The expression and role of protein kinase C (PKC) epsilon in clear cell renal cell carcinoma

Protein kinase C epsilon (PKCε), an oncogene overexpressed in several human cancers, is involved in cell proliferation, migration, invasion, and survival. However, its roles in clear cell renal cell carcinoma (RCC) are unclear. This study aimed to investigate the functions of PKCε in RCC, especially in clear cell RCC, to determine the possibility of using it as a therapeutic target. By immunohistochemistry, we found that the expression of PKCε was up-regulated in RCCs and was associated with tumor Fuhrman grade and T stage in clear cell RCCs. Clone formation, wound healing, and Borden assays showed that down-regulating PKCε by RNA interference resulted in inhibition of the growth, migration, and invasion of clear cell RCC cell line 769P and, more importantly, sensitized cells to chemotherapeutic drugs as indicated by enhanced activity of caspase-3 in PKCε siRNA-transfected cells. These results indicate that the overexpression of PKCε is associated with an aggressive phenotype of clear cell RCC and may be a potential therapeutic target for this disease

Diet-derived circulating antioxidants and risk of epilepsy: a Mendelian randomization study

BackgroundPrevious studies suggest a link between diet-derived circulating antioxidants and epilepsy, but the causal relationship is unclear. This study aims to investigate the causal effect of these antioxidants on epilepsy.MethodsTo assess the causal link between dietary antioxidants and epilepsy risk, we conducted a two-sample Mendelian randomization (MR) analysis. This involved examining antioxidants such as zinc, selenium, α- and γ-tocopherol, vitamin A (retinol), vitamin C (ascorbate), and vitamin E (α-tocopherol). We utilized instrumental variables (IVs) which were genetic variations highly associated with these commonly used antioxidants. Exposure data were sourced from a comprehensive genome-wide association study (GWAS). We aggregated data from the International League Against Epilepsy (ILAE) Consortium sample, which included various types of epilepsy, as an outcome variable. Finally, we applied the inverse variance weighting method and conducted sensitivity analyses for further validation.ResultsBased on the primary MR estimates and subsequent sensitivity analyses, the inverse variance weighting (IVW) method revealed that a genetically predicted increase in zinc per standard deviation was positively associated with three types of epilepsy. This includes all types of epilepsy (OR = 1.06, 95% CI: 1.02–1.11, p = 0.008), generalized epilepsy (OR = 1.13, 95% CI: 1.01–1.25, p = 0.030), and focal epilepsy (documented hippocampal sclerosis) (OR = 1.01, 95% CI: 1.00–1.02, p = 0.025). However, there is no evidence indicating that other antioxidants obtained from the diet affect the increase of epilepsy either positively or negatively.ConclusionOur research indicates that the risk of developing epilepsy may be directly linked to the genetic prediction of zinc, whereas no such association was found for other antioxidants

The role of macrophages in gastric cancer

As one of the deadliest cancers of the gastrointestinal tract, there has been limited improvement in long-term survival rates for gastric cancer (GC) in recent decades. The poor prognosis is attributed to difficulties in early detection, minimal opportunity for radical resection and resistance to chemotherapy and radiation. Macrophages are among the most abundant infiltrating immune cells in the GC stroma. These cells engage in crosstalk with cancer cells, adipocytes and other stromal cells to regulate metabolic, inflammatory and immune status, generating an immunosuppressive tumour microenvironment (TME) and ultimately promoting tumour initiation and progression. In this review, we summarise recent advances in our understanding of the origin of macrophages and their types and polarisation in cancer and provide an overview of the role of macrophages in GC carcinogenesis and development and their interaction with the GC immune microenvironment and flora. In addition, we explore the role of macrophages in preclinical and clinical trials on drug resistance and in treatment of GC to assess their potential therapeutic value in this disease

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Feature Optimization of EEG Signals Based on Ant Colony Algorithm

EEG signal can be understood as a kind of bioelectrical signal, which can reflect emotional information when the body is in different emotional states. However, the data collected are often high-dimensional. including many irrelevant or redundant features. The high-dimensional features make the space cost increase exponentially, which brings many difficulties to the research. Ant colony optimization algorithm, a swarm intelligence algorithm, can be used for feature selection. Ant colony optimization algorithm is used for feature selection of EEG signals. The feature subset to be selected is trained cooperatively and learned actively. The classification accuracy is evaluated through convolutional neural network, and the optimal subset is selected from the iterative local optimal solution. The results show that the ant colony optimization algorithm can effectively reduce the time complexity and calculation cost, Improve the accuracy of classification

A Double-Smoothing Algorithm for Integrating Satellite Precipitation Products in Areas with Sparsely Distributed In Situ Networks

The spatial distribution of automatic weather stations in regions of western China (e.g., Tibet and southern Xingjiang) is relatively sparse. Due to the considerable spatial variability of precipitation, estimations of rainfall that are interpolated in these areas exhibit considerable uncertainty based on the current observational networks. In this paper, a new statistical method for estimating precipitation is introduced that integrates satellite products and in situ observation data. This method calculates the differences between raster data and point data based on the theory of data assimilation. In regions in which the spatial distribution of automatic weather stations is sparse, a nonparametric kernel-smoothing method is adopted to process the discontinuous data through correction and spatial interpolation. A comparative analysis of the fusion method based on the double-smoothing algorithm proposed here indicated that the method performed better than those used in previous studies based on the average deviation, root mean square error, and correlation coefficient values. Our results indicate that the proposed method is more rational and effective in terms of both the efficiency coefficient and the spatial distribution of the deviations

The Characteristics of the Yangtze Flooding During 1998 and 2020 Based on Atmospheric Water Tracing

Abstract The June‐July Yangtze flooding in 1998 and 2020 drew incredible attention owing to the extreme precipitation events and devastating societal/economic damages. However, the quantitative estimation of the moisture transport mechanism is intensely discussed but still unresolved. Here we investigated two events from a unique perspective of Eulerian atmospheric water tracers that tries to explain the two events from model physics. The results showed that the moisture supplies from the Northwest Pacific decreased despite of different inducements, whereas the southwest summer monsoon (SWSM)‐related moisture supplies exhibited conspicuous enhancements in both events, suggesting that the SWSM‐related moisture supplies controlled the occurrence of Yangtze flooding. The physical processes of the two events were further compared. The 2020 flooding was more severe than the 1998 event, which was related to the stronger advective convergences and in‐stratus condensations of the SWSM‐related moisture