A Robust Gene Expression Prognostic Signature for Overall Survival in High-Grade Serous Ovarian Cancer.

The objective of this research was to develop a robust gene expression-based prognostic signature and scoring system for predicting overall survival (OS) of patients with high-grade serous ovarian cancer (HGSOC). Transcriptomic data of HGSOC patients were obtained from six independent studies in the NCBI GEO database. Genes significantly deregulated and associated with OS in HGSOCs were selected using GEO2R and Kaplan-Meier analysis with log-rank testing, respectively. Enrichment analysis for biological processes and pathways was performed using Gene Ontology analysis. A resampling/cross-validation method with Cox regression analysis was used to identify a novel gene expression-based signature associated with OS, and a prognostic scoring system was developed and further validated in nine independent HGSOC datasets. We first identified 488 significantly deregulated genes in HGSOC patients, of which 232 were found to be significantly associated with their OS. These genes were significantly enriched for cell cycle division, epithelial cell differentiation, p53 signaling pathway, vasculature development, and other processes. A novel 11-gene prognostic signature was identified and a prognostic scoring system was developed, which robustly predicted OS in HGSOC patients in 100 sampling test sets. The scoring system was further validated successfully in nine additional HGSOC public datasets. In conclusion, our integrative bioinformatics study combining transcriptomic and clinical data established an 11-gene prognostic signature for robust and reproducible prediction of OS in HGSOC patients. This signature could be of clinical value for guiding therapeutic selection and individualized treatment

China’s Missing Pigs: Correcting China’s Hog Inventory Data Using a Machine Learning Approach

Small sample size often limits forecasting tasks such as the prediction of production, yield, and consumption of agricultural products. Machine learning offers an appealing alternative to traditional forecasting methods. In particular, Support Vector Regression has superior forecasting performance in small sample applications. In this article, we introduce Support Vector Regression via an application to China’s hog market. Since 2014, China’s hog inventory data has experienced an abnormal decline that contradicts price and consumption trends. We use Support Vector Regression to predict the true inventory based on the price-inventory relationship before 2014. We show that, in this application with a small sample size, Support Vector Regression out-performs neural networks, random forest, and linear regression. Predicted hog inventory decreased by 3.9% from November 2013 to September 2017, instead of the 25.4% decrease in the reported data

Advantage of quantum coherence in postselected metrology

In conventional measurement, to reach the greatest accuracy of parameter estimation, all samples must be measured since each independent sample contains the same quantum Fisher information. In postselected metrology, postselection can concentrate the quantum Fisher information of the initial samples into a tiny post-selected sub-ensemble. It has been proven that this quantum advantage can not be realized in any classically commuting theory. In this work, we present that the advantage of postselection in weak value amplification (WVA) can not be achieved without quantum coherence. The quantum coherence of the initial system is closely related to the preparation costs and measurement costs in parameter estimation. With the increase of initial quantum coherence, the joint values of preparation costs and measurement costs can be optimized to smaller. Moreover, we derive an analytical tradeoff relation between the preparation, measurement and the quantum coherence. We further experimentally test the tradeoff relation in a linear optical setup. The experimental and theoretical results are in good agreement and show that the quantum coherence plays a key role in bounding the resource costs in the postselected metrology process

The 2021 X-ray outburst of magnetar SGR J1935+2154 -- I. Spectral properties

Over a period of multiple active episodes between January 2021 and January 2022, the magnetar SGR J1935+2154 emitted a total of 82 bursts observed by GECAM-B. Temporal and spectral analyses reveal that the bursts have an average duration of $\sim$145 ms and a fluence ranging from $1.2 \times 10^{-8} \ \mathrm{erg \cdot cm^{-2}}$to$3.7 \times 10^{-5} \ \mathrm{erg \cdot cm^{-2}}$(30 - 200 keV). The spectral properties of these bursts are similar to those of earlier active episodes. Specifically, we find that the emission area of the Double Black Body (BB2) model shows a Log-Linear correlation to its temperature, and there is a weak relation between fluence and$E_{\mathrm{peak}}$(or$\alpha$) in the Cut-Off Power Law (CPL) model. However, we note that the temperature distributions of BB2/BB models in GECAM-B samples are different from those in GBM-GECAM samples, due to differences in the energy range used for fitting. To understand this difference, we propose a Multi-Temperature Black Body (MBB) model, assuming that the BB temperatures follow a power law distribution. Our analysis shows that the minimum temperature$kT_{\mathrm{min}} \sim 5$ keV of the MBB model, which is consistent between GECAM-B and GBM-GECAM. This indicates that both samples originated from similar magnetar bursts. We also reveal the spectra of magnetar bursts tend to be soft. It indicates that magnetar bursts may be composed of multiple low BB temperatures and the majority of the BB temperatures are concentrated around the minimum temperature

Effect of Modified Roux-en-Y Gastric Bypass Surgery on GLP-1, GIP in Patients with Type 2 Diabetes Mellitus

The type 2 diabetes mellitus (T2DM) is one of the most serious diseases that threaten public health. Modified gastric bypass surgery has been applied to the treatment of T2DM patients in the 1990s, but the therapeutic mechanism to this function is still unclear. The aim of this study was to further clarify the effect and the mechanism of modified gastric bypass surgery on glucose metabolism in patients with T2DM. In the study, the incretin indexes and blood glucose indexes were analyzed before surgery and 1 week and 1, 3, and 6 months after surgery. The results suggested that modified Roux-en-Y gastric bypass can promote GLP-1 secretion in patients with T2DM, while reducing the secretion of GIP. Thus it could effectively control blood glucose of patients with T2DM

The role of spinal GABAB receptors in cancer-induced bone pain in rats

Cancer-induced bone pain (CIBP) remains a major challenge in advanced cancer patients due to our lack of understanding of its mechanisms. Previous studies have demonstrated the vital role of GABAB receptors (GABABRs) in regulating nociception and various neuropathic pain models have shown diminished activity of GABABRs. However, the role of spinal GABABRs in CIBP remains largely unknown. In this study, we investigated the specific cellular mechanisms of GABABRs in the development and maintenance of CIBP in rats. Our behavioral results show that both acute and chronic intrathecal treatment with baclofen, a GABABR agonist, significantly attenuated CIBP-induced mechanical allodynia and ambulatory pain. The expression levels of GABABRs were significantly decreased in a time-dependent manner and colocalized mostly with neuron and a minority with astrocyte and microglia. Chronic treatment with baclofen restored the expression of GABABRs and markedly inhibited the activation of cAMP-dependent protein kinase (PKA) and the cAMP-response element-binding protein (CREB) signaling pathway