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More than 30 years ago, findings from the Harvard Medical Practice Study (HMPS) helped bring public awareness to the problem of patient safety. Since the publication of the HMPS results, new strategies for preventing specific types of adverse events have been put into place, but it has been challenging to measure the impact on patient care.

To better understand what progress has been made in the last few decades, a team from Boston area hospitals conducted the SafeCare Study, which evaluated 11 hospitals in the region.

Led by investigators from Mass General Brigham and sponsored by CRICO, the medical professional liability insurer for the Harvard and its affiliated organizations, the study provides an estimate of adverse events in the inpatient environment, shedding light on the progress of two decades of work focused on improving and highlighting the need for continued improvement. Results are published in The New England Journal of Medicine.

One of the most dreaded effects of the bite of the brown recluse spider (Loxosceles spp) is the appearance of a necrotic skin lesion, but a clinical study by Brazilian researchers recently reported in PLOS Neglected Tropical Diseases shows that the problem can be solved by administering antivenom, especially if this is done within 48 hours of the incident.

An antivenom produced by Butantan Institute, an arm of the São Paulo State Department of Health, was used in the study. As the authors of the paper explain, there is no consensus regarding the to avoid necrosis and ulceration in cases of brown recluse spider bites.

A 2009 study involving rabbits showed that necrotic lesions were approximately 30% smaller even when the antivenom was administered 48 hours after the animals were bitten.

Summary: Researchers identify the role the Pig-Q gene plays in sleep regulation. Mutations of the Pig-Q gene increase sleep.

Source: Texas A&M

A research effort involving researchers from Texas A&M University, the Perelman School of Medicine at the University of Pennsylvania and Children’s Hospital of Philadelphia (CHOP) has used human genomics to identify a new genetic pathway involved in regulating sleep from fruit flies to humans—a novel insight that could pave the way for new treatments for insomnia and other sleep-related disorders.

https://youtu.be/I5Xarr7pBuk

Simon Waslander is the Director of Collaboration, at the CureDAO Alliance for the Acceleration of Clinical Research (https://www.curedao.org/), a community-owned platform for the precision health of the future.

CureDAO is creating an open-source platform to discover how millions of factors, like foods, drugs, and supplements affect human health, within a decentralized autonomous organization (DAO), making suffering optional through the creation of a “WordPress of health data”.

Simon is a native of the Dutch Caribbean island of Aruba, having been born on the island and initially chose to study medicine at the University of Groningen, but then transitioned over to healthcare innovation studies at the University of Maastricht where he wrote his master thesis on the topic of Predictive Healthcare Algorithms.

(For information on the discussion segment on AGI, please contact — www.Norn.AI)

An international team has succeeded in propagating a commercial hybrid rice strain as a clone through seeds with 95 percent efficiency. This could lower the cost of hybrid rice seed, making high-yielding, disease resistant rice strains available to low-income farmers worldwide. The work was published Dec. 27 in Nature Communications.

First-generation hybrids of crop plants often show higher performance than their parent strains, a phenomenon called hybrid vigor. But this does not persist if the hybrids are bred together for a second generation. So when farmers want to use high-performing hybrid plant varieties, they need to purchase new seed each season.

Rice, the staple crop for half the world’s population, is relatively costly to breed as a hybrid for a yield improvement of about 10 percent. This means that the benefits of hybrids have yet to reach many of the world’s farmers, said Gurdev Khush, adjunct professor emeritus in the Department of Plant Sciences at the University of California, Davis. Working at the International Rice Research Institute from 1967 until retiring to UC Davis in 2002, Khush led efforts to create new rice high-yield rice varieties, work for which he received the World Food Prize in 1996.

Fake scientific abstracts and research papers generated using OpenAI’s highly-advanced chatbox ChatGPT fooled scientists into thinking they were real reports nearly one-third of the time, according to a new study, as the eerily human-like program raises eyebrows over the future of artificial intelligence.

Researchers at Northwestern University and the University of Chicago instructed ChatGPT to generate fake research abstracts based on 10 real ones published in medical journals, and fed the fakes through two detection programs that attempted to distinguish them from real reports.


ChatGPT created completely original scientific abstracts based on fake numbers, and stumped reviewers nearly one-third of the time.

Portable, low-field strength MRI systems have the potential to transform neuroimaging – provided that their low spatial resolution and low signal-to-noise (SNR) ratio can be overcome. Researchers at Harvard Medical School are harnessing artificial intelligence (AI) to achieve this goal. They have developed a machine learning super-resolution algorithm that generates synthetic images with high spatial resolution from lower resolution brain MRI scans.

The convolutional neural network (CNN) algorithm, known as LF-SynthSR, converts low-field strength (0.064 T) T1-and T2-weighted brain MRI sequences into isotropic images with 1 mm spatial resolution and the appearance of a T1-weighted magnetization-prepared rapid gradient-echo (MP-RAGE) acquisition. Describing their proof-of-concept study in Radiology, the researchers report that the synthetic images exhibited high correlation with images acquired by 1.5 T and 3.0 T MRI scanners.

Morphometry, the quantitative size and shape analysis of structures in an image, is central to many neuroimaging studies. Unfortunately, most MRI analysis tools are designed for near-isotropic, high-resolution acquisitions and typically require T1-weighted images such as MP-RAGE. Their performance often drops rapidly as voxel size and anisotropy increase. As the vast majority of existing clinical MRI scans are highly anisotropic, they cannot be reliably analysed with existing tools.