Aging-Us最新文献

{"title":"Development and validation of an electronic frailty index in a national health maintenance organization.","authors":"Fabienne Hershkowitz Sikron, Rony Schenker, Yishay Koom, Galit Segal, Orit Shahar, Idit Wolf, Bawkat Mazengya, Maor Lewis, Irit Laxer, Dov Albukrek","doi":"10.18632/aging.206141","DOIUrl":"10.18632/aging.206141","url":null,"abstract":"<p><strong>Background: </strong>Frailty constitutes a major factor that puts the elderly at risk of health and functional deterioration.</p><p><strong>Objectives: </strong>To develop and validate an Electronic Frailty Index based on electronic data routinely collected in the HMO.</p><p><strong>Study design and setting: </strong>A retrospective cohort of the HMO members.</p><p><strong>Participants: </strong>120,986 patients, aged 65 years and over at the beginning of 2023.</p><p><strong>Predictors: </strong>A cumulative frailty index including 36 medical, functional, and social deficits.</p><p><strong>Outcomes: </strong>One-year all-cause mortality or hospitalization.</p><p><strong>Statistical analysis: </strong>One-year hazard ratios were estimated for composite outcome of mortality or hospitalization using multivariable hierarchical Cox regression.</p><p><strong>Results: </strong>The mean EFI score increased with the Social Security Nursing Benefit. Compared to fit patients, mild, moderate, and severe frailty patients had 2.07, 3.35, and 4.4-fold increased risks of mortality or hospitalization, after controlling for covariates.</p><p><strong>Conclusions: </strong>The findings showed that the Electronic Frailty Index version we created is valid in predicting mortality or hospitalization. In addition, the Electronic Frailty Index converged with an independent measurement produced by National Social Security.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"null ","pages":"13025-13038"},"PeriodicalIF":3.9,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552639/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142513505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Angiotensin-(1-7) relieves behavioral defects and α-synuclein expression through NEAT1/miR-153-3p axis in Parkinson's disease.","authors":"Qing Gao, Xiaoyuan Li, Ting Huang, Li Gao, Siyu Wang, Yang Deng, Feng Wang, Xue Xue, Rui Duan","doi":"10.18632/aging.206028","DOIUrl":"10.18632/aging.206028","url":null,"abstract":"<p><p>Parkinson's disease (PD) is the second most common neurodegenerative disorder, whose characteristic pathology involves progressive deficiency of dopaminergic neurons and generation of Lewy bodies (LBs). Aggregated and misfolded α-synuclein (α-syn) is the major constituent of LBs. As the newly discovered pathway of renin-angiotensin system (RAS), Angiotensin-(1-7) (Ang-(1-7)) and receptor Mas have attracted increasing attentions for their correlation with PD, but underlying mechanisms remain not fully clear. Based on above, this study established PD models of mice and primary dopaminergic neurons with AAV-hα-syn(A53T), then discussed the effects of Ang-(1-7)/Mas on α-syn level and neuronal apoptosis for these models combined with downstream long non-coding RNA (lncRNA) and microRNA (miRNA). Results showed that Ang-(1-7) alleviated behavioral impairments, rescued dopaminergic neurons loss and lowered α-syn expression in substantia nigra of hα-syn(A53T) overexpressed PD mice. We also discovered that Ang-(1-7) decreased level of α-syn and apoptosis in the hα-syn(A53T) overexpressed dopaminergic neurons through lncRNA NEAT1/miR-153-3p axis. Moreover, miR-153-3p level in peripheral blood is found negatively correlated with that of α-syn. In conclusion, our work not only showed neuroprotective effect and underlying mechanisms for Ang-(1-7) on α-syn <i>in vivo</i> and <i>vitro</i>, but also brought new hope on miR-153-3p and NEAT1 for diagnosis and treatment in PD.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"16 ","pages":"13304-13322"},"PeriodicalIF":3.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11719108/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell sequencing technology to characterize stem T-cell subpopulations in acute T-lymphoblastic leukemia and the role of stem T-cells in the disease process.","authors":"Yan Li, Zhenwei Jia, Xiaoyan Liu, Hongbo Zhao, Guirong Cui, Jianmin Luo, Xiaoyang Kong","doi":"10.18632/aging.206123","DOIUrl":"10.18632/aging.206123","url":null,"abstract":"<p><strong>Background: </strong>Precursor T-cell acute lymphoblastic leukemia (Pre-T ALL) is a malignant neoplastic disease in which T-cells proliferate in the bone marrow. Single-cell sequencing technology could identify characteristic cell types, facilitating the study of the therapeutic mechanisms in Pre-T ALL.</p><p><strong>Methods: </strong>The single-cell sequencing data (scRNA-seq) of Pre-T ALL were obtained from public databases. Key immune cell subpopulations involved in the progression of Pre-T ALL were identified by clustering and annotating the cellular data using AUCell. Next, pseudo-temporal analysis was performed to identify the differentiation trajectories of immune cell subpopulations using Monocle. Copy number mutation landscape of cell subpopulations was characterized by inferCNV. Finally, cellphoneDB was used to analyze intercellular communication relationships.</p><p><strong>Results: </strong>A total of 10 cellular subpopulations were classified, with Pre-T ALL showing a higher proportion of NK/T cells. NK/T cells were further clustered into two subpopulations. Stem T cells showed a high expression of marker genes related to hematopoietic stem cells, Naive T cells had a high expression of CCR7, CCR7, RCAN3, and NK cells high-expressed KLRD1, TRDC. The cell proliferation was reduced and the activation of T cell was increased during the differentiation of stem T cells to Naive T cells. We observed interaction between stem T cells with dendritic cells such as CD74-COPA, CD74-MIF as well as co-inhibition-related interactions such as LGALS9-HAVCR2, TGFB1-TGFBR3.</p><p><strong>Conclusion: </strong>Stem T cells were involved in the development of Pre-T-ALL through the regulatory effects of transcription factors (TFs) KLF2 and FOS and multiple ligand-receptor pairs.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"null ","pages":"13117-13131"},"PeriodicalIF":3.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552640/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Werner syndrome RECQ helicase participates in and directs maintenance of the protein complexes of constitutive heterochromatin in proliferating human cells.","authors":"Pavlo Lazarchuk, Matthew Manh Nguyen, Crina M Curca, Maria N Pavlova, Junko Oshima, Julia M Sidorova","doi":"10.18632/aging.206132","DOIUrl":"10.18632/aging.206132","url":null,"abstract":"<p><p>Werner syndrome of premature aging is caused by mutations in the WRN RECQ helicase/exonuclease, which functions in DNA replication, repair, transcription, and telomere maintenance. How the loss of WRN accelerates aging is not understood in full. Here we show that WRN is necessary for optimal constitutive heterochromatin levels in proliferating human fibroblasts. Locally, WRN deficiency derepresses SATII pericentromeric satellite repeats but does not reduce replication fork progression on SATII repeats. Globally, WRN loss reduces a subset of protein-protein interactions responsible for the organization of constitutive heterochromatin in the nucleus, namely, the interactions involving Lamin B1 and Lamin B receptor, LBR. Both the mRNA level and subcellular distribution of LBR are affected by WRN deficiency, and unlike the former, the latter phenotype does not require WRN catalytic activities. The phenotypes of heterochromatin disruption seen in WRN-deficient proliferating fibroblasts are also observed in WRN-proficient fibroblasts undergoing replicative or oncogene-induced senescence. WRN interacts with histone deacetylase 2, HDAC2; WRN/HDAC2 association is mediated by heterochromatin protein alpha, HP1α, and WRN complexes with HP1α and HDAC2 are downregulated in senescing cells. The data suggest that the effect of WRN loss on heterochromatin is separable from senescence program, but mimics at least some of the heterochromatin changes associated with it.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"null ","pages":"12977-13011"},"PeriodicalIF":3.9,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552638/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A lactate metabolism-related gene signature to diagnose osteoarthritis based on machine learning combined with experimental validation.","authors":"Jianhua Yang, Wenjun Li, Xuemei Lin, Wei Liang","doi":"10.18632/aging.205873","DOIUrl":"10.18632/aging.205873","url":null,"abstract":"<p><strong>Background: </strong>Lactate is gradually proved as the essential regulator in intercellular signal transduction, energy metabolism reprogramming, and histone modification. This study aims to clarify the diagnosis value of lactate metabolism-related genes in osteoarthritis (OA).</p><p><strong>Methods: </strong>Lactate metabolism-related genes were retrieved from the MSigDB. GSE51588 was downloaded from the Gene Expression Omnibus (GEO) as the training dataset. GSE114007, GSE117999, and GSE82107 datasets were adopted for external validation. Genomic difference detection, protein-protein interaction network analysis, LASSO, SVM-RFE, Boruta, and univariate logistic regression (LR) analyses were used for feature selection. Multivariate LR, Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB) were used to develop the multiple-gene diagnosis models. 12 control and 12 OA samples were collected from the local hospital for re-verification. The transfection assays were conducted to explore the regulatory ability of the gene to the apoptosis and vitality of chondrocytes.</p><p><strong>Results: </strong>Through the bioinformatical analyses and machine learning algorithms, SLC2A1 and NDUFB9 of the 273 lactate metabolism-related genes were identified as the significant diagnosis biomarkers. The LR, RF, SVM, and XGB models performed impressively in the cohorts (AUC > 0.7). The local clinical samples indicated that SLC2A1 and NDUFB9 were both down-regulated in the OA samples (both P < 0.05). The knockdown of NDUFB9 inhibited the viability and promoted the apoptosis of the CHON-001 cells treated with IL-1beta (both P < 0.05).</p><p><strong>Conclusions: </strong>A lactate metabolism-related gene signature was constructed to diagnose OA, which was validated in multiple independent cohorts, local clinical samples, and cellular functional experiments.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"16 ","pages":"13076-13103"},"PeriodicalIF":3.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longevity biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity.","authors":"Yu-Xuan Lyu, Qiang Fu, Dominika Wilczok, Kejun Ying, Aaron King, Adam Antebi, Aleksandar Vojta, Alexandra Stolzing, Alexey Moskalev, Anastasia Georgievskaya, Andrea B Maier, Andrea Olsen, Anja Groth, Anna Katharina Simon, Anne Brunet, Aisyah Jamil, Anton Kulaga, Asif Bhatti, Benjamin Yaden, Bente Klarlund Pedersen, Björn Schumacher, Boris Djordjevic, Brian Kennedy, Chieh Chen, Christine Yuan Huang, Christoph U Correll, Coleen T Murphy, Collin Y Ewald, Danica Chen, Dario Riccardo Valenzano, Dariusz Sołdacki, David Erritzoe, David Meyer, David A Sinclair, Eduardo Nunes Chini, Emma C Teeling, Eric Morgen, Eric Verdin, Erik Vernet, Estefano Pinilla, Evandro F Fang, Evelyne Bischof, Evi M Mercken, Fabian Finger, Folkert Kuipers, Frank W Pun, Gabor Gyülveszi, Gabriele Civiletto, Garri Zmudze, Gil Blander, Harold A Pincus, Joshua McClure, James L Kirkland, James Peyer, Jamie N Justice, Jan Vijg, Jennifer R Gruhn, Jerry McLaughlin, Joan Mannick, João Passos, Joseph A Baur, Joe Betts-LaCroix, John M Sedivy, John R Speakman, Jordan Shlain, Julia von Maltzahn, Katrin I Andreasson, Kelsey Moody, Konstantinos Palikaras, Kristen Fortney, Laura J Niedernhofer, Lene Juel Rasmussen, Liesbeth M Veenhoff, Lisa Melton, Luigi Ferrucci, Marco Quarta, Maria Koval, Maria Marinova, Mark Hamalainen, Maximilian Unfried, Michael S Ringel, Milos Filipovic, Mourad Topors, Natalia Mitin, Nawal Roy, Nika Pintar, Nir Barzilai, Paolo Binetti, Parminder Singh, Paul Kohlhaas, Paul D Robbins, Paul Rubin, Peter O Fedichev, Petrina Kamya, Pura Muñoz-Canoves, Rafael de Cabo, Richard G A Faragher, Rob Konrad, Roberto Ripa, Robin Mansukhani, Sabrina Büttner, Sara A Wickström, Sebastian Brunemeier, Sergey Jakimov, Shan Luo, Sharon Rosenzweig-Lipson, Shih-Yin Tsai, Stefanie Dimmeler, Thomas A Rando, Tim R Peterson, Tina Woods, Tony Wyss-Coray, Toren Finkel, Tzipora Strauss, Vadim N Gladyshev, Valter D Longo, Varun B Dwaraka, Vera Gorbunova, Victoria A Acosta-Rodríguez, Vincenzo Sorrentino, Vittorio Sebastiano, Wenbin Li, Yousin Suh, Alex Zhavoronkov, Morten Scheibye-Knudsen, Daniela Bakula","doi":"10.18632/aging.206135","DOIUrl":"10.18632/aging.206135","url":null,"abstract":"<p><p>The recent unprecedented progress in ageing research and drug discovery brings together fundamental research and clinical applications to advance the goal of promoting healthy longevity in the human population. We, from the gathering at the Aging Research and Drug Discovery Meeting in 2023, summarised the latest developments in healthspan biotechnology, with a particular emphasis on artificial intelligence (AI), biomarkers and clocks, geroscience, and clinical trials and interventions for healthy longevity. Moreover, we provide an overview of academic research and the biotech industry focused on targeting ageing as the root of age-related diseases to combat multimorbidity and extend healthspan. We propose that the integration of generative AI, cutting-edge biological technology, and longevity medicine is essential for extending the productive and healthy human lifespan.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"16 ","pages":"12955-12976"},"PeriodicalIF":3.9,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Retraction of: miR-627-3p inhibits osteosarcoma cell proliferation and metastasis by targeting PTN.","authors":"Ming He, Peng Shen, Chuang Qiu, Jiashi Wang","doi":"10.18632/aging.206128","DOIUrl":"10.18632/aging.206128","url":null,"abstract":"","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"16 19","pages":"12953-12954"},"PeriodicalIF":3.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11501389/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction for: High expression of CCNB1 driven by ncRNAs is associated with a poor prognosis and tumor immune infiltration in breast cancer.","authors":"Hongtao Fu, Kun Li, Shui Wang, Yuming Li","doi":"10.18632/aging.206137","DOIUrl":"10.18632/aging.206137","url":null,"abstract":"","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"16 19","pages":"12952"},"PeriodicalIF":3.9,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11501392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating cardiovascular risk biomarkers in the context of inflammaging.","authors":"Jacopo Sabbatinelli, Matilde Sbriscia, Fabiola Olivieri, Angelica Giuliani","doi":"10.18632/aging.206136","DOIUrl":"10.18632/aging.206136","url":null,"abstract":"","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"16 19","pages":"12670-12672"},"PeriodicalIF":3.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11501381/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lymph node metastasis determined miRNAs in esophageal squamous cell carcinoma.","authors":"Feng Wei, Shufeng Bi, Mengmeng Li, Jia Yu","doi":"10.18632/aging.206122","DOIUrl":"10.18632/aging.206122","url":null,"abstract":"<p><strong>Purpose: </strong>There is no golden noninvasive and effective technique to diagnose lymph node metastasis (LNM) for esophageal squamous cell carcinoma (ESCC) patients. Here, a classifier was proposed consisting of miRNAs to screen ESCC patients with LNM from the ones without LNM.</p><p><strong>Methods: </strong>miRNA expression and clinical data files of 93 ESCC samples were downloaded from TCGA as the discovery set and 119 ESCC samples with similar dataset GSE43732 as the validation set. Differentially expressed miRNAs (DE-miRNAs) were analyzed between patients with LNM and without LNM. LASSO regression was performed for selecting the DE-miRNA pair to consist the classifier. To validate the accuracy and reliability of the classifier, the SVM and AdaBoost algorithms were applied. The CCK-8 and wound healing assay were used to evaluate the role of the miRNA in ESCC cells.</p><p><strong>Result: </strong>There were 43 DE miRNAs between the LNM+ group and LNM- group. Among them, miR-224-5p, miR-99a-5p, miR-100-5p, miR-34c-5p, miR-503-5p, and miR-452-5p were identified by LASSO to establish the classifier. SVM and AdaBoost showed that the model could classify the ESCC patients with LNM from the ones without LNM precisely and reliably in 2 data sets. miR-224-5p in the classifier as the top contributor to discriminate the two groups of patients based on AdaBoost, promoted ESCC cell proliferation and migration <i>in vitro</i>.</p><p><strong>Conclusion: </strong>The classifier based on these 6 miRNAs could classify the ESCC patients with LNM from the ones without LNM successfully.</p>","PeriodicalId":55547,"journal":{"name":"Aging-Us","volume":"null ","pages":"13104-13116"},"PeriodicalIF":3.9,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11552642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142481704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}