Do early midlife work characteristics predict 20-year change in control beliefs?

Previous research showed the importance of control beliefs for many life outcomes. The present study examines associations between subjectively perceived work environment and objectively measured work activities at the beginning of midlife as a central developmental phase in the context of work, with control beliefs across the subsequent 20 years. We analyzed four-wave longitudinal data from N = 374 participants (born 1950-1952; Mage baseline = 44 years, SD = 1; 44% women) from the Interdisciplinary Longitudinal Study of Adult Development and Aging within a structural equation modeling framework. Over 20 years and overall, internal control beliefs were stable, while external control beliefs decreased. Individuals who reported higher task variety and better social integration at work at baseline also reported higher levels of control beliefs for positive life outcomes. In addition, higher social integration at work at baseline was related to lower levels of external control beliefs. Work characteristics at baseline were not associated with individual differences in change in control beliefs across the 20-year observational interval. In summary, our findings suggest that work experiences at the prime of job-related development around the midst of the fifth decade of life do not play a major role in subsequent control beliefs development across 20 years. However, investigations measuring control beliefs as well as work characteristics continuously over a long period of time are necessary to shed light on reciprocal influences between work and personality. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics.

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Development of combination therapies with BTK inhibitors and dasatinib to treat CNS-infiltrating E2A-PBX1+/preBCR+ ALL.

ABSTRACT: The t(1;19) translocation, encoding the oncogenic fusion protein E2A (TCF3)-PBX1, is involved in acute lymphoblastic leukemia (ALL) and associated with a pre-B-cell receptor (preBCR+) phenotype. Relapse in patients with E2A-PBX1+ ALL frequently occurs in the central nervous system (CNS). Therefore, there is a medical need for the identification of CNS active regimens for the treatment of E2A-PBX1+/preBCR+ ALL. Using unbiased short hairpin RNA (shRNA) library screening approaches, we identified Bruton tyrosine kinase (BTK) as a key gene involved in both proliferation and dasatinib sensitivity of E2A-PBX1+/preBCR+ ALL. Depletion of BTK by shRNAs resulted in decreased proliferation of dasatinib-treated E2A-PBX1+/preBCR+ cells compared with control-transduced cells. Moreover, the combination of dasatinib with BTK inhibitors (BTKi; ibrutinib, acalabrutinib, or zanubrutinib) significantly decreased E2A-PBX1+/preBCR+ human and murine cell proliferation, reduced phospholipase C gamma 2 (PLCG2) and BTK phosphorylation and total protein levels and increased disease-free survival of mice in secondary transplantation assays, particularly reducing CNS-leukemic infiltration. Hence, dasatinib with ibrutinib reduced pPLCG2 and pBTK in primary ALL patient samples, including E2A-PBX1+ ALLs. In summary, genetic depletion and pharmacological inhibition of BTK increase dasatinib effects in human and mouse with E2A-PBX1+/preBCR+ ALL across most of performed assays, with the combination of dasatinib and BTKi proving effective in reducing CNS infiltration of E2A-PBX1+/preBCR+ ALL cells in vivo.

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

Enrichment, Characterization, and Proteomic Profiling of Small Extracellular Vesicles Derived from Human Limbal Mesenchymal Stromal Cells and Melanocytes.

Limbal epithelial progenitor cells (LEPC) rely on their niche environment for proper functionality and self-renewal. While extracellular vesicles (EV), specifically small EVs (sEV), have been proposed to support LEPC homeostasis, data on sEV derived from limbal niche cells like limbal mesenchymal stromal cells (LMSC) remain limited, and there are no studies on sEVs from limbal melanocytes (LM). In this study, we isolated sEV from conditioned media of LMSC and LM using a combination of tangential flow filtration and size exclusion chromatography and characterized them by nanoparticle tracking analysis, transmission electron microscopy, Western blot, multiplex bead arrays, and quantitative mass spectrometry. The internalization of sEV by LEPC was studied using flow cytometry and confocal microscopy. The isolated sEVs exhibited typical EV characteristics, including cell-specific markers such as CD90 for LMSC-sEV and Melan-A for LM-sEV. Bioinformatics analysis of the proteomic data suggested a significant role of sEVs in extracellular matrix deposition, with LMSC-derived sEV containing proteins involved in collagen remodeling and cell matrix adhesion, whereas LM-sEV proteins were implicated in other cellular bioprocesses such as cellular pigmentation and development. Moreover, fluorescently labeled LMSC-sEV and LM-sEV were taken up by LEPC and localized to their perinuclear compartment. These findings provide valuable insights into the complex role of sEV from niche cells in regulating the human limbal stem cell niche.

Cathepsin D inhibition during neuronal differentiation selectively affects individual proteins instead of overall protein turnover.

Cathepsin D (CTSD) is a lysosomal aspartic protease and its inherited deficiency causes a severe pediatric neurodegenerative disease called neuronal ceroid lipofuscinosis (NCL) type 10. The lysosomal dysfunction in the affected patients leads to accumulation of undigested lysosomal cargo especially in none-dividing cells, such as neurons, resulting in death shortly after birth. To explore which proteins are mainly affected by the lysosomal dysfunction due to CTSD deficiency, Lund human mesencephalic (LUHMES) cells, capable of inducible dopaminergic neuronal differentiation, were treated with Pepstatin A. This inhibitor of "acidic" aspartic proteases caused accumulation of acidic intracellular vesicles in differentiating LUHMES cells. Pulse-chase experiments involving stable isotope labelling with amino acids in cell culture (SILAC) with subsequent mass-spectrometric protein identification and quantification were performed. By this approach, we studied the degradation and synthesis rates of 695 and 680 proteins during early and late neuronal LUHMES differentiation, respectively. Interestingly, lysosomal bulk proteolysis was not altered upon Pepstatin A treatment. Instead, the protease inhibitor selectively changed the turnover of individual proteins. Especially proteins belonging to the mitochondrial energy supply system were differentially degraded during early and late neuronal differentiation indicating a high energy demand as well as stress level in LUHMES cells treated with Pepstatin A.

Mass spectrometry-based proteomic applications in dental implants research.

Dental implants have been established as successful treatment options for missing teeth with steadily increasing demands. Today, the primary areas of research in dental implantology revolve around osseointegration, soft and hard tissue grafting as well as peri-implantitis diagnostics, prevention, and treatment. This review provides a comprehensive overview of the current literature on the application of MS-based proteomics in dental implant research, highlights how explorative proteomics provided insights into the biology of peri-implant soft and hard tissues and how proteomics facilitated the stratification between healthy and diseased implants, enabling the identification of potential new diagnostic markers. Additionally, this review illuminates technical aspects, and provides recommendations for future study designs based on the current evidence.

Neoadjuvant chemo- or chemo-radiation-therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo-radiation (NCRT) therapy. We employed data-independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment-naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment-naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post-NCT and post-NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment-naïve PDAC. Further analyses on patient survival and protein expression identified treatment-specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment-naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.

Comparative analyses of Netherton syndrome patients and Spink5 conditional knock-out mice uncover disease-relevant pathways.

Netherton syndrome (NS) is a rare skin disease caused by loss-of-function mutations in the serine peptidase inhibitor Kazal type 5 (SPINK5) gene. Disease severity and the lack of efficacious treatments call for a better understanding of NS mechanisms. Here we describe a novel and viable, Spink5 conditional knock-out (cKO) mouse model, allowing to study NS progression. By combining transcriptomics and proteomics, we determine a disease molecular profile common to mouse models and NS patients. Spink5 cKO mice and NS patients share skin barrier and inflammation signatures defined by up-regulation and increased activity of proteases, IL-17, IL-36, and IL-20 family cytokine signaling. Systemic inflammation in Spink5 cKO mice correlates with disease severity and is associated with thymic atrophy and enlargement of lymph nodes and spleen. This systemic inflammation phenotype is marked by neutrophils and IL-17/IL-22 signaling, does not involve primary T cell immunodeficiency and is independent of bacterial infection. By comparing skin transcriptomes and proteomes, we uncover several putative substrates of tissue kallikrein-related proteases (KLKs), demonstrating that KLKs can proteolytically regulate IL-36 pro-inflammatory cytokines. Our study thus provides a conserved molecular framework for NS and reveals a KLK/IL-36 signaling axis, adding new insights into the disease mechanisms and therapeutic targets.

Proteometabolomics of initial and recurrent glioblastoma highlights an increased immune cell signature with altered lipid metabolism.

BACKGROUND: There is an urgent need to better understand the mechanisms associated with the development, progression, and onset of recurrence after initial surgery in glioblastoma (GBM). The use of integrative phenotype-focused -omics technologies such as proteomics and lipidomics provides an unbiased approach to explore the molecular evolution of the tumor and its associated environment. METHODS: We assembled a cohort of patient-matched initial (iGBM) and recurrent (rGBM) specimens of resected GBM. Proteome and metabolome composition were determined by mass spectrometry-based techniques. We performed neutrophil-GBM cell coculture experiments to evaluate the behavior of rGBM-enriched proteins in the tumor microenvironment. ELISA-based quantitation of candidate proteins was performed to test the association of their plasma concentrations in iGBM with the onset of recurrence. RESULTS: Proteomic profiles reflect increased immune cell infiltration and extracellular matrix reorganization in rGBM. ASAH1, SYMN, and GPNMB were highly enriched proteins in rGBM. Lipidomics indicates the downregulation of ceramides in rGBM. Cell analyses suggest a role for ASAH1 in neutrophils and its localization in extracellular traps. Plasma concentrations of ASAH1 and SYNM show an association with time to recurrence. CONCLUSIONS: We describe the potential importance of ASAH1 in tumor progression and development of rGBM via metabolic rearrangement and showcase the feedback from the tumor microenvironment to plasma proteome profiles. We report the potential of ASAH1 and SYNM as plasma markers of rGBM progression. The published datasets can be considered as a resource for further functional and biomarker studies involving additional -omics technologies.

Three facets of emotion regulation in old and very old age: Strategy use, effectiveness, and variability.

The ability to regulate emotions in stressful situations is an important building block for high well-being across the lifespan. Yet, very little is known about how old and very old adults regulate their emotions. In this study, 123 young old adults (Mage = 67.18, SD = 0.94) and 47 very old adults (Mage = 86.70, SD = 1.46) were prompted 6 times a day for 7 consecutive days to report both their stressors and 10 emotion regulation strategies. Overall, there was little indication of age differences in the use of emotion regulation strategies during exposure to stressors, but very old, as compared with young old, individuals used three of the 10 strategies considered here more intensively. The 10 emotion regulation strategies were similarly effective across age groups based on their association with perceived overall emotion regulation success. We also did not find age group differences in within-strategy variability, defined as the variation in using a given strategy across stressor situations. By contrast, between-strategy variability, defined as the selective use of fewer rather than many strategies across stressor situations, was lower for very old participants. Only between-strategy, and not within-strategy, variability contributed to overall emotion regulation success. There was no age group difference in this regard. Taken together, the evidence suggests small age differences in emotion regulation if at all. This is noteworthy given the advanced age of the very old subsample in this study and the deficits in multiple domains of functioning reported in the literature for this advanced age. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Tpr Misregulation in Hippocampal Neural Stem Cells in Mouse Models of Alzheimer's Disease.

Nuclear pore complexes (NPCs) are highly dynamic macromolecular protein structures that facilitate molecular exchange across the nuclear envelope. Aberrant NPC functioning has been implicated in neurodegeneration. The translocated promoter region (Tpr) is a critical scaffolding nucleoporin (Nup) of the nuclear basket, facing the interior of the NPC. However, the role of Tpr in adult neural stem/precursor cells (NSPCs) in Alzheimer's disease (AD) is unknown. Using super-resolution (SR) and electron microscopy, we defined the different subcellular localizations of Tpr and phospho-Tpr (P-Tpr) in NSPCs in vitro and in vivo. Elevated Tpr expression and reduced P-Tpr nuclear localization accompany NSPC differentiation along the neurogenic lineage. In 5xFAD mice, an animal model of AD, increased Tpr expression in DCX+ hippocampal neuroblasts precedes increased neurogenesis at an early stage, before the onset of amyloid-ß plaque formation. Whereas nuclear basket Tpr interacts with chromatin modifiers and NSPC-related transcription factors, P-Tpr interacts and co-localizes with cyclin-dependent kinase 1 (Cdk1) at the nuclear chromatin of NSPCs. In hippocampal NSPCs in a mouse model of AD, aberrant Tpr expression was correlated with altered NPC morphology and counts, and Tpr was aberrantly expressed in postmortem human brain samples from patients with AD. Thus, we propose that altered levels and subcellular localization of Tpr in CNS disease affect Tpr functionality, which in turn regulates the architecture and number of NSPC NPCs, possibly leading to aberrant neurogenesis.

Differences in self-perceptions of aging across the adult lifespan: The sample case of awareness of age-related gains and losses.

Rooted in the premises of lifespan developmental theory, the concept of awareness of age-related change (AARC) posits that growing older comes with both experiences of gains and losses across different behavioral domains. However, little is known about how age-related change is perceived across the entire adult lifespan, provided that respective measures can be validly compared. Further, few studies have adopted an approach that examines gains and losses simultaneously to study a potential shift in the ratio of perceived age-related gains and losses from adolescence to advanced old age. Using cross-sectional data from the German Socio-Economic Panel, this study tested the measurement invariance of the 10-item AARC short form and examined age differences in the awareness of age-related changes across 1,612 participants aged 16-93 years. First, partial measurement invariance of the AARC-Gains and AARC-Losses scales was established, allowing for valid group comparisons across young adulthood, midlife, and old age. Second, results indicated that people experience more AARC-Gains than AARC-Losses throughout the adult lifespan. However, older adults exhibited an increasingly less favorable gains-to-losses ratio, primarily driven by more loss experiences. Gain experiences were mostly stable across age groups. Third, differences in levels of AARC were related to individuals' background characteristics relevant at the respective time of life, such as education (early adulthood), employment (midlife), and social resources (old age). These results highlight the utility of considering a broad age range when examining the nature and correlates of age differences in perceived age-related gains and losses. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Using proteomics for stratification and risk prediction in patients with solid tumors.

Proteomics, the study of proteins and their functions, has greatly evolved due to advances in analytical chemistry and computational biology. Unlike genomics or transcriptomics, proteomics captures the dynamic and diverse nature of proteins, which play crucial roles in cellular processes. This is exemplified in cancer, where genomic and transcriptomic information often falls short in reflecting actual protein expression and interactions. Liquid chromatography-mass spectrometry (LC-MS) is pivotal in proteomic data generation, enabling high-throughput analysis of protein samples. The MS-based workflow involves protein digestion, chromatographic separation, ionization, and fragmentation, leading to peptide identification and quantification. Computational biostatistics, particularly using tools in R (R Foundation for Statistical Computing, Vienna, Austria; www.R-project.org ), aid in data analysis, revealing protein expression patterns and correlations with clinical variables. Proteomic studies can be explorative, aiming to characterize entire proteomes, or targeted, focusing on specific proteins of interest. The integration of proteomics with genomics addresses database limitations and enhances peptide identification. Case studies in intrahepatic cholangiocarcinoma, glioblastoma multiforme, and pancreatic ductal adenocarcinoma highlight proteomics' clinical applications, from subtyping cancers to identifying diagnostic markers. Moreover, proteomic data augment molecular tumor boards by providing deeper insights into pathway activities and genomic mutations, supporting personalized treatment decisions. Overall, proteomics contributes significantly to advancing our understanding of cellular biology and improving clinical care.

A Galaxy of informatics resources for MS-based proteomics.

INTRODUCTION: Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting the analysis requirements of increasingly complex MS-based proteomic data and associated multi-omic data are critically needed. These requirements included availability of software that would span diverse types of analyses, scalability for large-scale, compute-intensive applications, and mechanisms to ease adoption of the software. AREAS COVERED: The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses. EXPERT OPINION: The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.

Systemic toxicity of snake venom metalloproteinases: Multi-omics analyses of kidney and blood plasma disturbances in a mouse model.

Snakebite envenomation is classified as a Neglected Tropical Disease. Bothrops jararaca venom induces kidney injury and coagulopathy. HF3, a hemorrhagic metalloproteinase of B. jararaca venom, participates in the envenomation pathogenesis. We evaluated the effects of HF3 in mouse kidney and blood plasma after injection in the thigh muscle, mimicking a snakebite. Transcriptomic analysis showed differential expression of 31 and 137 genes related to kidney pathology after 2 h and 6 h, respectively. However, only subtle changes were observed in kidney proteome, with differential abundance of 15 proteins after 6 h, including kidney injury markers. N-terminomic analysis of kidney proteins showed 420 proteinase-generated peptides compatible with meprin specificity, indicating activation of host proteinases. Plasma analysis revealed differential abundance of 90 and 219 proteins, respectively, after 2 h and 6 h, including coagulation-cascade and complement-system components, and creatine-kinase, whereas a semi-specific search of N-terminal peptides indicated activation of endogenous proteinases. HF3 promoted host reactions, altering the gene expression and the proteolytic profile of kidney tissue, and inducing plasma proteome imbalance driven by changes in abundance and proteolysis. The overall response of the mouse underscores the systemic action of a hemorrhagic toxin that transcends local tissue damage and is related to known venom-induced systemic effects.

Positional proteomics: is the technology ready to study clinical cohorts?

INTRODUCTION: Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED: We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION: Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.

Long-term aging trajectories of the accumulation of disease burden as predictors of daily affect dynamics and stressor reactivity.

Multiple-timescale studies provide new opportunities to examine how developmental processes that evolve at different cadences are intertwined. Developmental theories of emotion regulation suggest that the long-term, slowly evolving age-related accumulation of disease burden should shape short-term, faster evolving (daily) affective experiences. To empirically examine this proposition, we combined data from 123 old adults (65-69 years, 47% women) and 32 very old adults (85-88 years, 59% women) who provided 20 + year within-person longitudinal data on physician-rated morbidity and subsequently also completed repeated daily-life assessments of stress and affect six times a day over 7 consecutive days as they were going about their daily-life routines. Results from models that simultaneously articulate growth and intraindividual variability processes (in a dynamic structural equation modeling framework) revealed that individual differences in long-term aging trajectories of the accumulation of disease burden were indeed predictive of differences in three facets of affective dynamics that manifest in everyday life. In particular-over and above mean levels of disease burden-older adults whose disease burden had increased more over the past 20 years had higher base level of negative affect in their daily lives, more emotional reactivity to the experience of daily stressors, and more moment-to-moment fluctuations in negative affect that was unrelated to stressors (affective systemic noise). We highlight that developmental processes evolving over vastly different timescales are intertwined, and speculate how new knowledge about those relations can inform developmental theories of emotion regulation and daily-life functioning. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Levels of awareness of age-related gains and losses throughout adulthood and their developmental correlates.

Views of aging predict key developmental outcomes. Less is known, however, about the consequences of constellations of domain-specific perceived gains and losses across the full adult lifespan. First, we explored levels of awareness of age-related gains (AARC-gains) and losses (AARC-losses) in five behavioral domains across adulthood. Second, we identified the number and types of profiles of AARC-gains and AARC-losses in young adulthood, midlife, young-old age, and old-old age. Third, we investigated whether the identified profiles differed in their associations with developmental correlates. Data came from the 2018 German Socio-Economic Panel Innovation Sample (SOEP-IS), comprising 403 young, 721 middle-aged, 260 young-old and 228 old-old individuals. We assessed AARC, physical and mental functioning, information processing speed, social relations, lifestyle, and engagement. At the sample level, AARC-losses were higher in old age, whereas AARC-gains did not differ across adulthood. Latent profile analyses revealed two distinguishable constellations of AARC-gains and AARC-losses that characterize young adulthood and old-old age, whereas four and three gains-to-losses constellations are needed to characterize midlife and young-old age, respectively. In middle, young-old, and old-old age, profiles with more AARC-losses were associated with poorer scores on all developmental correlates. Overall, study results suggest that age-related experiences are most diversified in midlife and young-old age. Asking individuals about their negative age-related experiences may help identify those individuals who are doing less well in important developmental correlates. (PsycInfo Database Record (c) 2023 APA, all rights reserved).