Raising sons or daughters for old age? Influence of children's gender on intergenerational family support in rural families

Background: Under the background of miniaturization of family size and a growing number of young and middle-aged population outflow in rural China, the study of family pension mechanism in rural China from the perspective of changes in the pension functions of son and daughter will not only help to deepen the understanding of the change rules of China's family system, but also provide important reference for the future design of rural pension system. Data and method: The data come from the China Family Tracking Survey (CFPS), a nationwide social survey project runs by the Social Science Research Centre of Peking University. After excluding missing data, we obtained a valid sample of 11,207 sons and 2028 daughters in four data periods. We applied a fixed effects model for the analysis. Results: In rural areas, sons mainly provide economic support, while daughters mainly provide life care, thus forming a gender-based division of labor. With increasing off-farm job opportunities for daughters, they provide more economic support for their parents, but the time they spend on housework for their parents is reduced. As the number of children in a family has increased, daughters' role in supporting their parents has decreased. This research shows that although the traditional son-centered pension mode in China has not completely disintegrated, it has changed significantly. The findings reveal that changes in family size and improvements in women's status are important factors in changing family support patterns. Discussion: Different from the thought research about intergenerational relationship for a whole model, this article from the family internal different subjects role identity, shows the characteristics of the individual in the family, is conducive to theoretically explore the tension in the intergenerational relationship, individual and family which is helpful to understand the contemporary China's rural family generation ethics and intergenerational solidarity model. Families are classified more carefully according to the number, size and gender of children in the family, so as to fully show the heterogeneity and complexity of intergenerational relationships and old-age care models in rural families with different structural types. The discussion of the above issues has refined the description of rural family pension resources in China, which has certain reference significance for improving rural pension policies and actively dealing with the aging population

Disease-Aging Network Reveals Significant Roles of Aging Genes in Connecting Genetic Diseases

One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system–based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases

Inferring a protein interaction map of Mycobacterium tuberculosis based on sequences and interologs

Background: Mycobacterium tuberculosis is an infectious bacterium posing serious threats to human health. Due to the difficulty in performing molecular biology experiments to detect protein interactions, reconstruction of a protein interaction map of M. tuberculosis by computational methods will provide crucial information to understand the biological processes in the pathogenic microorganism, as well as provide the framework upon which new therapeutic approaches can be developed.Results: In this paper, we constructed an integrated M. tuberculosis protein interaction network by machine learning and ortholog-based methods. Firstly, we built a support vector machine (SVM) method to infer the protein interactions of M. tuberculosis H37Rv by gene sequence information. We tested our predictors in Escherichia coli and mapped the genetic codon features underlying its protein interactions to M. tuberculosis. Moreover, the documented interactions of 14 other species were mapped to the interactome of M. tuberculosis by the interolog method. The ensemble protein interactions were validated by various functional relationships, i.e., gene coexpression, evolutionary relationship and functional similarity, extracted from heterogeneous data sources. The accuracy and validation demonstrate the effectiveness and efficiency of our framework.Conclusions: A protein interaction map of M. tuberculosis is inferred from genetic codons and interologs. The prediction accuracy and numerically experimental validation demonstrate the effectiveness and efficiency of our method. Furthermore, our methods can be straightforwardly extended to infer the protein interactions of other bacterial species. © 2012 Liu et al.; licensee BioMed Central Ltd.Link_to_subscribed_fulltex

Características clínico-epidemiológicas de pacientes hipertensos en un Consultorio Médico de Santa Clara

High blood pressure is a chronic non-transmittable disease, which is also a risk factor for the development of other clinical conditions. The incidence of arterial hypertension in the Cuban population is high.Aim: to characterize the evolution of arterial hypertension in a Family Doctor's Office.Methods: an observational, descriptive and cross-sectional study was carried out at the Family Doctor's Office 17-19 in the municipality of Santa Clara. The study covered the months of January to March 2020. Of the 256 hypertensive patients, a sample of 52 was selected by a simple random method.Results: Males predominated (53.84 %), together with the age group between 40 and 49 years (28.84 %). A total of 63.46 % of the patients were white-skinned. 51.61% presented risk factors. The risk factors with the highest incidence were smoking, followed by obesity and sedentary lifestyle.Conclusions: the most affected hypertensive patients are male. Most patients have a family history of high blood pressure. Smoking is a high incidence risk factor in the hypertensive population.Introducción: la hipertensión arterial es una enfermedad crónica no transmisible, que a la vez constituye un factor de riesgo para el desarrollo de otras enfermedades. La incidencia de la hipertensión arterial en la población de Cuba es alta.Objetivo: caracterizar el comportamiento de la hipertensión arterial en un Consultorio Médico de Familia.Métodos: se realizó un estudio observacional, descriptivo y transversal en el Consultorio Médico de Familia 17-19 del municipio Santa Clara. El período de estudio comprendió los meses de enero a marzo del 2020. La población fue de 256 hipertensos y se escogió una muestra de 52 hipertensos por muestreo aleatorio simple.Resultados: predominó el sexo masculino (53,84 %), y el grupo de edad entre 40 y 49 años (28,84 %). El 63,46 % de los pacientes fueron de color de la piel blanca. El 51,61 % presentaron factores de riesgo. Los factores de riesgo de mayor incidencia fueron el tabaquismo, seguido por la obesidad y el sedentarismo.Conclusiones: los pacientes hipertensos más afectados son los del sexo masculino. La mayor parte de los pacientes tienen antecedentes familiares de hipertensión arterial. El tabaquismo es un factor de riesgo de alta incidencia en la población hipertensa

Theoretical study of hyperfine structure constants of Ga isotopes

info:eu-repo/semantics/publishe

Addressing biodisaster X threats with artificial intelligence and 6G technologies:literature review and critical insights

Abstract Background: With advances in science and technology, biotechnology is becoming more accessible to people of all demographics. These advances inevitably hold the promise to improve personal and population well-being and welfare substantially. It is paradoxical that while greater access to biotechnology on a population level has many advantages, it may also increase the likelihood and frequency of biodisasters due to accidental or malicious use. Similar to “Disease X” (describing unknown naturally emerging pathogenic diseases with a pandemic potential), we term this unknown risk from biotechnologies “Biodisaster X.” To date, no studies have examined the potential role of information technologies in preventing and mitigating Biodisaster X. Objective: This study aimed to explore (1) what Biodisaster X might entail and (2) solutions that use artificial intelligence (AI) and emerging 6G technologies to help monitor and manage Biodisaster X threats. Methods: A review of the literature on applying AI and 6G technologies for monitoring and managing biodisasters was conducted on PubMed, using articles published from database inception through to November 16, 2020. Results: Our findings show that Biodisaster X has the potential to upend lives and livelihoods and destroy economies, essentially posing a looming risk for civilizations worldwide. To shed light on Biodisaster X threats, we detailed effective AI and 6G-enabled strategies, ranging from natural language processing to deep learning–based image analysis to address issues ranging from early Biodisaster X detection (eg, identification of suspicious behaviors), remote design and development of pharmaceuticals (eg, treatment development), and public health interventions (eg, reactive shelter-at-home mandate enforcement), as well as disaster recovery (eg, sentiment analysis of social media posts to shed light on the public’s feelings and readiness for recovery building). Conclusions: Biodisaster X is a looming but avoidable catastrophe. Considering the potential human and economic consequences Biodisaster X could cause, actions that can effectively monitor and manage Biodisaster X threats must be taken promptly and proactively. Rather than solely depending on overstretched professional attention of health experts and government officials, it is perhaps more cost-effective and practical to deploy technology-based solutions to prevent and control Biodisaster X threats. This study discusses what Biodisaster X could entail and emphasizes the importance of monitoring and managing Biodisaster X threats by AI techniques and 6G technologies. Future studies could explore how the convergence of AI and 6G systems may further advance the preparedness for high-impact, less likely events beyond Biodisaster X