Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of 7A7, an anti-mouse EGFR monoclonal antibody proposed to be the mouse equivalent of cetuximab

The Epidermal Growth Factor Receptor (EGFR) is selectively expressed on the surface of numerous tumours, such as non-small cell lung, ovarian, colorectal and head and neck carcinomas. EGFR has therefore become a target for cancer therapy. Cetuximab is a chimeric human/mouse monoclonal antibody (mAb) that binds to EGFR, where it both inhibits signaling and induces cell death by antibody-dependent cell mediated cytotoxicity (ADCC). Cetuximab has been approved for clinical use in patients with head and neck squamous cell carcinoma (HNSCC) and colorectal cancer. However, only 15-20% patients benefit from this drug, thus new strategies to improve cetuximab efficiency are required. We aimed to develop a reliable and easy preclinical mouse model to evaluate the efficacy of EGFR-targeted antibodies and examine the immune mechanisms involved in tumour regression. We selected an anti-mouse EGFR mAb, 7A7, which has been reported to be “mouse cetuximab” and to exhibit similar properties to its human counterpart. Unfortunately, we were unable to reproduce previous results obtained with the 7A7 mAb. In our hands, 7A7 failed to recognize mouse EGFR, both in native and reducing conditions. Moreover, in vivo administration of 7A7 in an EGFR-expressing HPV38 tumour model did not have any impact on tumour regression or animal survival. We conclude that 7A7 does not recognize mouse EGFR and therefore cannot be used as the mouse equivalent of cetuximab use in humans. As a number of groups have spent effort and resources with similar issues we feel that publication is a responsible approach.
Change in Post-Traumatic Cognitions Mediates Treatment Effects for Traumatized Youth—A Randomized Controlled Trial

Posttraumatic stress symptoms (PTSS) are associated with serious impairments in psychological, social, and academic functioning in youth. The aim of this study was to investigate whether changes in posttraumatic cognitions mediate treatment effects. Participants were multitraumatized youth (N = 156, mean age = 15.1 years, range = 10–18; 79.5% girls) randomly assigned to receive trauma-focused cognitive–behavioral therapy (TF-CBT) or treatment-as-usual (TAU). Mixed-effects models were applied to investigate the impact of treatment conditions on posttraumatic cognitions. Mediation analyses were applied to examine whether changes in posttraumatic cognitions mediated the relationship between treatment conditions and outcome in posttraumatic stress symptoms, depressive symptoms, and general mental health. Participants receiving TF-CBT reported significantly lower levels of negative posttraumatic cognitions at the end of treatment compared to participants in TAU. Change in posttraumatic cognitions mediated the treatment effect difference found for PTSS. When the overall change in cognition was divided into early and late changes, it was only the late change that significantly mediated the PTSS treatment effect. A mediation effect of posttraumatic cognitions was also found for the treatment effect difference in depressive symptoms and in general mental health symptoms. Traumatized youth report having many negative posttraumatic cognitions and changes in negative cognitions plays a key role for treatment outcome.
Influence of Reciprocal Links in Social Networks

How does reciprocal links affect the function of real social network? Does reciprocal link and non-reciprocal link play the same role? Previous researches haven't displayed a clear picture to us until now according to the best of our knowledge. Motivated by this, in this paper, we empirically study the influence of reciprocal links in two representative real datasets, Sina Weibo and Douban. Our results demonstrate that the reciprocal links play a more important role than non-reciprocal ones in information diffusion process. In particular, not only coverage but also the speed of the information diffusion can be significantly enhanced by considering the reciprocal effect. We give some possible explanations from the perspectives of network connectivity and efficiency. This work may shed some light on the in-depth understanding and application of the reciprocal effect in directed online social networks.
An iterative algorithm to solve Algebraic Riccati Equations with an indefinite quadratic term

In this paper, an iterative algorithm to solve Algebraic Riccati Equations (ARE) arising from, for example, a standard H∞ control problem is proposed. By constructing two sequences of positive semidefinite matrices, we reduce an ARE with an indefinite quadratic term to a series of AREs with a negative semidefinite quadratic term which can be solved more easily by existing iterative methods (e.g. Kleinman algorithm in [2]). We prove that the proposed algorithm is globally convergent and has local quadratic rate of convergence. Numerical examples are provided to show that our algorithm has better numerical reliability when compared with some traditional algorithms (e.g. Schur method in [5]). Some proofs are omitted for brevity and will be published elsewhere.
Quality of Vitamin K Antagonist Control and 1-Year Outcomes in Patients with Atrial Fibrillation: A Global Perspective from the GARFIELD-AF Registry

Aims Vitamin K antagonists (VKAs) need to be individually dosed. International guidelines recommend a target range of international normalised ratio (INR) of 2.0–3.0 for stroke prevention in atrial fibrillation (AF). We analysed the time in this therapeutic range (TTR) of VKA-treated patients with newly diagnosed AF in the ongoing, global, observational registry GARFIELD-AF. Taking TTR as a measure of the quality of patient management, we analysed its relationship with 1-year outcomes, including stroke/systemic embolism (SE), major bleeding, and all-cause mortality. Methods and Results TTR was calculated for 9934 patients using 136,082 INR measurements during 1-year follow-up. The mean TTR was 55.0%; values were similar for different VKAs. 5851 (58.9%) patients had TTR<65%; 4083 (41.1%) TTR≥65%. The proportion of patients with TTR≥65% varied from 16.7% in Asia to 49.4% in Europe. There was a 2.6-fold increase in the risk of stroke/SE, 1.5-fold increase in the risk of major bleeding, and 2.4-fold increase in the risk of all-cause mortality with TTR<65% versus ≥65% after adjusting for potential confounders. The population attributable fraction, i.e. the proportion of events attributable to suboptimal anticoagulation among VKA users, was 47.7% for stroke/SE, 16.7% for major bleeding, and 45.4% for all-cause mortality. In patients with TTR<65%, the risk of first stroke/SE was highest in the first 4 months and decreased thereafter (test for trend, p = 0.021). In these patients, the risk of first major bleed declined during follow-up (p = 0.005), whereas in patients with TTR≥65%, the risk increased over time (p = 0.027). Conclusion A large proportion of patients with AF had poor VKA control and these patients had higher risks of stroke/SE, major bleeding, and all-cause mortality. Our data suggest that there is room for improvement of VKA control in routine clinical practice and that this could substantially reduce adverse outcomes. Trial Registration ClinicalTrials.gov NCT01090362
Efficiently engineered cell sheet using a complex of polyethylenimine–alginate nanocomposites plus bone morphogenetic protein 2 gene to promote new bone formation

Regeneration of large bone defects is a common clinical problem. Recently, stem cell sheet has been an emerging strategy in bone tissue engineering. To enhance the osteogenic potential of stem cell sheet, we fabricated bone morphogenetic protein 2 (BMP-2) gene-engineered cell sheet using a complex of polyethylenimine–alginate (PEI–al) nanocomposites plus human BMP-2 complementary(c)DNA plasmid, and studied its osteogenesis in vitro and in vivo. PEI–al nanocomposites carrying BMP-2 gene could efficiently transfect bone marrow mesenchymal stem cells. The cell sheet was made by culturing the cells in medium containing vitamin C for 10 days. Assays on the cell culture showed that the genetically engineered cells released the BMP-2 for at least 14 days. The expression of osteogenesis-related gene was increased, which demonstrated that released BMP-2 could effectively induce the cell sheet osteogenic differentiation in vitro. To further test the osteogenic potential of the cell sheet in vivo, enhanced green fluorescent protein or BMP-2-producing cell sheets were treated on the cranial bone defects. The results indicated that the BMP-2-producing cell sheet group was more efficient than other groups in promoting bone formation in the defect area. Our results suggested that PEI–al nanocomposites efficiently deliver the BMP-2 gene to bone marrow mesenchymal stem cells and that BMP-2 gene-engineered cell sheet is an effective way for promoting bone regeneration.
Computational analysis of protein interaction networks for infectious diseases

Abstract Infectious diseases caused by pathogens, including viruses, bacteria and parasites, pose a serious threat to human health worldwide. Frequent changes in the pattern of infection mechanisms and the emergence of multidrug-resistant strains among pathogens have weakened the current treatment regimen. This necessitates the development of new therapeutic interventions to prevent and control such diseases. To cater to the need, analysis of protein interaction networks (PINs) has gained importance as one of the promising strategies. The present review aims to discuss various computational approaches to analyse the PINs in context to infectious diseases. Topology and modularity analysis of the network with their biological relevance, and the scenario till date about host–pathogen and intra-pathogenic protein interaction studies were delineated. This would provide useful insights to the research community, thereby enabling them to design novel biomedicine against such infectious diseases.
Testing use of mitochondrial COI sequences for the identification and phylogenetic analysis of New Zealand caddisflies (Trichoptera)

Abstract We tested the hypothesis that cytochrome c oxidase subunit 1 (COI) sequences would successfully discriminate recognised species of New Zealand caddisflies. We further examined whether phylogenetic analyses, based on the COI locus, could recover currently recognised superfamilies and suborders. COI sequences were obtained from 105 individuals representing 61 species and all 16 families of Trichoptera known from New Zealand. No sequence sharing was observed between members of different species, and congeneric species showed from 2.3 to 19.5% divergence. Sequence divergence among members of a species was typically low (mean = 0.7%; range 0.0–8.5%), but two species showed intraspecific divergences in excess of 2%. Phylogenetic reconstructions based on COI were largely congruent with previous conclusions based on morphology, although the sequence data did not support placement of the purse‐cased caddisflies (Hydroptilidae) within the uncased caddisflies, and, in particular, the Rhyacophiloidea. We conclude that sequence variation in the COI gene locus is an effective tool for the identification of New Zealand caddisfly species, and can provide preliminary phylogenetic inferences. Further research is needed to ascertain the significance of the few instances of high intra‐specific divergence and to determine if any instances of sequence sharing will be detected with larger sample sizes.
ECAS score: a web-based risk model to predict moderate and severe extracranial carotid artery stenosis

Abstract Background and purpose To develop and validate a risk model (Extracranial Carotid Artery Stenosis score, ECAS score) to predict moderate and severe ECAS. Furthermore, we compared discrimination of the ECAS score and three existing models with regard to both moderate and severe ECAS. Methods The ECAS score was developed based on the Renqiu Stroke Screening Study (RSSS), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. ECAS was diagnosed by carotid duplex ultrasound according to the published criteria. Independent predictors of moderate (≥50%) and severe (≥70%) ECAS were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and the Hosmer–Lemeshow test were used to assess model discrimination and calibration. Results A total of 5010 participants were included and the mean age was 64.3. The proportion of ECAS of < 50%, 50–69%, 70–99% and occlusion was 4.4, 0.5, 0.4, and 0.4%, respectively. The ECAS score was developed from sets of predictors of moderate and severe ECAS. The ECAS score demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.785–0.846). The Hosmer–Lemeshow tests of ECAS score for moderate and severe ECAS were not significant in the derivation and validation cohorts (all P > 0.05). When compared to the three existing models, the ECAS score showed significantly better discrimination for both moderate and severe ECAS (all P < 0.001). Conclusion The ECAS score is a valid model for predicting moderate and severe ECAS. Further validation of the ECAS score in different populations and larger samples is warranted.
Sonata: query-driven streaming network telemetry

Managing and securing networks requires collecting and analyzing network traffic data in real time. Existing telemetry systems do not allow operators to express the range of queries needed to perform management or scale to large traffic volumes and rates. We present Sonata, an expressive and scalable telemetry system that coordinates joint collection and analysis of network traffic. Sonata provides a declarative interface to express queries for a wide range of common telemetry tasks; to enable real-time execution, Sonata partitions each query across the stream processor and the data plane, running as much of the query as it can on the network switch, at line rate. To optimize the use of limited switch memory, Sonata dynamically refines each query to ensure that available resources focus only on traffic that satisfies the query. Our evaluation shows that Sonata can support a wide range of telemetry tasks while reducing the workload for the stream processor by as much as seven orders of magnitude compared to existing telemetry systems.
Electrospun Polyvinylpyrrolidone (PVP) Nanofiber Mats Loaded by Garcinia mangostana L. Extracts

Composite nanofibers of polyvinylpyrrolidone (PVP) and Garcinia mangostana L. extract (GME) have been synthesized through electrospinning method for application in drug delivery systems. The precursor solution of 10 mL PVP 10% w/w and GME 2% w/w was then electrospun collected at the rotating collector at the following optimum parameters: a voltage of 15 kV, a collector-nozzle distance of 12 cm, and a flow rate of 1 mL/hour. SEM images showed that the average diameters were 476 nm and 690 nm for the PVP and PVP-GME composite nanofibers, respectively. To some degree, the addition of GME into PVP nanofibers increased the average diameter size of nanofibers. Moreover, the release studies, it was shown that 80% of the GME was released within 30 minutes. Therefore, the PVP-GME composite nanofibers can be applied as the drug delivery systems.
The pros and cons of ecological risk assessment based on data from different levels of biological organization

Abstract Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause–effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.
Genetic polymorphisms associated with pancreatic cancer survival: a genome‐wide association study

Previous findings on the association of genetic factors and pancreatic cancer survival are limited and inconsistent. In a two‐stage study, we analyzed the existing genome‐wide association study dataset of 868 pancreatic cancer patients from MD Anderson Cancer Center in relation to overall survival using Cox regression. Top hits were selected for replication in another 820 patients from the same institution using the Taqman genotyping method. Functional annotation, pathway analysis and gene expression analysis were conducted using existing software and databases. We discovered genome‐wide significant associations of patient survival with three imputed SNPs which, in complete LD (r2 = 1), were intronic SNPs of the PAIP2B (rs113988120) and DYSF genes (rs112493246 and rs138529893) located on Chromosome 2. The variant alleles were associated with a 3.06‐fold higher risk of death [95% confidence interval (CI) = 2.10–4.47, p=6.4 × 10−9 ] after adjusting for clinical factors. Eleven SNPs were tested in the replication study and the association of rs113988120 with survival was confirmed (hazard ratio: 1.57, 95% CI: 1.13–2.20, p=0.008 ). In silico analysis found rs1139988120 might lead to altered motif. This locus is in LD (D′ = 0.77) with three eQTL SNPs near or belong to the NAGK and MCEE genes. According to The Cancer Genome Atlas data and our previous RNA‐sequencing data, the mRNA expression level of PAIP2B but not NAGK, MCEE or DYSF was significantly lower in pancreatic tumors than in normal adjacent tissues. Additional validation efforts and functional studies are warranted to demonstrate whether PAIP2B is a novel tumor suppressor gene and a potential therapeutic target for pancreatic cancer.
On the applicability of random testing for aspect-oriented programs.

Abstract Random Testing(RT) and its derivatives such as Adaptive Random Testing (ART ) are active and important research topics in software testing, which have also a niche in practical settings due to the merits they offers, e.g. fault-detection capacities at low cost, ease of implementation, reliability estimation, facility for automation and so forth. Inspired by these advantages, we believe the idea behind random testing can be worthwhile and attractive for testing aspect-oriented programs since current research on testing of AOP, especially automated has not been adequately performed and is still in infancy. In this paper, we propose a preliminary approach to automated random testing of aspect-oriented programs, which are becoming an important part of software engineering theory and practice. This paper also includes a survey of applicable testing techniques and discussion of established testing methods in both area of Aspect-Oriented Programming (AOP) and Random Testing (RT). Keywords:
Current Management of Alcoholic Hepatitis and Future Therapies

Abstract Alcohol is one of the most common etiologies of liver disease, and alcoholic liver disease overall is the second most common indication for liver transplantation in the United States. It encompasses a spectrum of disease, including fatty liver disease, alcoholic hepatitis (AH), and alcoholic cirrhosis. AH can range from mild to severe disease, with severe disease being defined as: Discriminant Function (DF) ≥ 32, or Model for End-stage Liver Disease (MELD) ≥ 21, or presence of hepatic encephalopathy. Management of the mild disease consists mainly of abstinence and supportive care. Severe AH is associated with significant mortality. Currently, there is no ideal medical treatment for this condition. Besides alcohol cessation, corticosteroids have been used with conflicting results and are associated with an inherent risk of infection. Overall steroids have shown short term benefit when compared to placebo, but they have no obvious long term benefits. Pentoxifylline does not improve survival in patients with severe AH and is no longer recommended based on the results of the STOPAH (Steroid Or Pentoxifylline for Alcoholic Hepatitis) trial. Anti-tumor necrosis factor (TNF) agents are associated with increased risk of life threatening infections and death. Currently, early stage trials are underway, mainly targeting novel pathways based on disease pathogenesis, including modulation of innate immune system, inhibition of gut-liver axis and cell death pathways, and activation of transcription factor farnesyl X receptor (FXR). Future treatment may lie in human induced pluripotent stem cell (iPSC) technology, which is currently under investigation for the study of pathogenesis, drug discovery, and stem cell transplantation. Liver transplantation has been reported with good results in highly selected patients but is controversial due to limited organ supply.
Fast insight into time varying datasets with dynamic mesh

—Advances in computational power over the last two decades allowed fluid dynamic simulations that involve moving parts. Various mesh update methods are employed in such simulations to adapt cells around the moving parts, resulting in a separate new definition of the mesh geometry and associated values for each discrete simulation step. Common practice is to visualize every timestep of the simulation as a single static dataset. We present a novel method for interactive visualization of the evolving isosurfaces from the datasets with dynamic mesh. The effectiveness of the method is demonstrated on the real-life datasets from combustion simulation.