Ichthyosis refers to a group of skin disorders that lead to dry, itchy skin that appears scaly, rough, and red. Your health care provider may be able to diagnose ichthyosis with a genetic test that detects the mutated gene usually from a blood sample or a swab from the mouth. Find out more:
What is ichthyosis? It is a disorder that causes dry, thickened skin that may look similar to fish scales.
In the largest study of its kind, scientists report how combining health data with whole genome sequence (WGS) data in patients with cancer can help doctors provide more tailored care for their patients.
The research, published in Nature Medicine, shows that linking WGS data to real-world clinical data can identify changes in cancer DNA that may be relevant for an individual patient’s care, for example by helping identify what treatment might work best for them based on their cancer.
The study, led by Genomics England, NHS England, Queen Mary University of London, Guy’s and St Thomas’ NHS Foundation Trust and the University of Westminster, analyzed data covering over 30 types of solid tumors collected from more than 13,000 participants with cancer in the 100,000 Genomes Project. By looking at the genomic data alongside routine clinical data collected from participants over a 5-year period, such as hospital visits and the type of treatment they received, scientists were able to find specific genetic changes in the cancer associated with better or worse survival rates and improved patient outcomes.
An unexpected genetic discovery in wheat has led to opportunities for the metabolic engineering of versatile compounds with the potential to improve its nutritional qualities and resilience to disease.
Researchers in the Osbourn group at the John Innes Centre have been investigating biosynthetic gene clusters in wheat – groups of genes that are co-localized on the genome and work together to produce specific molecules.
NCI researchers have found a persistent decline in rates of both smoking-related and non-smoking-related lung cancer deaths.
In the U.S., lung cancer death rates have declined for decades, primarily due to decreases in cigarette smoking. However, it is unclear whether rates of smoking-unrelated lung cancer deaths are also decreasing. If the rates are increasing, that may suggest increases in exposure to other lung carcinogens that need to be investigated. Meredith Shiels, Ph.D., M.H.S., senior investigator in the Infections and Immunoepidemiology Branch, and colleagues in the Biostatistics Branch, the Division of Cancer Control and Population Sciences, and Information Management Services, conducted a study to estimate trends in U.S. lung cancer death rates from 1991–2018. They found that both smoking-attributable and smoking-unrelated lung cancer death rates declined over this period. The findings were published in the Journal of the National Cancer Institute on December 9, 2023.
Cancer registries and death certificates do not collect the smoking status of every person diagnosed with or who died from lung cancer. Thus, to estimate trends in lung cancer death rates by smoking status, the researchers needed another way to determine the age-specific trends in lung cancer deaths attributed to smoking, and unrelated to smoking. They estimated age-specific annual percentage of lung cancer deaths that could be attributed to smoking using smoking status data from the National Health Interview Survey linked to death certificate data. These population attributable fractions were then multiplied by national data on lung cancer mortality to estimate trends over time in smoking-attributable and smoking-unrelated deaths. The researchers found that the fraction of lung cancer deaths attributable to smoking decreased from 82% in 1991 to 75% in 2018. Over this same period, smoking-attributable lung cancer death rates declined 2.
Posted in biotech/medical, chemistry, health, robotics/AI
Laboratory “copilots” and automated labs are AI’s latest contribution to speeding up the development of new drugs, chemicals and materials. Why it matters: Scientific discovery itself must speed up if the world is to address its challenges — from climate change to personalized treatments for cancer — fast enough to make a difference. In scientific research, “manual effort is not scalable,” writes Microsoft Health Futures’ Hoifung Poon in the…
A new study published in Nature Cell Biology by Mark Alkema, PhD, professor of neurobiology, establishes an important molecular link between specific B12-producing bacteria in the gut of the roundworm C. elegans and the production of acetylcholine, a neurotransmitter important to memory and cognitive function.
There is growing recognition among scientists that diet and gut microbiota may play an important role in brain health. Changes in the composition of the microbiome have been linked to neurological disorders such as anxiety, depression, migraines and neurodegeneration. Yet, teasing out the cause and effect of individual bacteria or nutrients on brain function has been challenging.
“There are more bacteria in your intestine than you have cells in your body,” said Woo Kyu Kang, PhD, a postdoctoral fellow in the Alkema lab and first author of the current study. “The complexity of the brain, the hundreds of bacterial species that comprise the gut microbiome and the diversity of metabolites make it almost impossible to discern how bacteria impact brain function.”
Posted in biotech/medical, health
Diverse gut microbiomes protect against pathogens by blocking nutrient access, according to a new Science study. The findings highlight why microbiome diversity is important to human health.
While dementia is much more common in older adults, hundreds of thousands of people are diagnosed with young-onset dementia (YOD) each year – and an extensive new study sheds some considerable new light on why.
Most previous research in this area has looked at genetics passed down through generations, but here, the team was able to identify 15 different lifestyle and health factors that are associated with YOD risk.
“This is the largest and most robust study of its kind ever conducted,” says epidemiologist David Llewellyn from the University of Exeter in the UK.
YSM researchers are using deeplearning AI models to improve detection of patients at risk for multiple hospitalizations due to asthma and COPD.
Asthma and chronic obstructive pulmonary disease (COPD) are two of the most common lung diseases worldwide, and exacerbation of these conditions can negatively impact health and increase health care costs. A new study shows that deep learning, a type of artificial intelligence (AI) that uses large amounts of data to process information, can improve detection of patients with these diseases who are at increased risk for multiple hospitalizations.
The study was published Dec. 13, 2023, in the journal Respiratory Research.
In the study, researchers identified electronic health record (EHR) characteristics of severe asthma and COPD exacerbations. They then evaluated four machine learning models and one deep learning model in predicting hospital readmissions using EHR data. The researchers found that multilayer perceptron, a deep learning method, had the best performance.
Our smart devices take voice commands from us, check our heartbeats, track our sleep, translate text, send us reminders, capture photos and movies, and let us talk to family and friends continents away.
Now imagine turbocharging those capabilities. Holding in-depth, natural language exchanges on academic or personal queries; running our vital signs through a global database to check on imminent health issues; packing massive databases to provide comprehensive real-time translation among two or more parties speaking different languages; and conversing with GPS software providing details on the best burgers, movies, hotels or people-watching spots trending along your route.
Tapping into the seductive power of large language models and natural language processing, we’ve witnessed tremendous progress in communications between us and technology that we increasingly rely on in our daily lives.