Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanotoxicity of Inert Materials: The Case of Gold, Silver and Iron.

Nanotechnology has opened a new horizon of research in various fields including applied physics, chemistry, electronics, optics, robotics, biotechnology and medicine. In the biomedical field, nanomaterials have shown remarkable potential as theranostic agents. Materials which are considered inert are often used in nanomedicine owning to their nontoxic profile. At nanoscale, these inert materials have shown unique properties that differ from bulk and dissolved counterparts. In the case of metals, this unique behavior not only imparts paramount advantages but also confers toxicity due to their unwanted interaction with different cellular processes. In the literature, the toxicity of nanoparticles made from inert materials has been investigated and many of these have revealed toxic potential under specific conditions. The surge to understand underlying mechanism of toxicity has increased and different means have been employed to overcome toxicity problems associated with these agents. In this review, we have focused nanoparticles of three inert metallic materials i.e. gold, silver and iron as these are regarded as biologically inert in the bulk and dissolved form. These materials have gained wider research interest and studies indicating the toxicity of these materials are also emerging. Oxidative stress, physical binding and interference with intracellular signaling are the major role player in nanotoxicity and their predominance is highly dependent upon size, surface coating and administered dose of nanoparticles. Current strategies to overcome toxicity have also been reviewed in the light of recent literature. The authors also suggested that uniform testing standards and well-designed studies are needed to evaluate nanotoxicity of these materials that are otherwise considered as inert. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
The N-terminus of the prion protein is a toxic effector regulated by the C-terminus

PrPC, the cellular isoform of the prion protein, serves to transduce the neurotoxic effects of PrPSc, the infectious isoform, but how this occurs is mysterious. Here, using a combination of electrophysiological, cellular, and biophysical techniques, we show that the flexible, N-terminal domain of PrPC functions as a powerful toxicity-transducing effector whose activity is tightly regulated in cis by the globular C-terminal domain. Ligands binding to the N-terminal domain abolish the spontaneous ionic currents associated with neurotoxic mutants of PrP, and the isolated N-terminal domain induces currents when expressed in the absence of the C-terminal domain. Anti-PrP antibodies targeting epitopes in the C-terminal domain induce currents, and cause degeneration of dendrites on murine hippocampal neurons, effects that entirely dependent on the effector function of the N-terminus. NMR experiments demonstrate intramolecular docking between N- and C-terminal domains of PrPC, revealing a novel auto-inhibitory mechanism that regulates the functional activity of PrPC. DOI: http://dx.doi. org/10.7554/eLife.23473. 001
Loss in weight by grinding tablets on dispensing

Grinding tablets is often required on dispensing. Weight loss in tablet content caused in that process was investigated with several uncoated and coated tablets. Two grinding methods, one using a mortar with pestle and the other using a tablet grinding machine, were conducted and the test results were compared with each other. The loss in weight varied depending on number of tablets employed: the larger the number of tablets becomes, the smaller the loss in weight is, and vice versa.That tendency was observed in both methods. However, the loss in weight by the method using a mortar with pestle was always greater than that by the method using a tablet grinding machine. The loss in weight of the tablets on grinding in a mortar with pestle together with powder was smaller than that of the tablets without powder.
Analysis of Ausubel auctions by means of evolutionary computation

The increasing use of auctions has led to a growing interest in the subject. A recent method used for carrying out examinations on auctions has been the design of computational simulations. The aim of this paper is to develop a genetic algorithm to find bidders' optimal strategies for a specific dynamic multi-unit auction. The algorithm provides the bidding strategy (defined as the action to be taken under different auction conditions) that maximizes the bidder's payoff. The algorithm is tested under several experimental environments, number of bidders and quantity of lots auctioned. The results suggest that the approach leads to strategies that outperform canonical strategies.
Market Integration Predicts Human Gut Microbiome Attributes across a Gradient of Economic Development

Previous research has reported differences in the gut microbiome between populations residing in wealthy versus poorer countries, leading to the assertion that lifestyle changes associated with economic development promote changes in the gut microbiome that promote the proliferation of microbiome-associated diseases. However, a direct relationship between economic development and the gut microbiome has not previously been shown. We surveyed the gut microbiomes of a single indigenous population undergoing economic development and found signiﬁcant associations between features of the gut microbiome and lifestyle changes associated with economic development. These ﬁndings suggest that even the earliest stages of economic development can drive changes in the gut microbiome, which may provide a warning sign for the development of microbiome-associated diseases. ABSTRACT Economic development is marked by dramatic increases in the incidence of microbiome-associated diseases, such as autoimmune diseases and metabolic syndromes, but the lifestyle changes that drive alterations in the human microbiome are not known. We measured market integration as a proxy for economically related lifestyle attributes, such as ownership of speciﬁc market goods that index degree of market integration and components of traditional and nontraditional (more modern) house structure and infrastructure, and proﬁled the fecal microbiomes of 213 participants from a contiguous, indigenous Ecuadorian population. Despite relatively modest differences in lifestyle across the population, greater economic development correlated with signiﬁcantly lower within-host diversity, higher between-host dissimilarity, and a decrease in the relative abundance of the bacterium Prevotella. These microbiome shifts were most strongly associated with more modern housing, followed by reduced ownership of traditional subsistence lifestyle-associated items. IMPORTANCE Previous research has reported differences in the gut microbiome between populations residing in wealthy versus poorer countries, leading to the assertion that lifestyle changes associated with economic development promote changes in the gut microbiome that promote the proliferation of microbiome-associated diseases. However, a direct relationship between economic development and the gut microbiome has not previously been shown. We surveyed the gut microbiomes of a single indigenous population undergoing economic development and found signiﬁcant associations between features of the gut microbiome and lifestyle changes associated with economic development. These ﬁndings suggest that even the earliest stages of economic development can drive changes in the gut microbiome, which may provide a warning sign for the development of microbiome-associated diseases.
Lethal and sublethal effects of aniline and chlorinated anilines on zebrafish embryos and larvae

Environmental risk assessments show increased attention to the sublethal effects of chemicals on aquatic organisms. The Organization for Economic Cooperation and Development (OECD) established the “Fish, Short‐term Toxicity Test on Embryo and Sac‐fry Stages” (OECD test 212) to predict lethal effects. It is still unclear, however, whether this test can predict sublethal effects. Although their sublethal effects are still unknown, chlorinated anilines are widely used in various fields. The purpose of this study, therefore, is to investigate sublethal effects of chlorinated anilines using OECD test 212 with zebrafish, and to examine the correlation of several sublethal effects between embryo and larval stages. Embryos were exposed to aniline and nine chlorinated anilines until 8 days post‐fertilization. A delayed lethal effect was observed from three of the 10 anilines tested. In the control group, the swim bladder inflated after hatching, but there was no swim‐bladder inflation after exposure to the chlorinated anilines. Fertilized eggs exposed to lower concentrations of test chemicals showed effects during embryogenesis that did not affect mortality rates, such as changes in body curvature and edema. Our results show that chlorinated anilines induce not only lethal effects but also a variety of sublethal effects. Moreover, a detailed estimate of these effects requires study during both embryonic and larval stages. OECD test 212 may therefore prove useful as a method for screening chemicals for lethal and sublethal effects. Copyright © 2017 John Wiley & Sons, Ltd.
Angle-based space partitioning for efficient parallel skyline computation

Recently, skyline queries have attracted much attention in the database research community. Space partitioning techniques, such as recursive division of the data space, have been used for skyline query processing in centralized, parallel and distributed settings. Unfortunately, such grid-based partitioning is not suitable in the case of a parallel skyline query, where allpartitions are examined at the same time, since many data partitions do not contribute to the overall skyline set, resulting in a lot of redundant processing. In this paper we propose a novel angle-based space partitioning scheme using the hyperspherical coordinates of the data points. We demonstrate both formally as well as through an exhaustive set of experiments that this new scheme is very suitable for skyline query processing in a parallel share-nothing architecture. The intuition of our partitioning technique is that the skyline points are equally spread to all partitions. We also show that partitioning the data according to the hyperspherical coordinates manages to increase the average pruning power of points within a partition. Our novel partitioning scheme alleviates most of the problems of traditional grid partitioning techniques, thus managing to reduce the response time and share the computational workload more fairly. As demonstrated by our experimental study, our technique outperforms grid partitioning in all cases, thus becoming an efficient and scalable solution for skyline query processing in parallel environments.
How to Detect Insight Moments in Problem Solving Experiments

Arguably, it is not possible to study insight moments during problem solving without being able to accurately detect when they occur (Bowden and Jung-Beeman, 2007). Despite over a century of research on the insight moment, there is surprisingly little consensus on the best way to measure them in real-time experiments. There have also been no attempts to evaluate whether the different ways of measuring insight converge. Indeed, if it turns out that the popular measures of insight diverge, then this may indicate that researchers who have used one method may have been measuring a different phenomenon to those who have used another method. We compare the strengths and weaknesses of the two most commonly cited ways of measuring insight: The feelings-of-warmth measure adapted from Metcalfe and Wiebe (1987), and the self-report measure adapted from Bowden and Jung-Beeman (2007). We find little empirical agreement between the two measures, and conclude that the self-report measure of Aha! is superior both methodologically and theoretically, and provides a better representation of what is commonly regarded as insight. We go on to describe and recommend a novel visceral measure of insight using a dynamometer as described in Creswell et al. (2016).
Lifetime Doctor-Diagnosed Mental Health Conditions and Current Substance Use Among Gay and Bisexual Men Living in Vancouver, Canada

ABSTRACT Background: Studies have found that gay, bisexual, and other men who have sex with men (GBM) have higher rates of mental health conditions and substance use than heterosexual men, but are limited by issues of representativeness. Objectives: To determine the prevalence and correlates of mental health disorders among GBM in Metro Vancouver, Canada. Methods: From 2012 to 2014, the Momentum Health Study recruited GBM (≥16 years) via respondent-driven sampling (RDS) to estimate population parameters. Computer-assisted self-interviews (CASI) collected demographic, psychosocial, and behavioral information, while nurse-administered structured interviews asked about mental health diagnoses and treatment. Multivariate logistic regression using manual backward selection was used to identify covariates for any lifetime doctor diagnosed: (1) alcohol/substance use disorder and (2) any other mental health disorder. Results: Of 719 participants, 17.4% reported a substance use disorder and 35.2% reported any other mental health disorder; 24.0% of all GBM were currently receiving treatment. A lifetime substance use disorder diagnosis was negatively associated with being a student (AOR = 0.52, 95% CI [confidence interval]: 0.27–0.99) and an annual income ≥$30,000 CAD (AOR = 0.38, 95% CI: 0.21–0.67) and positively associated with HIV-positive serostatus (AOR = 2.54, 95% CI: 1.63–3.96), recent crystal methamphetamine use (AOR = 2.73, 95% CI: 1.69–4.40) and recent heroin use (AOR = 5.59, 95% CI: 2.39–13.12). Any other lifetime mental health disorder diagnosis was negatively associated with self-identifying as Latin American (AOR = 0.25, 95% CI: 0.08–0.81), being a refugee or visa holder (AOR = 0.18, 95% CI: 0.05–0.65), and living outside Vancouver (AOR = 0.52, 95% CI: 0.33–0.82), and positively associated with abnormal anxiety symptomology scores (AOR = 3.05, 95% CI: 2.06–4.51). Conclusions: Mental health conditions and substance use, which have important implications for clinical and public health practice, were highly prevalent and co-occurring.
Sunitinib: Ten Years of Successful Clinical Use and Study in Advanced Renal Cell Carcinoma.

The oral multikinase inhibitor sunitinib malate was approved by the U.S. Food and Drug Administration in January 2006 for use in patients with advanced renal cell carcinoma (RCC). Since then, it has been approved globally for this indication and for patients with imatinib-resistant or -intolerant gastrointestinal stromal tumors and advanced pancreatic neuroendocrine tumors. As we mark the 10-year anniversary of the beginning of the era of targeted therapy, and specifically the approval of sunitinib, it is worthwhile to highlight the progress that has been made in advanced RCC as it relates to the study of sunitinib. We present the key trials and data for sunitinib that established it as a reference standard of care for first-line advanced RCC therapy and, along with other targeted agents, significantly altered the treatment landscape in RCC. Moreover, we discuss the research with sunitinib that has sought to refine its role via patient selection and prognostic markers, improve dosing and adverse event management, and identify predictive efficacy biomarkers, plus the extent to which this research has contributed to the overall understanding and management of RCC. We also explore the key learnings regarding study design and data interpretation from the sunitinib studies and how these findings and the sunitinib development program, in general, can be a model for successful development of other agents. Finally, ongoing research into the continued and future role of sunitinib in RCC management is discussed. THE ONCOLOGIST 2017;22:41-52 IMPLICATIONS FOR PRACTICE: Approved globally, sunitinib is established as a standard of care for first-line advanced renal cell carcinoma (RCC) therapy and, along with other targeted agents, has significantly altered the treatment landscape in RCC. Research with sunitinib that has sought to refine its role via patient selection and prognostic markers, improve dosing and adverse event management, and identify predictive efficacy biomarkers has contributed to the overall understanding and management of RCC. Key learnings regarding study design and data interpretation from the sunitinib studies and the sunitinib development program, in general, can be a model for the successful development of other agents.
Salient Object Detection via Structured Matrix Decomposition

Low-rank recovery models have shown potential for salient object detection, where a matrix is decomposed into a low-rank matrix representing image background and a sparse matrix identifying salient objects. Two deficiencies, however, still exist. First, previous work typically assumes the elements in the sparse matrix are mutually independent, ignoring the spatial and pattern relations of image regions. Second, when the low-rank and sparse matrices are relatively coherent, e.g., when there are similarities between the salient objects and background or when the background is complicated, it is difficult for previous models to disentangle them. To address these problems, we propose a novel structured matrix decomposition model with two structural regularizations: (1) a tree-structured sparsity-inducing regularization that captures the image structure and enforces patches from the same object to have similar saliency values, and (2) a Laplacian regularization that enlarges the gaps between salient objects and the background in feature space. Furthermore, high-level priors are integrated to guide the matrix decomposition and boost the detection. We evaluate our model for salient object detection on five challenging datasets including single object, multiple objects and complex scene images, and show competitive results as compared with 24 state-of-the-art methods in terms of seven performance metrics.
Tuning the morphology of self-assisted GaP nanowires

Patterned arrays of self-assisted GaP nanowires (NWs) were grown on a Si substrate by gas source molecular beam epitaxy using various V/III flux ratios from 1–6, and various pitches from 360–1000 nm. As the V/III flux ratio was increased from 1–6, the NWs showed a change in morphology from outward tapering to straight, and eventually to inward tapering. The morphologies of the self-assisted GaP NWs are well described by a simple kinetic equation for the NW radius versus the position along the NW axis. The most important growth parameter that governs the NW morphology is the V/III flux ratio. Sharpened NWs with a stable radius equal to only 12 nm at a V/III flux of 6 were achieved, demonstrating their suitability for the insertion of quantum dots.
Large-scale school reform as viewed from the self-determination theory perspective

Successful school reform requires that administrators, teachers, and students internalize the value of improved teaching and learning and of the policies, structures, procedures, and behaviors implicit in the reform. This is most likely to happen when school personnel and students experience satisfaction of their basic psychological needs for autonomy, competence, and relatedness while planning and implementing the reform. When the components of a reform are relatively flexible rather than rigid and when the processes through which the reform is introduced and implemented are autonomy supportive, people will experience greater need satisfaction and will be more likely to internalize and endorse the reform. This article focuses on one approach to comprehensive school reform, namely, First Things First, and examines it in terms of self-determination theory principles.
West Nile Virus Infection in American Singer Canaries: An Experimental Model in a Highly Susceptible Avian Species

This study investigated the susceptibility of American singer canaries (Serinus canaria) to West Nile virus (WNV) infection. Adult canaries were inoculated with 105, 102, and 101 plaque forming units (PFU) of WNV. All birds became infected and mortality occurred by 5 days postinoculation. The load of viral RNA as determined by RT-qPCR was dose dependent, and was higher at all doses than the level of viral RNA detected in American crows (Corvus brachyrhynchos) challenged with 105 PFU of WNV. In a subset of birds, viremia was detected by virus isolation; canaries inoculated with 101 PFU of WNV developed viremia exceeding 1010 PFU/mL serum, a log higher than American crows inoculated with 105 PFU of virus. In canaries euthanized at 3 days postinoculation, WNV was isolated at >107 PFU of virus/100 mg of lung, liver, heart, spleen, and kidney tissues. Pallor of the liver and splenomegaly were the most common macroscopic observations and histologic lesions were most severe in liver, spleen, and kidney, particularly in canaries challenged with 102 and 101 PFU. Immunoreactivity to WNV was pronounced in the liver and spleen. IgG antibodies to WNV were detected in serum by enzyme immunoassay in 11 of 21 (52%) challenged canaries and, in 4 of 5 (20%) of these sera, neutralization antibodies were detected at a titer ≥ 1:20. American singer canaries provide a useful model as this bird species is highly susceptible to WNV infection.
Syddansk Universitet Identifying subgroups of patients using latent class analysis should we use a single-stage or a two-stage approach ? A methodological study using a cohort of patients with low back pain

Background: Heterogeneity in patients with low back pain (LBP) is well recognised and different approaches to subgrouping have been proposed. Latent Class Analysis (LCA) is a statistical technique that is increasingly being used to identify subgroups based on patient characteristics. However, as LBP is a complex multi-domain condition, the optimal approach when using LCA is unknown. Therefore, this paper describes the exploration of two approaches to LCA that may help improve the identification of clinically relevant and interpretable LBP subgroups. Methods: From 928 LBP patients consulting a chiropractor, baseline data were used as input to the statistical subgrouping. In a single-stage LCA, all variables were modelled simultaneously to identify patient subgroups. In a twostage LCA, we used the latent class membership from our previously published LCA within each of six domains of health (activity, contextual factors, pain, participation, physical impairment and psychology) (first stage) as the variables entered into the second stage of the two-stage LCA to identify patient subgroups. The description of the results of the single-stage and two-stage LCA was based on a combination of statistical performance measures, qualitative evaluation of clinical interpretability (face validity) and a subgroup membership comparison. Results: For the single-stage LCA, a model solution with seven patient subgroups was preferred, and for the two-stage LCA, a nine patient subgroup model. Both approaches identified similar, but not identical, patient subgroups characterised by (i) mild intermittent LBP, (ii) recent severe LBP and activity limitations, (iii) very recent severe LBP with both activity and participation limitations, (iv) work-related LBP, (v) LBP and several negative consequences and (vi) LBP with nerve root involvement. Conclusions: Both approaches identified clinically interpretable patient subgroups. The potential importance of these subgroups needs to be investigated by exploring whether they can be identified in other cohorts and by examining their possible association with patient outcomes. This may inform the selection of a preferred LCA approach.