gebhart/patrepeval huggingface dataset:
Antibody-Derived<i>In Vivo</i>Imaging of Tau Pathology (2014)

Antibodies or their derivatives as imaging probes for pathological tau protein have great potential, but have not been well studied. In particular, smaller, single-chain-variable antibody fragments (scFv's) are attractive for detecting tau lesions in live subjects. Here, we generated libraries of scFv's and identified numerous phospho-tau-selective scFv's. Peripheral injection of one of these scFv's consistently resulted in a strong in vivo brain signal in transgenic tauopathy mice, but not in wild-type or amyloid-β plaque mice. The parent tau antibody provided similar results, albeit with a weaker signal intensity. The imaging signal correlated very well with colocalization of the probe with intraneuronal tau aggregates. Both were associated with markers of endosomes, autophagosomes, and lysosomes, suggesting their interaction in these degradation pathways. Such specific antibody-derived imaging probes have great potential as diagnostic markers for Alzheimer's disease and related tauopathies.
Rapid Diffusion Magnetic Resonance Imaging Using Slice-Interleaved Encoding (2022)

In this paper, we present a robust reconstruction scheme for diffusion MRI (dMRI) data acquired using slice-interleaved diffusion encoding (SIDE). When combined with SIDE undersampling and simultaneous multi-slice (SMS) imaging, our reconstruction strategy is capable of significantly reducing the amount of data that needs to be acquired, enabling high-speed diffusion imaging for pediatric, elderly, and claustrophobic individuals. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume per diffusion wavevector, SIDE acquires in each repetition time (TR) a volume that consists of interleaved slice groups, each group corresponding to a different diffusion wavevector. This strategy allows SIDE to rapidly acquire data covering a large number of wavevectors within a short period of time. The proposed reconstruction method uses a diffusion spectrum model and multi-dimensional total variation to recover full DW images from DW volumes that are slice-undersampled due to unacquired SIDE volumes. We formulate an inverse problem that can be solved efficiently using the alternating direction method of multipliers (ADMM). Experiment results demonstrate that DW images can be reconstructed with high fidelity even when the acquisition is accelerated by 25 folds.
Interference alignment for channel-adaptive waveform modulation (2012)

For communication channels with delay spreads that are longer than the symbol interval, orthogonal frequency-division multiplexing is unusable due to its redundant cyclic prefix. In this regime other techniques are therefore required to deal with inter-symbol interference. In this paper we introduce a new modulation scheme that achieves perfect immunity from inter-symbol interference and perfect diagonalization of the channel. A crucial component of this scheme is interference alignment: portions of the potential inter-symbol interference are arranged to lie in the same output subspace, thereby increasing the number of available interference-free input waveforms.
Facilitation of Benzodiazepine Discontinuation by Melatonin (1999)

Controlled-release melatonin may effectively facilitate discontinuation of benzodiazepine therapy while maintaining good sleep quality.
Treatment of Perchlorate-Contaminated Groundwater Using Highly Selective, Regenerable Ion-Exchange Technologies (2007)

Treatment of perchlorate-contaminated water using highly selective, regenerable ion-exchange and perchlorate-destruction technologies was demonstrated at a field site in California. Four treatment and four regeneration cycles were carried out, and no significant deterioration of resin performance was noted in 2 years. The bifunctional resin (Purolite A-530E) treated about 37,000 empty bed volumes (BVs) of groundwater before a significant breakthrough of perchlorate occurred at an average flow rate of 150 gpm (or 1 BV/min) and a feed perchlorate concentration of about 860 microg/L. Sorbed perchlorate (approximately 20 kg) was quantitatively recovered by eluting with as little as 1 BV of the FeCl3-HCl regenerant solution. The eluted ClO4- was highly concentrated in the third quarter of the first BV of the regenerant solution with a concentration up to 100,000 mg/L. This concentrated effluent greatly facilitated subsequent perchlorate destruction or recovery by precipitation as KClO4 salts. High perchlorate destruction efficiency (92-97%) was observed by reduction with FeCl2 in a thermoreactor, which enabled recycling of the FeCl3-HCl regenerant solution, thereby minimizing the need to dispose of secondary wastes containing ClO4-. This study demonstrates that a combination of novel selective, regenerable ion-exchange and perchlorate-destruction and/or recovery technologies could potentially lead to enhanced treatment efficiency and minimized secondary waste production.
Multi-robot cooperation for human-robot communication (2003)

This paper illustrates how robots can effectively cooperate to facilitate communication with people. We expect that communication robots will play an important role in our daily life. Although these robots can communicate with each other by radio, infrared, or other invisible means, our results show that it is important to human understanding that they are able to communicate with each other by voice and gestures as well. This lets humans know that the robots can talk with them and among themselves. Thus, humans come to regard the robots as appropriate targets for natural communication.
Quantification of plasma DNA as a prognostic indicator in canine lymphoid neoplasia (2007)

Dogs have a similar incidence of spontaneous cancers as people, and a noninvasive test to monitor disease status in dogs would be of great value. Humans with cancer often have increased levels of cell-free circulating DNA in their plasma, which has shown promise for diagnosis, prognosis and detection of residual disease. We hypothesized that dogs with cancer have increased circulating DNA compared with healthy dogs or dogs with non-neoplastic diseases. Plasma DNA was measured in 40 healthy dogs, 20 dogs with non-neoplastic diseases and 80 dogs with cancer. The reference interval for plasma DNA in healthy dogs was 1-15 ng mL(-1). Dogs with lymphoma and lymphoid leukaemia had significantly higher concentrations (range: 0-91 ng mL(-1), P < 0.0001). Antigen receptor rearrangement assays suggest that plasma DNA had the same clonality as the primary lymphoid tumours. Dogs with lymphoid neoplasia and plasma DNA >25 ng mL(-1) had shorter remission times than those with < 25 ng mL(-1) (P = 0.0116). In contrast to humans, where increased plasma DNA is seen in many diseases, dogs with nonlymphoid malignancies and non-neoplastic diseases had plasma DNA concentrations similar to healthy dogs. This study shows that a portion of dogs with lymphoid neoplasia have increased tumour-derived plasma DNA, which serves as a negative prognostic indicator.
Production of galactose oxidase by Gibberella fujikuroi. (1981)

The distribution of galactose oxidase was investigated among microorganisms. Gibberella fujikuroi excreted a large amount of the enzyme into the culture medium. A study of the cultural conditions of this organism for enzyme formation showed that galactose oxidase production required copper. Copper was found to play a role, not only in the conversion of apoenzyme to holoenzyme, but also in regulation of the biosynthesis of galactose oxidase protein.
Development of an optically-based tension-indicating implanted orthopedic screw with a luminescent spectral ruler (2017)

An orthopaedic screw was designed with an optical tension-indicator to non-invasively quantify screw tension and monitor the load sharing between the bone and the implant. The screw both applies load to the bone, and measures this load by reporting the strain on the screw. The screw contains a colorimetric optical encoder that converts axial strain into colorimetric changes visible through the head of the screw, or luminescent spectral changes that are detected through tissue. Screws were tested under cyclic mechanical loading to mimic in-vivo conditions to verify the sensitivity, repeatability, and reproducibility of the sensor. In the absence to tissue, color was measured using a digital camera as a function of axial load on a stainless steel cannulated (hollow) orthopedic screw, modified by adding a passive colorimetric strain gauge through the central hole. The sensor was able to quantify clinically-relevant bone healing strains. The sensor exhibited good repeatability and reproducibility but also displayed hysteresis due to the internal mechanics of the screw. The strain indicator was also modified for measurement through tissue by replacing the reflective colorimetric sensor with a low-background X-ray excited optical luminescence signal. Luminescent spectra were acquired through 6 mm of chicken breast tissue. Overall, this research shows feasibility for a unique device which quantifies the strain on an orthopedic screw. Future research will involve reducing hysteresis by changing the mechanism of strain transduction in the screw, miniaturizing the luminescent strain gauge, monitoring bending as well as tension, using alternative luminescent spectral rulers based upon near infrared fluorescence or upconversion luminescence, and application to monitoring changes in pretension and load sharing during bone healing.
Distributed location detection in wireless sensor networks (2013)

A distributed location detection problem in wireless sensor networks (WSNs) with M anchors and one node is considered in this paper. In the presence of the transmitting node at a known location, each anchor receives a noisy signal in the presence of node. In the absence of the node, the anchors receive only noise. Each anchor makes a decision as to whether the node is present or not by using a Neyman-Pearson detector. The bit denoting the decision is transmitted to a fusion center (FC). If an anchor detects the node, a bit “1” will be sent; otherwise, a bit “0” will be sent. The FC will count the number of “1”s and “0”s, and declares the node present if it receives at least K “1”s from the anchors, where K ≤ M is a design parameter. We also consider the case of detecting a node in a known region, and detecting one node of interest with multiple interfering nodes. In comparison to the centralized location detection scheme, the distributed scheme benefits from both time and energy efficiency. Simulation results show that the choice of K depends on the requirement of the overall probability of false alarm.
Chlorine Gas Recovery from Waste PVC through CaCl<sub>2</sub>Reaction between Molten CaCl<sub>2</sub> and Oxygen Gas (2003)

Chlorine gas evolution was investigated by bubbling O2 gas into molten CaCl2 at temperatures higher than 1173 K, although a thermodynamic analysis shows almost no progress of the reaction 2CaCl2 + O2 = 2CaO + Cl2. To break the thermodynamic limitation, chlorine gas slightly evolved was quickly removed from the reactor by flowing O2. From the data obtained at the early stage of reaction, the rate equation for Cl2 evolution was determined to be d[Cl2]/dt = k(PO2)n/ (1 + k‘[CaO]), where 0.7 < n <0.9, with an activation energy of 157.6 kJ/mol. Upon prolonged reaction, the rate of Cl2 evolution rapidly decreased because of the progress of the reverse reaction between Cl2 and CaO generated during the reaction. Through the addition of silica powder into molten CaCl2, the rapid decrease in the Cl2 evolution rate on prolonged reaction was significantly moderated: about 60% of the Cl ions contained in the CaCl2 were recovered as Cl2 gas. This is due to the reaction of SiO2 with CaO to form calcium silicate, which is less reactive with Cl2 gas.
Novel Gene Expression Signature Predictive of Clinical Recurrence After Radical Prostatectomy in Early Stage Prostate Cancer Patients (2016)

We report a novel gene-expression based classifier identified using agnostic approaches from whole genome expression profiles that can improve upon the accuracy of clinical indicators to stratify early stage localized patients at risk of clinical recurrence after RP. Prostate 76:1239-1256, 2016. © 2016 Wiley Periodicals, Inc.
Code compression using variable-to-fixed coding based on arithmetic coding (2003)

Embedded computing systems are space and cost sensitive. Memory is one of the most restricted resources that post serious constraints on program size. Code compression, which is a special case of data compression where the input source is in machine instructions, has been proposed as a solution to this problem. Previous work in code compression has focused on either fixed-to-variable coding or dictionary-based algorithms. Code compression schemes that use variable-to-fixed (V2F) length coding were proposed, based on arithmetic coding. Experiments have shown that the compression ratio, using memoryless V2F coding for the TMS320C6x processor, have an average of 82.5% and decompression can be parallelized. A Markov-based V2F coding based on arithmetic coding has achieved an average compression ratio of 72% for TMS320C6x while decompression cannot be parallelized. Furthermore, the given experiments have shown that arithmetic coding based V2F coding has similar compression performance to Tunstall coding. Finally, a power reduction scheme for the instruction bus using the V2F coding scheme was presented.
Representation theory for high-rate multiple-antenna code design (2001)

Multiple antennas can greatly increase the data rate and reliability of a wireless communication link in a fading environment, but the practical success of using multiple antennas depends crucially on our ability to design high-rate space-time constellations with low encoding and decoding complexity. It has been shown that full transmitter diversity, where the constellation is a set of unitary matrices whose differences have nonzero determinant, is a desirable property for good performance. We use the powerful theory of fixed-point-free groups and their representations to design high-rate constellations with full diversity. Furthermore, we thereby classify all full-diversity constellations that form a group, for all rates and numbers of transmitter antennas. The group structure makes the constellations especially suitable for differential modulation and low-complexity decoding algorithms. The classification also reveals that the number of different group structures with full diversity is very limited when the number of transmitter antennas is large and odd. We, therefore, also consider extensions of the constellation designs to nongroups. We conclude by showing that many of our designed constellations perform excellently on both simulated and real wireless channels.
Ultralarge Modulation of Fluorescence by Neuromodulators in Carbon Nanotubes Functionalized with Self-Assembled Oligonucleotide Rings (2018)

Noncovalent interactions between single-stranded DNA (ssDNA) oligonucleotides and single wall carbon nanotubes (SWNTs) have provided a unique class of tunable chemistries for a variety of applications. However, mechanistic insight into both the photophysical and intermolecular phenomena underlying their utility is lacking, which results in obligate heuristic approaches for producing ssDNA-SWNT based technologies. In this work, we present an ultrasensitive "turn-on" nanosensor for neuromodulators dopamine and norepinephrine with strong relative change in fluorescence intensity (Δ F/ F<sub>0</sub>) of up to 3500%, a signal appropriate for in vivo neuroimaging, and uncover the photophysical principles and intermolecular interactions that govern the molecular recognition and fluorescence modulation of this nanosensor synthesized from the spontaneous self-assembly of (GT)<sub>6</sub> ssDNA rings on SWNTs. The fluorescence modulation of the ssDNA-SWNT conjugate is shown to exhibit remarkable sensitivity to the ssDNA sequence chemistry, length, and surface density, providing a set of parameters with which to tune nanosensor dynamic range, analyte selectivity and strength of fluorescence turn-on. We employ classical and quantum mechanical molecular dynamics simulations to rationalize our experimental findings. Calculations show that (GT)<sub>6</sub> ssDNA form ordered rings around (9,4) SWNTs, inducing periodic surface potentials that modulate exciton recombination lifetimes. Further evidence is presented to elucidate how dopamine analyte binding modulates SWNT fluorescence. We discuss the implications of our findings for SWNT-based molecular imaging applications.
Data from Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning–Assisted Gland Analysis (2023)

<div>Abstract<p>Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dimensional (3D) glandular structures via visual inspection of a limited number of two-dimensional (2D) histology sections is often unreliable, which contributes to the under- and overtreatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for nondestructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analogue of standard hematoxylin and eosin (H&E) staining. This analysis is based on interpretable glandular features and is facilitated by the development of image translation–assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep learning–based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring immunolabeling. As a preliminary demonstration of the translational value of a computational 3D versus a computational 2D pathology approach, we imaged 300 <i>ex vivo</i> biopsies extracted from 50 archived radical prostatectomy specimens, of which, 118 biopsies contained cancer. The 3D glandular features in cancer biopsies were superior to corresponding 2D features for risk stratification of patients with low- to intermediate-risk prostate cancer based on their clinical biochemical recurrence outcomes. The results of this study support the use of computational 3D pathology for guiding the clinical management of prostate cancer.</p>Significance:<p>An end-to-end pipeline for deep learning–assisted computational 3D histology analysis of whole prostate biopsies shows that nondestructive 3D pathology has the potential to enable superior prognostic stratification of patients with prostate cancer.</p></div>
An iterative interpolative transform method for modeling harmonic magnitudes (2003)

In this paper, we describe a method for modeling speech harmonic magnitudes, the accurate representation of which is essential for high quality speech synthesis in several parametric vocoders. The given set of harmonic magnitudes is interpolated and transformed into the auto-correlation domain before an all-pole model is derived. Through an iterative procedure, the interpolation curve used in the frequency domain is improved. This new iterative, interpolative, transform (IIT) method has been found to model the harmonic magnitudes more accurately than earlier methods when measured in terms of log-spectral distortion.
Deep learning for high-quality imaging and accurate classification of cells through Anderson localizing optical fiber (2021)

We demonstrate highly accurate and fast cell imaging and classification systems enabled by the combination of disordered optical fiber for data transport and deep convolutional neural networks (DCNNs) for data analysis. Disordered optical fiber feature unique light transport properties based on the principle of transverse Anderson localization. A dense network of single mode-like transmission channels results in high spatial resolution while providing robustness regarding bending and environmental changes. DCNNs optimized for cell image reconstruction or cell classification have been trained and applied to perform rigorous testing. We show artifact-free real-time image reconstruction and >90% correct classification of cell samples.
Automated Selection of Statistical Quality-Control Procedures to Assure Meeting Clinical or Analytical Quality Requirements (1997)

Efforts to totally automate laboratory testing processes must address the issue of how to assure the quality of the final test result. A recent survey by Tetrault and Steindel (1) reported that laboratories are using the same quality-control (QC) procedures today that they used 10 years ago. Actually, more than half of the laboratories indicated they are still using control limits set as the mean ± 2s (the 12s rule), a practice that dates to the 1950s and ’60s (2)(3), when statistical QC was first used with manual methods and the first generation of automated Technicon AutoAnalyzer systems. Other laboratories indicated they are using variations of the multirule type of QC procedure introduced in the early 1980s (4).

Tetrault and Steindel (1) recommend that “the best set of control rules will vary from method to method and cannot be determined through simple algorithms or formulas. The laboratorian has to balance true error-detection capabilities against the probabilities of falsely rejecting a good run.” The information needed about the error-detection and false-rejection characteristics of stable QC procedures became available in the clinical chemistry literature almost 20 years ago (5)(6)(7)(8) and was extended by Cembrowski et al. (9)(10)(11)(12) to consider patient data algorithms. This information was incorporated into laboratory QC texts (13)(14) and clinical chemistry texts (15)(16) in the 1990s and continues to be expanded and improved by Parvin (17)(18)(19)(20) and by Smith and Kroft (21).

Guidelines and strategies for selecting QC procedures were described in 1986 (13), and some detailed applications have been published to demonstrate the selection and design of QC procedures (22)(23)(24). QC selection grids were introduced in 1990 …
Commonly Occurring Cell Subsets in High-Grade Serous Ovarian Tumors Identified by Single-Cell Mass Cytometry (2018)

We have performed an in-depth single-cell phenotypic characterization of high-grade serous ovarian cancer (HGSOC) by multiparametric mass cytometry (CyTOF). Using a CyTOF antibody panel to interrogate features of HGSOC biology, combined with unsupervised computational analysis, we identified noteworthy cell types co-occurring across the tumors. In addition to a dominant cell subset, each tumor harbored rarer cell phenotypes. One such group co-expressed E-cadherin and vimentin (EV), suggesting their potential role in epithelial mesenchymal transition, which was substantiated by pairwise correlation analyses. Furthermore, tumors from patients with poorer outcome had an increased frequency of another rare cell type that co-expressed vimentin, HE4, and cMyc. These poorer-outcome tumors also populated more cell phenotypes, as quantified by Simpson's diversity index. Thus, despite the recognized genomic complexity of the disease, the specific cell phenotypes uncovered here offer a focus for therapeutic intervention and disease monitoring.
GPU triggered networking for intra-kernel communications (2017)

GPUs are widespread across clusters of compute nodes due to their attractive performance for data parallel codes. However, communicating between GPUs across the cluster is cumbersome when compared to CPU networking implementations. A number of recent works have enabled GPUs to more naturally access the network, but suffer from performance problems, require hidden CPU helper threads, or restrict communications to kernel boundaries.