The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is a standardized framework designed by the Observational Health Data Sciences and Informatics (OHDSI) community. This open-science community aims to improve the quality of healthcare by providing guidelines for a more harmonized approach to data science.
In a world where our health is paramount, fatty liver disease, known as metabolic dysfunction-associated steatotic liver disease (MASLD), is climbing the ranks of health concerns we can't afford to ignore. Imagine your liver, which controls over 500 vital functions, including the body's detox powerhouse, getting clogged with fat. Alarmingly, about 30% of people globally are wrestling against this silent epidemic. It's a complex disease with various risk factors, especially related to gender and sex hormonal differences, making a one-size-fits-all treatment difficult.
The number of offshore wind farms in the North Sea is exponentially increasing. Their construction responds to the urgent need to transition to green energy production and carbon neutrality. The installation of these man-made structures has a notable impact on the marine ecosystem. Some positive impacts include providing a new home for various animals, and offering shelter, food, and breeding grounds. However, there have been observations of black sediment patches in the sampled sediments near the turbine foundations, suggesting a high input of organic matter into the sediment, altering natural biogeochemical processes.
After several years of dismal market activity, 2024 is already looking up for deals in the pharmaceutical industry, with a recent flurry of billion-dollar mergers and acquisitions. Is this trend being driven by the impending loss of revenue caused by soon-to-expire blockbuster drug patents? And what does it mean for earlier-stage biotech startups?
Personalized healthcare is characterized by tailoring treatments to each individual patient’s needs. Despite evident benefits, implementing such a system is not straightforward. The ATHENA project consortium has successfully devised a set of building blocks to address the challenges associated. Both technological and governance tools were developed that can now be used on a larger scale to catalyze the transition towards personalized medicine and care.
The emergence of artificial intelligence and machine learning accelerates research and innovation across various sectors, particularly in healthcare. The potential for the development of innovative diagnostic tools and therapies based on insights from health data is limitless. However, progress should never compromise the privacy of patients. It’s a delicate balance that is essential to maintain.
Belgium is one of the top countries in the world for in vitro fertilization (IVF). Despite the high cumulative success rates of these interventions, disproportionally little attention has been given to the health of both mother and child during and after pregnancy. With the HEART (High risk for pre-Eclampsia after Assisted Reproductive Technology) project, Belgian researchers strive to understand why some women have an increased risk for pre-eclampsia after IVF and whether biomarkers can be identified to estimate these risks early in pregnancy or even before conception. They aim to raise the standard from successful conception to improved child and maternal health.
While a vast majority of women experience vaginal yeast infections, research has fallen short in providing an effective treatment approach. However, hope has emerged recently with the development of new model systems that allow exploration of the complex vaginal environment. Organ-on-chip models enable researchers to examine the interactions between human cells and microbes in a more accurate manner, offering the potential for the development of new therapies.
STEM has had a long reputation of being a masculine environment, though recent efforts have made this field much more accessible to all genders. Our gender can influence both the external factors and internal methods affecting how we work.
The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is a standardized framework designed by the Observational Health Data Sciences and Informatics (OHDSI) community. This open-science community aims to improve the quality of healthcare by providing guidelines for a more harmonized approach to data science.
In a world where our health is paramount, fatty liver disease, known as metabolic dysfunction-associated steatotic liver disease (MASLD), is climbing the ranks of health concerns we can't afford to ignore. Imagine your liver, which controls over 500 vital functions, including the body's detox powerhouse, getting clogged with fat. Alarmingly, about 30% of people globally are wrestling against this silent epidemic. It's a complex disease with various risk factors, especially related to gender and sex hormonal differences, making a one-size-fits-all treatment difficult.
The number of offshore wind farms in the North Sea is exponentially increasing. Their construction responds to the urgent need to transition to green energy production and carbon neutrality. The installation of these man-made structures has a notable impact on the marine ecosystem. Some positive impacts include providing a new home for various animals, and offering shelter, food, and breeding grounds. However, there have been observations of black sediment patches in the sampled sediments near the turbine foundations, suggesting a high input of organic matter into the sediment, altering natural biogeochemical processes.
After several years of dismal market activity, 2024 is already looking up for deals in the pharmaceutical industry, with a recent flurry of billion-dollar mergers and acquisitions. Is this trend being driven by the impending loss of revenue caused by soon-to-expire blockbuster drug patents? And what does it mean for earlier-stage biotech startups?
Personalized healthcare is characterized by tailoring treatments to each individual patient’s needs. Despite evident benefits, implementing such a system is not straightforward. The ATHENA project consortium has successfully devised a set of building blocks to address the challenges associated. Both technological and governance tools were developed that can now be used on a larger scale to catalyze the transition towards personalized medicine and care.
The emergence of artificial intelligence and machine learning accelerates research and innovation across various sectors, particularly in healthcare. The potential for the development of innovative diagnostic tools and therapies based on insights from health data is limitless. However, progress should never compromise the privacy of patients. It’s a delicate balance that is essential to maintain.
Belgium is one of the top countries in the world for in vitro fertilization (IVF). Despite the high cumulative success rates of these interventions, disproportionally little attention has been given to the health of both mother and child during and after pregnancy. With the HEART (High risk for pre-Eclampsia after Assisted Reproductive Technology) project, Belgian researchers strive to understand why some women have an increased risk for pre-eclampsia after IVF and whether biomarkers can be identified to estimate these risks early in pregnancy or even before conception. They aim to raise the standard from successful conception to improved child and maternal health.
While a vast majority of women experience vaginal yeast infections, research has fallen short in providing an effective treatment approach. However, hope has emerged recently with the development of new model systems that allow exploration of the complex vaginal environment. Organ-on-chip models enable researchers to examine the interactions between human cells and microbes in a more accurate manner, offering the potential for the development of new therapies.
STEM has had a long reputation of being a masculine environment, though recent efforts have made this field much more accessible to all genders. Our gender can influence both the external factors and internal methods affecting how we work.