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Dual-energy X-ray absorptiometry (DXA) is underutilized to measure bone mineral density (BMD) and evaluate fracture risk. We present an automated tool to identify fractures, predict BMD, and evaluate fracture risk using plain radiographs. The tool performance is evaluated on 5164 and 18175 patients with pelvis/lumbar spine radiographs and Hologic DXA. The model is well calibrated with minimal bias in the hip (slope = 0.982, calibration-in-the-large = −0.003) and the lumbar spine BMD (slope = 0.978, calibration-in-the-large = 0.003). The area under the precision-recall curve and accuracy are 0.89 and 91.7% for hip osteoporosis, 0.89 and 86.2% for spine osteoporosis, 0.83 and 95.0% for high 10-year major fracture risk, and 0.96 and 90.0% for high hip fracture risk. The tool classifies 5206 (84.8%) patients with 95% positive or negative predictive value for osteoporosis, compared to 3008 DXA conducted at the same study period. This automated tool may help identify high-risk patients for osteoporosis. Dual-energy X-ray absorptiometry and the Fracture Risk Assessment Tool are recommended tools for osteoporotic fracture risk evaluation, but are underutilized. Here, the authors present an opportunistic tool to identify fractures, predict bone mineral density and evaluate fracture risk using plain pelvis and lumbar spine radiographs.

Tumor-associated macrophages (TAMs) constitute a large population of glioblastoma and facilitate tumor growth and invasion of tumor cells, but the underlying mechanism remains undefined. In this study, we demonstrate that chemokine (C-C motif) ligand 8 (CCL8) is highly expressed by TAMs and contributes to pseudopodia formation by GBM cells. The presence of CCL8 in the glioma microenvironment promotes progression of tumor cells. Moreover, CCL8 induces invasion and stem-like traits of GBM cells, and CCR1 and CCR5 are the main receptors that mediate CCL8-induced biological behavior. Finally, CCL8 dramatically activates ERK1/2 phosphorylation in GBM cells, and blocking TAM-secreted CCL8 by neutralized antibody significantly decreases invasion of glioma cells. Taken together, our data reveal that CCL8 is a TAM-associated factor to mediate invasion and stemness of GBM, and targeting CCL8 may provide an insight strategy for GBM treatment.

Before the COVID-19 pandemic, Mycoplasma pneumoniae infections emerged during spring to summer yearly in Taiwan, but infections were few during the pandemic. M. pneumoniae macrolide resistance soared to 85.7% in 2020 but declined to 0% during 2022-2023. Continued molecular surveillance is necessary to monitor trends in macrolide-resistant M. pneumoniae.

Due to the outbreak of coronavirus disease 2019 (COVID-19), the Chinese government implemented strict lockdown measures to control the spread of infection. The impact of the COVID-19 lockdown on eating habits and lifestyles in the general population is unclear. This cross-sectional study was conducted via an online survey to obtain an overview of the food access, food intake, and physical activity of Chinese residents during the initial stage of the COVID-19 lockdown, and to investigate the association between staying at home/working from home and changes in eating habits and lifestyles. A total of 2702 participants (70.7% women) were included. Most of the participants maintained their habitual diet, while 38.2% increased their snack intake, 54.3% reported reduced physical activity, and 45.5% had increased sleep duration. Most people (70.1%) reported no change in body weight, while 25.0% reported an increase. Always staying at home/working from home was associated with an increase in animal product, vegetable, fruit, mushroom, nut, water, and snack intake, as well as sleep duration and frequency of skipping breakfast (odds ratio (OR) 1.54, 1.62, 1.58, 1.53, 1.57, 1.52, 1.77, 2.29, and 1.76 respectively). Suggestions should be made to encourage people to reduce their snack intake, maintain the daily consumption of breakfast, and increase physical activity during future lockdown periods.

Platelet-derived growth subunit A (PDGFA) plays critical roles in development of glioblastoma (GBM) with substantial evidence from TCGA database analyses and in vivo mouse models. So far, only platelet-derived growth receptor α (PDGFRA) has been identified as receptor for PDGFA. However, PDGFA and PDGFRA are categorized into different molecular subtypes of GBM in TCGA_GBM database. Our data herein further showed that activity or expression deficiency of PDGFRA did not effectively block PDGFA activity. Therefore, PDGFRA might be not necessary for PDGFA function.To profile proteins involved in PDGFA function, we performed co-immunoprecipitation (Co-IP) and Mass Spectrum (MS) and delineated the network of PDGFA-associated proteins for the first time. Unexpectedly, the data showed that EPHA2 could be temporally activated by PDGFA even without activation of PDGFRA and AKT. Furthermore, MS, Co-IP, in vitro binding thermodynamics, and proximity ligation assay consistently proved the interaction of EPHA2 and PDGFA. In addition, we observed that high expression of EPHA2 leaded to upregulation of PDGF signaling targets in TCGA_GBM database and clinical GBM samples. Co-upregulation of PDGFRA and EPHA2 leaded to worse patient prognosis and poorer therapeutic effects than other contexts, which might arise from expression elevation of genes related with malignant molecular subtypes and invasive growth. Due to PDGFA-induced EPHA2 activation, blocking PDGFRA by inhibitor could not effectively suppress proliferation of GBM cells, but simultaneous inhibition of both EPHA2 and PDGFRA showed synergetic inhibitory effects on GBM cells in vitro and in vivo. Taken together, our study provided new insights on PDGFA function and revealed EPHA2 as a potential receptor of PDGFA. EPHA2 might contribute to PDGFA signaling transduction in combination with PDGFRA and mediate the resistance of GBM cells to PDGFRA inhibitor. Therefore, combination of inhibitors targeting PDGFRA and EHA2 represented a promising therapeutic strategy for GBM treatment.

Dysfunctional immune responses contribute critically to the progression of Coronavirus Disease-2019 (COVID-19), with macrophages as one of the main cell types involved. It is urgent to understand the interactions among permissive cells, macrophages, and the SARS-CoV-2 virus, thereby offering important insights into effective therapeutic strategies. Here, we establish a lung and macrophage co-culture system derived from human pluripotent stem cells (hPSCs), modeling the host-pathogen interaction in SARS-CoV-2 infection. We find that both classically polarized macrophages (M1) and alternatively polarized macrophages (M2) have inhibitory effects on SARS-CoV-2 infection. However, M1 and non-activated (M0) macrophages, but not M2 macrophages, significantly up-regulate inflammatory factors upon viral infection. Moreover, M1 macrophages suppress the growth and enhance apoptosis of lung cells. Inhibition of viral entry using an ACE2 blocking antibody substantially enhances the activity of M2 macrophages. Our studies indicate differential immune response patterns in distinct macrophage phenotypes, which could lead to a range of COVID-19 disease severity. Model systems to study SARS-CoV-2 infection are required to better understand the immune response. Here the authors use a lung and macrophage co-culture system by differentiation of human pluripotent stem cells to better understand the phenotype and gene expression changes in host lung cells and macrophages after SARS-CoV-2 infection in vitro.

Chitinase-3-like protein-1 (CHI3L1), also known as YKL40, is a glycoprotein that belongs to the chitinase protein family. It is involved in various biological functions, including cell proliferation and tissue remodeling, with inflammatory and immunomodulatory capabilities. Several studies have shown that CHI3L1(YKL40) is upregulated in various diseases, such as cancer, asthma, and inflammatory bowel disease, among others. Although the expression level of CHI3L1(YKL40) is associated with disease activity, severity, and prognosis, its potential as a therapeutic target is still under investigation. In this review, we summarize the biological functions, pathological roles, and potential clinical applications of specific inhibitors and targeted therapies related to CHI3L1(YKL40).

Cancer is the leading cause of death in the world. Curcumin is the main ingredient in turmeric (Curcuma longa L.), and is widely used in the food industry. It shows anticancer properties on different types of cancers, and the underlying mechanisms of action include inhibiting cell proliferation, suppressing invasion and migration, promoting cell apoptosis, inducing autophagy, decreasing cancer stemness, increasing reactive oxygen species production, reducing inflammation, triggering ferroptosis, regulating gut microbiota, and adjuvant therapy. In addition, the anticancer action of curcumin is demonstrated in clinical trials. Moreover, the poor water solubility and low bioavailability of curcumin can be improved by a variety of nanotechnologies, which will promote its clinical effects. Furthermore, although curcumin shows some adverse effects, such as diarrhea and nausea, it is generally safe and tolerable. This paper is an updated review of the prevention and management of cancers by curcumin with a special attention to its mechanisms of action.

Change points indicate significant shifts in the statistical properties in data streams at some time points. Detecting change points efficiently and effectively are essential for us to understand the underlying data-generating mechanism in modern data streams with versatile parameter-varying patterns. However, it becomes a highly challenging problem to locate multiple change points in the noisy data. Although the Bayesian information criterion has been proven to be an effective way of selecting multiple change points in an asymptotical sense, its finite sample performance could be deficient. In this article, we have reviewed a list of information criterion-based methods for multiple change point detection, including Akaike information criterion, Bayesian information criterion, minimum description length, and their variants, with the emphasis on their practical applications. Simulation studies are conducted to investigate the actual performance of different information criteria in detecting multiple change points with possible model mis-specification for the practitioners. A case study on the SCADA signals of wind turbines is conducted to demonstrate the actual change point detection power of different information criteria. Finally, some key challenges in the development and application of multiple change point detection are presented for future research work.