A team of scientists is using the tools offered by the HBP’s digital research infrastructure EBRAINS to address one of the oldest enigmas in neuroscience: the dichotomy of brain structure and function.
Every human brain is different. But even with structural differences, individual brains function in a similar way. In other words, there are functional brains based on completely different configurations. At the same time, a structural change may cause loss of function in one brain, but have no consequences in another individual. Or a drug cocktail may be efficient for one patient, and have no effects for another.
A new model can accurately predict the height of waves created when a cliff collapses into water, allowing for a better evaluation of the threat the incident may pose to local people.
Cancer is one of the major global public health problems and is caused by abnormal cell proliferation. A plant immune protein has recently been found to enable widespread anti-tumor responses by alleviating micro-RNA
In recent years, engineers and computer scientists have created a wide range of technological tools that can enhance fitness training experiences, including smart watches, fitness trackers, sweat-resistant earphones or headphones, smart home gym equipment and smartphone applications. New state-of-the-art computational models, particularly deep learning algorithms, have the potential to improve these tools further, so that they can better meet the needs of individual users.
Researchers at University of Brescia in Italy have recently developed a computer vision system for a smart mirror that could improve the effectiveness of fitness training both in home and gym environments. This system, introduced in a paper published by the International Society of Biomechanics in Sports, is based on a deep learning algorithm trained to recognize human gestures in video recordings.
“Our commercial partner ABHorizon invented the concept of a product that can guide and teach you during your personal fitness training,” Bernardo Lanza, one of the researchers who carried out the study, told TechXplore. “This device can show you the best way to train based on your specific needs. To develop this device further, they asked us to investigate the viability of an integrated vision system for exercise evaluation.”
The study population comprised 6,245,282 older adults (age ≥65 years) who had medical encounters with healthcare organizations between 2/2/2020–5/30/2021 and had no prior diagnosis of Alzheimer’s disease. The population was divided into two cohorts: 1) COVID-19 cohort (n = 410,748)— contracted COVID-19 between 2/2/2020–5/30/2021; 2) non-COVID-19 cohort (n = 5,834,534)— had no documented COVID-19 but had medical encounters with healthcare organizations between 2/2/2020–5/30/2021. The status of Alzheimer’s disease and COVID-19 were based on the International Classification of Diseases (ICD-10) diagnosis codes and laboratory tests (details in the Supplementary Material).
We examined risks for new diagnosis of Alzheimer’s disease in COVID-19 and non-COVID-19 cohorts in all older adults, three age groups (65–74, 75–84, ≥85), and three racial/ethnic groups (Black, White, and Hispanic). Cohorts were propensity-score matched (1:1 using a nearest neighbor greedy matching) for demographics, adverse socioeconomical determinants of health including problems with education, occupational exposure, physical, social and psychosocial environment, and known risk factors for Alzheimer’s disease [13] (details in the Supplementary Material). Kaplan-Meier analysis was used to estimate the probability of new diagnosis of Alzheimer’s disease within 360 days after the COVID-19 diagnosis. Cox’s proportional hazards model was used to compare matched cohorts using hazard ratios and 95% confidence intervals. All statistical tests were conducted within the TriNetX Advanced Analytics Platform at significance set at p < 0.05 (2-sided).
How can mobile robots perceive and understand the environment correctly, even if parts of the environment are occluded by other objects? This is a key question that must be solved for self-driving vehicles to safely navigate in large crowded cities. While humans can imagine complete physical structures of objects even when they are partially occluded, existing artificial intelligence (AI) algorithms that enable robots and self-driving vehicles to perceive their environment do not have this capability.
Robots with AI can already find their way around and navigate on their own once they have learned what their environment looks like. However, perceiving the entire structure of objects when they are partially hidden, such as people in crowds or vehicles in traffic jams, has been a significant challenge. A major step towards solving this problem has now been taken by Freiburg robotics researchers Prof. Dr. Abhinav Valada and Ph.D. student Rohit Mohan from the Robot Learning Lab at the University of Freiburg, which they have presented in two joint publications.
The two Freiburg scientists have developed the amodal panoptic segmentation task and demonstrated its feasibility using novel AI approaches. Until now, self-driving vehicles have used panoptic segmentation to understand their surroundings.
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U.S. regulators have approved a new purple tomato, genetically engineered to be packed with antioxidants and anthocyanins. The fruit will go on sale in 2023.
Tumor cells are notoriously good at evading the human immune system; they put up physical walls, wear disguises and handcuff the immune system with molecular tricks. Now, UC San Francisco researchers have developed a drug that overcomes some of these barriers, marking cancer cells for destruction by the immune system.
The new therapy, described in Cancer Cell, pulls a mutated version of the protein KRAS to the surface of cancer cells, where the drug-KRAS complex acts as an “eat me” flag. Then, an immunotherapy can coax the immune system to effectively eliminate all cells bearing this flag.
“The immune system already has the potential to recognize mutated KRAS, but it usually can’t find it very well. When we put this marker on the protein, it becomes much easier for the immune system,” said UCSF chemist and Howard Hughes Medical Institute Investigator Kevan Shokat, Ph.D., who also helped lead the new work.
