Traditionally, medical discoveries are made by observing associations and then designing experiments to test these hypotheses. However, observing and quantifying associations in images can be difficult because of the wide variety of features, patterns, colors, values, shapes in real data. In this paper, we use deep learning, a machine learning technique that learns its own features, to discover new knowledge from retinal fundus images. Using models trained on data from 284,335 patients, and validated on two independent datasets of 12,026 and 999 patients, we predict cardiovascular risk factors not previously thought to be present or quantifiable in retinal images, such as such as age (within 3.26 years), gender (0.97 AUC), smoking status (0.71 AUC), HbA1c (within 1.39%), systolic blood pressure (within 11.23mmHg) as well as major adverse cardiac events (0.70 AUC). We further show that our models used distinct aspects of the anatomy to generate each prediction, such as the optic disc or blood vessels, opening avenues of further research.

Nanocrystals with advanced magnetic or optical properties have been actively pursued for potential biological applications, including integrated imaging, diagnosis and therapy. Among various magnetic nanocrystals, FeCo has superior magnetic properties, but it has yet to be explored owing to the problems of easy oxidation and potential toxicity. Previously, FeCo nanocrystals with multilayered graphitic carbon, pyrolytic carbon or inert metals have been obtained, but not in the single-shelled, discrete, chemically functionalized and water-soluble forms desired for biological applications. Here, we present a scalable chemical vapour deposition method to synthesize FeCo/single-graphitic-shell nanocrystals that are soluble and stable in water solutions. We explore the multiple functionalities of these core-shell materials by characterizing the magnetic properties of the FeCo core and near-infrared optical absorbance of the single-layered graphitic shell. The nanocrystals exhibit ultra-high saturation magnetization, r1 and r2 relaxivities and high optical absorbance in the near-infrared region. Mesenchymal stem cells are able to internalize these nanoparticles, showing high negative-contrast enhancement in magnetic-resonance imaging (MRI). Preliminary in vivo experiments achieve long-lasting positive-contrast enhancement for vascular MRI in rabbits. These results point to the potential of using these nanocrystals for integrated diagnosis and therapeutic (photothermal-ablation) applications.

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MicroRNAs (miRs) regulate gene expression at the posttranscriptional level and play crucial roles in vascular integrity. As such, they may have a role in modifying abdominal aortic aneurysm (AAA) expansion, the pathophysiological mechanisms of which remain incompletely explored. Here, we investigate the role of miRs in 2 murine models of experimental AAA: the porcine pancreatic elastase (PPE) infusion model in C57BL/6 mice and the AngII infusion model in Apoe -/-mice. AAA development was accompanied by decreased aortic expression of miR-29b, along with increased expression of known miR-29b targets, Col1a1, Col3a1, Col5a1, and Eln, in both models. In vivo administration of locked nucleic acid anti-miR-29b greatly increased collagen expression, leading to an early fibrotic response in the abdominal aortic wall and resulting in a significant reduction in AAA progression over time in both models. In contrast, overexpression of miR-29b using a lentiviral vector led to augmented AAA expansion and significant increase of aortic rupture rate. Cell culture studies identified aortic fibroblasts as the likely vascular cell type mediating the profibrotic effects of miR-29b modulation. A similar pattern of reduced miR-29b expression and increased target gene expression was observed in human AAA tissue samples compared with that in organ donor controls. These data suggest that therapeutic manipulation of miR29b and its target genes holds promise for limiting AAA disease progression and protecting from rupture.

Continuous monitoring of internal physiological parameters is essential for critical care patients, but currently can only be practically achieved via tethered solutions. Here we report a wireless, real-time pressure monitoring system with passive, flexible, millimetre-scale sensors, scaled down to unprecedented dimensions of 1 Â 1 Â 0.1 cubic millimeters. This level of dimensional scaling is enabled by novel sensor design and detection schemes, which overcome the operating frequency limits of traditional strategies and exhibit insensitivity to lossy tissue environments. We demonstrate the use of this system to capture human pulse waveforms wirelessly in real time as well as to monitor in vivo intracranial pressure continuously in proof-of-concept mice studies using sensors down to 2.5 Â 2.5 Â 0.1 cubic millimeters. We further introduce printable wireless sensor arrays and show their use in real-time spatial pressure mapping. Looking forward, this technology has broader applications in continuous wireless monitoring of multiple physiological parameters for biomedical research and patient care.

Identification and treatment of abdominal aortic aneurysm (AAA) remains among the most prominent challenges in vascular medicine. MicroRNAs are crucial regulators of cardiovascular pathology and represent possible targets for the inhibition of AAA expansion. We identified microRNA-21 (miR-21) as a key modulator of proliferation and apoptosis of vascular wall smooth muscle cells during development of AAA in two established murine models. In both models (AAA induced by porcine pancreatic elastase or infusion of angiotensin II), miR-21 expression increased as AAA developed. Lentiviral overexpression of miR-21 induced cell proliferation and decreased apoptosis in the aortic wall, with protective effects on aneurysm expansion. miR-21 overexpression substantially decreased expression of the phosphatase and tensin homolog (PTEN) protein, leading to increased phosphorylation and activation of AKT, a component of a pro-proliferative and antiapoptotic pathway. Systemic injection of a locked nucleic acid–modified antagomir targeting miR-21 diminished the pro-proliferative impact of down-regulated PTEN, leading to a marked increase in the size of AAA. Similar results were seen in mice with AAA augmented by nicotine and in human aortic tissue samples from patients undergoing surgical repair of AAA (with more pronounced effects observed in smokers). Modulation of miR-21 expression shows potential as a new therapeutic option to limit AAA expansion and vascular disease progression.

Getting enough sleep, exercising and limiting sedentary activities can greatly contribute to disease prevention and overall health and longevity. Measuring the full 24-hour activity cycle - sleep, sedentary behavior (SED), light intensity physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) - may now be feasible using small wearable devices. PURPOSE This study compares nine devices for accuracy in 24-hour activity measurement. METHODS Adults (N=40, 47% male) wore nine devices for 24-hours: Actigraph GT3X+, activPAL, Fitbit One, GENEactiv, Jawbone Up, LUMOback, Nike Fuelband, Omron pedometer, and Z-Machine. Comparisons (to standards) were made for total sleep time (Z-machine), time spent in SED (activPAL), LPA (GT3x+), MVPA (GT3x+), and steps (Omron). Analysis included mean absolute percent error, equivalence testing, and Bland-Altman plots. RESULTS Error rates ranged from 8.1–16.9% for sleep; 9.5–65.8% for SED; 19.7–28.0% for LPA; 51.8–92% for MVPA; and 14.1–29.9% for steps. Equivalence testing indicated only two comparisons were significantly equivalent to standards: the LUMOback for sedentary behavior and the GT3X+ for sleep. Bland-Altman plots indicated GT3X+ had the closest measurement for sleep, LUMOback for sedentary behavior, GENEactiv for LPA, Fitbit for MVPA and GT3X+ for steps. CONCLUSIONS Currently, no device accurately captures activity data across the entire 24-hour day, but the future of activity measurement should aim for accurate 24-hour measurement as a goal. Researchers should continue to select measurement devices based on their primary outcomes of interest.