Search Results (1,018)

Human epidermal growth factor receptor 2 (HER2) dysregulation contributes to tumorigenesis in gastric and gastroesophageal junction adenocarcinomas (GC/GEJ). HER2 overexpression has been associated in multiple cohorts with aggressive behavior and poor outcomes. While HER2 amplification has long guided therapy in HER2-positive disease, antibody–drug conjugates (ADCs) have shifted attention toward the HER2-low category, typically defined as immunohistochemistry (IHC) 1+ or IHC 2+ with negative in situ hybridization (ISH). This narrative review integrates evidence from the peer-reviewed literature, current testing recommendations, and registered clinical trials. It clarifies practical issues in HER2-low assessment and maps the evolving therapeutic landscape of HER2-targeted ADCs including rational combination strategies that may extend benefit beyond conventionally HER2-positive tumors. A cross-tumor perspective contrasts GC/GEJ testing and biology with the breast cancer paradigm and summarizes the importance of HER2-low expression in non-gastric malignancies. Finally, we discuss the therapeutic strategies in HER2-low GC/GEJ and highlight key safety and monitoring considerations for HER2-directed ADCs. Full article

The chiral-induced spin selectivity (CISS) effect enables the spin-selective transport of electrons through chiral systems, linking handedness with spin polarization. This review provides a comprehensive examination of the emerging field of chiral electrocatalysis, detailing also the extensive experimental and theoretical endeavor conducted to gain a deeper understanding of the fundamental physical principles and mechanistic characteristics of this phenomenon. In particular, the CISS effect has garnered significant attention within the scientific community due to its potential for broad applicability across several fields, ranging from spintronics to biology. Among them, the prospective harnessing of the CISS effect into electrocatalytic processes offers an innovative strategy to improve the performance of energy conversion and storage technologies. This review deeply examines the practical applications of the CISS effect across different electrocatalytic reactions, with particular emphasis on its influence on the oxygen reduction reaction (ORR) and its critical role in energy conversion systems where the ORR reaction is a key process, such as in metal–air batteries, whose safety and performance can be enhanced through spin-selective electron transport. Full article

Phosphonate natural products, characterized by a stable carbon–phosphorus (C–P) bond, represent a distinctive class of natural products with broad bioactivities and diverse applications in medicine and agriculture. Despite their potential, the field has lacked a systematic, quantitatively informed synthesis linking discovery trends to biological function and scalable production. In this review, we curate 71 reports of phosphonate natural products between 1959 and the present, primarily from bacterial sources, and analyze them across discovery modalities, bioactivity profiles, and producer taxonomy. We further summarize structure–activity relationships and consolidate engineering strategies—including metabolic engineering, synthetic biology, and biocatalytic cascades—employed to enhance phosphonate yields. Based on these analyses, we propose practical directions to accelerate the discovery of novel phosphonates, and improve their accessibility through advances in production and isolation technologies. Full article

Classic Hairy Cell Leukemia (cHCL) and related conditions are rare, indolent B-cell malignancies characterized by distinctive morphological, immunophenotypic, and molecular features. Over the past decade, major advances in understanding the pathophysiology and molecular underpinnings have reshaped diagnostic and therapeutic approaches. This review synthesizes current knowledge on the cellular origins and signaling pathways that drive cHCL and Hairy Cell Variant (HCL-v)/splenic B-cell lymphoma/leukemia (SBLPN) and other molecular aberrations in disease pathogenesis. We discuss evolving diagnostic modalities, including flow cytometry, immunohistochemistry, and next-generation sequencing, that enhance diagnostic precision and disease monitoring. Additionally, we examine established and emerging therapeutic strategies—from purine nucleoside analogs (PNA) to targeted inhibitors and immunotherapies—that have significantly improved patient outcomes while highlighting challenges such as relapse and treatment resistance. By integrating insights from molecular biology and clinical practice, this review aims to provide a comprehensive understanding of cHCL and related disorders. Full article

Synthetic biology is reshaping in vitro diagnostics (IVD) by enabling programmable and modular biosensing elements that can be integrated into point-of-care testing (POCT) platforms. Compared with conventional assays that depend on fixed chemistries and centralized instrumentation, synthetic biology-based systems offer adaptable molecular recognition, tunable signal processing, and flexible readout formats for decentralized diagnostics. In this review, we present synthetic biology-enabled IVD as programmable biosensing platforms organized into four functional layers: molecular recognition, signal transduction and amplification, output generation, and system integration. We discuss four major enabling modules, including cell-free protein synthesis (CFPS) systems, aptamer and riboswitch sensors, CRISPR-Cas diagnostic platforms, and microfluidic integration technologies. We summarize representative clinical applications from 2021 to 2025 in infectious disease detection, cancer biomarker analysis, and drug metabolism/toxicity screening. In addition, we examine practical considerations beyond analytical sensitivity, including matrix tolerance, workflow complexity, manufacturability, quantitative capability, and regulatory readiness. Finally, we highlight future directions for programmable diagnostics, including AI-assisted biosensor design, multimodal readouts, interoperable platform architectures, and real-world clinical validation. Full article

Duolang sheep, an indigenous breed of southern Xinjiang, are significant for their agricultural systems due to their adaptation to arid and semi-arid environments. This review integrates recent advancements in Duolang’s reproductive biology, genomic studies, and management strategies to address the breed’s reproductive efficiency under challenging ecological conditions. Reproductive traits such as puberty onset, estrous cycle characteristics, and seasonal breeding are influenced by complex genetic and several environmental factors. Numerous remarkable genomic findings highlight key loci related to fecundity, including the Booroola FecB mutation, as well as genes involved in steroidogenesis, folliculogenesis, and HPG axis regulation. Despite the genetic potential for increased prolificacy, Duolang sheep often exhibit low litter sizes, largely constrained by detrimental environmental factors and management practices. This review emphasizes the significance of integrating genetics, nutrition, and reproductive management to optimize productivity. Strategies such as nutritional flushing, hormone-based estrous synchronization, and selective breeding for increased litter size are discussed, with a focus on minimizing the risks associated with early puberty and lamb survival. Furthermore, the review explores the potential of genomic selection, marker-assisted breeding, and advanced reproductive technologies to enhance the breed’s performance. Finally, the review outlines future research directions, necessitating the development of genomic resources, precise breeding programs, and field trials on reproductive interventions to accelerate genetic gains in Duolang sheep. This integrated approach promises to improve reproductive outcomes, with implications for sustainable sheep production in Xinjiang and similar environments across the globe. Full article

Exopolysaccharides (EPSs) produced by lactic acid bacteria (LAB) are natural high-molecular-weight polymers secreted extracellularly during growth. They possess unique rheological properties and emulsifying stability and may exhibit prebiotic-related functionalities. In food systems, EPSs exhibit multiple functional values. In recent years, driven by the global “Clean Label” movement and increasing consumer demand for natural and healthy foods, EPSs, as safe and traceable natural food-grade prebiotics, have attracted extensive attention in the dairy industry. This review summarizes EPSs’ structure, properties, and mechanisms in dairy systems. It focuses on their functional effects and mechanisms in typical dairy products such as yogurt, cheese, and ice cream, and analyzes the technical bottlenecks limiting large-scale production, including low yield, high cost, and challenges in separation and purification. This review further outlines several promising research directions for EPS research. These include strain modification via synthetic biology strategies, fermentation optimization using high-throughput screening technologies, and targeted application based on structure–function relationships. It aims to provide systematic theoretical references and practical guidance for the efficient development and innovative application of EPSs in the food industry. Full article

Pancreatic ductal adenocarcinoma (PDAC) and biliary tract cancers (BTCs) remain highly lethal gastrointestinal malignancies because of late presentation, marked molecular heterogeneity, and limited durable benefit from conventional systemic therapy. This narrative review summarizes recent advances in both diseases, focusing on practice-informing clinical trials, biomarker-driven treatment strategies, and translational insights into tumor biology and resistance. In PDAC, progress includes refinement of perioperative management, broader germline and somatic testing, recognition of DNA damage repair-deficient subsets, and development of KRAS-directed therapies and rational combination strategies. In BTCs, especially intrahepatic cholangiocarcinoma, comprehensive molecular profiling has expanded precision oncology through actionable alterations such as FGFR2 rearrangements, IDH1 mutations, HER2 amplification/overexpression, BRAF V600E, NTRK fusions, and MSI-high/dMMR status. Immunotherapy has a clearer role in selected BTC populations, whereas in PDAC benefit remains largely restricted to rare biomarker-defined subsets. Across both diseases, circulating tumor DNA is emerging as a promising tool for prognostication, minimal residual disease assessment, response monitoring, and early resistance detection. Contemporary care increasingly depends on early molecular profiling, individualized treatment sequencing, and integration of targeted therapies, biomarker-guided immunotherapy, and clinical trials. Full article

Food security is increasingly threatened by climate change and population growth. Sweet potato has become a crucial crop for ensuring food security due to its adaptability to marginal lands and high yield potential. However, its sustainable production is severely limited by diverse biotic stresses (including fungi, viruses, nematodes, insect pests and bacteria), which cause substantial yield losses. Despite its considerable importance, the key bottlenecks in this field remain unresolved, including the incomplete elucidation of core resistance mechanisms, unclear molecular regulatory networks underlying defense responses, insufficient understanding of crosstalk among multiple stresses, and limited integration of emerging technologies into practical resistance breeding. This review synthesizes the latest advances over the past two years. We dissect sweet potato’s defense mechanisms from multiple dimensions and provide novel insights into biotic stress resistance gene regulatory networks. Given that sweet potato production faces the combined effects of multiple pests and biotic-abiotic stresses, we elaborate on the complex stress interactions in sweet potato. In addition, we propose biotic stress management strategies and a ten-year cultivar improvement roadmap that leverages the potential of emerging technologies, including artificial intelligence (AI), gene editing, novel omics approaches and synthetic biology. Taken together, with continuous intensification of global biotic stress challenges, systematic multi-dimensional strategies are imperative to alleviate biotic stress-associated yield and quality impairment in sweet potato. On this basis, this review provides a valuable theoretical and practical reference for resistance breeding and the sustainable production of sweet potato. Full article

Prostate cancer (PCa) progression and treatment resistance are driven by tumor-intrinsic mechanisms and adaptive remodeling of the tumor microenvironment, in which cancer-associated fibroblasts (CAFs) play a crucial role. Although CAF biology is increasingly recognized, a major translational gap remains: CAFs are highly heterogeneous, and comprise distinct functional states with divergent effects on disease progression, immune regulation, and therapeutic resistance. To bridge this gap, we synthesize evidence from single-cell and spatial transcriptomic studies, tissue-based pathology, liquid biopsy assays, and molecular imaging to construct an evidence-tiered, decision-oriented translational framework that connects stromal mechanisms, translational measurement strategies, and therapeutic interventions in PCa. Single-cell and spatial transcriptomic analyses have consistently identified multiple CAF programs, including matrix-remodeling, inflammatory, immunoregulatory, antigen-presenting, and therapy-imprinted states, each with distinct functional outputs and clinical correlates. Tissue-based readouts, including reactive stromal grade (RSG) and fibroblast activation protein (FAP) immunohistochemistry, provide practical proxies for stromal activation and correlate with disease-specific mortality and imaging phenotypes. Circulating CAFs (cCAFs) represent an emerging liquid biopsy modality for longitudinal stromal monitoring, although technical standardization is required before clinical implementation. FAP-targeted PET imaging and emerging dual prostate-specific membrane antigen (PSMA)/FAP-targeted theranostic strategies provide noninvasive tools for patient selection and response assessment, particularly in PSMA-discordant or tracer-heterogeneous disease. Androgen receptor (AR)-targeted therapy can reprogram stromal states toward resistance-promoting circuits, highlighting the dynamic and plastic nature of the CAF compartment. A state-based CAF framework organizes stromal biology into testable translational hypotheses rather than immediate clinical standards. RSG and FAP-based tissue or imaging readouts are practical markers of stromal activation, whereas spatial CAF-immune signatures and cCAF assays remain investigational and require assay harmonization and prospective validation. Future trials should pre-specify stromal biomarkers as enrichment or pharmacodynamic variables when matched to the intervention and should avoid treating CAFs as a uniform therapeutic target. Full article

Breast cancer surgery has evolved from radical procedures to increasingly individualized and less invasive approaches. This narrative review contextualizes this evolution, synthesizes current evidence supporting surgical de-escalation, and examines emerging strategies that may further reduce the need for surgery. The manuscript is based on a structured appraisal of PubMed/MEDLINE literature and major international guidelines, prioritizing randomized trials, prospective studies, and consensus statements. Contemporary practice is characterized by progressive reduction in both breast and axillary surgery, enabled by advances in tumour biology, neoadjuvant systemic therapy, sentinel node strategies, and oncoplastic techniques. Emerging approaches—including selective omission of axillary surgery, targeted axillary dissection, and investigational strategies aiming at omission of breast surgery in exceptional responders—highlight a shift toward response-adapted and biology-driven care. While technological innovations such as robotic surgery and intraoperative radiotherapy may influence surgical practice, their role in true de-escalation remains limited or context-dependent. Overall, the field is moving toward minimizing surgical burden without compromising oncological safety, with future progress likely driven by improved patient selection, imaging, and integration of systemic therapy response. Full article

Endometrial cancer (EC) is increasingly recognized as a heterogeneous disease, yet current treatment strategies often fail to explain why tumors with similar molecular profiles respond differently or develop resistance. This gap points to regulatory mechanisms beyond static genomic alterations. Epigenetic dysregulation through DNA methylation, histone modification, and non-coding RNA (ncRNAs) networks acts as a dynamic and reversible system that governs how tumors adapt under therapeutic pressure. In EC, alterations affecting key regulators such as MLH1, PTEN, and hormone receptors directly influence sensitivity to immunotherapy, targeted therapy, and endocrine treatment, defining treatment-responsive and treatment-resistant states. These observations shift the role of epigenetics from a descriptive feature of tumor biology to a determinant of therapeutic behaviour. Epigenetic states influence immune recognition, pathway activation, and cell cycle control, thereby shaping response to chemotherapy and immune checkpoint blockade. Biomarkers derived from these alterations, including methylation signatures and circulating RNAs, offer opportunities for patient stratification and longitudinal monitoring of treatment response. Therapeutically, targeting epigenetic regulators provides a strategy to reverse resistance and restore treatment sensitivity. DNA methyltransferase and histone deacetylase inhibitors, particularly in combination with established therapies, have shown potential to enhance treatment efficacy. Emerging approaches, including locus-specific epigenetic editing and liquid biopsy–guided monitoring, further support adaptive treatment strategies. Integrating epigenetic reprogramming into clinical decision-making offers a practical path toward improving treatment response and overcoming resistance in EC. Here, we propose an Epigenetic State–Response Framework (ESRF) in which dynamic epigenetic states define treatment-sensitive and resistant phenotypes, map to specific therapeutic vulnerabilities, and can be actively reprogrammed to restore treatment response. Full article

Opportunities abound in microfluidic technologies to impact how we understand extremely complex systems with many constituents which change with time and space. In these technologies, separation science plays a central role towards understanding everything from biology and healthcare to environmental monitoring to the search for life in the Solar system. Separations can amplify the capabilities of detection modalities by isolating targets and/or increasing their concentration while removing background constituents which can interfere with their sensing. In essence, separations increase the amount of information that can be gathered from a sample. The ideal features of next-generation separations capability are present in gradient insulator-based dielectrophoresis (g-iDEP), enabled by the length scale and precision of microfluidics. It acts through electric field interactions with particles, which enables unbiased (label-free) separations since all relevant particles, from atoms to cells, have an accessible response to electricity—either through linear (electrophoresis) or higher-order gradient (dielectrophoresis and related) effects. The technique isolates and concentrates, enabling improved detection function and multidimensional separations. Its foundational theoretical capabilities give it separations power on the order of 1:10⁸, beyond the resolving power of the best mass spectrometers and ultra-high resolution spectroscopies. Experimental evidence is amassing that shows it to be a powerful tool that can resolve tiny differences in cells (antibiotic resistance versus susceptible in unlabeled paired isolates across many species) and differentiate single-point mutations in proteins. Its capabilities are still emerging, and this work aims to quantify the current practice and connect those approaches to the ultimate capabilities of the technique towards quantifying the dynamic range and resolving power of the strategy as a whole. The technique uses two methods of quantifying the electrophysical properties of the target, voltage sweep and spatial methods. The voltage sweep method is lower-resolution and serves as a search mode, while the spatial method is higher-resolution and quantifies the properties over a smaller defined range determined via the sweep method. These quantification methods are examined by collating existing experimental data, performing relevant Monte Carlo simulations, and finite element model calculations. These are summarized to understand the mechanisms currently limiting the technique, facilitate quantitative comparisons with traditional separation science capabilities in terms of resolution and dynamic range, and compare them to the theoretical limits of the strategy. Full article

The prediction accuracy of RNA’s tertiary structure remains a core challenge in the field of computational biology. Existing models frequently encounter significant challenges due to the complexities of diverse topologies and the intricate nature of long-range interactions. We introduce RNAFoldDiff, a generative framework that integrates a sequence-aware graph transformer with a geometric diffusion process for end-to-end RNA 3D structure prediction. RNA sequences and secondary structures are converted into graph representations that capture backbone connectivity and base pair topology. The transformer models local motifs and global dependencies, while the diffusion module iteratively denoises coordinates into physically consistent conformations. The model was pretrained on more than 15,000 structural motifs from the RNA 3D Hub and fine-tuned on complete RNAs from the RNA-Puzzles dataset. In benchmarking tests, RNAFold-Diff achieved an average root mean square deviation (RMSD) of 2.64 Å, a Global Distance Test (GDT) score of 68.7%, and a base pair accuracy of 89.5%, reducing RMSD by nearly 30% and improving GDT by 9 points compared to RoseTTAFoldNA. The framework also outperformed FARFAR2, SimRNA, and RNAformer. Ablation experiments confirmed the contributions of diffusion refinement, edge-aware graph encoding, and motif-level pretraining, while qualitative analyses showed biologically plausible folds including helices, junctions, and multiloops. By combining topology-aware graph learning with generative diffusion, RNAFoldDiff advances RNA tertiary structure modeling and provides a practical tool for RNA design, ribozyme analysis, and structure-guided drug discovery. Full article

Background: While reducing LDL cholesterol (LDL-C) remains central focuses of conventional preventive cardiology, substantial heterogeneity exists in the cardiovascular risk associated with even extreme LDL-C elevations, likely depending heavily on the broader metabolic context. Specifically, the lean mass hyper-responder (LMHR) phenotype—characterized by markedly elevated LDL-C with elevated high-density lipoprotein cholesterol (HDL-C) and low triglycerides in the setting of a ketogenic diet—has recently been described, though its long-term risk profile remains poorly defined. Case Presentation: We describe a male in his 30s without any congenital dyslipidemia who adopted a ketogenic diet for the management of ulcerative colitis and who subsequently exhibited a sixfold increase in LDL-C from a baseline of 95 mg/dL to 574 mg/dL, with total cholesterol of up to 705 mg/dL, HDL-C at 124 mg/dL, and triglycerides at 34 mg/dL. Despite maintaining these extreme lipid levels for nearly seven years, he demonstrated no coronary plaque or stenosis on coronary computed tomography angiography (CCTA; CAD-RADS = 0). Additionally, quantification of coronary plaque as assessed by AI-guided quantified analysis by Heartflow^® identified 0 mm³ plaque in any vessels, placing him in the lowest percentile for atherosclerotic plaque. Conclusions: This case represents an extreme and extensively characterized example of the LMHR phenotype and highlights the limitations of extrapolating cardiovascular risk from LDL-C levels alone without consideration of broader patient context and the etiology of hypercholesterolemia. While a single case cannot redefine clinical practice, this well-characterized case is consistent with emergent literature on LMHR, and careful study of such individuals may provide valuable insights into lipid metabolism, atherosclerosis biology, and precision cardiovascular risk assessment. Full article