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“We show that focusing on genes whose expression patterns are evolutionarily conserved across species enhances our ability to learn and predict ‘genes of importance’ to growth performance for staple crops, as well as disease outcomes in animals,” explained Gloria Coruzzi, Carroll & Milton Petrie Professor in NYU’s Department of Biology and Center for Genomics and Systems Biology and the paper’s senior author.


Machine learning can pinpoint “genes of importance” that help crops to grow with less fertilizer, according to a new study published in Nature Communications. It can also predict additional traits in plants and disease outcomes in animals, illustrating its applications beyond agriculture.

Using to predict outcomes in agriculture and medicine is both a promise and challenge for . Researchers have been working to determine how to best use the vast amount of genomic data available to predict how organisms respond to changes in nutrition, toxins, and pathogen exposure—which in turn would inform crop improvement, disease prognosis, epidemiology, and public health. However, accurately predicting such complex outcomes in agriculture and medicine from genome-scale information remains a significant challenge.

In the Nature Communications study, NYU researchers and collaborators in the U.S. and Taiwan tackled this challenge using machine learning, a type of artificial intelligence used to detect patterns in data.

Circa 2018


Researchers at the University of Michigan just created the world’s smallest computer (again). Their previous micro-computer, the Michigan Micro Mote, measured 2x2x4mm. It was a complete, functioning system powered by solar cell batteries. But in March this year, IBM announced a new, smaller computer, which measured 1×1 mm, and was smaller than a grain of salt. It “raised a few eyebrows at the University of Michigan.”

After all, it’s unclear if the IBM computer even count as an actual microcomputer. The IBM device lost all its programming and data as soon as it turns off, unlike the Michigan Micro Mote, which retained its programming even when it wasn’t externally powered. “It’s more of a matter of opinion whether they have the minimum functionality required,” said David Blaauw, a professor of electrical and computer engineering at University of Michigan who helped develop the University of Michigan’s newest tiny device. If the IBM machine constituted a computer, then University of Michigan would work to gain back their title: their latest microdevice measures 0.3mm per side (1/10th the size of IBM’s computer), and is smaller than a grain of rice.

The device was designed to be a precision temperature sensor that can report temperatures in clusters of cells with an error of about 0.1 degrees Celsius. “When we first made our millimeter system, we actually didn’t know exactly all the things it would be useful for. But once we published it, we started receiving dozens and dozens and dozens of inquiries,” Blaauw said. It could, for instance, measure the temperature of tumors and conduct other cancer studies, monitor oil reservoirs, conduct audio or visual surveillance, or help in “tiny snail studies.”

Know Labs’ glucose monitors are both powered by its Body-Radio Frequency Identification, or Bio-RFID, technology. The Bio-RFID sensors emit radio waves to measure specific molecular signatures in the blood through the skin, calculated using spectroscopy.

“We know that not all people with diabetes are looking for a wearable continuous glucose monitoring device to manage their diabetes. Some simply want to replace the painful, inconvenient and expensive fingersticks they currently rely on,” said CEO Phil Bosua, who invented the Bio-RFID technology. “The Bio-RFID sensor we currently use for our internal product testing fits in your pocket and is ready for final use, so we decided to create the KnowU as a portable, affordable and convenient alternative requiring no disposable items, such as test strips and lancets.”

In vitro tests have found that the radiofrequency sensor technology was able to measure glucose levels with accuracy comparable to that of Abbott’s Freestyle Libre continuous glucose monitor, which uses a sensor attached to the back of the arm for up to two weeks at a time. According to a 2018 study (PDF) comparing the two, 97% of the UBand’s readings were within 15% of the values calculated by Abbott’s device.

Dowsett’s algorithm was recently published in npj Breast Cancer, a Nature Partner Journal supported by the Breast Cancer Research Foundation. It is intended to help physicians triage postmenopausal women with ER+ HER2–breast cancers, which represent around 70% of breast cancer cases.1 During the pandemic, many within this patient group were prescribed neoadjuvant endocrine therapy (NeoET), rather than surgery, as a disease management strategy.


Analysis of biomarkers in biopsies helps identify breast cancer patients in need of urgent surgery or chemotherapy during COVID-19 pandemic.

Summary: Mouse study reveals chronic stress affects neurogenesis in the dentate gyrus.

Source: Tokyo University of Science.

Depression is a serious medical condition that plagues modern society. Several theories have been proposed to explain the physiological basis of depression, of which the “neurogenic hypothesis of depression” has garnered much attention.

Back in 2,014 the World Health Organization (WHO) warned that within a decade, antibiotic-resistant bacteria could make routine surgery, organ transplantation, and cancer treatment life-threateningly risky — and spell the end of modern medicine as we know it.

Antibiotics are a cornerstone of modern medicine, used to treat infections and to protect vulnerable patients undergoing surgery or chemotherapy. The world desperately needs new antibiotics, and Covid-19 has only exacerbated the problem.

In our search for new antibiotics, we have focused on fungi, especially those found only in Aotearoa New Zealand. Our latest research describes the discovery of fungal compounds able to kill Mycobacteria, a family of slow-growing bacteria that includes another important global airborne killer — Mycobacterium tuberculosis — which causes the lung disease tuberculosis and kills thousands of people around the world each day.