Development of New Chemotherapeutics for Head & Neck Squamous Cell Carcinoma (HNSCC)

The signal transducers and activators of transcription STAT3 and STAT1 share common structure and targets, but they play opposing roles in tumorigenesis. While STAT3 is considered an oncogene that promotes cell survival, proliferation, motility, and immune tolerance, STAT1 enhances inflammation, favors cell cycle arrest, and apoptosis in most tumor cells. STAT3 has been found to be constitutively active in head and neck squamous cell carcinomas (HNSCC) where it promotes the cell cycle and prevents apoptosis, resulting in the proliferation and survival of HNSCC cells. We hypothesize that a small molecule inhibitor of STAT3 that is selective over STAT1 in HNSCC would serve as a powerful cancer therapeutic. The lead compound 669 that was identified through high content screening (HCS) displayed a pSTAT3 inhibition with 10-fold greater selectivity over pSTAT1 in HNSCC cells (pSTAT3 IC50 5.50 ± 1.50 μM (n = 7) vs. pSTAT1 > 50 μM). The mechanism of 669’s effect on the STAT3 pathway remains unknown, however, it does not proceed by a kinase inhibition pathway. This thesis describes the development of a structure activity relationship (SAR) for pSTAT3 inhibitors related to 669. The key reaction to synthesize these analogs is performed in a microwave reactor, which saves time, and is convenient for parallel synthesis

Research on the Reform of Teaching Management Emergency Mechanism in University Based on Big Data

Sudden major public health events once again test the ability of the whole society to deal with emergencies. Universities are no exception. There are many kinds of management work in Colleges and universities, among which teaching management is the most important one, which is also one of the most affected in this epidemic situation. Therefore, in view of the problems of teaching management in Colleges and universities exposed in the epidemic, combined with the characteristics of independent colleges, starting from the aspects of teaching guarantee mechanism, teaching supervision mechanism, teaching process construction, teaching resources construction and so on, the advantages of big data technology, such as large amount of information, easy to communicate and easy to integrate, are fully used to put forward a set of open-minded, perfect mechanism and advanced technology teaching management emergency response mechanism

Sonicverse: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear

Developing embodied agents in simulation has been a key research topic in recent years. Exciting new tasks, algorithms, and benchmarks have been developed in various simulators. However, most of them assume deaf agents in silent environments, while we humans perceive the world with multiple senses. We introduce Sonicverse, a multisensory simulation platform with integrated audio-visual simulation for training household agents that can both see and hear. Sonicverse models realistic continuous audio rendering in 3D environments in real-time. Together with a new audio-visual VR interface that allows humans to interact with agents with audio, Sonicverse enables a series of embodied AI tasks that need audio-visual perception. For semantic audio-visual navigation in particular, we also propose a new multi-task learning model that achieves state-of-the-art performance. In addition, we demonstrate Sonicverse's realism via sim-to-real transfer, which has not been achieved by other simulators: an agent trained in Sonicverse can successfully perform audio-visual navigation in real-world environments. Sonicverse is available at: https://github.com/StanfordVL/Sonicverse.Comment: In ICRA 2023. Project page: https://ai.stanford.edu/~rhgao/sonicverse/. Code: https://github.com/StanfordVL/sonicverse. Gao and Li contributed equally to this work and are in alphabetical orde

The Impact of Fertilizer Amendments on Soil Autotrophic Bacteria and Carbon Emissions in Maize Field on the Semiarid Loess Plateau

Soil autotrophic bacteria play a crucial role in regulating CO2 fixation and crop productivity. However, the information is limited to how fertilization amendments alter soil autotrophic bacterial community, crop yield, and carbon emission efficiency (CEE). Here, we estimated the impact of the structure and co-occurrence network of soil autotrophic bacterial community on maize yield and CEE. A long-term field experiment was conducted with five fertilization treatments in semiarid Loess Plateau, including no amendment (NA), chemical fertilizer (CF), chemical fertilizer plus commercial organic fertilizer (SC), commercial organic fertilizer (SM), and maize straw (MS). The results showed that fertilization amendments impacted the structure and network of soil Calvin–Benson–Bassham (CBB) (cbbL) gene-carrying bacterial community via changing soil pH and NO3–N. Compared with no amendment, the cbbL-carrying bacterial diversity was increased under the SC, SM, and MS treatments but decreased under the CF treatment. Soil autotrophic bacterial network contained distinct microbial modules that consisted of closely associated microbial species. We detected the higher abundances of soil cbbL-carrying bacterial genus Xanthobacter, Bradyrhizobium, and Nitrosospira. Structural equation modeling further suggested that the diversity, composition, and network of autotrophic bacterial community had strongly positive relationships with CEE and maize yield. Taken together, our results suggest that soil autotrophic bacterial community may drive crop productivity and CEE, and mitigate the atmospheric greenhouse effect

Molecular Criteria for Defining the Naive Human Pluripotent State.

Recent studies have aimed to convert cultured human pluripotent cells to a naive state, but it remains unclear to what extent the resulting cells recapitulate in vivo naive pluripotency. Here we propose a set of molecular criteria for evaluating the naive human pluripotent state by comparing it to the human embryo. We show that transcription of transposable elements provides a sensitive measure of the concordance between pluripotent stem cells and early human development. We also show that induction of the naive state is accompanied by genome-wide DNA hypomethylation, which is reversible except at imprinted genes, and that the X chromosome status resembles that of the human preimplantation embryo. However, we did not see efficient incorporation of naive human cells into mouse embryos. Overall, the different naive conditions we tested showed varied relationships to human embryonic states based on molecular criteria, providing a backdrop for future analysis of naive human pluripotency.This study was supported by grants from the Simons Foundation (SFLIFE #286977 to R.J) and in part by the NIH (RO1-CA084198) to R.J., from the Swiss National Science Foundation and the European Research Council (KRABnKAP, No. 268721) to D.T. The work in J.R.E’s laboratory was supported by the Howard Hughes Medical Institute and Gordon and Betty Moore Foundation (GBMF3034) and the Mary K. Chapman Foundation. J.R.E is an Investigator of the Howard Hughes Medical Institute. T.W.T. is supported by a Sir Henry Wellcome Postdoctoral Fellowship (098889/Z/12/Z), J.P. by a Foundation Bettencourt Award and by the Association pour la Recherche sur le Cancer (ARC), M.I. by a postdoctoral training grant from the Fonds de la Recherche en Santé du Québec. R.J. is co-founder of Fate Therapeutics and an adviser to Stemgent.This is the final version of the article. It first appeared from Cell Press via http://www.cell.com/cell-stem-cell/abstract/S1934-5909(16)30161-

The accessible chromatin landscape of the human genome

DNaseI hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers, and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ~2.9 million DHSs that encompass virtually all known experimentally-validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation, and regulatory factor occupancy patterns. We connect ~580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is choreographed with dozens to hundreds of co-activated elements, and the trans-cellular DNaseI sensitivity pattern at a given region can predict cell type-specific functional behaviors. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

NLP-based Cross-Layer 5G Vulnerabilities Detection via Fuzzing Generated Run-Time Profiling

The effectiveness and efficiency of 5G software stack vulnerability and unintended behavior detection are essential for 5G assurance, especially for its applications in critical infrastructures. Scalability and automation are the main challenges in testing approaches and cybersecurity research. In this paper, we propose an innovative approach for automatically detecting vulnerabilities, unintended emergent behaviors, and performance degradation in 5G stacks via run-time profiling documents corresponding to fuzz testing in code repositories. Piloting on srsRAN, we map the run-time profiling via Logging Information (LogInfo) generated by fuzzing test to a high dimensional metric space first and then construct feature spaces based on their timestamp information. Lastly, we further leverage machine learning-based classification algorithms, including Logistic Regression, K-Nearest Neighbors, and Random Forest to categorize the impacts on performance and security attributes. The performance of the proposed approach has high accuracy, ranging from $93.4 \%$ to $95.9 \%$, in detecting the fuzzing impacts. In addition, the proof of concept could identify and prioritize real-time vulnerabilities on 5G infrastructures and critical applications in various verticals