Deep-learning based segmentation of challenging myelin sheaths

The segmentation of axons and myelin in electron microscopy images allows neurologists to highlight the density of axons and the thickness of the myelin surrounding them. These properties are of great interest for preventing and anticipating white matter diseases. This task is generally performed manually, which is a long and tedious process. We present an update of the methods used to compute that segmentation via machine learning. Our model is based on the architecture of the U-Net network. Our main contribution consists in using transfer learning in the encoder part of the UNet network, as well as test time augmentation when segmenting. We use the SE-Resnet50 backbone weights which was pre-trained on the ImageNet 2012 dataset. We used a data set of 23 images with the corresponding segmented masks, which also was challenging due to its extremely small size. The results show very encouraging performances compared to the state-of-the-art with an average precision of 92% on the test images. It is also important to note that the available samples were taken from elderly mices in the corpus callosum. This represented an additional difficulty, compared to related works that had samples taken from the spinal cord or the optic nerve of healthy individuals, with better contours and less debri

Characterization of early ultrastructural changes in the cerebral white matter of CADASIL small vessel disease using high pressure freezing/freeze-substitution

AIMS: The objective of this study was to elucidate the early white matter changes in CADASIL small vessel disease. METHODS: We used high pressure freezing and freeze substitution (HPF/FS) in combination with high resolution electron microscopy (EM), immunohistochemistry and confocal microscopy of brain specimens from control and CADASIL (TgNotch3R169C ) mice aged 4 to 15 months to study white matter lesions in the corpus callosum. RESULTS: We first optimized the HPF/FS protocol in which samples were chemically prefixed, frozen in a sample carrier filled with 20% polyvinylpyrrolidone and freeze-substituted in a cocktail of tannic acid, osmium tetroxide and uranyl acetate dissolved in acetone. EM analysis showed that CADASIL mice exhibit significant splitting of myelin layers and enlargement of the inner tongue of small calibre axons from the age of 6 months, then vesiculation of the inner tongue and myelin sheath thinning at 15 months of age. Immunohistochemistry revealed an increased number of oligodendrocyte precursor cells, although only in older mice, but no reduction in the number of mature oligodendrocytes at any age. The number of Iba1 positive microglial cells was increased in older but not in younger CADASIL mice, but the number of activated microglial cells (Iba1 and CD68 positive) was unchanged at any age. CONCLUSION: We conclude that early WM lesions in CADASIL affect first and foremost the myelin sheath and the inner tongue, suggestive of a primary myelin injury. We propose that those defects are consistent with a hypoxic/ischaemic mechanism

Estimating blood pressure trends and the nocturnal dip from photoplethysmography

Objective: Evaluate a method for the estimation of the nocturnal systolic blood pressure dip from 24-hour blood pressure trends using a wrist-worn Photoplethysmography (PPG) sensor and a deep neural network in free-living individuals, comparing the deep neural network to traditional machine learning and non-machine learning baselines. Approach: A wrist-worn PPG sensor was worn by 106 healthy individuals for 226 days during which 5111 reference values for blood pressure were obtained with a 24-hour ambulatory blood pressure monitor as ground truth and matched with the PPG sensor data. Features based on heart rate variability and pulse morphology were extracted from the PPG waveforms. Machine learning models (linear regression, random forests, dense neural networks and long- and short-term memory neural networks) were then trained and evaluated in their capability of tracking trends in systolic and diastolic blood pressure, as well as the estimation of the nocturnal systolic blood pressure dip. Main results Best performance was obtained with a deep long- and shortterm memory neural network with a Root Mean Squared Error (RMSE) of 3.12±2.20 ∆mmHg and a correlation of 0.69 (p = 3 ∗ 10−5) with the ground truth Systolic Blood Pressure (SBP) dip. This dip was derived from trend estimates of blood pressure which had an RMSE of 8.22±1.49 mmHg for systolic and 6.55±1.39 mmHg for diastolic blood pressure. The random forest model showed slightly lower average error magnitude for SBP trends (7.86±1.57 mmHg), however Bland-Altmann analysis revealed systematic problems in its predictions that were less present in the long- and short-term memory model. Significance The work provides first evidence for the unobtrusive estimation of the nocturnal blood pressure dip, a highly prognostic clinical parameter. It is also the first to evaluate unobtrusive blood pressure measurement in a large data set of unconstrained 24-hour measurements in free-living individuals and provides evidence for the utility of long- and short-term models in this domain

Combination therapy with reovirus and anti-PD-1 blockade controls tumor growth through innate and adaptive immune responses.

Oncolytic reovirus can be delivered both systemically and intratumorally, in both pre-clinical models and in early phase clinical trials. Reovirus has direct oncolytic activity against a variety of tumor types and anti-tumor activity is directly associated with immune activation by virus replication in tumors. Immune mechanisms of therapy include both innate immune activation against virally infected tumor cells, and the generation of adaptive anti-tumor immune responses as a result of in vivo priming against tumor-associated antigens. We tested the combination of local oncolytic reovirus therapy with systemic immune checkpoint inhibition. We show that treatment of subcutaneous B16 melanomas with a combination of intravenous (i.v.) anti-PD-1 antibody and intratumoral (i.t.) reovirus significantly enhanced survival of mice compared to i.t. reovirus (p<0.01) or anti-PD-1 therapy alone. In vitro immune analysis demonstrated that checkpoint inhibition improved the ability of NK cells to kill reovirus-infected tumor cells, reduced Treg activity, and increased the adaptive CD8(+) T cell dependent anti-tumor T cell response. PD-1 blockade also enhanced the anti-viral immune response but through effector mechanisms which overlapped with, but also differed from those affecting the antitumor response. Therefore, combination with checkpoint inhibition represents a readily translatable next step in the clinical development of reovirus

Enteric Infection with Citrobacter rodentium Induces Coagulative Liver Necrosis and Hepatic Inflammation Prior to Peak Infection and Colonic Disease

Acute and chronic forms of inflammation are known to affect liver responses and susceptibility to disease and injury. Furthermore, intestinal microbiota has been shown critical in mediating inflammatory host responses in various animal models. Using C. rodentium, a known enteric bacterial pathogen, we examined liver responses to gastrointestinal infection at various stages of disease pathogenesis. For the first time, to our knowledge, we show distinct liver pathology associated with enteric infection with C. rodentium in C57BL/6 mice, characterized by increased inflammation and hepatitis index scores as well as prominent periportal hepatocellular coagulative necrosis indicative of thrombotic ischemic injury in a subset of animals during the early course of C. rodentium pathogenesis. Histologic changes in the liver correlated with serum elevation of liver transaminases, systemic and liver resident cytokines, as well as signal transduction changes prior to peak bacterial colonization and colonic disease. C. rodentium infection in C57BL/6 mice provides a potentially useful model to study acute liver injury and inflammatory stress under conditions of gastrointestinal infection analogous to enteropathogenic E. coli infection in humans.United States. Army Research Office (Institute for Soldier Nanotechnology grant 6915539 (SRT))National Institutes of Health (U.S.) (Grant P01 CA026731)National Institutes of Health (U.S.) (Grant P30 ES02109)National Institutes of Health (U.S.) (Toxicology Training grant ES-070220

Health state utilities associated with attributes of treatments for hepatitis C

BACKGROUND: Cost-utility analyses are frequently conducted to compare treatments for hepatitis C, which are often associated with complex regimens and serious adverse events. Thus, the purpose of this study was to estimate the utility associated with treatment administration and adverse events of hepatitis C treatments. DESIGN: Health states were drafted based on literature review and clinician interviews. General population participants in the UK valued the health states in time trade-off (TTO) interviews with 10- and 1-year time horizons. The 14 health states described hepatitis C with variations in treatment regimen and adverse events. RESULTS: A total of 182 participants completed interviews (50 % female; mean age = 39.3 years). Utilities for health states describing treatment regimens without injections ranged from 0.80 (1 tablet) to 0.79 (7 tablets). Utilities for health states describing oral plus injectable regimens were 0.77 (7 tablets), 0.75 (12 tablets), and 0.71 (18 tablets). Addition of a weekly injection had a disutility of −0.02. A requirement to take medication with fatty food had a disutility of −0.04. Adverse events were associated with substantial disutilities: mild anemia, −0.12; severe anemia, −0.32; flu-like symptoms, −0.21; mild rash, −0.13; severe rash, −0.48; depression, −0.47. One-year TTO scores were similar to these 10-year values. CONCLUSIONS: Adverse events and greater treatment regimen complexity were associated with lower utility scores, suggesting a perceived decrease in quality of life beyond the impact of hepatitis C. The resulting utilities may be used in models estimating and comparing the value of treatments for hepatitis C. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10198-014-0649-6) contains supplementary material, which is available to authorized users