Lifeboat Foundation

Sepsis is a condition in which the body responds improperly. More specifically, the infection causes the organs in the body to shut down. This is a serious illness which could lead to extremely low blood pressure or septic shock. In this case, permanent damage to the lungs, kidneys, liver, and other organs can occur. Unfortunately, if the damage is extensive enough, it could be fatal. Common symptoms associated with sepsis includes alteration of mental status, shallow breathing, sweating out of context, lightheadedness, chills, and other symptoms associated with infection or fever. Sepsis can lead to septic shock and raises the risk of death. Symptoms of septic shock include inability to stand, sleepiness, and extreme confusion. Interestingly, symptoms can vary between people, and it is important to monitor bodily changes to detect sepsis as early as possible. Bacterial, viral, or fungal infections can lead to sepsis including common infections such as pneumonia, urinary tract infections, and burns, among others. It is critical to see a doctor if you suspect you are not getting better or if your symptoms worsen. Early detection of sepsis can help improve survival rate and prevent permanent organ damage. Treatments include antibiotics, increased fluids, vasopressors to increase blood pressure, and steroids. Although scientists and physicians have worked to understand sepsis and how to treat it, other discoveries are yet to be made.

A recent study in Nature Immunology by Dr. Antoine Roquilly from Nantes University in France, demonstrated that patients that experienced sepsis build strong immune cells that aid in the prevention of tumor development. It was previously unknown how the immune landscape was shaped after a patient recovered from sepsis. Roquilly and his team wanted to understand the relationship between these exposed immune cells and the risk of developing cancer in the future.

Roquilly’s research team first analyzed big datasets that consisted of information from patients who survived sepsis. Researchers were able to determine the risk of cancer prevalence up to 10 years following the discharge from the hospital for sepsis patients. Interestingly, sepsis survivors had lower risk of developing cancer compared to those that did not have sepsis.

The new method developed by the Swedish researchers utilizes artificial intelligence for rapid and cost-effective assessment of chemical toxicity. It can therefore be used to identify toxic substances at an early phase and help reduce the need for animal testing.

“Our method is able to predict whether a substance is toxic or not based on its chemical structure. It has been developed and refined by analyzing large datasets from laboratory tests performed in the past. The method has thereby been trained to make accurate assessments for previously untested chemicals,” says Mikael Gustavsson, researcher at the Department of Mathematical Sciences at Chalmers University of Technology, and at the Department of Biology and Environmental Sciences at the University of Gothenburg.

“There are currently more than 100,000 chemicals on the market, but only a small part of these have a well-described toxicity towards humans or the environment. To assess the toxicity of all these chemicals using conventional methods, including animal testing, is not practically possible. Here, we see that our method can offer a new alternative,” says Erik Kristiansson, professor at the Department of Mathematical Sciences at Chalmers and at the University of Gothenburg.

Sam Altman isn’t sure the future of artificial intelligence requires new hardware.

Despite a flurry of new devices hitting the market, the OpenAI CEO told MIT Technology Review we might not need to buy separate devices to engage with AI in the future.

“I don’t think it will require a new piece of hardware,” he said while in Cambridge, Massachusetts, for events hosted by Harvard University and the venture-capital firm Xfund.

As Digital Physics gains traction, some theorists propose that our universe could fundamentally operate like a quantum computer, where space-time itself is a computational grid.

Owners of the Apple Vision Pro who are also in the developer beta can now download and install the fourth test build of visionOS 1.2.

The fourth build of visionOS 1.2 surfaces after the third, which Apple issued on April 24. The second arrived on April 16, while the first appeared on April 2.

Continue reading “Apple distributes its fourth visionOS 1.2 developer beta” »

AMD is getting serious about ray-tracing performance, RDNA 4’s RT hardware for Radeon is said to be ‘brand new’ and ‘completely different.’

How long does it take to improve your gut health? Learn what research is saying and how you can reset your microbiome through diet.

The open CMS detector during the second long shutdown of CERN’s accelerator complex. (Image: CERN) When we look at ourselves in a mirror, we see a virtual twin, identical in every detail except with left and right inverted. In particle physics, a transformation in which charge–parity (CP) symmetry is respected swaps a particle with the mirror image of its antimatter particle, which has opposite properties such as electric charge. The physical laws that govern nature don’t respect CP symmetry, however. If they did, the Universe would contain equal amounts of matter and antimatter, as it is believed to have done just after the Big Bang. To explain the large imbalance between matter and antimatter seen in the present-day Universe, CP symmetry has to be violated to a great extent. The Standard Model of particle physics can account for some CP violation, but it is not sufficient to explain the present-day matter–antimatter imbalance, prompting researchers to explore CP violation in all its known and unknown manifestations. One way CP violation can manifest itself is in the “mixing” of electrically neutral mesons such as the strange beauty meson, which is composed of a strange quark and a bottom antiquark. These mesons can travel macroscopic distances in the Large Hadron Collider (LHC) detectors before decaying into lighter particles, and during this journey they can turn into their corresponding antimesons and back. This phenomenon, called meson mixing, could be different for a meson turning into an antimeson versus an antimeson turning into a meson, generating CP violation. To see if that’s the case, researchers need to count how many mesons or antimesons survive a certain duration before decaying, and then repeat the measurement for a given range of durations. To do so, they have to separate mesons from antimesons, a task called flavour tagging. This task is crucial to pinning down CP violation in meson mixing and in the interference between meson mixing and decay. At a seminar held recently at CERN, the CMS collaboration at the LHC reported the first evidence of CP violation in the decay of the strange beauty meson into a pair of muons and a pair of electrically charged kaons. By deploying a new flavour-tagging algorithm on a sample of about 500 000 decays of the strange beauty meson into a pair of muons and a pair of charged kaons, collected during Run 2 of the LHC, the CMS collaboration measured with improved precision the parameter that determines CP violation in the interference between this meson’s mixing and decay. If this parameter is zero, CP symmetry is respected. The new flavour-tagging algorithm is based on a cutting-edge artificial intelligence (AI) technique called a graph neural network, which performs accurate flavour tagging by gathering information from the particles surrounding the strange beauty meson and those being produced alongside it. The collaboration then combined the result with its previous measurement of the parameter based on data from Run 1 of the LHC. The combined result is different from zero and is consistent with the Standard Model prediction and with previous measurements from CMS and the ATLAS and LHCb experiments. Notably, the combined result is comparable in precision to the world’s most precise measurement of the parameter, obtained by LHCb, a detector specifically designed to perform measurements of this kind. Moreover, the result has a statistical significance that crosses the conventional “3 sigma” threshold, providing the first evidence of CP violation in the decay of the strange beauty meson into a pair of muons and a pair of charged kaons. The result marks a milestone in CMS’s studies of CP violation. Thanks to AI, CMS has pushed the boundary of what its detector can achieve in the exploration of this fundamental matter–antimatter asymmetry. Find out more on the CMS website.