Bone marrow-derived mesenchymal stem cells (BMSCs), owing to their osteoblastogenic differentiation potential, are crucial for maintaining bone homeostasis and remodeling. Nevertheless, in aging and age-related bone diseases like osteoporosis, BMSCs show significantly diminished osteogenic potential, with a concomitant increase in adipogenic differentiation. The aged BMSCs also become desensitized to BMP2 stimulation to a large extent and exhibit aberrations in BMP2 signaling. However, the molecular mechanisms facilitating this shift in lineage commitment and mediating the cellular dysfunctions remain elusive. This knowledge gap hinders the development of regenerative strategies for skeletal aging and osteoporosis. This study employed an integrative tandem mass tag (TMT)-based phosphoproteomic and total proteomic profiling on BMSCs isolated from young (6-month) and aged (15-month) C57BL/6 (B6) mice to elucidate global alterations in both protein activity and expression. The analysis identified more than 500 proteins that underwent significant alterations (BH-adjusted p-value < 0.05) either in phosphorylation or expression between young and aged BMSCs. Many lineage-specific markers also underwent changes in both phosphorylation and expression with aging. Additionally, key biological processes, including cellular metabolism, clathrin-mediated endocytosis, and nucleocytoplasmic transport mechanisms, were enriched for the deregulated proteins. Signaling proteins, ERK-1/2, had increased activating phosphorylation in the aged BMSCs, while transcription factors Lrrfip1, Ruvbl1, and Ruvbl2 also exhibited dysregulated activity and abundance in the aged BMSCs. The findings from the study adds significant mechanistic insights into how aging disrupts signal transduction, metabolism, and transcriptional program in BMSCs, contributing to age-associated loss of bone mass and reduced skeletal regenerative capabilities. Through the identification of key mediators of BMSC dysfunction seen in aging, this work offers a strong foundation in devising potential therapeutic strategies to restore diminished osteogenic potential and treat osteoporosis.
The method of X-ray footprinting and mass spectrometry (XFMS) using high flux synchrotron X-ray sources has become an established method in structural biology and is based on the radiolytic production of hydroxyl radicals, which oxidatively modify protein sidechains. While other methods of producing hydroxyl radicals are available, one benefit of using high flux density sources is that hydroxyl radical scavenging reactions can be minimized, and exposure times kept short to minimize secondary reactions. Here we present an application of the XFMS method using low dose rate X-rays from a commercial instrument. We demonstrate the feasibility of the approach using short peptides, characterizing the oxidative modifications +14, +16, and +32 Da under both aerobic and low oxygen conditions, and we additionally quantify the hydrogen peroxide production for various doses using the low dose rate source. These results provide fundamental information on the oxidative damage to peptides due to hydroxyl radicals using a low dose rate X-ray source.
Emotion recognition from physiological signals has immense applications in healthcare and human-computer interaction. We developed an electrodermal activity (EDA)-graph signal processing pipeline that produces highly sensitive features for detecting the affective dimensions (arousal and valence) of emotions. Using the Continuously Annotated Signals of Emotion dataset, we compared our graph-based EDA features (EDA-graph) with traditional time- and frequency-domain EDA features and features derived from other signals (heart rate variability, pulse transit time, electromyography, skin temperature, and respiration) for detecting affective dimensions using machine learning regression models. The EDA-graph features showed superior performance in continuous affective dimension recognition compared to the most accurate state-of-the-art models, achieving RMSE values of 0.801 for arousal and 0.714 for valence. Furthermore, we used a variety of traditional and recently published datasets collected in laboratory and ambulatory settings to perform a comprehensive evaluation of the robust generalization capabilities of our approach across different emotional contexts. The models demonstrated exceptional performance in classifying emotional states across the datasets, achieving 98.2% accuracy in detecting positive, negative, and mixed emotions; 92.75% in discriminating between emotions (relaxed, amused, bored, scared, and neutral); and 86.54% in detecting stress vs. no stress. These results highlight the potential of a graph-based analysis of EDA in emotion recognition systems in different contexts, especially for real-world applications.
Traumatic brain injury (TBI) presents a major biomedical challenge due to its complex biomechanics and the heterogeneous cellular responses it elicits, including neuronal death, glial activation, and blood–brain barrier disruption. Traditional in vitro models, including 2D neuronal cultures, brain slices and transwell systems, have provided valuable insights into molecular and cellular biology but remain limited by their lack of human-specific architecture, vascularization, and neurovascular interactions. The purpose of this review is to systematically examine advances in in vitro TBI modeling, with particular attention to studies leveraging human induced pluripotent stem cell (iPSC)-derived neural and vascular tissues, organoids, hydrogel scaffolds, microfluidic platforms, and mechanical injury. We highlight how the integration of neurovascular unit (NVU) components has improved the physiological and functional relevance of these models. Finally, we identify key limitations, including variability in organoid maturation, incomplete vascularization, and lack of methodological standardization, and outline future directions for improving translational fidelity. Therefore, this review contributes to a critical evaluation of emerging technologies and their potential to advance neurotrauma research and therapeutic discovery.
Bone Morphogenetic Protein-2 (BMP2) is a growth factor that maintains bone homeostasis through the BMP receptor type Ia (BMPRIa) and type II (BMPRII). BMP2 promotes osteogenesis by inducing the differentiation of bone marrow mesenchymal stem cells (BMSCs) into osteoblasts; however, it can also trigger BMSC differentiation into adipocytes. BMP2’s osteo-inductive ability has made it a potential treatment for osteoporosis, yet its dual role in BMSC differentiation complicates its efficacy. High BMP2 levels cause BMPRIa cleavage, but the downstream effects and the mechanisms governing BMP2-induced osteogenesis or adipogenesis are unresolved. Here, we identify Caspase-1 as a key mediator of BMPRIa cleavage and its downstream effects on adipogenesis. We used primary BMSCs from C57BL/6 mice, stimulated with varying BMP2 concentrations, to explore BMP2-induced BMPRIa cleavage and its impact on PPARγ—a key regulator of adipogenesis. Western blotting and immunostaining using antibodies against BMPRIa and PPARγ uncovered BMPRIa cleavage and revealed the nuclear translocation of the cleaved segment, colocalizing with PPARγ. Caspase-1 inhibition significantly reduced BMPRIa cleavage and PPARγ expression, highlighting its pivotal role in adipogenic differentiation. Understanding the molecular mechanisms of BMP2-induced adipogenesis and Caspase-1 inhibition could improve BMP2 therapeutic efficacy for osteoporosis by promoting osteogenesis over adipogenesis.
