The Synergistic Effect of Zuogui Pill and Eldecalcitol on Improving Bone Mass and Osteogenesis in Type 2 Diabetic Osteoporosis.

Background and Objectives: The incidence of diabetic osteoporosis, an important complication of diabetes mellitus, is increasing gradually. This study investigated the combined effect of the Zuogui pill (ZGP) and eldecalcitol (ED-71), a novel vitamin D analog, on type 2 diabetic osteoporosis (T2DOP) and explored their action mechanism. Materials and Methods: Blood glucose levels were routinely monitored in db/db mice while inducing T2DOP. We used hematoxylin and eosin staining, Masson staining, micro-computed tomography, and serum biochemical analysis to evaluate changes in the bone mass and blood calcium and phosphate levels of mice. Immunohistochemical staining was performed to assess the osteoblast and osteoclast statuses. The MC3T3-E1 cell line was cultured in vitro under a high glucose concentration and induced to undergo osteogenic differentiation. Quantitative real-time polymerase chain reaction, Western blot, immunofluorescence, ALP, and alizarin red staining were carried out to detect osteogenic differentiation and PI3K-AKT signaling pathway activity. Results: ZGP and ED-71 led to a dramatic decrease in blood glucose levels and an increase in bone mass in the db/db mice. The effect was strongest when both were used together. ZGP combined with ED-71 promoted osteoblast activity and inhibited osteoclast activity in the trabecular bone region. The in vitro results revealed that ZGP and ED-71 synergistically promoted osteogenic differentiation and activated the PI3K-AKT signaling pathway. The PI3K inhibitor LY294002 or AKT inhibitor ARQ092 altered the synergistic action of both on osteogenic differentiation. Conclusions: The combined use of ZGP and ED-71 reduced blood glucose levels in diabetic mice and promoted osteogenic differentiation through the PI3K-AKT signaling pathway, resulting in improved bone mass. Our study suggests that the abovementioned combination constitutes an effective treatment for T2DOP.

Brain-derived neurotrophic factor promotes orthodontic tooth movement by alleviating periodontal ligament stem cell senescence.

Orthodontic treatment in older adults is more difficult than in younger adults, partially due to delayed osteogenesis caused by senescence of human periodontal ligament stem cells (hPDLSCs). The production of brain-derived neurotrophic factor (BDNF) which regulates the differentiation and survival of stem cells decreases with age. We aimed to investigate the relationship between BDNF and hPDLSC senescence and its effects on orthodontic tooth movement (OTM). We constructed mouse OTM models using orthodontic nickel­titanium springs and compared the responses of wild-type (WT) and BDNF+/- mice with or without addition of exogenous BDNF. In vitro, hPDLSCs subjected to the mechanical stretch were used to simulate the cell stretch environment during OTM. We extracted periodontal ligament cells from WT and BDNF+/- mice to evaluate their senescence-related indicators. The application of orthodontic force increased BDNF expression in the periodontium of WT mice, while the mechanical stretch increased BDNF expression in hPDLSCs. Osteogenesis-related indicators, including RUNX2 and ALP decreased and cellular senescence-related indicators such as p16, p53 and ß-galactosidase increased in BDNF+/- mice periodontium. Furthermore, periodontal ligament cells extracted from BDNF+/- mice exhibited more senescent compared with cells from WT mice. Application of exogenous BDNF decreased the expression of senescence-related indicators in hPDLSCs by inhibiting Notch3, thereby promoting osteogenic differentiation. Periodontal injection of BDNF decreased the expression of senescence-related indicators in periodontium of aged WT mice. In conclusion, our study showed that BDNF promotes osteogenesis during OTM by alleviating hPDLSCs senescence, paving a new path for future research and clinical applications.

Significance of Melt Pool Structure on the Hydrogen Embrittlement Behavior of a Selective Laser-Melted 316L Austenitic Stainless Steel.

The hydrogen embrittlement (HE) behavior of a selective laser-melted (SLM) 316L austenitic stainless steel has been investigated by hydrogen charging experiments and slow strain rate tensile tests (SSRTs) at room temperature. The results revealed that compared to the samples without H, the ultimate tensile strength (UTS) and elongation (EL) of specimens were decreased from 572 MPa to 552 MPa and from 60% to 36%, respectively, after 4 h of electrochemical hydrogenation with a current density of 100 mA/cm2. The negative effects of hydrogen charging were more pronounced on the samples' ductility than on their strength. A quasi in situ EBSD observation proved that there was little phase transformation in the samples but an increased density of low angle grain boundaries, after 4 h H charging. After strain was applied, the surface of the H-sample displayed many hydrogen-induced cracks along the melt pool boundaries (MPBs) showing that these MPBs were the preferred areas for the gathering and transferring of hydrogen.

The mechanism underlying the TC-G 1008 rescue of reactive oxygen species (ROS)-induced osteoblast apoptosis by the upregulation of peroxiredoxin 1.

Osteoporosis is a common bone disease in the elderly with high morbidity and mortality. Previous studies have shown ROS-revulsive osteoblast apoptosis to be involved in the pathogenesis of osteoporosis. At present, a research hotspot exists on the topic of the ROS-targeted clinical treatment of osteoporosis. TC-G 1008, a potent and selective GPR39 agonist, exerts a conspicuous influence on a myriad of cellular processes, ranging from cellular redox status, to gene expression, to cell apoptosis. However, the underlying mechanism by which TC-G 1008 regulates osteoblast function under oxidative stress has not yet been elucidated. The purpose of this study was to investigate the effect and underlying mechanism of TC-G 1008 in the rescue of ROS-induced apoptosis by upregulating peroxiredoxin (Prx1). In this study, experimental results demonstrated that TC-G 1008 could activate GPR39, which then accelerated ROS obliteration and apoptosis inhibition in osteoblasts via Prx1 upregulation through the nuclear factor (erythroid-derived 2)-related factor 2 (Nrf2). Interestingly, being regarded as an 'information' molecule rather than an anti-oxidase molecule, Prx1 was shown to restrict the dissociation of the apoptosis signal-regulating kinase 1 (ASK1)/thioredoxin (Trx) under oxidative stress, which signified the activation of the ASK1 pathway, thereby resulting in the suppression of apoptosis. In summary, this study explores the double mechanism of TC-G 1008 in osteoblast apoptosis amelioration under oxidative stress through (i) ROS elimination and (ii) ASK1/Trx signal suppression, both of which contribute to increased Prx1 expression, and the results suggest that TC-G 1008 has great potential in the clinical treatment of osteoporosis.

Enhancing dynamic ECG heartbeat classification with lightweight transformer model.

Arrhythmia is a common class of Cardiovascular disease which is the cause for over 31% of all death over the world, according to WHOs' report. Automatic detection and classification of arrhythmia, as an effective tool of early warning, has recently been received more and more attention, especially in the applications of wearable devices for data capturing. However, different from traditional application scenarios, wearable electrocardiogram (ECG) devices have some drawbacks, such as being subject to multiple abnormal interferences, thus making accurate ventricular contraction (PVC) and supraventricular premature beat (SPB) detection to be more challenging. The traditional models for heartbeat classification suffer from the problem of large-scale parameters and the performance in dynamic ECG heartbeat classification is not satisfactory. In this paper, we propose a novel light model Lightweight Fussing Transformer to address these problems. We developed a more lightweight structure named LightConv Attention (LCA) to replace the self-attention of Fussing Transformer. LCA has reached remarkable performance level equal to or higher than self-attention with fewer parameters. In particular, we designed a stronger embedding structure (Convolutional Neural Network with attention mechanism) to enhance the weight of features of internal morphology of the heartbeat. Furthermore, we have implemented the proposed methods on real datasets and experimental results have demonstrated outstanding accuracy of detecting PVC and SPB.