Targeting ARPC1B Cancer Stem Cells to Sensitise Pancreatic Cancer to Gemcitabine Treatment.

ARPC1B cancer stem cells (CSCs) in pancreatic cancer are identified as a subpopulation resistant to gemcitabine. In our study, drug repositioning, molecular docking, and surface plasmon resonance (SPR) technique jointly revealed that CK-636 can directly target ARPC1B protein with high affinity. In vitro cytotoxicity, ex vivo organoid cultures, in vivo xenograft and orthotopic gemcitabine-resistant pancreatic cancer model demonstrated that combination therapy of gemcitabine plus CK-636 showed a superior anti-tumor effect compared with gemcitabine monotherapy.

Effect of Metal-Metal Distance on the Performance of Dual-Atom Catalysts for the Oxygen Reduction Reaction: A Density Functional Theory and Micro-kinetics Study.

Dual-atom catalysts (DACs) display excellent activity for the oxygen reduction reaction (ORR). The dual-metal configuration allows for synergistic interactions and tailored adsorption of key intermediates, thereby breaking traditional OH-OOH scaling relations and enabling dissociative O activation pathways. Recent studies suggest that the metal-metal (M-M) distance within DACs critically influences their electronic structure and catalytic behavior; however, a deep understanding of M-M distance effects on ORR thermodynamics and kinetics is presently lacking.

Identification of copper related biomarkers in breast cancer using machine learning.

Background: Breast cancer is the most prevalent and deadly cancer among women globally, necessitating more effective diagnostic and therapeutic approaches. This study aims to explore new treatment targets and diagnostic tools.

Methods: Employing machine learning techniques and utilizing PCR, IHC technologies, and multiple databases, we identified and validated genes closely linked with breast cancer and copper-induced cell death.

Bioinspired Photodriven Camouflaged Soft Robot.

Soft bionic robots have garnered significant attention recently due to their exceptional adaptability to various environments, making them ideal for hazardous missions, particularly in the military. Developing robots with active camouflage is vital for their operational success. Dynamic structural colors, known for their durability, high tunability, and broad color range, are widely employed in camouflage.

Pathway-based cancer transcriptome deciphers a high-resolution intrinsic heterogeneity within bladder cancer classification.

Background: The heterogeneity of bladder cancer (BLCA) is affected by its inherent transcriptional properties and tumor microenvironment (TME). Stromal transcriptional components in the TME significantly influence the transcriptional classification of BLCA, and the intrinsic biological transcriptional characteristics of cancer cells may be obscured by the dominant, lineage-dependent transcriptional components of stromal origin. This study aimed to explore the degree and mechanisms by which cancer-intrinsic gene expression profiles contribute to the classification and prognosis of BLCA patients.

Insights into next-generation immunotherapy designs and tools: molecular mechanisms and therapeutic prospects.

Immunotherapy has revolutionized the oncology treatment paradigm, and CAR-T cell therapy in particular represents a significant milestone in treating hematological malignancies. Nevertheless, tumor resistance due to target heterogeneity or mutation remains a Gordian knot for immunotherapy. This review elucidates molecular mechanisms and therapeutic potential of next-generation immunotherapeutic tools spanning genetically engineered immune cells, multi-specific antibodies, and cell engagers, emphasizing multi-targeting strategies to enhance personalized immunotherapy efficacy.

Research letter: the global clinical trial landscape for non-alcoholic fatty liver disease (NAFLD) current status and future prospects.

Purpose: This study comprehensively analyzed the global clinical trials and depicted a landscape for non-alcoholic fatty liver disease (NAFLD) therapy.

Methods: Using the Trialtrove database, we collected trial information of 2,242 clinical trials. Using molecular docking analysis, we investigated the pharmacological properties of glucagon-like peptide-1 receptor (GLP-1 R) agonist such as semaglutide and its binding affinity to GLP-1 R protein.

Investigating the Mechanism of the Fuzheng Huayu Formula in Treating Cirrhosis through Network Pharmacology, Molecular Docking, and Experimental Verification.

Cirrhosis, characterized by liver fibrosis and structural remodeling, is a leading cause of liver cancer. The Fuzheng Huayu formula (FZHY) has been approved for treating liver fibrosis in China since 2002, but its effects and mechanisms on cirrhosis remain largely unknown. This study employed network pharmacology, molecular docking, and in vitro experiments to elucidate the specific mechanisms of FZHY against liver cirrhosis.

Integrated analysis of scRNA-seq and bulk RNA-seq data identifies BHLHE40 as a key gene in pancreatic cancer progression and gemcitabine resistance.

Objective: Pancreatic cancer is characterized by its high mortality rate and short survival periods, and novel therapeutic targets and tailor personalized strategies are urgently needed. In this study, we aim to investigate the molecular mechanisms underlying pancreatic ductal adenocarcinoma (PDAC) progression and chemoresistance, with a focus on identifying novel therapeutic targets.

Methods: Multiomics approaches were integrated to identify novel actionable targets for PDAC.

Therapeutic strategies for adrenocortical carcinoma: integrating genomic insights, molecular targeting, and immunotherapy.

Adrenocortical carcinoma (ACC) is an uncommon and highly aggressive cancer originating in the adrenal cortex, characterized by a high likelihood of recurrence and unfavorable survival rates, particularly in the advanced disease stages. This review discusses the complex molecular pathogenesis of ACC, focusing on critical pathways implicated in the tumorigenesis and providing potential targets for therapy: the Wnt/β-catenin signaling pathway, the IGF2/IGF1R axis, and the apoptosis pathway regulated by p53. Current treatment strategies include surgical resection and mitotane, the sole adrenolytic agent approved by the FDA; however, its effects in advanced disease are suboptimal.

Identification of CACNB1 protein as an actionable therapeutic target for hepatocellular carcinoma via metabolic dysfunction analysis in liver diseases: An integrated bioinformatics and machine learning approach for precise therapy.

In addition to histological evaluation for nonalcoholic fatty liver disease (NAFLD), a comprehensive analysis of the metabolic landscape is urgently needed to categorize patients into distinct subgroups for precise treatment. In this study, a total of 806 NAFLD and 267 normal liver samples were comprehensively analyzed. Alterations in 114 metabolic pathways were investigated and two distinct metabolic clusters were identified.

Multi-omics and single-cell analysis reveals machine learning-based pyrimidine metabolism-related signature in the prognosis of patients with lung adenocarcinoma.

Pyrimidine metabolism is a hallmark of tumor metabolic reprogramming, while its significance in the prognostic and therapeutic implications of patients with lung adenocarcinoma (LUAD) still remains unclear. In this study, an integrated framework of various machine learning and deep learning algorithms was used to develop the pyrimidine metabolism-related signature (PMRS). Its efficacy in genomic stability, chemotherapy and immunotherapy resistance was evaluated through comprehensive multi-omics analysis.

Rational metabolic engineering of Escherichia coli for the industrial-scale production of l-phenylalanine.

Rational metabolic engineering has numerous applications in the optimization of microorganisms for the production of valuable compounds at the laboratory-scale. However, the existing strategies and tools are far from sufficient for engineering of industrial strains due to their specificity. The aim of this project was to implement novel strategies to enhance industrial l-phenylalanine (l-PHE) production and yield, including the regulation of key gene expressions, modifications of global transcription factors, creation of NADPH-independent pentose phosphate pathway and pyruvate-oxaloacetate-phosphoenolpyruvate cycle.

Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes.

In addition to traditional biomarkers like PD-(L)1 expression and tumor mutation burden (TMB), more reliable methods for predicting immune checkpoint blockade (ICB) response in cancer patients are urgently needed. This study utilized multiple machine learning approaches on nonsynonymous mutations to identify key mutations that are most significantly correlated to ICB response. We proposed a classifier, Gene mutation-based Predictive Signature (GPS), to categorize patients based on their predicted response and clinical outcomes post-ICB therapy.

CAR-T therapy for endocrine neoplasms: novel targets and combination of therapies.

Endocrine malignancies constitute a heterogeneous tumour group with diverse biological characteristics. While typically indolent, they encompass aggressive types and presence of any metastatic sign indicates a high probability of recurrence and a diminished response to conventional therapies. Chimeric antigen receptor (CAR)-T cell immunotherapy has constituted a revolutionary advance in cancer treatment and exhibited significant potential for application in endocrine cancer.

Glucose Metabolism-Targeted Poly(amino acid) Nanoformulation of Oxaliplatin(IV)-Aspirin Prodrug for Enhanced Chemo-Immunotherapy.

Inappropriate glucose metabolism in cancer cells is associated with immunosuppressive tumor microenvironments (TMEs). Although glycolysis inhibition enhances T cell-mediated immune responses, the integrated platforms combining glycolysis inhibition with immunotherapy remain underdeveloped. To address this gap, a glucose metabolism-targeted poly(amino acid) nanoformulation of oxaliplatin(IV)-aspirin prodrug (NP/OXA-ASP) is developed to improve chemo-immunotherapy by suppressing tumor glycolysis.

Relationship Between Obstructive Sleep Apnea and Enuresis in Children: Current Perspectives and Beyond.

Background: Nocturnal enuresis (NE) and obstructive sleep apnea (OSA) are common diseases in children, which often cause various social and psychological problems. The coexistence of both seriously affects the physical and mental health of children. However, whether OSA can directly lead to NE and the specific pathogenesis is still unclear.

Wafer-Scale Transfer and Integration of Tungsten-Doped Vanadium Dioxide Films.

Modern optoelectronic devices trend toward greater flexibility, wearability, and multifunctionality, demanding higher standards for fabrication and operation temperatures. Vanadium dioxide (VO), with its metal-insulator transition (MIT) at 68 °C, serves as a crucial functional layer in many optoelectronic devices. However, VO usually needs to grow at >450 °C in an oxygen-containing atmosphere and to function across its MIT temperature, leading to low compatibility with most optoelectronic devices, especially on flexible substrates.

Solar-Driven Conversion of Nitrogen and Water to Solid Fertilizer in an Outdoor 1 m Panel Reactor.

Harnessing solar energy to convert molecular N into nitrogen-rich chemicals (e.g., ammonia) provides a potential pathway for the manufacture of "solar fertilizers".

Efficient Photocatalytic Propane Direct Dehydrogenation to Propylene Over PtO Clusters.

The direct dehydrogenation of alkanes to olefins under mild conditions is challenging due to the inert nature of alkyl C─H bonds. Herein, an efficient photocatalytic system is developed for propane direct dehydrogenation (PDH) to propylene, consisting of ≈1.30 nm sized PtO clusters immobilized on a layered double hydroxide -derived ZnO/AlO support (LD-Pt).

Complete BmFib-L knockout reveals its indispensable role in silk fiber formation.

Silkworm (Bombyx mori), belonging to the order Lepidoptera, is an important model insect for economic and scientific research. The capacity of the silkworm to secrete robust silk renders it a valuable economic resource, while its biological characteristics offer insights into a number of scientific disciplines. Despite the extensive research conducted to elucidate the mechanisms of silk secretion, many aspects remain unclear.