gebhart/patrepeval huggingface dataset:
Thiazoline-related TRPA1 agonist odorants orchestrate survival fate in mice (2020)

Summary Therapeutic hypothermia protects the brain after cardiopulmonary arrest. Innate fear has evolved to orchestrate protective effects in life-threatening situations. Thus, strong fear perception may induce a specialized life-protective metabolism based on hypothermia/hypometabolism; however, such phenomena and their inducers are yet to be elucidated. Here, we report that thiazoline-related fear odors (tFOs), which are TRPA1 agonists and induce robust innate fear in mice, induced hibernation-like systemic hypothermia/hypometabolism, accelerated glucose uptake in the brain, and suppressed aerobic metabolism via phosphorylation of pyruvate dehydrogenase, thereby enabling long-term survival in a lethal hypoxic environment. In contrast to hibernation, during which immune functions are generally suppressed, tFO-stimulation induced a crisis-response immune state characterized by potentiated innate immune functions but suppressed inflammation with anti-hypoxic ability. Collectively, these responses exerted potent therapeutic effects in cutaneous and cerebral ischemia/reperfusion injury models. Whole brain mapping and chemogenetic activation revealed that sensory representation of tFOs orchestrate survival fate via brain stem Sp5/NST to midbrain PBN pathway. TFO-induced strong crisis perception maximizes latent life-protective effects by shifting metabolism to a crisis response mode characterized by hypothermia, hypometabolism and crisis immunity.
Interaction of the Cytoplasmic Tail of CTLA-4 (CD152) with a Clathrin-Associated Protein Is Negatively Regulated by Tyrosine Phosphorylation (1997)

CTLA-4 (CD152), high-avidity receptor for CD80 and CD86, is a powerful regulator of T cell activation. While CTLA-4 functions at the cell surface, it is primarily localized in intracellular vesicles and cycles to the cell surface. The CTLA-4 cytoplasmic domain contains sequences that direct its intracellular localization and regulate its signaling. Here we demonstrate that effector molecules involved in receptor trafficking and signaling interact with distinct, but overlapping, sequences in the CTLA-4 cytoplasmic domain. Using the yeast two-hybrid method, we demonstrate association of the mu2 subunit of AP-2, the clathrin-associated complex found in plasma membrane-associated coated pits, with the cytoplasmic tail of CTLA-4, but not CD28. The mu1 subunit of AP-1, found in Golgi-associated coated pits, associated with neither CTLA-4 nor CD28. Sequences required for interaction of mu2 and CTLA-4 were localized to residues, 161TTGVY in CTLA-4; this sequence is N-terminal to, but overlaps with, a previously identified SH2 binding motif, 165YVKM, involved in CTLA-4 signaling. Mu2 interacted preferentially with CTLA-4 when residue 165Y was nonphosphorylated, whereas a PI3 kinase SH2 domain interacted preferentially when 165Y was phosphorylated. In co-transfection experiments, both tyrosine residues in the cytoplasmic tail of CTLA-4 (165Y and 182Y) were phosphorylated by the T lymphocyte-associated tyrosine kinase, p56lck. Thus, phosphorylation of CTLA-4 residue 165Y may reciprocally regulate signaling and trafficking of CTLA-4 by determining which effector molecules bind to its cytoplasmic tail.
Strain design optimization using reinforcement learning (2022)

Abstract Engineered microbial cells present a sustainable alternative to fossil-based synthesis of chemicals and fuels. Cellular synthesis routes are readily assembled and introduced into microbial strains using state-of-the-art synthetic biology tools. However, the optimization of the strains required to reach industrially feasible production levels is far less efficient. It typically relies on trial-and-error leading into high uncertainty in total duration and cost. New techniques that can cope with the complexity and limited mechanistic knowledge of the cellular regulation are called for guiding the strain optimization. In this paper, we put forward a multi-agent reinforcement learning (MARL) approach that learns from experiments to tune the metabolic enzyme levels so that the production is improved. Our method is model-free and does not assume prior knowledge of the microbe’s metabolic network or its regulation. The multi-agent approach is well-suited to make use of parallel experiments such as multi-well plates commonly used for screening microbial strains. We demonstrate the method’s capabilities using the genome-scale kinetic model of Escherichia coli , k-ecoli457, as a surrogate for an in vivo cell behaviour in cultivation experiments. We investigate the method’s performance relevant for practical applicability in strain engineering i.e. the speed of convergence towards the optimum response, noise tolerance, and the statistical stability of the solutions found. We further evaluate the proposed MARL approach in improving L-tryptophan production by yeast Saccharomyces cerevisiae , using publicly available experimental data on the performance of a combinatorial strain library. Overall, our results show that multi-agent reinforcement learning is a promising approach for guiding the strain optimization beyond mechanistic knowledge, with the goal of faster and more reliably obtaining industrially attractive production levels. Author summary Engineered microbial cells offer a sustainable alternative solution to chemical production from fossil resources. However, to make the chemical production using microbial cells economically feasible, they need to be substantially optimized. Due to the biological complexity, this optimization to reach sufficiently high production is typically a costly trial and error process. This paper presents an Artificial Intelligence (AI) approach to guide this task. Our tool learns a model from previous experiments and uses the model to suggest improvements to the engineering design, until a satisfactory production performance is reached. This paper evaluates the behaviour of the proposed AI method from several angles, including the amount of experiments needed, the tolerance to noise as well as the stability of the proposed designs.
Biotinylated Polymer-Ruthenium Conjugates: In Vitro and In Vivo Studies in a Triple-Negative Breast Cancer Model (2022)

The need for new therapeutic approaches for triple-negative breast cancer is a clinically relevant problem that needs to be solved. Using a multi-targeting approach to enhance cancer cell uptake, we synthesized a new family of ruthenium(II) organometallic complexes envisaging simultaneous active and passive targeting, using biotin and polylactide (PLA), respectively. All compounds with the general formula, [Ru(η<sup>5</sup>-CpR)(P)(2,2'-bipy-4,4'-PLA-biotin)][CF<sub>3</sub>SO<sub>3</sub>], where R is -H or -CH<sub>3</sub> and P is P(C<sub>6</sub>H<sub>5</sub>)<sub>3</sub>, P(C<sub>6</sub>H<sub>4</sub>F)<sub>3</sub> or P(C<sub>6</sub>H<sub>4</sub>OCH<sub>3</sub>)<sub>3</sub>, were tested against triple-negative breast cancer cells MDA-MB-231 showing IC<sub>50</sub> values between 2.3-14.6 µM, much better than cisplatin, a classical chemotherapeutic drug, in the same experimental conditions. We selected compound <b>1</b> (where R is H and P is P(C<sub>6</sub>H<sub>5</sub>)<sub>3</sub>), for further studies as it was the one showing the best biological effect. In a competitive assay with biotin, we showed that cell uptake via SMVT receptors seems to be the main transport route into the cells for this compound, validating the strategy of including biotin in the design of the compound. The effects of the compound on the hallmarks of cancer show that the compound leads to apoptosis, interferes with proliferation by affecting the formation of cell colonies in a dose-dependent manner and disrupts the cell cytoskeleton. Preliminary in vivo assays in N: NIH(S)II-nu/nu mice show that the concentrations of compound <b>1</b> used in this experiment (maximum 4 mg/kg) are safe to use in vivo, although some signs of liver toxicity are already found. In addition, the new compound shows a tendency to control tumor growth, although not significantly. In sum, we showed that compound <b>1</b> shows promising anti-cancer effects, bringing a new avenue for triple-negative breast cancer therapy.
Management of Cardiovascular Disease Patients With Confirmed or Suspected COVID-19 in Limited Resource Settings (2020)

In this paper, we provide recommendations on the management of cardiovascular disease (CVD) among patients with confirmed or suspected coronavirus disease (COVID-19) to facilitate the decision making of healthcare professionals in low resource settings. The emergence of novel coronavirus disease, also known as Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2), has presented an unprecedented global challenge for the healthcare community. The ability of SARS-CoV-2 to get transmitted during the asymptomatic phase and its high infectivity have led to the rapid transmission of COVID-19 beyond geographic regions, leading to a pandemic. There is concern that COVID-19 is cardiotropic, and it interacts with the cardiovascular system on multiple levels. Individuals with established CVD are more susceptible to severe COVID-19. Through a consensus approach involving an international group this WHF statement summarizes the links between cardiovascular disease and COVID-19 and present some practical recommendations for the management of hypertension and diabetes, acute coronary syndrome, heart failure, rheumatic heart disease, Chagas disease, and myocardial injury for patients with COVID-19 in low-resource settings. This document is not a clinical guideline and it is not intended to replace national clinical guidelines or recommendations. Given the rapidly growing burden posed by COVID-19 illness and the associated severe prognostic implication of CVD involvement, further research is required to understand the potential mechanisms linking COVID-19 and CVD, clinical presentation, and outcomes of various cardiovascular manifestations in COVID-19 patients.
High rate deposition of ZnO thin films by a small-scale inductively coupled argon plasma generated in open air (2010)

Linear transparent ZnO films were deposited using a millimetre sized inductively coupled argon plasma at atmospheric pressure in open air. Increasing the substrate temperature enabled high growth rates between 200 and 1 µm s−1 to be obtained. The optical transmission of the obtained films is above 80% in the visible and the roughness of the films had a value of 15 nm. Plasma gas temperatures estimated from the rotational temperature of N2 assessed by optical emission spectroscopy suggest values of up to approximately 1800 K. The detected species in the plasma were argon and zinc radicals, but no ions. The high growth rate of the films is attributed to the rapid melting and sputtering of the metallic source filament, the produced species being carried to the substrate surface by the plasma gas. High substrate temperatures as well as high scanning rates are considered crucial to the formation of transparent, dense ZnO films, the first promoting surface migration and the second permitting regulation of the flux of oxygen to the surface.
Molecular mechanism of the chitinolytic peroxygenase reaction (2020)

Lytic polysaccharide monooxygenases (LPMOs) are a recently discovered class of monocopper enzymes broadly distributed across the tree of life. Recent reports indicate that LPMOs can use H<sub>2</sub>O<sub>2</sub> as an oxidant and thus carry out a novel type of peroxygenase reaction involving unprecedented copper chemistry. Here, we present a combined computational and experimental analysis of the H<sub>2</sub>O<sub>2</sub>-mediated reaction mechanism. In silico studies, based on a model of the enzyme in complex with a crystalline substrate, suggest that a network of hydrogen bonds, involving both the enzyme and the substrate, brings H<sub>2</sub>O<sub>2</sub> into a strained reactive conformation and guides a derived hydroxyl radical toward formation of a copper-oxyl intermediate. The initial cleavage of H<sub>2</sub>O<sub>2</sub> and subsequent hydrogen atom abstraction from chitin by the copper-oxyl intermediate are the main energy barriers. Stopped-flow fluorimetry experiments demonstrated that the priming reduction of LPMO-Cu(II) to LPMO-Cu(I) is a fast process compared to the reoxidation reactions. Using conditions resulting in single oxidative events, we found that reoxidation of LPMO-Cu(I) is 2,000-fold faster with H<sub>2</sub>O<sub>2</sub> than with O<sub>2</sub>, the latter being several orders of magnitude slower than rates reported for other monooxygenases. The presence of substrate accelerated reoxidation by H<sub>2</sub>O<sub>2</sub>, whereas reoxidation by O<sub>2</sub> became slower, supporting the peroxygenase paradigm. These insights into the peroxygenase nature of LPMOs will aid in the development and application of enzymatic and synthetic copper catalysts and contribute to a further understanding of the roles of LPMOs in nature, varying from biomass conversion to chitinolytic pathogenesis-defense mechanisms.
Nonlinear manipulation and analysis of large DNA datasets (2022)

Information processing functions are essential for organisms to perceive and react to their complex environment, and for humans to analyze and rationalize them. While our brain is extraordinary at processing complex information, winner-take-all, as a type of biased competition is one of the simplest models of lateral inhibition and competition among biological neurons. It has been implemented as DNA-based neural networks, for example, to mimic pattern recognition. However, the utility of DNA-based computation in information processing for real biotechnological applications remains to be demonstrated. In this paper, a biased competition method for nonlinear manipulation and analysis of mixtures of DNA sequences was developed. Unlike conventional biological experiments, selected species were not directly subjected to analysis. Instead, parallel computation among a myriad of different DNA sequences was carried out to reduce the information entropy. The method could be used for various oligonucleotide-encoded libraries, as we have demonstrated its application in decoding and data analysis for selection experiments with DNA-encoded chemical libraries against protein targets.
CMOS-Compatible Dielectric Constant Engineering by Embedding Metallic Particles in Aluminum Oxide (2012)

We report the fabrication of a composite dielectric with increased dielectric constant consisting of aluminum oxide deposited by ALD and aluminum nanoparticles. The fabrication process of the composite is CMOS compatible. For a metal fraction of 0.28 the composite's dielectric constant increases by up to 60% compared to simple Al2O3. The composite dielectric preserves high breakdown strength with a breakdown field larger than 2 MV/cm at the highest metal concentration. Additionally, the material exhibits a low leakage current density of ~10-8 A/cm2 at a field of at least 0.5 MV/cm. © 2012 The Electrochemical Society.
More Is Less: Signal Processing and the Data Deluge (2011)

The data deluge is changing the operating environment of many sensing systems from data-poor to data-rich--so data-rich that we are in jeopardy of being overwhelmed. Managing and exploiting the data deluge require a reinvention of sensor system design and signal processing theory. The potential pay-offs are huge, as the resulting sensor systems will enable radically new information technologies and powerful new tools for scientific discovery.
VoiceFilter-Lite: Streaming Targeted Voice Separation for On-Device Speech Recognition (2020)

We introduce VoiceFilter-Lite, a single-channel source separation model that runs on the device to preserve only the speech signals from a target user, as part of a streaming speech recognition system. Delivering such a model presents numerous challenges: It should improve the performance when the input signal consists of overlapped speech, and must not hurt the speech recognition performance under all other acoustic conditions. Besides, this model must be tiny, fast, and perform inference in a streaming fashion, in order to have minimal impact on CPU, memory, battery and latency. We propose novel techniques to meet these multi-faceted requirements, including using a new asymmetric loss, and adopting adaptive runtime suppression strength. We also show that such a model can be quantized as a 8-bit integer model and run in realtime.
Preclinical Characterization of Once Weekly Basal Insulin Fc (BIF) (2021)

Abstract Weekly basal insulin injections may increase treatment adherence in subjects with diabetes and an appropriately engineered weekly basal insulin may reduce daily pharmacokinetic (PK)/pharmacodynamic (PD) fluctuations compared to currently available daily basal insulins. Therefore, a weekly insulin has the potential to not only ease the burden of insulin therapy, but also improve outcomes for subjects with diabetes in a real-world setting. Basal insulin Fc (BIF, LY3209590) is an insulin Fc-fusion protein in clinical testing as a once weekly treatment for type 1 and type 2 diabetes mellitus (T1DM, T2DM). BIF is comprised of a human single-chain insulin fused to a human IgG2 Fc domain through a peptide linker. The in vitro evaluation determined that BIF exhibited reduced insulin receptor (IR) potency with full agonism, selectivity against human insulin-like growth factor-1 receptor (hIGF-1R), and functional properties similar to native human insulin. The binding affinity of BIF for hIR isoform A, Ki = 25 nM (SEM = 4, n=10), and hIR isoform B, Ki = 26 nM (SEM = 4, n=10), was more than two orders of magnitude weaker than human insulin. BIF stimulated IR phosphorylation in cells with reduced potency, but full agonism, and showed a significantly faster hIR dephosphorylation profile than either human insulin or AspB10 insulin. BIF stimulated de novo lipogenesis in 3T3-L1 adipocytes and cell proliferation in SAOS-2 and H4IIE cells with at least a 70-fold reduction in potency compared to human insulin. BIF possessed markedly reduced binding and activation of hIGF-1R making definitive mitogenic measurements unattainable. In preclinical in vivo pharmacology studies using streptozotocin (STZ)-treated diabetic rats, a statistically significant decrease in blood glucose compared to vehicle-treated animals was seen 24 hours post-injection and persisted through 336 hours post-injection following a single subcutaneous administration (30 nmol/kg) of BIF. In STZ-treated rats, BIF reached a Tmax at 48 hours, possessed an apparent clearance rate of ~0.85 mL/hr/kg, and t1/2 of ~120 hrs. Collectively, these results demonstrate that BIF possesses selective IR agonism with a pharmacological profile similar to native insulin, however with a significantly reduced potency, and a significantly extended time action profile in preclinical animal models supporting once weekly testing in the clinic.
An RFID-based technology for electronic component and system Counterfeit detection and Traceability (2015)

The vulnerabilities in today's supply chain have raised serious concerns about the security and trustworthiness of electronic components and systems. Testing for device provenance, detection of counterfeit integrated circuits/systems, and traceability are challenging issues to address. In this paper, we develop a novel RFID-based system suitable for electronic component and system Counterfeit detection and System Traceability called CST. CST is composed of different types of on-chip sensors and in-system structures that provide the information needed to detect multiple counterfeit IC types (recycled, cloned, etc.), verify the authenticity of the system with some degree of confidence, and track/identify boards. Central to CST is an RFID tag employed as storage and a channel to read the information from different types of chips on the printed circuit board (PCB) in both power-off and power-on scenarios. Simulations and experimental results using Spartan 3E FPGAs demonstrate the effectiveness of this system. The efficiency of the radio frequency (RF) communication has also been verified via a PCB prototype with a printed slot antenna.
Standoff handheld real-time early warning detector (SHREWD) (2000)

A lightweight, compact sensor breadboard demonstrator is being developed that will be capable of detecting chemical agents in the 8 - 12 micrometers band by DIAL for ranges on the order of 4 km. Engineering analysis shows that the overall sensor size and weight would be approximately 1 cu. ft. and 35 lbs., respectively. The sensor is composed of a 12.5 cm diameter, off-axis paraboloid receive telescope and a 300 Hz repetition rate solid-state laser transmitter. The transmitter is based on a diode-pumped, 1.06 micrometers laser with an output energy of 20 mJ and two cascaded OPO stages that shift the laser wavelength to the far IR bands. The first stage OPO is configured in an arrangement that shifts the laser output to beyond 2 micrometers . The second stage OPO completes the shift to the 8 - 12 micrometers band, giving an overall 1.06 (mu) $m yields 8 - 12 micrometers conversion efficiency of 2% and a sensor output power of 0.1 W.
Delay-Induced Multistability and Loop Formation in Neuronal Networks with Spike-Timing-Dependent Plasticity (2018)

Spike-timing-dependent plasticity (STDP) adjusts synaptic strengths according to the precise timing of pre- and postsynaptic spike pairs. Theoretical and computational studies have revealed that STDP may contribute to the emergence of a variety of structural and dynamical states in plastic neuronal populations. In this manuscript, we show that by incorporating dendritic and axonal propagation delays in recurrent networks of oscillatory neurons, the asymptotic connectivity displays multistability, where different structures emerge depending on the initial distribution of the synaptic strengths. In particular, we show that the standard deviation of the initial distribution of synaptic weights, besides its mean, determines the main properties of the emergent structural connectivity such as the mean final synaptic weight, the number of two-neuron loops and the symmetry of the final structure. We also show that the firing rates of the neurons affect the evolution of the network, and a more symmetric configuration of the synapses emerges at higher firing rates. We justify the network results based on a two-neuron framework and show how the results translate to large recurrent networks.
Extreme Temperature Electronics based on Self-Adaptive System using Field Programmable Gate Array (2007)

Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a self-adaptive system using a field programmable gate array (FPGA) and data converters. The self-adaptive system can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the self-adaptive system are operating in extreme temperatures (from 120degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The self-adaptive system controls the RAA IC and is realized on Commercial-Off-The-Shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) show the change over temperature of the response of the RAA for all possible bias voltage and demonstrate the feasibility of this approach.