Miracle-dz/UniFAR-FTUs huggingface dataset:
High level production of functional antibody Fab fragments in an oxidizing bacterial cytoplasm.

The antigen-binding fragments (Fab) of antibodies are powerful tools in clinical therapy, molecular diagnostics and basic research. However, their principal applications require pure recombinant molecules in large amounts, which are challenging to obtain. Severe limitations in yield, folding and functionality are commonly encountered in bacterial production of Fab fragments. Secretion into the oxidizing periplasm generally results in low yield, whereas expression in the reducing cytoplasmic environment produces unfolded or non-functional protein. We hypothesized that an impaired reducing environment of the cytoplasm would permit correctly folded, functional cytoplasmic expression of Fabs with high yield. We used the Escherichia coli strain FA113, which has no activity of both thioredoxin and glutathione reductase, and thus has an oxidizing cytoplasmic environment. With the newly constructed vector pFAB1 we tested the cytoplasmic expression of two Fab fragments, which recognize the integral membrane protein NhaA, a bacterial Na(+)/H(+) antiporter. These antibodies differ in terms of DNA sequence and stability. Both antibody fragments were produced to very high yields (10-30 mg/l from bacterial cultures at an A(600 nm)=1.2-1.3). This is a factor 50-250 times higher than any other reported over-expression strategy for Fab fragments and currently represents the highest production rate ever been reported for antibody Fab fragments in bacteria grown to similar cell densities. The fragments are fully functional and can be efficiently purified by His-tag chromatography. Expression of active Fab fragments in the bacterial cytoplasm unlocks the possibility of using antibody specific targeting in an intracellular environment. Such a capacity opens new perspectives for investigating metabolic and regulatory pathways in vivo and also provides a powerful selection system for functional genomics.
Differential Diagnosis of Taenia saginata and Taenia solium Infection by PCR

ABSTRACT We have designed species-specific oligonucleotides which permit the differential detection of two species of cestodes, Taenia saginata and Taenia solium. The oligonucleotides contain sequences established for two previously reported, noncoding DNA fragments cloned from a genomic library of T. saginata. The first, which is T. saginata specific (fragment HDP1), is a repetitive sequence with a 53-bp monomeric unit repeated 24 times in direct tandem along the 1,272-bp fragment. From this sequence the two oligonucleotides that were selected (oligonucleotides PTs4F1 and PTs4R1) specifically amplified genomic DNA (gDNA) from T. saginata but not T. solium or other related cestodes and had a sensitivity down to 10 pg of T. saginata gDNA. The second DNA fragment (fragment HDP2; 3,954 bp) hybridized to bothT. saginata and T. solium DNAs and was not a repetitive sequence. Three oligonucleotides (oligonucleotides PTs7S35F1, PTs7S35F2, and PTs7S35R1) designed from the sequence of HDP2 allowed the differential amplification of gDNAs from T. saginata, T. solium, and Echinococcus granulosus in a multiplex PCR, which exhibits a sensitivity of 10 pg.
Response Selection During a Joint Action Task

ABSTRACT It has been suggested that a shared task representation is used to predict a coactors’ needs and that these predictions influence each coactor's response selection in a joint action task. The authors tested this idea using a joint action task in which participants passed a jug to a confederate under different conditions. They hypothesized that if participants predicted the needs of their coactor and planned their movement according to these predictions, the jug would be passed with the handle available to the confederate. Consistent with this hypothesis, the jug was passed with the handle available on 86% of the trials. This strategy may be adopted to improve the efficiency of the whole task as opposed to each individual's portion of the task.
An Efficient and Scalable Algorithmic Method for Generating Large-Scale Random Graphs

Many real-world systems and networks are modeled and analyzed using various random graph models. These models must incorporate relevant properties such as degree distribution and clustering coefficient. Many models, such as the Chung-Lu (CL), stochastic Kronecker, stochastic block model (SBM), and block two-level Erdős-Rényi (BTER) models have been devised to capture those properties. However, the generative algorithms for these models are mostly sequential and take prohibitively long time to generate large-scale graphs. In this paper, we present a novel time and space efficient algorithmic method to generate random graphs using CL, BTER, and SBM models. First, we present an efficient sequential algorithm and an efficient distributed-memory parallel algorithm for the CL model. Our sequential algorithm takes O(m) time and O(Λ) space, where m and Λ are the number of edges and distinct degrees, and our parallel algorithm takes O (m/p + Λ + P) time w.h. p. and O(Λ) space using P processors. These algorithms are almost time optimal since any sequential and parallel algorithms need at least Ω(m) and Ω(m/p) time, respectively. Our algorithms outperform the best known previous algorithms by a significant margin in terms of both time and space. Experimental results on various large-scale networks show that both of our sequential and parallel algorithms require 400–15000 times less memory than the existing sequential and parallel algorithms, respectively, making our algorithms suitable for generating very large-scale networks. Moreover, both of our algorithms are about 3–4 times faster than the existing sequential and parallel algorithms. Finally, we show how our algorithmic method also leads to efficient parallel and sequential algorithms for the SBM and BTER models.
Pulsed ultrafiltration mass spectrometry: a new method for screening combinatorial libraries.

In response to the need for rapid screening of combinatorial libraries to identify new lead compounds during drug discovery, we have developed an on-line combination of ultrafiltration and electrospray mass spectrometry, called pulsed ultrafiltration mass spectrometry, which facilitates the identification of solution-phase ligands in library mixtures that bind to solution-phase receptors. After ligands contained in a library mixture were bound to a macromolecular receptor, e.g., human serum albumin or calf intestine adenosine deaminase, the ligand-receptor complexes were purified by ultrafiltration and then dissociated using methanol to elute the ligands into the electrospray mass spectrometer for detection. Ligands with dissociation constants in the micromolar to nanomolar range were successfully bound, released, and detected using this method, including warfarin, salicylate, furosemide, and thyroxine binding to human serum albumin, and erythro-9-(2-hydroxy-3-nonyl)adenine binding to calf intestine adenosine deaminase. Repetitive bind- and-release experiments demonstrated that the receptor could be reused. Thus, pulsed ultrafiltration mass spectrometry was shown to provide a simple and powerful new method for the screening of combinatorial libraries in support of new drug discovery.
VolleyBot: A competative framework for AI and UAV research and development

This paper proposes a new setup for AI and UAV research and development, using the volleyball competition as a framework called VolleyBot. Similar to the way RoboCup is used for ground mobile robotic competition, VolleyBot offers a competitive setup for teams of small and medium sized unmanned aerial vehicles (UAVs), in particular quadrotors. In VolleyBot, two teams, separated by a net, are trying to score points by grounding a ball in the opposing team's court. Each player consists of a UAV that is equipped with a racket or a bat to handle the ball. Each UAV team member must be capable of intercepting the ball and operate at a high level of coordination and collaboration with other team members. VolleyBot offers a common task for evaluating theories, algorithms, designs, and implementations of multi-UAV systems. The VolleyBot setup is a dynamic challenging competitive environment that advances UAV researchers and users.
Circulating current calculation using fault modeling of IPM type BLDC motor of inter-turn fault

This paper proposes a finite element method (FEM)-based model of an interior permanent magnet (IPM) type BLDC motor having stator inter-turn faults. For more realistic simulation studies, the magnetic non-linearity is also considered in proposed model. And the simulation data are verified through experiment. By integrating the developed model with a current-controlled voltage source inverter (CCVSI) model, the characteristics of an inter-turn fault operated by six-switched inverter are investigated considering the speed control. And the circulating current, which is induced by magnetic linkage flux originated from PM, was analyzed from the view point of distortion of air-gap magnetic flux distribution caused deterioration of their torque.
Tau pathology and neurodegeneration contribute to cognitive impairment in Alzheimer’s disease

Neuropathological and in vivo studies have revealed a tight relationship between tau pathology and cognitive impairment across the Alzheimer's disease spectrum. However, tau pathology is also intimately associated with neurodegeneration and amyloid pathology. The aim of the present study was therefore to assess whether grey matter atrophy and amyloid pathology contribute to the relationship between tau pathology, as measured with 18F-AV-1451-PET imaging, and cognitive deficits in Alzheimer's disease. We included 40 amyloid-positive patients meeting criteria for mild cognitive impairment due to Alzheimer's disease (n = 5) or probable Alzheimer's disease dementia (n = 35). Twelve patients additionally fulfilled the diagnostic criteria for posterior cortical atrophy and eight for logopenic variant primary progressive aphasia. All participants underwent 3 T magnetic resonance imaging, amyloid (11C-PiB) positron emission tomography and tau (18F-AV-1451) positron emission tomography, and episodic and semantic memory, language, executive and visuospatial functions assessment. Raw cognitive scores were converted to age-adjusted Z-scores (W-scores) and averaged to compute composite scores for each cognitive domain. Independent regressions were performed between 18F-AV-1451 binding and each cognitive domain, and we used the Biological Parametric Mapping toolbox to further control for local grey matter volumes, 11C-PiB uptake, or both. Partial correlations and causal mediation analyses (mediation R package) were then performed in brain regions showing an association between cognition and both 18F-AV-1451 uptake and grey matter volume. Our results showed that decreased cognitive performance in each domain was related to increased 18F-AV-1451 binding in specific brain regions conforming to established brain-behaviour relationships (i.e. episodic memory: medial temporal lobe and angular gyrus; semantic memory: left anterior temporal regions; language: left posterior superior temporal lobe and supramarginal gyrus; executive functions: bilateral frontoparietal regions; visuospatial functions: right more than left occipitotemporal regions). This pattern of regional associations remained essentially unchanged-although less spatially extended-when grey matter volume or 11C-PiB uptake maps were added as covariates. Mediation analyses revealed both direct and grey matter-mediated effects of 18F-AV-1451 uptake on cognitive performance. Together, these results show that tau pathology is related in a region-specific manner to cognitive impairment in Alzheimer's disease. These regional relationships are weakly related to amyloid burden, but are in part mediated by grey matter volumes. This suggests that tau pathology may lead to cognitive deficits through a variety of mechanisms, including, but not restricted to, grey matter loss. These results might have implications for future therapeutic trials targeting tau pathology.
One‐Dimensional SDS Gel Electrophoresis of Proteins

One‐dimensional gel electrophoresis of proteins provides information about the molecular size, amount, and purity of a protein sample. Separated proteins can be recovered from polyacrylamide gels for subsequent characterization by a variety of secondary techniques, such as mass spectrometry to determine post‐translational modifications and the amino acid sequence. In addition, one‐dimensional electrophoresis is the standard first step in immunoblotting and immunodetection. Protein separations in vertical slab gels are performed in a variety of formats. Most recently, small format minigels are typical due to their ease of use, low relative cost, and ready commercial availability. Larger gels provide more separation area and thus better resolution for complex samples and continue to be in use for specialized analysis. Curr. Protoc. Mol. Biol. 97:10.2A. 1‐10.2A. 44. © 2012 by John Wiley & Sons, Inc.
Promising evidence and remaining issues regarding the clinical application of oxytocin in autism spectrum disorders

Oxytocin is a potential therapeutic for the core symptoms of autism spectrum disorder (ASD), which is currently untreatable with pharmacotherapy. Previous clinical trials of a single dose of oxytocin have consistently reported significantly positive effects on various experimental measures associated with the core symptoms of ASD. These studies used various experimental measures as surrogate endpoints of the trials. However, to date, randomized clinical trials of continual administration of oxytocin have failed to reveal significant positive effects on clinically meaningful endpoints, such as how those with ASD interact during interpersonal interactions. This article reviews both the negative and positive effects of oxytocin on the core symptoms of ASD and their surrogate markers. Some unresolved and critical issues on the development of oxytocin as a new therapeutic have been extracted: optimization of dose, duration of oxytocin treatment, and the development of objective and reliable measurements of clinically meaningful endpoints for the core symptoms of ASD. Furthermore, optimization to the intranasal delivery system and careful consideration of how individuals respond differently to treatments should be addressed in future studies.
Precision evaluation for thermal fatigue life of power module using coupled electrical-thermal-mechanical analysis

For power module, the reliability evaluation of thermal fatigue life by power cycling has been prioritized as an important concern. Since in power cycling produces there exists non-uniform temperature distribution in the power module, coupled thermal-structure analysis is required to evaluate thermal fatigue mechanism. The thermal expansion difference between a Si chip and a substrate causes thermal fatigue. In this study, thermal fatigue life of solder joints on power module was evaluated. The finite element method (FEM) was used to evaluate temperature distribution induced by joule heating. Higher temperature appears below the Al wire because the electric current flows through the bonding Al wire. Coupled thermal-structure analysis is also required to evaluate the inelastic strain distribution. The damage of each part of solder joint can be calculated from equivalent inelastic strain range and crack propagation was simulated by deleting damaged elements step by step. The initial cracks were caused below the bonding Al wire and propagated concentrically under power cycling. There is the difference from environmental thermal cycling where the crack initiated at the edge of solder layer. In addition, in order to accurately evaluate the thermal fatigue life, the factors affecting the thermal fatigue life of solder joint where verified using coupled electrical-thermal-structural analysis. Then, the relation between the thermal fatigue life of solder joint and each factor is clarified. The precision evaluation for the thermal fatigue life of power module is improved.
The Impact of Emotion Regulation and Illness-focused Coping Strategies on the Relation of Illness-related Negative Emotions to Subjective Health

In this study we examined whether emotion regulation and illness-focused coping strategies mediate and/ or moderate the relation of illness-related negative emotions to patients’ subjective health. One hundred and thirty-five cardiac patients participated in the study. Illness-focused coping strategies were found to mediate the relation of emotions to physical functioning, whereas emotion regulation strategies mediated the relation to psychological well-being. Moreover, an emotion regulation strategy (i.e. emotion suppression) and two illness-focused coping strategies (instrumental coping and adherence) moderated the two relationships. These findings suggest that both emotion regulation and illness-focused coping strategies are integral parts of the illness-related negative emotions—health relationship.
Sequential change detection using estimators of entropy & divergence rate

We study the sequential change detection problem, with incomplete knowledge of source statistics, through the use of universal estimators of entropy and divergence rate. A novel technique, to reduce the time complexity of JB-Page change detection test(Jacob-Bansal(2008)), is described and a lemma justifying the method is proved. Inspired by the Page(1954) test, we propose a test, to detect a change from a stationary Markov ψ-mixing process to a stationary ergodic process. Statistics of both the sources are unknown except for a training sequence for the source before change. The test uses a universal estimator of the divergence rate between a stationary ergodic process and a stationary Markov ψ-mixing process, which we propose and prove to be almost-surely convergent. It is based on the Fixed-Database-Lempel-Ziv(FDLZ) cross-parsing technique. The proof of convergence of our estimator of divergence rate uses the almost-sure convergence of a match-length like quantity between a stationary ergodic process and a stationary Markov ψ-mixing process which we establish here.
Effects of acute alcohol withdrawal on memory performance in alcohol‐dependent patients: a pilot study

Studies on the neuropsychological performance in detoxified alcoholic patients often begin by acknowledging that there is a cognitive impairment to be found. Only little attention has been paid to date to the question as to how acute alcohol withdrawal might affect cognitive functions. Twenty‐nine alcohol‐dependent inpatients, nine in moderate alcohol withdrawal, treated with carbamazepine (group 1), 10 in mild alcohol withdrawal without pharmacological treatment (group 2), 10 in mild alcohol withdrawal with carbamazepine treatment (group 3) and 31 healthy subjects as controls (group 4) underwent repeated investigations using memory tests. The tests were performed on the first, third, seventh and fourteenth days of withdrawal. Immediate free recall of a word‐list was impaired in the three patient groups in comparison with the control group on the 1st day. Thereafter no significant differences could be revealed between patients and controls. In a word‐list recognition test the memory functions were not impaired in group 1 and group 2 in comparison with the control subjects. However, patients in group 3 showed impairment in this recognition test in comparison with the healthy subjects on the first and third days. The present study suggests that acute alcohol withdrawal impairs memory functions, especially free recall. This should be considered in treatment interventions in the early days of withdrawal.
Medullary thyroid carcinoma cell lines contain a self-renewing CD133+ population that is dependent on ret proto-oncogene activity.

CONTEXT Medullary thyroid carcinoma (MTC) is a cancer of the parafollicular C cells commonly caused by an inherited or acquired RET proto-oncogene mutation. Therapeutic resistance and recurrence of the disease imply the presence of cancer stem cells in MTC. OBJECTIVE In this study, we sought to identify and characterize cancer stem cell-like cells in MTC. MAIN OUTCOME MEASURES The characterization of stem cell properties was performed using immunostaining, flow cytometry, sphere formation assay, rederivation assay, Western blotting, and quantitative RT-PCR of defined markers of neural stem and progenitor cells. The role of ret proto-oncogene activation was assessed through RNA interference knockdown. RESULTS CD133 positivity was identified by immunostaining patient MTC. Flow cytometry confirmed a subpopulation of CD133(+) cells in two MTC cell lines. The CD133(+) cells could be expanded by sphere formation assay, passaged multiple times, and expressed neural progenitor markers beta-tubulin 3 and glial fibrillary acidic protein. The MZ-CRC-1 cell line, which harbors a M918T RET mutation, had greater CD133(+) cell numbers and sphere-forming ability than the TT cell line, which harbors the less active C634W mutation. Sphere formation was more dependent on ret proto-oncogene activity than epidermal growth factor or fibroblast growth factor. CONCLUSION Our data support the existence of cancer stem-like cells in MTC, which exhibit the features of self-renewal and of multiple lineage differentiation that is dependent on ret proto-oncogene receptor activity. These findings may provide new insights to develop more promising therapy for MTC.
Mergers and Acquisitions and Productivity in the U.S. Meat Products Industries: Evidence from the Micro Data

This article investigates the motives for mergers and acquisitions (M&As) in the U.S. meat products industry from 1977 to 1992. Results show that acquired meat and poultry plants were very productive before mergers, and that all but the very largest meat slaughter and processing plants and all but the bottom 20% of the poultry slaughter and processing plants significantly improved their productivity growth in their postmerger periods. These results lead to the conclusion that synergies and related efficiencies are important motives for M&As.
Design of high brightness symmetric and asymmetric emittance RF photoinjectors for TESLA

Development work leading to emittance‐compensated symmetric emittance and asymmetric emittance RF photoinjectors is discussed. A mature design for a symmetric emittance photoinjector is described, and current work leading to an asymmetric design is detailed. An experimental program to characterize both injectors and to explore the physical mechanism of emittance compensation using the facilities of the Argonne Wakefield Accelerator is outlined.
Attitudes and opinions.

Now, we come to offer you the right catalogues of book to open. attitudes and opinions is one of the literary work in this world in suitable to be reading material. That's not only this book gives reference, but also it will show you the amazing benefits of reading a book. Developing your countless minds is needed; moreover you are kind of people with great curiosity. So, the book is very appropriate for you.
Comparison of artificial intelligence techniques for the enhancement of power quality

Artificial Intelligence techniques are the recent trends used for the enhancement of power quality. This paper deals with analysis and comparison of different artificial techniques for harmonic reduction in the source current. Artificial Intelligence may include Fuzzy logic and Artificial Neural Network. The purpose of the simulation is to enhance the power quality by using the concepts that cannot be expressed as "true" or "false" but rather as "partially true" called as Fuzzy logic and intelligent features of the neuron cell. Shunt Active Filter is one of the controller that can be used for suppress the source current harmonics and compensates the reactive power. Hysteresis current controller is used to control the switching of Voltage Source Inverter. The D-Q Frame theory is used to generate the reference compensating current. Simulations are carried out in MATLAB environment using power system toolbox.