Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Group B Streptococcus and Blood-Brain Barrier Interaction by Using Induced Pluripotent Stem Cell-Derived Brain Endothelial Cells

Here for the first time, human iPSC-derived BMECs were used to model bacterial interaction with the BBB. Unlike models previously used to study these interactions, iPSC-derived BMECs possess robust BBB properties, such as the expression of complex tight junctions that are key components for the investigation of bacterial effects on the BBB. Here, we demonstrated that GBS interacts with the iPSC-derived BMECs and specifically disrupts these tight junctions. Thus, using this BBB model may allow researchers to uncover novel mechanisms of BBB disruption during meningitis that are inaccessible to immortalized or primary cell models that lack substantial tight junctions. ABSTRACT Bacterial meningitis is a serious infection of the central nervous system (CNS) that occurs after bacteria interact with and penetrate the blood-brain barrier (BBB). The BBB is comprised of highly specialized brain microvascular endothelial cells (BMECs) that function to separate the circulation from the CNS and act as a formidable barrier for toxins and pathogens. Certain bacteria, such as Streptococcus agalactiae (group B Streptococcus [GBS]), possess the ability to interact with and penetrate the BBB to cause meningitis. Modeling bacterial interaction with the BBB in vitro has been limited to primary and immortalized BMEC culture. While useful, these cells often do not retain BBB-like properties, and human primary cells have limited availability. Recently, a human induced pluripotent stem cell (iPSC)-derived BMEC model has been established that is readily renewable and retains key BBB phenotypes. Here, we sought to evaluate whether the iPSC-derived BMECs were appropriate for modeling bacterial interaction with the BBB. Using GBS as a model meningeal pathogen, we demonstrate that wild-type GBS adhered to, invaded, and activated the iPSC-derived BMECs, while GBS mutants known to have diminished BBB interaction were attenuated in the iPSC-derived model. Furthermore, bacterial infection resulted in the disruption of tight junction components ZO-1, occludin, and claudin-5. Thus, we show for the first time that the iPSC-derived BBB model can be utilized to study BBB interaction with a bacterial CNS pathogen. IMPORTANCE Here for the first time, human iPSC-derived BMECs were used to model bacterial interaction with the BBB. Unlike models previously used to study these interactions, iPSC-derived BMECs possess robust BBB properties, such as the expression of complex tight junctions that are key components for the investigation of bacterial effects on the BBB. Here, we demonstrated that GBS interacts with the iPSC-derived BMECs and specifically disrupts these tight junctions. Thus, using this BBB model may allow researchers to uncover novel mechanisms of BBB disruption during meningitis that are inaccessible to immortalized or primary cell models that lack substantial tight junctions.
Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications

We investigate two novel mixed robust/average-case submodular data partitioning problems that we collectively call Submodular Partitioning. These problems generalize purely robust instances of the problem, namely max-min submodular fair allocation (SFA) [12] and min-max submodular load balancing (SLB) [25], and also average-case instances, that is the submodular welfare problem (SWP) [26] and submodular multiway partition (SMP) [5]. While the robust versions have been studied in the theory community [11, 12, 16, 25, 26], existing work has focused on tight approximation guarantees, and the resultant algorithms are not generally scalable to large real-world applications. This is in contrast to the average case, where most of the algorithms are scalable. In the present paper, we bridge this gap, by proposing several new algorithms (including greedy, majorization-minimization, minorization-maximization, and relaxation algorithms) that not only scale to large datasets but that also achieve theoretical approximation guarantees comparable to the state-of-the-art. We moreover provide new scalable algorithms that apply to additive combinations of the robust and average-case objectives. We show that these problems have many applications in machine learning (ML), including data partitioning and load balancing for distributed ML, data clustering, and image segmentation. We empirically demonstrate the efficacy of our algorithms on real-world problems involving data partitioning for distributed optimization (of convex and deep neural network objectives), and also purely unsupervised image segmentation.
Modeling of low-frequency Stoneley-wave propagation in an irregular borehole

A fast modeling method is formulated for low-frequency Stoneley-wave propagation in an irregular borehole. This fast modeling method provides synthetic waveforms which include the effects of two borehole irregularities, diameter changes (washout), and formation property changes. The essential physics of the low-frequency Stoneley waves are captured with a simple 1-D model. A mass-balance boundary condition and a propagator matrix are used to express Stoneley-wave interactions with the borehole irregularities. The accuracy of the proposed method was confirmed through comparison with existing finite-difference and boundary integral modeling methods that yielded cross-correlations greater than 0.98. Comparison of synthetic records calculated for an actual borehole with field records showed qualitative agreement in the major reflections because of the washout zones, but showed some disagreements in the reflections caused by the fractures. Since the synthetic records include only information relating to the borehole geometry and the elastic properties of formation, the reflection caused by the fracture will appear only in the field record. These results suggest the possibility of distinguishing Stoneley-wave reflections caused by fractures from those caused by borehole irregularities. Further, the fast computational speed of this method--over 300 times faster than either boundary integral or finite-difference methods--makes it quite suitable for field application.
An efficient two step purification and molecular characterization of β‐galactosidases from Aspergillus oryzae

β‐Galactosidases (β‐D‐galactoside‐galactohydrolases (EC 3.2.1.23), lactases) are important industrial enzymes used for the hydrolysis of lactose from milk and milk whey. These enzymes are produced by different organisms and purified by multi‐step procedures. The multi‐step purification schemes are cost and time ineffective which can also lead to poor yield, denaturation and loss of enzymatic activity. In our study, extracellular β‐galactosidase from mutant strain Aspergillus oryzaeH26‐10‐7 was purified by a two step procedure, Metal‐ion Affinity Chromatography (IMAC) followed by size‐exclusion separation. Purified enzyme was characterized by sodium dodecyl Sulphate polyacrylamide gel electrophoresis (SDS‐PAGE) and zymographic analysis. This fungal β‐galactosidase was characterized as a protein corresponding to 113 kDa. Enzyme from mutant strain was found to have five times higher catalytic activity on the synthetic substrate o‐nitrophenyl‐β‐D‐galactopyranoside (ONPG) compared to the wild type enzyme. Moreover, the mutant enzyme was more thermo resistant compared to the wild type. This highly important technological characteristic can be exploited in food industry. Moreover, based on the IMAC patterns of wild type and mutant enzymes, similarities in their His topography were supposed. Copyright © 2006 John Wiley & Sons, Ltd.
Cell Culture-Selected Substitutions in Influenza A(H3N2) Neuraminidase Affect Drug Susceptibility Assessment

ABSTRACT Assessment of drug susceptibility has become an integral part of influenza virus surveillance. In this study, we describe the drug resistance profile of influenza A(H3N2) virus, A/Mississippi/05/2011, collected from a patient treated with oseltamivir and detected via surveillance. An MDCK cell-grown isolate of this virus exhibited highly reduced inhibition by the neuraminidase (NA) inhibitors (NAIs) oseltamivir (8,005-fold), zanamivir (813-fold), peramivir (116-fold), and laninamivir (257-fold) in the NA inhibition assay. Sequence analysis of its NA gene revealed a known oseltamivir-resistance marker, the glutamic acid-to-valine substitution at position 119 (E119V), and an additional change, threonine to isoleucine at position 148 (T148I). Unlike E119V, T148I was not detected in the clinical sample but acquired during viral propagation in MDCK cells. Using recombinant proteins, T148I by itself was shown to cause only a 6-fold increase in the zanamivir 50% inhibitory concentration (IC50) and had no effect on inhibition by other drugs. The T148I substitution reduced NA activity by 50%, most likely by affecting the positioning of the 150 loop at the NA catalytic site. Using pyrosequencing, changes at T148 were detected in 35 (23%) of 150 MDCK cell-grown A(H3N2) viruses tested, which was lower than the frequency of changes at D151 (85%), an NA residue previously implicated in cell selection. We demonstrate that culturing of the A(H3N2) viruses (n = 11) at a low multiplicity of infection delayed the emergence of the NA variants with changes at position 148 and/or 151, especially when conducted in MDCK-SIAT1 cells. Our findings highlight the current challenges in monitoring susceptibility of influenza A(H3N2) viruses to the NAI class of antiviral drugs.
Molecular phylogeny of the genus Amygdalus (Rosaceae) based on nrDNA ITS and cpDNA trnS-trnG sequences

With over 40 species, almonds (Amygdalus L.) are among the most economically important Rosaceae fruit crops distributed in the Irano-Turanian region of southwestern and Central Asia and southeastern Europe. While Amygdalus is considered a separate genus in floristic treatments of Asian countries it is a subgenus or a section of Prunus L. s.l. in other treatments. Phylogenetic relationships of the Iranian wild almonds based on data from 2 nuclear and chloroplast spacers (nrDNA ITS and cpDNA trnS-trnG) were constructed using the maximum parsimony and maximum likelihood, Bayesian inference, and NeighborNet methods. Data from 2 nuclear and chloroplast spacers were congruent. All of the Iranian almonds formed a well-established monophyletic clade, and the subgenus Cerasus was recovered as sister to Amygdalus. Amygdalus spinosissima Bge. was sister to all other Amygdalus species included in this study. Most of the Amygdalus species were grouped in a monophyletic clade that consisted of 2 subclades. The taxonomic status of 2 traditional subgenera of Amygdalus, Amygdalus and Dodecandra (Spach) Browicz, did not agree with the phylogenetic relationships revealed here. Among the studied species of Amygdalus, species of the section Spartioides Spach form a monophyletic clade (BV = 83%). Amygdalus mira Koehne, Amygdalus davidiana (Carriere) Franch. , Amygdalus triloba Ltdl. , and Amygdalus nana L. were recovered outside the main clade Amygdalus, indicating that these species should be excluded from Amygdalus. Similar to the previous phylogenetic studies in Prunus s.l. , phylogenetic analysis did not fully resolve relationships of the studied Amygdalus. NeighborNet analysis of the nrDNA ITS dataset of Iranian almonds supported reticulate relationships for all Amygdalus hybrids as previously reported.
Testing for Homogeneity in Meta‐Analysis I. The One‐Parameter Case: Standardized Mean Difference

Summary Meta‐analysis seeks to combine the results of several experiments in order to improve the accuracy of decisions. It is common to use a test for homogeneity to determine if the results of the several experiments are sufficiently similar to warrant their combination into an overall result. Cochran’s Q statistic is frequently used for this homogeneity test. It is often assumed that Q follows a chi‐square distribution under the null hypothesis of homogeneity, but it has long been known that this asymptotic distribution for Q is not accurate for moderate sample sizes. Here, we present an expansion for the mean of Q under the null hypothesis that is valid when the effect and the weight for each study depend on a single parameter, but for which neither normality nor independence of the effect and weight estimators is needed. This expansion represents an order O(1/n) correction to the usual chi‐square moment in the one‐parameter case. We apply the result to the homogeneity test for meta‐analyses in which the effects are measured by the standardized mean difference (Cohen’s d‐statistic). In this situation, we recommend approximating the null distribution of Q by a chi‐square distribution with fractional degrees of freedom that are estimated from the data using our expansion for the mean of Q. The resulting homogeneity test is substantially more accurate than the currently used test. We provide a program available at the Paper Information link at the Biometrics website http://www.biometrics. tibs.org for making the necessary calculations.
Analysis of heartbeat dynamics by point process adaptive filtering

Heartbeats are a point process yet, most of the current analysis methods do not model this important characteristic of these data. We describe human heartbeat time series as a history dependent inverse Gaussian model. We present a point process adaptive filter algorithm to estimate the model's time-varying parameters, and use it to compute new measures of heart rate variability. We apply our algorithm to analyze simulated heartbeat data and actual heartbeat data from a tilt table experiment and from healthy subjects and subjects with congestive heart failure during sleep. Our results suggest a new approach for characterizing heartbeat dynamics.
Photometric Stereo in a Scattering Medium

Photometric stereo is widely used for 3D reconstruction. However, its use in scattering media such as water, biological tissue and fog has been limited until now, because of forward scattered light from both the source and object, as well as light scattered back from the medium (backscatter). Here we make three contributions to address the key modes of light propagation, under the common single scattering assumption for dilute media. First, we show through extensive simulations that single-scattered light from a source can be approximated by a point light source with a single direction. This alleviates the need to handle light source blur explicitly. Next, we model the blur due to scattering of light from the object. We measure the object point-spread function and introduce a simple deconvolution method. Finally, we show how imaging fluorescence emission where available, eliminates the backscatter component and increases the signal-to-noise ratio. Experimental results in a water tank, with different concentrations of scattering media added, show that deconvolution produces higher-quality 3D reconstructions than previous techniques, and that when combined with fluorescence, can produce results similar to that in clear water even for highly turbid media.
Identification of Genes Influencing Skeletal Phenotypes in Congenic P/NP Rats

We previously showed that alcohol‐preferring (P) rats have higher bone density than alcohol‐nonpreferring (NP) rats. Genetic mapping in P and NP rats identified a major quantitative trait locus (QTL) between 4q22 and 4q34 for alcohol preference. At the same location, several QTLs linked to bone density and structure were detected in Fischer 344 (F344) and Lewis (LEW) rats, suggesting that bone mass and strength genes might cosegregate with genes that regulate alcohol preference. The aim of this study was to identify the genes segregating for skeletal phenotypes in congenic P and NP rats. Transfer of the NP chromosome 4 QTL into the P background (P.NP) significantly decreased areal bone mineral density (aBMD) and volumetric bone mineral density (vBMD) at several skeletal sites, whereas transfer of the P chromosome 4 QTL into the NP background (NP.P) significantly increased bone mineral content (BMC) and aBMD in the same skeletal sites. Microarray analysis from the femurs using Affymetrix Rat Genome arrays revealed 53 genes that were differentially expressed among the rat strains with a false discovery rate (FDR) of less than 10%. Nine candidate genes were found to be strongly correlated (r2 > 0.50) with bone mass at multiple skeletal sites. The top three candidate genes, neuropeptide Y (Npy), α synuclein (Snca), and sepiapterin reductase (Spr), were confirmed using real‐time quantitative PCR (qPCR). Ingenuity pathway analysis revealed relationships among the candidate genes related to bone metabolism involving β‐estradiol, interferon‐γ, and a voltage‐gated calcium channel. We identified several candidate genes, including some novel genes on chromosome 4 segregating for skeletal phenotypes in reciprocal congenic P and NP rats. © 2010 American Society for Bone and Mineral Research
Molecular modeling and simulation of polyamide membrane for forward osmosis process

As a first step in studying the molecular-level water transport and reverse solute diffusion mechanisms in forward osmosis (FO) process, this paper presents the molecular modeling and simulation of a polyamide (PA) membrane used in FO. In this study, a repeat unit of the starting monomers (m-phenylenediamine (MPD) and trimesoyl chloride (TMC)) was first modeled and then packed into chain, forming a linear PA chain. Geometry optimization and partial charge calculations of the linear PA chain were undergone using Density Functional Theory (DFT) calculations. A fully atomistic molecular dynamics (MD) simulation of the PA chains was performed to create a final representative model of PA membrane. The generated dehydrated and linear (un-crosslinked) PA membrane structure obtained a density value which is in close agreement with recent experimental and other simulation results. In addition, the calculated small-angle x-ray scattering intensities show that the obtained PA membrane structure is indeed amorphous. The amorphous structure of the membrane is believed to be due to the annealing scheme in the simulation which removed the lattice periodicity from the initial structure of the membrane.
Aerosol measurements with a combined elastic/non-elastic backscatter lidar in Beijing

In order to reach a green Olympics in 2008, an unprecedented environmental experiment jointly launched by the Beijing municipal government and the Chinese Academy of Sciences (CAS) was carried out. AIOFM (Anhui Institute of Optics and Fine Mechanics Experiment) took part in the campaign with an elastic/non-elastic lidar to measure the aerosol distribution and the boundary layer in summer in Beijing. With the combining solution of the Raman lidar and the elastic lidar equation, the important optical parameters of the aerosols (extinction coefficient, backscatter coefficients thus the lidar ratio) were attained. The lidar ratio on July 22 varied from 10sr to 30sr. Since the vertical distribution of the lidar ratio demonstrate different microphysical characteristics in the lower and upper parts of the cloud, so probably the cirrus with the mean lidar ratio of 25sr at the height of 6km can be assumed. On the other hand, a well-mixed boundary layer was observed. Taking into account the effects of the multiple scattering (5%-10%),we obtain a single-scattering optical depth of 0.15. The boundary layer also offered the explanation of the steady ozone concentration measured by the DOAS system at the same position of the observing site.
Spatio-temporal Video Parsing for Abnormality Detection

Abnormality detection in video poses particular challenges due to the infinite size of the class of all irregular objects and behaviors. Thus no (or by far not enough) abnormal training samples are available and we need to find abnormalities in test data without actually knowing what they are. Nevertheless, the prevailing concept of the field is to directly search for individual abnormal local patches or image regions independent of another. To address this problem, we propose a method for joint detection of abnormalities in videos by spatio-temporal video parsing. The goal of video parsing is to find a set of indispensable normal spatio-temporal object hypotheses that jointly explain all the foreground of a video, while, at the same time, being supported by normal training samples. Consequently, we avoid a direct detection of abnormalities and discover them indirectly as those hypotheses which are needed for covering the foreground without finding an explanation for themselves by normal samples. Abnormalities are localized by MAP inference in a graphical model and we solve it efficiently by formulating it as a convex optimization problem. We experimentally evaluate our approach on several challenging benchmark sets, improving over the state-of-the-art on all standard benchmarks both in terms of abnormality classification and localization.
Incentive-Driven and Privacy-Preserving Message Dissemination in Large-Scale Mobile Networks

In this paper, we propose a new type of incentive-driven and privacy-preserving systems for large-scale message dissemination in mobile networks. To distribute incentives which encourage forwarding behaviors, such as monetary rewards, we want to keep track of the forwarder list. In our algorithms, we rely on a Probabilistic one-ownership forwarding algorithm to record the list, so that the exchanged messages can be kept short and privacy preserving. More specifically, only one hop of forwarder information, instead of the complete list, is recorded, and the information is updated probabilistically following two ownership flipping models, namely, One-Flip and Always-Flip models. We also use a Bluetooth Service Discovery Protocol (SDP) toolkit to enable fast, configuration-free message exchange. Throughout the paper, we use coupon as a typical type of message to illustrate the core ideas. We have implemented the coupon dissemination system in Java ME. Our experiments on real-world mobile phones, such as Nokia and Samsung phones, and large-scale simulations show that our system is efficient in peer-to-peer message distribution and capable of massive deployment. We believe our key methodology can serve as a general framework for facilitating information propagation on mobile phones, where incentives and privacy protection are both essential.