Auto-adjustable Spoiler Control System

Veroptimal Solution would like to present the Auto-adjustable Spoiler Control System (ASCS).  This system is a feedback control system which is able to either automatically or manually change the elevation and angle of attack (AOA) of the car spoiler. Research shows that when the spoiler elevation is low, or stays very close to the surface of the boot lid, the spoiler can more effectively spoil out the undesirable flows and reshape airflow streams around the vehicle.  The major benefit to this would be the reduction of drag and the increase of fuel efficiency. When the spoiler elevation is high, the AOA of the spoiler plays a crucial role because the angle determines how much air should be deflected upwards and this generates downforce at the rear of the vehicle

A comprehensive review on motion trajectory reconstruction for EEG-based brain-computer interface

The advance in neuroscience and computer technology over the past decades have made brain-computer interface (BCI) a most promising area of neurorehabilitation and neurophysiology research. Limb motion decoding has gradually become a hot topic in the field of BCI. Decoding neural activity related to limb movement trajectory is considered to be of great help to the development of assistive and rehabilitation strategies for motor-impaired users. Although a variety of decoding methods have been proposed for limb trajectory reconstruction, there does not yet exist a review that covers the performance evaluation of these decoding methods. To alleviate this vacancy, in this paper, we evaluate EEG-based limb trajectory decoding methods regarding their advantages and disadvantages from a variety of perspectives. Specifically, we first introduce the differences in motor execution and motor imagery in limb trajectory reconstruction with different spaces (2D and 3D). Then, we discuss the limb motion trajectory reconstruction methods including experiment paradigm, EEG pre-processing, feature extraction and selection, decoding methods, and result evaluation. Finally, we expound on the open problem and future outlooks

Precision Cas9 Genome Editing in vivo with All-in-one, Self-targeting AAV Vectors [preprint]

Adeno-associated virus (AAV) vectors are important delivery platforms for therapeutic genome editing but are severely constrained by cargo limits, especially for large effectors like Cas9s. Simultaneous delivery of multiple vectors can limit dose and efficacy and increase safety risks. The use of compact effectors has enabled single-AAV delivery of Cas9s with 1-3 guides for edits that use end-joining repair pathways, but many precise edits that correct disease-causing mutations in vivo require homology-directed repair (HDR) templates. Here, we describe single-vector, ~4.8-kb AAV platforms that express Nme2Cas9 and either two sgRNAs to produce segmental deletions, or a single sgRNA with an HDR template. We also examine the utility of Nme2Cas9 target sites in the vector for self-inactivation. We demonstrate that these platforms can effectively treat two disease models [type I hereditary tyrosinemia (HT-I) and mucopolysaccharidosis type I (MPS-I)] in mice. These results will enable single-vector AAVs to achieve diverse therapeutic genome editing outcomes

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

Does the built environment of settlements affect our sentiments? A multi-level and non-linear analysis of Xiamen, China, using social media data

IntroductionHumans spend most of their time in settlements, and the built environment of settlements may affect the residents' sentiments. Research in this field is interdisciplinary, integrating urban planning and public health. However, it has been limited by the difficulty of quantifying subjective sentiments and the small sample size.MethodsThis study uses 147,613 Weibo text check-ins in Xiamen from 2017 to quantify residents' sentiments in 1,096 neighborhoods in the city. A multilevel regression model and gradient boosting decision tree (GBDT) model are used to investigate the multilevel and nonlinear effects of the built environment of neighborhoods and subdistricts on residents' sentiments.ResultsThe results show the following: (1) The multilevel regression model indicates that at the neighborhood level, a high land value, low plot ratio, low population density, and neighborhoods close to water are more likely to improve the residents' sentiments. At the subdistrict level, more green space and commercial land, less industry, higher building density and road density, and a smaller migrant population are more likely to promote positive sentiments. Approximately 19% of the total variance in the sentiments occurred among subdistricts. (2) The proportion of green space and commercial land, and the density of buildings and roads are linearly correlated with residents' sentiments. The land value is a basic need and exhibits a nonlinear correlation with sentiments. The plot ratio, population density, and the proportions of industrial land and the migrant population are advanced needs and are nonlinearly correlated with sentiments.DiscussionThe quantitative analysis of sentiments enables setting a threshold of the influence of the built environment on residents' sentiments in neighborhoods and surrounding areas. Our results provide data support for urban planning and implementing targeted measures to improve the living environment of residents

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

The Relationship between Gene Polymorphism of miRNAs Regulating FGA and Schizophrenia

AIM: To investigate the relationship between the polymorphism of related gene loci of miRNAs regulated fibrinopeptide A and schizophrenia. Lay the foundation for the aetiology of schizophrenia. METHODS: Adapt to the phase match of sex and age case-control study, a total of 513 Chinese Han patients with schizophrenia were selected as the case group, 513 normal healthy persons as a control group. Obtaining SNPs information of the FGA gene by querying the dbSNP database, and reference HapMap database included SNPs site frequency information for screening. The frequency distributions of SNPs were genotyped by iMLDR® SNP detection technology. Two SNPs (pre-hsa-miR-605rs2043556 T>C, pre-hsa-miR-499a/pre-hsa-miR-499brs4909237 T < C) were analyzed to demonstrate their association with susceptibility to schizophrenia. RESULTS: There were no significant differences between patients and controls in genotype and allele distribution of SNPs（rs2043556 and rs4909237）in the precursor region of hsa-miR-605 and pre-hsa-miR-499a/pre-hsa-miR-499b. Their gene-gene interaction, which suggests that the polymorphisms of miRNA genes might not contribute to schizophrenia susceptibility in the Han Chinese population. CONCLUSION: No significant difference existed between schizophrenic patients and controls in SNP (rs2043556 and rs4909237) in the precursor region of hsa-miR-605 and pre-hsa-miR-499a/pre-hsa-miR-499b. There may not regulate FGA gene expression. Thus, hsa-miR-605 and pre-hsa-miR-499a/pre-hsa-miR-499b may not influence the risks of schizophrenia

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

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

Dynamic Covalent Hydrogels: Strong yet Dynamic

Hydrogels are crosslinked polymer networks with time-dependent mechanical response. The overall mechanical properties are correlated with the dynamics of the crosslinks. Generally, hydrogels crosslinked by permanent chemical crosslinks are strong but static, while hydrogels crosslinked by physical interactions are weak but dynamic. It is highly desirable to create synthetic hydrogels that possess strong mechanical stability yet remain dynamic for various applications, such as drug delivery cargos, tissue engineering scaffolds, and shape-memory materials. Recently, with the introduction of dynamic covalent chemistry, the seemingly conflicting mechanical properties, i.e., stability and dynamics, have been successfully combined in the same hydrogels. Dynamic covalent bonds are mechanically stable yet still capable of exchanging, dissociating, or switching in response to external stimuli, empowering the hydrogels with self-healing properties, injectability and suitability for postprocessing and additive manufacturing. Here in this review, we first summarize the common dynamic covalent bonds used in hydrogel networks based on various chemical reaction mechanisms and the mechanical strength of these bonds at the single molecule level. Next, we discuss how dynamic covalent chemistry makes hydrogel materials more dynamic from the materials perspective. Furthermore, we highlight the challenges and future perspectives of dynamic covalent hydrogels