Toggle light / dark theme

Deep model predictive control of gene expression in thousands of single cells

Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. Here the authors train a deep neural network to predict and dynamically control gene expression in thousands of individual bacteria in real-time which they then apply to control antibiotic resistance and study single-cell survival dynamics.

CRISPR Gene Drives and the Future of Evolution

Immunizing enormous numbers of wild mice, however, is prohibitively difficult. By using genetic engineering, researchers could create white-footed mice that produced these antibodies from birth and could pass this ability on to their offspring. But did the island residents want to live with genetically engineered mice?

The answer was perhaps, but with caveats. In consulting with communities on this technology development, researchers found that community members preferred a cisgenic approach: They wanted white-footed mice that were engineered with DNA only from other white-footed mice.18 This would make the project more difficult for the researchers, and meant that a CRISPR-based gene drive, even one with limited spread, could not be used, since no white-footed mouse naturally has this gene-editing system. However, said Esvelt, “It’s their environment, so it’s their call.”

“We’re potentially causing an irreversible change to the environment,” said Telford. “We need to think about informed consent of the community as a proxy for informed consent of the environment. That’s been a real advance and something [that Esvelt] has pioneered—involving the communities from the very start.”

The wild race to improve synthetic embryos

“We need a defined framework, but instead what we see here is a fairly wild race between labs,” one journal editor told me during the ISSCR meeting. “The overarching question is: How far do they go, and where do we place them in a legal-moral spectrum? How can we endorse working with these models when they are much further along than we were two years ago?”

So where will the race lead? Most scientists say the point of mimicking the embryo is to study it during the period when it would be implanting in the wall of the uterus. In humans, this moment is rarely observed. But stem-cell embryos could let scientists dissect these moments in detail.

Yet it’s also possible that these lab embryos turn out to be the real thing—so real that if they were ever transplanted into a person’s womb, they could develop into a baby.

Metformin slows colorectal cancer growth using microRNAs, study finds

This study provides new insights into metformin’s effect on the molecular mechanisms inside cells and why it reduces proliferation of cancer cells, emphasising the role of miRNAs in colorectal cancer.

The authors suggest their findings highlight the potential for developing RNA therapeutics for cancer prevention and treatment and possibly for targeted interventions. Although there are several challenges in the field of miRNA therapeutics, this study could signal another step in their development as potential cancer treatments.

AI Models Aid in Predicting Lung Cancer Risk

Colin Jacobs, PhD, assistant professor in the Department of Medical Imaging at Radboud University Medical Center in Nijmegen, The Netherlands, and Kiran Vaidhya Venkadesh, a second-year PhD candidate with the Diagnostic Image Analysis Group at Radboud University Medical Center discuss their 2021 Radiology study, which used CT images from the National Lung Cancer Screening Trial (NLST) to train a deep learning algorithm to estimate the malignancy risk of lung nodules.

New DNA sequencing technique detects early genetic mutations

HiDEF-seq advances cancer treatment:


HiDEF-seq technique could further help develop or advance new prevention approaches or develop treatments for genetic diseases and even cancer.

Gilad Evrony, senior study author and a core member of the Center for Human Genetics & Genomics at NYU Grossman School of Medicine told Science Direct:

“Our new HiDEF-seq sequencing technique allows us to see the earliest fingerprints of molecular changes in DNA when the changes are only in single strands of DNA.”