99 research outputs found
SIMILAR TOPICS ROUTING FOR CALLS ON CONTACT CENTER
One issue with contact or call centers is long wait times. Proposed herein is a solution that seeks to tackle or decrease customer wait times when calling a call center by implementing a routing system based on a graph algorithm. This advanced routing system can help to ensure that customers are directed to the most suitable available agent. Moreover, the system may facilitate cost optimization by offering a user-friendly platform for training the existing agents on new topics
Numerical Simulation on the Gas Explosion Propagation Related to Roadway
AbstractBased on the combustion, explosions and air dynamics and related theory etc, this paper describes the mathematical model of gas explosion in detail, combined with the gas explosion transmission mechanism, make a research on two wave-three area structure of gas explosion and the energy change rule of the array face of precursor wave and the array face of flame wave, with the fluid dynamics analysis Fluent software, this paper makes a numerical simulation and analysis on the overpressure transmission rule when gas explosion takes place in different types roadways. The results of the study show that: Fluent software can be used to accurately simulate gas explosion condition, when explosion wave spreads in the roadway turns, the bigger of the overpressure value in corner, the stronger of the destructive power; when tunnel has bifurcation, the overpressure will release in bifurcation, but explosions wave with flame wave will produce more powerful destruction effect. The research results can be used as a certain reference for how to prevent and control the gas explosion, and how to reduce the power of the gas explosion etc
Phenotypic, Proteomic, and Genomic Characterization of a Putative ABC-Transporter Permease Involved in Listeria monocytogenes Biofilm Formation
Corticosteroids showed more efficacy in treating hospitalized patients with COVID-19 than standard care but the effect is minimal: A systematic review and meta-analysis
BackgroundDuring the ongoing coronavirus disease 2019 (COVID-19) pandemic, the use of corticosteroids for COVID-19 has ignited worldwide debate. Previous systematic reviews, including randomized controlled trials (RCTs) and retrospective observational studies, found that corticosteroids have beneficial effects in treating COVID-19.AimThis systematic review and meta-analysis only included RCTs to assess the effectiveness and safety of corticosteroids in hospitalized patients with COVID-19.MethodsComprehensive research strategies (PubMed, Embase, MEDLINE, and Coherence Library) were used to search for RCTs from December 2019 to January 2021.ResultsFive RCTs were included with 7,235 patients, of which 2,508 patients were receiving corticosteroid treatments (dexamethasone or methylprednisolone), and 4,727 received standard care. The primary outcome was mortality within 28 days. The use of corticosteroids decreased the 28-day mortality of patients with COVID-19, but the findings were not statistically significant (RR, 0.91; 95% CI, 0.78–1.06, p = 0.24). The secondary outcome was the duration of hospitalization; no differences were found between the corticosteroid and standard care groups. However, corticosteroids were associated with a higher hospital discharge rate than standard treatment, but the result was not statistically significant (RR, 1.36; 95% CI, 0.95–1.96, p = 0.09).ConclusionsThe results suggest that corticosteroids are comparable to standard care in terms of safety in treating COVID-19. Corticosteroids showed greater efficacy than standard care; however, the effect was minimal
Clinical Study The Prognosis of IVF in Poor Responders Depending on the Bologna Criteria: A Large Sample Retrospective Study from China
Somatic mutation of the cohesin complex subunit confers therapeutic vulnerabilities in cancer
A synthetic lethality-based strategy has been developed to identify therapeutic targets in cancer harboring tumor-suppressor gene mutations, as exemplified by the effectiveness of poly ADP-ribose polymerase (PARP) inhibitors in BRCA1/2-mutated tumors. However, many synthetic lethal interactors are less reliable due to the fact that such genes usually do not perform fundamental or indispensable functions in the cell. Here, we developed an approach to identifying the "essential lethality" arising from these mutated/deleted essential genes, which are largely tolerated in cancer cells due to genetic redundancy. We uncovered the cohesion subunit SA1 as a putative synthetic-essential target in cancers carrying inactivating mutations of its paralog, SA2. In SA2-deficient Ewing sarcoma and bladder cancer, further depletion of SA1 profoundly and specifically suppressed cancer cell proliferation, survival, and tumorigenic potential. Mechanistically, inhibition of SA1 in the SA2-mutated cells led to premature chromatid separation, dramatic extension of mitotic duration, and consequently, lethal failure of cell division. More importantly, depletion of SA1 rendered those SA2-mutated cells more susceptible to DNA damage, especially double-strand breaks (DSBs), due to reduced functionality of DNA repair. Furthermore, inhibition of SA1 sensitized the SA2-deficient cancer cells to PARP inhibitors in vitro and in vivo, providing a potential therapeutic strategy for patients with SA2-deficient tumors
ICTD: A semi-supervised cell type identification and deconvolution method for multi-omics data
We developed a novel deconvolution method, namely Inference of Cell Types and Deconvolution (ICTD) that addresses the fundamental issue of identifiability and robustness in current tissue data deconvolution problem. ICTD provides substantially new capabilities for omics data based characterization of a tissue microenvironment, including (1) maximizing the resolution in identifying resident cell and sub types that truly exists in a tissue, (2) identifying the most reliable marker genes for each cell type, which are tissue and data set specific, (3) handling the stability problem with co-linear cell types, (4) co-deconvoluting with available matched multi-omics data, and (5) inferring functional variations specific to one or several cell types. ICTD is empowered by (i) rigorously derived mathematical conditions of identifiable cell type and cell type specific functions in tissue transcriptomics data and (ii) a semi supervised approach to maximize the knowledge transfer of cell type and functional marker genes identified in single cell or bulk cell data in the analysis of tissue data, and (iii) a novel unsupervised approach to minimize the bias brought by training data. Application of ICTD on real and single cell simulated tissue data validated that the method has consistently good performance for tissue data coming from different species, tissue microenvironments, and experimental platforms. Other than the new capabilities, ICTD outperformed other state-of-the-art devolution methods on prediction accuracy, the resolution of identifiable cell, detection of unknown sub cell types, and assessment of cell type specific functions. The premise of ICTD also lies in characterizing cell-cell interactions and discovering cell types and prognostic markers that are predictive of clinical outcomes
Atractylenolide I enhances responsiveness to immune checkpoint blockade therapy by activating tumor antigen presentation
One of the primary mechanisms of tumor cell immune evasion is the loss of antigenicity, which arises due to lack of immunogenic tumor antigens as well as dysregulation of the antigen processing machinery. In a screen for small-molecule compounds from herbal medicine that potentiate T cell–mediated cytotoxicity, we identified atractylenolide I (ATT-I), which substantially promotes tumor antigen presentation of both human and mouse colorectal cancer (CRC) cells and thereby enhances the cytotoxic response of CD8+ T cells. Cellular thermal shift assay (CETSA) with multiplexed quantitative mass spectrometry identified the proteasome 26S subunit non–ATPase 4 (PSMD4), an essential component of the immunoproteasome complex, as a primary target protein of ATT-I. Binding of ATT-I with PSMD4 augments the antigen-processing activity of immunoproteasome, leading to enhanced MHC-I–mediated antigen presentation on cancer cells. In syngeneic mouse CRC models and human patient–derived CRC organoid models, ATT-I treatment promotes the cytotoxicity of CD8+ T cells and thus profoundly enhances the efficacy of immune checkpoint blockade therapy. Collectively, we show here that targeting the function of immunoproteasome with ATT-I promotes tumor antigen presentation and empowers T cell cytotoxicity, thus elevating the tumor response to immunotherapy
MAL2 drives immune evasion in breast cancer by suppressing tumor antigen presentation
Immune evasion is a pivotal event in tumor progression. To eliminate human cancer cells, current immune checkpoint therapy is set to boost CD8+ T cell-mediated cytotoxicity. However, this action is eventually dependent on the efficient recognition of tumor-specific antigens via T cell receptors. One primary mechanism by which tumor cells evade immune surveillance is to downregulate their antigen presentation. Little progress has been made toward harnessing potential therapeutic targets for enhancing antigen presentation on the tumor cell. Here, we identified MAL2 as a key player that determines the turnover of the antigen-loaded MHC-I complex and reduces the antigen presentation on tumor cells. MAL2 promotes the endocytosis of tumor antigens via direct interaction with the MHC-I complex and endosome-associated RAB proteins. In preclinical models, depletion of MAL2 in breast tumor cells profoundly enhanced the cytotoxicity of tumor-infiltrating CD8+ T cells and suppressed breast tumor growth, suggesting that MAL2 is a potential therapeutic target for breast cancer immunotherapy
Genome Sequence and Transcriptome Analysis of the Radioresistant Bacterium Deinococcus gobiensis: Insights into the Extreme Environmental Adaptations
The desert is an excellent model for studying evolution under extreme environments. We present here the complete genome and ultraviolet (UV) radiation-induced transcriptome of Deinococcus gobiensis I-0, which was isolated from the cold Gobi desert and shows higher tolerance to gamma radiation and UV light than all other known microorganisms. Nearly half of the genes in the genome encode proteins of unknown function, suggesting that the extreme resistance phenotype may be attributed to unknown genes and pathways. D. gobiensis also contains a surprisingly large number of horizontally acquired genes and predicted mobile elements of different classes, which is indicative of adaptation to extreme environments through genomic plasticity. High-resolution RNA-Seq transcriptome analyses indicated that 30 regulatory proteins, including several well-known regulators and uncharacterized protein kinases, and 13 noncoding RNAs were induced immediately after UV irradiation. Particularly interesting is the UV irradiation induction of the phrB and recB genes involved in photoreactivation and recombinational repair, respectively. These proteins likely include key players in the immediate global transcriptional response to UV irradiation. Our results help to explain the exceptional ability of D. gobiensis to withstand environmental extremes of the Gobi desert, and highlight the metabolic features of this organism that have biotechnological potential
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