H

With the help of a stochastic bounded real lemma, we deal with finite horizon H2/H∞ control problem for discrete-time MJLS, whose Markov chain takes values in an infinite set. Besides, a unified control design for H2, H∞, and H2/H∞ is given

Study on the Impact of Private Enterprises\u27 Participation in the Mixed Reform of State-owned Enterprises on the Value Preservation and Appreciation of State-owned Assets

State-owned listed companies in the commercial category in Shanghai and Shenzhen A-shares from 2013 to 2020 were selected as the research sample. Data related to the shareholding and delegated behavior of private shareholders among the top ten shareholders are utilized. Using a fixed-effects model, we empirically analyze the impact of private companies\u27 participation in the mixed reform of state-owned enterprises on the value preservation and appreciation of state-owned assets at the equity level and the management right level. Explore the moderating effects of internal control and the level of market-oriented development on the above relationships. The study shows that the participation of private enterprises in the mixed reform of SOEs can effectively contribute to the value preservation and appreciation of state-owned assets, both at the equity level and at the management level. Meanwhile, the level of internal control of SOEs has a significant positive moderating effect on the relationship between the participation of private firms in SOEs\u27 mixed reform and the value-added of SOEs\u27 assets; The participation of private firms can effectively compensate for the impact of insufficient market development on the value-added of SOEs\u27 assets

Genetically determined blood pressure, antihypertensive drug classes, and frailty: A Mendelian randomization study

Observational studies have suggested that the use of antihypertensive drugs was associated with the risk of frailty; however, these findings may be biased by confounding and reverse causality. This study aimed to explore the effect of genetically predicted lifelong lowering blood pressure (BP) through different antihypertensive medications on frailty. One‐sample Mendelian randomization (MR) and summary data‐based MR (SMR) were applied. We utilized two kinds of genetic instruments to proxy the antihypertensive medications, including genetic variants within or nearby drugs target genes associated with systolic/diastolic BP, and expression level of the corresponding gene. Among 298,618 UK Biobank participants, one‐sample MR analysis observed that genetically proxied BB use (relative risk ratios, 0.76; 95% CI, 0.65–0.90; p = 0.001) and CCB use (0.83; 0.72–0.95; p = 0.007), equivalent to a 10‐mm Hg reduction in systolic BP, was significantly associated with lower risk of pre‐frailty. In addition, although not statistically significant, the effect directions of systolic BP through ACEi variants (0.72; 0.39–1.33; p = 0.296) or thiazides variants (0.74; 0.53–1.03; p = 0.072) on pre‐frailty were also protective. Similar results were obtained in analyses for diastolic BP. SMR of expression in artery showed that decreased expression level of KCNH2, a target gene of BBs, was associated with lower frailty index (beta −0.02, p = 2.87 × 10−4). This MR analysis found evidence that the use of BBs and CCBs was potentially associated with reduced frailty risk in the general population, and identified KCNH2 as a promising target for further clinical trials to prevent manifestations of frailty

Depletion of TRRAP induces p53-independent senescence in liver cancer by downregulating mitotic genes

Hepatocellular carcinoma (HCC) is an aggressive subtype of liver cancer with few effective treatments and the underlying mechanisms that drive HCC pathogenesis remain poorly characterized. Identifying genes and pathways essential for HCC cell growth will aid the development of new targeted therapies for HCC. Using a kinome CRISPR screen in three human HCC cell lines, we identified transformation/transcription domain-associated protein (TRRAP) as an essential gene for HCC cell proliferation. TRRAP has been implicated in oncogenic transformation, but how it functions in cancer cell proliferation is not established. Here, we show that depletion of TRRAP or its co-factor, histone acetyltransferase KAT5, inhibits HCC cell growth via induction of p53- and p21-independent senescence. Integrated cancer genomics analyses using patient data and RNA-sequencing identified mitotic genes as key TRRAP/KAT5 targets in HCC, and subsequent cell cycle analyses revealed that TRRAP- and KAT5-depleted cells are arrested at G2/M phase. Depletion of TOP2A, a mitotic gene and TRRAP/KAT5 target, was sufficient to recapitulate the senescent phenotype of TRRAP/KAT5 knockdown. CONCLUSION: Our results uncover a role for TRRAP/KAT5 in promoting HCC cell proliferation via activation of mitotic genes. Targeting the TRRAP/KAT5 complex is a potential therapeutic strategy for HCC

YAP1 withdrawal in hepatoblastoma drives therapeutic differentiation of tumor cells to functional hepatocyte-like cells

BACKGROUND and AIMS: Despite surgical and chemotherapeutic advances, the five-year survival rate for Stage IV Hepatoblastoma (HB), the predominant pediatric liver tumor, remains at 27%. YAP1 and beta-Catenin co-activation occurs in 80% of children\u27s HB; however, a lack of conditional genetic models precludes tumor maintenance exploration. Thus, the need for a targeted therapy remains unmet. Given the predominance of YAP1 and beta-Catenin activation in HB, we sought to evaluate YAP1 as a therapeutic target in HB. APPROACH and RESULTS: We engineered the first conditional HB murine model using hydrodynamic injection to deliver transposon plasmids encoding inducible YAP1(S127A) , constitutive beta-Catenin(DelN90) , and a luciferase reporter to murine liver. Tumor regression was evaluated using bioluminescent imaging, and tumor landscape characterized using RNA and ATAC sequencing, and DNA foot-printing. Here we show that YAP1(S127A) withdrawal mediates \u3e90% tumor regression with survival for 230+ days in mice. YAP1 (S127A) withdrawal promotes apoptosis in a subset of tumor cells and in remaining cells induces a cell fate switch driving therapeutic differentiation of HB tumors into Ki-67 negative hbHep cells with hepatocyte-like morphology and mature hepatocyte gene expression. YAP1 (S127A) withdrawal drives formation of hbHeps by modulating liver differentiation transcription factor (TF) occupancy. Indeed, tumor-derived hbHeps, consistent with their reprogrammed transcriptional landscape, regain partial hepatocyte function and rescue liver damage in mice. CONCLUSIONS: YAP1(S127A) withdrawal, without silencing oncogenic beta-Catenin, significantly regresses hepatoblastoma, providing the first in vivo data to support YAP1 as a therapeutic target for HB. YAP1(S127A) withdrawal alone sufficiently drives long-term regression in hepatoblastoma because it promotes cell death in a subset of tumor cells and modulates transcription factor occupancy to reverse the fate of residual tumor cells to mimic functional hepatocytes

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Chemical modifications of adenine base editor mRNA and guide RNA expand its application scope

CRISPR-Cas9-associated base editing is a promising tool to correct pathogenic single nucleotide mutations in research or therapeutic settings. Efficient base editing requires cellular exposure to levels of base editors that can be difficult to attain in hard-to-transfect cells or in vivo. Here we engineer a chemically modified mRNA-encoded adenine base editor that mediates robust editing at various cellular genomic sites together with moderately modified guide RNA, and show its therapeutic potential in correcting pathogenic single nucleotide mutations in cell and animal models of diseases. The optimized chemical modifications of adenine base editor mRNA and guide RNA expand the applicability of CRISPR-associated gene editing tools in vitro and in vivo

Integrated analysis reveals potential significance of FKBP5 in the prognosis and immunity of osteoarthritis and pan-cancer

Background: The high disability rate of osteoarthritis (OA), a joint disease with an insidious onset and widespread effects, places a heavy financial burden on patients, families, and society. Traditional diagnostic approaches, including radiology and physical examination, cannot achieve early-stage screening of OA and thus, miss early intervention for patients. Therefore, the need of biomarkers for the early diagnosis of OA is crucial. Results: A total of 390 differentially expressed genes (DEGs) were identified from the training set, and 1077 key module genes were found by constructing a weighted gene co-expression network, and 161 key genes were obtained as a result. Four diagnostic marker genes highly associated with OA were screened for key genes using machine learning algorithms, and the resulting nomogram model showed excellent predictive power and clinical value. After further background studies, immune infiltration and functional enrichment analysis, we found that FKBP5 may play an important role in the prognosis and immune infiltration of multiple cancers, and this hypothesis was verified by pan-cancer analysis. Conclusions: We screened four diagnostic marker genes (FKBP5, EPYC, KLF9 and PDZRN4) that are highly associated with OA. And this led to a diagnostic model, which was assessed to have good predictive power and clinical value. FKBP5 may be a potential intervention target for human diseases such as osteoarthritis and tumors. How to cite: Xiao Y, Wang Y, Xu X, et al. Integrated analysis reveals potential significance of FKBP5 in the prognosis and immunity of osteoarthritis and pan-cancer. Electron J Biotechnol 2023;65. https://doi.org/10.1016/j.ejbt.2023.05.002