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Category: bioengineering – Page 8

A team of researchers at the George R. Brown School of Engineering and Computing at Rice University has developed an innovative artificial intelligence (AI)-enabled, low-cost device that will make flow cytometry—a technique used to analyze cells or particles in a fluid using a laser beam—affordable and accessible.

The prototype identifies and counts cells from unpurified blood samples with similar accuracy as the more expensive and bulky conventional flow cytometers, provides results within minutes and is significantly cheaper and compact, making it highly attractive for point-of-care clinical applications, particularly in low-resource and rural areas.

Peter Lillehoj, the Leonard and Mary Elizabeth Shankle Associate Professor of Bioengineering, and Kevin McHugh, assistant professor of bioengineering and chemistry, led the development of this new device. The study was published in Microsystems & Nanoengineering.

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A platform developed nearly 20 years ago previously used to detect protein interactions with DNA and conduct accurate COVID-19 testing has been repurposed to create a highly sensitive water contamination detection tool.

The technology merges two exciting fields— and nanotechnology—to create a new platform for chemical monitoring. When tuned to detect different contaminants, the technology could detect the metals lead and cadmium at concentrations down to two and one parts per billion, respectively, in a matter of minutes.

The paper was published this week in the journal ACS Nano and represents research from multiple disciplines within Northwestern’s McCormick School of Engineering.

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A new algorithm, Evo 2, trained on roughly 128,000 genomes—9.3 trillion DNA letter pairs—spanning all of life’s domains, is now the largest generative AI model for biology to date. Built by scientists at the Arc Institute, Stanford University, and Nvidia, Evo 2 can write whole chromosomes and small genomes from scratch.

It also learned how DNA mutations affect proteins, RNA, and overall health, shining light on “non-coding” regions, in particular. These mysterious sections of DNA don’t make proteins but often control gene activity and are linked to diseases.

The team has released Evo 2’s software code and model parameters to the scientific community for further exploration. Researchers can also access the tool through a user-friendly web interface. With Evo 2 as a foundation, scientists may develop more specific AI models. These could predict how mutations affect a protein’s function, how genes operate differently across cell types, or even help researchers design new genomes for synthetic biology.

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It is unclear if this is an autonomous robot, but I want one.🤖

NEO Gamma is the next generation of home humanoids designed and engineered by 1X Technologies. The Gamma series includes improvements across NEO’s hardware and AI, featuring a new design that is deeply considerate of life at home. The future of Home Humanoids is here.

Website: www.1x.tech.
X: https://twitter.com/1x_tech.
LinkedIn: / 1x-technologies.
Instagram: / 1x.technologies

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Microbes, Ecology And Medicine — Dr. Sean M. Gibbons, Ph.D. — Associate Professor, Institute for Systems Biology (ISB)

Dr. Sean Gibbons, Ph.D. is Associate Professor at the Institute for Systems Biology (ISB — https://isbscience.org/people/sean-gibbons-phd/?tab=biography where his lab investigates how the structure and composition of evolving ecological networks of microorganisms change across environmental gradients, with a specific focus on how ecological communities in the gut change and adapt to individual people over their lifespans (i.e. host genotype, host development and host behavior) and how these changes impact human health (https://gibbons.isbscience.org/). His lab develops computational and experimental tools for investigating host-associated microbial communities to explore the interactions between ecology, evolution and ecosystem function, applying these insights to develop personalized interventions for improving human health and well-being.

Dr. Gibbons received his PhD in biophysical sciences from the University of Chicago in 2015, dual-advised by Jack Gilbert and Maureen Coleman. His graduate work focused on using microbial communities as empirical models for testing ecological theory.

Dr. Gibbons completed his postdoctoral training in Eric Alm’s laboratory in the Department of Biological Engineering at MIT from 2015–2018. His postdoctoral work focused on developing techniques to quantify individual-specific eco-evolutionary dynamics within the human gut microbiome.

Dr. Gibbons was awarded a Fulbright Graduate Fellowship to study microbiology and synthetic biology at Uppsala University in Sweden, where he earned a master’s degree in 2010. His PhD work was supported by an EPA STAR Graduate Fellowship. Upon joining the ISB faculty in 2018, his startup package was supported, in part, by a Washington Research Foundation Distinguished Investigator Award.

Continue reading “Dr. Sean Gibbons, Ph.D. — Institute for Systems Biology (ISB) — Microbes, Ecology And Medicine” | >

You can learn a lot from a little slime mold. For Nate Cira, assistant professor of biomedical engineering in Cornell Engineering, the tiny eukaryotic organism provided inspiration for modeling “traveling networks”—connected systems that move by rearranging their structure.

Understanding these networks could help explain the structures and movements of certain biological systems and human organizations, from protein units that reassemble themselves to corporations expanding their product lines.

The findings were published Feb. 26 in Nature Communications.

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Working in the field of genetics is a bizarre experience. No one seems to be interested in the most interesting applications of their research.

We’ve spent the better part of the last two decades unravelling exactly how the human genome works and which specific letter changes in our DNA affect things like diabetes risk or college graduation rates. Our knowledge has advanced to the point where, if we had a safe and reliable means of modifying genes in embryos, we could literally create superbabies. Children that would live multiple decades longer than their non-engineered peers, have the raw intellectual horsepower to do Nobel prize worthy scientific research, and very rarely suffer from depression or other mental health disorders.

The scientific establishment, however, seems to not have gotten the memo. If you suggest we engineer the genes of future generations to make their lives better, they will often make some frightened noises, mention “ethical issues” without ever clarifying what they mean, or abruptly change the subject. It’s as if humanity invented electricity and decided the only interesting thing to do with it was make washing machines.

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Then came gene targeting technologies, like CRISPR, over 10 years ago. With these technologies we can delete, modify, add, or change any gene in any organism’s DNA and it’s easy and cheap. Are you thinking what I’m thinking? Where are my Pokémon?

The scientific industrial complex is fundamentally broken. Scientists are trapped in a system of their own creation that values paywalled publications over real progress. If they can’t even make knowledge freely available, how can they be expected to push the boundaries of innovation? A field built on gatekeeping will never lead the future.

The real question isn’t whether we can do this. The real question is what comes next. The first steps are already happening in the lab of my new company, the Los Angeles Project (LAP). We are learning to harvest large amounts of embryos and eggs from different animal species so we can understand the development of life on a scale no one has tried before. We are editing genes and injecting DNA with micro-precision, sculpting biology at its most fundamental level.

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Unlock the full potential of CRISPR technology while ensuring precision and safety! In this video, we dive deep into the science of CRISPR gene editing, explore the challenges of off-target effects, and reveal cutting-edge strategies to minimize risks.
📌 Key Topics Covered:

1️⃣ What is CRISPR?

Discover the origins of CRISPR-Cas9, its revolutionary impact on genetics, agriculture, and medicine, and the latest advancements like base editing and AI-driven optimization.
2️⃣ Understanding Off-Target Effects.

Learn why unintended DNA modifications occur, how gRNA promiscuity and nuclease activity contribute to risks, and proven mitigation strategies (e.g., HiFi Cas9, dual gRNA systems).
3️⃣ Off-Target Prediction & Detection.

Explore bioinformatics tools (e.g., CRISOT) and advanced detection methods like Whole Genome Sequencing (WGS), LAM-HTGTS, and Digenome-seq for unbiased, high-sensitivity analysis.
4️⃣ Validation & Solutions.

See how CD Genomics’ off-target validation service combines multiplex PCR, Illumina sequencing, and cloud-based analytics to deliver publication-ready results with unmatched accuracy.

Continue reading “Genome Editing with CRISPR: How to Effectively Minimize Off-Target Effects” | >