Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell surface beta 1,4-galactosyltransferase functions during neural crest cell migration and neurulation in vivo

Mesenchymal cell migration and neurite outgrowth are mediated in part by binding of cell surface beta 1,4-galactosyltransferase (GalTase) to N-linked oligosaccharides within the E8 domain of laminin. In this study, we determined whether cell surface GalTase functions during neural crest cell migration and neural development in vivo using antibodies raised against affinity-purified chicken serum GalTase. The antibodies specifically recognized two embryonic proteins of 77 and 67 kD, both of which express GalTase activity. The antibodies also immunoprecipitated and inhibited chick embryo GalTase activity, and inhibited neural crest cell migration on laminin matrices in vitro. Anti-GalTase antibodies were microinjected into the head mesenchyme of stage 7-9 chick embryos or cranial to Henson's node of stage 6 embryos. Anti-avian GalTase IgG decreased cranial neural crest cell migration on the injected side but did not cross the embryonic midline and did not affect neural crest cell migration on the uninjected side. Anti-avian GalTase Fab crossed the embryonic midline and perturbed cranial neural crest cell migration throughout the head. Neural fold elevation and neural tube closure were also disrupted by Fab fragments. Cell surface GalTase was localized to migrating neural crest cells and to the basal surfaces of neural epithelia by indirect immunofluorescence, whereas GalTase was undetectable on neural crest cells prior to migration. These results suggest that, during early embryogenesis, cell surface GalTase participates during neural crest cell migration, perhaps by interacting with laminin, a major component of the basal lamina. Cell surface GalTase also appears to play a role in neural tube formation, possibly by mediating neural epithelial adhesion to the underlying basal lamina.
Globular and asymmetric acetylcholinesterase in the synaptic basal lamina of skeletal muscle

The aim of this study was to characterize the molecular forms of acetylcholinesterase (AChE) associated with the synaptic basal lamina at the neuromuscular junction. The observations were made on the neuromuscular junctions of cutaneous pectoris muscles of frog, Rana pipiens, which are similar to junctions of most other vertebrates including mammals, but are especially convenient for experimentation. By measuring relative AChE activity in junctional and extrajunctional regions of muscles after selective inactivation of extracellular AChE with echothiophate, or of intracellular AChE with DFP and 2-PAM, we found that > 66% of the total AChE activity in the muscle was junction- specific, and that > 50% of the junction-specific AChE was on the cell surface. More than 80% of the cell surface AChE was solubilized in high ionic strength detergent-free buffer, indicating that most, if not all, was a component of the synaptic basal lamina. Sedimentation analysis of that fraction indicated that while asymmetric forms (A12, A8) were abundant, globular forms sedimenting at 4-6 S (G1 and G2), composed > 50% of the AChE. It was also found that when muscles were damaged in various ways that caused degeneration of axons and muscle fibers but left intact the basal lamina sheaths, the small globular forms persisted at the synaptic site for weeks after phagocytosis of cellular components; under certain damage conditions, the proportion of globular to asymmetric forms in the vacated basal lamina sheaths was as in normal junctions. While the asymmetric forms required high ionic strength for solubilization, the extracellular globular AChE could be extracted from the junctional regions of normal and damaged muscles by isotonic buffer. Some of the globular AChE appeared to be amphiphilic when examined in detergents, suggesting that it may form hydrophobic interactions, but most was non-amphiphilic consistent with the possibility that it forms weak electrostatic interactions. We conclude that the major form of AChE in frog synaptic basal lamina is globular and that its mode of association with the basal lamina differs from that of the asymmetric forms.
Improving Vision-Based Motor Rehabilitation Interactive Systems for Users with Disabilities Using Mirror Feedback

Observation is recommended in motor rehabilitation. For this reason, the aim of this study was to experimentally test the feasibility and benefit of including mirror feedback in vision-based rehabilitation systems: we projected the user on the screen. We conducted a user study by using a previously evaluated system that improved the balance and postural control of adults with cerebral palsy. We used a within-subjects design with the two defined feedback conditions (mirror and no-mirror) with two different groups of users (8 with disabilities and 32 without disabilities) using usability measures (time-to-start (T s) and time-to-complete (T c)). A two-tailed paired samples t-test confirmed that in case of disabilities the mirror feedback facilitated the interaction in vision-based systems for rehabilitation. The measured times were significantly worse in the absence of the user's own visual feedback (T s = 7.09 (P < 0.001) and T c = 4.48 (P < 0.005)). In vision-based interaction systems, the input device is the user's own body; therefore, it makes sense that feedback should be related to the body of the user. In case of disabilities the mirror feedback mechanisms facilitated the interaction in vision-based systems for rehabilitation. Results recommends developers and researchers use this improvement in vision-based motor rehabilitation interactive systems.
Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms

MOTIVATION Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes. This approach, which better reflects the functional constraints on the evolution of organisms, can exploit the large amount of data generated by genome-wide expression analyses. However, it requires new methodologies to represent the data in a more accessible way for cross-species comparisons. RESULTS In this work, we present an approach based on Multi-dimensional Scaling techniques, to compare the conformation of two gene expression networks, represented in a multi-dimensional space. The expression networks are optimally superimposed, taking into account two criteria: (1) inter-organism orthologous gene pairs have to be nearby points in the final multi-dimensional space and (2) the distortion of the gene expression networks, the organization of which reflects the similarities between the gene expression measurements, has to be circumscribed. Using this approach, we compared the transcriptional programs that drive sporulation in budding and fission yeasts, extracting some common properties and differences between the two species.
Pancreatic-Cell-specific Ablation of the Multiple Endocrine Neoplasia Type 1 ( MEN 1 ) Gene Causes Full Penetrance of Insulinoma Development in Mice 1

The function of the predisposition gene to multiple endocrine neoplasia type 1 (MEN1) syndrome remains largely unknown. Previous studies demonstrated that null mutation of the Men1 gene caused mid-gestation lethality in mice, whereas heterozygous Men1 knockout mice developed multiple endocrine tumors late in life. To seek direct evidence on the causal role of menin in suppressing tumor development, we generated mice in which the Men1 gene was disrupted specifically in pancreatic cells. These mice began to develop hyperplastic islets at as early as 2 months of age and insulinomas at 6 months of age. The islet lesions exhibited features of multistage tumor progression, including -cell dedifferentiation, angiogenesis, and altered expression of both E-cadherin and -catenin. Additionally, disturbance of blood insulin and glucose levels correlated with tumor development, mimicking human MEN1 symptoms. Our data indicate that this strain of mice provides a powerful tool for the study of the mechanisms of tumorigenesis related to MEN1 disease.
A Generic QoS Framework for Cloud Workflow Systems

Due to the dynamic nature of cloud computing, how to achieve satisfactory QoS (Quality of Service) in cloud workflow systems becomes a challenge. Meanwhile, since QoS requirements have many dimensions, a unified system design for different QoS management components is required to reduce the system complexity and software development cost. Therefore, this paper proposes a generic QoS framework for cloud workflow systems. Covering the major stages of a workflow lifecycle, the framework consists of four components, viz. QoS requirement specification, QoS-aware service selection, QoS consistency monitoring and QoS violation handling. While there are many QoS dimensions, this paper illustrates a concrete performance framework as a case study and briefly touches others. We also demonstrate the system implementation and evaluate the effectiveness of the performance framework in our cloud workflow system.
Neural systems of positive affect: Relevance to understanding child and adolescent depression?

From an affective neuroscience perspective, the goal of achieving a deeper, more mechanistic understanding of the development of depression will require rigorous models that address the core underlying affective changes. Such an understanding will necessitate developing and testing hypotheses focusing on specific components of the complex neural systems involved in the regulation of emotion and motivation. In this paper, we illustrate these principles by describing one example of this type of approach: examining the role of disruptions in neural systems of positive affect in major depressive disorder in school-age children and adolescents. We begin by defining positive affect, proposing that positive affect can be distinguished from negative affect by its neurobehavioral features. We provide an overview of neural systems related to reward and positive affect, with a discussion of their potential involvement in depression. We describe a developmental psychopathology framework, addressing developmental issues that could play a role in the etiology and maintenance of early-onset depression. We review the literature on altered positive affect in depression, suggesting directions for future research. Finally, we discuss the treatment implications of this framework.This research was supported by a Klingenstein Third Generation Foundation Postdoctoral Fellowship, NIMH Training Grant T32 MH018269, and NIMH Research Network R24 MH67346. We thank David J. Kupfer for his compelling suggestions about clinical course and development across the life span, and we thank Anna Lotze for help with references.
A new scalable aggregation scheme for fuzzy clustering Taking unstructured textual resources as a case

The performance of clustering is a crucial challenge, especially for pattern recognition. The models aggregation has a positive impact on the efficiency of Data clustering. This technique is used to obtain more cluttered decision boundaries by aggregating the resulting clustering models. In this paper, we study an aggregation scheme to improve the stability and accuracy of clustering, which allows to find a reliable and robust clustering model. We demonstrate the advantages of our aggregation method by running Fuzzy C-Means (FCM) clustering on Reuters-21578 corpus. Experimental studies showed that our scheme optimized the bias-variance on the selected model and achieved enhanced clustering for unstructured textual resources.
D‐dimer threshold increase with pretest probability unlikely for pulmonary embolism to decrease unnecessary computerized tomographic pulmonary angiography

Summary. Background: Increasing the threshold to define a positive D‐dimer could reduce unnecessary computed tomographic pulmonary angiography (CTPA) for a suspected pulmonary embolism (PE) but might increase rates of a missed PE and missed pneumonia, the most common non‐thromboembolic diagnosis seen on CTPA.
A Demonstration of Iterative Parallel Array Processing in Support of Telescope Image Analysis

In this demonstration, we present AscotDB, a new tool for the analysis of telescope image data. AscotDB results from the integration of ASCOT, a Web-based tool for the collaborative analysis of telescope images and their metadata, and SciDB, a parallel array processing engine. We demonstrate the novel data exploration supported by this integrated tool on a 1 TB dataset comprising scientifically accurate, simulated telescope images. We also demonstrate novel iterative-processing features that we added to SciDB in order to support this use-case.
nZDC: A compiler technique for near Zero Silent Data Corruption

Exponentially growing rate of soft errors makes reliability a major concern in modern processor design. Since software-oriented approaches offer flexible protection even in off-the-shelf processes, they are attractive solutions in protecting against soft errors. Among such approaches, in-application instruction duplication based approaches have been widely used and are deemed to be the most effective. Such techniques duplicate the program assembly instructions and periodically check the results to identify possible errors. Even though early reports suggest that these achieve close to 100% protection from soft errors, we find several gaps in the protection. Existing techniques are unable to protect several important microarchitectural components, as well as a significant fraction of instructions, resulting in Silent Data Corruptions (SDCs). This paper presents nZDC or near Zero silent Data Corruption - an effective instruction duplication based approach to protect programs from soft errors. Extensive fault injection experiments on almost all the unprotected microarchitectural components in simulated ARM Cortex A53, while executing benchmarks from MiBench suite, demonstrate that nZDC is extremely effective, without incurring any more performance penalty than the state-of-the-art.
Bioaerosols from a Food Waste Composting Plant Affect Human Airway Epithelial Cell Remodeling Genes

The composting procedure in food waste plants generates airborne bioaerosols that have the potential to damage human airway epithelial cells. Persistent inflammation and repair responses induce airway remodeling and damage to the respiratory system. This study elucidated the expression changes of airway remodeling genes in human lung mucoepidermoid NCI-H292 cells exposed to bioaerosols from a composting plant. Different types of microorganisms were detectable in the composting plant, using the agar culture method. Real-time polymerase chain reaction was used to quantify the level of Aspergillus fumigatus and the profile of remodeling genes. The real-time PCR results indicated that the amount of A. fumigatus in the composting hall was less than 102 conidia. The endotoxins in the field bioaerosols were determined using a limulus amebocyte lysate test. The endotoxin levels depended on the type of particulate matter (PM), with coarse particles (2.5–10 μm) having higher endotoxin levels than did fine particles (0.5–2.5 μm). After exposure to the conditioned medium of field bioaerosol samples, NCI-H292 cells showed increased pro-inflammatory interleukin (IL)-6 release and activated epidermal growth factor receptor (EGFR), transforming growth factor (TGF)-β1 and cyclin-dependent kinase inhibitor 1 (p21WAF1/CIP1) gene expression, but not of matrix metallopeptidase (MMP)-9. Airborne endotoxin levels were higher inside the composting hall than they were in other areas, and they were associated with PM. This suggested that airborne bioaerosols in the composting plant contained endotoxins and microorganisms besides A. fumigatus that cause the inflammatory cytokine secretion and augment the expression of remodeling genes in NCI-H292 cells. It is thus necessary to monitor potentially hazardous materials from bioaerosols in food composting plants, which could affect the health of workers.
Efficient Euclidean Projections onto the Intersection of Norm Balls

Using sparse-inducing norms to learn robust models has received increasing attention from many fields for its attractive properties. Projection-based methods have been widely applied to learning tasks constrained by such norms. As a key building block of these methods, an efficient operator for Euclidean projection onto the intersection of $\ell_1$ and $\ell_{1,q}$ norm balls $(q=2\text{or}\infty)$ is proposed in this paper. We prove that the projection can be reduced to finding the root of an auxiliary function which is piecewise smooth and monotonic. Hence, a bisection algorithm is sufficient to solve the problem. We show that the time complexity of our solution is $O(n+g\log g)$ for $q=2$ and $O(n\log n)$ for $q=\infty$, where $n$ is the dimensionality of the vector to be projected and $g$ is the number of disjoint groups; we confirm this complexity by experimentation. Empirical study reveals that our method achieves significantly better performance than classical methods in terms of running time and memory usage. We further show that embedded with our efficient projection operator, projection-based algorithms can solve regression problems with composite norm constraints more efficiently than other methods and give superior accuracy.
GFCache: A Greedy Failure Cache Considering Failure Recency and Failure Frequency for an Erasure-coded Storage System

In the big data era, data unavailability, either temporary or permanent, becomes a normal occurrence on a daily basis. Unlike the permanent data failure, which is fixed through a background job, temporarily unavailable data is recovered on-the-fly to serve the ongoing read request. However, those newly revived data is discarded after serving the request, due to the assumption that data experiencing temporary failures could come back alive later. Such disposal of failure data prevents the sharing of failure information among clients, and leads to many unnecessary data recovery processes, (e.g. caused by either recurring unavailability of a data or multiple data failures in one stripe), thereby straining system performance. To this end, this paper proposes GFCache to cache corrupted data for the dual purposes of failure information sharing and eliminating unnecessary data recovery processes. GFCache employs a greedy caching approach of opportunism to promote not only the failed data, but also sequential failure-likely data in the same stripe. Additionally, GFCache includes a FARC (Failure ARC) catch replacement algorithm, which features a balanced consideration of failure recency, frequency to accommodate data corruption with good hit ratio. The stored data in GFCache is able to support fast read of the normal data access. Furthermore, since GFCache is a generic failure cache, it can be used anywhere erasure coding is deployed with any specific coding schemes and parameters. Evaluations show that GFCache achieves good hit ratio with our sophisticated caching algorithm and manages to significantly boost system performance by reducing unnecessary data recoveries with vulnerable data in the cache.
How much do antiretroviral drugs penetrate into the central nervous system?

The central nervous system can act as a compartment in which HIV can replicate independently from plasma, and also as a sanctuary in which, under suboptimal drug pressure, HIV antiretroviral genetic variants can occur. Continuous replication of HIV in brain can contribute to neurocognitive impairment. Therefore, reaching adequate concentrations of antiretrovirals in the central nervous system might be essential in providing neuroprotection and improving neurocognition. Antiretrovirals have a restricted entry into the brain, due to several factors: the unique structure of the blood-brain barrier, and the existence of efficient efflux mechanisms. However, there is a high variability of antiretrovirals in reaching therapeutic drug concentrations in cerebrospinal fluid, that depend on the characteristics of the antiretrovirals (molecular weight, lipophilicity, protein binding) and on their capacity to be substrate for efflux transporters. The review aims to discuss the main mechanisms that interfere with antiretroviral penetration into central nervous system, and to summarize the current data concerning the penetrability of different antiretrovirals into the cerebrospinal fluid. Abbreviations: ART = antiretroviral treatment; ARV = antiretrovirals; NRTI = nucleos(t)idic reverse-transcriptase inhibitors; NNRTI = non-nucleosidic reverse transcriptase inhibitors; INNRT = integrase inhibitors; CNS = central nervous system; BBB = blood-brain barrier; CMT = carrier-mediated transport; AET = active efflux transports; PGP = P-glycoprotein; MRP = multidrug resistance-associated proteins; SLC = solute carriers; OATP = organic anion transporting polypeptide; OAT = organic anion transporters; OCT = organic cation transporters; EFV = Efavirenz; IDV = Indinavir; ZDV = Zidovudine; d4T = Stavudine; ABC = Abacavir; ddI = Didanosine; 3TC = Lamivudine; TDF = Tenofovir; NVP = Nevirapine; PI = Protease inhibitors; APV = Amprenavir; NFV = Nelfinavir; SQV = Saquinavir; ATV = Ataznavir; TPV = Tipranavir; DRV = Darunavir; T20 = Enfuvirtide; RGV = Raltegravir
Reasoning about Dynamic Depth Profiles

Reasoning about perception of depth and about spatial relations between moving physical objects is a challenging problem. We investigate the representation of depth and motion by means of depth profiles whereby each object in the world is represented as a single peak. We propose a logical theory, formulated in the situation calculus (SC), that is used for reasoning about object motion (including motion of the observer). The theory proposed here is comprehensive enough to accommodate reasoning about both sensor data and actions in the world. We show that reasoning about depth profiles is sound and complete with respect to actual motion in the world. This shows that in the conceptual neighbourhood diagram (CND) of all possible depth perceptions, the transitions between perceptions are logical consequences of the proposed theory of depth and motion.
Performance Analysis of IEEE 802.11 Rate Adaptation Algorithms Categorized Under Rate Controlling Parameters

Signal to Noise Ratio(SNR) and Frame Loss Statistic are two basic information used by IEEE 802.11 Rate Adaptation Algorithms for controlling data rates to achieve optimal data transfer. Despite these common information, different Rate Adaptation Algorithms initiate their Rate Control Activities depending on several other parameters such as successful or fail frame count, calculated SNR, Bit Error Rate (BER), loss ratio threshold, statistical analysis etc. In these paper we classify Rate Adaptation Algorithms into three rate controlling categories, Namely- i.Packet Count Based, ii.Analysis and Calculation Based, iii.Statistical Measurement Based. We survey algorithms from different categories and prepare a summarized activity table for better assessment. We also present a simulation based performance analysis of different algorithms using Network Simulator 3 (ns-3). The survey and performance analysis led us to enlist some open issues on Rate Adaptation technique, in the concluding section.