December 12th, 2025 10:00 EST
https://www.bocsci.com/delivery-nanocarriers-to-desirable-vascular-destinations-fortuitous-tropism-vs-cognizant-targeting.html
Free registration

In this session, Dr. Vladimir Muzykantov will present an in-depth analysis of the current advances and challenges in drug targeting, biomaterials, nanomedicine, drug delivery systems (DDS), intracellular delivery, and biotherapeutics (Bios).

HIGHLIGHTS

Biotherapeutics (Bios) as a new pharmacological class: Discussion of their catalytic precision, biological potency, and delivery challenges within systemic circulation.

Delivery challenges and bottlenecks: Exploration of nanoscale targeting requirements, intracellular addressing (cytosol vs nucleus), and barriers to effective biodistribution and clearance.

Cognizant vs. Fortuitous Targeting Approaches: Comparison of rational ligand-based targeting versus chance discoveries ("fortuitous homing"), including advantages, limitations, and potential synergies.

Mechanistic understanding through DDS design: How tracing, modeling, and controlled modification of nanocarriers advance rational design for vascular delivery.

Re-engineering Fortuitous Nanocarriers: Strategies to transform serendipitous findings into predictable and tunable delivery platforms through modulation of carrier configuration, size, shape, and biological context.

Translational impact – Vascular Nanomedicine: Case studies where endothelial-targeted antioxidants, antithrombotics, and anti-inflammatory agents outperform untargeted drugs in animal models of lung injury, ischemia-reperfusion, and sepsis.

The legacy of James Dewey Watson (April 6, 1928 – November 6, 2025) begins with the discovery that transformed all of biology: the double-helical structure of DNA. By helping reveal the molecular architecture of heredity, he set in motion the conceptual framework that now supports modern genomics and the field of bioinformatics.

His influence on bioinformatics grew most clearly through his early leadership of the Human Genome Project, a visionary effort that required new computational approaches for sequencing, assembling, and analyzing vast quantities of biological data. Watson encouraged open data access, high-throughput sequencing technologies, and international cooperation, and this support accelerated the rise of computational genomics.

Watson was also a strong advocate for personalized medicine, believing that understanding an individual's genome could transform healthcare. In a demonstration of this vision, he became the second person ever to have his entire genome sequenced, showing the power and promise of genomic information for guiding medical decisions.

His life's work reshaped biological inquiry, data generation, and scientific communication. The field of bioinformatics stands as a central element of modern life science in part because Watson helped bring the genome and its computational interpretation to the center of biological research.

Researchers cultured 250+ gut bacteria and found 134 "hidden" phages that could be awakened. Most stayed silent in the lab until exposed to human gut cells or complex bacterial communities.

That means phage activity depends on both the microbiome and the human host. Some phages have even lost the genes needed to reactivate, becoming permanent passengers.

This study gives us a powerful resource of real, testable phage-host pairs and shows that phages are active players shaping our gut ecosystem.

ARTICLE

Dahlman, Samuel, Tom O. Delmont, Alejandro Reyes, Anna L. Mallott, and Emily B. Hollister, et al. "Isolation, Engineering and Ecology of Temperate Phages from the Human Gut." Nature 638 (2025): 145-152. https://doi.org/10.1038/s41586-025-09614-7.

A large UK study has shown that analyzing the entire genetic code of breast tumors can reveal important information about how the disease develops and how patients might respond to treatment. Researchers found that whole-genome sequencing can identify DNA changes linked to survival outcomes and uncover treatment options that standard genetic tests may miss. The findings suggest that using full-genome data could help doctors better match therapies to individual patients and avoid unnecessary treatments in the future.

ARTICLE

Turnbull, Clare, Helen Davies, Peter Van Loo, Serena Nik-Zainal, and colleagues. "Clinical Potential of Whole-Genome Data Linked to Mortality Statistics in Patients with Breast Cancer in the UK: A Retrospective Analysis." The Lancet Oncology (2025). https://doi.org/10.1016/S1470-2045(25)00400-0

Scientists have created a new way to measure how quickly a person's body is aging by analyzing two kinds of blood data with artificial intelligence. The method, called gtAge, uses information from the sugars attached to antibodies and from gene activity in blood cells. By combining these data with deep reinforcement learning, the researchers built a model that predicts biological age more accurately than traditional approaches. They say it could one day help track how lifestyle or medical treatments slow aging and reduce disease risk.

ARTICLE

Xia, Yao, Syed Mohammed Shamsul Islam, Xingang Li, Abdul Baten, Xuerui Tan, and Wei Wang. "Deep Reinforcement Learning – Driven Multi-Omics Integration for Constructing gtAge: A Novel Aging Clock from IgG N-glycome and Blood Transcriptome." Engineering (2025). https://doi.org/10.1016/j.eng.2025.08.016.

Researchers have developed a powerful new system called MetaGraph that allows scientists to search through enormous DNA and RNA databases containing more than a quadrillion genetic letters. The tool can rapidly find genetic sequences across global repositories such as the Sequence Read Archive, making it possible to uncover links between genes, microbes, and diseases that were previously hidden within petabytes of raw data.

ARTICLE

Karasikov, Mikhail, Harun Mustafa, Daniel Danciu, Oleksandr Kulkov, Marc Zimmermann, Christopher Barber, Gunnar Rätsch, and André Kahles. "Efficient and Accurate Search in Petabase-Scale Sequence Repositories." Nature (October 8, 2025). https://doi.org/10.1038/s41586-025-09603-w.

Frontiers, an open-science publisher, has launched FAIR² Data Management, an AI-powered service designed to address the fact that approximately 90% of scientific data never gets reused to drive new discoveries. The platform automates data curation, compliance checking, and formatting – tasks that previously took months – to make research datasets properly preserved, citable, and reusable by both humans and AI systems. Out of every 100 datasets created, about 80 remain in labs and only one typically leads to new findings, a bottleneck that delays advances in fields like cancer treatment and climate research. The service has completed pilot projects spanning COVID variants, brain injury research, climate indicators, and biodiversity, with researchers noting that it could accelerate scientific progress while ensuring data creators receive proper credit for their work.

Source: https://www.frontiersin.org/news/2025/10/13/90-of-science-is-lost-frontiers-revolutionary-ai-powered-service-transforms

A new method called SDR-seq – short for single-cell DNA-RNA sequencing – enables researchers to measure DNA mutations and gene activity within the same cell, offering a direct view of how genetic variation shapes cell function. The approach improves on previous multi-omic techniques, which often suffered from data loss and could not reliably connect genotype to transcriptomic effects at single-cell resolution. By reducing allelic dropout and scaling to hundreds of genomic targets, SDR-seq provides more accurate and comprehensive insights, demonstrating its effectiveness in both laboratory models and primary tumour samples.

ARTICLE

Lindenhofer, Dominik, Christian E. Saliba, René Schmutz, et al. "Functional Phenotyping of Genomic Variants Using Joint Multiomic Single-Cell DNA-RNA Sequencing." Nature Methods (2025). https://doi.org/10.1038/s41592-025-02805-0.

A large-scale genomic study of more than 218,000 participants in Geisinger's MyCode Community Health Initiative has revealed that rare genetic disorders (RGDs) may be more common and less clinically recognised than previously thought. Researchers found that 2.5% of participants carried high-confidence pathogenic variants linked to RGDs, yet only about one in five of those who were positive had corresponding clinical diagnoses. The findings suggest that genomic-first approaches could identify many undiagnosed cases, refine estimates of disease penetrance, and improve early diagnosis and management of RGDs.

ARTICLE

Torene, Rebecca I., et al. "A Scalable Approach for Genomic-First Rare Disorder Detection in a Healthcare-Based Population." The American Journal of Human Genetics, published online October 6, 2025. https://doi.org/10.1016/j.ajhg.2025.09.010. [not open-access]

Researchers analyzed ancient microbial DNA from 483 mammoth specimens, including 440 newly sequenced samples dating back up to 1.1 million years, and identified six microbial clades likely associated with living mammoths – spanning Actinobacillus, Pasteurella, Streptococcus, and Erysipelothrix. They reconstructed partial genomes of Erysipelothrix from the oldest specimen – representing the oldest authenticated host-associated microbial DNA known to date – and also found putative virulence factors in some lineages, including a Pasteurella relative linked to disease in modern elephants.

ARTICLE

Guinet, Benjamin, et al. "Ancient Host-Associated Microbes Obtained from Mammoth Remains." Cell (2025). https://doi.org/10.1016/j.cell.2025.08.003.