Shuhui Sun’s research while affiliated with State Key Laboratory of Stem Cell and Reproductive Biology and other places

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Publications (35)

Single-nucleus Transcriptomics Decodes the Link Between Aging and Lumbar Disc Herniation
  • Article

March 2025

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16 Reads

Protein & Cell

Min Wang

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Zan He

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Anqi Wang

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Lumbar disc (LD) herniation and aging are prevalent conditions that can result in substantial morbidity. This study aimed to clarify the mechanisms connecting the LD aging and herniation, particularly focusing on cellular senescence and molecular alterations in the nucleus pulposus (NP). We performed a detailed analysis of NP samples from a diverse cohort, including individuals of varying ages and those with diagnosed LD herniation. Our methodology combined histological assessments with single-nucleus RNA sequencing to identify phenotypic and molecular changes related to NP aging and herniation. We discovered that cellular senescence and a decrease in nucleus pulposus progenitor cells (NPPCs) are central to both processes. Additionally, we found an age-related increase in NFAT1 expression that promotes NPPC senescence and contributes to both aging and herniation of LD. This research offers fresh insights into LD aging and its associated pathologies, potentially guiding the development of new therapeutic strategies to target the root causes of LD herniation and aging.

Phenotypic alterations in skeletal muscles of old cynomolgus monkeys a, Flowchart overview of multidimensional analysis of cynomolgus monkey skeletal muscle ageing. b, WGA staining and immunofluorescence staining showing fibre cross-sectional area, type IIX (MYH1-positive) fibres, type IIA (MYH2-positive) fibres and type I (MYH7-positive) fibres in young and old cynomolgus monkey skeletal muscles. Top, representative images. Scale bars, 200 μm. Bottom, the fibre cross-sectional area, and the percentage of MYH2-positive and MYH7-positive fibres were quantified. c, Western blotting analysis of Fbx32 protein levels in young and old cynomolgus monkey skeletal muscles. β-tubulin was used as a loading control. mkMuscle, monkey muscle. d, Masson’s Trichrome staining of young and old cynomolgus monkey skeletal muscles. Left, representative images. Scale bars, 100 μm. Right, the proportion of fibrosis area was quantified. e, BODIPY staining in young and old cynomolgus monkey skeletal muscles. Scale bars, 100 μm and 25 μm (zoomed in). Right, the proportion of BODIPY-positive area was quantified. f, Neurofilament (NF) staining of axon area and terminal buttons from young and old cynomolgus monkey skeletal muscles. Scale bars, 100 μm and 25 μm (zoomed in), 50 μm and 25 μm (zoomed in). g, Immunofluorescence staining showing the PAX7-positive muscle stem cells in young and old cynomolgus monkey skeletal muscles. Left, representative images. Scale bars, 100 μm and 25 μm (zoomed in). Right, the proportion of PAX7-positive cells was quantified. h–j, Immunofluorescence staining of CD31 (h), Lamin B1 (i) and H3K9me3 (j) in young and old cynomolgus monkey skeletal muscles. Left, representative images. Scale bars, 100 μm and 25 μm (zoomed in) in h and i; 80 μm and 10 μm (zoomed in) in j. Right, the proportion of positively stained cells or nuclei (h–i), and the fluorescence intensity (j) were quantified. Arrows indicate the positively stained cells in g–i. Two-tailed Student’s t-test was used for statistical analysis and data are shown as mean ± s.e.m. in b–j. n = 8 monkeys per group in b–j, from both genders. P values are annotated in the figures. Images in a and f were created with BioRender.com. Source data
Inflammation is a pronounced feature of primate skeletal muscle ageing a, Scatterplot showing upregulated and downregulated DEGs in old versus young cynomolgus monkey skeletal muscles. b, Representative Gene Ontology (GO) terms and pathways for upregulated and downregulated DEGs in old versus young cynomolgus monkey skeletal muscles. c, Scatterplot showing upregulated and downregulated DEPs in old versus young cynomolgus monkey skeletal muscles. d, Representative GO terms and pathways for upregulated and downregulated DEPs in old versus young monkey skeletal muscles. e, Integrated analysis of the proportion of upregulated and downregulated DEGs and DEPs in old versus young cynomolgus monkey skeletal muscles. f, Lollipop plots showing the shared upregulated and downregulated GO terms and pathways for upregulated and downregulated DEGs and DEPs in old versus young cynomolgus monkey skeletal muscles. g, Immunofluorescence staining of CD45 in young and old monkey skeletal muscles. Left, representative images. Scale bars, 100 μm and 25 μm (zoomed in). Right, the proportion of CD45-positive cells was quantified. h, Immunofluorescence staining of CD68 in young and old cynomolgus monkey skeletal muscles. Left, representative images. Scale bars, 100 μm and 25 μm (zoomed in). Right, the proportion of CD68-positive cells was quantified. i, Immunofluorescence staining of CD86 in young and old cynomolgus monkey skeletal muscles. Left, representative images. Scale bars, 100 μm and 25 μm (zoomed in). Right, the proportion of CD86-positive cells was quantified. j,k, Immunohistochemical analysis of S100A8 (j) and S100A9 (k) in young and old cynomolgus monkey skeletal muscles. Left, representative images. Scale bars, 200 μm and 50 μm (zoomed in). Right, the proportion of positively stained cells was quantified. l, Western blotting analysis of IL-6 protein levels in young and old cynomolgus monkey skeletal muscles. β-actin was used as a loading control. m, RT–qPCR analysing the relative transcript levels of IFNB and IL1B in young and old cynomolgus monkey skeletal muscles. Arrows indicate positively stained cells in g–k. Two-tailed Student’s t-test was used for statistical analysis in c and g–m, and data are shown as the mean ± s.e.m. in g–m. n = 8 monkeys per group in g–m, from both genders. Hypergeometric tests were performed in b, d and f. P values are annotated in the figures. Images in e and f were created with BioRender.com. Source data
SIRT5 deficiency induces senescence in hMyotubes a, The top ten downregulated DEPs in old versus young monkey skeletal muscles. b, Dot plot showing the expression changes of sirtuins proteins between old and young monkey skeletal muscles. The dark grey outer ring indicates that the protein was not detected in the proteomic data. c, Western blotting analysis of SIRT5 protein levels in young and old monkey skeletal muscles. n = 8 monkeys per group, from both genders. GAPDH was used as a loading control. d, Western blotting analysis of SIRT5 levels in different-age human skeletal muscles. hMuscle, human muscle. e, Flowchart overview of hMyotube generation from SIRT5+/+ and SIRT5−/− hES cells. f, Western blotting analysis of SIRT5 protein levels in SIRT5+/+ and SIRT5−/− hMyotubes. g, SA-β-gal staining analysis of SIRT5+/+ and SIRT5−/− hMyotubes. Scale bars, 150 μm and 50 μm (zoomed in). h, Left, representative images of MyHC-positive myotubes in SIRT5+/+ and SIRT5−/− hMyotubes. Scale bars, 75 μm and 25 μm (zoomed in). Right, the diameter of the hMyotube was quantified. i, Western blotting analysis of Fbx32 and MuRF1 protein levels in SIRT5+/+ and SIRT5−/− hMyotubes. j, Left, representative images of TMRM fluorescence staining in SIRT5+/+ and SIRT5−/− hMyotubes. Scale bars, 100 μm. Right, the fluorescence intensity of TMRM was quantified. k, Cellular hydrogen peroxide (H2O2) level in SIRT5+/+ and SIRT5−/− hMyotubes measured by Amplex Red fluorescence. l, RT–qPCR analysis of the relative transcript levels of IL6, IL8 and MCP1 in SIRT5+/+ and SIRT5−/− hMyotubes. m, ELISA analysis of IL-6 and TNF levels in SIRT5+/+ and SIRT5−/− hMyotubes. n, Scatterplot showing the upregulated and downregulated DEGs in SIRT5+/+ and SIRT5−/− hMyotubes. o, Representative GO terms and pathways for upregulated and downregulated DEGs in SIRT5+/+ and SIRT5−/− hMyotubes. Two-tailed Student’s t-test was used for statistical analysis and data are presented as mean ± s.e.m. in c and g–m. Hypergeometric test was performed in o. β-tubulin was used as loading control in d, f and i. n = 3 biological replicates in g–m. P values are annotated in the figures. Images in e were created in BioRender.com. Source data
SIRT5 interacts with and desuccinylates TBK1 a, Schematic diagram of Co-IP assay followed by mass spectrometry analysis. FLAG–Luc served as the negative control. b, Representative GO terms and pathways for SIRT5-interacting proteins. c, HEK293T cells were transfected with FLAG–Luc or FLAG–SIRT5 plasmid. FLAG-tagged proteins were immunoprecipitated with anti-FLAG antibody and incubated with cynomolgus monkey skeletal muscle lysate. Antibody against TBK1 was used for western blotting analysis. d, HEK293T cells were transfected with FLAG–Luc or FLAG–TBK1 plasmid. FLAG-tagged proteins were immunoprecipitated with anti-FLAG and analysed with an antibody against SIRT5. e, HEK293T cells were transfected with FLAG–Luc or FLAG–SIRT5 plasmid. FLAG-tagged proteins were immunoprecipitated with anti-FLAG and analysed with an antibody against TBK1. f, hMyotubes were transduced with lentivirus vectors expressing FLAG–Luc or FLAG–SIRT5. FLAG-tagged proteins were immunoprecipitated with anti-FLAG and analysed with an antibody against TBK1. g, Schematic diagram showing the desuccinylation of TBK1 by SIRT5-WT but not SIRT5-H158Y. Ksucc, lysine succinylation. h, HEK293T cells were co-transfected with FLAG–TBK1 and HA–Luc, HA–SIRT5-WT or HA-SIRT5-H158Y plasmids. FLAG–TBK1 proteins were immunoprecipitated with anti-FLAG and analysed with antibodies against succinylated lysine, p-TBK1 (S172) or FLAG. The yellow arrows indicate an elevation and the green arrows indicate a reduction in both TBK1 succinylation levels and the ratio of phosphorylated to total TBK1 levels, respectively. n = 3 biological replicates. i, Schematic diagram showing the succinylation levels of TBK1 in SIRT5+/+ and SIRT5−/− hMyotubes. j, Left, lysates prepared from SIRT5+/+ and SIRT5−/− hMyotubes were immunoprecipitated with an antibody against succinylated lysine and analysed with antibodies against TBK1 by western blotting. Right, western blotting analysis of p-TBK1 (S172), SIRT5 protein levels in SIRT5+/+ and SIRT5−/− hMyotubes. β-tubulin was used as a loading control. n = 3 biological replicates. Two-tailed Student’s t-test was used for statistical analysis and data are presented as the mean ± s.e.m. in h and j. Hypergeometric test was performed in b. The representative results from one of three independent experiments in c–f. P values are annotated in the figures. Images in a were created with BioRender.com. Source data
SIRT5 desuccinylates TBK1 at Lys137 and facilitates its dephosphorylation a, Network diagram showing putative TBK1 lysine succinylation sites analysed by HybridSucc, SuccinSite and iSuc-PseAAC databases. b, HEK293T cells were co-transfected with wild-type FLAG–TBK1 (WT) or FLAG–TBK1 mutant (K137R, K451R, K460R, K567R or K615R) and HA–Luc, or HA–SIRT5 plasmids. FLAG–TBK1 proteins were immunoprecipitated with anti-FLAG and analysed with antibodies against succinylated lysine, p-TBK1 (S172) or FLAG. c, HEK293T cells were co-transfected with wild-type FLAG-TBK1 (WT) or FLAG-TBK1 mutant (K137R) and HA-Luc or HA-SIRT5 plasmids. FLAG–TBK1 proteins were immunoprecipitated with anti-FLAG and analysed with antibodies against succinylated lysine, p-TBK1 (S172) or FLAG. d, Western blotting analysis of p-TBK1 (S172) and SIRT5 levels in SIRT5−/− hMyotubes transduced with lentivirus vectors expressing FLAG–Luc, FLAG–SIRT5-WT or FLAG–SIRT5-H158Y. β-tubulin was used as a loading control. e, Western blotting analysis of p-TBK1 (S172) and TBK1 levels in young and old monkey skeletal muscles. n = 8 monkeys per group, from both genders. f, Schematic showing the primary structure of TBK1. KD, kinase domain; ULD, ubiquitin-like domain; SDD, scaffold and dimerization domain; CTD, carboxy-terminal domain. g, Schematic showing the three-dimensional structure of TBK1. h, Spatial position and distances between putative TBK1 lysine succinylation sites and its serine 172 site. The distance between two amino acids is determined by the mean distance of distinct amino acid atoms. i, Heatmap showing the RT–qPCR analysis of the relative transcript levels of IL6, IL8 and MCP1 of hMyotubes transduced with lentivirus vectors expressing FLAG–Luc, FLAG–TBK1-WT or FLAG–TBK1-K137R. j, SA-β-gal staining analysis of hMyotubes transduced with lentivirus vectors expressing FLAG–Luc, FLAG–TBK1-WT or FLAG–TBK1-K137R. Scale bars, 150 μm and 50 μm (zoomed in). k, Left, representative images of MyHC-positive myotubes in hMyotubes transduced with lentivirus vectors expressing FLAG–Luc, FLAG–TBK1-WT or FLAG–TBK1-K137R. Scale bars, 75 μm and 25 μm (zoomed in). Right, the diameter of hMyotubes was quantified. Two-tailed Student’s t-test was used for statistical analysis in d, e, j and k, and data are presented as the mean ± s.e.m. in d, e, h, j and k. Representative results from one of three independent experiments in b and c. n = 3 biological replicates in d, i, j and k. P values are annotated in the figures. Source data

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SIRT5 safeguards against primate skeletal muscle ageing via desuccinylation of TBK1
  • Article
  • Publisher preview available

March 2025

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168 Reads

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1 Citation

Nature Metabolism

Qian Zhao

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Ying Jing

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Xiaoyu Jiang

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Ageing-induced skeletal muscle deterioration contributes to sarcopenia and frailty, adversely impacting the quality of life in the elderly. However, the molecular mechanisms behind primate skeletal muscle ageing remain largely unexplored. Here, we show that SIRT5 expression is reduced in aged primate skeletal muscles from both genders. SIRT5 deficiency in human myotubes hastens cellular senescence and intensifies inflammation. Mechanistically, we demonstrate that TBK1 is a natural substrate for SIRT5. SIRT5 desuccinylates TBK1 at lysine 137, which leads to TBK1 dephosphorylation and the suppression of the downstream inflammatory pathway. Using SIRT5 lentiviral vectors for skeletal muscle gene therapy in male mice enhances physical performance and alleviates age-related muscle dysfunction. This study sheds light on the molecular underpinnings of skeletal muscle ageing and presents the SIRT5–TBK1 pathway as a promising target for combating age-related skeletal muscle degeneration.

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Figure 1. Timeline of generating hNSCs from hESCs (A) Representative images illustrating the self-renewal growth state of H9 hESCs. Scale bars, 200 mm. (B) Representative images depicting the neural differentiation of H9 hESCs in a 6-well plate from 0 to 2 days in vitro (DIV0-2). Scale bars, 200 mm. (C) Representative images depicting the neural differentiation of H9 hESCs in a 6-well plate from 3 to 7 days in vitro (DIV3-7). Scale bars, 200 mm.
Figure 2. Quality controls confirming high yield and successful neural induction (A) Brightfield images showing the morphology of hNSCs after the reattachment of dissociated EBs cells through several passages (annotated as P1, P2, P3). Scale bars, 100 mm. (B) The density of hNSCs that can continue to be passaged. Scale bars, 100 mm. (C) Immunofluorescence staining of hNSCs on P3 confirming the expression of hNSC markers SOX2, PAX6 and NESTIN. Scale bars, 20 mm. n = 3 biological samples. Data are represented as the mean G SEM.
Figure 4. Detection of senescent phenotypes in long-term cultured hNeurons (A) From left to right, immunofluorescence staining of Lamin B1, Lamin B2, SA-b-Gal staining, immunofluorescence staining of Ab (4G8) and aggresome staining in MAP2-marked hNeurons during prolonged culture. White arrowheads indicate the corresponding positively stained cells. Scale bars, for SAb-Gal, 50 mm; for Lamin B1, Lamin B2, Ab (4G8) and aggresome staining, 20 mm and 5 mm (zoomed-in images). (B) Quantitative data for fluorescence intensity of Lamin B1 and Lamin B2, as well as the percentages of SA-b-Gal-positive hNeurons, Ab (4G8)-positive hNeurons and aggresome-positive hNeurons as shown in (A). n = 3 biological samples. Data are represented as the mean G SEM. Two-tailed unpaired t-test.
Figure 5. Example data demonstrating the efficiency of the siRNA approach (A) Verification of knockdown efficiency by qRT-PCR at 48 h after transfection with negative control (NC) or siRNA duplexes against LMNB1 and LMNB2 (si-LB1&2) in hNeurons. n = 3 biological samples. (B) Verification of knockdown efficiency by immunofluorescence staining of Lamin B1 at 72 h after transfection with negative control (NC) or siRNA duplexes against LMNB1 and LMNB2 in hNeurons. Scale bars, 20 mm and 5 mm (zoomed-in images). n = 3 biological samples. (C) Verification of knockdown efficiency by immunofluorescence staining of Lamin B2 at 72 h after transfection with negative control (NC) or siRNA duplexes against LMNB1 and LMNB2 in hNeurons. Scale bars, 20 mm and 5 mm (zoomed-in images). n = 3 biological samples. (D) SA-b-Gal staining in hNeurons transfected with NC or siRNA duplexes against LMNB1 and LMNB2. Scale bars, 50 mm. n = 3 biological samples. (E) Aggresome staining in MAP2-marked hNeurons transfected with NC or siRNA duplexes against LMNB1 and LMNB2. White arrowheads indicate the aggresome positive cells. Scale bars, 20 mm and 5 mm (zoomed-in images). n = 3 biological samples. (F) Verification of knockdown efficiency by qRT-PCR at 48 h after transfection with NC or siRNA duplexes against cGAS (si-cGAS) in hNeurons transfected with siRNA duplexes against LMNB1 and LMNB2. n = 3 biological samples. (G) Verification of knockdown efficiency by immunofluorescence staining of cGAS at 72 h after transfection with NC or siRNA duplexes against cGAS in hNeurons transfected with siRNA duplexes against LMNB1 and LMNB2. Scale bars, 20 mm and 5 mm (zoomed-in images). n = 3 biological samples. (H) SA-b-Gal staining in LMNB1 and LMNB2 knockdown hNeurons after transfection with NC or siRNA duplexes against cGAS. Scale bars, 50 mm. n = 3 biological samples. Data are represented as the mean G SEM. Two-tailed unpaired t-test.
Figure 6. Example data demonstrating the effects of drug treatment on long-term cultured hNeurons (A) SA-b-Gal staining in hNeurons at day 35 after treatment with vehicle or abacavir. n = 3 biological samples. (B) Left, aggresome staining in hNeurons at day 35 after treatment with vehicle or abacavir. White arrowheads indicate the aggresome positive cells. Right, Quantitative data for the relative aggresome-positive neurons. n = 3 biological samples. (C) SA-b-Gal staining in hNeurons transfected with siRNA duplexes against LMNB1 and LMNB2 after treatment with vehicle or abacavir. n = 3 biological samples. (D) Left, aggresome staining in hNeurons transfected with siRNA duplexes against LMNB1 and LMNB2 after treatment with vehicle or abacavir. White arrowheads indicate the aggresome positive cells. Right, Quantitative data for the relative aggresome-positive neurons. n = 3 biological samples. Data are represented as the mean G SEM. Two-tailed unpaired t-test.
Protocols for the application of human embryonic stem cell-derived neurons for aging modeling and gene manipulation

February 2025

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33 Reads

STAR Protocols

Hui Zhang

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Shuhui Sun

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In vitro models of neuronal aging and gene manipulation in human neurons (hNeurons) are valuable tools for investigating human brain aging and diseases. Here, we present a protocol for applying human embryonic stem cell (hESC)-derived neurons to model aging and the further application of small interfering RNA (siRNA)-mediated gene silencing for functional investigations. We describe steps for neuronal differentiation and culture, siRNA transfection, and technical considerations to ensure reproducibility. Our protocol enables investigations of the molecular mechanism underlying neuronal aging and facilitates drug evaluation. For complete details on the use and execution of this protocol, please refer to Zhang et al.¹

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CRISPR screening uncovers nucleolar RPL22 as a heterochromatin destabilizer and senescence driver

September 2024

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116 Reads

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1 Citation

Nucleic Acids Research

Hong-Yu Li

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Min Wang

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Xiaoyu Jiang

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Dysfunction of the ribosome manifests during cellular senescence and contributes to tissue aging, functional decline, and development of aging-related disorders in ways that have remained enigmatic. Here, we conducted a comprehensive CRISPR-based loss-of-function (LOF) screen of ribosome-associated genes (RAGs) in human mesenchymal progenitor cells (hMPCs). Through this approach, we identified ribosomal protein L22 (RPL22) as the foremost RAG whose deficiency mitigates the effects of cellular senescence. Consequently, absence of RPL22 delays hMPCs from becoming senescent, while an excess of RPL22 accelerates the senescence process. Mechanistically, we found in senescent hMPCs, RPL22 accumulates within the nucleolus. This accumulation triggers a cascade of events, including heterochromatin decompaction with concomitant degradation of key heterochromatin proteins, specifically heterochromatin protein 1γ (HP1γ) and heterochromatin protein KRAB-associated protein 1 (KAP1). Subsequently, RPL22-dependent breakdown of heterochromatin stimulates the transcription of ribosomal RNAs (rRNAs), triggering cellular senescence. In summary, our findings unveil a novel role for nucleolar RPL22 as a destabilizer of heterochromatin and a driver of cellular senescence, shedding new light on the intricate mechanisms underlying the aging process.

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Citations (27)

... Living organisms display a sophisticated organization throughout their lifetimes, characterized by intricate system-wide coordination and specialized organspecific compartmental functions [1][2][3]. Aging, a complex physiological process, strongly correlates with the risk of chronic illnesses such as metabolic disorders, cardiovascular diseases, and neurodegenerative conditions [4]. This process involves a multiorgan aging network, where primary organ aging progresses to affect multiple systems [5,6]. ...

Reference:

Integrative cross‐tissue analysis unveils complement‐immunoglobulin augmentation and dysbiosis‐related fatty acid metabolic remodeling during mammalian aging
Spatial transcriptomic landscape unveils immunoglobin-associated senescence as a hallmark of aging
  • Citing Article

  • November 2024

Cell

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Bin Zhang

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... [4][5][6] Beyond epidemiological evidence, mechanistic insights also support the notion that metformin may exert neuroprotective effects through multiple pathways. These include not only its metabolic effects 3 but also its role in attenuating general mechanisms of cellular aging, 7 slowing brain aging, 8 and modulating key AD-related pathologies, including amyloid and tau. 9 Furthermore, metformin at 500 mg/day is the most widely prescribed antidiabetic drug worldwide, is recognized as an essential medicine by the World Health Organization as of 2023, and is available off-patent at low cost in most countries. ...

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Long‐term metformin use for Alzheimer's disease prevention?
Metformin decelerates aging clock in male monkeys
  • Citing Article

  • September 2024

Cell

Yuanhan Yang

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... This process involves a multiorgan aging network, where primary organ aging progresses to affect multiple systems [5,6]. Although several traits, like chronic inflammation, metabolic reprogramming, and dysbiosis, are known to contribute to age-related decline [7][8][9], the relationships between them are unclear. A systematic investigation into multiorgan aging is necessary to obtain a panoramic view of aging-derived disturbance in trajectories and identify potential gero-protective targets for healthy aging and longevity. ...

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Integrative cross‐tissue analysis unveils complement‐immunoglobulin augmentation and dysbiosis‐related fatty acid metabolic remodeling during mammalian aging
Exploring the heterogeneous targets of metabolic aging at single-cell resolution
  • Citing Article

  • August 2024

Trends in Endocrinology and Metabolism

Shuhui Sun

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Mengmeng Jiang

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... CRISPR / Cas9-based genetic screening has become an established and powerful approach to uncovering regulatory networks in many biological processes (51)(52)(53)(54). In this study, we performed a CRISPR-based LOF screen that targeted proteins associated with ribosomes in senescent hMPCs and identified that deficiency of RPL22 ameliorates hMPC senescence. ...

Reference:

CRISPR screening uncovers nucleolar RPL22 as a heterochromatin destabilizer and senescence driver
CRISPR-based screening pinpoints H2AZ1 as a driver of senescence in human mesenchymal stem cells
  • Citing Article

  • June 2024

Protein & Cell

Ming-Heng Li

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Xiaoyu Jiang

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... To evaluate performance on tasks where query and reference datasets were sequenced using different technologies, we applied the methods on the 9 pancreas datasets in scIB [24] that were designed to evaluate data integration tools. For phenotypic effects, specifically age on the monkey adrenal gland, we used the datasets provided in [25]. To test for cross-species annotation, we used the ALM, MTG, and VISp datasets from the Allen brain atlas [26] [27]. ...

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Automated Cell Type Annotation with Reference Cluster Mapping
Aging induces region-specific dysregulation of hormone synthesis in the primate adrenal gland

Nature Aging

Qiaoran Wang

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Xuebao Wang

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... Secure enterprise systems play a pivotal role in safeguarding data and ensuring the integrity of digital transactions within the logistics infrastructure. The integration of SES in logistics operations ensures that environmental data and compliance information are securely managed, promoting transparency and trust among stakeholders [82]Furthermore, SES can enhance decision-making processes, supporting long-term sustainability initiatives by providing reliable and secure data-handling capabilities [83]. ...

Reference:

Cloud and Web Technology Influences on Mitigating Environmental Footprint A Review of Sustainable Logistics Solutions with AI, IoT, and Secure Enterprise Systems
CRL2APPBP2-mediated TSPYL2 degradation counteracts human mesenchymal stem cell senescence
  • Citing Article

  • December 2023

Science China. Life sciences

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Qian Zhao

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Kuan Yang

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... According to previous studies, FoxO1 plays an important role in combating cellular senescence and promoting the prolongation of cell lifespan by participating in several key biological processes, such as anti-oxidative stress, DNA repair, cell cycle regulation, cell autophagy, and metabolic regulation. 25,26 In KEGG pathway enrichment analysis, we found that the potential targets of YFJP for HCC treatment were significantly enriched in FoxO signaling pathway. Furthermore, FoxO1 was identified to be the core transcription factor in YFJP treatment of HCC by transcriptional regulatory network construction and topological analysis. ...

Reference:

FoxO1 as a Hub in Immunosenescence Induced by Hepatocellular Carcinoma and the Effect of Yangyin Fuzheng Jiedu Prescription
Identification of FOXO1 as a geroprotector in human synovium through single-nucleus transcriptomic profiling

Protein & Cell

Feifei Liu

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Yi Lu

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Xuebao Wang

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... Eight young monkeys (4-6 years old) and eight old monkeys (18-21 years old) of both genders from Southeast Asia were housed at 25 °C with 40-60% humidity at a certified Primate Research Center in Beijing (Xieerxin Biology Resource) [68][69][70][71][72][73] . NOD-SCID mice and C57BL/6J mice, purchased from HFK Bioscience Co., Ltd. ...

Reference:

SIRT5 safeguards against primate skeletal muscle ageing via desuccinylation of TBK1
Nuclear lamina erosion-induced resurrection of endogenous retroviruses underlies neuronal aging
  • Citing Article

  • November 2023

Cell Reports

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... Living organisms display a sophisticated organization throughout their lifetimes, characterized by intricate system-wide coordination and specialized organspecific compartmental functions [1][2][3]. Aging, a complex physiological process, strongly correlates with the risk of chronic illnesses such as metabolic disorders, cardiovascular diseases, and neurodegenerative conditions [4]. This process involves a multiorgan aging network, where primary organ aging progresses to affect multiple systems [5,6]. ...

Reference:

Integrative cross‐tissue analysis unveils complement‐immunoglobulin augmentation and dysbiosis‐related fatty acid metabolic remodeling during mammalian aging
CHIT1-positive microglia drive motor neuron aging in the primate spinal cord

Nature

Shuhui Sun

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... Living organisms display a sophisticated organization throughout their lifetimes, characterized by intricate system-wide coordination and specialized organspecific compartmental functions [1][2][3]. Aging, a complex physiological process, strongly correlates with the risk of chronic illnesses such as metabolic disorders, cardiovascular diseases, and neurodegenerative conditions [4]. This process involves a multiorgan aging network, where primary organ aging progresses to affect multiple systems [5,6]. ...

Reference:

Integrative cross‐tissue analysis unveils complement‐immunoglobulin augmentation and dysbiosis‐related fatty acid metabolic remodeling during mammalian aging
Decoding aging-dependent regenerative decline across tissues at single-cell resolution
  • Citing Article

  • October 2023

Cell Stem Cell

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Muzhao Xiong

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