Miracle-dz/UniFAR-FTUs huggingface dataset:
How electrostatic networks modulate specificity and stability of collagen

Significance We designed a synthetic heterotrimeric triple helix by jointly considering stability of a target abc association of three unique chains and the energy gap between the target and 26 competing states. The critical balance of electrostatic and hydrogen-bonding interactions is dramatically revealed in an atomic-resolution structure of the design. Mutations in multibody electrostatic interactions uncover cooperative networks of salt bridges. This work advances our understanding of the role of surface electrostatics and hydrogen bonding in protein stability and fold specificity and provides computational tools for modeling collagen. One-quarter of the 28 types of natural collagen exist as heterotrimers. The oligomerization state of collagen affects the structure and mechanics of the extracellular matrix, providing essential cues to modulate biological and pathological processes. A lack of high-resolution structural information limits our mechanistic understanding of collagen heterospecific self-assembly. Here, the 1.77-Å resolution structure of a synthetic heterotrimer demonstrates the balance of intermolecular electrostatics and hydrogen bonding that affects collagen stability and heterospecificity of assembly. Atomistic simulations and mutagenesis based on the solved structure are used to explore the contributions of specific interactions to energetics. A predictive model of collagen stability and specificity is developed for engineering novel collagen structures.
ASP8273 tolerability and antitumor activity in tyrosine kinase inhibitor‐naïve Japanese patients with EGFR mutation‐positive non‐small‐cell lung cancer

Epidermal growth factor receptor (EGFR) activating mutations occur in approximately 50% of East Asian patients with non‐small‐cell lung cancer (NSCLC) and confer sensitivity to tyrosine kinase inhibitors (TKIs). ASP8273 is an irreversible EGFR‐TKI, given orally, that inhibits EGFR activating mutations and has shown clinical activity in patients with EGFR mutation‐positive NSCLC. Epidermal growth factor receptor‐TKI‐naïve Japanese adult patients (≥20 years) with NSCLC harboring EGFR mutations were enrolled in this open‐label, single‐arm, phase II study (ClinicalTrials.gov identifier NCT02500927). Patients received ASP8273 300 mg once daily until discontinuation criteria were met. The primary end‐point was to determine the safety of ASP8273 300 mg; the secondary end‐point was antitumor activity defined by RECIST version 1.1. Thirty‐one patients (12 men and 19 women; median age, 64 years [range, 31‐82 years]) with EGFR mutation‐positive NSCLC were enrolled; as of 23 February 2016, 25 patients (81%) were still on study. Of the 31 patients, 27 (87%) had an exon 19 deletion (n = 13, 42%) or an L858R (n = 14, 45%) EGFR activating mutation, and two (7%) had an L861Q mutation. Five patients (16%) had other EGFR activating mutations, two had an activating mutation and the T790M resistance mutation. The most commonly reported treatment‐emergent adverse event was diarrhea (n = 24, 77%). All patients had at least one post‐baseline scan; one patient (3%) achieved a confirmed complete response, 13 (42%) had a confirmed partial response, and 15 (48%) had confirmed stable disease (disease control rate, 94% [n = 29/31]) per investigator assessment. Once‐daily ASP8273 at 300 mg was generally well tolerated and showed antitumor activity in TKI‐naïve Japanese patients with EGFR mutation‐positive NSCLC.
Generation of a multi‐functional, target organ‐specific, anti‐fibrotic molecule by molecular engineering of the extracellular matrix protein, decorin

Extracellular matrix (ECM) molecules play important roles in regulating processes such as cell proliferation, migration, differentiation and survival. Decorin is a proteoglycan that binds to (‘decorates’) collagen fibrils in the ECM. Decorin also interacts with many growth factors and their receptors, the most notable of these interactions being its inhibitory activity on TGF‐β, the growth factor responsible for fibrosis formation. We have generated a recombinant, multi‐functional, fusion‐protein consisting of decorin as a therapeutic domain and a vascular homing and cell‐penetrating peptide as a targeting vehicle. This recombinant decorin (CAR‐DCN) accumulates at the sites of the targeted disease at higher levels and, as a result, has substantially enhanced biological activity over native decorin. CAR‐DCN is an example of how molecular engineering can give a compound the ability to seek out sites of disease and enhance its therapeutic potential. CAR‐DCN will hopefully be used to treat severe human diseases.
How polarization can provide an increase in content dissemination amongst the highly ranked influencers

This work extends a model of simulating influence in a network of stochastic edge dynamics to account for polarization. The model built upon is termed Dynamic Communicators and seeks to understand the process which produces low volume, high influence amongst users. This model is extended to introduce the effects polarization. The fundamental assumption of the model is that a parameter of importance governs the rate of message responsiveness. With the introduction of relative incremental changes according to the response incurred in adjacent nodes receiving content, the changes in the power brokerage of a network can be examined. This provides a content agnostic interpretation for the desire to proliferate content amongst peers. From the results of the simulations, the analysis shows that a lack of polarization incrementally develops a more level discussion network with more even response rates whereas the polarization introduction leads to a gradual increase in response rate disparity.
Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond

Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful because it can be used to test specific questions of central interest in studies with factorial designs. It weighs several means and combines them into one or two sets that can be tested with t tests. The effect size produced by a contrast analysis is simply the difference between means. The CI of the effect size informs directly about direction, hypothesis exclusion, and the relevance of the effects of interest. However, any interpretation in terms of precision or likelihood requires the use of likelihood intervals or credible intervals (Bayesian). These various intervals and even a Bayesian t test can be obtained easily with free software. This tutorial reviews these methods to guide researchers in answering the following questions: When I analyze mean differences in factorial designs, where can I find the effects of central interest, and what can I learn about their effect sizes?
Acute Clinical Manifestation of Mesenteric Heterotopic Pancreatitis: A Pre- and Postoperative Confirmed Case

Heterotopic pancreas is a relatively uncommon congenital anomaly, defined as pancreatic tissue in ectopic sites without an anatomic and vascular continuity with the main body of the pancreas. We report the case of a 58-year-old woman who was admitted to the hospital with the clinical suspicion of a mild, acute pancreatitis. Computed tomography, magnetic resonance imaging, transabdominal ultrasound, and endoscopic ultrasound revealed a normal orthotopic pancreas and the suspicion of a large heterotopic pancreas in the small bowel mesentery with signs of acute inflammation. The diagnosis of mesenteric heterotopic pancreatitis was preoperatively confirmed by endoscopic ultrasound-guided fine-needle aspiration and consequently histologically established after surgical resection.
Oxidative stress and metabolic markers in pre- and postnatal polycystic ovary syndrome rat protocols

Background Several studies have described an enhanced inflammatory status and oxidative stress balance disruption in women with polycystic ovary syndrome (PCOS). However, there is scarce information about redox markers in the blood of androgenized animal models. Here, we evaluated the serum/plasma oxidative stress marker and metabolic parameter characteristics of prenatal (PreN) and postnatal (PostN) androgenized rat models of PCOS. Materials and methods For PreN androgenization (n=8), 2.5 mg of testosterone propionate was subcutaneously administered to dams at embryonic days 16, 17, and 18, whereas PostN androgenization (n=7) was accomplished by subcutaneously injecting 1.25 mg of testosterone propionate to animals at PostN day 5. A unique control group (n=8) was constituted for comparison. Results Our results indicate that PostN group rats exhibited particular modifications in the oxidative stress marker, an increased plasma ferric-reducing ability of plasma, and an increased antioxidant capacity reflected by higher albumin serum levels. PostN animals also presented increased total cholesterol and triglyceride–glucose levels, suggesting severe metabolic disarrangement. Conclusion Study findings indicate that changes in oxidative stress could be promoted by testosterone propionate exposure after birth, which is likely associated with anovulation and/or lipid disarrangement.
Advanced Wireless Local Positioning via Compressed Sensing

Wireless local positioning systems are based on measurements of signal time of flights and/or bearing angles to determine the position of an active transmitter in 3-D space. Traditional time-of-flight and angle measurements with such positioning systems require many data samples at high rates to fulfill the Nyquist criterion. Moreover, in multipath channels the ability of classical signal processing methods to resolve the delay and bearing vectors of the multiple transmission paths is strictly limited by the radio frequency bandwidth and aperture size. In this paper, we show that the wireless channel is ideally suited for the application of compressed sensing. We can thus reduce the number of samples without major losses in localization performance, or we can improve the resolution. After introducing a general model of a localization task with multipath propagation, and following the definition of key parameters of existing systems, we review the necessary data processing stages with compressed sensing and verify its excellent applicability. Finally, measurements are presented to verify the theoretical predictions experimentally.
Automated Performance Modeling Based on Runtime Feature Detection and Machine Learning

Automated performance modeling and performance prediction of parallel programs are highly valuable in many use cases, such as in guiding task management and job scheduling, offering insights of application behaviors, assisting resource requirement estimation, etc. The performance of parallel programs is affected by numerous factors, including but not limited to hardware, system software, applications, algorithms, and input parameters, thus an accurate performance prediction is often a challenging and daunting task. In this study, we focus on automatically predicting the execution time of parallel programs (more specifically, MPI programs) with different inputs, at different scale, and without domain knowledge. We model the correlation between the execution time and domain-independent runtime features. These features include values of variables, counters of branches, loops, and MPI communications. Through automatically instrumenting an MPI program, each execution of the program will output a feature vector and its corresponding execution time. After collecting data from executions with different inputs, a random forest machine learning approach is used to build an empirical performance model, which can predict the execution time of the program with a new input. Our experiments and analyses of three parallel programs, Graph500, GalaxSee and SMG2000, on three different systems show that our method performs well, with less than 20% error in predictions on average.
A DVFS-Capable Heterogeneous Network-on-Chip Architecture for Power Constrained Multi-Cores

In the multi-core era, the Networks-on-Chip (NoCs) emerged as the de-facto interconnect due to their scalability and flexibility. Moreover, they strongly influence the power consumption and performance of the entire platform, thus representing a key component to be optimized. In this scenario, several proposals in the literature presented Dynamic Voltage and Frequency (DVFS) capable NoCs to trade the power and performance metrics. However, the NoC traffic is highly variable due to the different phases an application crosses during its own execution. Last, the coherence protocol greatly contributes to the traffic shape. In a nutshell, the NoC traffic shape is mainly due to the coherence protocol, while the specific application only influences the traffic volume. Few seminal works discussed coherence-aware DVFS schemes for NoCs. This thesis presented a novel DVFS-capable heterogeneous NoCs. A fine grain analysis of the traffic composition enabled a further optimization of the DVFS actuation. The proposed NoC is capable to optimally balance the power and performance at low, medium and high traffic. Thus delivering an holistic solution that is roughly application independent. This is achieved thanks to a load balancer module that can route the traffic to the different implemented physical networks. The mechanism observes the traffic load and adjusts the frequency of each physical NoC to optimally match the objective function. The novel NoC has been integrated in the Gem5 fullsystem simulator and compared with the baseline NoC and a state of the art DVFS-capable methodology. Results are extracted considering a 64-core architecture executing the Splash2 benchmarks. Results show that the proposed NoC almost provides the same performance of the performance-aware baseline NoC with an energy reduction of 30% and one third less resources.
Robust Gyroscope-Aided Camera Self-Calibration

Camera calibration for estimating the intrinsic parameters and lens distortion is a prerequisite for various monocular vision applications including feature tracking and video stabilization. This application paper proposes a model for estimating the parameters on the fly by fusing gyroscope and camera data, both readily available in modern day smartphones. The model is based on joint estimation of visual feature positions, camera parameters, and the camera pose, the movement of which is assumed to follow the movement predicted by the gyroscope. Our model assumes the camera movement to be free, but continuous and differentiable, and individual features are assumed to stay stationary. The estimation is performed online using an extended Kalman filter, and it is shown to outperform existing methods in robustness and insensitivity to initialization. We demonstrate the method using simulated data and empirical data from an iPad.
Evidence for the presence of Ctenocephalides orientis in livestock dwellings in northwest Iran

Fleas are important vectors of diseases such as murine typhus, tularaemia, hymenolepiasis and plague. The presence of active foci and history of human‐ and flea‐transmitted plague in northwest Iran prompted the present group to collect and identify fleas from human and livestock dwellings across West Azerbaijan Province. Adult fleas were collected and identified using routine taxonomic keys. Species designation was confirmed by sequencing the cytochrome oxidase subunit I (COI). Of the collected specimens (n = 989), 104 were collected off‐host (30 from human dwellings and 74 in light traps) and the rest were found on hosts (107 on animals and 778 by human bait). Of these fleas, 394 (40%) were male and 595 (60%) were female. The collected specimens belonged to the species Ctenocephalides canis, Ctenocephalides felis, Ctenocephalides orientis and Pulex irritans (all: Siphonaptera: Pulicidae). The amplified COI fragment, in addition to confirming the morphological identification of species, showed good efficacy in separating the different species in the phylogenetic analysis. In addition to the identification of fleas from human and livestock dwellings using morphological and molecular characteristics, the current paper represents the first report of the presence of C. orientis in northwest Iran. This finding suggests that changing climate conditions may have expanded the distribution of this species.
Spline: Spark Lineage, not only for the Banking Industry

Data lineage tracking is one of the significant problems that financial institutions face. Banking and other highly regulated industries are forced to have a good understanding of how data flows through their systems to comply with strict regulatory frameworks. Many of these organizations also utilize big data technologies such as Hadoop and Apache Spark. Spark has become one of the most popular engines for big data computation, but it lacks support for data lineage tracking. This paper describes Spline - a data lineage tracking and visualization tool for Apache Spark. Spline captures and stores lineage information from internal Spark execution plans in a lightweight, unobtrusive and easy to use manner. Additionally, Spline offers a modern user interface that allows non-technical users to understand the logic of Apache Spark applications.
Biotic responses buffer warming‐induced soil organic carbon loss in Arctic tundra

Climate warming can result in both abiotic (e.g., permafrost thaw) and biotic (e.g., microbial functional genes) changes in Arctic tundra. Recent research has incorporated dynamic permafrost thaw in Earth system models (ESMs) and indicates that Arctic tundra could be a significant future carbon (C) source due to the enhanced decomposition of thawed deep soil C. However, warming‐induced biotic changes may influence biologically related parameters and the consequent projections in ESMs. How model parameters associated with biotic responses will change under warming and to what extent these changes affect projected C budgets have not been carefully examined. In this study, we synthesized six data sets over 5 years from a soil warming experiment at the Eight Mile Lake, Alaska, into the Terrestrial ECOsystem (TECO) model with a probabilistic inversion approach. The TECO model used multiple soil layers to track dynamics of thawed soil under different treatments. Our results show that warming increased light use efficiency of vegetation photosynthesis but decreased baseline (i.e., environment‐corrected) turnover rates of SOC in both the fast and slow pools in comparison with those under control. Moreover, the parameter changes generally amplified over time, suggesting processes of gradual physiological acclimation and functional gene shifts of both plants and microbes. The TECO model predicted that field warming from 2009 to 2013 resulted in cumulative C losses of 224 or 87 g/m2, respectively, without or with changes in those parameters. Thus, warming‐induced parameter changes reduced predicted soil C loss by 61%. Our study suggests that it is critical to incorporate biotic changes in ESMs to improve the model performance in predicting C dynamics in permafrost regions.
Design of an Intelligent Agent for Stimulating Brainstorming

In recent years, brainstorming has gradually become a mainstream approach used by groups of people to collect ideas before making decisions. This approach is useful in handling the predicament of lacking ideas on specific topics for individual members, and breaking through the limitations of their own experiences. However, in the process of group brainstorming, there exists some common problems such as the lack of comprehensive discussion contents due to the limited experiences recalled by the members, the stagnation in the progress, and so on. Therefore, in this paper, we propose the design of an intelligent agent system that plays the vital role of facilitator to participate in the brainstorming process; in other words, our system can discuss a designated topic on an on-line chatroom with other members in a brainstorming discussion. This system collects textual data and establishes the knowledge model in a specific domain with machine learning methods prior to the brainstorming. Then, in the brainstorming process, it attempts to conjecture the topic of the current dialogues, determine the progress, and generate responses to the brainstorming chatroom in order to come up with diverse ideas or extend the present topic. The goal of this system is to increase the diversity and profundity of discussions, and make the whole process smooth and fruitful. The results of our experiments show that our intelligent agent is effective in helping on-line brainstorming, especially idea generations.
Activity-Based Detection and Bioanalytical Confirmation of a Fatal Carfentanil Intoxication

Carfentanil, one of the most potent opioids known, has recently been reported as a contaminant in street heroin in the United States and Europe, and is associated with an increased number of life-threatening emergency department admissions and deaths. Here, we report on the application of a novel in vitro opioid activity reporter assay and a sensitive bioanalytical assay in the context of a fatal carfentanil intoxication, revealing the highest carfentanil concentrations reported until now. A 21-year-old male was found dead at home with a note stating that he had taken carfentanil with suicidal intentions. A foil bag and plastic bag labeled “C.50” were found at the scene. These bags were similar to a sample obtained by the Belgian Early Warning System on Drugs from a German darknet shop and to those found in the context of a fatality in Norway. Blood, urine and vitreous, obtained during autopsy, were screened with a newly developed in vitro opioid activity reporter assay able to detect compounds based on their μ-opioid receptor activity rather than their chemical structure. All extracts showed strong opioid activity. Results were confirmed by a bioanalytical assay, which revealed extremely high concentrations for carfentanil and norcarfentanil. It should be noted that carfentanil concentrations are typically in pg/mL, but here they were 92 ng/mL in blood, 2.8 ng/mL in urine, and 23 ng/mL in vitreous. The blood and vitreous contained 0.532 and 0.300 ng/mL norcarfentanil, respectively. No norcarfentanil was detected in urine. This is the first report where a novel activity-based opioid screening assay was successfully deployed in a forensic case. Confirmation and quantification using a validated bioanalytical procedure revealed the, to our knowledge, highest carfentanil concentrations reported in humans so far.