gebhart/patrepeval huggingface dataset:
Optimized Monophasic Pulses with Equivalent Electric Field for Rapid-Rate Transcranial Magnetic Stimulation (2022)

Abstract Objective Transcranial magnetic stimulation (TMS) with monophasic pulses achieves greater changes in neuronal excitability but requires higher energy and generates more coil heating than TMS with biphasic pulses, and this limits the use of monophasic pulses in rapid-rate protocols. We sought to design a stimulation waveform that retains the characteristics of monophasic TMS but significantly reduces coil heating, thereby enabling higher pulse rates and increased neuromodulation effectiveness. Approach A two-step optimization method was developed that uses the temporal relationship between the electric field (E-field) and coil current waveforms. The model-free optimization step reduced the ohmic losses of the coil current and constrained the error of the E-field waveform compared to a template monophasic pulse, with pulse duration as a second constraint. The second, amplitude adjustment step scaled the candidate waveforms based on simulated neural activation to account for differences in stimulation thresholds. The optimized waveforms were implemented to validate the changes in coil heating. Main results Depending on the pulse duration and E-field matching constraints, the optimized waveforms produced 12% to 75% less heating than the original monophasic pulse. The reduction in coil heating was robust across a range of neural models. The changes in the measured ohmic losses of the optimized pulses compared to the original pulse agreed with numeric predictions. Significance The first step of the optimization approach was independent of any potentially inaccurate or incorrect model and exhibited robust performance by avoiding the highly nonlinear behavior of neural responses, whereas neural simulations were only run once for amplitude scaling in the second step. This significantly reduced computational cost compared to iterative methods using large populations of candidate solutions and more importantly reduced the sensitivity to the choice of neural model. The reduced coil heating and power losses of the optimized pulses can enable rapid-rate monophasic TMS protocols.
Increased angiotensin-converting enzyme activity in essential hypertension. (1990)

We compared the activities in serum of 12 kinds of proteases including renin, angiotensin-converting enzyme, aminopeptidases, kallikrein, and other endopeptidases, between control subjects and patients with essential hypertension. In the patients, the activity of angiotensin-converting enzyme was increased by more than two times, although the activities of most of other proteases were significantly decreased, when compared with the age-matched controls. A multivariate study using discriminant function analysis suggested that angiotensin-converting enzyme plays an important role in the protease changes in the patients. The results altogether indicate that the pathogenesis of essential hypertension is closely related to an imbalance between vasoconstrictive and vasodilatative peptides such as angiotensins and kinins.
Boosting multi-feature visual texture classiffiers for the authentication of Jackson Pollock's drip paintings (2011)

Early attempts at authentication Jackson Pollock's drip paintings based on computer image analysis were restricted to a single "fractal" or "multi-fractal" visual feature, and achieved classification nearly indistinguishable from chance. Irfan and Stork pointed out that such Pollock authentication is an instance of visual texture recognition, a large discipline that universally relies on multiple visual features, and showed that modest, but statistically significant improvement in recognition accuracy can be achieved through the use of multiple features. Our work here extends such multi-feature classification by training on more image data and images of higher resolution of both genuine Pollocks and fakes. We exploit methods for feature extraction, feature selection and classiffier techniques commonly used in pattern recognition research including Support Vector Machines (SVM), decision trees (DT), and AdaBoost. We extract features from the fractality, multifractality, pink noise patterns, topological genus, and curvature properties of the images of candidate paintings, and address learning issues that have arisen due to the small number of examples. In our experiments, we found that the unmodified classiffiers like Support Vector Machines or Decision Tree alone give low accuracies (60%), but that statistical boosting through AdaBoost leads to accuracies of nearly 75%. Thus, although our set of observations is very small, we conclude that boosting methods can improve the accuracy of multi-feature classiffication of Pollock's drip paintings.
Preemptive T-Rapa Cell DLI after Low Intensity Allogeneic HCT May Allow for Improved Overall Survival in High Risk Lymphoid Malignancies (2016)

characterizing the effector (cytolytic capacity) profile of the expanded cells, and plan to map immunodominant T cell epitopes. Finally, to verify the importance of T cell immunity in providing in vivo protection against PIV-3 we isolated blood from 2 post-HSCT recipients who naturally controlled their infections and in both cases, detected an amplification of endogenous T cells directed to M, HN, N, F and PC coincident with viral clearance. Thus, we have demonstrated the feasibility of generating PIV-3-directed VSTs in vitro and have preliminary evidence demonstrating the protective capacity of reactive cells in vivo. Our ultimate goal is to develop an immune-based therapy for allogeneic HSCT recipients with active infections whose endogenous immunity is lacking.
Delay Versus Deviance in the Language Acquisition of Language-Impaired Children (1992)

To investigate the issue of delay versus deviance in the language acquisition of language-impaired (LI) children, the order of acquisition of a set of linguistic structures and the relationship obtaining between one structure and another were examined in comprehension and production over a 5-year period in a group of LI and language-matched normal children. The results demonstrated a marked similarity between groups, both in the point at which mastery of individual structures was achieved and in the overall patterns of acquisition demonstrated. These data suggest that LI children are constructing grammars based on the same rules and principles as those of linguistically normal control subjects, and that their linguistic impairments may be principally processing, not representational, in nature.
Comparison between a lyse-and-then-wash method and a lyse-non-wash technique for the enumeration of CD34+ hematopoietic progenitor cells (1998)

The flow cytometric enumeration of CD34+ hemopoietic precursor cells (HPC) present in samples used for transplantation of HPC has proven to be the most powerful single parameter for prediction of engraftment. At present, several different methodological approaches are used for the flow cytometric enumeration of CD34+ HPC. In the present study we have compared two of these methods as regards enumeration of CD34+ HPC and their CD34+/CD19- and CD34+/CD19+ subsets: a lyse-non-wash procedure based on the use of a recently commercialized red cell lysing solution (Quicklysis, Cytognos, Salamanca, Spain) and a lyse-and-then-wash method in which the Becton Dickinson (San Jose, CA) FACS Lysing Solution was used. For that purpose a total of 52 samples corresponding to 20 G-CSF mobilized peripheral blood (PB) samples and 21 PB-derived leucapheresis products from patients undergoing autologous PB stem cell harvest, together with 11 bone marrow (BM) samples from healthy volunteers were analyzed. Our results show that for each of the three types of samples analyzed the use of the lyse-and-then-wash method is associated with significantly lower numbers of both total CD34+ HPC (P < or = 0.003) and its major CD34+/CD19- subset (P < or = 0.01) while no significant changes are detected in the number of CD34+/CD19+ HPC in BM samples (P > 0.05). The use of an internal standard (reference beads) added just prior to data acquisition, showed that the differences between both methods are due to a selective loss of CD34+ HPC and its major CD34+/CD19- subset in BM (P=0.002 and P=0.003), PB (P < 0.0001 and P < 0.0001) and PB-derived leucapheresis products (P < 0.0001 and P=0.0001). Finally, addition of a centrifugation and washing step to a group of 11 leucapheresis samples lysed with Quicklysis showed that they did not significantly affect the overall number of total CD34+, CD34+/CD19- and CD34+/CD19+ HPC obtained. In line with these findings elimination of centrifugation and washing steps when FACS Lysing Solution was used to lyse mature red cells almost corrected for the selective loss of CD34+ HPC. In spite of these differences a significant degree of correlation (r > 0.83 in all cases) was found between both methods regarding the total number of CD34+, CD34+/CD19- and CD34+/CD19+ HPC present in the BM, PB and PB-derived leucapheresis samples analyzed in this study.
The Ebolavirus VP24 Protein Blocks Phosphorylation of p38 Mitogen-Activated Protein Kinase (2011)

Type I interferon (IFN) signaling is mediated through several signaling pathways, including the Janus kinase and signal transducer and activator (JAK-STAT) and p38 mitogen-activated protein (MAP) kinase pathways. The VP24 protein of Ebolavirus is an IFN antagonist, blocking type I IFN signaling through the JAK-STAT pathway. Here, we show that, in 293 cells, VP24 also interferes with the p38 MAP kinase pathway by blocking IFN-β-stimulated phosphorylation of p38-α. Similar inhibition was not observed in HeLa cells, suggesting cell type-specific differences in signal transduction.
Commentary: Chronic PD-1 Checkpoint Blockade Does Not Affect Cognition or Promote Tau Clearance in a Tauopathy Mouse Model (2020)

GENERAL COMMENTARY article Front. Aging Neurosci., 13 May 2020Sec. Parkinson’s Disease and Aging-related Movement Disorders Volume 12 - 2020 | https://doi.org/10.3389/fnagi.2020.00135
Translation Acquisition Using Synonym Sets (2013)

We propose a new method for translation ac-quisition which uses a set of synonyms to ac-quire translations from comparable corpora. The motivation is that, given a certain query term, it is often possible for a user to specify one or more synonyms. Using the resulting set of query terms has the advantage that we can overcome the problem that a single query term’s context vector does not always reliably represent a terms meaning due to the context vector’s sparsity. Our proposed method uses a weighted average of the synonyms ’ context vectors, that is derived by inferring the mean vector of the von Mises-Fisher distribution. We evaluate our method, using the synsets from the cross-lingually aligned Japanese and English WordNet. The experiments show that our proposed method significantly improves translation accuracy when compared to a pre-vious method for smoothing context vectors. 1
Analysis of generalized processor-sharing systems with two classes of customers and exponential services (2004)

We derive in this paper closed formulae for the joint probability generating function of the number of customers in the two FIFO queues of a generalized processor-sharing (GPS) system with two classes of customers arriving according to Poisson processes and requiring exponential service times. In contrast to previous studies published on the GPS system, we show that it is possible to establish explicit expressions for the generating functions of the number of customers in each queue without calling for the formulation of a Riemann–Hilbert problem. We specifically prove that the problem of determining the unknown functions due to the reflecting conditions on the boundaries of the positive quarter plane can be reduced to a Poisson equation. The explicit formulae are then used to derive some characteristics of the GPS system (in particular the tails of the probability distributions of the numbers of customers in each queue).
Gold Nanoparticles/Carbon Nanotubes and Gold Nanoporous as Novel Electrochemical Platforms for L-Ascorbic Acid Detection: Comparative Performance and Application (2021)

Herein, the effects of nanostructured modifications of a gold electrode surface in the development of electrochemical sensors for L-ascorbic acid detection have been investigated. In particular, a bare gold electrode has been modified by electrodeposition of gold single-walled carbon nanotubes (Au/SWCNTs) and by the formation of a highly nanoporous gold (h-nPG) film. The procedure has been realized by sweeping the potential between +0.8 V and 0 V vs. Ag/AgCl for 25 scans in a suspension containing 5 mg/mL of SWCNTs in 10 mM HAuCl4 and 2.5 M NH4Cl solution for Au/SWCNTs modified gold electrode. A similar procedure was applied for a h-nPG electrode in a 10 mM HAuCl4 solution containing 2.5 M NH4Cl, followed by applying a fixed potential of −4 V vs. Ag/AgCl for 60 s. Cyclic voltammetry and electrochemical impedance spectroscopy were used to characterize the properties of the modified electrodes. The developed sensors showed strong electrocatalytic activity towards ascorbic acid oxidation with enhanced sensitivities of 1.7 × 10−2 μA μM−1cm−2 and 2.5 × 10−2 μA μM−1cm−2 for Au/SWCNTs and h-nPG modified electrode, respectively, compared to bare gold electrode (1.0 × 10−2 μA μM−1cm−2). The detection limits were estimated to be 3.1 and 1.8 μM, respectively. The h-nPG electrode was successfully used to determine ascorbic acid in human urine with no significant interference and with satisfactory recovery levels.
Micro-RNA signature differences in lung adenocarcinoma with specific driver alterations. (2013)

11066 Background: Oncogenic driving alterations define types of lung adenocarcinoma with different prognosis and sensitivity to targeted agents. MicroRNAs (miRNAs) are a new class of non-coding RNAs involved in gene expression regulation. How miRNAs are dysregulated in lung cancer with ALK translocation, EGFR or KRAS mutation is unknown. In this study we aimed to identify miRNA signatures according to the presence of specific driver and to correlate miRNAs deregulation with patient outcome. Methods: The study was conducted in a cohort of 70 lung cancer patients (pts) including 18 ALK+ tumors, 11 ALK-/EGFR mutation+, 15 ALK-/KRAS mutation+, 26 ALK-/EGFR and KRAS wild-type and defined as triple negative. Matched normal lung tissue from 18 cases representative of the entire cohort were also included onto the analysis. RNA was isolated from formalin-fixed paraffin-embedded tissue (FFPE), using the Recover ALL kit (Ambion). NanoString nCounter system platform was used to generate the miRNA profile. We used Limma to test for differential expression analysis of data. The miR-515 family expression between tissues was validated by RT-qPCRs, analyzed using the parametric t-test (unpaired, 2-tailed for validation). Results: miRNA expression profile clusters distinctly ALK+ pts from ALK- and normal lung tissue. Within the ALK- group we found specific miRNAs subsets able to sub-stratify KRAS versus EGFR careers clustering sharply triple negative versus EGFR mutation+ and triple negative versus KRAS mutation+. miRNAs belonging to the miR-515 family seems to be the most deregulated in the ALK+ versus ALK-. Although their expression is stably high in normal tissues and ALK+ class, they are highly downregulated in KRAS mutated versus EGFR mutated and versus triple negative (p-value &lt;0.001 for all comparisons). Conclusions: miRNAs profile significantly differs in pts with ALK translocation, EGFR mutations and KRAS mutations. Analysis of miR-515 family members is ongoing in order to correlate their expression levels with pts’ outcome. In vitro modulation of miR-515 family expression levels, together with drugs treatment are ongoing in order to find possible chemo-resistance/chemo-sensitivity miRNA dependent, in ALK+ and ALK- model.
Cooperative Adsorption of Carbon Disulfide in Diamine-Appended Metal– Organic Frameworks (2018)

&lt;p&gt;Over one million tons of carbon disulfide are produced globally each year for an array of applications, and emissions of this highly volatile and toxic liquid, known to generate acid rain, remain poorly controlled. As such, materials capable of reversibly capturing this commodity chemical in an energy-efficient manner are of interest. Recently, we detailed a family of diamine-appended metal–organic frameworks capable of selectively capturing carbon dioxide through a cooperative insertion mechanism that promotes efficient adsorption–desorption cycling. We therefore sought to explore the fundamental ability of these materials to capture CS&lt;sub&gt;2 &lt;/sub&gt;through a similar mechanism. Employing crystallography, spectroscopy, and gas adsorption analysis, we demonstrate that CS&lt;sub&gt;2&lt;/sub&gt; is indeed cooperatively adsorbed in &lt;i&gt;N,N&lt;/i&gt;-dimethylethylenediamine-appended M&lt;sub&gt;2&lt;/sub&gt;(dobpdc) (M = Mg, Mn, Zn; dobpdc&lt;sup&gt;4− &lt;/sup&gt;= 4,4′-dioxidobiphenyl-3,3′-dicarboxylate), via the formation of electrostatically paired ammonium dithiocarbamate chains. Notably, in the weakly thiophilic Mg congener, chemisorption is cleanly reversible with mild thermal input. Importantly, this work demonstrates that the hitherto CO&lt;sub&gt;2&lt;/sub&gt;-specific cooperative insertion mechanism can be generalized to other high-impact target molecules.&lt;/p&gt;
Tethys: Collecting Sensor Data without Infrastracture or Trust (2018)

Careful resource monitoring is necessary to understand usage patterns and set conservation goals in an institutional setting. Sensor systems provide data to measure consumption and evaluate the effectiveness of active interventions. However, deploying sensing systems can be difficult when infrastructure support is limited. This paper describes the process of designing Tethys, a wireless water flow sensor that collects data at per-fixture granularity without dependence on existing infrastructure and trusted gateways. Rather than rely on electrical infrastructure, Tethys implements energy harvesting to allow for long term deployment. To avoid dependence on existing network infrastructure, Tethys crowdsources the data collection process to residents' smartphones acting as gateways. These gateways are untrusted and unreliable, so Tethys implements end-to-end reliability and security between the sensing device and a cloud backend. We present initial findings from a deployment in undergraduate residential halls. Our results demonstrate that Tethys can capture meaningful patterns in shower use. For instance, visible water conservation signs are statistically correlated with shorter mean shower length (p <; 0:05) and are a potential area for future studies.
Exploring Proteomes of Robust Yarrowia lipolytica Isolates Cultivated in Biomass Hydrolysate Reveals Key Processes Impacting Mixed Sugar Utilization, Lipid Accumulation, and Degradation (2021)

Yarrowia lipolytica is an oleaginous yeast exhibiting robust phenotypes beneficial for industrial biotechnology. The phenotypic diversity found within the undomesticated Y. lipolytica clade from various origins illuminates desirable phenotypic traits not found in the conventional laboratory strain CBS7504 (or W29), which include xylose utilization, lipid accumulation, and growth on undetoxified biomass hydrolysates. Currently, the related phenotypes of lipid accumulation and degradation when metabolizing nonpreferred sugars (e.g., xylose) associated with biomass hydrolysates are poorly understood, making it difficult to control and engineer in Y. lipolytica. To fill this knowledge gap, we analyzed the genetic diversity of five undomesticated Y. lipolytica strains and identified singleton genes and genes exclusively shared by strains exhibiting desirable phenotypes. Strain characterizations from controlled bioreactor cultures revealed that the undomesticated strain YB420 used xylose to support cell growth and maintained high lipid levels, while the conventional strain CBS7504 degraded cell biomass and lipids when xylose was the sole remaining carbon source. From proteomic analysis, we identified carbohydrate transporters, xylose metabolic enzymes, and pentose phosphate pathway proteins stimulated during the xylose uptake stage for both strains. Furthermore, we distinguished proteins involved in lipid metabolism (e.g., lipase, NADPH generation, lipid regulators, and β-oxidation) activated by YB420 (lipid maintenance phenotype) or CBS7504 (lipid degradation phenotype) when xylose was the sole remaining carbon source. Overall, the results relate genetic diversity of undomesticated Y. lipolytica strains to complex phenotypes of superior growth, sugar utilization, lipid accumulation, and degradation in biomass hydrolysates. <b>IMPORTANCE</b> Yarrowia lipolytica is an important industrial oleaginous yeast due to its robust phenotypes for effective conversion of inhibitory lignocellulosic biomass hydrolysates into neutral lipids. While lipid accumulation has been well characterized in this organism, its interconnected lipid degradation phenotype is poorly understood during fermentation of biomass hydrolysates. Our investigation into the genetic diversity of undomesticated Y. lipolytica strains, coupled with detailed strain characterization and proteomic analysis, revealed metabolic processes and regulatory elements conferring desirable phenotypes for growth, sugar utilization, and lipid accumulation in undetoxified biomass hydrolysates by these natural variants. This study provides a better understanding of the robust metabolism of Y. lipolytica and suggests potential metabolic engineering strategies to enhance its performance.
Learning binary or real-valued time-series via spike-timing dependent plasticity (2016)

A dynamic Boltzmann machine (DyBM) has been proposed as a model of a spiking neural network, and its learning rule of maximizing the log-likelihood of given time-series has been shown to exhibit key properties of spike-timing dependent plasticity (STDP), which had been postulated and experimentally confirmed in the field of neuroscience as a learning rule that refines the Hebbian rule. Here, we relax some of the constraints in the DyBM in a way that it becomes more suitable for computation and learning. We show that learning the DyBM can be considered as logistic regression for binary-valued time-series. We also show how the DyBM can learn real-valued data in the form of a Gaussian DyBM and discuss its relation to the vector autoregressive (VAR) model. The Gaussian DyBM extends the VAR by using additional explanatory variables, which correspond to the eligibility traces of the DyBM and capture long term dependency of the time-series. Numerical experiments show that the Gaussian DyBM significantly improves the predictive accuracy over VAR.
Reduced graphene oxide films used as matrix of MALDI-TOF-MS for detection of octachlorodibenzo-p-dioxin (2010)

A reduced graphene oxide (rGO) film was used as the matrix in the matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy (MALDI-TOF-MS) for the detection of octachlorodibenzo-p-dioxin (OCDD) with a detection weight as low as 500 pg.