Integrated investigation and experimental validation of PPARG as an oncogenic driver: implications for prognostic assessment and therapeutic targeting in hepatocellular carcinoma.

Peroxisome proliferator-activated receptor gamma (PPARG), a key transcription factor involved in lipid metabolism and glucose homeostasis, has been implicated in various types of cancer. However, its precise role in cancer remains unclear. In this study, we conducted a comprehensive pan-cancer analysis of PPARG expression using various types of cancer obtained from public databases. We observed significant heterogeneity in PPARG expression across different types of cancer. The association between PPARG expression and patient prognosis was investigated using Cox proportional hazards regression models and survival analysis. Clinical features and protein expression levels in the cohort showed that PPARG expression was strongly associated, suggesting its potential as a therapeutic target. We also evaluated the prognostic potential of PPARG by analyzing immune infiltration and genomic stability. We experimentally validated the potential of PPARG as a therapeutic target by analyzing drug sensitivity profiles, molecular docking simulations, and in vitro cell proliferation assays associated with PPARG expression. We identified common expression patterns of PPARG with other genes involved in key carcinogenic pathways. This provides deeper insights into the molecular mechanisms underlying its carcinogenic role. Additionally, functional enrichment analysis revealed significant enrichment of genes related to drug metabolism, cell proliferation, and immune response pathways associated with PPARG. Our findings highlight the importance of PPARG in the broader biology of cancer and suggest its potential as a diagnostic and therapeutic target for specific types of cancer. The results of our study provide strong support for the potential role of PPARG as a promising prognostic biomarker and immunotherapeutic target across various types of cancer.

Industrial structure upgrading, population aging and migration: An empirical study based on Chinese provincial panel data.

Population aging and migration are two important phenomena in the process of social development in China, which have a significant impact on industrial structure upgrading. This study explores the moderating effect of the population migration on the population aging impacting the industrial structure upgrading based on Chinese provincial panel data from 2000 to 2021. The results demonstrate that the population aging has become a development trend of China's population, and it has a significantly hinder industrial structure upgrading. Furthermore, the population migration resulting diffusion and convergence of economic factors has a meaningful moderating effects on the population aging impacting the industrial structure upgrading. Our study suggests that a reasonable and orderly population migration is critical in achieving stable and sustainable industrial structure upgrading, especially in the context of the China's population aging.

A cross-sectional study: an assessment of low muscle mass and osteoporosis in type 2 diabetes mellitus patients with a high glycated hemoglobin level.

BACKGROUND: Low muscle mass and osteoporosis are commonly observed in individuals with type 2 diabetes mellitus (T2DM). We investigated the prevalence of low muscle mass and osteoporosis in patients with T2DM who had high glycated hemoglobin (HbA1c) levels. METHODS: We included 187 Chinese patients with T2DM who were aged ⩾50 years and evaluated their body composition using dual-energy X-ray absorptiometry. We measured levels of fasting blood glucose, HbA1c, B collagen-specific sequences (B-CTX), osteocalcin (OC), propeptide of type 1 procollagen (P1NP), and 25-hydroxy vitamin D. RESULTS: Of the total patients, 82 were men and 105 were women. The prevalence rates of low muscle mass, osteopenia, and osteoporosis were 35.8%, 38.0%, and 31.0%, respectively. The prevalence rate of low muscle mass was significantly higher in women with HbA1c levels >9.0% than in those with HbA1c levels <9.0%. The prevalence rates of osteopenia and osteoporosis in men with HbA1c levels >9.0% differed significantly from those with HbA1c levels <9.0%. The appendicular skeletal muscle mass index (ASMI), trunk muscle mass, lumbar spinal bone mineral content (BMC), lumbar spine BMD, femoral BMC, and femoral BMD were significantly decreased, and the serum levels of B-CTX, OC, and P1NP were significantly increased in patients with T2DM who had osteoporosis. The ASMI was associated with osteopenia/osteoporosis in men and women with T2DM. CONCLUSIONS: In patients with T2DM, high HbA1c levels were associated with higher prevalence rates of low muscle mass in women and osteoporosis in men, and ASMI was a risk factor of osteoporosis.

Preclinical Assessment of the Effectiveness of Magnetic Resonance Molecular Imaging of Extradomain-B Fibronectin for Detection and Characterization of Oral Cancer.

PURPOSE: Oral squamous cell carcinoma (OSCC) has not seen a substantial improvement in patient survival despite therapeutic advances, making accurate detection and characterization of the disease a clinical priority. Here, we aim to demonstrate the effectiveness of magnetic resonance imaging (MRI) with the targeted MRI contrast agent MT218 specific to extradomain-B fibronectin (EDB-FN) in the tumor microenvironment for detection and characterization of aggressive OSCC tumors. PROCEDURES: EDB-FN expression was evaluated in human normal tongue and OSCC specimens with immunohistochemistry. Invasiveness of human CAL27, HSC3, and SCC4 OSCC cells was analyzed with spheroid formation and transwell assays. EDB-FN expression in the cells was analyzed with semiquantitative real-time PCR, western blotting, and a peptide binding study with confocal microscopy. Contrast-enhanced MRI with MT218 was performed on subcutaneous OSCC mouse models at a dose of 0.04 mmol/kg, using gadoteridol (0.1 mmol/kg) as a control. RESULTS: Strong EDB-FN expression was observed in human untreated primary and metastatic OSCC, reduced expression in treated OSCC, and little expression in normal tongue tissue. SCC4 and HSC3 cell lines demonstrated high invasive potential with high and moderate-EDB-FN expression, respectively, while CAL27 showed little invasive potential and low-EDB-FN expression. In T1-weighted MRI, MT218 produced differential contrast enhancement in the subcutaneous tumor models in correlation with EDB-FN expression in the cancer cells. Enhancement in the high-EDB-FN tumors was greater with MT218 at 0.04 mmol/kg than gadoteridol at 0.1 mmol/kg. CONCLUSIONS: The results suggest EDB-FN has strong potential as an imageable biomarker for aggressive OSCC. MRMI results demonstrate the effectiveness of MT218 and the potential for differential diagnostic imaging of oral cancer for improving the management of the disease.

Assessment of Balance Control Subsystems by Artificial Intelligence.

Recent studies have shown that balance performance assessment based on artificial intelligence (AI) is feasible. However, balance control is very complex and requires different subsystems to participate, which have not been evaluated individually yet. Furthermore, these studies only classified individual's balance performance across limited grades. Therefore, in this study we attempted to implement AI to precisely evaluate different types of balance control subsystems (BCSes). First, a total of 224 commonly used and newly developed features were extracted from the center of pressure (CoP) data for each participant, respectively. Then, regressors were employed in order to map these features to the evaluation scores given by physical therapists, which include the total score in Mini-Balance-Evaluation-Systems-Tests (Mini-BESTest) and its sub-scores on BCSes, namely anticipatory postural adjustments (APA), reactive postural control (RPC), sensory orientation (SO), and dynamic gait (DG). Their scoring ranges should be 0-28, 0-6, 0-6, 0-6, and 0-10, respectively. The results show that their minimum mean absolute errors from AI estimation reach up to 2.658, 0.827, 0.970, 0.642, and 0.98, respectively. In sum, our study is a preliminary study for assessing BCSes based on AI, which shows its possibility to be used in the clinics in the future.

An Effective Treatment for Heart Failure Caused by Valvular Heart Diseases: Thoracic Sympathetic Block.

BACKGROUND: The pilot study is designed to investigate the effect of continuous thoracic sympathetic block (TSB) on cardiac function, reconstruction, and hemodynamic parameters in patients with heart failure resulting from valvular heart disease. METHOD: The cardiac function parameters, including left ventricle ejection fraction (LVEF), left ventricle end-diastole diameter (LVEDD), fractional shortening (FS), and N-terminal prohormone of brain natriuretic peptide (NT-proBNP), were measured in 19 patients before and after TSB treatment. The patients were also classified on the basis of NYHA classification system. RESULTS: 4 weeks of TSB administration improved cardiac function in 18 of 19 patients (94.74%). The patients' LVEF, LVEDD, and NT-proBNP were all improved significantly after treatment. CONCLUSIONS: The favorable clinical outcome of TSB administration suggests an alternative treatment for the patients with heart failure caused by valvular dysfunctions.

Spectral Similarity Assessment Based on a Spectrum Reflectance-Absorption Index and Simplified Curve Patterns for Hyperspectral Remote Sensing.

Hyperspectral images possess properties such as rich spectral information, narrow bandwidth, and large numbers of bands. Finding effective methods to retrieve land features from an image by using similarity assessment indices with specific spectral characteristics is an important research question. This paper reports a novel hyperspectral image similarity assessment index based on spectral curve patterns and a reflection-absorption index. First, some spectral reflection-absorption features are extracted to restrict the subsequent curve simplification. Then, the improved Douglas-Peucker algorithm is employed to simplify all spectral curves without setting the thresholds. Finally, the simplified curves with the feature points are matched, and the similarities among the spectral curves are calculated using the matched points. The Airborne Visible Infrared Imaging Spectrometer (AVIRIS) and Reflective Optics System Imaging Spectrometer (ROSIS) hyperspectral image datasets are then selected to test the effect of the proposed index. The practical experiments indicate that the proposed index can achieve higher precision and fewer points than the traditional spectral information divergence and spectral angle match.

Accelerating magnetic resonance fingerprinting (MRF) using t-blipped simultaneous multislice (SMS) acquisition.

PURPOSE: We incorporate simultaneous multislice (SMS) acquisition into MR fingerprinting (MRF) to accelerate the MRF acquisition. METHODS: The t-Blipped SMS-MRF method is achieved by adding a Gz blip before each data acquisition window and balancing it with a Gz blip of opposing polarity at the end of each TR. Thus the signal from different simultaneously excited slices are encoded with different phases without disturbing the signal evolution. Furthermore, by varying the Gz blip area and/or polarity as a function of repetition time, the slices' differential phase can also be made to vary as a function of time. For reconstruction of t-Blipped SMS-MRF data, we demonstrate a combined slice-direction SENSE and modified dictionary matching method. RESULTS: In Monte Carlo simulation, the parameter mapping from multiband factor (MB) = 2 t-Blipped SMS-MRF shows good accuracy and precision when compared with results from reference conventional MRF data with concordance correlation coefficients (CCC) of 0.96 for T1 estimates and 0.90 for T2 estimates. For in vivo experiments, T1 and T2 maps from MB=2 t-Blipped SMS-MRF have a high agreement with ones from conventional MRF. CONCLUSION: The MB=2 t-Blipped SMS-MRF acquisition/reconstruction method has been demonstrated and validated to provide more rapid parameter mapping in the MRF framework.