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Irritant contact dermatitis (ICD) is a nonspecific skin inflammation caused by irritants, leading to itch and pain. We tested whether differential responses to histamine-dependent and -independent pruritogens can be evoked in ICD induced by sodium lauryl sulfate (SLS). An ICD mouse model was established with 5% SLS in acetone versus a vehicle topically applied for 24 h to the cheek. Site-directed itch- and pain-like behaviors, occurring spontaneously and in response to mechanical, thermal, and chemical stimuli (histamine, ß-alanine, BAM8-22, and bradykinin) applied to the cheek, were recorded before (day 0) and after irritant removal (days 1, 2, 3, and 4). Skin inflammation was assessed through visual scoring, ultrasound, and measurements of skin thickness. SLS-treated mice exhibited hyperalgesia-like behavior in response to mechanical and heat stimuli on day 1 compared to the controls. SLS mice exhibited more spontaneous wipes (pain) but not scratching bouts (itch) on day 1. Pruritogen injections caused more scratching but not wiping in SLS-treated mice compared to the controls. Only bradykinin increased wiping behavior compared to saline. SLS-treated mice developed noticeable erythema, scaling, and increased skin thickness on days 1 and 2. SLS induced cutaneous inflammation and behavioral signs of spontaneous pain and itching, hyperalgesia to mechanical and heat stimuli and a chemical algogen, and enhanced itch response to pruritogens. These sensory reactions preceded the inflammation peak and lasted up to two days.
Sujet(s)
Dermatite irritative , Modèles animaux de maladie humaine , Douleur , Prurit , Dodécyl-sulfate de sodium , Animaux , Dodécyl-sulfate de sodium/effets indésirables , Prurit/induit chimiquement , Souris , Dermatite irritative/étiologie , Dermatite irritative/anatomopathologie , Dermatite irritative/physiopathologie , Douleur/induit chimiquement , Douleur/physiopathologie , Mâle , Hyperalgésie/induit chimiquement , Peau/effets des médicaments et des substances chimiques , Peau/anatomopathologie , Peau/métabolisme , Histamine , Irritants/toxicité , Bradykinine/pharmacologie , Comportement animal/effets des médicaments et des substances chimiquesRÉSUMÉ
Objectively In objective terms, the return of rural labor force shortens the spatial distance with parents, leading to changes in caregiving support, emotional support, and financial support for parents, thereby affecting the health status of parents. This article, using data from the Chinese Family Panel Studies, analyzes the characteristics of the health status of parents with and without returning migrant children. By employing multiple linear regression models, PSM models, and IV-2SLS methods to address endogeneity bias, the study preliminarily explores the impact of rural labor force return on parental health. The results show that: (1) among the 5,760 older adult individuals, 1866 of them have returning migrant chil-dren, while the remaining 3,894 do not have returning migrant children. (2) Parents' health status generally follows a normal distribution, with a small proportion of parents having very poor or very good health. The proportions of parents with relatively poor, fair, and relatively good health status range between 20 and 40%. Among parents with returning chil-dren, 40.12% have relatively poor health status, 45.01% have fair health status, and a small proportion have very poor or very good health status. In contrast, among parents without returning children, the proportions of parents with relatively poor, fair, and rela-tively good health status are 21.69, 33.21, and 38.45%, respectively. When parents tran-sition from not having returning children to having returning children, their health status decreases by 0.541 levels, indicating a negative impact of rural labor force return on par-ents' health. Based on the analysis results, this article provides policy recommendations from three aspects: how to increase the income of returning labor force, improve the rural pension system, and enhance the concept of children supporting their parents.
Sujet(s)
État de santé , Parents , Population rurale , Humains , Chine , Parents/psychologie , Femelle , Population rurale/statistiques et données numériques , Mâle , Adulte d'âge moyen , Adulte , Population de passage et migrants/statistiques et données numériques , Reprise du travail/statistiques et données numériques , Emploi/statistiques et données numériques , Sujet âgéRÉSUMÉ
Schizophrenia is a psychiatric disorder that results from abnormal levels of neurotransmitters in the brain. Risperidone (RIS) is a common drug prescribed for the treatment of schizophrenia. RIS is a hydrophobic drug that is typically administered orally or intramuscularly. Transdermal drug delivery (TDD) could potentially improve the delivery of RIS. This study focused on the development of RIS nanocrystals (NCs), for the first time, which were incorporated into dissolving microneedle array patches (DMAPs) to facilitate the drug delivery of RIS. RIS NCs were formulated via wet-media milling technique using poly(vinylalcohol) (PVA) as a stabiliser. NCs with particle size of 300 nm were produced and showed an enhanced release profile up to 80 % over 28 days. Ex vivo results showed that 1.16 ± 0.04 mg of RIS was delivered to both the receiver compartment and full-thickness skin from NCs loaded DMAPs compared to 0.75 ± 0.07 mg from bulk RIS DMAPs. In an in vivo study conducted using female Sprague Dawley rats, both RIS and its active metabolite 9-hydroxyrisperidone (9-OH-RIS) were detected in plasma samples for 5 days. In comparison with the oral group, DMAPs improved the overall pharmacokinetic profile in plasma with a â¼ 15 folds higher area under the curve (AUC) value. This work has represented the novel delivery of the antipsychotic drug, RIS, through microneedles. It also offers substantial evidence to support the broader application of MAPs for the transdermal delivery of poorly water-soluble drugs.
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Administration par voie cutanée , Neuroleptiques , Rat Sprague-Dawley , Rispéridone , Schizophrénie , Animaux , Rispéridone/administration et posologie , Rispéridone/pharmacocinétique , Schizophrénie/traitement médicamenteux , Femelle , Neuroleptiques/administration et posologie , Neuroleptiques/pharmacocinétique , Patch transdermique , Nanoparticules/composition chimique , Nanoparticules/administration et posologie , Libération de médicament , Absorption cutanée , Rats , Systèmes de délivrance de médicaments , Peau/métabolisme , Poly(alcool vinylique)/composition chimique , Palmitate de palipéridone/administration et posologie , Palmitate de palipéridone/pharmacocinétique , Taille de particule , Solubilité , AiguillesRÉSUMÉ
With increasing demands for data transfer, the production of components with low dielectric loss is crucial for the development of advanced antennas, which are needed to meet the requirements of next-generation communication technologies. This study investigates the impact of a variation in energy density on the part properties of a low-loss cyclic olefin copolymer (COC) in the SLS process as a way to manufacture complex low-dielectric-loss structures. Through a systematic variation in the laser energy, its impact on the part density, geometric accuracy, surface quality, and dielectric properties of the fabricated parts is assessed. This study demonstrates notable improvements in material handling and the quality of the manufactured parts while also identifying areas for further enhancement, particularly in mitigating thermo-oxidative aging. This research not only underscores the potential of COC in the realm of additive manufacturing but also sets the stage for future studies aimed at optimizing process parameters and enhancing material formulations to overcome current limitations.
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In the scope of the latest upgrade of the Swiss Light Source, five hard X-ray beamlines will be constructed or rebuilt. To use synergies between these beamline projects, a concept is developed here for hard X-ray beamlines that is tailored to the new storage ring. Herein, this concept is described from the source, via the front end, to the beamline optics. The latter will be outlined in detail, including a new and modular concept for hard X-ray monochromators, focusing optics and heat-load management. With a simple, easy-to-operate and robust beamline design, the new beamlines will greatly profit from the increased brilliance of the new storage ring. The performance increase is up to four orders of magnitude, while the beamline concept allows for the broad application of experimental techniques, from propagation-based methods, such as phase-contrast tomography, to imaging techniques with nanometre resolution. At the same time, spectroscopy experiments are possible as well as high-performance serial X-ray crystallography.
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Leaf senescence is a complex process strictly regulated by various external and endogenous factors. However, the key signaling pathway mediating leaf senescence remains unknown. Here, we show that Arabidopsis SPX1/2 negatively regulate leaf senescence genetically downstream of the strigolactone (SL) pathway. We demonstrate that the SL receptor AtD14 and MAX2 mediate the age-dependent degradation of SPX1/2. Intriguingly, we uncover an age-dependent accumulation of SLs in leaves via transcriptional activation of SL biosynthetic genes by the transcription factors (TFs) SPL9/15. Furthermore, we reveal that SPX1/2 interact with the WRKY75 subclade TFs to inhibit their DNA-binding ability and thus repress transcriptional activation of salicylic acid (SA) biosynthetic gene SA Induction-Deficient 2, gating the age-dependent SA accumulation in leaves at the leaf senescence onset stage. Collectively, our new findings reveal a signaling pathway mediating sequential activation of SL and salicylate biosynthesis for the onset of leaf senescence in Arabidopsis.
Sujet(s)
Protéines d'Arabidopsis , Arabidopsis , Régulation de l'expression des gènes végétaux , Lactones , Feuilles de plante , Sénescence des plantes , Facteurs de transcription , Arabidopsis/génétique , Arabidopsis/métabolisme , Arabidopsis/effets des médicaments et des substances chimiques , Feuilles de plante/métabolisme , Feuilles de plante/effets des médicaments et des substances chimiques , Protéines d'Arabidopsis/métabolisme , Protéines d'Arabidopsis/génétique , Régulation de l'expression des gènes végétaux/effets des médicaments et des substances chimiques , Lactones/métabolisme , Facteurs de transcription/métabolisme , Facteurs de transcription/génétique , Acide salicylique/métabolisme , Salicylates/métabolisme , Transduction du signal , Liaison aux protéines/effets des médicaments et des substances chimiques , Protéolyse/effets des médicaments et des substances chimiques , Voies de biosynthèse/effets des médicaments et des substances chimiques , Voies de biosynthèse/génétiqueRÉSUMÉ
This research paper aims to explore the mechanical characteristics of polyamide PA12 (PA12) as a 3D material printed utilizing Selective Laser Sintering (SLS) and HP MultiJet Fusion (HP MJF) technologies in order to design and manufacture forearm orthoses. The study assessed the flowability of the materials used and compared the mechanical performance of PA12 with each other using tensile, flexure, and impact tests in five different fabrication orientations: X, Y, Z, tilted 45° XZ, and tilted 45° YZ. The results of the study provide, firstly-the data for testing the quality of the applied polyamide powder blend and, secondly-the data for the design of the orthosis geometry from the aspect of its strength parameters and the safety of construction. The mechanical parameters of SLS specimens had less variation than MJF specimens in a given orientation. The difference in tensile strength between the 3D printing technologies tested was 1.8%, and flexural strength was 4.7%. A process analysis of the forearm orthoses revealed that the HP MJF 5200 system had a higher weekly production capacity than the EOS P396 in a production variance based on obtaining maximum strength parameters and a variance based on maximizing economic efficiency. The results suggest that medical device manufacturers can use additive manufacturing technologies to produce prototypes and small-batch parts for medical applications. This paper pioneers using 3D printing technology with Powder Bed Fusion (PBF) methods in designing and manufacturing forearm orthoses as a low- to medium-volume product. The applied solution addresses the problem of medical device manufacturers with regard to the analysis of production costs and mechanical properties when using 3D printing for certified medical devices.
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Selective laser sintering (SLS) is one of the most well-regarded additive manufacturing (AM) sub-processes, whose popularity has been increasing among numerous critical and demanding industries due to its capabilities, mainly manufacturing parts with highly complex geometries and desirable mechanical properties, with potential to replace other, more expensive, conventional processes. However, due to its various underlying multi-physics phenomena, the intrinsic complexity of the SLS process often hampers its industrial implementation. Such limitation has motivated academic interest in obtaining better insights into the process to optimize it and attain the required standards. In that regard, the usual experimental optimization methods are time-consuming and expensive and can fail to provide the optimal configurations, leading researchers to resort to computational modeling to better understand the process. The main objective of the present work is to develop a computational model capable of simulating the SLS process for polymeric applications, within an open-source framework, at a particle-length scale to assess the main process parameters' impact. Following previous developments, virgin and used polymer granules with different viscosities are implemented to better represent the actual process feedstock. The results obtained agree with the available experimental data, leading to a powerful tool to study, in greater detail, the SLS process and its physical parameters and material properties, contributing to its optimization.
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In Ghana, malaria remains the number 1 reason for outpatient department visits, making it a major public health problem. Thus, there could be significant lost productivity days as a result of malaria morbidity and mortality, which could negatively affect economic output at the macrolevel. Nonetheless, there is a dearth of empirical evidence of the effect of malaria on macroeconomic output in Ghana. This study therefore aims to provide the foremost empirical evidence regarding the effect of malaria prevalence on macroeconomic output in Ghana using a time series design with data spanning the period 1990 to 2019. Gross Domestic Product (GDP), serving as a proxy for macroeconomic output, is the dependent variable, while the prevalence of malaria (overall, among only males and among only females) serves as the main independent variable. The Ordinary Least Square (OLS) regression is used as the baseline estimation technique and the Instrumental Variable Two-Stage Least Square (IV2SLS) regression is employed as the robustness check estimator due to its ability to deal with endogeneity. The IV2SLS regression results show that a percentage increase in the overall prevalence of malaria is associated with a 1.16% decrease in macroeconomic output at 1% significance level. We also find that the effect of malaria in males on macroeconomic output is slightly higher relative to females. The findings from the OLS regression are not qualitatively different from the IV2SLS regression estimates. There is therefore the need to strengthen efforts such as quality case management, larval source management, mass distribution of long-lasting insecticide-treated bed nets, social behavior change, surveillance (both epidemiological and entomological), intermittent preventive treatment of malaria in pregnancy, research among others, which are important toward eliminating malaria.
Sujet(s)
Paludisme , Humains , Ghana/épidémiologie , Paludisme/épidémiologie , Prévalence , Femelle , Mâle , Produit intérieur brut/statistiques et données numériques , Facteurs sexuelsRÉSUMÉ
This study delves into the mechanical characteristics of polyamide PA2200 components crafted using selective laser sintering (SLS) technology. Our primary objective is to analyze the tensile behavior of the components printed at various orientations, showing its response to diverse loading conditions. Finite element method (FEM) modeling was employed to analyze the tensile behavior of these details. The time determined for breaking the detail is 9 s. In addition we forecast key properties, such as tensile behavior and strength, using machine learning (ML) techniques, and the best models are for predicting relative elongation are KNeighborsRegressor and SVR.
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Different microscopy and scattering methods used in the literature to determine the dimensions of cellulose nanocrystals derived from cotton and bacterial cellulose were compared to investigate potential bias and discrepancies. Atomic force microscopy (AFM), small-angle X-ray scattering (SAXS), depolarized dynamic light scattering (DDLS), and static light scattering (SLS) were compared. The lengths, widths, and heights of the particles and their respective distributions were determined by AFM. In agreement with previous work, the CNCs were found to have a ribbon-like shape, regardless of the source of cellulose or the surface functional groups. Tip broadening and agglomeration of the particles during deposition cause AFM-derived lateral dimensions to be systematically larger those obtained from SAXS measurements. The radius of gyration determined by SLS showed a good correlation with the dimensions obtained by AFM. The hydrodynamic lateral dimensions determined by DDLS were found to have the same magnitude as either the width or height obtained from the other techniques; however, the precision of DDLS was limited due to the mismatch between the cylindrical model and the actual shape of the CNCs, and to constraints in the fitting procedure. Therefore, the combination of AFM and SAXS, or microscopy and small-angle scattering, is recommended for the most accurate determination of CNC dimensions.
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Applied researchers often confront two issues when using the fixed effect-two-stage least squares (FE-2SLS) estimator for panel data models. One is that it may lose its consistency due to too many instruments. The other is that the gain of using FE-2SLS may not exceed its loss when the endogeneity is weak. In this paper, an L2Boosting regularization procedure for panel data models is proposed to tackle the many instruments issue. We then construct a Stein-like model-averaging estimator to take advantage of FE and FE-2SLS-Boosting estimators. Finite sample properties are examined in Monte Carlo and an empirical application is presented.
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Three-dimensional printing (3DP) has gained popularity among scientists and researchers in every field due to its potential to drastically reduce energy costs for the production of customised products by utilising less energy-intensive machines as well as minimising material waste. The 3D printing technology is an additive manufacturing approach that uses material layer-by-layer fabrication to produce the digitally specified 3D model. The use of 3D printing technology in the pharmaceutical sector has the potential to revolutionise research and development by providing a quick and easy means to manufacture personalised one-off batches, each with unique dosages, distinct substances, shapes, and sizes, as well as variable release rates. This overview addresses the concept of 3D printing, its evolution, and its operation, as well as the most popular types of 3D printing processes utilised in the health care industry. It also discusses the application of these cutting-edge technologies to the pharmaceutical industry, advancements in various medical fields and medical equipment, 3D bioprinting, the most recent initiatives to combat COVID-19, regulatory frameworks, and the major challenges that this technology currently faces. In addition, we attempt to provide some futuristic approaches to 3DP applications.
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Transcriptome-wide association studies (TWAS) have been increasingly applied to identify (putative) causal genes for complex traits and diseases. TWAS can be regarded as a two-sample two-stage least squares method for instrumental variable (IV) regression for causal inference. The standard TWAS (called TWAS-L) only considers a linear relationship between a gene's expression and a trait in stage 2, which may lose statistical power when not true. Recently, an extension of TWAS (called TWAS-LQ) considers both the linear and quadratic effects of a gene on a trait, which however is not flexible enough due to its parametric nature and may be low powered for nonquadratic nonlinear effects. On the other hand, a deep learning (DL) approach, called DeepIV, has been proposed to nonparametrically model a nonlinear effect in IV regression. However, it is both slow and unstable due to the ill-posed inverse problem of solving an integral equation with Monte Carlo approximations. Furthermore, in the original DeepIV approach, statistical inference, that is, hypothesis testing, was not studied. Here, we propose a novel DL approach, called DeLIVR, to overcome the major drawbacks of DeepIV, by estimating a related but different target function and including a hypothesis testing framework. We show through simulations that DeLIVR was both faster and more stable than DeepIV. We applied both parametric and DL approaches to the GTEx and UK Biobank data, showcasing that DeLIVR detected additional 8 and 7 genes nonlinearly associated with high-density lipoprotein (HDL) cholesterol and low-density lipoprotein (LDL) cholesterol, respectively, all of which would be missed by TWAS-L, TWAS-LQ, and DeepIV; these genes include BUD13 associated with HDL, SLC44A2 and GMIP with LDL, all supported by previous studies.
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Apprentissage profond , Transcriptome , Humains , Locus de caractère quantitatif , Phénotype , Étude d'association pangénomique/méthodes , Cholestérol , Prédisposition génétique à une maladie , Polymorphisme de nucléotide simpleRÉSUMÉ
This article examines the effect of information and communication technologies (ICT) and democracy on early child health using data from 51 African countries. We first specify and estimate a panel data model using ordinary least squares and two-stage least squares over the period 2001-2019. We apply the Hodrick-Prescott filter before analysis. Our results show that the extension of mobile phone use significantly contributes to the improvement of early child health in Africa. This effect is indifferent to the state or the level of democracy. Also, the internet diffusion plays a positive role in early child health when the democracy environment improves and becomes better. We suggest policies in favour of a large access to ICT tools and internet infrastructure as well as the promotion of democracy in Africa to better prevent infant mortality.
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Santé de l'enfant , Démocratie , Nourrisson , Enfant , Humains , Afrique , Communication , Mortalité infantileRÉSUMÉ
Recently, piezoresistive sensors made by 3D printing have gained considerable interest in the field of wearable electronics due to their ultralight nature, high compressibility, robustness, and excellent electromechanical properties. In this work, building on previous results on the Selective Laser Sintering (SLS) of porous systems based on thermoplastic polyurethane (TPU) and graphene (GE)/carbon nanotubes (MWCNT) as carbon conductive fillers, the effect of variables such as thickness, diameter, and porosity of 3D printed disks is thoroughly studied with the aim of optimizing their piezoresistive performance. The resulting system is a disk with a diameter of 13 mm and a thickness of 0.3 mm endowed with optimal reproducibility, sensitivity, and linearity of the electrical signal. Dynamic compressive strength tests conducted on the proposed 3D printed sensors reveal a linear piezoresistive response in the range of 0.1-2 N compressive load. In addition, the optimized system is characterized at a high load frequency (2 Hz), and the stability and sensitivity of the electrical signal are evaluated. Finally, an application test demonstrates the ability of this system to be used as a real-time wearable pressure sensor for applications in prosthetics, consumer products, and personalized health-monitoring systems.
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Transcriptome-wide association studies (TWAS) have recently emerged as a popular tool to discover (putative) causal genes by integrating an outcome GWAS dataset with another gene expression/transcriptome GWAS (called eQTL) dataset. In our motivating and target application, we'd like to identify causal genes for low-density lipoprotein cholesterol (LDL), which is crucial for developing new treatments for hyperlipidemia and cardiovascular diseases. The statistical principle underlying TWAS is (two-sample) two-stage least squares (2SLS) using multiple correlated SNPs as instrumental variables (IVs); it is closely related to typical (two-sample) Mendelian randomization (MR) using independent SNPs as IVs, which is expected to be impractical and lower-powered for TWAS (and some other) applications. However, often some of the SNPs used may not be valid IVs, e.g. due to the widespread pleiotropy of their direct effects on the outcome not mediated through the gene of interest, leading to false conclusions by TWAS (or MR). Building on recent advances in sparse regression, we propose a robust and efficient inferential method to account for both hidden confounding and some invalid IVs via two-stage constrained maximum likelihood (2ScML), an extension of 2SLS. We first develop the proposed method with individual-level data, then extend it both theoretically and computationally to GWAS summary data for the most popular two-sample TWAS design, to which almost all existing robust IV regression methods are however not applicable. We show that the proposed method achieves asymptotically valid statistical inference on causal effects, demonstrating its wider applicability and superior finite-sample performance over the standard 2SLS/TWAS (and MR). We apply the methods to identify putative causal genes for LDL by integrating large-scale lipid GWAS summary data with eQTL data.
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Fiscal decentralization, widely believed to be one essential tool to boost economic growth, is typically presented as something that works for developed countries. However, this needs to be investigated, which is what this paper aims to do. This paper investigates the relationship between fiscal decentralization and economic growth, specifically focusing on its applicability in both developed and developing countries. Using cross-sectional data from 23 African and 23 OECD countries, we employ two-stage estimation methods, including two-stage least squares (2SLS), Generalized Method of Moments (GMM), and Limited Information Maximum Likelihood (LIML), to address concerns related to endogeneity. The inclusion of instruments representing country size, ethnoreligious diversity, and administrative structure enhances the analysis. The dependent variable is based on average values for the five-year period between 2015 and 2019, while the explanatory variables are derived from data in 2017, representing the midpoint of the 2013-2021 period. The results highlight the effectiveness of the 2SLS method in estimating the relationship between fiscal decentralization, control variables, instrument variables, and per capita GDP. Empirical findings indicate significant positive impacts of both expenditure decentralization and revenue decentralization on per capita GDP, holding true for both developed and developing countries, with a slightly stronger effect observed in the latter. These results underscore the potential benefits of fiscal decentralization across diverse economies and offer valuable insights for policymakers. The study uses cross-sectional data from 23 African and 23 OECD countries and applies two-stage estimation methods to effectively address the endogeneity issue in the modeling. A variety of such methods in two-stage least squares (2SLS), Generalized Method of Moments (GMM), and Limited Information Maximum Likelihood (LIML) are applied and compared against the ordinary least squares (OLS) method. Variables that represent the size, the ethnoreligious diversity and the type of administrative structure of the countries are employed as instruments. The 2SLS method proved to excellently estimate the relationship between the fiscal decentralization terms as well as other control and instrument variables and the per capita GDP. The findings from the empirical analysis showed that both expenditure decentralization and revenue decentralization have significant positive impacts on per capita GDP of a country. This relationship holds not only for developed countries but also for developing ones, even to a slightly better degree in the latter.
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Flexible structures are increasingly important in biomedical applications, where they can be used to achieve adaptable designs. This paper presents a study of the design and behavior of 3D-printed lightweight flexible structures. In this work, we focus on the design principles and numerical modelling of spatial patterns, as well as their mechanical properties and behavior under various loads. Contact surface fraction was determined as the ratio of the surface area of the printed pattern to the surface area of the entire curved surface. The objective of this work is to design a spatial pattern reducing contact surface fraction and develop a non-linear numerical model evaluating the structure's stiffness; in addition, we aimed to identify the best design pattern with respect to its stiffness:mass ratio. The experimental verification of the numerical model is performed on 3D-printed prototypes prepared using the Selective Laser Sintering (SLS) method and made of Nylon-Polyamide 12. The obtained results provide insights into designing and optimizing lightweight external biomedical applications such as prostheses, orthoses, helmets, or adaptive cushions.
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Background: The rapid population aging in China, characterized by a higher prevalence of illnesses, earlier onset of diseases, and longer durations of living with ailments, substantially engenders challenges within the domain of older adults' healthcare. Community home-based elderly care services (CHECS) are a feasible solution to solve the problem of older adults' care and protect older adults' health. The aim of this study is to investigate the relationship, heterogeneity effects and influential mechanisms between older adults' use of CHECS and their self- reported health. Methods: The study employs the Instrumental Variable technique and empirically investigates the relationship, heterogeneity effects and influential mechanisms between older adults using CHECS and their self-reported health using data from the China Longitudinal Aging Social Survey from 2018. Results: The findings indicate, firstly, that using CHECS considerably improves older adults' self-reported health. Secondly, the heterogeneity test reveals that the effect is more pronounced for older adults who are under the age of 80, have functional disabilities, are free of chronic diseases, have never attended school, reside in lower-income households, are single, rarely interact with their children, and live in central urban or city/county regions. Thirdly, the mechanism test reveals that the "social network effect" and "family care effect" are the key influence channels of using CHECS. Conclusion: An empirical foundation for the policy reform of community home-based care for seniors is provided by this study with the limitations to discuss the other socioeconomic aspects such as government health expenditure and discuss the specific services aspects such as health care. The findings carry substantial implications for improving the health of older individuals and provide suggestions for establishing a socialized aged care system in China.