Analysis of Forsythia suspensa fruit and leaf extracts using UHPLC-Q-Exactive-Orbitrap/MS: In vivo antioxidant activity on D-galactose-induced aging mice.

Making health-enhancing tea from Forsythia suspensa leaves has been a tradition of Chinese folk culture for centuries. However, these leaves were not officially recognized as a new food source until 2017 by the Chinese government. In this study, ethyl acetate fractions from Forsythia suspensa fruit and leaves exhibited excellent antioxidant activity in vitro antioxidant assays and in vivo D-galactose-induced aging mice model. The antioxidant activity of the leaves was higher than that of fruit both in vitro and in vivo. The chemical constituents present in these ethyl acetate fractions were comprehensively analyzed using UHPLC-Q-Exactive-Orbitrap/MS. A total of 20 compounds were identified, among which forsythoside E, (+)-epipinoresinol, dihydromyricetin, chlorogenic acid, and ursolic acid were exclusively detected in the ethyl acetate fraction of Forsythia suspensa leaves, but absent in the ethyl acetate fraction derived from its fruit. This study provides theoretical support for the utilization of Forsythia suspensa fruit and leaves.

Recording of Age-Related Changes on Murine and Human Brain Slices.

Preparation of brain slices for electrophysiological and imaging experiments has been developed several decades ago, and the method is still widely used due to its simplicity and advantages over other techniques. It can be easily combined with other well established and recently developed methods as immunohistochemistry and morphological analysis or opto- and chemogenetics. Several aspects of this technique are covered by a plethora of excellent and detailed review papers, in which one can gain a deep insight of variations in it. In this chapter, I briefly describe the solutions, equipment, and preparation techniques routinely used in our laboratory. I also aim to present how certain "old school" brain slice lab devices can be made in a cost-efficient way. These devices can be easily adapted for the special needs of the experiments. I also aim to present some differences in the preparatory techniques of acutely isolated human brain tissue.

γδ T-Cell Immunophenotype for the Study of Human Aging.

Flow cytometry serves as a crucial tool in immunology, allowing for the detailed analysis of immune cell populations. γδ T cells, a subset of T cells, play pivotal roles in immune surveillance and immune aging. Assessing the phenotype and functional capabilities of γδ T cells isolated from whole blood or tissue within the context of human aging yields invaluable insights into the dynamic changes affecting immune function, tissue homeostasis, susceptibility to infections, and inflammatory responses.

Application of Multiplex Immunoassay in Aging Research: A Methodological Approach.

One of the characteristics of aging and age-related disorders is the formation and evolution of a chronic, low-grade, and hence subclinical, inflammatory state known as inflammaging. Although the progression of inflammaging is now recognized as one of the main driving forces of aging and one of the main risk factors for morbidity and mortality in older subjects, current knowledge on the causative agents of inflammaging itself and chronic, aging-related diseases is still incomplete. In this chapter, we offer a methodological approach for assessing inflammation associated with aging through the use of multiplex immunoassay, which enables the rapid, reproducible, and simultaneous dosage of several cytokines, chemokines, and inflammatory mediators with little biological sample usage.

Analysis of Cytokine-Inducible SH2-Containing Protein (CISH) in the Study of Immunosenescence.

The aging immune system undergoes significant changes, leading to a state known as immunosenescence. Understanding the molecular mechanisms underlying immunosenescence is crucial for developing targeted interventions to enhance immune functions in older individuals. This bio-protocol review focuses on the application of quantitative reverse transcription-polymerase chain reaction (qRT-PCR) for the mRNA quantification of cytokine-inducible SH2-containing protein (CISH), an immune regulator overexpressed in T-cell responses from older adults. We outline a comprehensive protocol for the quantitative assessment of CISH mRNA expression, providing a valuable tool for researchers investigating immunosenescence.

Characterization of Age-Dependent Changes in Skeletal Muscle Repair and Regeneration Using a Mouse Model of Acute Muscle Injury.

Acute skeletal muscle injury initiates a process of necrosis, debris clearance, and ultimately tissue regeneration via myogenesis. While skeletal muscle stem cells (MuSCs) are responsible for populating the proliferative myogenic progenitor pool to fuel muscle repair, recruited and resident immune cells have a central role in the regulation of muscle regeneration via the execution of phagocytosis and release of soluble factors that act directly on MuSCs to regulate myogenic differentiation. Therefore, the timing of MuSC proliferation and differentiation is closely linked to the populations and behaviors of immune cells present within skeletal muscle. This has important implications for aging and muscle repair, as systemic changes in immune system function contribute to a decline in muscle regenerative capacity. Here, we present adapted protocols for the isolation of mononuclear cells from skeletal muscles for the quantification of immune cell populations using flow cytometry. We also describe a cardiotoxin skeletal muscle injury protocol and detail the expected outcomes including immune cell infiltration to the injured sites and formation of new myocytes. As immune cell function is substantially influenced by aging, we extend these approaches and outcomes to aged mice.

Mediating role of accelerated aging in the association between depression and mortality risk: findings from NHANES.

OBJECTIVE: To investigate the association between depression, accelerated biological aging, and mortality risk, and to assess whether accelerated aging mediates the relationship between major depression and mortality risk. METHODS: A prospective cohort of 12,761 participants aged 20 years or older from the 2005-2010 cycle of the National Health and Nutrition Examination Survey (NHANES) was analyzed. Depression was assessed using the Patient Health Questionnaire-9 (PHQ-9), with scores of ≥ 10 indicating major depression. Accelerated biological aging was measured using phenotypic age acceleration (PhenoAgeAccel). Multivariable linear regression models and subgroup analyses were used to examine the association between depression and accelerated aging, while weighted multivariable Cox proportional hazards regression models and subgroup analyses assessed the impact of major depression on mortality risk. Mediation analysis was performed to assess whether PhenoAgeAccel mediated the relationship between major depression and mortality outcomes. RESULTS: Among the 12,761 adults, the weighted mean age was 46.6 years, with 48.8% being male, and 6.9% experiencing major depression. The results showed a positive association between major depression and PhenoAgeAccel (ß: 0.61, 95% CI: 0.06-1.16). Over a median follow-up duration of 11.3 years (interquartile range: 9.9-13.1), major depression was associated with increased all-cause mortality (HR: 1.35, 95% CI: 1.13-1.62) and cardiovascular mortality (HR: 1.73, 95% CI: 1.18-2.54). However, the relationship with cancer mortality was not statistically significant after full adjustment for confounding factors. The mediation analysis further revealed that PhenoAgeAccel accounted for 10.32% and 5.12% of the associations between major depression and all-cause mortality, and cardiovascular mortality, respectively. CONCLUSION: Depression is associated with accelerated aging and contributes to increased all-cause and cardiovascular mortality. Accelerated aging partially mediates the association between major depression and mortality risk. Our findings highlight the urgent need to incorporate mental health care into public health strategies to delay population aging and reduce mortality risk.

Brain Iron in signature regions relating to cognitive aging in older adults: the Taizhou Imaging Study.

BACKGROUND: Recent magnetic resonance imaging (MRI) studies have established that brain iron accumulation might accelerate cognitive decline in Alzheimer's disease (AD) patients. Both normal aging and AD are associated with cerebral atrophy in specific regions. However, no studies have investigated aging- and AD-selective iron deposition-related cognitive changes during normal aging. Here, we applied quantitative susceptibility mapping (QSM) to detect iron levels in cortical signature regions and assessed the relationships among iron, atrophy, and cognitive changes in older adults. METHODS: In this Taizhou Imaging Study, 770 older adults (mean age 62.0 ± 4.93 years, 57.5% women) underwent brain MRI to measure brain iron and atrophy, of whom 219 underwent neuropsychological tests nearly every 12 months for up to a mean follow-up of 2.68 years. Global cognition was assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Domain-specific cognitive scores were obtained from MoCA subscore components. Regional analyses were performed for cortical regions and 2 signature regions where atrophy affected by aging and AD only: Aging (AG) -specific and AD signature meta-ROIs. The QSM and cortical morphometry means of the above ROIs were also computed. RESULTS: Significant associations were found between QSM levels and cognitive scores. In particular, after adjusting for cortical thickness of regions of interest (ROIs), participants in the upper tertile of the cortical and AG-specific signature QSM exhibited worse ZMMSE than did those in the lower tertile [ ß = -0.104, p = 0.026; ß = -0.118, p = 0.021, respectively]. Longitudinal analysis suggested that QSM values in all ROIs might predict decline in ZMoCA and key domains such as attention and visuospatial function (all p < 0.05). Furthermore, iron levels were negatively correlated with classic MRI markers of cortical atrophy (cortical thickness, gray matter volume, and local gyrification index) in total, AG-specific signature and AD signature regions (all p < 0.05). CONCLUSION: AG- and AD-selective iron deposition was associated with atrophy and cognitive decline in elderly people, highlighting its potential as a neuroimaging marker for cognitive aging.

The senolytic drug ABT-263 accelerates ovarian aging in older female mice.

Previous studies have reported that senolytic drugs can reverse obesity-mediated accumulation of senescent cells in the ovary and protect against cisplatin-induced ovarian injury by removing senescent cells. Early intervention with ABT-263 has been shown to mitigate ovarian aging. However, it remains unknown whether treatment with ABT-263 could rejuvenate the aged ovary in reproductively old females. Therefore, the current study was aimed to investigate whether advanced age intervention with ABT-263 could ameliorate age-related decline in ovarian function. Fourteen 16-month-old mice with a C57/BL6 background were treated with ABT-263 (N = 7) or vehicle (N = 7) for two weeks. Mice were initially treated with ABT-263 (60 mg/kg/d) or vehicle for 7 consecutive days. After a 7-day break, the treatment was repeated for another 7 consecutive days. Six 2-month-old mice with C57BL/6 were used as a young control. The hormonal levels, estrus cycles, ovarian reserve, ovarian cell proliferation and apoptosis, ovarian fibrosis, and steroidogenic gene expression of ovarian stromal cells were evaluated. ABT-263 treatment did not rescue abnormal estrus cycles and sex hormonal levels, or inhibit the formation of multinucleated giant cells and ovarian stromal cell apoptosis in aged ovaries. However, it reduced ovarian fibrosis and preserved the steroidogenic gene expression of ovarian stromal cells in aged ovaries. Importantly, ABT-263 treatment further depleted ovarian follicles in aged mice. In conclusion, ABT-263 treatment accelerated the depletion of ovarian follicles in aged mice, suggesting that senolytic drugs for reproductively old female may adversely affect female fertility.

The association between BMI and cognition in India: data from the Longitudinal Aging Study in India (LASI).

BACKGROUND: High body-mass index (BMI) is an established risk factor for late-life cognitive impairment and dementia, but most evidence comes from high-income contexts. Existing evidence from cross-sectional data in low- and middle-income settings is inconsistent, and many studies do not adequately address potential sources of bias. METHODS: We used data from Wave 1 of the Longitudinal Aging Study in India (LASI) (analytic N = 56,753) to estimate the association between BMI categories and cognitive functioning among older adults aged 45 + years using survey-weighted linear regression models stratified by gender and controlling for potential confounders including demographic factors, socio-economic status (SES) characteristics, and health-related behaviors. To probe potential sources of bias, including residual confounding and reverse causation, we used weighting and trimming methods, sample restriction, and explored effect modification. RESULTS: In fully adjusted models, relative to normal BMI underweight BMI was associated with lower cognitive scores (Men: -0.16 SD difference, 95% CI -0.18, -0.13; Women: -0.12 SD, -0.15, -0.10). Overweight and obesity were associated with higher cognitive scores in both men (overweight: 0.09; 0.07, 0.12, obese: 0.10; 0.05, 0.15) and women (overweight: 0.09; 0.07-0.12, obese: 0.12; 0.08-0.15). Estimates were similar after weighting and trimming but were attenuated after excluding those with low cognition (≥1 SD below the mean relative to those with similar demographic characteristics). Positive associations between overweight and obese BMI and cognition were attenuated or null in those living in urban settings and those with higher levels of educational attainment. CONCLUSIONS: Underweight BMI is a risk factor for poor cognitive outcomes in adults 45 years and older and may be indicative of poor nutritional status and life-course disadvantage in India. In tandem with existing literature, supplemental analyses and effect modification results indicate that unmeasured confounding and reverse causation may explain the observed positive associations between overweight and obese BMI and cognitive functioning from cross-sectional studies in low- and middle-income settings. Future data with longitudinal follow-up will be helpful to further disentangle biases.

The Power of a Complex Systems Perspective to Elucidate Aging.

It is becoming highly accepted that aging, age-related diseases, and geriatric healthcare can move forward if reductionist research is complemented by integrative research uniting knowledge on specific aging mechanisms, multiple biomedical, social, psychological, lifestyle, and environmental factors and their interactions. In this special issue, we present exciting papers that illustrate how complexity science theory and practice can be applied to aging research and provide a better understanding and quantification of healthy aging and vulnerability to disease. Recent insights on biomarkers, clocks of aging, frailty, and resilience are covered and studied in interaction with a dynamic multiscale perspective. The editorial and closing viewpoint guide you through basic principles of gerontological complexity science and shed light on new research horizons, including innovative systems-based interventions.

Unveiling hidden sources of noise.

Changes in neural activity thought to reflect brain aging may be partly influenced by age-dependent signals 'leaking' from the heart.

Functional connectivity across the lifespan: a cross-sectional analysis of changes.

In the era of functional brain networks, our understanding of how they evolve across life in a healthy population remains limited. Here, we investigate functional connectivity across the human lifespan using magnetoencephalography in a cohort of 792 healthy individuals, categorized into young (13 to 30 yr), middle (31 to 54 yr), and late adulthood (55 to 80 yr). Employing corrected imaginary phase-locking value, we map the evolving landscapes of connectivity within delta, theta, alpha, beta, and gamma classical frequency bands among brain areas. Our findings reveal significant shifts in functional connectivity patterns across all frequency bands, with certain networks exhibiting increased connectivity and others decreased, dependent on the frequency band and specific age groups, showcasing the dynamic reorganization of neural networks as age increases. This detailed exploration provides, to our knowledge, the first all-encompassing view of how electrophysiological functional connectivity evolves at different life stages, offering new insights into the brain's adaptability and the intricate interplay of cognitive aging and network connectivity. This work not only contributes to the body of knowledge on cognitive aging and neurological health but also emphasizes the need for further research to develop targeted interventions for maintaining cognitive function in the aging population.

Transcript errors generate amyloid-like proteins in huwman cells.

Aging is characterized by the accumulation of proteins that display amyloid-like behavior. However, the molecular mechanisms by which these proteins arise remain unclear. Here, we demonstrate that amyloid-like proteins are produced in a variety of human cell types, including stem cells, brain organoids and fully differentiated neurons by mistakes that occur in messenger RNA molecules. Some of these mistakes generate mutant proteins already known to cause disease, while others generate proteins that have not been observed before. Moreover, we show that these mistakes increase when cells are exposed to DNA damage, a major hallmark of human aging. When taken together, these experiments suggest a mechanistic link between the normal aging process and age-related diseases.

Steps to developing a DXA-based risk score for cardiovascular outcomes among older adults: the health, aging, and body composition study.

Cardiovascular disease (CVD) is a major chronic disease worldwide and its risk factors have long been investigating in epidemiological studies. Our study aims to develop a body composition-based risk score and integrate it into the Framingham Risk Score (FRS) to improve CVD prediction among well-functioning older adults. We included 1882 older adults from the Health, Aging and Body Composition (Health ABC) study to screen body composition variables obtained from the Dual-energy X-ray absorptiometry (DXA). Three models were developed and compared: the 4-DXA model, the refit FRS, and the refit FRS plus 4-DXA model. C-statistics were 0.62 (95% CI: 0.59, 0.65) for the refit FRS, 0.58 (95% CI: 0.55, 0.61) for the 4-DXA model, and 0.63 (95% CI: 0.60, 0.66) for the refit FRS plus 4-DXA model. Compared to the refit FRS, the refit FRS plus 4-DXA model slightly improved CVD outcome prediction as the discrimination slope, net reclassification index, and the integrated discrimination index were 0.053 (95% CI: 0.041, 0.066), 0.098 (95% CI = - 0.0033, 0.20) and 0.013 (95% CI: 0.0069-0.019). This study provides a model for more accurate risk stratification and draws more attention on DXA-based indices in the clinical setting. It also encourages further research in validating the developed risk score in more diverse population and in investigating a broader range of CVD risk factors.

Bioinformatics analysis of effective biomarkers and immune infiltration in type 2 diabetes with cognitive impairment and aging.

With the increasing prevalence of diabetes mellitus worldwide, type 2 diabetes mellitus (T2D) combined with cognitive impairment and aging has become one of the common and important complications of diabetes mellitus, which seriously affects the quality of life of the patients, and imposes a heavy burden on the patients' families and the society. Currently, there are no special measures for the treatment of cognitive impairment and aging in type 2 diabetes mellitus. Therefore, the search for potential biological markers of type 2 diabetes mellitus combined with cognitive impairment and aging is of great significance for future precisive treatment. We downloaded three gene expression datasets from the GEO database: GSE161355 (related to T2D with cognitive impairment and aging), GSE122063, and GSE5281 (related to Alzheimer's disease). Differentially expressed genes (DEGs) were identified, followed by gene set enrichment analysis (GSEA). A protein-protein interaction (PPI) network was constructed using the STRING database, and the top 15 hub genes were identified using the CytoHubba plugin in Cytoscape. Core genes were ultimately determined using three machine learning methods: LASSO regression, Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Linear Discriminant Analysis (LDA). The diagnostic performance of these genes was assessed using ROC curve analysis and validated in an independent dataset (GSE5281). Regulatory genes related to ferroptosis were screened from the FerrDb database, and their biological functions were further explored through GO and KEGG enrichment analyses. Finally, the CIBERSORT algorithm was used to analyze immune cell infiltration, and the correlation between core genes and immune cell infiltration levels was calculated, leading to the construction of an mRNA-miRNA regulatory network. In the GSE161355 and GSE122063 datasets, 217 common DEGs were identified. GSEA analysis revealed their enrichment in the PI3K-PLC-TRK signaling pathway, TP53 regulation of metabolic genes pathway, Notch signaling pathway, among others. PPI network analysis identified 15 candidate core genes, and further selection using LASSO, LDA, and SVM-RFE machine learning algorithms resulted in 6 core genes: BCL6, TP53, HSP90AA1, CRYAB, IL1B, and DNAJB1. ROC curve analysis indicated that these genes had good diagnostic performance in the GSE161355 dataset, with TP53 and IL1B achieving an AUC of 0.9, indicating the highest predictive accuracy. BCL6, HSP90AA1, CRYAB, and DNAJB1 also had AUCs greater than 0.8, demonstrating moderate predictive accuracy. Validation in the independent dataset GSE5281 showed that these core genes also had good diagnostic performance in Alzheimer's disease samples (AUC > 0.6). Ferroptosis-related analysis revealed that IL1B and TP53 play significant roles in apoptosis and immune response. Immune cell infiltration analysis showed that IL1B is significantly positively correlated with infiltration levels of monocytes and NK cells, while TP53 is significantly negatively correlated with infiltration levels of follicular helper T cells. The construction of the miRNA-mRNA regulatory network suggested that miR-150a-5p might play a key role in the regulation of T2D-associated cognitive impairment and aging by TP53. This study, by integrating bioinformatics and machine learning methods, identified BCL6, TP53, HSP90AA1, CRYAB, IL1B, and DNAJB1 as potential diagnostic biomarkers for T2D with cognitive impairment and aging, with a particular emphasis on the significance of TP53 and IL1B in immune cell infiltration. These findings not only enhance our understanding of the molecular mechanisms linking type 2 diabetes to cognitive impairment and aging, providing new targets for early diagnosis and treatment, but also offer new directions and targets for basic research.

Applicability of epigenetic age models to next-generation methylation arrays.

BACKGROUND: Epigenetic clocks are mathematical models used to estimate epigenetic age based on DNA methylation at specific CpG sites. As new methylation microarrays are developed and older models discontinued, existing epigenetic clocks might become obsolete. Here, we explored the effects of the changes introduced in the new EPICv2 DNA methylation array on existing epigenetic clocks. METHODS: We tested the performance of four epigenetic clocks on the probeset of the EPICv2 array using a dataset of 10,835 samples. We developed a new epigenetic age prediction model compatible across the 450 k, EPICv1, and EPICv2 microarrays and validated it on 2095 samples. We estimated technical noise and intra-subject variation using two datasets with repeated sampling. We used data from (i) cancer survivors who had undergone different therapies, (ii) breast cancer patients and controls, and (iii) an exercise-based interventional study, to test the ability of our model to detect alterations in epigenetic age acceleration in response to theoretically antiaging interventions. RESULTS: The results of the four epiclocks tested are significantly distorted by the EPICv2 probeset, causing an average difference of up to 25 years. Our new model produced highly accurate chronological age predictions, comparable to a state-of-the-art epiclock. The model reported the lowest epigenetic age acceleration in normal populations, as well as the lowest variation across technical replicates and repeated samples from the same subjects. Finally, our model reproduced previous results of increased epigenetic age acceleration in cancer patients and in survivors treated with radiation therapy, and no changes from exercise-based interventions. CONCLUSION: Existing epigenetic clocks require updates for full EPICv2 compatibility. Our new model translates the capabilities of state-of-the-art epigenetic clocks to the EPICv2 platform and is cross-compatible with older microarrays. The characterization of epigenetic age prediction variation provides useful metrics to contextualize the relevance of epigenetic age alterations. The analysis of data from subjects influenced by radiation, cancer, and exercise-based interventions shows that despite being good predictors of chronological age, neither a pathological state like breast cancer, a hazardous environmental factor (radiation), nor exercise (a beneficial intervention) caused significant changes in the values of the "epigenetic age" determined by these first-generation models.

The effect of age on aqueous humor of humans with high myopia.

Background: High myopia is a common cause of vision loss. Age is an important factor in the development of high myopia. However, the effect of age on aqueous humor proteins in the context of high myopia is unknown. This study explored the effect of age on the aqueous humor protein of humans with high myopia. Methods: The aqueous humor of high myopia patients of different ages with implantable collamer lens implantation (ICL) was collected. Data-independent acquisition proteomic analysis was employed to explore differentially expressed proteins (DEPs). Two different bioinformatics analysis methods were used to interpret the proteomic results. Furthermore, three proteins were confirmed by enzyme-linked immunosorbent assay (ELISA). Results: The study showed 18 upregulated and 20 downregulated proteins. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the upregulated DEPs were highly enriched in coagulation and complement cascades. Weighted gene coexpression network analysis showed that the blue module was identified as a key module for high myopia and that the plasminogen (PLG) protein is a hub protein. ELISA confirmed that the expression levels of Alpha-1-antitrypsin were significantly upregulated in the aqueous humor of older patients presenting with high myopia. Conclusions: This is the first study to investigate the effect of age on the level of aqueous humor protein in high myopia. Our study provided a comprehensive data set on the overall protein changes of different ages of human high myopia, shedding light on its potential molecular mechanism in high myopia damage to the eyeball.

[Knockout of Hsp70 Genes Modulates Age-Related Transcriptomic Changes in Leg Muscles and Reduces the Locomotion Speed and Lifespan of Drosophila melanogaster].

This study investigated the effect of knockout of six Hsp70 genes (orthologues of the mammalian genes Hspa1a, Hspa1b, Hspa2, and Hspa8) on age-related changes in gene expression in the legs of Drosophila melanogaster, which contain predominantly skeletal muscle bundles. For this, the leg transcriptomic profile was examined in males of the w^(1118) control strain and the Hsp70^(-) strain on the 7th, 23rd and 47th days of life. In w^(1118) flies, an age-related decrease in the locomotion (climbing) speed (a marker of functional state and endurance) was accompanied by a pronounced change in the transcriptomic profile of the leg skeletal muscles, which is conservative in nature. In Hsp70^(-) flies, the median lifespan was shorter and the locomotion speed was significantly lower compared to the control; at the same time, complex changes in the age-related dynamics of the skeletal muscle transcriptome were observed. Mass spectrometry-based quantitative proteomics showed that 47-day-old Hsp70^(-) flies, compared with w^(1118) flies, demonstrated multidirectional changes in the contents of key enzymes of glucose metabolism and fat oxidation (glycolysis, pentose phosphate pathway, Krebs cycle, beta-oxidation, and oxidative phosphorylation). Such dysregulation may be associated with a compensatory increase in the expression of other genes encoding chaperones (small Hsp, Hsp40, 60, and 70), which regulate specific sets of target proteins. Taken together, our data show that knockout of six Hsp70 genes slightly reduced the median lifespan of flies, but significantly reduced the locomotion speed, which may be associated with complex changes in the transcriptome of the leg skeletal muscles and with multidirectional changes in the contents of key enzymes of energy metabolism.

Submaximal eccentric resistance training increases serial sarcomere number and improves dynamic muscle performance in old rats.

The age-related loss of muscle mass is partly accounted for by the loss of sarcomeres in series, contributing to declines in muscle mechanical performance. Resistance training biased to eccentric contractions increases serial sarcomere number (SSN) in young muscle, however, maximal eccentric training in old rats previously did not alter SSN and worsened performance. A submaximal eccentric training stimulus may be more conducive to adaptation for aged muscle. The purpose of this study was to assess whether submaximal eccentric training can increase SSN and improve mechanical function in old rats. Twelve 32-month-old male F344/BN rats completed 4 weeks of submaximal (60% maximum) eccentric plantar-flexion training 3 days/week. Pre- and post-training, we assessed in-vivo maximum isometric torque at a stretched and neutral ankle angle, the passive torque-angle relationship, and the isotonic torque-velocity-power relationship. The soleus and medial gastrocnemius (MG) were harvested for SSN measurements via laser diffraction, with the untrained leg as a control. SSN increased 11% and 8% in the soleus and MG, respectively. Training also shifted optimal torque production towards longer muscle lengths, reduced passive torque 42%, and increased peak isotonic power 23%. Submaximal eccentric training was beneficial for aged muscle adaptations, increasing SSN, reducing muscle passive tension, and improving dynamic contractile performance.