Miracle-dz/UniFAR-FTUs huggingface dataset:
The Disulfide Isomerase Grp58 Is a Protective Factor against Prion Neurotoxicity

Prion diseases are transmissible neurodegenerative disorders characterized by extensive neuronal apoptosis and accumulation of misfolded prion protein (PrPSC). Recent reports indicate that PrPSC induces neuronal apoptosis via activation of the endoplasmic reticulum (ER) stress pathway and activation of the ER resident caspase-12. Here, we investigate the relationship between prion replication and induction of ER stress during different stages of the disease in a murine scrapie model. The first alteration observed consists of the upregulation of the ER chaperone of the glucose-regulated protein Grp58, which was detected during the presymptomatic phase and followed closely the formation of PrPSC. An increase in Grp58 expression correlated with PrPSC accumulation at all stages of the disease in different brain areas, suggesting that this chaperone may play an important role in the cellular response to prion infection. Indeed, in vitro studies using N2a neuroblastoma cells demonstrated that inhibition of Grp58 expression with small interfering RNA led to a significant enhancement of PrPSC toxicity. Conversely, overexpression of Grp58 protected cells against PrPSC toxicity and decreased the rate of caspase-12 activation. Grp58 and PrP were shown to interact by coimmunoprecipitation, observing a higher interaction in cells infected with scrapie prions. Our data indicate that expression of Grp58 is an early cellular response to prion replication, acting as a neuroprotective factor against prion neurotoxicity. Our findings suggest that targeting Grp58 interaction may have applications for developing novel strategies for treatment and early diagnosis of prion diseases.
Tests for Genetic Interactions in Type 1 Diabetes

OBJECTIVE Interactions between genetic and environmental factors lead to immune dysregulation causing type 1 diabetes and other autoimmune disorders. Recently, many common genetic variants have been associated with type 1 diabetes risk, but each has modest individual effects. Familial clustering of type 1 diabetes has not been explained fully and could arise from many factors, including undetected genetic variation and gene interactions. RESEARCH DESIGN AND METHODS To address this issue, the Type 1 Diabetes Genetics Consortium recruited 3,892 families, including 4,422 affected sib-pairs. After genotyping 6,090 markers, linkage analyses of these families were performed, using a novel method and taking into account factors such as genotype at known susceptibility loci. RESULTS Evidence for linkage was robust at the HLA and INS loci, with logarithm of odds (LOD) scores of 398.6 and 5.5, respectively. There was suggestive support for five other loci. Stratification by other risk factors (including HLA and age at diagnosis) identified one convincing region on chromosome 6q14 showing linkage in male subjects (corrected LOD = 4.49; replication P = 0.0002), a locus on chromosome 19q in HLA identical siblings (replication P = 0.006), and four other suggestive loci. CONCLUSIONS This is the largest linkage study reported for any disease. Our data indicate there are no major type 1 diabetes subtypes definable by linkage analyses; susceptibility is caused by actions of HLA and an apparently random selection from a large number of modest-effect loci; and apart from HLA and INS, there is no important susceptibility factor discoverable by linkage methods.
Improvements on Restricted Insecticide Application Protocol for Control of Human and Animal African Trypanosomiasis in Eastern Uganda

Background African trypanosomes constrain livestock and human health in Sub-Saharan Africa, and aggravate poverty and hunger of these otherwise largely livestock-keeping communities. To solve this, there is need to develop and use effective and cheap tsetse control methods. To this end, we aimed at determining the smallest proportion of a cattle herd that needs to be sprayed on the legs, bellies and ears (RAP) for effective Human and Animal African Trypanosomiasis (HAT/AAT) control. Methodology/Principal finding Cattle in 20 villages were ear-tagged and injected with two doses of diminazene diaceturate (DA) forty days apart, and randomly allocated to one of five treatment regimens namely; no treatment, 25%, 50%, 75% monthly RAP and every 3 month Albendazole drench. Cattle trypanosome re-infection rate was determined by molecular techniques. ArcMap V10.3 was used to map apparent tsetse density (FTD) from trap catches. The effect of graded RAP on incidence risk ratios and trypanosome prevalence was determined using Poisson and logistic random effect models in R and STATA V12.1 respectively. Incidence was estimated at 9.8/100 years in RAP regimens, significantly lower compared to 25.7/100 years in the non-RAP regimens (incidence rate ratio: 0.37; 95% CI: 0.22–0.65; P<0.001). Likewise, trypanosome prevalence after one year of follow up was significantly lower in RAP animals than in non-RAP animals (4% vs 15%, OR: 0.20, 95% CI: 0.08–0.44; P<0.001). Contrary to our expectation, level of protection did not increase with increasing proportion of animals treated. Conclusions/significance Reduction in RAP coverage did not significantly affect efficacy of treatment. This is envisaged to improve RAP adaptability to low income livestock keepers but needs further evaluation in different tsetse challenge, HAT/AAT transmission rates and management systems before adopting it for routine tsetse control programs.
Net Worth: Facebook Use and Changes in Social Capital Over Time

Facebook is one of the largest social network sites and is widely used on college campuses. This paper builds upon earlier research which established a link between intensive Facebook use and bridging social capital, although the directionality of the relationship was unclear. Using longitudinal data, this paper provides preliminary evidence of a causal link between Facebook use and bridging social capita. We argue that bridging social capital, which is linked with the concept of weak ties, is especially important for individuals in the 18-25 year age range, and that the design of Facebook exposes individuals to those outside their close circle of friends. Although the high number of “friends” reported by many Facebook users would seem to suggest ephemeral and shallow relationships, we argue that this is in fact characteristic of a large, heterogeneous network ‐ precisely the kind of network that supports the formation of bridging social capital.
MAXIMAL COMMUTATIVE SUBALGEBRAS, POISSON GEOMETRY AND HOCHSCHILD HOMOLOGY.

A Poisson geometry arising from maximal commutative subalgebras is studied. A spectral sequence convergent to Hochschild homology with coefficients in a bimodule is presented. It depends on the choice of a maximal commutative subalgebra inducing appropriate filtrations. Its E p,q -groups are computed in terms of canonical homology with values in a Poisson module defined by a given bimodule and a maximal commutative subalgebra.
Predicting the Failure of Dental Implants Using Supervised Learning Techniques

Prosthodontic treatment has been a crucial part of dental treatment for patients with full mouth rehabilitation. Dental implant surgeries that replace conventional dentures using titanium fixtures have become the top choice. However, because of the wide-ranging scope of implant surgeries, patients’ body conditions, surgeons’ experience, and the choice of implant system should be considered during treatment. The higher price charged by dental implant treatments compared to conventional dentures has led to a rush among medical staff; therefore, the future impact of surgeries has not been analyzed in detail, resulting in medial disputes. Previous literature on the success factors of dental implants is mainly focused on single factors such as patients’ systemic diseases, operation methods, or prosthesis types for statistical correlation significance analysis. This study developed a prediction model for providing an early warning mechanism to reduce the chances of dental implant failure. We collected the clinical data of patients who received artificial dental implants at the case hospital for a total of 8 categories and 20 variables. Supervised learning techniques such as decision tree (DT), support vector machines, logistic regressions, and classifier ensembles (i.e., Bagging and AdaBoost) were used to analyze the prediction of the failure of dental implants. The results show that DT with both Bagging and Adaboost techniques possesses the highest prediction performance for the failure of dental implant (area under the receiver operating characteristic curve, AUC: 0.741); the analysis also revealed that the implant systems affect dental implant failure. The model can help clinical surgeons to reduce medical failures by choosing the optimal implant system and prosthodontics treatments for their patients.
The complete genome of the crenarchaeon Sulfolobus solfataricus P2

The genome of the crenarchaeon Sulfolobus solfataricus P2 contains 2,992,245 bp on a single chromosome and encodes 2,977 proteins and many RNAs. One-third of the encoded proteins have no detectable homologs in other sequenced genomes. Moreover, 40% appear to be archaeal-specific, and only 12% and 2.3% are shared exclusively with bacteria and eukarya, respectively. The genome shows a high level of plasticity with 200 diverse insertion sequence elements, many putative nonautonomous mobile elements, and evidence of integrase-mediated insertion events. There are also long clusters of regularly spaced tandem repeats. Different transfer systems are used for the uptake of inorganic and organic solutes, and a wealth of intracellular and extracellular proteases, sugar, and sulfur metabolizing enzymes are encoded, as well as enzymes of the central metabolic pathways and motility proteins. The major metabolic electron carrier is not NADH as in bacteria and eukarya but probably ferredoxin. The essential components required for DNA replication, DNA repair and recombination, the cell cycle, transcriptional initiation and translation, but not DNA folding, show a strong eukaryal character with many archaeal-specific features. The results illustrate major differences between crenarchaea and euryarchaea, especially for their DNA replication mechanism and cell cycle processes and their translational apparatus.
Towards the Development of XML Benchmark for XML Updates

Many XML Benchmarks have been proposed to study strengths and weaknesses of any given XML database system. All existing benchmarks can be applied to evaluate data retrieval queries, but cannot be used to evaluate update performance of XML database systems. Therefore, this paper will propose criteria to evaluate the abilities to update XML documents of XML database systems. These criteria will be realized by a data set and corresponding queries that are applied to benchmark XML updates. Finally, the competence of the proposal will be examined by using a case study.
Secure sharing between untrusted users in a transparent source/binary deployment model

The Nix software deployment system is based on the paradigm of transparent source/binary deployment: distributors deploy descriptors that build components from source, while client machines can transparently optimise such source builds by downloading pre-built binaries from remote repositories. This model combines the simplicity and flexibility of source deployment with the efficiency of binary deployment. A desirable property is sharing of components: if multiple users install from the same source descriptors, ideally only one remotely built binary should be installed. The problem is that users must trust that remotely downloaded binaries were built from the sources they are claimed to have been built from, while users in general do not have a trust relation with each other or with the same remote repositories.This paper presents three models that enable sharing: the extensional model that requires that all users on a system have the same remote trust relations, the intensional model that does not have this requirement but may be suboptimal in terms of space use, and the mixed model that merges the best properties of both. The latter two models are achieved through a novel technique of hash rewriting in content-addressable component stores, and were implemented in the context of the Nix system.
Artistic Language: An Emotional Behavior

Language is the carrier of communication for the people to reflect the objective world and the psychological behavior.The selection of lexical items not only mirrors the motives of communication,the function and naturalness of language,but also reflects the speech act and the psychological behavior of the speaker,that is,the logical behavior and emotional behavior.The science language is the carrier of logical behavior of the speaker;the artistic language,however,is the carrier of emotional behavior of the speaker.Emotional behavior of the artistic language is a type of the aesthetic behavior of the speaker,which expresses a kind of emotional image.The artistic language reflects the emotion mainly by way of the mental representation that is full of the speaker's emotion,which is an emotional and aesthetic process.
The Effects of Hesperidin and Quercetin on Serum Tumor Necrosis Factor-Alpha and Interleukin-6 Levels in Streptozotocin-induced Diabetes Model

Background: Diabetes mellitus (DM) is a metabolic disorder that occurs as a result of absolute or relative insufficiency of insulin release and/or insulin effect due to impairment of carbohydrate, fat and protein metabolism, and it is characterized by hyperglycemia and leads to various complications. Objective: In this study, it was aimed to investigate the effects of hesperidin (HP) and quercetin, which are natural flavonoids, on serum malondialdehyde (MDA), glutathione (GSH), tumor necrosis factor alpha (TNF-α), and interleukin-6 (IL-6) levels in rats with streptozotocin (STZ)-induced diabetes. Materials and Methods: The experimental animals were divided into four groups, each group comprising ten rats designated as follows: Group 1 served as control rats (C); Group 2 served as diabetic rats (DM); Group 3 served as diabetic rats administered HP (DM + HP) (100 mg/kg b. w.); and Group 4 served as diabetic rats administered quercetin (DM + Q) (100 mg/kg b. w.). Results: Serum MDA and GSH levels were significantly higher in STZ-induced DM group than control group (P < 0.05). In DM + HP and DM + Q groups, MDA levels were significantly decreased compared to DM groups (P < 0.05), but there was no significant difference GSH levels between DM, DM + HP, and DM + Q groups (P > 0.05). TNF-α levels in STZ-induced DM group were significantly decreased compared to control group (P < 0.05), and groups of DM + HP and DM + Q had higher serum TNF-α levels than STZ-induced DM group (P < 0.05). In STZ-induced DM group, serum IL-6 levels were decreased compared to control group (P < 0.05). Conclusion: As a result, in this study, we determined that HP and quercetin may play an effective role in regulating insulin metabolism metabolism in diabetes. However, considering the incompatibility of various results in the literature as well as our own results, we think that the actual role of cytokines in the pathogenesis of diabetes is one of the issues that need to be clarified in further studies. Abbreviations used: DM: Diabetes mellitus, MDA: Malondialdehyde, GSH: Glutathione; IL-6: Interleukin-6, TNF-α: Tumor necrosis factor alpha, HP: Hesperidin, Q; Quercetin, STZ: Streptozotocin, TC: Total cholesterol, TG: Triglyceride, HDL-C: High density lipoprotein cholesterol, LDL-C: Low density lipoprotein cholesterol, VLDL-C: Very-low-density lipoprotein cholesterol.
Energy-efficient propulsion inspired by whirligig beetles

Whirligig beetle, claimed in the literature to be one of the highest measured for a thrust-generating apparatus within the animal kingdom, has evolved a series of propulsion strategies that may serve as a source of inspiration for designing highly efficient propulsive systems. First, a robotic platform was developed to test an energy-efficient propulsion mechanism inspired by the whirligig beetle. Second, a mathematical model for the robot was proposed to account for the fluid dynamics generated by the robotic swimming. Third, an optimal problem was formulated and solved for the propulsor and beating pattern design. The results indicated that soft middle, stiff end propulsor, and alternating, asymmetrical beating pattern will improve the propulsion efficiency for a swimming robot with four propulsors. Finally, simulation and experiments were conducted to further analyze the effect of beating pattern to the robotic propulsion efficiency. It was found that the oscillated body movement and S-shaped trajectory introduced by the optimal beating pattern would improve the propulsion efficiency for the designed robot.
Multiple Episodes of Convergence in Genes of the Dim Light Vision Pathway in Bats

The molecular basis of the evolution of phenotypic characters is very complex and is poorly understood with few examples documenting the roles of multiple genes. Considering that a single gene cannot fully explain the convergence of phenotypic characters, we choose to study the convergent evolution of rod vision in two divergent bats from a network perspective. The Old World fruit bats (Pteropodidae) are non-echolocating and have binocular vision, whereas the sheath-tailed bats (Emballonuridae) are echolocating and have monocular vision; however, they both have relatively large eyes and rely more on rod vision to find food and navigate in the night. We found that the genes CRX, which plays an essential role in the differentiation of photoreceptor cells, SAG, which is involved in the desensitization of the photoactivated transduction cascade, and the photoreceptor gene RH, which is directly responsible for the perception of dim light, have undergone parallel sequence evolution in two divergent lineages of bats with larger eyes (Pteropodidae and Emballonuroidea). The multiple convergent events in the network of genes essential for rod vision is a rare phenomenon that illustrates the importance of investigating pathways and networks in the evolution of the molecular basis of phenotypic convergence.
Robust neonatal EEG seizure Detection through Adaptive Background Modeling

Adaptive probabilistic modeling of the EEG background is proposed for seizure detection in neonates with hypoxic ischemic encephalopathy. The decision is made based on the temporal derivative of the seizure probability with respect to the adaptively modeled level of background activity. The robustness of the system to long duration "seizure-like" artifacts, in particular those due to respiration, is improved. The system was developed using statistical leave-one-patient-out performance assessment, on a large clinical dataset, comprising 38 patients of 1479 h total duration. The developed technique was then validated by a single test on a separate totally unseen randomized prospective dataset of 51 neonates totaling 2540 h of duration. By exploiting the proposed adaptation, the ROC area is increased from 93.4% to 96.1% (41% relative improvement). The number of false detections per hour is decreased from 0.42 to 0.24, while maintaining the correct detection of seizure burden at 70%. These results on the unseen data were predicted from the rigorous leave-one-patient-out validation and confirm the validity of our algorithm development process.
Spike timing-dependent plasticity induces complexity in the brain

To study neuroplasticity, the capacity of neurons and neural networks to change temporarily or permanently their connections and behavior, we investigate the effects of spike timing-dependent plasticity (STDP) on synchronization in Hodgkin-Huxley neural networks. We consider spike timing-dependent plasticity of excitatory and inhibitory synapses according to the known Hebbian rules for synaptic plasticity. With regard to network architecture, initially the network presents an all-to-all topology, and due to the SDTP the connectivity suffers alteration. With this procedure, we verify that the STDP induces complexity in the brain. In particular, we show that the synchronous behavior has a dependence on the initial conditions in the plastic brain and, in addition, when a perturbation is included, we show that the plastic brain is able to present bistability: synchronous and non synchronous behaviors.
Percolation lithography: Tuning and freezing disorder in 3D photonic crystals using partial wetting and drying

Although complex, hierarchical nanoscale geometries with tailored degrees of disorder are commonly found in biological systems, few simple self-assembly routes to fabricating synthetic analogues have been identified. We present two techniques that exploit basic capillary phenomena to finely control disorder in porous 3D photonic crystals, leading to complex and hierarchical geometries. In the first, we exposed the structures to mixtures of ethanol and water that partially wet their pores, where small adjustments to the ethanol content controlled the degree of partial wetting. In the second, we infiltrated the structures with thin films of volatile alkanes and observed a sequence of partial infiltration patterns as the liquid evaporated. In both cases, macroscopic symmetry breaking was driven by subtle sub-wavelength variations in the pore geometry that directed site-selective infiltration of liquids. The resulting patterns, well described by percolation theory, had significant effects on the photonic structures' optical properties, including the wavelength-dependence and angular dependence of scattering. Incorporating cross-linkable resins into our liquids, we were able create permanent photonic structures with these properties by freezing in place the filling patterns at arbitrary degrees of partial wetting and intermediate stages of drying. These techniques illustrate the versatility of interfacial phenomena in directing and tuning self-assembly of aperiodic structures.
Supporting Window Analytics over Large-scale Dynamic Graphs

In relational DBMS, window functions have been widely used to facilitate data analytics. Surprisingly, while similar concepts have been employed for graph analytics, there has been no explicit notions of graph window analytic functions. In this paper, we formally introduce window queries for graph analytics. In such queries, for each vertex, the analysis is performed on a window of vertices defined based on the graph structure. In particular, we identify two instantiations, namely the k-hop window and the topological window. We develop two novel indices, Dense Block index (DBIndex) and Inheritance index (I-Index), to facilitate efficient processing of these two types of windows respectively. Extensive experiments are conducted over both real and synthetic datasets with hundreds of millions of vertices and edges. Experimental results indicate that our proposed index-based query processing solutions achieve four orders of magnitude of query performance gain than the non-index algorithm and are superior over EAGR wrt scalability and efficiency.