Clustered regularly interspaced palindromic repeats(CRISPR) gene editing, known for its precision, is revolutionizing tumor research and treatment. This article covers the evolution of the CRISPR system from Cas9, which produces DNA double-strand breaks, to Cas12, Cas13, base editors, and prime editors. These breakthroughs allow DNA/RNA editing, transcriptional regulation, and epigenetic reprogramming. The study encompasses CRISPR's diverse applications in tumor research, including high-throughput screening of cancer driver genes, identification of synthetic lethal targets, and analysis of drug resistance pathways across various cancer types. It highlights CRISPR's importance in therapeutic tactics, such as targeting oncogene inactivation, restoring tumor suppressor gene activity, and engineering immune effector cells like CAR-T and NK cells to increase persistence, cytotoxicity, and resistance to exhaustion. This review also examines CRISPR's role in modifying the tumor microenvironment(TME), encompassing the regulation of immune checkpoints, metabolic reprogramming, and the targeted eradication of specific immunosuppressive cells. Off-target consequences for both delivery and efficiency are discussed, along with cutting-edge technologies including high-fidelity Cas variants, AI-assisted sgRNA design, and stimuli-responsive delivery systems. Finally, the paper examines how CRISPR can be integrated with combination medicines, multimodal editing methods, and single-cell and multi-omics data to deliver tailored, precision-based interventions. This review explains the molecular logic and translational routes of CRISPR, highlighting its promise to revolutionize precision oncology.  

This study introduces an innovative cloud-based Genome-Wide Association Study (GWAS) platform​that addresses critical challenges in genomic research, including inefficient data access, high computational demands, and complex data integration. By leveraging Kubernetes-based distributed architecture and hybrid storage systems, the platform integrates multi-omics data (neuroimaging, proteomics, microbiome, metabolomics, immunology) from major databases (GWAS Catalog, UK Biobank, FinnGen) encompassing​40,000+ phenotypes. A key innovation is the ​FastGWASR R package, enabling seamless Mendelian randomization, drug target validation, and multi-omics analyses. Performance evaluations demonstrate​sub-second data extraction,​>99% reduction in local storage needs, and significantly lower hardware requirements​compared to traditional methods. The platform successfully processed large-scale analyses (e.g., MR-PheWAS, multi-omics integration) with comparable scientific accuracy but dramatically improved efficiency. Case studies validated its effectiveness in metabolite-diabetes causal analysis, PCSK9 drug target validation, and gut microbiome-inflammation network analysis. The​cloud ecosystem democratizes genomic research, reducing barriers for resource-limited institutions and fostering interdisciplinary collaboration. Its secure, scalable, and user-friendly design accelerates discoveries in precision medicine, from disease risk prediction to drug development. Future enhancements will expand data diversity, optimize algorithms, and strengthen ecosystem interoperability, positioning the platform as a transformative force in global genomics and personalized healthcare.

Precuneus dysfunction is a crucial biomarker of Alzheimer's disease (AD), playing a central role in AD continuum. However, the stage-specific changes and temporal effects of structural and functional connectivity (FC) within para-cingulate networks (PCNs), which are newly discovered and highly precuneus-related networks across the AD continuum remain unclear. This study aimed to characterize the abnormalities in brain regions associated with PCN and default mode network (DMN) across the stages of subjective memory complaints (SMC), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD, and to assess the temporal effects on the stage-dependent changes. A total of 153 elderlies were included. Baseline and two-year follow-up data were collected, including demographic information (six-month and 12-month intervals were also collected), neuropsychological assessments, and T1-weighted and resting-state functional MRI. We mapped the trajectory of structural and functional abnormalities in PCN/DMN-related regions across the AD continuum, along with their associations with neuropsychological measures. At the baseline, reduced gray matter volume (GMV) in PCN was observed exclusively in the AD, specifically in Brodmann areas 7 posterior-medial (Ba7), Ba 23 part c/d, parieto-occipital sulcus, and retro-splenial cortex. After 2 years, GMV abnormalities gradually emerged in LMCI. This decline was associated with global cognitive, functional activity deficits and increased dementia severity. Reduced FC between precuneus and Ba7 was observed in AD and LMCI at 2-year visit and was associated with dementia severity. Over time, the gap in GMV and FC within DMN/PCN-related regions across AD continuum progressively narrowed. Functional connectivity and structural abnormalities in PCN regions exhibit age dependency, first emerging in AD and progressively affecting LMCI over time. Abnormalities in DMN can initially be observed in SMC. Both of which intensify over time and with increasing disease severity within the AD spectrum. These findings suggest that the disruption of organizational integrity of these two networks is a key factor in the progression of AD and may dynamically reflect the development of the disease.

A new review from Beijing Chest Hospital, Capital Medical University, systematically expounds the dual role of DNA repair core protein Rad51 in tumors. This article reveals that Rad51 not only maintains genomic stability through homologous recombination repair, but its overexpression is also closely related to chemotherapy, radiotherapy and PARP inhibitor resistance in various cancers. Most importantly, the review delves deeply into how Rad51 shapes the tumor immune microenvironment by regulating the cGAS-STING pathway, influencing neoantigen generation and PD-L1 expression, providing a new theoretical basis for the anti-cancer strategy of combining Rad51 with immune checkpoint inhibitors.

A comprehensive review by Professor Dong's research group, published in eGastroenterology, delineates the intertwined mechanisms linking steatotic liver disease (SLD) and cancer. It highlights the genetic, metabolic, and immunological factors driving disease progression from steatosis to hepatocellular carcinoma (HCC). The authors summarize emerging therapeutics—thyroid hormone receptor β agonists, GLP-1-based poly-agonists, FGF21 analogues, and FXR modulators—offering hope for SLD and related malignancies.

In a paper published in Frontiers of Engineering Management, researchers conducted a meta-analysis of 62 empirical studies and 11228 study subjects published between 2012 and 2023, to revisit what factors promote BIM adoption more effectively through the TOE framework. This study quantifies the relationship between BIM adoption and its determinants, proposing a comprehensive theoretical model. It provides new insights for analyzing BIM adoption and the potential mechanism behind it, aiding in clarifying the long-standing disputes in the BIM adoption literature and promoting the further adoption of BIM in the AEC industry.

In a paper published in Frontiers of Engineering Mangement, a team of scientists including Qingqi LONG, Xiaobo WU, and Juanjuan PENG present a simulation study on recovery strategies for government-led food supply chains during the COVID-19 pandemic. This study focuses on government-led food supply chains, employs simulations across different pandemic phases, identifies main factors contributing to food shortages such as insufficient transportation capacity, uneven distribution of district warehouses, and production-demand mismatches, and confirms effective recovery strategies like enhancing transportation capacity, establishing new district warehouses, and increasing production capacity, while also finding that some strategies may have unintended negative consequences.

A new study published in Frontiers of Engineering Management presents a framework for improving the visualization of blockchain-based data management processes (DMP) in construction engineering and management (CEM). The study highlights the growing adoption of blockchain technology in CEM but notes that current visualization methods remain too simplistic to drive widespread adoption. To address this, the researchers develop a conceptual model, analyze 49 scholarly cases, and identify four key challenges: data diversity, visualization tools, visualization mediums, and domain-specific representation. Based on their findings, they offer a five-step guideline for optimizing blockchain visualization in construction projects, including targeting the right domain, planning the visualization approach, selecting appropriate tools and mediums, and refining the final solution. This research aims to inspire further development of visualization techniques to maximize blockchain's potential in CEM.