7.24 ± 5.53, respectively. The factors of gender, social support, and anxiety were identified as significantly influential factors related to depression among diabetic patients in elderly caring SOs. The effect of social support on depression was significantly mediated by anxiety (ß = -0.467, 95%CI: -0.813 to -0.251). Furthermore, anxiety partially mediated the relationship between family support and depression (ß = -0.112, 95%CI: -0.229 to -0.012), and anxiety functioned as a complete mediator in the effect of significant others' support and depression (ß = -0.135, 95%CI: -0.282 to -0.024). CONCLUSIONS: The indirect effect of social support on depression through anxiety among diabetic patients in elderly caring SOs was elucidated. Social support played a key role in maintaining and regulating their mental health, particularly from family and significant others. Social support provided by both family and significant others exerted an important influence on maintaining and regulating their mental health. In light of this pathway, the elderly caring SOs should enhance the magnitude of social support from these two sources, thereby diminishing the likelihood of experiencing anxiety and depression.

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Based on in-situ measurement of black carbon (BC) and carbon monoxide (CO), the characteristics of BC emissions and wet scavenging were comprehensively investigated in Nanning, South China. The average annual BC concentration was 1.02 ± 0.53 µg m-3 with higher pollution levels during winter. In winter, a higher net BC/CO (ΔBC/ΔCO) ratio of 3.3 ± 0.3 ng m-3 ppb-1 along with an increased absorption Ångström exponent (AAE) and BC mass from biomass burning (BCbb), indicated a significant contribution of biomass burning to BC emissions. However, emissions from the traffic sector consistently exerted a dominant influence throughout the year. Cluster analysis of backward trajectories identified three types of air masses with distinct origins. Cluster #1 originated from Guangxi province and its vicinity, intermittently influencing the sampling site throughout the year with varying effects between winter and summer. This air mass brought in clean sea breeze in summer whereas transported a higher proportion of BCbb to the site during wintertime due to local open biomass burning. Cluster #3 primarily arrived in autumn and winter (October-December) from polluted central China, resulting in substantially high BC mass at the site. Cluster #2 coincided with the period (January-March) when extensive surface open biomass burning events occurred in Southeast Asia (SEA) regions. These BC aerosols in cluster#2 initially rose to higher altitudes above SEA before being regionally transported, but were significantly scavenged by clouds and precipitation during vertical uplift. The remaining BC exhibited a notably lower BC loss rate on relative humidity (RH) of -0.01 ng m-3 ppb-1 %-1 compared to cluster #1 (-0.03) and cluster #3 (-0.06), corresponding to an average BC transport efficiency of 0.85, 0.73, and 0.53, respectively. Nonetheless, air masses in cluster #2 could still transport considerably high BC mass to Nanning due to dry conditions and less wet scavenging along trajectory pathways. These findings provide valuable insights for policymakers and government officials in regulating and mitigating BC pollution in South China.

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Lower back injuries are the most common work-related musculoskeletal disorders. As a wearable device, a back-support exoskeleton (BSE) can reduce the risk of lower back injuries and passive BSEs can achieve a low device weight. However, with current passive BSEs, there is a problem that the user must push against the device when lifting the leg to walk, which is perceived as particularly uncomfortable due to the resistance. To solve this problem, we propose a novel passive BSE that can automatically distinguish between lifting and walking. A unique spring-cable-differential acts as a torque generator to drive both hip joints, providing adequate assistive torque during lifting and low resistance during walking. The optimization of parameters can accommodate the asymmetry of human gait. In addition, the assistive torque on both sides of the user is always the same to ensure the balance of forces. By using a cable to transmit the spring force, we placed the torque generator on the person's back to reduce the weight on the legs. To test the effectiveness of the device, we performed a series of simulated lifting tasks and walking trials. When lifting a load of 10 kg in a squatting and stooping position, the device was able to reduce the activation of the erector spinae muscles by up to 41%. No significant change in the activation of the leg and back muscles was detected during walking.

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The immune system is divided into two broad categories, consisting of innate and adaptive immunity. As recognition and effector factors of innate immunity and regulators of adaptive immune responses, lectins are considered to be important defense chemicals against microbial pathogens, cell trafficking, immune regulation, and prevention of autoimmunity. Pentraxins, important members of animal lectins, play a significant role in protecting the body from pathogen infection and regulating inflammatory reactions. They can recognize and bind to a variety of ligands, including carbohydrates, lipids, proteins, nucleic acids and their complexes, and protect the host from pathogen invasion by activating the complement cascade and Fcγ receptor pathways. Based on the primary structure of the subunit, pentraxins are divided into short and long pentraxins. The short pentraxins are comprised of C-reactive protein (CRP) and serum amyloid P (SAP), and the most important member of the long pentraxins is pentraxin 3 (PTX3). The CRP and SAP exist in both vertebrates and invertebrates, while the PTX3 may be present only in vertebrates. The major ligands and functions of CRP, SAP and PTX3 and three activation pathways involved in the complement system are summarized in this review. Their different characteristics in various animals including humans, and their evolutionary trees are analyzed. The clinical applications of CRP, SAP and PTX3 in human are reviewed. Some questions that remain to be understood are also highlighted.

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BACKGROUND: Aging has given birth to the demand for high-quality elderly care service and social organizations (ESOs) are gradually taking on a supportive role in the field of elderly care services.. In view of this, our study is designed to examine influencing factors of social capital within the elderly-caring social organizations. METHOD: The study was conducted in four districts of Chongqing Province and a multi-stage random sampling method was used to sample 80 ESOs as subjects for the research. Through a meticulously crafted questionnaire, we gathered valuable data on internal social capital, basic information about the organization, and other variables. Univariate and Binary Logistic Regression analysis were performed on the data to explore the factors associated with social capital within the elderly-caring social organizations using IBM SPSS version 26.0. RESULT: The results showed that 67(83.8%) OF ESOs surveyed were A-type institutions and 13(16.3%) B-type institutions. Among them, 49(61.3%) institutions covered an area of more than 50m2.The institutions of ≤ 2 years were 33(41.3%), 21(26.3%) were established for ≤ 3 ≤ 8 years, and residual 26(32.5%) were institutions ˃ 8 years old. ESOs that possessed 4-6 management employees were 52.422 times more likely to score high for social support (p<0.05, OR = 52.422). Accommodating special care objects and hiring 16-30 employees were significantly linked to the shared language and shared vision dimension (p<0.001, OR = 0.8) and (p<0.05, OR = 8.672), respectively. and the overall social capital dimension (p<0.01, OR = 0.221) (p<0.05, OR = 5.730). CONCLUSION: ESOs with different basic conditions have different amounts of social capital. Factors such as the presence of special care and volunteer staff, a certain number of full-time staff as well as types of services rendered are accompanied with the higher internal social capital of ESOs.

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RNA helicases participate in nearly all aspects of RNA metabolism by rearranging RNAs or RNA-protein complexes in an adenosine triphosphate-dependent manner. Due to the large RNA helicase families in plants, the precise roles of many RNA helicases in plant physiology and development remain to be clarified. Here, we show that mutations in maize (Zea mays) DEAD-box RNA helicase 48 (ZmRH48) impair the splicing of mitochondrial introns, mitochondrial complex biosynthesis, and seed development. Loss of ZmRH48 function severely arrested embryogenesis and endosperm development, leading to defective kernel formation. ZmRH48 is targeted to mitochondria, where its deficiency dramatically reduced the splicing efficiency of five cis-introns (nad5 intron 1; nad7 introns 1, 2, and 3; and ccmFc intron 1) and one trans-intron (nad2 intron 2), leading to lower levels of mitochondrial complexes I and III. ZmRH48 interacts with two unique pentatricopeptide repeat (PPR) proteins, PPR-SMR1 and SPR2, which are required for the splicing of over half of all mitochondrial introns. PPR-SMR1 interacts with SPR2, and both proteins interact with P-type PPR proteins and Zm-mCSF1 to facilitate intron splicing. These results suggest that ZmRH48 is likely a component of a splicing complex and is critical for mitochondrial complex biosynthesis and seed development.

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BACKGROUND: With the deepening of China's aging population, higher demands have been placed on the supply of elderly care services. As one of the main sources of providing elderly care services, the quality of service provided by elderly caring social organizations (SOs) directly affects the quality of life of the elderly. In recent years, mental health issues among the elderly have become increasingly prominent, especially with the onset of the COVID-19 pandemic. Necessitating the need to pay much more attention to the social support and mental health of this population. This study, therefore, explores the mediating role of institutional satisfaction between the social support and anxiety levels of elderly people in Chongqing's elderly caring SOs. METHOD: This study employed a multi-stage stratified random sampling method to survey 1004 service recipients in elderly caring social organizations from July to August 2022. The self-made sociodemographic questionnaire, institutional satisfaction questionnaire, MSPSS, and GAD-7 were used to collect data on sociodemographic characteristics, institutional satisfaction, social support, and anxiety levels of older adults. Exploratory Factor Analysis and Cronbach's alpha were used to test construct validity and scale reliability, respectively. Data features were described with One-Way Analysis of Variance, while Multiple Linear Regression and Structural Equation Modeling were used to evaluate relationships between social support, institutional satisfaction, and anxiety levels. RESULTS: The average institutional satisfaction score for elderly people in elderly caring SOs was 48.14 ± 6.75. Specifically, the satisfaction score for environmental quality and the satisfaction score for service quality were 16.63 ± 2.56 and 31.52 ± 4.76, respectively. In terms of socio-demographic variables, the presence of visits from relatives, personal annual average income, and self-rated health status all have significant effects on anxiety. Elders who receive visits from relatives have lower levels of anxiety compared to those who do not. Personal annual average income and self-rated health status are negatively correlated with anxiety levels. Social support had significant positive effect on institutional satisfaction, while institutional satisfaction had significant negative effect on anxiety. Institutional satisfaction partially mediated the relationship between social support and anxiety. CONCLUSIONS: Our research demonstrates that improving the quality of organizational services in elderly caring SOs and increasing institutional satisfaction among the elders has significant potential for reducing anxiety levels among the elderly. Additionally, the social support by visits from family members cannot be overlooked. We encourage increasing the frequency of family visits through various means to enhance the support provided to elderly individuals.

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