gebhart/patrepeval huggingface dataset:
Unbounded system verification using decision procedure and predicate abstraction (2004)

Modeling and analysis of systems with large, infinite or parameterized state spaces has received much attention in the last decade. These systems include microprocessors with unbounded buffers and memories; parameterized cache-coherence and communication protocols with unbounded channels; and distributed algorithms for mutual exclusion. Most previous works have either used general purpose theorem provers with considerable manual guidance or techniques specific to a particular class of systems. 
In this work, we express unbounded systems in the Logic of Counter arithmetic with Lambda expressions and Uninterpreted functions (CLU), a quantifier-free fragment of first-order logic. We illustrate the strengths and limitations of the logic with respect to the expressiveness in modeling systems and efficient tools for reasoning in this logic. We exploit efficient Boolean translation of CLU formulas as a basis for constructing a decision procedure for CLU that exploits recent advances in Boolean Satisfiability (SAT) solving. We use a case study of complex out-of-order microprocessors to illustrate the effective use of decision procedures in reducing manual guidance in proving the verification conditions. 
To automate the construction of inductive invariants, we use predicate number of theorem prover calls, they often failed to scale to large problems. the exponentially large number of decision procedure calls. We leverage recent advances in Boolean methods to perform the task efficiently. We illustrate the effectiveness of the approach for distributed systems and benchmarks from the verification of device drivers in Microsoft Windows. 
For verifying unbounded systems, it is crucial to construct quantified inside the predicates. We formalize the extension and provide a weakest precondition transformer based mechanism for discovering indexed predicates automatically. This has facilitated automatic safety verification of a number of interesting systems including directory based cache coherence protocols and mutual exclusion algorithms.
Enzymatic Removal of Bilirubin From Blood: A Potential Treatment for Neonatal Jaundice (1985)

Current treatments for severe jaundice can result in major complications. Neonatal jaundice is caused by excessive accumulation of bilirubin in the blood. A small blood filter containing immobilized bilirubin oxidase was developed to reduce serum bilirubin concentrations. When human or rat blood was passed through the enzyme filter, more than 90 percent of the bilirubin was degraded in a single pass. This procedure may have important applications in the clinical treatment of neonatal jaundice.
Fuzz-SSVS: A Fuzzy logic based voting scheme to improve protein secondary structure prediction (2011)

This paper presents a novel approach, Fuzz-SSVS, to improve the secondary structure prediction of proteins. In this work, a Sugeno based Fuzzy System is trained to act as a voting system to combine results of several secondary structure prediction techniques and produce superior answers. Fuzz-SSVS is tested with three of the well-known benchmarks in this field. The results demonstrate the superiority of the proposed technique even in the case of formidable sequences.
Structurally Sophisticated Octahedral Metal Complexes as Highly Selective Protein Kinase Inhibitors (2011)

The generation of synthetic compounds with exclusive target specificity is an extraordinary challenge of molecular recognition and demands novel design strategies, in particular for large and homologous protein families such as protein kinases with more than 500 members. Simple organic molecules often do not reach the necessary sophistication to fulfill this task. Here, we present six carefully tailored, stable metal-containing compounds in which unique and defined molecular geometries with natural-product-like structural complexity are constructed around octahedral ruthenium(II) or iridium(III) metal centers. Each of the six reported metal compounds displays high selectivity for an individual protein kinase, namely GSK3α, PAK1, PIM1, DAPK1, MLCK, and FLT4. Although being conventional ATP-competitive inhibitors, the combination of the unusual globular shape and rigidity characteristics, of these compounds facilitates the design of highly selective protein kinase inhibitors. Unique structural features of the octahedral coordination geometry allow novel interactions with the glycine-rich loop, which contribute significantly to binding potencies and selectivities. The sensitive correlation between metal coordination sphere and inhibition properties suggests that in this design, the metal is located at a "hot spot" within the ATP binding pocket, not too close to the hinge region where globular space is unavailable, and at the same time not too far out toward the solvent where the octahedral coordination sphere would not have a significant impact on potency and selectivity. This study thus demonstrates that inert (stable) octahedral metal complexes are sophisticated structural scaffolds for the design of highly selective chemical probes.
C7 Epimerization of Benzylidene-Protected β-d-Idopyranosides Brings Structural Insights into Idose Conformational Flexibility (2022)

Idose is unique among other aldohexoses because of its high conformational flexibility in solution. We herein show that benzylidene acetal-protected 3-<i>O</i>-acyl-β-d-idopyranosides undergo Lewis acid-catalyzed C7 epimerization with concomitant <sup>4</sup><i>C</i><sub>1</sub> to <sup>1</sup><i>C</i><sub>4</sub> ring inversion. The reaction conditions and structural parameters for this transformation to occur have been thoroughly investigated through an extensive glycosylation study combined with NMR analyses, X-ray diffraction, and quantum molecular modeling. In addition to reporting a direct, β-stereoselective idosylation approach, our work brings fundamental structural insights into the conformational flexibility of idose.
Cytotoxicant‐induced trophoblast dysfunction and abnormal pregnancy outcomes: Role of zinc and metallothionein (2004)

Normal trophoblast function, including implantation, hormone production, and formation of the selectively permeable maternofetal barrier, is essential for the establishment and maintenance of the fetoplacental unit and proper fetal development. Maternal cytotoxicant exposure causes the destruction of these cells, especially the terminally differentiated syncytiotrophoblasts, and results in a myriad of poor pregnancy outcomes. These outcomes range from intrauterine growth retardation and malformation to spontaneous abortion or stillbirth. There is recent evidence that the metal-binding protein, metallothionein, is involved in the protection of human trophoblastic cells from heavy metal-induced and severe oxidative stress-induced apoptosis. Metallothionein, with its unique biochemical structure, can both bind essential metal ions, such as the transcription modulator zinc, and yet allow their ready displacement by toxic nonessential metal ions or damaging free radicals. These properties suggest that metallothionein may be responsible not only for sequestering the cytotoxic agents, but also for altering signal transduction in the affected cells. Here, we review several identified causes of adverse pregnancy outcomes (specifically, prenatal exposure to cigarette smoke and alcohol, gestational infection, and exposure to environmental contaminants), discuss the role of zinc in modulating the cellular response to these toxic insults, and then propose how metallothionein may function to mediate this protective response.
Differences in age at diagnosis of ovarian cancer for each BRCA mutation type in Japan: optimal timing to carry out risk-reducing salpingo-oophorectomy (2022)

There appears to be no difference in the age at diagnosis of OC depending on the type of <i>BRCA</i> common mutation. Further analysis would be needed.
Trivalent mosaic or consensus HIV immunogens prime humoral and broader cellular immune responses in adults (2023)

BACKGROUNDMosaic and consensus HIV-1 immunogens provide two distinct approaches to elicit greater breadth of coverage against globally circulating HIV-1 and have shown improved immunologic breadth in nonhuman primate models.METHODSThis double-blind randomized trial enrolled 105 healthy HIV-uninfected adults who received 3 doses of either a trivalent global mosaic, a group M consensus (CON-S), or a natural clade B (Nat-B) gp160 env DNA vaccine followed by 2 doses of a heterologous modified vaccinia Ankara-vectored HIV-1 vaccine or placebo. We performed prespecified blinded immunogenicity analyses at day 70 and day 238 after the first immunization. T cell responses to vaccine antigens and 5 heterologous Env variants were fully mapped.RESULTSEnv-specific CD4+ T cell responses were induced in 71% of the mosaic vaccine recipients versus 48% of the CON-S recipients and 48% of the natural Env recipients. The mean number of T cell epitopes recognized was 2.5 (95% CI, 1.2-4.2) for mosaic recipients, 1.6 (95% CI, 0.82-2.6) for CON-S recipients, and 1.1 (95% CI, 0.62-1.71) for Nat-B recipients. Mean breadth was significantly greater in the mosaic group than in the Nat-B group using overall (P = 0.014), prime-matched (P = 0.002), heterologous (P = 0.046), and boost-matched (P = 0.009) measures. Overall T cell breadth was largely due to Env-specific CD4+ T cell responses.CONCLUSIONPriming with a mosaic antigen significantly increased the number of epitopes recognized by Env-specific T cells and enabled more, albeit still limited, cross-recognition of heterologous variants. Mosaic and consensus immunogens are promising approaches to address global diversity of HIV-1.TRIAL REGISTRATIONClinicalTrials.gov NCT02296541.FUNDINGUS NIH grants UM1 AI068614, UM1 AI068635, UM1 AI068618, UM1 AI069412, UL1 RR025758, P30 AI064518, UM1 AI100645, and UM1 AI144371, and Bill & Melinda Gates Foundation grant OPP52282.
Metabolic Syndrome Increases Risk of Venous Thromboembolism Recurrence after Acute Pulmonary Embolism (2020)

<b>Rationale:</b> Metabolic syndrome (MetS), the clinical clustering of hypertension, dyslipidemia, insulin resistance, and abdominal obesity, has been associated with a prothrombotic and hypofibrinolytic state, although data linking MetS with venous thromboembolism (VTE) remain limited.<b>Objectives:</b> The aim of this study was to measure the prevalence of MetS in patients with pulmonary embolism (PE) across a large population and to examine its impact on VTE recurrence.<b>Methods:</b> This was a retrospective, population-based analysis using deidentified information from a large statewide database, the Indiana Network for Patient Care. All patients with an <i>International Classification of Diseases</i>-defined diagnosis of PE from 2004 to 2017 were included. We measured the frequency with which patients with PE carried a comorbid diagnosis of each MetS component. Multiple logistic regression analysis was performed with VTE recurrence as the dependent variable to test the independent effect of MetS diagnosis, with a statistical model using a directed acyclic graph to account for potential confounders and mediators. Kaplan-Meier curves were constructed to compare rates of VTE recurrence over time based on the presence or absence of MetS and its individual components.<b>Results:</b> A total of 72,936 patients were included in this analysis. The most common MetS component was hypertension with a prevalence of 59%, followed by hyperlipidemia (41%), diabetes mellitus (24%), and obesity (22%). Of these patients, 69% had at least one comorbid component of MetS. The overall incidence of VTE recurrence was 17%, increasing stepwise with each additional MetS component and ranging from 6% in patients with zero components to 37% in those with all four. Logistic regression analysis yielded an adjusted odds ratio of 3.03 (95% CI, 2.90-3.16) for the effect of composite diagnosis requiring at least three of the four components of MetS diagnosis on VTE recurrence.<b>Conclusions:</b> The presence of comorbid MetS in patients with PE is associated with significantly higher rates of VTE recurrence, supporting the importance of recognizing these risk factors and initiating appropriate therapies to reduce recurrence risk.
Deep learning-based reconstruction of highly accelerated 3D MRI (2022)

Purpose: To accelerate brain 3D MRI scans by using a deep learning method for reconstructing images from highly-undersampled multi-coil k-space data Methods: DL-Speed, an unrolled optimization architecture with dense skip-layer connections, was trained on 3D T1-weighted brain scan data to reconstruct complex-valued images from highly-undersampled k-space data. The trained model was evaluated on 3D MPRAGE brain scan data retrospectively-undersampled with a 10-fold acceleration, compared to a conventional parallel imaging method with a 2-fold acceleration. Scores of SNR, artifacts, gray/white matter contrast, resolution/sharpness, deep gray-matter, cerebellar vermis, anterior commissure, and overall quality, on a 5-point Likert scale, were assessed by experienced radiologists. In addition, the trained model was tested on retrospectively-undersampled 3D T1-weighted LAVA (Liver Acquisition with Volume Acceleration) abdominal scan data, and prospectively-undersampled 3D MPRAGE and LAVA scans in three healthy volunteers and one, respectively. Results: The qualitative scores for DL-Speed with a 10-fold acceleration were higher than or equal to those for the parallel imaging with 2-fold acceleration. DL-Speed outperformed a compressed sensing method in quantitative metrics on retrospectively-undersampled LAVA data. DL-Speed was demonstrated to perform reasonably well on prospectively-undersampled scan data, realizing a 2-5 times reduction in scan time. Conclusion: DL-Speed was shown to accelerate 3D MPRAGE and LAVA with up to a net 10-fold acceleration, achieving 2-5 times faster scans compared to conventional parallel imaging and acceleration, while maintaining diagnostic image quality and real-time reconstruction. The brain scan data-trained DL-Speed also performed well when reconstructing abdominal LAVA scan data, demonstrating versatility of the network.
Platelet-Mediated Cardioprotective Effect Against Ischemia-Reperfusion Injury in Isolated Rat Hearts: Role of Platelet Number and Contribution of Supernatant of Aggregated Platelets (1998)

BACKGROUND: Previous studies have documented cardioprotective effects of circulating platelets after reperfusion injury. The present study was designed to examine the role of platelet number and contribution of platelet-released mediators in the platelet supernatant in cardioprotection against ischemia-reperfusion-induced myocardial dysfunction. METHODS AND RESULTS: Isolated buffer-perfused (constant volume) Sprage-Dawley rat hearts were subjected to 25 minutes of global ischemia followed by 30 minutes of reperfusion. Ischemia-reperfusion resulted in myocardial dysfunction, indicated by an increase in coronary perfusion pressure and left ventricular end-diastolic pressure, and a decrease in developed left ventricular pressure. Perfusion of hearts with washed rat platelets (10(3)-2.2 x 10(7) cells/mL) significantly (P <.01) attenuated these indices of myocardial dysfunction upon ischemia-reperfusion in a concentration-dependent manner. A cardioprotective effect of platelets was observed at a concentration as low as 10(5) platelets/mL. Similar cardioprotection was seen in hearts perfused with the supernatant of aggregated platelets. CONCLUSIONS: These observations indicate that the platelet-mediated cardioprotective effect against ischemia-reperfusion in vitro is concentration dependent, and platelet-released mediators in the platelet supernatant are protective against ischemia-reperfusion injury.
Femtomole analysis of prostaglandin pharmaceuticals. (1985)

An analytical method is described whereby the major classes of prostaglandins are fully resolved by microcolumn liquid chromatography and detected at the subfemtomole level by laser-induced fluorescence. The prostaglandins are labeled with the fluorescent reagent 4-bromo-methyl-7-methoxycoumarin and are subsequently separated on a high-efficiency fused-silica microcolumn (0.2 mm i.d., 1.06 m length, 150,000 theoretical plates). The optimal chromatographic conditions consist of a 3-micron octadecylsilica packing material and an isocratic mobile phase of 47.6% methanol, 23.8% acetonitrile, and 28.6% water. The prostaglandin derivatives are detected directly on the microcolumn by laser fluorimetry, using a helium/cadmium laser (325 nm, 15 mW) as the excitation source together with a simple filter/photo-multiplier optical detection system. In real sample matrices, the prostaglandin PGF2 alpha is readily quantifiable from the detection limit (0.3 fmol) to the formulation strength of the therapeutic agent Lutalyse (Upjohn), spanning more than six orders of magnitude in concentration. The simplicity and general applicability of the present analytical methodology and instrumentation suggest that this technique can be used to attack a wide variety of biomedically important problems with exceptional sensitivity and selectivity.
Power Control in Cellular Massive MIMO with Varying User Activity: A\n Deep Learning Solution (2019)

This paper considers the sum spectral efficiency (SE) optimization problem in\nmulti-cell Massive MIMO systems with a varying number of active users. This is\nformulated as a joint pilot and data power control problem. Since the problem\nis non-convex, we first derive a novel iterative algorithm that obtains a\nstationary point in polynomial time. To enable real-time implementation, we\nalso develop a deep learning solution. The proposed neural network, PowerNet,\nonly uses the large-scale fading information to predict both the pilot and data\npowers. The main novelty is that we exploit the problem structure to design a\nsingle neural network that can handle a dynamically varying number of active\nusers; hence, PowerNet is simultaneously approximating many different power\ncontrol functions with varying number inputs and outputs. This is not the case\nin prior works and thus makes PowerNet an important step towards a practically\nuseful solution. Numerical results demonstrate that PowerNet only loses $2\\%$\nin sum SE, compared to the iterative algorithm, in a nine-cell system with up\nto $90$ active users per in each coherence interval, and the runtime was only\n$0.03$ ms on a graphics processing unit (GPU). When good data labels are\nselected for the training phase, PowerNet can yield better sum SE than by\nsolving the optimization problem with one initial point.\n
Behind the Curtain: Service Selection via Trust in Composite Services (2012)

Service selection, where some of the services are accessed indirectly as constituents of composite services, is difficult for the following reasons: (1) the interpretation of service qualities is subjective; (2) evidence must be combined from multiple sources; (3) service profiles change dynamically; and (4) constituent services may be only partially observable behind composite services. We propose an approach where we map service qualities to a common probabilistic trust metric. Whereas current trust approaches estimate the trustworthiness of a composite service based on a fully observable and static setting, we propose a statistical approach built on expectation maximized over a finite mixture model. Our experiments show that our approach can dynamically punish or reward the constituents of composite services while making only partial observations.
NGF attenuates 3-nitrotyrosine formation in a 3-NP model of Huntingtonʼs disease (1996)

Nerve growth factor (NGF)-secreting fibroblasts are able to protect against the Huntington-like striatal neurodegeneration induced by the mitochondrial toxin 3-nitropropionic acid (3-NP). In the present study, we investigated whether the neuroprotective effects of NGF are mediated through antioxidative mechanisms. Rats were grafted in the corpus callosum with NGF[+] or NGF[-] fibroblasts 7 days before administration of 3-NP. The generation of peroxynitrite was evaluated by measuring the striatal levels of 3-nitrotyrosine. NGF significantly decreased the 3-NP induced generation of 3-nitrotyrosine, presumably by decreasing peroxynitrite formation. These findings suggest that NGF might protect against neuronal death by inhibiting the production of nitric oxide or decreasing the levels of superoxide radicals, thereby decreasing the generation of oxidative agents such as peroxynitrite.
Sequential Reliability Analysis Framework for Multidisciplinary Systems (2004)

This study presents an ecien t strategy for reliability analysis under multidisciplinary analysis systems. Existing methods have performed the reliability analysis using the nonlinear optimization techniques. This is mainly due to the fact that they directly apply Multidisciplinary Design Optimization(MDO) frameworks to the reliability analysis formulation. Accordingly, the reliability analysis and the Multidisciplinary Analysis(MDA) are tightly coupled in a single optimizer, which hampers utilizing the recursive and functionapproximation based reliability analysis methods such as the Advanced First Order Reliability Method(AFORM). In order to utilize the ecien t reliability analysis method under multidisciplinary analysis systems, we propose a new strategy named Sequential Approach on Reliability Analysis under Multidisciplinary analysis systems(SARAM). In this approach, the reliability analysis and the MDA are decomposed and arranged in a sequential manner, making a recursive loop. The eciency of the SARAM method was veried using two illustrative examples taken from the literatures. Compared with existing methods, it showed the least number of subsystem analyses over the other methods while maintaining accuracy.
ChemInform Abstract: Inhibition of γ‐Butyrobetaine Hydroxylase by Cyclopropyl‐Substituted γ‐Butyrobetaines. (1990)

Abstract Starting with phosphonates such as (I) or (IX), cyclopropyl‐substituted γ‐butyrobetaines, e.g. (VIII) or (X), are prepared.
VLSI implementation of a high speed second order sigma-delta modulator with high-performance integrators (2002)

Oversampling analog-to-digital converters based on second-order sigma-delta (/spl Sigma//spl Delta/) modulation are attractive for VLSI implementation because they are tolerant of circuit nonidealities and component mismatch. This paper compares a high speed second-order /spl Sigma//spl Delta/ modulator to several alternative modulator architectures in the context of large bandwidth signal acquisition. Design details are presented for 0.5-/spl mu/m CMOS implementation. The experimental modulator is a fully differential circuit that operates from a /spl plusmn/3 V power supply and does not require the use of precision sample-and-hold circuitry. With an input bandwidth of 20 MHz and a clock rate of 160 MHz, the modulator reaches 26 dB signal-to-quantization noise (power) ratio (SQNR) using spectra simulation. All the elements of this design have implemented using switched-capacitor circuit techniques. Two identical noninverting parasitics-insensitive lossless switch capacitor sharing integrators have been used in order to achieve a large bandwidth and a linear integration.
Robust CLRF based nonlinear control design for time delay systems (2000)

The concept of control Lyapunov-Razumikhin function (CLRF) has been introduced as a tool for designing globally stabilizing control law for time delay systems. The control law has the same form as the domination redesign control law for nondelay systems which is (inverse) optimal and, hence, provides infinite gain margin and a nonlinear equivalent of 60/spl deg/ phase margin. In this paper we show that the CLRF based control laws also posses robustness to input unmodeled dynamics. The robustness to static input uncertainties is the same as the one of optimal nondelay systems. The robustness to dynamic uncertainties proven in this paper is weaker than that of optimal systems.