91 research outputs found

    Direct Conversion of Mouse Astrocytes Into Neural Progenitor Cells and Specific Lineages of Neurons

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    Background: Cell replacement therapy has been envisioned as a promising treatment for neurodegenerative diseases. Due to the ethical concerns of ESCs-derived neural progenitor cells (NPCs) and tumorigenic potential of iPSCs, reprogramming of somatic cells directly into multipotent NPCs has emerged as a preferred approach for cell transplantation. Methods: Mouse astrocytes were reprogrammed into NPCs by the overexpression of transcription factors (TFs) Foxg1, Sox2, and Brn2. The generation of subtypes of neurons was directed by the force expression of cell-type specific TFs Lhx8 or Foxa2/Lmx1a. Results: Astrocyte-derived induced NPCs (AiNPCs) share high similarities, including the expression of NPC-specific genes, DNA methylation patterns, the ability to proliferate and differentiate, with the wild type NPCs. The AiNPCs are committed to the forebrain identity and predominantly differentiated into glutamatergic and GABAergic neuronal subtypes. Interestingly, additional overexpression of TFs Lhx8 and Foxa2/Lmx1a in AiNPCs promoted cholinergic and dopaminergic neuronal differentiation, respectively. Conclusions: Our studies suggest that astrocytes can be converted into AiNPCs and lineage-committed AiNPCs can acquire differentiation potential of other lineages through forced expression of specific TFs. Understanding the impact of the TF sets on the reprogramming and differentiation into specific lineages of neurons will provide valuable strategies for astrocyte-based cell therapy in neurodegenerative diseases

    Neoadjuvant Immune Checkpoint Inhibitors in hepatocellular carcinoma: a meta-analysis and systematic review

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    BackgroundNeoadjuvant immunotherapy has demonstrated beneficial outcomes in various cancer types; however, standardized protocols for neoadjuvant immunotherapy in hepatocellular carcinoma (HCC) are currently lacking. This systematic review and meta-analysis aims to investigate the reliability of neoadjuvant immunotherapy’s efficacy and safety in the context of HCC.MethodsA systematic search was conducted across PubMed (MEDLINE), EMBASE, the Web of Science, the Cochrane Library, and conference proceedings to identify clinical trials involving resectable HCC and neoadjuvant immunotherapy. Single-arm meta-analyses were employed to compute odds ratios and 95% confidence intervals (CIs). Heterogeneity analysis, data quality assessment, and subgroup analyses based on the type of immunotherapy drugs and combination therapies were performed. This meta-analysis is registered in PROSPERO (identifier CRD42023474276).ResultsThis meta-analysis included 255 patients from 11 studies. Among resectable HCC patients, neoadjuvant immunotherapy exhibited an overall major pathological response (MPR) rate of 0.47 (95% CI 0.31-0.70) and a pathological complete response (pCR) rate of 0.22 (95% CI 0.14-0.36). The overall objective response rate (ORR) was 0.37 (95% CI 0.20-0.69), with a grade 3-4 treatment-related adverse event (TRAE) incidence rate of 0.35 (95% CI 0.24-0.51). Furthermore, the combined surgical resection rate was 3.08 (95% CI 1.66-5.72). Subgroup analysis shows no significant differences in the efficacy and safety of different single-agent immunotherapies; the efficacy of dual ICIs (Immune Checkpoint Inhibitors) combination therapy is superior to targeted combined immunotherapy and monotherapy, while the reverse is observed in terms of safety.DiscussionNeoadjuvant immunotherapy presents beneficial outcomes in the treatment of resectable HCC. However, large-scale, high-quality experiments are warranted in the future to provide robust data support

    Exploring the pathogenesis of colorectal carcinoma complicated with hepatocellular carcinoma via microarray data analysis

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    Background: Despite the increasing number of research endeavors dedicated to investigating the relationship between colorectal carcinoma (CRC) and hepatocellular carcinoma (HCC), the underlying pathogenic mechanism remains largely elusive. The aim of this study is to shed light on the molecular mechanism involved in the development of this comorbidity.Methods: The gene expression profiles of CRC (GSE90627) and HCC (GSE45267) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis and atherosclerosis, three kinds of analyses were performed, namely, functional annotation, protein‐protein interaction (PPI) network and module construction, and hub gene identification, survival analysis and co-expression analysis.Results: A total of 150 common downregulated differentially expressed genes and 148 upregulated differentially expressed genes were selected for subsequent analyses. The significance of chemokines and cytokines in the pathogenesis of these two ailments is underscored by functional analysis. Seven gene modules that were closely connected were identified. Moreover, the lipopolysaccharide-mediated signaling pathway is intricately linked to the development of both diseases. Finally, 10 important hub genes were identified using cytoHubba, including CDK1, KIF11, CDC20, CCNA2, TOP2A, CCNB1, NUSAP1, BUB1B, ASPM, and MAD2L1.Conclusion: Our study reveals the common pathogenesis of colorectal carcinoma and hepatocellular carcinoma. These common pathways and hub genes may provide new ideas for further mechanism research

    The matched projections of idempotents on Hilbert CC^*-modules

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    The aim of this paper is to give new characterizations of some fundamental issues about idempotents. In the general setting of adjointable operators on Hilbert CC^*-modules, a new term of quasi-projection pair is introduced. For each idempotent QQ, a projection m(Q)m(Q), called the matched projection of QQ, is constructed. It is shown that QQ and m(Q)m(Q) as idempotents are homotopic, and (m(Q),Q)\big(m(Q),Q\big) is a quasi-projection pair. Some formulas for m(Q)m(Q) are derived. Based on these formulas, representations and norm estimations associated with m(Q)m(Q) are dealt with.Comment: The original submission entitled "Quasi-projection pairs on Hilbert CC^*-modules" will be divided into three parts, and this is the first par

    A Deep Neural Network Model for Short-Term Load Forecast Based on Long Short-Term Memory Network and Convolutional Neural Network

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    Accurate electrical load forecasting is of great significance to help power companies in better scheduling and efficient management. Since high levels of uncertainties exist in the load time series, it is a challenging task to make accurate short-term load forecast (STLF). In recent years, deep learning approaches provide better performance to predict electrical load in real world cases. The convolutional neural network (CNN) can extract the local trend and capture the same pattern, and the long short-term memory (LSTM) is proposed to learn the relationship in time steps. In this paper, a new deep neural network framework that integrates the hidden feature of the CNN model and the LSTM model is proposed to improve the forecasting accuracy. The proposed model was tested in a real-world case, and detailed experiments were conducted to validate its practicality and stability. The forecasting performance of the proposed model was compared with the LSTM model and the CNN model. The Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) were used as the evaluation indexes. The experimental results demonstrate that the proposed model can achieve better and stable performance in STLF

    Spatiotemporal Variation of Net Primary Productivity and Its Response to Climate Change and Human Activities in the Yangtze River Delta, China

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    Exploring the temporal and spatial changes, as well as driving factors, of net primary productivity (NPP) of terrestrial ecosystems is essential for maintaining regional carbon balance. This work focuses on the spatiotemporal variation and future trends of NPP and the response mechanisms of NPP to various driving factors. The Theil–Sen estimator, as well as Mann–Kendall and Hurst exponent methods, were used to analyze the spatiotemporal dynamics and future trends of NPP, and geographical detectors and correlation analysis were used to reveal the response of NPP to various driver changes to environmental factors. The results showed that the NPP was generally on an increasing trend in the Yangtze River Delta region from 2000 to 2019, with the average NPP value of 550.17 g C m−2 a−1, of which 85.90% was the increasing regions and 14.10% was the decreasing regions, showing a significant spatiotemporal heterogeneity characteristic. The trend of future changes in NPP is dominated by an anti-persistence trend in the study area, i.e., the opposite of the past trend. Notably, annual precipitation is the most significant positive driver of NPP; while NPP was negatively correlated with population, meanwhile, different land use/land cover (LULC) also significantly affected the spatial distribution of NPP. Besides, there was a two-factor enhanced interaction between the various drivers on NPP, with the highest interaction occurring between temperature and elevation. Overall, this study provides data support for future regional NPP predictions and ecosystem evaluations
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