112 research outputs found
Innate and Adaptive Immunity in Aging and Longevity: The Foundation of Resilience
The interrelation of the processes of immunity and senescence now receives an unprecedented emphasis during the COVID-19 pandemic, which brings to the fore the critical need to combat immunosenescence and improve the immune function and resilience of older persons. Here we review the historical origins and the current state of the science of innate and adaptive immunity in aging and longevity. From the modern point of view, innate and adaptive immunity are not only affected by aging but also are important parts of its underlying mechanisms. Excessive levels or activity of antimicrobial peptides, C-reactive protein, complement system, TLR/NF-ΞΊB, cGAS/STING/IFN 1,3 and AGEs/RAGE pathways, myeloid cells and NLRP3 inflammasome, declined levels of NK cells in innate immunity, thymus involution and decreased amount of naive T-cells in adaptive immunity, are biomarkers of aging and predisposition factors for cellular senescence and aging-related pathologies. Long-living species, human centenarians, and women are characterized by less inflamm-aging and decelerated immunosenescence. Despite recent progress in understanding, the harmonious theory of immunosenescence is still developing. Geroprotectors targeting these mechanisms are just emerging and are comprehensively discussed in this article
The Neuronal Overexpression of Gclc in Drosophila melanogaster Induces Life Extension With Longevity-Associated Transcriptomic Changes in the Thorax
Some effects of aging in animals are tissue-specific. In D. melanogaster neuronal overexpression of Gclc increases lifespan and improves certain physiological parameters associated with health benefits such as locomotor activity, circadian rhythmicity, and stress resistance. Our previous transcriptomic analyses of Drosophila heads, primarily composed of neuronal tissue, revealed significant changes in expression levels of genes involved in aging-related signaling pathways (Jak-STAT, MAPK, FOXO, Notch, mTOR, TGF-beta), translation, protein processing in endoplasmic reticulum, proteasomal degradation, glycolysis, oxidative phosphorylation, apoptosis, regulation of circadian rhythms, differentiation of neurons, synaptic plasticity, and transmission. Considering that various tissues age differently and age-related gene expression changes are tissue-specific, we investigated the effects of neuronal Gclc overexpression on gene expression levels in the imago thorax, which is primarily composed of muscles. A total of 58 genes were found to be differentially expressed between thoraces of control and Gclc overexpressing flies. The Gclc level demonstrated associations with expression of genes involved in the circadian rhythmicity, the genes in categories related to the muscle system process and the downregulation of genes involved in proteolysis. Most of the functional categories altered by Gclc overexpression related to metabolism including Drug metabolism, Metabolism of xenobiotics by cytochrome P450, Glutathione metabolism, Starch and sucrose metabolism, Citrate cycle (TCA cycle), One carbon pool by folate. Thus, the transcriptomic changes caused by neuron-specific Gclc overexpression in the thorax were less pronounced than in the head and affected pathways also differed from previous results. Although these pathways don't belong to the canonical longevity pathways, we suggest that they could participate in the delay of aging of Gclc overexpressing flies
eXplainable Artificial Intelligence (XAI) in aging clock models
eXplainable Artificial Intelligence (XAI) is a rapidly progressing field of
machine learning, aiming to unravel the predictions of complex models. XAI is
especially required in sensitive applications, e.g. in health care, when
diagnosis, recommendations and treatment choices might rely on the decisions
made by artificial intelligence systems. AI approaches have become widely used
in aging research as well, in particular, in developing biological clock models
and identifying biomarkers of aging and age-related diseases. However, the
potential of XAI here awaits to be fully appreciated. We discuss the
application of XAI for developing the "aging clocks" and present a
comprehensive analysis of the literature categorized by the focus on particular
physiological systems
Cavity-QED simulation of a quantum metamaterial with tunable disorder
We explore experimentally a quantum metamaterial based on a superconducting chip with 25 frequency-tunable transmon qubits coupled to a common coplanar resonator. The collective bright and dark modes are probed via the microwave response, i.e., by measuring the transmission amplitude of an external microwave signal. All qubits have individual control and readout lines. Their frequency tunability allows to change the number N of resonantly coupled qubits and also to introduce a disorder in their excitation frequencies with preassigned distributions. While increasing N, we demonstrate the expected N scaling law for the energy gap (Rabi splitting) between bright modes around the cavity frequency. By introducing a controllable disorder and averaging the transmission amplitude over a large number of realizations, we demonstrate a decay of mesoscopic fluctuations which mimics an approach towards the thermodynamic limit. The collective bright states survive in the presence of disorder when the strength of individual qubit coupling to the cavity dominates over the disorder strength
ΠΡΠΎΠ³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ ΠΠ’ Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ Ρ ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΈΡ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΠΉ Π΄ΠΈΠ²Π΅ΡΡΠΈΠΊΡΠ»ΡΡΠ½ΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΠΈ ΠΎΠ±ΠΎΠ΄ΠΎΡΠ½ΠΎΠΉ ΠΊΠΈΡΠΊΠΈ
Objective: to determine the diagnostic effectiveness of computed tomography (CT) in predicting the course of the disease in patients with chronic inflammatory complications of diverticular disease (DD).Material and methods. The study included 70 patients with a complicated course of colon diverticular disease in the phase of exacerbation of the chronic inflammatory process. All patients underwent CT of the abdominal cavity with intravenous contrast to assess the type and severity of inflammatory changes in the colon and surrounding tissues in the area of localization of diverticula. All patients received conservative treatment and were monitored as part of the ongoing study for 12 months from the moment of initial treatment at the Center. Surgical intervention due to the ineffectiveness of conservative therapy or the recurrence of the inflammatory process during the established follow-up period was considered as an unfavorable outcome of the disease (42/60%). The positive effect of drug therapy without signs of a return of the clinical picture of inflammation within 12 months was considered as a favorable outcome (28/40%). A statistical analysis of CT signs of inflammatory changes in various DD outcomes was performed to identify prognostic CT parameters.Results. Statistically significant differences were revealed between the severity of inflammatory changes according to CT data for different outcomes of the disease. In the favorable outcome group, the main part (23/28.82%) were patients with diverticulitis, in the unfavorable outcome group, 2/3 of patients (29/42.64%) were diagnosed with pericolic infiltrates, including abscesses/cavities, and colon fistulas. It was found that the thickness of the intestinal wall, the extent of inflammatory changes in the intestinal wall, the extent of inflammatory infiltration of pericolic fiber, the symptom of βcentipedeβ, the accumulation of fluid in the pericolic region statistically significantly differed with different outcomes of chronic inflammatory complications of diverticular disease. Πultivariate Cox proportional hazard model revealed two main predictors of the onset of an unfavorable outcome β thickening of the intestinal wall and the presence of fluid in the pericolic region. Thickening of the intestinal wall at values equal to or greater than 0,6 cm increased the risk of an unfavorable outcome by 4.69 times, and the presence of fluid by 4.52 times.Conclusion. The use in clinical practice of the revealed CT predictors of the onset of an unfavorable outcome in chronic inflammatory complications of DB can serve as one of the factors for deciding on elective surgery in this category of patients.Β Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ: ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΡΡ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ (ΠΠ’) Π² ΠΏΡΠΎΠ³Π½ΠΎΠ·ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
Ρ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΠΌΠΈ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΡΠΌΠΈ Π΄ΠΈΠ²Π΅ΡΡΠΈΠΊΡΠ»ΡΡΠ½ΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΠΈ (ΠΠ).ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΠΊΠ»ΡΡΠ΅Π½ΠΎ 70 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½Π½ΡΠΌ ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ΠΌ ΠΠ ΠΎΠ±ΠΎΠ΄ΠΎΡΠ½ΠΎΠΉ ΠΊΠΈΡΠΊΠΈ Π² ΡΠ°Π·Ρ ΠΎΠ±ΠΎΡΡΡΠ΅Π½ΠΈΡ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ°. ΠΡΠ΅ΠΌ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌ Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π° ΠΠ’ Π±ΡΡΡΠ½ΠΎΠΉ ΠΏΠΎΠ»ΠΎΡΡΠΈ Ρ Π²Π½ΡΡΡΠΈΠ²Π΅Π½Π½ΡΠΌ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π²ΠΈΠ΄Π° ΠΈ ΡΡΠΆΠ΅ΡΡΠΈ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΎΠ±ΠΎΠ΄ΠΎΡΠ½ΠΎΠΉ ΠΊΠΈΡΠΊΠΈ ΠΈ ΠΎΠΊΡΡΠΆΠ°ΡΡΠΈΡ
ΡΠΊΠ°Π½Π΅ΠΉ Π² ΠΎΠ±Π»Π°ΡΡΠΈ Π»ΠΎΠΊΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π΄ΠΈΠ²Π΅ΡΡΠΈΠΊΡΠ»ΠΎΠ². ΠΡΠ΅ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ ΠΏΠΎΠ»ΡΡΠΈΠ»ΠΈ ΠΊΠΎΠ½ΡΠ΅ΡΠ²Π°ΡΠΈΠ²Π½ΠΎΠ΅ Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΠΈ Π½Π°Ρ
ΠΎΠ΄ΠΈΠ»ΠΈΡΡ ΠΏΠΎΠ΄ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΠ΅ΠΌ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠΌΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠΈ 12 ΠΌΠ΅Ρ Ρ ΠΌΠΎΠΌΠ΅Π½ΡΠ° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ°ΡΠ΅Π½ΠΈΡ Π² Π¦Π΅Π½ΡΡ. ΠΠΏΠ΅ΡΠ°ΡΠΈΠ²Π½ΠΎΠ΅ Π²ΠΌΠ΅ΡΠ°ΡΠ΅Π»ΡΡΡΠ²ΠΎ Π² ΡΠ²ΡΠ·ΠΈ Ρ Π½Π΅ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡΡ ΠΊΠΎΠ½ΡΠ΅ΡΠ²Π°ΡΠΈΠ²Π½ΠΎΠΉ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΠΈΠ»ΠΈ ΡΠ΅ΡΠΈΠ΄ΠΈΠ²ΠΎΠΌ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ° Π² ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½Π½ΡΠΉ ΠΏΠ΅ΡΠΈΠΎΠ΄ Π½Π°Π±Π»ΡΠ΄Π΅Π½ΠΈΡ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π»ΠΎΡΡ ΠΊΠ°ΠΊ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΉ ΠΈΡΡ
ΠΎΠ΄ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ (42/60%). ΠΠΎΠ»ΠΎΠΆΠΈΡΠ΅Π»ΡΠ½ΡΠΉ ΡΡΡΠ΅ΠΊΡ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΠ΅ΡΠ°ΠΏΠΈΠΈ Π±Π΅Π· ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² Π²ΠΎΠ·Π²ΡΠ°ΡΠ° ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠ°ΡΡΠΈΠ½Ρ Π²ΠΎΡΠΏΠ°Π»Π΅Π½ΠΈΡ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 12 ΠΌΠ΅Ρ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π»ΡΡ ΠΊΠ°ΠΊ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΡΠΉ ΠΈΡΡ
ΠΎΠ΄ (28/40%). ΠΡΠΎΠ²Π΅Π΄Π΅Π½ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°Π½Π°Π»ΠΈΠ· ΠΠ’-ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΏΡΠΈ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΈΡΡ
ΠΎΠ΄Π°Ρ
ΠΠ Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΠ’-ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ².Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΡΠ²Π»Π΅Π½Ρ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡ ΠΌΠ΅ΠΆΠ΄Ρ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΠΎΡΡΡΡ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΠΠ’ ΠΏΡΠΈ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΈΡΡ
ΠΎΠ΄Π°Ρ
Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΡ. Π Π³ΡΡΠΏΠΏΠ΅ Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡ
ΠΎΠ΄Π° ΠΎΡΠ½ΠΎΠ²Π½ΡΡ ΡΠ°ΡΡΡ (23/28,82%) ΡΠΎΡΡΠ°Π²ΠΈΠ»ΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ Ρ Π΄ΠΈΠ²Π΅ΡΡΠΈΠΊΡΠ»ΠΈΡΠΎΠΌ, Β Π² Π³ΡΡΠΏΠΏΠ΅ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡ
ΠΎΠ΄Π° Ρ 2/3 Π±ΠΎΠ»ΡΠ½ΡΡ
(29/42,64%) Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠΎΠ²Π°Π½Ρ ΠΏΠ°ΡΠ°ΠΊΠΈΡΠ΅ΡΠ½ΡΠ΅ ΠΈΠ½ΡΠΈΠ»ΡΡΡΠ°ΡΡ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Ρ Π°Π±ΡΡΠ΅ΡΡΠ°ΠΌΠΈ/ΠΏΠΎΠ»ΠΎΡΡΡΠΌΠΈ, ΠΈ ΡΠ²ΠΈΡΠΈ ΠΎΠ±ΠΎΠ΄ΠΎΡΠ½ΠΎΠΉ ΠΊΠΈΡΠΊΠΈ. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠΎΠ»ΡΠΈΠ½Π° ΠΊΠΈΡΠ΅ΡΠ½ΠΎΠΉ ΡΡΠ΅Π½ΠΊΠΈ, ΠΏΡΠΎΡΡΠΆΠ΅Π½Π½ΠΎΡΡΡ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΊΠΈΡΠ΅ΡΠ½ΠΎΠΉ ΡΡΠ΅Π½ΠΊΠΈ, ΠΏΡΠΎΡΡΠΆΠ΅Π½Π½ΠΎΡΡΡ Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠΈΠ»ΡΡΡΠ°ΡΠΈΠΈ ΠΏΠ΅ΡΠΈΠΊΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΊΠ»Π΅ΡΡΠ°ΡΠΊΠΈ, ΡΠΈΠΌΠΏΡΠΎΠΌ βΡΠΎΡΠΎΠΊΠΎΠ½ΠΎΠΆΠΊΠΈβ, ΡΠΊΠΎΠΏΠ»Π΅Π½ΠΈΠ΅ ΠΆΠΈΠ΄ΠΊΠΎΡΡΠΈ Π² ΠΏΠ΅ΡΠΈΠΊΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎ ΡΠ°Π·Π»ΠΈΡΠ°Π»ΠΈΡΡ ΠΏΡΠΈ ΡΠ°Π·Π½ΡΡ
ΠΈΡΡ
ΠΎΠ΄Π°Ρ
Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΠΉ ΠΠ. ΠΠ½ΠΎΠ³ΠΎΡΠ°ΠΊΡΠΎΡΠ½ΡΠΉ ΠΠΎΠΊΡ-ΡΠ΅Π³ΡΠ΅ΡΡΠΈΠΎΠ½Π½ΡΠΉ Π°Π½Π°Π»ΠΈΠ· Π²ΡΡΠ²ΠΈΠ» Π΄Π²Π° ΠΎΡΠ½ΠΎΠ²Π½ΡΡ
ΠΏΡΠ΅Π΄ΠΈΠΊΡΠΎΡΠ°Β Π½Π°ΡΡΡΠΏΠ»Π΅Π½ΠΈΡ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡ
ΠΎΠ΄Π° β ΡΡΠΎΠ»ΡΠ΅Π½ΠΈΠ΅ ΠΊΠΈΡΠ΅ΡΠ½ΠΎΠΉ ΡΡΠ΅Π½ΠΊΠΈ ΠΈ Π½Π°Π»ΠΈΡΠΈΠ΅ ΠΆΠΈΠ΄ΠΊΠΎΡΡΠΈ Π² ΠΏΠ΅ΡΠΈΠΊΠΎΠ»ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΎΠ±Π»Π°ΡΡΠΈ. Π£ΡΠΎΠ»ΡΠ΅Π½ΠΈΠ΅ ΠΊΠΈΡΠ΅ΡΠ½ΠΎΠΉ ΡΡΠ΅Π½ΠΊΠΈ ΠΏΡΠΈ Π·Π½Π°ΡΠ΅Π½ΠΈΡΡ
, ΡΠ°Π²Π½ΡΡ
ΠΈΠ»ΠΈ Π±ΠΎΠ»Π΅Π΅ 0,6 ΡΠΌ, Π² 4,69 ΡΠ°Π·Π° ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π»ΠΎ ΡΠΈΡΠΊ Π½Π°ΡΡΡΠΏΠ»Π΅Π½ΠΈΡ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡ
ΠΎΠ΄Π°, Π° Π½Π°Π»ΠΈΡΠΈΠ΅ ΠΆΠΈΠ΄ΠΊΠΎΡΡΠΈ Π² 4,52 ΡΠ°Π·Π°.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ Π² ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅ Π²ΡΡΠ²Π»Π΅Π½Π½ΡΡ
ΠΠ’-ΠΏΡΠ΅Π΄ΠΈΠΊΡΠΎΡΠΎΠ² Π½Π°ΡΡΡΠΏΠ»Π΅Π½ΠΈΡ Π½Π΅Π±Π»Π°Π³ΠΎΠΏΡΠΈΡΡΠ½ΠΎΠ³ΠΎ ΠΈΡΡ
ΠΎΠ΄Π° ΠΏΡΠΈ Ρ
ΡΠΎΠ½ΠΈΡΠ΅ΡΠΊΠΈΡ
Π²ΠΎΡΠΏΠ°Π»ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΎΡΠ»ΠΎΠΆΠ½Π΅Π½ΠΈΡΡ
ΠΠ ΠΌΠΎΠΆΠ΅Ρ ΠΏΠΎΡΠ»ΡΠΆΠΈΡΡ ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π΄Π»Ρ ΠΏΡΠΈΠ½ΡΡΠΈΡ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΠΎ ΠΏΠ»Π°Π½ΠΎΠ²ΠΎΠΌ Ρ
ΠΈΡΡΡΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΌ Π²ΠΌΠ΅ΡΠ°ΡΠ΅Π»ΡΡΡΠ²Π΅ Ρ ΡΡΠΎΠΉ ΠΊΠ°ΡΠ΅Π³ΠΎΡΠΈΠΈ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ²
The Digital Ageing Atlas: integrating the diversity of age-related changes into a unified resource
Multiple studies characterizing the human ageing phenotype have been conducted for decades. However, there is no centralized resource in which data on multiple age-related changes are collated. Currently, researchers must consult several sources, including primary publications, in order to obtain age-related data at various levels. To address this and facilitate integrative, system-level studies of ageing we developed the Digital Ageing Atlas (DAA). The DAA is a one-stop collection of human age-related data covering different biological levels (molecular, cellular, physiological, psychological and pathological) that is freely available online (http://ageing-map.org/). Each of the >3000 age-related changes is associated with a specific tissue and has its own page displaying a variety of information, including at least one reference. Age-related changes can also be linked to each other in hierarchical trees to represent different types of relationships. In addition, we developed an intuitive and user-friendly interface that allows searching, browsing and retrieving information in an integrated and interactive fashion. Overall, the DAA offers a new approach to systemizing ageing resources, providing a manually-curated and readily accessible source of age-related changes
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