remains unclear how and why cancer occurs and progresses. Using an evolutionary approach, the concept of a complex adaptive system (CAS) was developed to describe the behaviors of cancer tumorigenesis, [2] which may suggest a frameshift away from the limitations of current approaches that mainly address the importance of alteration in specific target molecules in cancer cells. This change in perspectives toward tumors, not simply as a disease to be cured but also as CAS, is expected to be the cornerstone of the paradigm shift toward innovative cancer therapies. [3] The human immune system can also be viewed as a CAS and therefore expected to initiate self-defense mechanisms against cancer in a complex adaptive manner as long as it recognizes the cancer cells as the non-self-signals. Consequently, the key to controlling cancer could lie in understanding how to manipulate the immune system and strengthen its defenses against cancer. The concept of facilitating the immune system to fight against cancer was first suggested in the late 1800s by Dr. Wiliam Coley, who was the first to observe anti-tumor effects after intratumoral injection of microbe-derived toxins. [4] Since then, the field of cancer immunotherapy research has flourished, resulting in clinical achievements such as immune checkpoint blockades and chimeric antigen receptor T cell (CAR-T) therapy. [5] However, immune suppression resistance mechanisms have simultaneously been identified that have impeded favorable response to cancer immunotherapy. [6,7] Exosome-based cancer therapies have emerged as a potential option for overcoming these limitations to the effects of current cancer therapies due to their pathophysiological efficacy against tumors. [8] Exosomes are secreted externally by cells and are found ubiquitously in blood, urine, saliva, cerebrospinal fluid, pleural fluid, and breast milk. [9,10] The distinction between different types of extracellular vesicles (EVs) is unclear; however, they are conventionally classified as either ectosomes (microvesicles or microparticles) or exosomes. [11] While ectosomes are formed by the outward budding of the plasma membrane, exosomes are formed from multivesicular bodies (MVB) containing intraluminal vesicles via inward budding of the late endosome, which later fuses to the membrane. The formed vesicles are then secreted via a process known as exocytosis (Figure 1). The two types of vesicle also differ in diameter, Exosomes are a class of extracellular vesicles of around 100 nm in diameter that are secreted by most cells and contain various bioactive molecules reflecting their cellular origin and mediate intercellular communication. Studies of these exosomal features in tumor pathogenesis have led to the development of therapeutic and diagnostic approaches using exosomes for cancer therapy. Exosomes have many advantages for conveying therapeutic agents such as small interfering RNAs, microRNAs, membrane-associated proteins, and chemotherapeutic compounds; thus, they are considered a prime candidate as a deliv...
There have been multiple recent proposals on using deep neural networks for code search using natural language. Common across these proposals is the idea of embedding code and natural language queries, into real vectors and then using vector distance to approximate semantic correlation between code and the query. Multiple approaches exist for learning these embeddings [15,19,24,26], including unsupervised techniques, which rely only on a corpus of code examples, and supervised techniques, which use an aligned corpus of paired code and natural language descriptions. The goal of this supervision is to produce embeddings that are more similar for a query and the corresponding desired code snippet.Clearly, there are choices in whether to use supervised techniques at all, and if one does, what sort of network and training to use for supervision. This paper is the first to evaluate these choices systematically. To this end, we assembled implementations of stateof-the-art techniques to run on a common platform, training and evaluation corpora. To explore the design space in network complexity, we also introduced a new design point that is a minimal supervision extension to an existing unsupervised technique.Our evaluation shows that: 1. adding supervision to an existing unsupervised technique can improve performance, though not necessarily by much; 2. simple networks for supervision can be more effective that more sophisticated sequence-based networks for code search; 3. while it is common to use docstrings to carry out supervision, there is a sizeable gap between the effectiveness of docstrings and a more query-appropriate supervision corpus.
In most autoimmune diseases the serologic hallmarks of disease precede clinical pathology by years. Therefore the use of animal models in defining early disease events becomes critical. Herein we have taken advantage of a “designer” mouse with dysregulation of interferon gamma (IFNγ) characterized by prolonged and chronic expression of IFNγ through deletion of the IFNγ 3′ UTR AU-rich element. These mice develop primary biliary cholangitis (PBC) with a female predominance that mimics human disease and is characterized by upregulation of total bile acids, spontaneous production of AMA, and portal duct inflammation. Transfer of CD4 T cells from ARE-Del−/− to B6/Rag1−/− mice induced moderate portal inflammation, and parenchymal inflammation, RNA-sequencing of liver gene expression revealed that upregulated genes potentially define early stages of cholangitis. Interestingly, upregulated genes specifically overlap with the gene expression signature of biliary epithelial cells in PBC, implying that IFNγ may play a pathogenic role in biliary epithelial cells (BEC) in the initiation stage of PBC. Moreover, differentially expressed genes in female mice have stronger Type I and II interferon signaling and lymphocyte-mediated immune responses and thus may drive the female bias of the disease. In conclusion, changes in IFNγ expression are critical for the pathogenesis of PBC.
Code prediction, more specifically autocomplete, has become an essential feature in modern IDEs. Autocomplete is more effective when the desired next token is at (or close to) the top of the list of potential completions offered by the IDE at cursor position. This is where the strength of the underlying machine learning system that produces a ranked order of potential completions comes into play.We advance the state-of-the-art in the accuracy of code prediction (next token prediction) used in autocomplete systems. Our work uses Transformers as the base neural architecture. We show that by making the Transformer architecture aware of the syntactic structure of code, we increase the margin by which a Transformer-based system outperforms previous systems. With this, it outperforms the accuracy of several state-of-the-art next token prediction systems by margins ranging from 14% to 18%.We present in the paper several ways of communicating the code structure to the Transformer, which is fundamentally built for processing sequence data. We provide a comprehensive experimental evaluation of our proposal, along with alternative design choices, on a standard Python dataset, as well as on a company internal Python corpus. Our code and data preparation pipeline will be available in open source.
The DEMETER (DME) DNA glycosylase initiates active DNA demethylation via the base-excision repair pathway and is vital for reproduction in Arabidopsis thaliana. DME-mediated DNA demethylation is preferentially targeted to small, AT-rich, and nucleosome-depleted euchromatic transposable elements, influencing expression of adjacent genes and leading to imprinting in the endosperm. In the female gametophyte, DME expression and subsequent genome-wide DNA demethylation are confined to the companion cell of the egg, the central cell. Here, we show that, in the male gametophyte, DME expression is limited to the companion cell of sperm, the vegetative cell, and to a narrow window of time: immediately after separation of the companion cell lineage from the germline. We define transcriptional regulatory elements of DME using reporter genes, showing that a small region, which surprisingly lies within the DME gene, controls its expression in male and female companion cells. DME expression from this minimal promoter is sufficient to rescue seed abortion and the aberrant DNA methylome associated with the null dme-2 mutation. Within this minimal promoter, we found short, conserved enhancer sequences necessary for the transcriptional activities of DME and combined predicted binding motifs with published transcription factor binding coordinates to produce a list of candidate upstream pathway members in the genetic circuitry controlling DNA demethylation in gamete companion cells. These data show how DNA demethylation is regulated to facilitate endosperm gene imprinting and potential transgenerational epigenetic regulation, without subjecting the germline to potentially deleterious transposable element demethylation.S exual reproduction is characterized by fertilization of an egg by a sperm cell, generating the embryo. Uniquely in angiosperms, a second sperm cell fertilizes the companion cell of the egg, the central cell, to generate the endosperm, which supports development of the embryo. During reproduction in angiosperm Arabidopsis thaliana, the DEMETER (DME) DNA glycosylase exhibits a striking expression pattern. Within the ovule, the female gametophyte is generated by mitosis of the haploid megaspore, forming a mature gametophyte of seven cells. During this process, the egg and central cell lineages are separated, and, at this point, DME expression and DNA demethylation is initiated solely in the central cell (1, 2). DME expression is switched off after fertilization (2). This precise pattern of expression initiated in the central cell, and not in the egg cell, is responsible for hypomethylation specifically in the maternal endosperm genome and not in the maternal embryo genome (3). DME expression in the central cell is essential for plant reproduction and genomic imprinting, whereby its absence results in loss of genomic imprinting, aberrant endosperm development, and early seed abortion (2, 4, 5).In the male gametophyte, indirect evidence suggests that DME is expressed during development of the mature three-cell pollen gra...
BackgroundStatins preferentially promote tumor-specific apoptosis by depleting isoprenoid such as farnesyl pyrophosphate and geranylgeranyl pyrophosphate. However, statins have not yet been approved for clinical cancer treatment due, in part, to poor understanding of molecular determinants on statin sensitivity. Here, we investigated the potential of statins to elicit enhanced immunogenicity of KRAS-mutant (KRASmut) tumors.MethodsThe immunogenicity of treated cancer cells was determined by western blot, flow cytometry and confocal microscopy. The immunotherapeutic efficacy of mono or combination therapy using statin was assessed in KRASmut tumor models, including syngeneic colorectal cancer and genetically engineered lung and pancreatic tumors. Using NanoString analysis, we analyzed how statin influenced the gene signatures associated with the antigen presentation of dendritic cells in vivo and evaluated whether statin could induce CD8+ T-cell immunity. Multiplex immunohistochemistry was performed to better understand the complicated tumor-immune microenvironment.ResultsStatin-mediated inhibition of KRAS prenylation provoked severe endoplasmic reticulum (ER) stress by attenuating the anti-ER stress effect of KRAS mutation, thereby resulting in the immunogenic cell death (ICD) of KRASmut cancer cells. Moreover, statin-mediated ICD enhanced the cross-priming ability of dendritic cells, thereby provoking CD8+ T-cell immune responses against KRASmut tumors. Combination therapy using statin and oxaliplatin, an ICD inducer, significantly enhanced the immunogenicity of KRASmut tumors and promoted tumor-specific immunity in syngeneic and genetically engineered KRASmut tumor models. Along with immune-checkpoint inhibitors, the abovementioned combination therapy overcame resistance to PD-1 blockade therapies, improving the survival rate of KRASmut tumor models.ConclusionsOur findings suggest that KRAS mutation could be a molecular target for statins to elicit potent tumor-specific immunity.
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