gebhart/patrepeval huggingface dataset:
<i>In Vitro</i> and <i>In Vivo</i> Activities of Three Oxazolidinones against Nonreplicating Mycobacterium tuberculosis (2014)

Oxazolidinones represent a new class of antituberculosis drugs that exert their function by inhibiting protein synthesis. Here, we compared the activities of three oxazolidinones, linezolid, PNU-100480, and AZD5847, against latent tuberculosis using a simple model employing the streptomycin-starved Mycobacterium tuberculosis strain 18b. The in vitro drug susceptibility results showed that the three oxazolidinones had a bacteriostatic effect against actively growing bacilli but potent bactericidal activity against nonreplicating cells. In the murine model of latent infection with M. tuberculosis 18b, the efficacy of the three compounds varied greatly. Indeed, AZD5847 or its prodrug exhibited no activity or only modest activity, respectively, after 2 months of treatment, whereas both linezolid and PNU-100480 were effective against latent bacilli in mice and showed promising outcomes in combination therapy with rifampin. Moreover, the potency of PNU-100480 was significantly greater than that of linezolid, making it an attractive drug candidate in the development of new combination therapies for latent tuberculosis.
Ivosidenib or enasidenib combined with intensive chemotherapy in patients with newly diagnosed AML: a phase 1 study (2020)

Ivosidenib (AG-120) and enasidenib (AG-221) are targeted oral inhibitors of the mutant isocitrate dehydrogenase (mIDH) 1 and 2 enzymes, respectively. Given their effectiveness as single agents in mIDH1/2 relapsed or refractory acute myeloid leukemia (AML), this phase 1 study evaluated the safety and efficacy of ivosidenib or enasidenib combined with intensive chemotherapy in patients with newly diagnosed mIDH1/2 AML. Ivosidenib 500 mg once daily and enasidenib 100 mg once daily were well tolerated in this setting, with safety profiles generally consistent with those of induction and consolidation chemotherapy alone. The frequency of IDH differentiation syndrome was low, as expected given the concurrent administration of cytotoxic chemotherapy. In patients receiving ivosidenib, the frequency and grades of QT interval prolongation were similar to those observed with ivosidenib monotherapy. Increases in total bilirubin were more frequently observed in patients treated with enasidenib, consistent with this inhibitor's known potential to inhibit UGT1A1, but did not appear to have significant clinical consequences. In patients receiving ivosidenib (n = 60) or enasidenib (n = 91), end-of-induction complete remission (CR) rates were 55% and 47%, respectively, and CR/CR with incomplete neutrophil or platelet recovery (CR/CRi/CRp) rates were 72% and 63%, respectively. In patients with a best overall response of CR/CRi/CRp, 16/41 (39%) receiving ivosidenib had IDH1 mutation clearance and 15/64 (23%) receiving enasidenib had IDH2 mutation clearance by digital polymerase chain reaction; furthermore, 16/20 (80%) and 10/16 (63%), respectively, became negative for measurable residual disease by multiparameter flow cytometry. This trial was registered at www.clinicaltrials.gov as #NCT02632708.
Expression and characterization of delayed rectifying K<sup>+</sup> channels in anterior rat taste buds (2005)

Delayed rectifying K+ (DRK) channels in taste cells have been implicated in the regulation of cell excitability and as potential targets for direct and indirect modulation by taste stimuli. In the present study, we have used patch-clamp recording to determine the biophysical properties and pharmacological sensitivity of DRK channels in isolated rat fungiform taste buds. Molecular biological assays at the taste bud and single-cell levels are consistent with the interpretation that taste cells express a variety of DRK channels, including members from each of the three major subfamilies: KCNA, KCNB, and KCNC. Real-time PCR assays were used to quantify expression of the nine DRK channel subtypes. While taste cells express a number of DRK channels, the electrophysiological and molecular biological assays indicate that the Shaker Kv1.5 channel (KCNA5) is the major functional DRK channel expressed in the anterior rat tongue.
Web Services Security and Threats: A Systematic Literature Review (2020)

Privacy and data protection issues are the main problems in using web services to transmit data. Three aspects of information security that contains confidentiality, integrity, and availability need to be considered in maintaining web service security. Data sent by data providers can be easily attacked, resulting in data leaks when the data traffic process. Privacy data such as personal information and location data providers are sensitive data and need to be protected from unauthorized parties to avoid improper use of data. Also, data sent via the web service must be guaranteed that data is not changed by unauthorized persons in the data transmission process, because attacks that result in data changes can occur when the data has not yet arrived at the data recipient. The web service system must also ensure that data can always be available when needed. However, various attacks can be carried out to inhibit or stop the availability of this data. Therefore, we conducted a systematic literature review which aims to review and present some observation that has been done on existing research on web services security. Based on the results of our literature review, the secure coding method can be an available security solution. However, this method needs further development if it is applied to web services with the REST architecture which is currently being widely used.
14-3-3 Protein cerebrospinal fluid detection in human growth hormone-treated Creutzfeldt-Jakob disease patients (2001)

The usefulness of the detection of 14-3-3 protein in the cerebrospinal fluid (CSF) in the diagnosis of Creutzfeldt-Jakob disease transmitted from human growth hormone was evaluated in 20 French patients. The 14-3-3 protein was rarely detectable within the first 3 months of the disease but always positive after 7 months associated with the aggravation of the disease and the occurrence of dementia. 14-3-3 detection was not predictive of the survival time of the patients. The genotype at PRNP codon 129 could influence the timing of appearance of the 14-3-3 protein in the CSF.
The Ard1 Gene from Streptomyces capreolus Encodes a Polypeptide of the ABC-Transporters Superfamily Which Confers Resistance to the Aminonucleoside Antibiotic A201A (1995)

A gene (ard1) encoding resistance to the aminonucleoside antibiotic A201A was cloned from Streptomyces capreolus NRRL 3817, the producing organism, and expressed in Streptomyces lividans. The gene ard1 induced antibiotic resistance that was highly specific for A201A. The nucleotide sequence of ard1 contains an open reading frame of 1677 bp. Transcription initiation was found to take place approximately 86 nucleotides preceding the ATG translation-initiation codon, indicating that ard1 is transcribed from its own promoter. The deduced protein sequence (Ard1, 558 amino acids) presents two ATP-binding domains with significant similarities to those of the ATP-binding cassette transporters (ABC-transporters) superfamily, including some that confer drug resistance in a variety of antibiotic-producing Streptomyces, other Gram-positive bacteria and eukaryotic cells. As is probably the case for most of these proteins, the mechanism of A201A resistance conferred by Ard1 is an active efflux energized by ATP hydrolysis.
원저 : 긴장성 두통에 대한 동통유발점 자침과 원위취혈 자침의 치료효과에 대한 임상적 비교 연구 (2001)

Purpose ; lension-type headache is the most common headache. The effect of acupuncture for headache is already known, but the methods and technique of acupuncture is varied. Choice of acupuncture points is mostly relied on experience. Moreover, objective evaluation of acupuncture effects is lacking. Objective ; The objective of this study is to assess the difference of effects between dry needling on trigger point and dry needling on remote acupuncture point. The patients who were diagnosed as tension-type headache and administrated herb-medication were divided into two groups: Trigger point dry needling group and remote acupuncture point dry needling group, matching in sex, age. The degree of pain was measured by visual analogue scale(VAS) two times, before and after dry needling. Conclusion ; VAS showed significant decrement after dry needling on tension-type headache in both groups, but there was no statistically significant difference between two groups according to sex, age and duration. In addition, it is not statistically approved that there exists the difference of VAS between two groups about the treatment effects.
Cylindrical Brush Polymers with Polysarcosine Side Chains: A Novel Biocompatible Carrier for Biomedical Applications (2015)

Cylindrical brush polymers constitute promising polymeric drug delivery systems (nanoDDS). Because of the densely grafted side chains such structures may intrinsically exhibit little protein adsorption (“stealth” effect) while providing a large number of functional groups accessible for bioconjugation reactions. Polysarcosine (PSar) is a highly water-soluble, nonionic and nonimmunogenic polypeptoid based on the endogenous amino acid sarcosine (N-methyl glycine). Here we report on the synthesis, characterization and biocompatibility of cylindrical brush polymers with either polysarcosine side chains or poly-l-lysine-b-polysarcosine side chains. The latter leads to block copolypept(o)id based core–shell cylindrical brushes with a cationic poly-l-lysine (PLL) core and a neutral polysarcosine corona. The cylindrical brush polymers were prepared by ring-opening polymerization of the respective N-carboxyanhydrides (NCA) from a macroinitiator chain. Preliminary experiments on complex formation with siRNA demonstrate that a core–shell cylindrical brush polymer may complex on average up to 270 RNA molecules amounting to a high loading efficiency of N+/P– = 1.1. No bridging between cylindrical brushes leading to larger aggregates is observed. In vitro studies on the silencing of the expression of ApoB100, which is abundantly expressed in AML-12 hepatocytes, induced by siRNA-cylindrical core–shell brush complexes showed high efficiency, leading to a knock-down efficiency of ApoB100 mRNA of 70%.
An I2C based mixed-signal test and measurement infrastructure (2014)

The framework being proposed addresses the test and measurement of circuits and systems populated with varying types of sensors and functional blocks, among which one can find embedded test instruments. Its conceptual functionality is based on four types of operations: setup, capture, process, and scan (SCPS), and aims to provide a unifying methodology for managing and synchronizing test operations and instruments. The generalized physical structure and examples of operating commands are described. An application illustrates its use in a particular case.
Quantum machine learning: a classical perspective (2018)

Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication alongside the increasing size of datasets is motivating a growing number of researchers to explore the possibility of harnessing the power of quantum computation to speed up classical ML algorithms. Here we review the literature in quantum ML and discuss perspectives for a mixed readership of classical ML and quantum computation experts. Particular emphasis will be placed on clarifying the limitations of quantum algorithms, how they compare with their best classical counterparts and why quantum resources are expected to provide advantages for learning problems. Learning in the presence of noise and certain computationally hard problems in ML are identified as promising directions for the field. Practical questions, such as how to upload classical data into quantum form, will also be addressed.
Prediction of human-virus protein-protein interactions through a sequence embedding-based machine learning method (2019)

The identification of human-virus protein-protein interactions (PPIs) is an essential and challenging research topic, potentially providing a mechanistic understanding of viral infection. Given that the experimental determination of human-virus PPIs is time-consuming and labor-intensive, computational methods are playing an important role in providing testable hypotheses, complementing the determination of large-scale interactome between species. In this work, we applied an unsupervised sequence embedding technique (doc2vec) to represent protein sequences as rich feature vectors of low dimensionality. Training a Random Forest (RF) classifier through a training dataset that covers known PPIs between human and all viruses, we obtained excellent predictive accuracy outperforming various combinations of machine learning algorithms and commonly-used sequence encoding schemes. Rigorous comparison with three existing human-virus PPI prediction methods, our proposed computational framework further provided very competitive and promising performance, suggesting that the doc2vec encoding scheme effectively captures context information of protein sequences, pertaining to corresponding protein-protein interactions. Our approach is freely accessible through our web server as part of our host-pathogen PPI prediction platform (http://zzdlab.com/InterSPPI/). Taken together, we hope the current work not only contributes a useful predictor to accelerate the exploration of human-virus PPIs, but also provides some meaningful insights into human-virus relationships.
Q(λ) learning-based dynamic route guidance algorithm for overhead hoist transport systems in semiconductor fabs (2019)

A learning-based dynamic routing algorithm is proposed for the overhead hoist transport (OHT) systems of semiconductor fabrication facilities (fabs). An OHT system, which consists of multiple vehicles moving at high speeds on guided rails, is the primary automated material-handling system (AMHS) in a fab. Modern large-scale fabs have hundreds of vehicles moving lots between multiple processing machines. The dynamic routing method is a route guidance method that dynamically selects the best vehicle paths under given traffic conditions and congestion levels. Building on the $Q(\lambda ) $Q(λ) learning method, we develop a reinforcement learning-based dynamic routing algorithm called QLBWR(λ), which consists of a Boltzmann softmax policy and a reward function. The proposed algorithm uses real-time information to effectively guide each vehicle so that it avoids congestion and finds an efficient path. The algorithm is also designed with a low computational burden, such that the efficient route can be found for hundreds of vehicles in real time. Simulation analyses on an actual fab layout are used to compare the performance of the proposed algorithm with common static and dynamic algorithms. The results show that the proposed algorithm outperforms the benchmarking algorithms.
Silicone fluids: Synthesis, properties and applications (1986)

Abstract This paper describes the structure and derivation of ‘classical’ silicone fluids, giving the reactions for the production of dimethyl fluids by Miiller‐Rochow synthesis, polymerisation, direct synthesis, hydrosilylation, and transesterification. The properties of siloxanes are described, and the applications of silicone fluids and compounds are discussed in relation to their properties, particularly insolubility in water, viscosity‐temperature characteristics, and dielectric properties.
On the use of prior and external knowledge in neural sequence models (2019)

Neural sequence models have recently achieved great success across various natural language processing tasks. In practice, neural sequence models require massive amount of annotated training data to reach their desirable performance; however, there will not always be available data across languages, domains or tasks at hand. Prior and external knowledge provides additional contextual information, potentially improving the modelling performance as well as compensating the lack of large training data, particular in low-resourced situations. In this thesis, we investigate the usefulness of utilising prior and external knowledge for improving neural sequence models. We propose the use of various kinds of prior and external knowledge and present different approaches for integrating them into both training and inference phases of neural sequence models. The followings are main contributions of this thesis which are summarised in two major parts:

We present the first part of this thesis which is on Training and Modelling for neural sequence models. In this part, we investigate different situations (particularly in low resource settings) in which prior and external knowledge, such as side information, linguistic factors, monolingual data, is shown to have great benefits for improving performance of neural sequence models. In addition, we introduce a new means for incorporating prior and external knowledge based on the moment matching framework. This framework serves its purpose for exploiting prior and external knowledge as global features of generated sequences in neural sequence models in order to improve the overall quality of the desired output sequence.

The second part is about Decoding of neural sequence models in which we propose a novel decoding framework with relaxed continuous optimisation in order to address one of the drawbacks of existing approximate decoding methods, namely the limited ability to incorporate global factors due to intractable search.

We hope that this PhD thesis, constituted by two above major parts, will shed light on the use of prior and external knowledge in neural sequence models, both in their training and decoding phases.
Performance, clinical chemistry, and carcass responses of finishing lambs to formulated sometribove (methionyl bovine somatotropin)1 (1994)

Formulated zinc methionyl bST (sometribove, 50, 100, or 150 mg) was administered as a single treatment once every 2 wk or as two equal treatments once/week to evaluate the efficacy of prolonged release delivery of bovine somatotropin (bST) in finishing lambs. Feed conversion during the 6-wk treatment period was improved 9 and 19% in lambs that received treatments once and twice/2 wk, respectively (P < .05), and the responses to differing doses were similar within a dosing frequency (P > .05). Carcass muscle:fat ratio indicators generally were affected in a dose-related manner and were independent of frequency of administration. For example, fat thickness was 17, 30, and 42% lower than control in lambs that received 50, 100, and 150 mg of formulated sometribove/2 wk, respectively (P < .05). Percentages of muscle were higher and of fat were lower with increasing dose of formulated sometribove, but weight of only fat was significantly affected (P < .05). Clinical chemistry indices of metabolic effects of bST (e.g., circulating bST, IGF-I, insulin, glucose, and urinary nitrogen concentrations) were affected in directions similar to those observed with bST administered by daily injection. The results of this study demonstrate the growth performance and carcass composition advantages of a formulation designed to deliver bST over a 2-wk period.
Regression models for twin studies: a critical review (2005)

Twin studies have long been recognized for their value in learning about the aetiology of disease and specifically for their potential for separating genetic effects from environmental effects. The recent upsurge of interest in life-course epidemiology and the study of developmental influences on later health has provided a new impetus to study twins as a source of unique insights. Twins are of special interest because they provide naturally matched pairs where the confounding effects of a large number of potentially causal factors (such as maternal nutrition or gestation length) may be removed by comparisons between twins who share them. The traditional tool of epidemiological 'risk factor analysis' is the regression model, but it is not straightforward to transfer standard regression methods to twin data, because the analysis needs to reflect the paired structure of the data, which induces correlation between twins. This paper reviews the use of more specialized regression methods for twin data, based on generalized least squares or linear mixed models, and explains the relationship between these methods and the commonly used approach of analysing within-twin-pair difference values. Methods and issues of interpretation are illustrated using an example from a recent study of the association between birth weight and cord blood erythropoietin. We focus on the analysis of continuous outcome measures but review additional complexities that arise with binary outcomes. We recommend the use of a general model that includes separate regression coefficients for within-twin-pair and between-pair effects, and provide guidelines for the interpretation of estimates obtained under this model.
Color interpolation algorithm for an RWB color filter array including double-exposed white channel (2016)

In this paper, we propose a color interpolation algorithm for a red-white-blue (RWB) color filter array (CFA) that uses a double exposed white channel instead of a single exposed green (G) channel. The double-exposed RWB CFA pattern, which captures two white channels at different exposure times simultaneously, improves the sensitivity and provides a solution for the rapid saturation problem of W channel although spatial resolution is degraded due to the lack of a suitable color interpolation algorithm. The proposed algorithm is designed and optimized for the double-exposed RWB CFA pattern. Two white channels are interpolated by using directional color difference information. The red and blue channels are interpolated by applying a guided filter that uses the interpolated white channel as a guided value. The proposed method resolves spatial resolution degradation, particularly in the horizontal direction, which is a challenging problem in the double-exposed RWB CFA pattern. Experimental results demonstrate that the proposed algorithm outperforms other color interpolation methods in terms of both objective and subjective criteria.
Vav3 collaborates with p190-BCR-ABL in lymphoid progenitor leukemogenesis, proliferation, and survival (2012)

Despite the introduction of tyrosine kinase inhibitor therapy, the prognosis for p190-BCR-ABL(+) acute lymphoblastic leukemia remains poor. In the present study, we present the cellular and molecular roles of the Rho GTPase guanine nucleotide exchange factor Vav in lymphoid leukemogenesis and explore the roles of Vav proteins in BCR-ABL-dependent signaling. We show that genetic deficiency of the guanine nucleotide exchange factor Vav3 delays leukemogenesis by p190-BCR-ABL and phenocopies the effect of Rac2 deficiency, a downstream effector of Vav3. Compensatory up-regulation of expression and activation of Vav3 in Vav1/Vav2-deficient B-cell progenitors increases the transformation ability of p190-BCR-ABL. Vav3 deficiency induces apoptosis of murine and human leukemic lymphoid progenitors, decreases the activation of Rho GTPase family members and p21-activated kinase, and is associated with increased Bad phosphorylation and up-regulation of Bax, Bak, and Bik. Finally, Vav3 activation only partly depends on ABL TK activity, and Vav3 deficiency collaborates with tyrosine kinase inhibitors to inhibit CrkL activation and impair leukemogenesis in vitro and in vivo. We conclude that Vav3 represents a novel specific molecular leukemic effector for multitarget therapy in p190-BCR-ABL-expressing acute lymphoblastic leukemia.