3D facial imaging: a novel approach for metabolic abnormalities risk profiling.

The human face harbors a rich tapestry of complex phenotypic information spanning genetic, environmental, and physiological dimensions. While facial images excel in diagnosing genetic diseases, their untapped potential for predicting metabolic health presents an intriguing prospect. Metabolic Syndrome (MetS), marked by a constellation of metabolic abnormalities, poses a significant risk for various chronic diseases.

Innovations in aging biology: highlights from the ARDD emerging science & technologies workshop.

The field of biogerontology has established itself through significant lines of research in recent decades. However, despite early breakthroughs, progress in understanding the aging process has been slow. To push the field forward, new methodologies and technologies are likely needed to unravel the complexity of aging.

Conversion of placental hemogenic endothelial cells to hematopoietic stem and progenitor cells.

Hematopoietic stem and progenitor cells (HSPCs) are critical for the treatment of blood diseases in clinic. However, the limited source of HSPCs severely hinders their clinical application. In the embryo, hematopoietic stem cells (HSCs) arise from hemogenic endothelial (HE) cells lining the major arteries in vivo.

Oral microbiota in aging and diseases.

Human microbiomes are microbial populations that form a symbiotic relationship with humans. There are up to 1000 species on the surface of human skin and mucosal system, among which gut microbiota attracts the most interest. As the beginning of the digestive tract, oral cavity is also an important microbial habitat in the human body which is the first line of defense against pathogens entering the body.

Characterizing biomarkers of ageing in Singaporeans: the ABIOS observational study protocol.

Ageing is the primary driver of age-associated chronic diseases and conditions. Asian populations have traditionally been underrepresented in studies understanding age-related diseases. Thus, the Ageing BIOmarker Study in Singaporeans (ABIOS) aims to characterise biomarkers of ageing in Singaporeans, exploring associations between molecular, physiological, and digital biomarkers of ageing.

Exploring the relationship among Alzheimer's disease, aging and cognitive scores through neuroimaging-based approach.

Alzheimer's disease (AD) is a fatal neurodegenerative disorder, with the Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) serving significant roles in monitoring its progression. We hypothesize that while cognitive assessment scores can detect AD-related brain changes, the targeted brain regions may differ. Additionally, given AD's strong association with aging, we propose that specific brain regions are influenced by both AD pathology and aging, exhibiting strong correlations with both.

Thermal facial image analyses reveal quantitative hallmarks of aging and metabolic diseases.

Although human core body temperature is known to decrease with age, the age dependency of facial temperature and its potential to indicate aging rate or aging-related diseases remains uncertain. Here, we collected thermal facial images of 2,811 Han Chinese individuals 20-90 years old, developed the ThermoFace method to automatically process and analyze images, and then generated thermal age and disease prediction models. The ThermoFace deep learning model for thermal facial age has a mean absolute deviation of about 5 years in cross-validation and 5.

Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators.

Cellular senescence underlies many aging-related pathologies, but its heterogeneity poses challenges for studying and targeting senescent cells. We present here a machine learning program senescent cell identification (SenCID), which accurately identifies senescent cells in both bulk and single-cell transcriptome. Trained on 602 samples from 52 senescence transcriptome datasets spanning 30 cell types, SenCID identifies six major senescence identities (SIDs).

Coordinate-wise monotonic transformations enable privacy-preserving age estimation with 3D face point cloud.

The human face is a valuable biomarker of aging, but the collection and use of its image raise significant privacy concerns. Here we present an approach for facial data masking that preserves age-related features using coordinate-wise monotonic transformations. We first develop a deep learning model that estimates age directly from non-registered face point clouds with high accuracy and generalizability.

Identification of the metaphyseal skeletal stem cell building trabecular bone.

Skeletal stem cells (SSCs) that are capable of self-renewal and multipotent differentiation contribute to bone development and homeostasis. Several populations of SSCs at different skeletal sites have been reported. Here, we identify a metaphyseal SSC (mpSSC) population whose transcriptional landscape is distinct from other bone mesenchymal stromal cells (BMSCs).

Application of AI in biological age prediction.

The development of anti-aging interventions requires quantitative measurement of biological age. Machine learning models, known as "aging clocks," are built by leveraging diverse aging biomarkers that vary across lifespan to predict biological age. In addition to traditional aging clocks harnessing epigenetic signatures derived from bulk samples, emerging technologies allow the biological age estimating at single-cell level to dissect cellular diversity in aging tissues.

Tissue-specific profiling of age-dependent miRNAomic changes in Caenorhabditis elegans.

Ageing exhibits common and distinct features in various tissues, making it critical to decipher the tissue-specific ageing mechanisms. MiRNAs are essential regulators in ageing and are recently highlighted as a class of intercellular messengers. However, little is known about the tissue-specific transcriptomic changes of miRNAs during ageing.

The ticking of aging clocks.

Computational models that measure biological age and aging rate regardless of chronological age are called aging clocks. The underlying counting mechanisms of the intrinsic timers of these clocks are still unclear. Molecular mediators and determinants of aging rate point to the key roles of DNA damage, epigenetic drift, and inflammation.

Human PBMC scRNA-seq-based aging clocks reveal ribosome to inflammation balance as a single-cell aging hallmark and super longevity.

Quantifying aging rate is important for evaluating age-associated decline and mortality. A blood single-cell RNA sequencing dataset for seven supercentenarians (SCs) was recently generated. Here, we generate a reference 28-sample aging cohort to compute a single-cell level aging clock and to determine the biological age of SCs.

Spatial Reconstruction of Oligo and Single Cells by De Novo Coalescent Embedding of Transcriptomic Networks.

Single cell RNA-seq (scRNA-seq) profiles conceal temporal and spatial tissue developmental information. De novo reconstruction of single cell temporal trajectory has been fairly addressed, but reverse engineering single cell 3D spatial tissue organization is hitherto landmark based, and de novo spatial reconstruction is a compelling computational open problem. Here it is shown that a proposed algorithm for de novo coalescent embedding (D-CE) of oligo/single cell transcriptomic networks can help to address this problem.

Nuclear lamina erosion-induced resurrection of endogenous retroviruses underlies neuronal aging.

The primate frontal lobe (FL) is sensitive to aging-related neurocognitive decline. However, the aging-associated molecular mechanisms remain unclear. Here, using physiologically aged non-human primates (NHPs), we depicted a comprehensive landscape of FL aging with multidimensional profiling encompassing bulk and single-nucleus transcriptomes, quantitative proteome, and DNA methylome.

Biomarkers of aging.

Aging biomarkers are a combination of biological parameters to (i) assess age-related changes, (ii) track the physiological aging process, and (iii) predict the transition into a pathological status. Although a broad spectrum of aging biomarkers has been developed, their potential uses and limitations remain poorly characterized. An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research: How old are we? Why do we get old? And how can we age slower? This review aims to address this need.

LncRNAs: the missing link to senescence nuclear architecture.

During cellular senescence and organismal aging, cells display various molecular and morphological changes. Although many aging-related long noncoding RNAs (lncRNAs) are highly associated with senescence-associated secretory phenotype, the roles of lncRNAs in senescence-associated nuclear architecture and morphological changes are just starting to emerge. Here I review lncRNAs associated with nuclear structure establishment and maintenance, their aging-related changes, and then focus on the pervasive, yet underappreciated, role of RNA double-strand DNA triplexes for lncRNAs to recognize targeted genomic regions, making lncRNAs the nexus between DNA and proteins to regulate nuclear structural changes.

Immunosuppression Induced by Brain-Specific HDAC6 Knockdown Improves Aging Performance in .

Unlabelled: HDAC6 is involved in several biological processes related to aging-associated diseases. However, it was unknown whether HDAC6 could directly regulate lifespan and healthspan. We found that HDAC6 knockdown induced transcriptome changes to attenuate the aging changes in the head, particularly on the inflammation and innate immunity-related genes.