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BACKGROUND: Regulatory T cells (Tregs) are central to determine immune response, thus targeting Tregs for immunotherapy is a promising strategy against tumor development and metastasis. OBJECTIVES: The objective of this study was to identify genes for targeting Tregs to improve the outcome of HCC. METHODS: We integrated expression data from different samples to remove batch effects and further applied embedding function in Scanpy to conduct sub-clustering of CD4+ T cells in HCC for each of two independent scRNA-seq data. The activity of transcription factors (TFs) was inferred by DoRothEA. Gene expression network analysis was performed in WGCNA R package. We finally used R packages (survminer and survival) to conduct survival analysis. Multiplex immunofluorescence analysis was performed to validate the result from bioinformatic analyses. RESULTS: We found that regulator of G protein signaling 1 (RGS1) expression was significantly elevated in Tregs compared to other CD4+ T cells in two independent public scRNA-seq datasets, and increased RGS1 predicted inferior clinical outcome of HCC patients. Multiplex immunofluorescence analysis supported that the higher expression of RGS1 in HCC Tregs in tumor tissue compared to it in adjacent tissue. Moreover, RGS1 expression in Tregs was positively correlated with the expression of marker genes of Tregs, C-X-C chemokine receptor 4 (CXCR4), and three CXCR4-dependent genes in both scRNA-seq and bulk RNA-seq data. We further identified that these three genes were selectively expressed in Tregs as compared to other CD4+ T cells. The activities of two transcription factors, recombination signal binding protein for immunoglobulin kappa J region (RBPJ) and yin yang 1 (YY1), were significantly different in HCC Tregs with RGS1 high and RGS1 low. CONCLUSIONS: Our findings suggested that RGS1 may regulate Treg function possibly through CXCR4 signaling and RGS1 could be a potential target to improve responses for immunotherapy in HCC.

PDF file - 499K, Recombinant his-RXRa was unable to interact with GST-hNRF2 mutant fusion protein that lacked residues 209-316 between the Neh5 and Neh6 domains.

The transcription factor NRF2 (NFE2L2) is a pivotal activator of genes encoding cytoprotective and detoxifying enzymes that limit the action of cytotoxic therapies in cancer. NRF2 acts by binding antioxidant response elements (ARE) in its target genes, but there is relatively limited knowledge about how it is negatively controlled. Here, we report that retinoic X receptor alpha (RXRα) is a hitherto unrecognized repressor of NRF2. RNAi-mediated knockdown of RXRα increased basal ARE-driven gene expression and induction of ARE-driven genes by the NRF2 activator tert-butylhydroquinone (tBHQ). Conversely, overexpression of RXRα decreased ARE-driven gene expression. Biochemical investigations showed that RXRα interacts physically with NRF2 in cancer cells and in murine small intestine and liver tissues. Furthermore, RXRα bound to ARE sequences in the promoters of NRF2-regulated genes. RXRα loading onto AREs was concomitant with the presence of NRF2, supporting the hypothesis that a direct interaction between the two proteins on gene promoters accounts for the antagonism of ARE-driven gene expression. Mutation analyses revealed that interaction between the two transcription factors involves the DNA-binding domain of RXRα and a region comprising amino acids 209-316 in human NRF2 that had not been defined functionally, but that we now designate as the NRF2-ECH homology (Neh) 7 domain. In non–small cell lung cancer cells where NRF2 levels are elevated, RXRα expression downregulated NRF2 and sensitized cells to the cytotoxic effects of therapeutic drugs. In summary, our findings show that RXRα diminishes cytoprotection by NRF2 by binding directly to the newly defined Neh7 domain in NRF2. Cancer Res; 73(10); 3097–108. ©2013 AACR.

PDF file - 572K, Cellular co-localization of ectopic GFP and RFP in HEK293T cells.

PDF file - 239K, The interaction of mNrf2 with RXRa in MCF7-RXRa cells.

PDF file - 288K, The binding of NRF2 to the ARE sites in MCF7 and MCF7-RXRo cells.

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PDF file - 97K, Includes plasmid construction data, GST pull-down assay, and immunoprecipitation data. Also includes supplementary references.

Cellular stresses elicit signaling cascades that are capable of both mitigating the inciting dysfunction and initiating cell death when the stress cannot be overcome. During endoplasmic reticulum (ER) stress, the transcription factor CHOP is widely recognized to promote cell death. Yet CHOP carries out this function largely by augmenting protein synthesis, which is an essential component of recovery from stress. In addition, the mechanisms that drive cell fate during ER stress have largely been explored under super-physiological experimental conditions that do not permit cellular adaptation. Thus, it is not clear whether CHOP also has a beneficial role during that adaptation. Here, we have created a new, versatile, genetically modifiedChopallele, which we combined with single cell analysis and stresses of physiological intensity, to rigorously examine the contribution of CHOP to cell fate. Surprisingly, we found that, within the cell population, CHOP paradoxically promoted death in some cells but proliferation—and hence recovery—in others. Strikingly, this function of CHOP conferred a stress-specific competitive growth advantage to wild-type cells over cells lacking CHOP. The dynamics of CHOP expression and UPR activation at the single cell level suggested that, by promoting protein synthesis, CHOP maximizes UPR activation which in turn favors stress resolution, subsequent UPR deactivation, and proliferation. Taken together, these findings suggest that CHOP’s function can be better described as a “stress test” that drives cells into either of two mutually exclusive fates—adaptation or death—during stress. They point to a previously unappreciated pro-survival function of CHOP during stresses of physiological intensity.

Visible light sensing technique has shown great potential in locating human in the building. For indoor positioning using fingerprints, how to reduce the offline labor cost while maintaining accurate location estimation is of vital importance. In this paper, a novel coarse fingerprint-assisted device-free localization (DFL) approach is proposed for locating multiple targets via visible light sensing, which does not need too much calibration effort to build high accurate fingerprint database. Furthermore, a successive cancellation algorithm based on the coarse single target fingerprint database is designed to address the problem of pseudo target positioning in the multi-target DFL. Since the intersection points of shadowed links could not be guaranteed to be symmetrically located around the center of mass of the human body, the estimated location would be biased from the true location of the target. To solve this problem, a convex hull-based localization algorithm is introduced to improve positioning accuracy. Extensive simulation results show that our proposed approach exhibits superior performance in terms of target counting and localization accuracy.

The operation and planning of power systems depend heavily on M-LTLF, which is complicated and nonlinear, making it challenging for conventional medium- and long-term forecasting models to produce reliable results. The SARIMA model is chosen for M-LTLF in this study, and the model’s parameters are tuned. This study takes the electricity consumption data of the whole Yunnan as the research object. Among them, the electricity consumption data from 2008 to 2018 is used as a training sample for fitting and analysis, and the electricity consumption of the whole province is predicted from 2019 to 2020. The end results demonstrate the viability and efficacy of the SARIMA model for M-LTLF.

Headland and field edges have a higher traffic frequency compared to the field centre, which causes more compaction. Most repeated compaction is located at the field entrance area and headland during machinery turning and material transporting that takes place during the fertilisation, herbicide laying, and harvesting of fields, which could cause soil structure destruction and yield reduction. In this study, the differences between headland, field edges, and field centre were studied using yield maps and the vegetation indices (VIs) calculated by the Google Earth Engine (GEE). First, thirteen yield maps from 2019 to 2022 were used to measure the yield difference between headland, field edges, and field centre. Then, one hundred and eleven fields from northern Italy were used to compare the vegetation indices (VIs) differences between headland, field edges, and field centre area. Then, field size, sand, and clay content were calculated and estimated from GEE. The yield map showed that headland and field edges were 12.20% and 2.49% lower than the field centre. The results of the comparison of the VIs showed that headlands and field edges had lower values compared to the field centre, with reductions of 4.27% and 2.70% in the normalised difference vegetation index (NDVI), 4.17% and 2.67% in the green normalized difference vegetation index (GNDVI), and 5.87% and 3.59% in the normalised difference red edge (NDRE). Additionally, the results indicated that the yield losses in the headland and field edges increased as the clay content increased and sand content decreased. These findings suggest that soil compaction and structural damage caused by the higher traffic frequency in the headland and field edges negatively affect crop yield.

Ruili Yu,1 Tingyi Sun,1 Xianwei Zhang,1 Zhen Li,1 Yang Xu,2 Kaihua Liu,2 Yuqian Shi,2 Xue Wu,2 Yang Shao,2,3 Lingfei Kong1 1Department of Pathology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China; 2Geneseeq Research Institute, Nanjing Geneseeq Technology Inc., Nanjing, Jiangsu, People’s Republic of China; 3School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of ChinaCorrespondence: Lingfei KongDepartment of Pathology, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, 7 Weiwu Road, Zhengzhou, 450003, Henan Province, People’s Republic of ChinaTel +86 138 0386 8286Email lfkong9@163.comPurpose: TP53 is the most frequently mutated gene in gastric cancer and it can be potentially used for gastric cancer diagnosis and screening. However, standardized clinical approaches that could accurately and cost-effectively detect TP53 mutations in gastric cancer are largely lagged behind.Patients and Methods: We conducted next-generation sequencing (NGS) analysis of 425 cancer-related genes in 42 gastric cancer patients in our cohort. A 1313-patient cohort derived from the cBioPortal database was used for validation. We performed immunohistochemistry (IHC) staining with four commonly used p53 antibodies, and the NGS results were used as the gold standard to optimize the IHC threshold for each antibody.Results: By NGS analysis, we found that around 80% of gastric cancer patients in our cohort harbored TP53 alterations. Genetic alterations of BRCA1/ 2 or KMT2B were mostly exclusive with TP53 mutations, so were the MSI status or low grade of tumors. These results were further validated using the data from cBioPortal. We then used the NGS-derived TP53 status to optimize four commonly used IHC antibodies for detecting TP53 mutations. We showed that all antibodies could achieve more than 93% accuracy when proper IHC positivity thresholds were used, especially for the SP5 antibody that could reach 100% sensitivity and specificity with the 20% threshold.Conclusion: Our results indicated that exclusivity between TP53 and BRCA mutations could be potentially used as a cost-effective way to predict BRCA status. Also, setting proper IHC thresholds for each specific antibody is critical to accurately detect TP53 mutations and facilitate disease diagnosis.Keywords: TP53, gastric cancer, next-generation sequencing, co-mutation, immunohistochemistry threshold