Miracle-dz/UniFAR-FTUs huggingface dataset:
Wheat Germ Cell-Free System-Based Production of Malaria Proteins for Discovery of Novel Vaccine Candidates

ABSTRACT One of the major bottlenecks in malaria research has been the difficulty in recombinant protein expression. Here, we report the application of the wheat germ cell-free system for the successful production of malaria proteins. For proof of principle, the Pfs25, PfCSP, and PfAMA1 proteins were chosen. These genes contain very high A/T sequences and are also difficult to express as recombinant proteins. In our wheat germ cell-free system, native and codon-optimized versions of the Pfs25 genes produced equal amounts of proteins. PfCSP and PfAMA1 genes without any codon optimization were also expressed. The products were soluble, with yields between 50 and 200 μg/ml of the translation mixture, indicating that the cell-free system can be used to produce malaria proteins without any prior optimization of their biased codon usage. Biochemical and immunocytochemical analyses of antibodies raised in mice against each protein revealed that every antibody retained its high specificity to the parasite protein in question. The development of parasites in mosquitoes fed patient blood carrying Plasmodium falciparum gametocytes and supplemented with our mouse anti-Pfs25 sera was strongly inhibited, indicating that both Pfs25-3D7/WG and Pfs25-TBV/WG retained their immunogenicity. Lastly, we carried out a parallel expression assay of proteins of blood-stage P. falciparum. The PCR products of 124 P. falciparum genes chosen from the available database were used directly in a small-scale format of transcription and translation reactions. Autoradiogram testing revealed the production of 93 proteins. The application of this new cell-free system-based protocol for the discovery of malaria vaccine candidates will be discussed.
Exact Maximum Entropy Inverse Optimal Control for modeling human attention switching and control

Maximum Causal Entropy (MCE) Inverse Optimal Control (IOC) has become an effective tool for modeling human behavior in many control tasks. Its advantage over classic techniques for estimating human policies is the transferability of the inferred objectives: Behavior can be predicted in variations of the control task by policy computation using a relaxed optimality criterion. However, exact policy inference is often computationally intractable in control problems with imperfect state observation. In this work, we present a model class that allows modeling human control of two tasks of which only one be perfectly observed at a time requiring attention switching. We show how efficient and exact objective and policy inference via MCE can be conducted for these control problems. Both MCE-IOC and Maximum Causal Likelihood (MCL)-IOC, a variant of the original MCE approach, as well as Direct Policy Estimation (DPE) are evaluated using simulated and real behavioral data. Prediction error and generalization over changes in the control process are both considered in the evaluation. The results show a clear advantage of both IOC methods over DPE, especially in the transfer over variation of the control process. MCE and MCL performed similar when training on a large set of simulated data, but differed significantly on small sets and real data.
Trend Detection in Annual Temperature & Precipitation using the Mann Kendall Test – A Case Study to Assess Climate Change on Select States in the Northeastern United States

The impact of climate change on annual air temperature and precipitation has received a great deal of attention by scholars worldwide. Many studies have been conducted to illustrate that changes in annual temperature and precipitation are becoming evident on a global scale. This study focuses on detecting trends in annual temperature and precipitation for the nine states in the Northeastern United States. For this study, the widely used modified Mann-Kendall test was run at 5% significance level on time series data for each of the nine states for the time period, 1900 to 2011. The resultant MannKendall test statistic (S) indicates how strong the trend in temperature and precipitation is and whether it is increasing or decreasing. For temperature, all the states indicate statistically significant increasing trends, except for Pennsylvania and Maine that do not indicate statistically significant trends. In the case of precipitation, the states of New Hampshire and Maine do not show statistically significant results, while the other states show statistically significant increasing trends. On the contrary, linear trend line plotting indicates increasing trend in temperature for all nine northeastern states in the range of 0.00006 to 0.02 °F/yr, while a US EPA study demonstrates that the US average temperature rise is 1.3°F/century. [1] For precipitation, the linear trend line indicates a decreasing trend for Maine, while the other eight states have an increasing trend that ranges from 0.03 to 0.13 mm/yr. This thesis or dissertation is available at ScholarlyCommons: http://repository.upenn. edu/mes_capstones/47 Trend Detection in Annual Temperature & Precipitation using the Mann Kendall Test – A Case Study to Assess Climate Change on Select States in the Northeastern United States
Atmospheric record in the Hadean Eon from multiple sulfur isotope measurements in Nuvvuagittuq Greenstone Belt (Nunavik, Quebec)

Significance Sulfur isotopes in ancient Earth sediments have peculiar compositions resulting from photochemical reactions of sulfur-bearing gaseous species with UV photons in the anoxic early Earth's atmosphere. High-precision measurements of sediments from distinct localities have revealed that these isotopic anomalies are sensitive to the abundances of atmospheric gases. They thus appear as promising metrics of ancient atmospheric composition. In the present study, we focus on the origin and extent of this atmospheric memory. We analyzed the multiple S-isotope compositions of some of the oldest metasediments preserved on Earth (originating from the >3.8-Ga Nuvvuagittuq Greenstone Belt, Canada) and found that this unusual atmospheric fingerprint has been present since the end of the Hadean, the earliest eon of Earth history. Mass-independent fractionation of sulfur isotopes (S-MIF) results from photochemical reactions involving short-wavelength UV light. The presence of these anomalies in Archean sediments [(4–2.5 billion years ago, (Ga)] implies that the early atmosphere was free of the appropriate UV absorbers, of which ozone is the most important in the modern atmosphere. Consequently, S-MIF is considered some of the strongest evidence for the lack of free atmospheric oxygen before 2.4 Ga. Although temporal variations in the S-MIF record are thought to depend on changes in the abundances of gas and aerosol species, our limited understanding of photochemical mechanisms complicates interpretation of the S-MIF record in terms of atmospheric composition. Multiple sulfur isotope compositions (δ33S, δ34S, and δ36S) of the >3.8 billion-year-old Nuvvuagittuq Greenstone Belt (Ungava peninsula) have been investigated to track the early origins of S-MIF. Anomalous S-isotope compositions (Δ33S up to +2.2‰) confirm a sedimentary origin of sulfide-bearing banded iron and silica-rich formations. Sharp isotopic transitions across sedimentary/igneous lithological boundaries indicate that primary surficial S-isotope compositions have been preserved despite a complicated metamorphic history. Furthermore, Nuvvuagittuq metasediments recorded coupled variations in 33S/32S, 34S/32S, and 36S/32S that are statistically indistinguishable from those identified several times later in the Archean. The recurrence of the same S-isotope pattern at both ends of the Archean Eon is unexpected, given the complex atmospheric, geological, and biological pathways involved in producing and preserving this fractionation. It implies that, within 0.8 billion years of Earth’s formation, a common mechanism for S-MIF production was established in the atmosphere.
Ultraviolet resistance modification of poly(p-phenylene-1,3,4-oxadiazole) and poly(p-phenylene terephthalamide) fibers with polyhedral oligomeric silsesquioxane

Octa-ammonium chloride salt of polyhedral oligomeric silsesquioxane (POSS) was synthesized by a hydrolysis reaction and introduced into poly(p-phenylene-1,3,4-oxadiazole) (p-POD) and poly(p-phenylene terephthalamide) (PPTA) fibers by a finishing method to enhance the UV resistance. The effects of the POSS concentration, treatment temperature, and time on the tensile strength of the fibers were investigated. The surface morphology, mechanical properties, crystallinity, degree of orientation of fibers, and intrinsic viscosity of the polymer solution were characterized in detail. The results indicate that the tensile strength retention and intrinsic viscosity retention of the fibers treated with POSS were much higher than those of the untreated fibers after the same accelerated irradiation time; this demonstrated that this treatment method was feasible. We also found that the efficacy of the protection provided by POSS was more beneficial to p-POD than PPTA because of the different structure. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42643.
Model-based machine learning

Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.
Antibacterial and Antidiarrheal Activities of Plant Products against Enterotoxinogenic Escherichia coli

Enterotoxigenic Escherichia coli (ETEC) produces two types of enterotoxins: heat-labile (LT) and heat-stable (STa and STb). These molecules are involved in the induction of secretory diarrhea in animals including humans. This condition is currently treated using a fluid replacement therapy and antibiotics. This treatment is often not available to people in developing countries, and several die from the condition provoke by ETEC. Over the years, plants and plant extracts have been use as traditional medicine to treat various gastrointestinal ailments including diarrhea. Many of these plant products have been claimed to be active against diarrhea, however few have been extensively studied. The main objective of this review was to gather the scattered information on the antidiarrheal activities reported for various plant products on ETEC. This includes two major effects: (1) The inhibitory effect on bacterial growth or viability and (2) The interference with ETEC enterotoxins activity upon the intestinal epithelium. We will focus on plant products and extracts for which we have major indications of their biological activity against ETEC and their enterotoxins. Because Vibrio cholerae toxin (CT) is structurally, antigenically and mechanistically related to LT, it will also be discussed in this review.
Morphology and viscoelasticity of PP/TiO2 nanocomposites prepared by in situ sol–gel method

PP/TiO2 nanocomposites were prepared from an original method based on the hydrolysis-condensation (sal-gel method) reactions of titanium alkoxide inorganic precursor premixed with polypropylene (PP) under molten conditions. Nanocomposites with a mean diameter of primary particles lower than 5 nm were then prepared. The TiO2 particle dispersion in the PP matrix was characterized over a wide length scale from the combination of small angle X-ray scattering, transmission electron microscopy, and linear viscoelasticty of molten nanocomposites. As a result, a fractal structure of these particles was highlighted at the highest concentration (phi(r) >= 0.014) with a characteristic aggregation size d(aggr) approximate to 130 nm. The relationships between fractal structure and linear viscoelastic have been discussed from the main works of the literature on the reinforcement of nanocomposites. The drastic alteration of the terminal relaxation zone (solid-like behavior) is correlated to the formation of an aggregate-particle network. The study of the nonlinear viscoelastic behavior (Payne effect) agrees qualitatively with this reinforcement mechanism. (C) 2010 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 48: 1213-1222, 2010
Dispersive estimates for the Schrödinger operator on step-2 stratified Lie groups

The present paper is dedicated to the proof of dispersive estimates on stratified Lie groups of step 2, for the linear Schrodinger equation involving a sublaplacian. It turns out that the propagator behaves like a wave operator on a space of the same dimension p as the center of the group, and like a Schrodinger operator on a space of the same dimension k as the radical of the canonical skew-symmetric form, which suggests a decay rate of exponant -(k+p-1)/2. In this article, we identify a property of the canonical skew-symmetric form under which we establish optimal dispersive estimates with this rate. The relevance of this property is discussed through several examples.
Genome-Wide Identification of Transcription Start Sites, Promoters and Transcription Factor Binding Sites in E. coli

Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5′ RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of σ factors that control the expression of about 80% of these genes. As expected, the housekeeping σ70 was the most common type of promoter, followed by σ38. The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli.
African elephants have expectations about the locations of out-of-sight family members

Monitoring the location of conspecifics may be important to social mammals. Here, we use an expectancy-violation paradigm to test the ability of African elephants (Loxodonta africana) to keep track of their social companions from olfactory cues. We presented elephants with samples of earth mixed with urine from female conspecifics that were either kin or unrelated to them, and either unexpected or highly predictable at that location. From behavioural measurements of the elephants' reactions, we show that African elephants can recognize up to 17 females and possibly up to 30 family members from cues present in the urine–earth mix, and that they keep track of the location of these individuals in relation to themselves.
A Quantitative Error Analysis of the Mobility Extraction According to the Matthiessen Rule in Advanced MOS Transistors

This paper presents a quantitative analysis of the errors produced by the Matthiessen rule in the extraction of the inversion-layer mobility in metal-oxide-semiconductor transistors. We show that the Matthiessen rule results in large inaccuracies in the mobility extraction, and most of all, it can lead to wrong trends, namely, to an incorrect dependence of the mobility on the temperature or the strain level. Consequently, when the Matthiessen rule is used to infer a given mobility component from the experiments, the inaccuracy of the extraction procedure can yield apparent discrepancies between experiments and simulations. Our results demonstrate that the mobility components extracted from the measurements by using the Matthiessen rule should not be regarded as experimental data because the extraction procedure relies on assumptions that are not fulfilled in most practical cases.
HLS-Based Methodology for Fast Iterative Development Applied to Elliptic Curve Arithmetic

High-Level Synthesis (HLS) is used by hardware developers to achieve higher abstraction in circuit descriptions. In order to shorten the hardware development time via HLS, we present an adjustment of the Iterative and Incremental Design (IID) methodology, frequently used in software development. In particular, our methodology is relevant for the development of applications with unusual complexity: the method was applied here to the development of large modular arithmetic, commonly used for cryptography applications (e.g., Elliptic Curves). Rapid feedback on circuit characteristics is used to evaluate deep architectural changes in short time, greatly reducing the time-to-market with respect to hand-made designs. In addition, our approach is highly flexible, since the same generic high-level description can be used to produce an entire set of circuits, each with different area/performance trade-offs. Thanks to the proposed approach, any change to the initial specification (e.g., the curve used) is also very fast, while it may require a large effort in the case of hand-made designs.
Intermittency in the velocity distribution of heavy particles in turbulence

The statistics of velocity differences between pairs of heavy inertial point particles suspended in an incompressible turbulent flow is studied and found to be extremely intermittent. The problem is particularly relevant to the estimation of the efficiency of collisions among heavy particles in turbulence. We found that when particles are separated by distances within the dissipative subrange, the competition between regions with quiet regular velocity distributions and regions where very close particles have very different velocities (caustics) leads to a quasi bi-fractal behaviour of the particle velocity structure functions. Contrastingly, we show that for particles separated by inertial-range distances, the velocity-difference statistics can be characterized in terms of a local roughness exponent, which is a function of the scale-dependent particle Stokes number only. Results are obtained from high-resolution direct numerical simulations up to 20483 collocation points and with millions of particles for each Stokes number.
Structural bioinformatics MMM : a sequence-to-structure alignment protocol

Motivation: Accurate alignment of a target sequence to a template structure continues to be a bottleneck in producing good quality comparative protein structure models. Results: Multiple Mapping Method (MMM) is a comparative protein structure modeling server with an emphasis on a novel alignment optimization protocol. MMM takes inputs from five profile-to-profile based alignment methods. The alternatively aligned regions from the input alignment set are combined according to their fit in the structural environment of the template structure. The resulting, optimally spliced MMMalignment isusedas input toanautomatedcomparativemodeling module to produce a full atom model. Availability: The MMM server is freely accessible at http://www. fiserlab.org/servers/mmm Contact: andras@fiserlab.org
Pax2/5/8 proteins promote cell survival in C. elegans

Programmed cell death, or apoptosis, plays an important role during normal development, and is disrupted in a range of disease states. Although the key molecular events that occur during apoptosis are well characterized, less is known about the regulatory inputs that influence whether a cell will live or die. Work in mouse and human cells has shown that Pax transcription factors can influence cell death and promote cell survival, but the mechanism for their activity is not clear. Here, we show that two Pax2/5/8-related genes (egl-38 and pax-2) influence both somatic and germline cell death in C. elegans. Using genetic and molecular experiments, we show that the Pax proteins act as transcriptional regulators of ced-9, the C. elegans bcl-2 gene. These results identify a mechanism for Pax2/5/8-mediated regulation of cell death, and underscore the importance of transcriptional regulation of core apoptotic pathway genes in influencing cell survival.
Multiple-kernel based soft subspace fuzzy clustering

Soft subspace fuzzy clustering algorithms have been successfully utilized for high dimensional data in recent studies. However, the existing works often utilize only one distance function to evaluate the similarity between data items along with each feature, which leads to performance degradation for some complex data sets. In this work, a novel soft subspace fuzzy clustering algorithm MKEWFC-K is proposed by extending the existing entropy weight soft subspace clustering algorithm with a multiple-kernel learning setting. By incorporating multiple-kernel learning strategy into the framework of soft subspace fuzzy clustering, MKEWFC-K can learning the distance function adaptively during the clustering process. Moreover, it is more immune to ineffective kernels and irrelevant features in soft subspace, which makes the choice of kernels less crucial. Experiments on real-world data demonstrate the effectiveness of the proposed MKEWFC-K algorithm.
Glia Protein Aquaporin‐4 Regulates Aversive Motivation of Spatial Memory in Morris Water Maze

Although extensive investigation has revealed that an astrocyte‐specific protein aquaporin‐4 (AQP4) participates in regulating synaptic plasticity and memory, a functional relationship between AQP4 and learning processing has not been clearly established. This study was designed to test our hypothesis that AQP4 modulates the aversive motivation in Morris water maze (MWM).