The immunosenescence and lipotoxicity in thyrotoxicosis mice

COVID-19 is a worldwide outbreak now, and it is found to be age-related. Immunosenescence may be a predisposing and severe factor for COVID-19. Besides, many infectious diseases in clinic are age-related, and elderly patients have longer hospitalization and worse prognosis. Therefore, finding suitable aging models is of great significance for fighting aging related diseases and promoting the prognosis of elderly patients. In this study, the relationship between thyrotoxicosis and aging was investigated by routine detection and serum metabonomics in mice. The results of routine blood test and flow cytometry showed significant decrease in neutrophils, lymphocytes, CD4+/CD8+ and CD4+IFN-γ + lymphocytes in thyrotoxicosis mice. Biochemical examination combined with serum metabolomics analysis showed that serious disorder of lipid metabolism may be one of the causes of immunosenescence, including lower cholesterol levels, lower levels of VD and bile acids, high level of glucocorticoids, triglycerides, free fatty acids, Sphingolipids and decrease of Docosanoids, especially DPA. This study proves that thyrotoxicosis mice are an accelerated aging model. In present study, the main performance is immunosenescence, which may be due to lipotoxicity, suggesting that the immunosenescence state can be adjusted by improving lipotoxicity, whether anti thyroxine or not. However, there are other manifestations of thyroid toxicity mouse model simulating aging, such as organ aging, which need to continue to be studied by means of system biology to provide more comprehensive evidence.

Physiological Ovarian Aging Is Associated with Altered Expression of Post-Translational Modifications in Mice

Post-translational modifications (PTMs) have been confirmed to be involved in multiple female reproductive events, but their role in physiological ovarian aging is far from elucidated. In this study, mice aged 3, 12 or 17 months (3M, 12M, 17M) were selected as physiological ovarian aging models. The expression of female reproductive function-related genes, the global profiles of PTMs, and the level of histone modifications and related regulatory enzymes were examined during physiological ovarian aging in the mice by quantitative real-time PCR and western blot, respectively. The results showed that the global protein expression of Kbhb (lysineβ-hydroxybutyryllysine), Khib (lysine 2-hydroxyisobutyryllysine), Kglu (lysineglutaryllysine), Kmal (lysinemalonyllysine), Ksucc (lysinesuccinyllysine), Kcr (lysinecrotonyllysine), Kbu (lysinebutyryllysine), Kpr (lysinepropionyllysine), SUMO1 (SUMO1 modification), ub (ubiquitination), P-Typ (phosphorylation), and 3-nitro-Tyr (nitro-tyrosine) increased significantly as mice aged. Moreover, the modification level of Kme2 (lysinedi-methyllysine) and Kac (lysineacetyllysine) was the highest in the 3M mice and the lowest in 12M mice. In addition, only trimethylation of histone lysine was up-regulated progressively and significantly with increasing age (p < 0.001), H4 ubiquitination was obviously higher in the 12M and 17M mice than 3M (p < 0.001), whereas the modification of Kpr (lysinepropionylation) and O-GlcNA in 17M was significantly decreased compared with the level in 3M mice (p < 0.05, p < 0.01). Furthermore, the expression levels of the TIP60, P300, PRDM9, KMT5B, and KMT5C genes encoding PTM regulators were up-regulated in 17M compared to 3M female mice (p < 0.05). These findings indicate that altered related regulatory enzymes and PTMs are associated with physiological ovarian aging in mice, which is expected to provide useful insights for the delay of ovarian aging and the diagnosis and treatment of female infertility.

Epigenetic models developed for plains zebras predict age in domestic horses and endangered equids

Effective conservation and management of threatened wildlife populations require an accurate assessment of age structure to estimate demographic trends and population viability. Epigenetic aging models are promising developments because they estimate individual age with high accuracy, accurately predict age in related species, and do not require invasive sampling or intensive long-term studies. Using blood and biopsy samples from known age plains zebras (Equus quagga), we model epigenetic aging using two approaches: the epigenetic clock (EC) and the epigenetic pacemaker (EPM). The plains zebra EC has the potential for broad application within the genus Equus given that five of the seven extant wild species of the genus are threatened. We test the EC’s ability to predict age in sister taxa, including two endangered species and the more distantly related domestic horse, demonstrating high accuracy in all cases. By comparing chronological and estimated age in plains zebras, we investigate age acceleration as a proxy of health status. An interaction between chronological age and inbreeding is associated with age acceleration estimated by the EPM, suggesting a cumulative effect of inbreeding on biological aging throughout life.

Human iPSC-Derived Neurons as A Platform for Deciphering the Mechanisms behind Brain Aging

With an increased life expectancy among humans, aging has recently emerged as a major focus in biomedical research. The lack of in vitro aging models—especially for neurological disorders, where access to human brain tissues is limited—has hampered the progress in studies on human brain aging and various age-associated neurodegenerative diseases at the cellular and molecular level. In this review, we provide an overview of age-related changes in the transcriptome, in signaling pathways, and in relation to epigenetic factors that occur in senescent neurons. Moreover, we explore the current cell models used to study neuronal aging in vitro, including immortalized cell lines, primary neuronal culture, neurons directly converted from fibroblasts (Fib-iNs), and iPSC-derived neurons (iPSC-iNs); we also discuss the advantages and limitations of these models. In addition, the key phenotypes associated with cellular senescence that have been observed by these models are compared. Finally, we focus on the potential of combining human iPSC-iNs with genome editing technology in order to further our understanding of brain aging and neurodegenerative diseases, and discuss the future directions and challenges in the field.

A field guide for aging passerine nestlings using growth data and predictive modeling

Background Accurate nestling age is valuable for studies on nesting strategies, productivity, and impacts on reproductive success. Most aging guides consist of descriptions and photographs that are time consuming to read and subjective to interpret. The Western Bluebird (Sialia mexicana) is a secondary cavity-nesting passerine that nests in coniferous and open deciduous forests. Nest box programs for cavity-nesting species have provided suitable nesting locations and opportunities for data collection on nestling growth and development. Methods We developed models for predicting the age of Western Bluebird nestlings from morphometric measurements using model training and validation. These were developed for mass, tarsus, and two different culmen measurements. Results Our models were accurate to within less than a day, and each model worked best for a specific age range. The mass and tarsus models can be used to estimate the ages of Western Bluebird nestlings 0–10 days old and were accurate to within 0.5 days for mass and 0.7 days for tarsus. The culmen models can be used to estimate ages of nestlings 0–15 days old and were also accurate to within less than a day. The daily mean, minimum, and maximum values of each morphometric measurement are provided and can be used in the field for accurate nestling age estimations in real time. Conclusions The model training and validation procedures used here demonstrate that this method can create aging models that are highly accurate. The methods can be applied to any passerine species provided sufficient nestling morphometric data are available.