gebhart/patrepeval huggingface dataset:
Computerized detection and 3-way classification of breast lesions on ultrasound images (2004)

Computer-aided diagnosis has great potential to improve performance of the detection and classification of abnormalities on breast ultrasound. Our goal is to develop a computerized tool that detects suspicious areas and distinguishes among false-positive detections, benign lesions, and malignancies. One-step classification into 3 categories is a largely unexplored territory with many possibilities. The computerized scheme first identifies potential lesions based on expected lesion shape and margin characteristics. Our main focus here, however, is the subsequent classification of the potential lesions into 3 categories. For this purpose, we use a 3-way Bayesian neural net (BNN) based on extracted image features of the lesion candidates. The method was tested on a database of 858 cases (1832 images) consisting of complex and simple cysts, benign solid lesions, and malignant lesions. In order to verify whether performance conforms to expectations, the output of a 3-way classifier ("A" vs. "B" vs. "C") can be projected onto that of two 2-way classifiers ("A" vs. "B or C", and "A or B" vs. "C"). We compared the projected performance of the 3-way classifier to two specifically trained 2-way classifiers. The first task was to distinguish cancer from all other lesion candidates, and the second was to distinguish actual lesions from false-positive detections. For these tasks, the performance of the 2-way classifiers and the projected performance of the 3-way classifier were indistinguishable based on calculated means and standard deviations of ROC area (Az). For example, in round robin analysis the average Az values obtained with both approaches were 0.92 and 0.83, for the two tasks, with standard deviations of 0.006 and 0.010, respectively. The potential of 3-way classification is illustrated graphically through the estimated probability density functions of the three truth categories. We have implemented a promising computerized scheme for detection and subsequent one-step 3-way classification of breast lesions on ultrasound images. The method was tested on an extensive database. The main challenge is the development of an objective evaluation method of performance such as the equivalent of ROC analysis for the 2-class problem.
Supplementary Data from Comprehensive Genetic Characterization of Human Thyroid Cancer Cell Lines: A Validated Panel for Preclinical Studies (2023)

&lt;p&gt;Supplementary Methods, Supplementary Figure and Table Legends&lt;/p&gt;
Layer-by-Layer Fabrication of Oriented Porous Thin Films Based on Porphyrin-Containing Metal–Organic Frameworks (2013)

We report the synthesis and characterization of two thin films (DA-MOF and L2-MOF) of porphyrin-based MOFs on functionalized surfaces using a layer-by-layer (LbL) approach. Profilometry measurements confirm that the film thickness increases systematically with number of growth cycles. Polarization excitation and fluorescence measurements indicate that the porphyrin units are preferentially oriented, while X-ray reflectivity scans point to periodic ordering. Ellipsometry measurements show that the films are highly porous. Since there are currently few methods capable of yielding microporous MOFs containing accessible free-base porphyrins, it is noteworthy that the LbL growth permits direct MOF incorporation of unmetalated porphyrins. Long-range energy transfer is demonstrated for both MOF films. The findings offer useful insights for subsequent fabrication of MOF-based solar energy conversion devices.
FPGA Acceleration of Fluid-Flow Kernels (2020)

Adding heterogeneity to high-performance systems has the potential to meet the increasing performance demands of applications beyond the era of Moore's Law speedup. In this paper we design and evaluate an FPGA pipeline to accelerate the CMT-bone-BE physics application, which is highly scalable, but performance bound by compute-heavy fluid-flow kernels. For the targeted kernels, a single instance of our FPGA pipeline shows a speedup of up to 9.4x over a CPU core. For the entire application workload, this kernel acceleration provides an average 1.5× speedup over a CPU core, while also outperforming a GPU. With even mid-range FPGAs providing enough resources to replicate our pipeline over 8 times, we project that the FPGA accelerator can add and/or replace 12 equivalent cores with a low-power alternative, with additional time-sharing optimizations potentially increasing that amount significantly.
The role of Nrf2 signaling in counteracting neurodegenerative diseases (2018)

The transcription factor Nrf2 (nuclear factor-erythroid 2 p45-related factor 2) functions at the interface of cellular redox and intermediary metabolism. Nrf2 target genes encode antioxidant enzymes, and proteins involved in xenobiotic detoxification, repair and removal of damaged proteins and organelles, inflammation, and mitochondrial bioenergetics. The function of Nrf2 is altered in many neurodegenerative disorders, such as Huntington's disease, Alzheimer's disease, amyotrophic lateral sclerosis, and Friedreich's ataxia. Nrf2 activation mitigates multiple pathogenic processes involved in these neurodegenerative disorders through upregulation of antioxidant defenses, inhibition of inflammation, improvement of mitochondrial function, and maintenance of protein homeostasis. Small molecule pharmacological activators of Nrf2 have shown protective effects in numerous animal models of neurodegenerative diseases, and in cultures of human cells expressing mutant proteins. Targeting Nrf2 signaling may provide a therapeutic option to delay onset, slow progression, and ameliorate symptoms of neurodegenerative disorders.
Taxanes from the Seeds of Taxus baccata (1993)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTTaxanes from the Seeds of Taxus baccataGiovanni Appendino, Silvia Tagliapietra, Hasan Çetin Özen, Pierluigi Gariboldi, Bruno Gabetta, and Ezio BombardelliCite this: J. Nat. Prod. 1993, 56, 4, 514–520Publication Date (Print):April 1, 1993Publication History Published online1 July 2004Published inissue 1 April 1993https://pubs.acs.org/doi/10.1021/np50094a010https://doi.org/10.1021/np50094a010research-articleACS PublicationsRequest reuse permissionsArticle Views219Altmetric-Citations39LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
The Origin of COVID-19 and Why It Matters (2020)

The COVID-19 pandemic is among the deadliest infectious diseases to have emerged in recent history. As with all past pandemics, the specific mechanism of its emergence in humans remains unknown. Nevertheless, a large body of virologic, epidemiologic, veterinary, and ecologic data establishes that the new virus, SARS-CoV-2, evolved directly or indirectly from a β-coronavirus in the sarbecovirus (SARS-like virus) group that naturally infect bats and pangolins in Asia and Southeast Asia. Scientists have warned for decades that such sarbecoviruses are poised to emerge again and again, identified risk factors, and argued for enhanced pandemic prevention and control efforts. Unfortunately, few such preventive actions were taken resulting in the latest coronavirus emergence detected in late 2019 which quickly spread pandemically. The risk of similar coronavirus outbreaks in the future remains high. In addition to controlling the COVID-19 pandemic, we must undertake vigorous scientific, public health, and societal actions, including significantly increased funding for basic and applied research addressing disease emergence, to prevent this tragic history from repeating itself.
A recombinant fusion protein containing a spider toxin specific for the insect voltage-gated sodium ion channel shows oral toxicity towards insects of different orders (2014)

Recombinant fusion protein technology allows specific insecticidal protein and peptide toxins to display activity in orally-delivered biopesticides. The spider venom peptide δ-amaurobitoxin-PI1a, which targets insect voltage-gated sodium channels, was fused to the "carrier" snowdrop lectin (GNA) to confer oral toxicity. The toxin itself (PI1a) and an amaurobitoxin/GNA fusion protein (PI1a/GNA) were produced using the yeast Pichia pastoris as expression host. Although both proteins caused mortality when injected into cabbage moth (Mamestra brassicae) larvae, the PI1a/GNA fusion was approximately 6 times as effective as recombinant PI1a on a molar basis. PI1a alone was not orally active against cabbage moth larvae, but a single 30 μg dose of the PI1a/GNA fusion protein caused 100% larval mortality within 6 days when fed to 3rd instar larvae, and caused significant reductions in survival, growth and feeding in 4th - 6th instar larvae. Transport of fusion protein from gut contents to the haemolymph of cabbage moth larvae, and binding to the nerve chord, was shown by Western blotting. The PI1a/GNA fusion protein also caused mortality when delivered orally to dipteran (Musca domestica; housefly) and hemipteran (Acyrthosiphon pisum; pea aphid) insects, making it a promising candidate for development as a biopesticide.
Unsupervised Ensemble Classification With Sequential and Networked Data (2020)

Ensemble learning, the machine learning paradigm where multiple models are combined, has exhibited promising perfomance in a variety of tasks. The present work focuses on unsupervised ensemble classification. The term unsupervised refers to the ensemble combiner who has no knowledge of the ground-truth labels that each classifier has been trained on. While most prior works on unsupervised ensemble classification are designed for independent and identically distributed (i.i.d.) data, the present work introduces an unsupervised scheme for learning from ensembles of classifiers in the presence of data dependencies. Two types of data dependencies are considered: sequential data and networked data whose dependencies are captured by a graph. For both, novel moment matching and Expectation-Maximization algorithms are developed. Performance of these algorithms is evaluated on synthetic and real datasets, which indicate that knowledge of data dependencies in the meta-learner is beneficial for the unsupervised ensemble classification task.
ChemInform Abstract: Total Asymmetric Synthesis of Highly Constrained Amino Acids β‐ Isopropyl‐2′,6′‐dimethyl‐tyrosines. (1997)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
A Novel In Vitro Multiple-Stress Dormancy Model for Mycobacterium tuberculosis Generates a Lipid-Loaded, Drug-Tolerant, Dormant Pathogen (2009)

The new in vitro multiple stress dormancy model efficiently generates Mtb cells meeting all criteria of dormancy, and this method is adaptable to high-throughput screening for drugs that can kill dormant Mtb. A critical link between storage-lipid accumulation and development of phenotypic drug-resistance in Mtb was established. Storage lipid biosynthetic genes may be appropriate targets for novel drugs that can kill latent Mtb.
Strongly correlated spatiotemporal encoding and simple decoding in the prefrontal cortex (2019)

We studied the fine temporal structure of spiking patterns of groups of up to 100 simultaneously recorded units in the prefrontal cortex of monkeys performing a visual discrimination task. We characterized the vocabulary of population activity patterns using 10 ms time bins and found that different sets of population activity patterns (codebooks) are used in different task epochs and that spiking correlations between units play a large role in defining those codebooks. Models that ignore those correlations fail to capture the population codebooks in all task epochs. Further, we show that temporal sequences of population activity patterns have strong history-dependence and are governed by different transition probabilities between patterns and different correlation time scales, in the different task epochs, suggesting different computational dynamics governing each epoch. Together, the large impact of spatial and temporal correlations on the dynamics of the population code makes the observed sequences of activity patterns many orders of magnitude more likely to appear than predicted by models that ignore these correlations and rely only on the population rates. Surprisingly, however, models that ignore these correlations perform quite well for decoding behavior from population responses. The difference of encoding and decoding complexity of the neural codebook suggests that one of the goals of the complex encoding scheme in the prefrontal cortex is to accommodate simple decoders that do not have to learn correlations.
Clipping Compensation of Noise Shaper for Digital Audio Amplifier (2011)

The Noise Shaper of a full digital amplifier overflows randomly when the Modulation Index of PWM is higher than a certain value. The clipping from the overflow produces an abrupt increase of THD+N that limits MI or the maximum output power. In this paper, we discussed the reason of NS overflow and derived the critical value of MI. We proposed a compensation method for the clipping error and optimized compensation in the audio band. The measurement results show that the proposed method can increase the maximum output power by 6.4% at a 1% THD+N condition. The compensation is more important where the power supply voltage and speaker impedance are difficult to change as that in a car stereo or mobile.
Ultra-miniature UHF antenna for nomadic device (2010)

In this paper, a new design based on the twisted slot antenna is proposed covering the full UHF band [470-862MHz]. Realized on a 130*230 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> PCB board, the design combines artifacts such as folding the metallic shape using the third dimension and using a tunable component for frequency tunability in order to cover the full UHF band. The achieved ultra-miniature antenna size is lower than λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> /51* λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> /118 * λ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> /138 at the lowest frequency for a simulated peak antenna gain higher than EICTA/MBRAI recommendations.
Polarized infrared spectroscopic study on the orientation of the molecules in the smectic-C*phase of a ferroelectric liquid crystal with a naphthalene ring: Alternative theory for the analysis of polarization-angle-dependent intensity changes (2001)

A theory to explain the polarization-angle dependence of polarized infrared spectra of a ferroelectric liquid crystal in the surface-stabilized ferroelectric liquid crystal state is proposed. It describes the relationship between the intensity of the absorption bands and the polarization angle of the infrared radiation. Using this theory the polarization-angle dependence of the infrared band intensities was analyzed for a ferroelectric liquid crystal with a naphthalene ring and two phenyl rings with a stacked layer structure in the smectic-C* phase. The polarization-angle-dependent spectra were measured at 137 degrees C under external dc electric fields of +40 and -40 V to investigate the orientation of the molecules. Plots of the infrared absorbance versus polarization angle for representative bands were subjected to a curve fitting procedure by a least squares method. From the curves obtained the orientation of the transition dipole moments with respect to the molecular long axis and the orientation of the molecular long axis with respect to the rubbing direction of the cell were estimated based upon the suggested theory. The polarization-angle-dependent infrared spectra obtained were also analyzed by two-dimensional (2D) correlation spectroscopy. The 2D correlation analysis clearly detects a slight phase difference in the polarization-angle dependence which is hardly recognized in ordinary plots of the intensity changes in the infrared bands. The 2D correlation analysis allows us to separate asymmetric and symmetric stretching bands due to the chiral methyl group from those arising from other methyl groups in the alkyl chains.
Transition Metal Complex-Doped Hydroxyapatite Layers on Porous Silicon (1998)

In this work, the encapsulation of the transition metal complexes cis-Pt(NH3)2Cl2, Ru(bpy)32+, and Ru(phen)32+ within layers of hydroxyapatite on a porous Si/Si substrate are described. These specific complexes were selected as a consequence of their biological activity (cis-Pt(NH3)2Cl2) or polynucleotide binding ability (Ru(bpy)32+ and Ru(phen)32+). The complex-doped hydroxyapatite/porous Si/Si materials have been characterized by scanning electron microscopy, energy-dispersive X-ray spectroscopy, secondary ion mass spectrometry, and photoluminescence spectroscopy. It is possible to exercise some control of the release of a given complex into the surrounding medium through thermal heating of the complex-doped hydroxyapatite/porous Si/Si structure.
Nonmyeloablative Transplantation (2004)

High-dose chemotherapy followed by autologous hematopoietic stem cell transplantation has been explored as a method to enhance the efficacy of chemotherapy for advanced solid tumors. The failure of autologous hematopoietic stem cell transplantation to prolong survival in patients with metastatic solid tumors has sparked interest recently in studies exploring the potential of allogeneic hematopoietic stem cell transplantation for such patients. Allogeneic hematopoietic stem cell transplantation is widely accepted as a potent form of immunotherapy capable of curing patients with chemotherapy-refractory hematologic malignancies. However, it was not until the end of the 20th century that investigators initiated trials to test the potential of allogeneic hematopoietic stem cell transplantation as immunotherapy in malignancies of epithelial origin. Early pilot trials have established proof-of-principle that graft-versus-tumor effects can induce complete or partial remission in some treatment-refractory metastatic solid tumors. In this review, we discuss the rationale for pilot trials investigating the potential of nonmyeloablative allogeneic hematopoietic stem cell transplantation in advanced cytokine-refractory renal cancer, highlighting the preliminary success, limitations, and future clinical directions of this approach.
Methods to increase reproducibility in differential gene expression via meta-analysis (2016)

Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce. Here, we hypothesized that studying subsets of very large meta-analyses would allow for systematic identification of best practices to improve reproducibility. We therefore constructed three very large gene expression meta-analyses from clinical samples, and then examined meta-analyses of subsets of the datasets (all combinations of datasets with up to N/2 samples and K/2 datasets) compared to a 'silver standard' of differentially expressed genes found in the entire cohort. We tested three random-effects meta-analysis models using this procedure. We showed relatively greater reproducibility with more-stringent effect size thresholds with relaxed significance thresholds; relatively lower reproducibility when imposing extraneous constraints on residual heterogeneity; and an underestimation of actual false positive rate by Benjamini-Hochberg correction. In addition, multivariate regression showed that the accuracy of a meta-analysis increased significantly with more included datasets even when controlling for sample size.
Laser frequency drift compensation with Han-Kobayashi coding in superchannel nonlinear optical communications (2015)

We investigate the impact of laser frequency drift, which can cause inter-channel interference (ICI) in superchannel communications. We show that Han-Kobayashi coding significantly improves robustness against the drift, achieving 2-times higher achievable rate than conventional coding.
Abstract C91: Targeting enzalutamide resistance in prostate cancer. (2013)

Abstract Prostate cancer initially responses to androgen ablation or castration, but progression to incurable castrate-resistant prostate cancer often occurs within three years. Androgen receptor pathway inhibitor Enzalutamide (ENZ) has produced promising survival gains of patients with CRPC. However, resistance to this novel therapy also rapidly occurs and novel treatment strategies are needed. We have recently developed a unique ENZ and castrate-resistant LNCaP xenograft model. To identify key regulators and active pathways in ENZ resistant cells, genome-wide gene expression analysis was performed and analyzed using systems biological approaches. We identified that forkhead box M1 (FOXM1) is one of the key upstream regulators activated in ENZ resistant prostate cancer cells. FOXM1 is overexpressed in several cancers and it is an important regulator of cancer characteristics such as cell cycle, proliferation, invasion, metastases and cancer stem cells. FOXM1 is also a critical regulator of oxidative stress and its depletion sensitises cells to oxidative stress induced apoptosis. Interestingly, we further found out that the antibiotic ionophore and oxidative stress inducer monensin that was previously identified as a cancer-specific prostate cancer inhibitor in high-throughput screening, reduces FOXM1 pathway activity and viability of ENZ resistant cells. Thus, the results suggest that inhibition of FOXM1 is a potent novel mean to impair redox control and target ENZ resistant prostate cancer cells. Taken together, our results indicated that FOMX1 activity is increased in ENZ resistant prostate cancer cells and that targeting FOXM1 is a potential means to overcome ENZ resistance in prostate cancer. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C91. Citation Format: Kirsi Ketola, Jennifer Bishop, Martin Gleave, Amina Zoubeidi. Targeting enzalutamide resistance in prostate cancer. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C91.
Dispersibility of Flame Retardants and Their Effects on Mechanical Properties of Flame Retarding Polypropylene (1980)

難燃性ポリプロピレンは, 難燃剤をポリプロピレンにブレンドすることにより, その機械的物性が明らかに影響を受ける。著者らは・難燃剤の分散性をケイ光X線およびX線マイクロアナライザーを用いて評価する方法を確立し, 難燃性ポリプロピレンの機械的物性におよぼす主要因が難燃剤の分散性であることを確かめた。さらに, すぐれた機械的物性を示す難燃性ポリプロピレンを, 原料としてペレット状のポリプロピレンを用いて作ることができるブレンド加工法を検討した。