UC-69 Team 10B BChain

BChain is a new P2P file sharing system that is fully private, anonymous, globally self-verifying, and utilizes an automatic peer-maintained network of trust in data, accomplished through new methods of routing content over the whole network, encrypted, rather than per torrent download. Verification is done by adding file metadata to a blockchain giving the network consistent knowledge of each file it can transfer, and how to verify file received against the network. This enables a policy of zero trust against peers. This system is implemented by an app that interfaces with the network using the protocol, using it for upload, download and file discovery. The interface is built using web technologies, which allows for flexible use across native platforms.Advisors(s): Prof. Ken HogansonTopic(s): IoT/Cloud/NetworkingCS 485

Shallow Water ’06 : a joint acoustic propagation/nonlinear internal wave physics experiment

Author Posting. © Oceanography Society, 2007. This article is posted here by permission of Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 20, 4 (2007): 156-167.Since the end of the Cold War, the US Navy has had an increasing interest in continental shelves and slopes as operational areas. To work in such areas requires a good understanding of ocean acoustics, coastal physical oceanography, and, in the modern era, autonomous underwater vehicle (AUV) operations

Cutaneous Papilloma and Squamous Cell Carcinoma Therapy Utilizing Nanosecond Pulsed Electric Fields (nsPEF)

Nanosecond pulsed electric fields (nsPEF) induce apoptotic pathways in human cancer cells. The potential therapeutic effective of nsPEF has been reported in cell lines and in xenograft animal tumor model. The present study investigated the ability of nsPEF to cause cancer cell death in vivo using carcinogen-induced animal tumor model, and the pulse duration of nsPEF was only 7 and 14 nano second (ns). An nsPEF generator as a prototype medical device was used in our studies, which is capable of delivering 7-30 nanosecond pulses at various programmable amplitudes and frequencies. Seven cutaneous squamous cell carcinoma cell lines and five other types of cancer cell lines were used to detect the effect of nsPEF in vitro. Rate of cell death in these 12 different cancer cell lines was dependent on nsPEF voltage and pulse number. To examine the effect of nsPEF in vivo, carcinogen-induced cutaneous papillomas and squamous cell carcinomas in mice were exposed to nsPEF with three pulse numbers (50, 200, and 400 pulses), two nominal electric fields (40 KV/cm and 31 KV/cm), and two pulse durations (7 ns and 14 ns). Carcinogen-induced cutaneous papillomas and squamous carcinomas were eliminated efficiently using one treatment of nsPEF with 14 ns duration pulses (33/39 = 85%), and all remaining lesions were eliminated after a 2nd treatment (6/39 = 15%). 13.5% of carcinogen-induced tumors (5 of 37) were eliminated using 7 ns duration pulses after one treatment of nsPEF. Associated with tumor lysis, expression of the anti-apoptotic proteins Bcl-xl and Bcl-2 were markedly reduced and apoptosis increased (TUNEL assay) after nsPEF treatment. nsPEF efficiently causes cell death in vitro and removes papillomas and squamous cell carcinoma in vivo from skin of mice. nsPEF has the therapeutic potential to remove human squamous carcinoma

Universal prediction of cell-cycle position using transfer learning.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBackground: The cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data. Results: Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the use of transfer learning. We estimate a cell-cycle embedding using a fixed reference dataset and project new data into this reference embedding, an approach that overcomes key limitations of learning a dataset-dependent embedding. Tricycle then predicts a cell-specific position in the cell cycle based on the data projection. The accuracy of tricycle compares favorably to gold-standard experimental assays, which generally require specialized measurements in specifically constructed in vitro systems. Using internal controls which are available for any dataset, we show that tricycle predictions generalize to datasets with multiple cell types, across tissues, species, and even sequencing assays. Conclusions: Tricycle generalizes across datasets and is highly scalable and applicable to atlas-level single-cell RNA-seq data. Keywords: Cell cycle; Single-cell RNA-sequencing; Transfer learning.Chan Zuckerberg Initiative DAF Silicon Valley Community Foundation United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of General Medical Sciences (NIGMS) Appeared in source as:National Institute of General Medical Sciences of the National Institutes of Health National Science Foundation (NSF) National Institute of Agin Maryland Stem Cell Research Foundation Kavli Neurodiscovery Institute Johns Hopkins Provost Award Program BRAIN Initiative United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute of Neurological Disorders & Stroke (NINDS) Appeared in source as:National Institute of Neurological Disorder

Inflammatory Markers in Schizophrenia: Comparing Antipsychotic Effects in Phase 1 of the CATIE Schizophrenia Trial

C-reactive protein (CRP), intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1) and E-selectin are systemic inflammatory markers (IM) that positively correlate with cardiovascular (CV) risk. Despite the known CV effects of atypical antipsychotics, there is limited prospective data on IM changes during treatment

Impact of antipsychotic treatment on nonfasting triglycerides in the CATIE Schizophrenia Trial phase 1

Recent literature documents a stronger association between nonfasting triglycerides (TG) and cardiovascular risk compared to fasting TG. Given concerns over antipsychotic effects on serum TG, this analysis explored changes in nonfasting TG in phase 1 of the CATIE Schizophrenia Trial

Antipsychotic effects on estimated 10-year coronary heart disease risk in the CATIE schizophrenia study

Persons with schizophrenia die earlier than the general population, in large part due to cardiovascular disease. The study objective was to examine effects of different antipsychotic treatments on estimates of 10 year coronary heart disease (CHD) risk calculated by the Framingham Heart Study formula

Change in metabolic syndrome parameters with antipsychotic treatment in the CATIE Schizophrenia Trial: Prospective data from phase 1

The metabolic syndrome (MS) is associated with increased risk for diabetes mellitus and coronary heart disease, and is highly prevalent among schizophrenia patients. Given concerns over antipsychotic metabolic effects, this analysis explored MS status and outcomes in phase 1 of the CATIE Schizophrenia Trial