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A quantum experiment revealed two observers can experience different, coexisting realities.

Our understanding of reality is often shaped by biases—our senses, cultures, and knowledge influence how we see the world. But even science, often regarded as a path to objective truth, may not always offer a single, consistent version of reality. A recent experiment testing a 1961 thought experiment by Nobel Prize winner Eugen Wigner highlights this issue, showing that two versions of reality can coexist in the quantum world.

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Published in Nature Communications, a new study led by the University of Minnesota Medical School and Duke University found that a DNA sequencing test for advanced prostate cancer patients can distinguish between patients with poor and favorable prognoses.

The new blood-based —called AR-ctDETECT—is designed to detect and analyze small fragments of tumor-derived DNA in the blood of certain with advanced, .

In this new study, the AR-ctDETECT test was used to analyze DNA from more than 770 from a phase 3 clinical trial of advanced prostate cancer patients. The test identified circulating tumor DNA (ctDNA) in 59% of patients with metastatic prostate cancer. Patients with detectable circulating tumor DNA had significantly worse overall survival compared to those without. These results demonstrate the potential of the AR-ctDETECT test to provide key genetic information to tailor treatments based on similar characteristics among patients.

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New research found that the protein MANF helps cells manage toxic protein clumps, improving cellular health and potentially aiding treatments for age-related diseases like Alzheimer’s and Parkinson’s.

Researchers at McMaster University have uncovered a previously unidentified cell-protective role of a protein, potentially paving the way for new treatments for age-related diseases and promoting healthier aging.

The team has found that a class of protective proteins known as MANF plays a role in the process that keep cells efficient and working well.

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A newly published research study from the UNC Lineberger Comprehensive Cancer Center describes how the absence of the protein NLRP12 significantly increases susceptibility to colitis-associated colon cancer in pre-clinical models.

A family of proteins is yielding new information about how it contributes to the development of gastrointestinal disease and cancer. A team of UNC scientists reports that in pre-clinical models, the absence of a protein called NLRP12 significantly increases susceptibility to colitis-associated colon cancer.

The NLR family of proteins is very complex and scientists have determined that the majority of them act as activators of inflammation. However, scientists at UNC and elsewhere have recently reported that one NLR protein, NLRP12, actually functions to reduce disease by inhibiting a major inflammatory pathway mediated by a protein called NF-Kappa B activation has been long associated with inflammation and cancer promotion. But NF-Kappa B has an alternate signaling pathway that is not as well understood. This alternative pathway was the focus of the UNC team’s study. Their study was published in the April 12, 2012 online issue of the journal Immunity.

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UNIVERSITY PARK, Pa. — A recently developed electronic tongue is capable of identifying differences in similar liquids, such as milk with varying water content; diverse products, including soda types and coffee blends; signs of spoilage in fruit juices; and instances of food safety concerns. The team, led by researchers at Penn State, also found that results were even more accurate when artificial intelligence (AI) used its own assessment parameters to interpret the data generated by the electronic tongue.

(Many people already posted this. This is the press release from Penn Sate who did the research)

The tongue comprises a graphene-based ion-sensitive field-effect transistor, or a conductive device that can detect chemical ions, linked to an artificial neural network, trained on various datasets. Critically, Das noted, the sensors are non-functionalized, meaning that one sensor can detect different types of chemicals, rather than having a specific sensor dedicated to each potential chemical. The researchers provided the neural network with 20 specific parameters to assess, all of which are related to how a sample liquid interacts with the sensor’s electrical properties. Based on these researcher-specified parameters, the AI could accurately detect samples — including watered-down milks, different types of sodas, blends of coffee and multiple fruit juices at several levels of freshness — and report on their content with greater than 80% accuracy in about a minute.

“After achieving a reasonable accuracy with human-selected parameters, we decided to let the neural network define its own figures of merit by providing it with the raw sensor data. We found that the neural network reached a near ideal inference accuracy of more than 95% when utilizing the machine-derived figures of merit rather than the ones provided by humans,” said co-author Andrew Pannone, a doctoral student in engineering science and mechanics advised by Das. “So, we used a method called Shapley additive explanations, which allows us to ask the neural network what it was thinking after it makes a decision.”

Continue reading “A matter of taste: Electronic tongue reveals AI inner thoughts” | >

Chronological age (CA) does not reflect individual variation in the aging process. However, existing biological age predictors are mostly based on European populations and overlook the widespread nonlinear effects of clinical biomarkers.

Using data from the prospective Dongfeng-Tongji (DFTJ) cohort of elderly Chinese, we propose a physiological aging index (PAI) based on 36 routine clinical biomarkers to measure aging progress. We first determined the optimal level of each biomarker by restricted cubic spline Cox models. For biomarkers with a U-shaped relationship with mortality, we derived new variables to model their distinct effects below and above the optimal levels. We defined PAI as a weighted sum of variables predictive of mortality selected by a LASSO Cox model. To measure aging acceleration, we defined ΔPAI as the residual of PAI after regressing on CA. We evaluated the predictive value of ΔPAI on cardiovascular diseases (CVD) in the DFTJ cohort, as well as nine major chronic diseases in the UK Biobank (UKB).

In the DFTJ training set (n = 12,769, median follow-up: 10.38 years), we identified 25 biomarkers with significant nonlinear associations with mortality, of which 11 showed insignificant linear associations. By incorporating nonlinear effects, we selected CA and 17 clinical biomarkers to calculate PAI. In the DFTJ testing set (n = 15,904, 5.87 years), PAI predict mortality with a concordance index (C-index) of 0.816 (95% confidence interval, [0.796, 0.837]), better than CA (C-index = 0.771 [0.755, 0.788]) and PhenoAge (0.799 [0.784, 0.814]). ΔPAI was predictive of incident CVD and its subtypes, independent of traditional risk factors. In the external validation set of UKB (n = 296,931, 12.80 years), PAI achieved a C-index of 0.749 (0.746, 0.752) to predict mortality, remaining better than CA (0.706 [0.702, 0.709]) and PhenoAge (0.743 [0.739, 0.746]).

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ATLANTA — An innovative approach to public safety is taking shape on Cleveland Avenue, where Atlanta City Councilman Antonio Lewis has partnered with the 445 Cleveland apartment complex to deploy AI-powered robotic dogs to deter crime.

The robotic dog, named “Beth,” is equipped with 360-degree cameras, a siren, and stair-climbing capabilities. Unlike other artificial intelligence robots like “Spunky” on Boulevard, Beth is monitored in real time by a human operator located in Bogotá, Colombia.

“Our operator who is physically watching these cameras needs to deploy the dog. It’s all in one system, and they are just controlling it, like a video game at home, except it’s not a video game—it’s Beth,” said Avi Wolf, the owner of 445 Cleveland.

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A team of Chinese researchers from Xiamen University has won the 2023 “Best Paper Prize” from Applied Optics for their groundbreaking work on a single-photon Raman lidar system. Published in June last year, their paper outshone 1,278 other submissions, securing the top spot.

The paper presented radar technology capable of detecting objects at significant depths with such clarity that it has been compared to “fishing for a needle in the sea.”

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