Targeting P4HA1 promotes CD8 T cell progenitor expansion toward immune memory and systemic anti-tumor immunity.

Successful immunotherapy relies on both intratumoral and systemic immunity, which is yet to be achieved for most patients with cancer. Here, we identify P4HA1, encoding prolyl 4-hydroxylase 1, as a crucial regulator of CD8 T cell differentiation strongly upregulated in tumor-draining lymph nodes (TDLNs) and hypoxic tumor microenvironment. P4HA1 accumulates in mitochondria, disrupting the tricarboxylic acid (TCA) cycle through aberrant α-ketoglutarate and succinate metabolism, promoting mitochondria unfitness and exhaustion while suppressing progenitor expansion.

scMoMtF: An interpretable multitask learning framework for single-cell multi-omics data analysis.

With the rapidly development of biotechnology, it is now possible to obtain single-cell multi-omics data in the same cell. However, how to integrate and analyze these single-cell multi-omics data remains a great challenge. Herein, we introduce an interpretable multitask framework (scMoMtF) for comprehensively analyzing single-cell multi-omics data.

Occurrences, source apportionment, and potential risks of 55 progestins in surface water of the Yellow River Delta, China.

Progestins (PGs) are a group of emerging contaminants with endocrine disrupting effects. Despite their large amounts of use and excretion, investigations have been limited to several compounds in the aqueous phase, and the occurrences and distribution of numerous PGs in different matrices remain unclear. In this study, water, suspended particulate matter and sediment samples from rivers in the Yellow River Delta (YRD), China were investigated over two seasons to elucidate the occurrences, sources, and ecological risks of 55 natural and synthetic PGs.

Single-cell RNA sequencing reveals anti-tumor potency of CD56 NK cells and CD8 T cells in humanized mice via PD-1 and TIGIT co-targeting.

In solid tumors, the exhaustion of natural killer (NK) cells and cytotoxic T cells in the immunosuppressive tumor microenvironment poses challenges for effective tumor control. Conventional humanized mouse models of hepatocellular carcinoma patient-derived xenografts (HCC-PDX) encounter limitations in NK cell infiltration, hindering studies on NK cell immunobiology. Here, we introduce an improved humanized mouse model with restored NK cell reconstitution and infiltration in HCC-PDX, coupled with single-cell RNA sequencing (scRNA-seq) to identify potential anti-HCC treatments.

Structural mechanism of proton conduction in otopetrin proton channel.

The otopetrin (OTOP) proteins were recently characterized as extracellular proton-activated proton channels. Several recent OTOP channel structures demonstrated that the channels form a dimer with each subunit adopting a double-barrel architecture. However, the structural mechanisms underlying some basic functional properties of the OTOP channels remain unresolved, including extracellular pH activation, proton conducting pathway, and rapid desensitization.

Structural insights into the molecular effects of the anthelmintics monepantel and betaine on the Caenorhabditis elegans acetylcholine receptor ACR-23.

Anthelmintics are drugs used for controlling pathogenic helminths in animals and plants. The natural compound betaine and the recently developed synthetic compound monepantel are both anthelmintics that target the acetylcholine receptor ACR-23 and its homologs in nematodes. Here, we present cryo-electron microscopy structures of ACR-23 in apo, betaine-bound, and betaine- and monepantel-bound states.

Role of TAP1 in the identification of immune-hot tumor microenvironment and its prognostic significance for immunotherapeutic efficacy in gastric carcinoma.

Background: Gastric cancer (GC), a multifaceted gastrointestinal malignancy, is the fourth most prevalent contributor to cancer-related fatalities globally. As a member of the ATP-binding cassette (ABC) family, transporter associated with antigen processing 1 (TAP1) is crucial for conveying antigen peptides from the cytoplasm to the lumen of the endoplasmic reticulum and subsequently loading them onto the major histocompatibility complex (MHC) class I molecules. Recent studies have established the biological significance of TAP1 in upholding tumor survival and facilitating immune evasion by remodeling the tumor microenvironment (TME) and orchestrating immune infiltration.

A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification.

Objective: This study aimed to construct a machine learning model using clinical variables and ultrasound radiomics features for the prediction of the benign or malignant nature of pancreatic tumors.

Methods: 242 pancreatic tumor patients who were hospitalized at the First Affiliated Hospital of Guangxi Medical University between January 2020 and June 2023 were included in this retrospective study. The patients were randomly divided into a training cohort (n=169) and a test cohort (n=73).

Novel OX40 and 4-1BB derived spacers enhance CD30 CAR activity and safety in CD30 positive lymphoma models.

The chimeric antigen receptor (CAR) derived from the CD30 specific murine antibody, HRS-3, has produced promising clinical efficacy with a favorable safety profile in the treatment of relapsed or refractory CD30-positive lymphomas. However, persistence of the autologous CAR-T cells was brief, and many patients relapsed a year after treatment. The lack of persistence may be attributed to the use of a wild-type immunoglobulin (Ig)G1 spacer that can associate with Fc receptors.

A high-density microfluidic bioreactor for the automated manufacturing of CAR T cells.

The manufacturing of autologous chimaeric antigen receptor (CAR) T cells largely relies either on fed-batch and manual processes that often lack environmental monitoring and control or on bioreactors that cannot be easily scaled out to meet patient demands. Here we show that human primary T cells can be activated, transduced and expanded to high densities in a 2 ml automated closed-system microfluidic bioreactor to produce viable anti-CD19 CAR T cells (specifically, more than 60 million CAR T cells from donor cells derived from patients with lymphoma and more than 200 million CAR T cells from healthy donors). The in vitro secretion of cytokines, the short-term cytotoxic activity and the long-term persistence and proliferation of the cell products, as well as their in vivo anti-leukaemic activity, were comparable to those of T cells produced in a gas-permeable well.

Global daily mask use estimation in the pandemic and its post environmental health risks: Analysis based on a validated dynamic mathematical model.

The outbreak of the COVID-19 pandemic led to a sharp increase in disposable surgical mask usage. Discarded masks can release microplastic and cause environmental pollution. Since masks have become a daily necessity for protection against virus infections, it is necessary to review the usage and disposal of masks during the pandemic for future management.

Similarity-guided graph contrastive learning for lncRNA-disease association prediction.

The increasing research evidence indicates that long non-coding RNAs (lncRNAs) play important roles in regulating biological processes and are closely associated with many human diseases. Computational methods have emerged as indispensable tools for identifying associations between long non-coding RNA (lncRNA) and diseases, primarily due to the time-consuming and costly nature of traditional biological experiments. Given the scarcity of verified lncRNA-disease associations, the intensifying focus on deep learning is playing a crucial role in refining the accuracy of predictive models.

B7-H3-Targeting Chimeric Antigen Receptors Epstein-Barr Virus-specific T Cells Provides a Tumor Agnostic Off-The-Shelf Therapy Against B7-H3-positive Solid Tumors.

Unlabelled: Encouraged by the observations of significant B7-H3 protein overexpression in many human solid tumors compared to healthy tissues, we directed our focus towards targeting B7-H3 using chimeric antigen receptor (CAR) T cells. We utilized a nanobody as the B7-H3-targeting domain in our CAR construct to circumvent the stability issues associated with single-chain variable fragment-based domains. In efforts to expand patient access to CAR T-cell therapy, we engineered our nanobody-based CAR into human Epstein-Barr virus-specific T cells (EBVST), offering a readily available off-the-shelf treatment.

DeepKEGG: a multi-omics data integration framework with biological insights for cancer recurrence prediction and biomarker discovery.

Deep learning-based multi-omics data integration methods have the capability to reveal the mechanisms of cancer development, discover cancer biomarkers and identify pathogenic targets. However, current methods ignore the potential correlations between samples in integrating multi-omics data. In addition, providing accurate biological explanations still poses significant challenges due to the complexity of deep learning models.

Deep learning of pretreatment multiphase CT images for predicting response to lenvatinib and immune checkpoint inhibitors in unresectable hepatocellular carcinoma.

Objectives: Combination therapy of lenvatinib and immune checkpoint inhibitors (CLICI) has emerged as a promising approach for managing unresectable hepatocellular carcinoma (HCC). However, the response to such treatment is observed in only a subset of patients, underscoring the pressing need for reliable methods to identify potential responders.

Materials & Methods: This was a retrospective analysis involving 120 patients with unresectable HCC.

LGCDA: Predicting CircRNA-Disease Association Based on Fusion of Local and Global Features.

CircRNA has been shown to be involved in the occurrence of many diseases. Several computational frameworks have been proposed to identify circRNA-disease associations. Despite the existing computational methods have obtained considerable successes, these methods still require to be improved as their performance may degrade due to the sparsity of the data and the problem of memory overflow.

Deep Imputation Bi-stochastic Graph Regularized Matrix Factorization for Clustering Single-cell RNA-sequencing Data.

By generating massive gene transcriptome data and analyzing transcriptomic variations at the cell level, single-cell RNA-sequencing (scRNA-seq) technology has provided new way to explore cellular heterogeneity and functionality. Clustering scRNA-seq data could discover the hidden diversity and complexity of cell populations, which can aid to the identification of the disease mechanisms and biomarkers. In this paper, a novel method (DSINMF) is presented for single cell RNA sequencing data by using deep matrix factorization.

Swin-cryoEM: Multi-class cryo-electron micrographs single particle mixed detection method.

Cryo-electron micrograph images have various characteristics such as varying sizes, shapes, and distribution densities of individual particles, severe background noise, high levels of impurities, irregular shapes, blurred edges, and similar color to the background. How to demonstrate good adaptability in the field of image vision by picking up single particles from multiple types of cryo-electron micrographs is currently a challenge in the field of cryo-electron micrographs. This paper combines the characteristics of the MixUp hybrid enhancement algorithm, enhances the image feature information in the pre-processing stage, builds a feature perception network based on the channel self-attention mechanism in the forward network of the Swin Transformer model network, achieving adaptive adjustment of self-attention mechanism between different single particles, increasing the network's tolerance to noise, Incorporating PReLU activation function to enhance information exchange between pixel blocks of different single particles, and combining the Cross-Entropy function with the softmax function to construct a classification network based on Swin Transformer suitable for cryo-electron micrograph single particle detection model (Swin-cryoEM), achieving mixed detection of multiple types of single particles.