RESEARCH ARTICLE: End Point–Based Threshold for the Ambulatory Arterial Stiffness Index @jasta49 @melgarejo1024 @neurociencias @PPBoggia
BACKGROUND: The ambulatory arterial stiffness index (AASI) is increasingly used in clinical research and practice. This individual-participant meta-analysis aims to consolidate the prognostic accuracy of AASI in the general population and to derive an end point–based AASI risk threshold. METHODS: In 12 558 individuals enrolled in 14 population studies (48.8% women; mean age, 59.3 years), AASI was derived by regressing 24-hour diastolic on systolic blood pressure (mm Hg/mm Hg). Using Cox regression, the risk-carrying AASI threshold was established by examining stepwise increasing AASI levels and by determining the AASI level, yielding a 10-year risk similar to an office systolic pressure of 140 mm Hg. RESULTS: Over 10.7 years (median), 3,027 all-cause deaths and 2,183 cardiovascular end points occurred.
Central vein sign and paramagnetic rim lesions can aid in an earlier diagnosis of late-onset multiple sclerosis and may circumvent the need for biopsy. Learn more in this Pearls & Oy-sters article.
CSF analysis revealed lymphocytic pleocytosis (41 total nucleated cells [normal 0–5/μL], 98% lymphocytes) and an elevated protein of 89 mg/dL (normal, 0–35 mg/dL) without hypoglycorrhachia. CSF kappa free light chains (KFLC) and IgG index were not elevated, and CSF-specific oligoclonal bands (OCBs) were absent. CSF cytology and flow cytometry were negative for malignancy. Extensive neural antibody testing was negative including serum aquaporin-4-immunoglobulin G, myelin oligodendrocyte glycoprotein-immunoglobulin G, and CSF glial fibrillary acidic protein antibody. Extensive rheumatological and infectious testing was also negative. Neurofilament light chain was elevated to 188 pg/mL (normal ≤19 pg/mL for age 60–65 years). Whole body PET was negative, and optical coherence tomography was normal.
Owing to concerns for neurosarcoidosis, lymphoma, or vasculitis, a percutaneous stereotactic biopsy of a right occipital lesion was performed. Pathology revealed a demarcated CD68/163+ macrophage-rich lesion with myelin loss, relative axonal preservation, and a CD3+ predominant lymphocytic infiltrate with rare CD20+ B cells, consistent with active demyelination (Figure 2). She initiated a 5-day course of high-dose oral prednisone (1,250 mg daily) followed by a taper. Within 2 days of treatment, she experienced mild improvement in dysarthria and ataxia, although her EDSS score remained 6 on discharge.
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Heart disease is the leading cause of adult death worldwide, making cardiovascular disease diagnosis and management a global health priority. An echocardiogram, or cardiac ultrasound, is one of the most commonly used imaging tools employed by physicians to diagnose a variety of heart diseases and conditions.
Most standard echocardiograms provide two-dimensional visual images (2D) of the three-dimensional (3D) cardiac anatomy. These echocardiograms often capture hundreds of 2D slices or views of a beating heart that can enable physicians to make clinical assessments about the function and structure of the heart.
To improve diagnostic accuracy of cardiac conditions, researchers from UC San Francisco set out to determine whether deep neural networks (DNNs), a type of AI algorithm, could be re-designed to better capture complex 3D anatomy and physiology from multiple imaging views simultaneously. They developed a new “multiview” DNN structure—or architecture—to enable it to draw information from multiple imaging views at once, rather than the current approach of using only a single view. They then trained demonstration DNNs using this architecture to detect disease states for three cardiovascular conditions: left and right ventricular abnormalities, diastolic dysfunction, and valvular regurgitation.
Researchers publishing in Aging Cell have discovered that the nuclei of the cells that line injured arteries quickly become misshapen and that this leads to accelerated cellular senescence. Delivering zinc to these cells partially alleviates this dysmorphism.
Two seemingly unrelated concepts
This paper begins with a discussion of two different concepts that, on the surface, appear to be unrelated. First, the researchers discuss vascular damage, particularly in the context of surgeries; even minimally invasive procedures that involve cutting, scraping, or burning arteries must cause some level of damage. This includes such procedures as catheter implantation as a treatment for heart disease [1] and the resection of cancerous tumors [2].
Infants born with congenital heart disease (CHD) often have neurodevelopmental impairments that affect them later in life, including their ability to regulate their emotions and movements. As CHD is the most prevalent congenital disorder in the United States, researchers are eager to find new ways to treat it.
To better understand how CHD affects an infant’s developing nervous system, researchers at Children’s National Hospital used resting-state functional magnetic resonance imaging (rs-fMRI) to evaluate how healthy infants and those with CHD differed. They recently reported in the Journal of Neuroscience that babies with CHD had altered brain activity in their sensorimotor and limbic networks, but after neonatal heart surgery, these brain networks looked more like those of healthy children.
“Using fMRI, we can identify brain networks that are vulnerable to altered oxygen and blood flow from congenital heart disease, which could help guide interventions to improve care for children,” said Jung-Hoon Kim, a brain researcher at Children’s National Hospital and a coauthor of the study, in a press release.
In their study, the researchers analyzed rs-fMRI data from 448 neonates. They first analyzed publicly available data from the Developing Human Connectome Project, which contains a large amount infant brain development MRI data.3 They identified 15 different resting state networks, which represented different regions of brain activity, in the healthy neonate brains.
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Babies with congenital heart disease have altered brain activity in regions involved in movement and emotions, but heart surgery restored these brain networks to healthy connectivity.
Inside a diseased cell, the genes are in chaos. Some are receiving signals to overproduce a protein. Others are reducing activity to abnormal levels. Up is down and down is up. The right molecule could restore order, reversing dysregulation in specific genes. But finding the ideal compound could require examining millions of chemicals for their influence on hundreds or thousands of genes.
An MSU-led team of researchers has demonstrated a better way. Using machine learning trained on enormous amounts of published data, they were able to predict how chemicals will influence gene expression, based solely on the structure of the chemical.
Their study, recently published in the journal Cell, has discovered compounds that are promising for treatment of two difficult diseases: the most aggressive form of liver cancer and a chronic lung disease with no curative options.
Scientists at Caltech have figured out how to precisely engineer tiny three-dimensional (3D) metallic pieces with nanoscale dimensions. The process can work with any metal or metal alloy and yields components of surprising strength despite having a porous and defect-ridden microstructure, making it potentially useful in a wide range of applications, including medical devices, computer chips, and equipment needed for space missions.
The scientists describe their method in a paper published in the journal Nature Communications. The work was completed in the lab of Julia R. Greer, the Ruben F. and Donna Mettler Professor of Materials Science, Mechanics and Medical Engineering at Caltech, and Huajian Gao of Tsinghua University in Beijing.
The researchers use a technique called two-photon lithography that allows them to sequentially build an object of a desired size and shape by carefully controlling the geometry at the level of individual voxels, the smallest distinguishable volumes, or features, in a 3D image. Beginning with a light-sensitive liquid, the scientists use a tightly focused femtosecond laser beam—a femtosecond is 1 quadrillionth of a second—to build a desired shape out of a gel-like material called hydrogel. After infusing the miniature hydrogel sculpture with metallic salts, such as copper nitrate or nickel nitrate, they heat the structure twice in a specialized furnace to produce a shrunken metallic replica of the original shape.
Plastic trash has reached the world’s most remote locations, from the bottom of the Mariana Trench to the summit of Everest. Hundreds of plastic-eating microbes that could help us clean up have been discovered over the past quarter of a century, but there is a long way to go before they can be put to work in natural environments: Microbial digestion of plastic is still slow, requires high temperatures, and only proceeds efficiently in bioreactors. Moreover, most plastic-eating microbes discovered so far can only digest a single kind of plastic.
One solution would be to combine different microbes to tackle plastic pollution as a team. This allows them to share tasks, compensate for each other’s weaknesses, and continue working even when environmental conditions change.
Now, scientists in Germany have discovered such a synergistic “consortium” of plastic-eating bacteria, which can eat phthalate esters (PAEs)—plasticizers that are often found in building materials, food packages, and personal care products, but have been implicated in hormonal, metabolic, and developmental disorders and some cancers. The results are published in Frontiers in Microbiology.