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Doxorubicin (DOX)-induced cardiotoxicity has been widely observed, yet the specific impact on cardiac fibroblasts is not fully understood. Additionally, the modulation of the transforming growth factor beta (TGF-β) signaling pathway by DOX remains to be fully elucidated. This study investigated DOX’s ability to modulate the expression of genes and proteins involved in the TGF-β signaling cascade in mouse fibroblasts from two sources by assessing the impact of DOX treatment on TGF-β inducible expression of pivotal genes and proteins within fibroblasts. Mouse embryonic fibroblasts (NIH3T3) and mouse primary cardiac fibroblasts (CFs) were treated with DOX in the presence of TGF-β1 to assess changes in protein levels by western blot and changes in mRNA levels by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Our results revealed a dose-dependent reduction in cellular communication network factor 2 (CCN2) protein levels upon DOX treatment in both NIH3T3 and CFs, suggesting an antifibrotic activity by DOX in these fibroblasts. However, DOX only inhibited the TGF-β1 induced expression of COL1 in NIH3T3 cells but not in CFs. In addition, we observed that DOX treatment reduced the expression of BMP1 in NIH3T3 but not primary cardiac fibroblasts. No significant changes in SMAD2 protein expression and phosphorylation in either cells were observed after DOX treatment. Finally, DOX inhibited the expression of Atf4 gene and increased the expression of Cdkn1a, Id1, Id2, Runx1, Tgfb1, Inhba, Thbs1, Bmp1, and Stat1 genes in NIH3T3 cells but not CFs, indicating the potential for cell-specific responses to DOX and its modulation of the TGF-β signaling pathway.

A primary component of exercise, mechanical signals, when applied in the form of low intensity vibration (LIV), increases mesenchymal stem cell (MSC) osteogenesis and proliferation. While it is generally accepted that exercise effectively combats the deleterious effects of aging in the musculoskeletal system, how long-term exercise affects stem cell aging, which is typified by reduced proliferative and differentiative capacity, is not well explored. As a first step in understanding the effect of long-term application of mechanical signals on stem cell function, we investigated the effect of LIV during in vitro expansion of MSCs. Primary MSCs were subjected to either a control or to a twice-daily LIV regimen for up to sixty cell passages (P60) under in vitro cell expansion conditions. LIV effects were assessed at both early passage (EP) and late passage (LP). At the end of the experiment, P60 cultures exposed to LIV maintained a 28% increase of cell doubling and a 39% reduction in senescence-associated β-galactosidase activity (p < 0.01) but no changes in telomere lengths and p16 INK4a levels were observed. Prolonged culture-associated decreases in osteogenic and adipogenic capacity were partially protected by LIV in both EP and LP groups (p < 0.05). Mass spectroscopy of late passage MSC indicated a synergistic decrease of actin and microtubule cytoskeleton-associated proteins in both control and LIV groups while LIV induced a recovery of proteins associated with oxidative reductase activity. In summary, our findings show that the application of long-term mechanical challenge (+LIV) during in vitro expansion of MSCs for sixty passages significantly alters MSC proliferation, differentiation and structure. This suggests LIV as a potential tool to investigate the role of physical activity during aging.

Objectives Osteoarthritis (OA) is a major concern in the United States and worldwide. Development and validation of robust decellularization techniques is critical in generating suitable bioscaffolds for future OA treatment options. Data descriptions In the present study, proteins from porcine auricular cartilage before and after decellularization were extracted, digested, and identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The data represents protein profiles of both non-decellularized and decellularized porcine auricular cartilage. This data is intended to be useful to scientists who are interesting in generating biomaterials for potential relevant clinical applications using decellularized cartilage tissue.

Oncostatin M (OSM) is a pleiotropic, interleukin-6 family inflammatory cytokine that plays an important role in inflammatory diseases, including inflammatory bowel disease, rheumatoid arthritis, and cancer progression and metastasis. Recently, elevated OSM levels have been found in the serum of COVID-19 patients in intensive care units. Multiple anti-OSM therapeutics have been investigated, but to date no OSM small molecule inhibitors are clinically available. To pursue a high-throughput screening and structure-based drug discovery strategy to design a small molecule inhibitor of OSM, milligram quantities of highly pure, bioactive OSM are required. Here, we developed a reliable protocol to produce highly pure unlabeled and isotope enriched OSM from E. coli for biochemical and NMR studies. High yields (ca. 10 mg/L culture) were obtained in rich and minimal defined media cultures. Purified OSM was characterized by mass spectrometry and circular dichroism. The bioactivity was confirmed by induction of OSM/OSM receptor signaling through STAT3 phosphorylation in human breast cancer cells. Optimized buffer conditions yielded 1 H, 15 N HSQC NMR spectra with intense, well-dispersed peaks. Titration of 15 N OSM with a small molecule inhibitor showed chemical shift perturbations for several key residues with a binding affinity of 12.2 ± 3.9 μM. These results demonstrate the value of bioactive recombinant human OSM for NMR-based small molecule screening.

Objective Doxorubicin (DOX) is a highly effective chemotherapeutic used to treat many adult and pediatric cancers. However, its use is limited due to a dose-dependent cardiotoxicity, which can lead to lethal cardiomyopathy. In contrast to the extensive research efforts on toxic effects of DOX in cardiomyocytes, its effects and mechanisms on cardiac extracellular matrix (ECM) homeostasis and remodeling are poorly understood. In this study, we examined the potential effects of DOX on cardiac ECM to further our mechanistic understanding of DOX-induced cardiotoxicity. Results DOX-induced significant down-regulation of several ECM related genes in primary cardiac fibroblasts, including Adamts1, Adamts5, Col4a1, Col4a2, Col5a1, Fbln1, Lama2, Mmp11, Mmp14, Postn, and TGF β . Quantitative proteomics analysis revealed significant global changes in the fibroblast proteome following DOX treatment. A pathway analysis using iPathwayGuide of the differentially expressed proteins revealed changes in a list of biological pathways that involve cell adhesion, cytotoxicity, and inflammation. An apparent increase in Picrosirius red staining indicated that DOX-induced an increase in collagen production in cardiac primary fibroblasts after 3-day treatment. No significant changes in collagen organization nor glycoprotein production were observed.

The purpose of this investigation was to utilize pulsed electric field (PEF) technology to make sweet potato kettle chips (SPKC) healthier by lowering the amount of oil absorbed and reducing the amount of acrylamide formed during frying. Sweet potatoes were treated continuously in an Elea PEF Advantage Belt One system and prepared as SPKC, without peeling and sliced to a thickness of 1.7 mm. The specific energy for PEF application was set to either low (1.5 kJ/kg) or high (3.0 kJ/kg) with a field strength of 1.0 kV/cm and a pulse width of 6 μm. Batches of 500 g unrinsed potato slices were fried in canola oil at 130 °C for 360 s. The oil content in 3.0 g of fried SPKC was 1.39 g or 46.3%, whereas the oil content was 37.9% for high and 37.7% for low PEF-treatment conditions. Acrylamide (AA) in the fried SPKC was quantified by mass spectrometry to be 0.668 μg/g in the non-PEF control and 0.498 μg/g for low and 0.370 μg/g for high PEF treatment. The results of this study support the use of PEF in SPKC processing to reduce oil absorbance during frying by up to 9% and lower AA by up to 45%.

Objective Extracellular matrix proteins play important roles in embryonic development and antibodies that specifically detect these proteins are essential to understanding their function. The zebrafish embryo is a popular model for vertebrate development but suffers from a dearth of authenticated antibody reagents for research. Here, we describe a novel antibody designed to detect the minor fibrillar collagen chain Col11a1a in zebrafish (AB strain). Results The Col11a1a antibody was raised in rabbit against a peptide comprising a unique sequence within the zebrafish Col11a1a gene product. The antibody was affinity-purified and characterized by ELISA. The antibody is effective for immunoblot and immunohistochemistry applications. Protein bands identified by immunoblot were confirmed by mass spectrometry and sensitivity to collagenase. Col11a1a knockout zebrafish were used to confirm specificity of the antibody. The Col11a1a antibody labeled cartilaginous structures within the developing jaw, consistent with previously characterized Col11a1 antibodies in other species. Col11a1a within formalin-fixed paraffin-embedded zebrafish were recognized by the antibody. The antibodies and the approaches described here will help to address the lack of well-defined antibody reagents in zebrafish research.

The ability of pore-forming proteins to interact with various analytes has found vast applicability in single molecule sensing and characterization. In spite of their abundance in organisms from all kingdoms of life, only a few pore-forming proteins have been successfully reconstituted in artificial membrane systems for sensing purposes. Lysenin, a pore-forming toxin extracted from the earthworm E. fetida , inserts large conductance nanopores in lipid membranes containing sphingomyelin. Here we show that single lysenin channels may function as stochastic nanosensors by allowing the short cationic peptide angiotensin II to be electrophoretically driven through the conducting pathway. Long-term translocation experiments performed using large populations of lysenin channels allowed unequivocal identification of the unmodified analyte by Liquid Chromatography-Mass Spectrometry. However, application of reverse voltages or irreversible blockage of the macroscopic conductance of lysenin channels by chitosan addition prevented analyte translocation. This investigation demonstrates that lysenin channels have the potential to function as nano-sensing devices capable of single peptide molecule identification and characterization, which may be further extended to other macromolecular analytes.

Several risk factors have been identified as potential contributors to pancreatic cancer development, including environmental and lifestyle factors, such as smoking, drinking and diet, and medical conditions such as diabetes and pancreatitis, all of which generate oxidative stress and DNA damage. Oxidative stress status can be modified by environmental factors and also by an individual's unique genetic makeup. Here we examined the contribution of environment and genetics to an individual's level of oxidative stress, DNA damage and susceptibility to pancreatic cancer in a pilot study using three groups of subjects: a newly diagnosed pancreatic cancer group, a healthy genetically-unrelated control group living with the case subject, and a healthy genetically-related control group which does not reside with the subject. Oxidative stress and DNA damage was evaluated by measuring total antioxidant capacity, direct and oxidative DNA damage by Comet assay, and malondialdehyde levels. Direct DNA damage was significantly elevated in pancreatic cancer patients (age and sex adjusted mean ± standard error: 1.00 ± 0.05) versus both healthy unrelated and related controls (0.70 ± 0.06, p<0.001 and 0.82 ± 0.07, p = 0.046, respectively). Analysis of 22 selected SNPs in oxidative stress and DNA damage genes revealed that CYP2A6 L160H was associated with pancreatic cancer. In addition, DNA damage was found to be associated with TNFA -308G>A and ERCC4 R415Q polymorphisms. These results suggest that measurement of DNA damage, as well as select SNPs, may provide an important screening tool to identify individuals at risk for development of pancreatic cancer.

The growth of Internet of Things (IoT) devices and social media platforms generates large volumes of multimodal behavioral data that present both great opportunities and challenges to cross-domain behavior prediction. The current models do not deal with time misalignment, distributional drift, and personalization when only a limited amount of data is available. To address these issues, Adaptive Cross-Modal Behavioral Prediction (ACMBP), introduced in this study, is a new framework that merges the streams of IoT activity and social media characteristics via adaptive graph networks. ACMBP combines temporal-semantic offset attention to align activities by the IoT with social actions, drift-conscious dynamic graph rewiring to adapt to changing user relations, hierarchical cross-domain transfer to adapt across different platforms, and few-shot personalization with meta-learning and behavioral prototypes. ACMBP possibility in large-scale heterogeneous digital ecosystems is compared to a fused IoT social dataset (wearable sensors + Twitter) and two public multimodal benchmarks against 10 strong baselines (LSTM, GRU, BERT, GCN, GAT, HAN, GraphSAGE, DCRNN, DeepFM, Multimodal Transformer). ACMBP has been tested on a custom IoT–Social Fusion dataset (1,200 users, 90-day collection, 2.3M sensor records, 850K Twitter posts) and two public benchmarks (PAMAP2, USC-HAD). The results of all improvements are statistically significant (Wilcoxon signed-rank test, p < 0.001). ACMBP attains Behavioral Transition Accuracy (BTA) of 91.4%, Temporal Offset Prediction Error (TOPE) of 1.2 hours, Drift Detection Precision (DDP) of 84.7%, Cross-Platform Transfer Efficiency (CPTE) of 82.3%, and Few-Shot Adaptation only with five samples, which are improvements by 7.3%, 32%, 11.8%, 13.4%, and 50% respectively over the best baselines. Each module’s contribution is supported by ablation studies, and the results of scalability experiments indicate stable performance in large-scale heterogeneous IoT-social environments.