
Molecular Cell, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Molecular Cell, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Cell, Год журнала: 2024, Номер 187(3), С. 545 - 562
Опубликована: Фев. 1, 2024
Determining the structure and mechanisms of all individual functional modules cells at high molecular detail has often been seen as equal to understanding how work. Recent technical advances have led a flush high-resolution structures various macromolecular machines, but despite this wealth detailed information, our cellular function remains incomplete. Here, we discuss present-day limitations structural biology highlight novel technologies that may enable us analyze functions directly inside cells. We predict progression toward cell will involve shift conceptualizing 4D virtual reality using digital twins. These capture segments in highly enriched detail, include dynamic changes, facilitate simulations processes, leading experimentally testable predictions. Transferring biological questions into algorithms learn from existing data explore solutions ultimately unveil
Язык: Английский
Процитировано
22Cancer Cell, Год журнала: 2024, Номер 42(9), С. 1497 - 1506
Опубликована: Авг. 29, 2024
Язык: Английский
Процитировано
20Computational and Structural Biotechnology Journal, Год журнала: 2025, Номер 27, С. 265 - 277
Опубликована: Янв. 1, 2025
Despite the wealth of single-cell multi-omics data, it remains challenging to predict consequences novel genetic and chemical perturbations in human body. It requires knowledge molecular interactions at all biological levels, encompassing disease models humans. Current machine learning methods primarily establish statistical correlations between genotypes phenotypes but struggle identify physiologically significant causal factors, limiting their predictive power. Key challenges modeling include scarcity labeled generalization across different domains, disentangling causation from correlation. In light recent advances data integration, we propose a new artificial intelligence (AI)-powered biology-inspired multi-scale framework tackle these issues. This will integrate organism hierarchies, species genotype-environment-phenotype relationships under various conditions. AI inspired by biology may targets, biomarkers, pharmaceutical agents, personalized medicines for presently unmet medical needs.
Язык: Английский
Процитировано
8Frontiers in Immunology, Год журнала: 2025, Номер 15
Опубликована: Янв. 7, 2025
Gastric cancer is a common malignant tumor of the digestive tract, and its treatment remains significant challenge. In recent years, role various immune cells in microenvironment progression has gained increasing attention. Immunotherapy, primarily based on checkpoint inhibitors, notably improved prognosis patients with gastric cancer; however, challenges regarding therapeutic efficacy persist. Histological features within microenvironment, such as tertiary lymphoid structures (TLSs), tumor-infiltrating lymphocytes, proportion intratumoral stroma, are emerging potentially effective prognostic factors. cancer, TLSs may serve local hubs, enhancing ability to interact recognize antigens, which closely linked effectiveness immunotherapy survival rates patients. However, specific cell type driving TLS formation tumors not yet been elucidated. Mature B-cell regions containing germinal centers. During center formation, B undergo transformations become mature function, exerting anti-tumor effects. Therefore, targeting could provide new avenues for immunotherapy. This review, combined current research elaborates relationship between aiming guidance precise
Язык: Английский
Процитировано
5Cellular and Molecular Life Sciences, Год журнала: 2023, Номер 80(11)
Опубликована: Окт. 5, 2023
Язык: Английский
Процитировано
28Biomolecules, Год журнала: 2024, Номер 14(6), С. 692 - 692
Опубликована: Июнь 14, 2024
As an essential component of modern drug discovery, the role drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in process discovering targets. However, it difficult for any level to clearly expound causal connection between drugs and how they give rise emergence complex phenotypes. With progress large-scale sequencing development high-throughput technologies, tendency has shifted towards integrated multi-omics techniques, gradually replacing traditional techniques. Herein, this review centers on recent advancements domain techniques target identification, highlights common analysis strategies, briefly summarizes selection tools, explores challenges existing analyses, as well applications technology identification.
Язык: Английский
Процитировано
18The Plant Journal, Год журнала: 2024, Номер 119(5), С. 2168 - 2180
Опубликована: Июль 11, 2024
SUMMARY Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability characterize complex chemical, spatial, and temporal aspects of metabolism. Over the past decade, as emerging unique features various MSI techniques have continued support new discoveries studies metabolism closely associated with function physiology, spatial metabolomics based on positioned it at forefront metabolic studies, providing opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges levels resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, multi‐omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview emergent widely used sciences, particular emphasis recent advances methodological breakthroughs. Having established detailed context MSI, outline both golden opportunities key currently facing metabolomics, presenting our vision how enormous potential technologies will contribute progress coming years.
Язык: Английский
Процитировано
15Current Biology, Год журнала: 2024, Номер 34(6), С. 1206 - 1221.e6
Опубликована: Фев. 5, 2024
The physiological performance of any sensory organ is determined by its anatomy and physical properties. Consequently, complex structures with elaborate features have evolved to optimize stimulus detection. Understanding these their nature forms the basis for mechanistic insights into function. Despite crucial role as a sensor pheromones other behaviorally instructive chemical cues, vomeronasal (VNO) remains poorly characterized mammalian structure. Fundamental principles physico-mechanical function, including basic aspects sampling, remain explored. Here, we revisit classical vasomotor pump hypothesis uptake. Using advanced anatomical, histological, methods, demonstrate that large parts lateral mouse VNO are composed smooth muscle. Vomeronasal muscle tissue comprises two subsets fibers distinct topography, structure, excitation-contraction coupling, and, ultimately, contractile Specifically, contractions population noradrenaline-sensitive cells mediate both transverse longitudinal lumen expansion, whereas cholinergic stimulation targets an adluminal group fibers. latter run parallel VNO's rostro-caudal axis ideally situated antagonistic constriction lumen. This newly discovered arrangement implies novel mode Single-cell transcriptomics pharmacological profiling reveal receptor subtypes involved. Finally, 2D/3D tomography provides non-invasive insight intact mechanics, enables measurement luminal fluid volume, allows assessment relative volume change upon noradrenergic stimulation. Together, propose revised conceptual framework pumping thus, sampling.
Язык: Английский
Процитировано
14npj Imaging, Год журнала: 2024, Номер 2(1)
Опубликована: Март 1, 2024
Abstract Multimodal bioimaging is a broad term used to describe experimental workflows that employ two or more different imaging modalities. Such approaches have been in use across life science domains for several years but these remain relatively limited scope, part due the complexity of undertaking types analysis. Expanding encompass diverse, emerging technology holds potential revolutionize our understanding spatial biology. In this perspective we reflect on instrument and current use, areas consider experience barriers broader adoption progress. We propose enabling solutions challenge areas, opportunities consideration highlight some key community activities help move field forward.
Язык: Английский
Процитировано
13Journal of Personalized Medicine, Год журнала: 2024, Номер 14(9), С. 931 - 931
Опубликована: Авг. 31, 2024
Aging is a fundamental biological process characterized by progressive decline in physiological functions and an increased susceptibility to diseases. Understanding aging at the molecular level crucial for developing interventions that could delay or reverse its effects. This review explores integration of machine learning (ML) with multi-omics technologies-including genomics, transcriptomics, epigenomics, proteomics, metabolomics-in studying hallmarks develop personalized medicine interventions. These include genomic instability, telomere attrition, epigenetic alterations, loss proteostasis, disabled macroautophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, dysbiosis. Using ML analyze big complex datasets helps uncover detailed interactions pathways play role aging. The advances can facilitate discovery biomarkers therapeutic targets, offering insights into anti-aging strategies. With these developments, future points toward better understanding process, aiming ultimately promote healthy extend life expectancy.
Язык: Английский
Процитировано
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