PDGFRβ-P2A-CreERT2 mice: a genetic tool to target pericytes in angiogenesis.

Pericytes are essential mural cells distinguished by their association with small caliber blood vessels and the presence of a basement membrane shared with endothelial cells. Pericyte interaction with the endothelium plays an important role in angiogenesis; however, very few tools are currently available that allow for the targeting of pericytes in mouse models, limiting our ability to understand their biology. We have generated a novel mouse line expressing tamoxifen-inducible Cre-recombinase under the control of the platelet-derived growth factor receptor β promoter: PDGFRβ-P2A-CreER T2 . We evaluated the expression of the PDGFRβ-P2A-CreER T2 line by crossing it with fluorescent reporter lines and analyzed reporter signal in the angiogenic retina and brain at different time points after tamoxifen administration. Reporter lines showed labeling of NG2+, desmin+, PDGFRβ+ perivascular cells in the retina and the brain, indicating successful targeting of pericytes; however, signal from reporter lines was also observed in a small subset of glial cells both in the retina and the brain. We also evaluated recombination in tumors and found efficient recombination in perivascular cells associated with tumor vasculature. As a proof of principle, we used our newly generated driver to delete Notch signaling in perivascular cells and observed a loss of smooth muscle cells in retinal arteries, consistent with previously published studies evaluating Notch3 null mice. We conclude that the PDGFRβ-P2A-CreER T2 line is a powerful new tool to target pericytes and will aid the field in gaining a deeper understanding of the role of these cells in physiological and pathological settings.S

Investigation of the use of a sensor bracelet for the presymptomatic detection of changes in physiological parameters related to COVID-19: an interim analysis of a prospective cohort study (COVI-GAPP).

OBJECTIVES We investigated machinelearningbased identification of presymptomatic COVID-19 and detection of infection-related changes in physiology using a wearable device. DESIGN Interim analysis of a prospective cohort study. SETTING, PARTICIPANTS AND INTERVENTIONS Participants from a national cohort study in Liechtenstein were included. Nightly they wore the Ava-bracelet that measured respiratory rate (RR), heart rate (HR), HR variability (HRV), wrist-skin temperature (WST) and skin perfusion. SARS-CoV-2 infection was diagnosed by molecular and/or serological assays. RESULTS A total of 1.5 million hours of physiological data were recorded from 1163 participants (mean age 44±5.5 years). COVID-19 was confirmed in 127 participants of which, 66 (52%) had worn their device from baseline to symptom onset (SO) and were included in this analysis. Multi-level modelling revealed significant changes in five (RR, HR, HRV, HRV ratio and WST) device-measured physiological parameters during the incubation, presymptomatic, symptomatic and recovery periods of COVID-19 compared with baseline. The training set represented an 8-day long instance extracted from day 10 to day 2 before SO. The training set consisted of 40 days measurements from 66 participants. Based on a random split, the test set included 30% of participants and 70% were selected for the training set. The developed long short-term memory (LSTM) based recurrent neural network (RNN) algorithm had a recall (sensitivity) of 0.73 in the training set and 0.68 in the testing set when detecting COVID-19 up to 2 days prior to SO. CONCLUSION Wearable sensor technology can enable COVID-19 detection during the presymptomatic period. Our proposed RNN algorithm identified 68% of COVID-19 positive participants 2 days prior to SO and will be further trained and validated in a randomised, single-blinded, two-period, two-sequence crossover trial. Trial registration number ISRCTN51255782; Pre-results

Defining Natural History: Assessment of the Ability of College Students to Aid in Characterizing Clinical Progression of Niemann-Pick Disease, Type C

Niemann-Pick Disease, type C (NPC) is a fatal, neurodegenerative, lysosomal storage disorder. It is a rare disease with broad phenotypic spectrum and variable age of onset. These issues make it difficult to develop a universally accepted clinical outcome measure to assess urgently needed therapies. To this end, clinical investigators have defined emerging, disease severity scales. The average time from initial symptom to diagnosis is approximately 4 years. Further, some patients may not travel to specialized clinical centers even after diagnosis. We were therefore interested in investigating whether appropriately trained, community-based assessment of patient records could assist in defining disease progression using clinical severity scores. In this study we evolved a secure, step wise process to show that pre-existing medical records may be correctly assessed by non-clinical practitioners trained to quantify disease progression. Sixty-four undergraduate students at the University of Notre Dame were expertly trained in clinical disease assessment and recognition of major and minor symptoms of NPC. Seven clinical records, randomly selected from a total of thirty seven used to establish a leading clinical severity scale, were correctly assessed to show expected characteristics of linear disease progression. Student assessment of two new records donated by NPC families to our study also revealed linear progression of disease, but both showed accelerated disease progression, relative to the current severity scale, especially at the later stages. Together, these data suggest that college students may be trained in assessment of patient records, and thus provide insight into the natural history of a disease

Neurocognition across the spectrum of mucopolysaccharidosis type I: Age, severity, and treatment

OBJECTIVES: Precise characterization of cognitive outcomes and factors that contribute to cognitive variability will enable better understanding of disease progression and treatment effects in mucopolysaccharidosis type I (MPS I). We examined the effects on cognition of phenotype, genotype, age at evaluation and first treatment, and somatic disease burden. METHODS: Sixty patients with severe MPS IH (Hurler syndrome treated with hematopoietic cell transplant and 29 with attenuated MPS I treated with enzyme replacement therapy), were studied with IQ measures, medical history, genotypes. Sixty-seven patients had volumetric MRI. Subjects were grouped by age and phenotype and MRI and compared to 96 normal controls. RESULTS: Prior to hematopoietic cell transplant, MPS IH patients were all cognitively average, but post-transplant, 59% were below average, but stable. Genotype and age at HCT were associated with cognitive ability. In attenuated MPS I, 40% were below average with genotype and somatic disease burden predicting their cognitive ability. White matter volumes were associated with IQ for controls, but not for MPS I. Gray matter volumes were positively associated with IQ in controls and attenuated MPS I patients, but negatively associated in MPS IH. CONCLUSIONS: Cognitive impairment, a major difficulty for many MPS I patients, is associated with genotype, age at treatment and somatic disease burden. IQ association with white matter differed from controls. Many attenuated MPS patients have significant physical and/or cognitive problems and receive insufficient support services. Results provide direction for future clinical trials and better disease management

Unjust Punishments For People Of Color

Created by Neenah Estrella-Luna\u27s Fall 2019 Sociology 110 course. Zine addresses the racial disparities in prison sentences and incarceration rates, preamble of a white constitution, #Blacklivesmatter, victims on death row, and traffic stop victims.https://digitalcommons.salemstate.edu/zines/1005/thumbnail.jp

PDGFRb-P2A-CreERT2 mice: a genetic tool to target pericytes in angiogenesis

Pericytes are essential mural cells distinguished by their association with small caliber blood vessels and the presence of a basement membrane shared with endothelial cells. Pericyte interaction with the endothelium plays an important role in angiogenesis; however, very few tools are currently available that allow for the targeting of pericytes in mouse models, limiting our ability to understand their biology. We have generated a novel mouse line expressing tamoxifen-inducible Cre-recombinase under the control of the platelet-derived growth factor receptor β promoter: PDGFRβ-P2A-CreER T2. We evaluated the expression of the PDGFRβ-P2A-CreER T2 line by crossing it with fluorescent reporter lines and analyzed reporter signal in the angiogenic retina and brain at different time points after tamoxifen administration. Reporter lines showed labeling of NG2+, desmin+, PDGFRβ+ perivascular cells in the retina and the brain, indicating successful targeting of pericytes; however, signal from reporter lines was also observed in a small subset of glial cells both in the retina and the brain. We also evaluated recombination in tumors and found efficient recombination in perivascular cells associated with tumor vasculature. As a proof of principle, we used our newly generated driver to delete Notch signaling in perivascular cells and observed a loss of smooth muscle cells in retinal arteries, consistent with previously published studies evaluating Notch3 null mice. We conclude that the PDGFRβ-P2A-CreER T2 line is a powerful new tool to target pericytes and will aid the field in gaining a deeper understanding of the role of these cells in physiological and pathological settings

Toward a universal decoder of linguistic meaning from brain activation

Prior work decoding linguistic meaning from imaging data has been largely limited to concrete nouns, using similar stimuli for training and testing, from a relatively small number of semantic categories. Here we present a new approach for building a brain decoding system in which words and sentences are represented as vectors in a semantic space constructed from massive text corpora. By efficiently sampling this space to select training stimuli shown to subjects, we maximize the ability to generalize to new meanings from limited imaging data. To validate this approach, we train the system on imaging data of individual concepts, and show it can decode semantic vector representations from imaging data of sentences about a wide variety of both concrete and abstract topics from two separate datasets. These decoded representations are sufficiently detailed to distinguish even semantically similar sentences, and to capture the similarity structure of meaning relationships between sentences

Changing sub-Arctic tundra vegetation upon permafrost degradation: impact on foliar mineral element cycling

Arctic warming and permafrost degradation are modifying northern ecosystems through changes in microtopography, soil water dynamics, nutrient availability, and vegetation succession. Upon permafrost degradation, the release of deep stores of nutrients such as nitrogen and phosphorus from newly thawed permafrost stimulates Arctic vegetation production. More specifically, wetter lowlands show an increase in sedges (as part of graminoids), whereas drier uplands favor shrub expansion. In turn, shifts in the composition of vegetation may influence local mineral element cycling through litter production. In this study, we evaluate the influence of permafrost degradation on mineral element foliar stocks and potential annual fluxes upon litterfall. We measured the foliar elemental composition (Al, Ca, Fe, K, Mn, P, S, Si, and Zn) on ~500 samples of typical tundra vegetation species from two contrasting Alaskan sites, i.e., under experimental (CiPEHR) and ambient (Gradient) warming. The foliar concentration of these mineral elements was species specific, with sedge leaves having relatively high Si concentration, and shrub leaves having relatively high Ca and Mn concentrations. Therefore, changes in the species biomass composition of the Arctic tundra in response to permafrost thaw are expected to be the main factors that dictate changes in elemental composition of foliar stocks and maximum potential foliar fluxes upon litterfall. We observed an increase in the mineral element foliar stocks and potential annual litterfall fluxes, with Si increasing with sedge expansion in wetter sites (CiPEHR), and Ca and Mn increasing with shrub expansion in drier sites (Gradient). Consequently, we expect that sedge and shrub expansion upon permafrost thaw will lead to changes in litter elemental composition, and affect nutrient cycling across the sub-Arctic tundra, with potential implications for further vegetation succession