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Colorectal carcinoma (CRC) is one of the most prevalent malignant tumors worldwide. Meanwhile, the majority of CRC related deaths results from liver metastasis. Gene expression profile of CRC patients with liver Metastasis was identified using 4 datasets. The data was analyzed using GEO2R tool. GO and KEGG pathway analysis were performed. PPI network of the DEGs between 1 and 2 gene sets was also constructed. The set 1 is named between primary CRC tissues and metastatic CRC tissues. The set 2 is named between primary CRC tissues and normal tissues. Finally, the prognostic value of hub genes was also analyzed. 35 DEGs (set 1) and 142 DEGs (set 2) were identified between CRC liver metastatic cancer patients. The PPI network was constructed using the top 10 set 1 hub genes which included AHSG, SERPINC1, FGA, F2, CP, ITIH2, APOA2, HPX, PLG, HRG and set 2 hub genes which included TIMP1, CXCL1, COL1A2, MMP1, AURKA, UBE2C, CXCL12, TOP2A, ALDH1A1 and PRKACB. Therefore, ITIH2 might represent the potential core gene for colon cancer liver metastasis. COL1A2 behaves as a key gene in colorectal carcinoma.

Accurate long-term forecasting of stock prices, especially using high-frequency data, remains a significant challenge due to the inherent non-stationarity, noise, and complex long-term dependencies present in such series. To address this, we propose StockCI, a novel hybrid model that strategically integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and the Informer architecture. The model is designed with a two-stage workflow: first, the CEEMDAN module adaptively decomposes the original complex price series into a set of simpler, more stationary sub-series (IMFs), effectively filtering out noise and mitigating the problem of mode mixing. Subsequently, the Informer module, renowned for its efficiency in long-sequence forecasting, predicts future values of each decomposed component by leveraging its ProbSparse self-attention mechanism. The final forecast is obtained by reconstructing the predicted components. We evaluated StockCI on minute-level high-frequency data from China’s A-share market, including major indices and individual stocks. Empirical results demonstrate that StockCI significantly outperforms a comprehensive suite of benchmarks, including traditional models (ARIMA), deep learning models (RNN, LSTM, GRU), and state-of-the-art transformers (Autoformer, FEDformer, PatchTST). For instance, StockCI achieved an average reduction in MAE of over 15% compared to the standalone Informer model. Empirical findings confirm StockCI’s superior performance in accurately forecasting long-term stock prices, demonstrating significant improvements over established academic benchmarks including ARIMA, RNN, LSTM, and Informer.

Timely and effective pest detection is essential for agricultural production, facing challenges such as complex backgrounds and a vast number of parameters. Seeking solutions has become a pressing matter. This paper, based on the YOLOv5 algorithm, developed the PestLite model. The model surpasses previous spatial pooling methods with our uniquely designed Multi-Level Spatial Pyramid Pooling (MTSPPF). Using a lightweight unit, it integrates convolution, normalization, and activation operations. It excels in capturing multi-scale features, ensuring rich extraction of key information at various scales. Notably, MTSPPF not only enhances detection accuracy but also reduces the parameter size, making it ideal for lightweight pest detection models. Additionally, we introduced the Involution and Efficient Channel Attention (ECA) attention mechanisms to enhance contextual understanding. We also replaced traditional upsampling with Content-Aware ReAssembly of FEatures (CARAFE), which enable the model to achieve higher mean average precision in detection. Testing on a pest dataset showed improved accuracy while reducing parameter size. The mAP50 increased from 87.9% to 90.7%, and the parameter count decreased from 7.03 M to 6.09 M. We further validated the PestLite model using the IP102 dataset, and on the other hand, we conducted comparisons with mainstream models. Furthermore, we visualized the detection targets. The results indicate that the PestLite model provides an effective solution for real-time target detection in agricultural pests.

Human immunodeficiency virus 1 (HIV-1) reservoir cells persist lifelong despite antiretroviral treatment 1 , 2 but may be vulnerable to host immune responses that could be exploited in strategies to cure HIV-1. Here we used a single-cell, next-generation sequencing approach for the direct ex vivo phenotypic profiling of individual HIV-1-infected memory CD4 + T cells from peripheral blood and lymph nodes of people living with HIV-1 and receiving antiretroviral treatment for approximately 10 years. We demonstrate that in peripheral blood, cells harbouring genome-intact proviruses and large clones of virally infected cells frequently express ensemble signatures of surface markers conferring increased resistance to immune-mediated killing by cytotoxic T and natural killer cells, paired with elevated levels of expression of immune checkpoint markers likely to limit proviral gene transcription; this phenotypic profile might reduce HIV-1 reservoir cell exposure to and killing by cellular host immune responses. Viral reservoir cells harbouring intact HIV-1 from lymph nodes exhibited a phenotypic signature primarily characterized by upregulation of surface markers promoting cell survival, including CD44, CD28, CD127 and the IL-21 receptor. Together, these results suggest compartmentalized phenotypic signatures of immune selection in HIV-1 reservoir cells, implying that only small subsets of infected cells with optimal adaptation to their anatomical immune microenvironment are able to survive during long-term antiretroviral treatment. The identification of phenotypic markers distinguishing viral reservoir cells may inform future approaches for strategies to cure and eradicate HIV-1. A proteogenomic profiling analysis of single cells from the blood and lymph nodes of individuals living with HIV-1 reveals that CD4 + memory T cells harbouring intact provirus show signatures associated with resistance to immune-mediated killing and cell survival.

HIV-1 reservoir cells that circulate in peripheral blood during suppressive antiretroviral therapy (ART) have been well characterized, but little is known about the dissemination of HIV-1-infected cells across multiple anatomical tissues, especially the CNS. Here, we performed single-genome, near full-length HIV-1 next-generation sequencing to evaluate the proviral landscape in distinct anatomical compartments, including multiple CNS tissues, from 3 ART-treated participants at autopsy. While lymph nodes and, to a lesser extent, gastrointestinal and genitourinary tissues represented tissue hotspots for the persistence of intact proviruses, we also observed intact proviruses in CNS tissue sections, particularly in the basal ganglia. Multi-compartment dissemination of clonal intact and defective proviral sequences occurred across multiple anatomical tissues, including the CNS, and evidence for the clonal proliferation of HIV-1-infected cells was found in the basal ganglia, in the frontal lobe, in the thalamus and in periventricular white matter. Deep analysis of HIV-1 reservoirs in distinct tissues will be informative for advancing HIV-1 cure strategies. Approximately 39 million people in the world live with HIV infection. Currently available treatments can reduce the amount of virus to near undetectable levels. But they do not eliminate the virus. A reservoir of HIV-infected cells persists during treatment. If treatment stops, these cells can cause rebounding virus levels and a return of symptoms. As a result, patients living with HIV must remain on treatment their entire lives. HIV reservoir cells often do not express viral proteins, making them hard for the immune system to find and destroy. Many of these reservoir cells occur in lymph nodes, which makes them difficult for researchers to access for study. Learning more about where these cells hide in the body may enable scientists to develop new treatments to help eliminate them. Sun et al. show that HIV reservoir cells exist in many body tissues, including the brain. In the experiments, Sun et al. used single HIV genome sequencing to identify HIV genetic sequences in the brain and other body tissues from three recently deceased individuals with HIV. The individuals agreed to donate their tissues for postmortem studies before their deaths. All received antiretroviral therapy until death. The experiments identified functional HIV genetic sequences in lymph nodes and gastrointestinal tissues, known hotspots for HIV-infected cells. Sun et al. also found genetically intact HIV in brain tissue from two of the individuals. The HIV genetic sequences were identical to sequences found in other body tissues. This discovery suggests HIV-infected cells had divided into more HIV-infected cells and spread. The results suggest that cells harboring intact HIV invade the brain and persist there for extended periods during antiretroviral therapy. To eradicate the virus, interventions targeting HIV reservoir cells must be able to reach the brain. This new information may help researchers developing HIV-reservoir targeting drugs decide which candidates will likely be the most effective. Future studies may also shed light on how HIV reaches the brain and how the infected cells escape destruction by immune cells, which may suggest more treatment strategies.

This study statistically evaluates the suitability of the construction industry as a diversification target for infrastructure corporations by integrating Data Envelopment Analysis (DEA-BCC), panel data regression, and entropy-based diversification metrics. Twenty actively operating highway companies in China were selected, and their annual reports from 2011 to 2021 were meticulously reviewed. This study quantifies the impact of diversification strategies on firm performance, resource allocation efficiency, and X-inefficiency. The findings reveal that strategic diversification into construction-related activities enhances operational efficiency and mitigates X-inefficiency, aligning with Penrose’s theory of surplus resource deployment. The study contributes a robust analytical framework for assessing diversification in the infrastructure sectors, offering actionable insights for corporations considering expansion into construction. The results underscore the importance of organizational optimization and business capability in reducing X-inefficiency and enhancing sustainable development, particularly in maturing markets where traditional growth avenues are limited.

Cell therapy has emerged as a viable approach for treating damaged organs or tissues, particularly with advancements in stem cell research and regenerative medicine. The innovative technique of cell sheet engineering offers the potential to create a cell-dense lamellar structure that preserves the extracellular matrix (ECM) secreted by cells, along with the cell-matrix and intercellular junctions formed during in vitro cultivation. In recent years, significant progress has been made in developing cell sheet engineering technology. A variety of novel materials and methods were utilized for enzyme-free cell detachment during the cell sheet formation process. The complexity of cell sheet structures increased to meet advanced usage demands. This review aims to provide an overview of the preparation methods and types of cell sheets, thereby enhancing the understanding of this rapidly evolving technology and offering a fresh perspective on the development and future application of cell sheet engineering. Graphical Abstract

Further understanding the mechanism for microglia activation is necessary for developing novel anti-inflammatory strategies. Our previous study found that the activation of sigma-1 receptor can effectively inhibit the neuroinflammation, independent of the canonical mechanisms, such as NF-κB, JNK and ERK inflammatory pathways. Thus, it is reasonable that an un-identified, non-canonical pathway contributes to the activation of microglia. In the present study, we found that a sigma-1 receptor agonist of 2-morpholin-4-ylethyl 1-phenylcyclohexane-1-carboxylate (PRE-084) suppressed lipopolysaccharide (LPS) elevated nitric oxide (NO) content in BV-2 microglia culture supernatant and LPS-raised mRNA levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), inducible nitric oxide synthase (iNOS) in BV-2 microglia. Moreover, PRE-084 alleviated LPS-increased Ser 9 de-phosphorylation of glycogen synthase kinase-3 beta (GSK-3β), LPS-elevated catalytic activity of calcineurin, and LPS-raised percent and frequency of Ca2+ oscillatory BV-2 cells. We further found that the inhibitory effect of PRE-084 was reversed by a calcineurin activator of chlorogenic acid and a GSK-3β activator of pyrvinium. Moreover, an IP3 receptor inhibitor of 2-aminoethoxydiphenyl borate mimicked the anti-inflammatory activity of PRE-084. Thus, we identified a noncanonical pro-neuroinflammary pathway of Ca2+ oscillation/Calcineurin/GSK-3β and the inhibition of this pathway is necessary for the anti-inflammatory activity of sigma-1 receptor activation.

Due to its widespread occurrence and high mortality rate, hepatocellular carcinoma (HCC) is an abhorrent kind of cancer. Immunotherapy is a hot spot in the field of cancer treatment, represented by immune checkpoint inhibitors (ICIs), which aim to improve the immune system’s ability to recognize, target and eliminate cancer cells. The composition of the HCC immune microenvironment is the result of the interaction of immunosuppressive cells, immune effector cells, cytokine environment, and tumor cell intrinsic signaling pathway, and immunotherapy with strong anti-tumor immunity has received more and more research attention due to the limited responsiveness of HCC to ICI monotherapy. There is evidence of an organic combination of radiotherapy, chemotherapy, anti-angiogenic agents and ICI catering to the unmet medical needs of HCC. Moreover, immunotherapies such as adoptive cellular therapy (ACT), cancer vaccines and cytokines also show encouraging efficacy. It can significantly improve the ability of the immune system to eradicate tumor cells. This article reviews the role of immunotherapy in HCC, hoping to improve the effect of immunotherapy and develop personalized treatment regimens.

Target detection in hyperspectral imagery (HSI) aims at extracting target components of interest from hundreds of narrow contiguous spectral bands, where the prior target information plays a vital role. However, the limitation of the previous methods is that only single-layer detection is carried out, which is not sufficient to discriminate the target parts from complex background spectra accurately. In this paper, we introduce a hierarchical structure to the traditional algorithm matched filter (MF). Because of the advantages of MF in target separation performance, that is, the background components are suppressed while preserving the targets, the detection result of MF is used to further suppress the background components in a cyclic iterative manner. In each iteration, the average output of the previous iteration is used as a suppression criterion to distinguish these pixels judged as backgrounds in the current iteration. To better stand out the target spectra from the background clutter, HSI spectral input and the given target spectrum are whitened and then used to construct the MF in the current iteration. Finally, we provide the corresponding proofs for the convergence of the output and suppression criterion. Experimental results on three classical hyperspectral datasets confirm that the proposed method performs better than some traditional and recently proposed methods.