Miracle-dz/UniFAR-FTUs huggingface dataset:
A subset of chemosensory genes differs between two populations of a specialized leaf beetle after host plant shift

Abstract Due to its fundamental role in shaping host selection behavior, we have analyzed the chemosensory repertoire of Chrysomela lapponica. This specialized leaf beetle evolved distinct populations which shifted from the ancestral host plant, willow (Salix sp., Salicaceae), to birch (Betula rotundifolia, Betulaceae). We identified 114 chemosensory candidate genes in adult C. lapponica: 41 olfactory receptors (ORs), eight gustatory receptors, 17 ionotropic receptors, four sensory neuron membrane proteins, 32 odorant binding proteins (OBPs), and 12 chemosensory proteins (CSP) by RNA‐seq. Differential expression analyses in the antennae revealed significant upregulation of one minus‐C OBP (Clap OBP27) and one CSP (Clap CSP12) in the willow feeders. In contrast, one OR (Clap OR17), four minus‐C OBPs (Clap OBP02, 07, 13, 20), and one plus‐C OBP (Clap OBP32) were significantly upregulated in birch feeders. The differential expression pattern in the legs was more complex. To narrow down putative ligands acting as cues for host discrimination, the relative abundance and diversity of volatiles of the two host plant species were analyzed. In addition to salicylaldehyde (willow‐specific), both plant species differed mainly in their emission rate of terpenoids such as (E,E)‐α‐farnesene (high in willow) or 4,8‐dimethylnona‐1,3,7‐triene (high in birch). Qualitatively, the volatiles were similar between willow and birch leaves constituting an “olfactory bridge” for the beetles. Subsequent structural modeling of the three most differentially expressed OBPs and docking studies using 22 host volatiles indicated that ligands bind with varying affinity. We suggest that the evolution of particularly minus‐C OBPs and ORs in C. lapponica facilitated its host plant shift via chemosensation of the phytochemicals from birch as novel host plant.
Exclusive Independent Probability Estimation using Deep 3D Fully Convolutional DenseNets for IsoIntense Infant Brain MRI Segmentation

Background and Objective: The most recent fast and accurate image segmentation methods are built upon fully convolutional deep neural networks. In particular, densely connected convolutional neural networks have shown excellent performance in detection and segmentation tasks. Infant brain MRI tissue segmentation is a complex segmentation task as the white matter and gray matter of the developing brain at about 6 months of age show similar T1 and T2 relaxation times, thus appear to have similar intensity values on both T1and T2-weighted MRI scans. Brain tissue segmentation in this period is, therefore, very challenging. In this paper, we propose new deep learning strategies to overcome the challenges of isointense infant brain MRI tissue segmentation. Methods: We propose new training strategies to train powerful 3D multi-channel fully convolutional deep DenseNets for isointense tissue segmentation. We introduce an exclusive multi-label training method to independently segment the mutually exclusive brain tissues with similarity loss function parameters that are balanced based on class prevalence. Using our proposed training technique based on similarity loss functions and patch prediction fusion we decrease the number of parameters in the network, reduce the complexity of the training process focusing the attention on less number of tasks, while mitigating the effects of data imbalance between labels and inaccuracies near patch borders. Results: By taking advantage of these strategies we were able to perform fast image segmentation (less than 90 seconds per 3D volume), using a network with less parameters than many state-of-the-art networks (1.4 million parameters), overcoming issues such as 3D vs 2D training and large vs small patch size selection, while achieving the top performance in segmenting brain tissue among all methods tested in first and second round submissions of the 2017 MICCAI iSeg grand challenge. Conclusion: We present a new and powerful 3D FC-DenseNet architecture, a novel exclusive multi-label patch-wise training technique with balanced similarity loss functions and a patch prediction fusion strategy that can be used on new classification and segmentation applications with two or more very similar classes. This strategy improves the training process by reducing its complexity while providing a trained model that works for any size input and is fast and more accurate than many state-of-the-art methods. c © 2018 Elsevier B.V. All rights reserved.
Distinct Tie2 tyrosine phosphorylation sites dictate phenotypic switching in endothelial progenitor cells

Angiogenesis is a regulated process involving the proliferation, migration, and remodeling of different cell types particularly mature endothelial and their progenitor cells, nominated as endothelial progenitor cells (EPCs). Tie2/Tek is a tyrosine kinase receptor expressed by endothelial cells that induces signal transduction pathways involved in endothelial biology. To address the potential importance of the various tyrosine residues of Tie2 in EPC development, we generated a series of Tie2 tyrosine mutated (Y1106F, Y1100F, and Y1111F) EPCs and then assess the biological features of these cells. Clonogenic, tubulogenic, proliferative, migratory, and functional properties of these cells were analyzed. Next, GFP‐positive EPCs containing Tie2 tyrosine mutations were systemically transplanted into sublethaly irradiated mice to analyze the potency of these cells for marrow reconstitution. We found that mutation in the Tie2 tyrosine 1106 residue directed EPCs toward a mature endothelial phenotype, which was associated with augmented tubulogenic and migratory properties, and increased phosphorylation of the active site (tyrosine 992) as well as increased vascular perfusion in the in vivo Matrigel plug assay. Moreover, transplantation of 1106 Tie2 mutant EPCs failed to reconstitute the bone marrow after myeloablation, whereas transplantation of EPCs with the 1100 or 1111 Tie2 tyrosine mutation resulted in bone marrow engraftment, leading to improved survival of recipient mice. Our findings demonstrate that the tyrosine 1106 residue in Tie2 plays a key role to maintain the stemness features of EPCs.
Deep Domain Adaptation under Deep Label Scarcity

The goal behind Domain Adaptation (DA) is to leverage the labeled examples from a source domain so as to infer an accurate model in a target domain where labels are not available or in scarce at the best. A state-of-the-art approach for the DA is due to (Ganin et al. 2016), known as DANN, where they attempt to induce a common representation of source and target domains via adversarial training. This approach requires a large number of labeled examples from the source domain to be able to infer a good model for the target domain. However, in many situations obtaining labels in the source domain is expensive which results in deteriorated performance of DANN and limits its applicability in such scenarios. In this paper, we propose a novel approach to overcome this limitation. In our work, we first establish that DANN reduces the original DA problem into a semi-supervised learning problem over the space of common representation. Next, we propose a learning approach, namely TransDANN, that amalgamates adversarial learning and transductive learning to mitigate the detrimental impact of limited source labels and yields improved performance. Experimental results (both on text and images) show a significant boost in the performance of TransDANN over DANN under such scenarios. We also provide theoretical justification for the performance boost.
LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking

In this paper, we present LaSOT, a high-quality benchmark for Large-scale Single Object Tracking. LaSOT consists of 1,400 sequences with more than 3.5M frames in total. Each frame in these sequences is carefully and manually annotated with a bounding box, making LaSOT the largest, to the best of our knowledge, densely annotated tracking benchmark. The average video length of LaSOT is more than 2,500 frames, and each sequence comprises various challenges deriving from the wild where target objects may disappear and re-appear again in the view. By releasing LaSOT, we expect to provide the community with a large-scale dedicated benchmark with high quality for both the training of deep trackers and the veritable evaluation of tracking algorithms. Moreover, considering the close connections of visual appearance and natural language, we enrich LaSOT by providing additional language specification, aiming at encouraging the exploration of natural linguistic feature for tracking. A thorough experimental evaluation of 35 tracking algorithms on LaSOT is presented with detailed analysis, and the results demonstrate that there is still a big room for improvements.
Integrating the Rural: Gellner and the Study of Anatolia

Turkey has a special place in the heart of many Western commentators. In spite of the perorations of Edward Said, they remain attracted by its colourful past, beautiful mosques and sensuous culture. It is neither too big to be overwhelming, nor is it so small as to be insignificant on the world's stage. ' Its recent history is absolutely fascinating. Ataturk's reforms, which transformed a dying theocratic empire into a vibrant secular nation-state constitute without doubt the most major, sustained and intricate attempt at social engineering outside communism. Little wonder then that so many people have felt the call to research, to travel and to publish their findings on its past and present. Intriguingly, however, there is a lacuna at the heart of several
Evaluation on the effect of hydrogen sulfide on the NLRP3 signaling pathway and its involvement in the pathogenesis of atherosclerosis

As a common disease, the incidence of atherosclerosis (AS) in the world is high. Therefore, we aimed to evaluate the involvement of hydrogen sulfide (H 2S)/cystathionine γ‐lyase (CSE) in the pathogenesis of AS as well as their possible signaling pathways.
How do users adopt health information from social media? The narrative paradigm perspective

Introduction: A recent trend in health information seeking and sharing is the use of social media. Although there are several benefits to the use of social media for health communication, the quality of health information exchanged on social media is troubling due to its informal, unregulated mechanisms for information collection, sharing and promotion. Therefore, it is important to understand how users adopt health information from social media. Method: Considering the user-generated and storytelling nature of social media messages, this research employed the narrative paradigm perspective to explain the social media health information adoption phenomenon. Specifically, narrative coherence (NC) and narrative fidelity (NF) were hypothesised to have positive effects on the intention to adopt (IA). Additionally, socio-economic status (SES) was viewed as a proxy variable to cognitive capability and was hypothesised to moderate the effects of NC and NF. A scenario-based survey was conducted to test the proposed research model. Results: We obtained a total of 257 valid questionnaires. The results indicated that NF (p < 0.001) had a positive effect on the IA social media health information. The NC (p < 0.01) had no impact on the low SES users but a positive impact on the high SES users. Further, the effect of NF (p < 0.01) on the IA was higher for high SES users than low SES users. Conclusions: NC and NF are two major driving forces in social media health information adoption, and the effect of both narrative paradigm variables depends on the SES users. Implications Results of this study show how the narrative paradigm, with a focus on the storytelling method of communication rather than logical scientific argument, can not only explain the uptake of health messages from social media, but also provide guidance as to how to create health messages on social media that more effectively target end users.
Compressed Sensing Diffusion Spectrum Imaging for Accelerated Diffusion Microstructure MRI in Long-Term Population Imaging

Mapping non-invasively the complex microstructural architecture of the living human brain, diffusion magnetic resonance imaging (dMRI) is one of the core imaging modalities in current population studies. For the application in longitudinal population imaging, the dMRI protocol should deliver reliable data with maximum potential for future analysis. With the recent introduction of novel MRI hardware, advanced dMRI acquisition strategies can be applied within reasonable scan time. In this work we conducted a pilot study based on the requirements for high resolution dMRI in a long-term and high throughput population study. The key question was: can diffusion spectrum imaging accelerated by compressed sensing theory (CS-DSI) be used as an advanced imaging protocol for microstructure dMRI in a long-term population imaging study? As a minimum requirement we expected a high level of agreement of several diffusion metrics derived from both CS-DSI and a 3-shell high angular resolution diffusion imaging (HARDI) acquisition, an established imaging strategy used in other population studies. A wide spectrum of state-of-the-art diffusion processing and analysis techniques was applied to the pilot study data including quantitative diffusion and microstructural parameter mapping, fiber orientation estimation and white matter fiber tracking. When considering diffusion weighted images up to the same maximum diffusion weighting for both protocols, group analysis across 20 subjects indicates that CS-DSI performs comparable to 3-shell HARDI in the estimation of diffusion and microstructural parameters. Further, both protocols provide similar results in the estimation of fiber orientations and for local fiber tracking. CS-DSI provides high radial resolution while maintaining high angular resolution and it is well-suited for analysis strategies that require high b-value acquisitions, such as CHARMED modeling and biomarkers from the diffusion propagator.
Preoperative Evaluation of Pancreatic Fibrosis and Lipomatosis: Correlation of Magnetic Resonance Findings With Histology Using Magnetization Transfer Imaging and Multigradient Echo Magnetic Resonance Imaging

Objectives The purpose of this study was to evaluate the diagnostic performance of magnetization transfer (MT) imaging and multigradient echo magnetic resonance imaging (MRI) to quantify pancreatic fibrosis and lipomatosis in patients before pancreatoduodenectomy for postoperative risk stratification with histopathology as the reference standard. Materials and Methods Twenty-four patients (age, 68 ± 8 years, 16 males) prospectively underwent quantitative MT imaging using a 2-dimensional gradient echo sequence with and without MT prepulse and multigradient echo imaging on a 3 T MRI 1 day before pancreatoduodenectomy due to adenocarcinoma of the pancreatic head region (n = 20), neuroendocrine tumor (n = 3), or intraductal papillary mucinous neoplasm (n = 1). Magnetization transfer ratio (MTR) and proton density fat fraction (PDFF) were measured in pancreatic tail (PT) and at the resection margin (RM). Histopathologically, pancreatic fibrosis was graded as mild, moderate, or severe (F1–F3), lipomatosis was graded as 0% to 10%, 11% to 30%, and greater than 30% fat deposition (L1–L3). In addition, MTR and histopathologic fibrosis was assessed in pancreatic adenocarcinoma. Mann-Whitney U test and Spearman correlation were used. Results Patients with advanced pancreatic fibrosis (F3) showed a significantly higher MTR compared with the F1 group at the RM and PT (38 ± 4 vs 32.3 ± 1.6, P = 0.018 and 39.7 ± 5.5 vs 31.2 ± 1.7, P = 0.001). Spearman correlation coefficient of MTR and fibrosis grade was r = 0.532 (P = 0.011) and 0.554 (P = 0.008), respectively. Pancreatic parenchyma with advanced fat deposition (L2–L3) showed significantly higher PDFF compared with lipomatosis grade L1 (RM: P = 0.002 and PT: P = 0.001). Proton density fat fraction of pancreatic parenchyma exhibited a moderate and significant correlation with histopathologic lipomatosis grade (RM: r = 0.668 and PT: r = 0.707, P < 0.001). Magnetization transfer ratio was significantly higher in pancreatic adenocarcinoma compared with pancreatic parenchyma (44 ± 5.5 vs 36.0 ± 4.4 and 37.4 ± 5.4, P = 0.004). Conclusions Multiparametric MRI of the pancreas including MTR and PDFF maps may provide quantitative and noninvasive information on pancreatic fibrosis and lipomatosis before surgery.
Surface Modification of Esophageal Stent Materials by a Drug-Eluting Layer for Better Anti-Restenosis Function

It is generally accepted that stent implantation is the mainstream therapy in clinics for esophageal cancer in the later period. However, the restenosis caused by tumor cells, epithelial cells, and fibroblasts seriously interferes with the stent medical application and limits its long-term services. To address this conundrum, a series of drug-eluting stents were invented and verified to be feasible in the early stage after implantation, but the limited drug loading and good cell compatibility of the stent materials may lead to more serious restenosis and further endanger the patient’s life. In previous work, we modified the esophageal stent material 317L stainless steel (317L SS) surface with a poly-dopamine/poly-ethylenimine layer (PDA/PEI), which had strong anti-tumor functions. In this contribution, we employed a usual drug in clinic, 5-fluorouracil (5-Fu), with series of density onto the PDA/PEI modified 317L SS to investigate the influence of 5-Fu immobilization on the anti-restenosis function. The surface characterization including 5-Fu quantity, atomic force microscopy (AFM). Water contact angle measurement indicated successful preparation of the PDA/PEI/5-Fu layers. The spectrophotometric characterization revealed that the immobilized 5-Fu rapidly released over 24 h. However, the Eca109, Het-1A, and L929 cells culture results suggested that the released 5-Fu made a significant contribution to improving the apoptosis and necrosis of these pathological cells, and the PDA/PEI/5-Fu layers maintain the consistent anti-restenosis function on their surfaces with the PDA/PEI layer after 24 h. All the results demonstrated the PDA/PEI/5-Fu layers’ excellent ability to suppress esophageal tumor cells, epithelial cells, and fibroblasts, suggesting a potential application on the surface modification of esophageal stents for better anti-restenosis function.
Who has insights? The who, where, and when of the Eureka moment

Background: Research investigating insight problem solving consists predominantly of experimental studies exploring the neurological and cognitive mechanisms. A limited number of studies have focused on individual differences. Of the few studies that have been conducted, most centre on neurological associates and cognitive ability/style. A tacit assumption is that all people experience insight, meaning some studies are afflicted with methodological issues; for example, that “insight problems” are solved only with an insight. Additionally, few studies have investigated insight using qualitative methods. Aims: The overall goal of this thesis was to investigate individual differences in insight problem solving. Using a mixed-methods approach, the first study aimed to investigate the subjective meaning, and contexts in which insights occur. The second study aimed to construct a brief scale which measures insight as a disposition (Dispositional Insight Scale). The third study aimed to uncover traits that may predict insight, including positive affect, flow, and mindfulness. The fourth study aimed to compare the personality traits of insightful people and analytical people, and to confirm whether those who are highly insightful have a higher predisposition to arousability than those lower in insightfulness. Method: A sample of 1,114 participants completed an online self-report questionnaire. The study included demographic questions, and open-ended questions regarding where and when insights occur, the personal meaning of their insights, and an additional opportunity to report other thoughts. The questionnaire also included closedended questions on insight, rated on a Likert scale, and scales assessing cognitive style, and the dispositions: affect, flow, mindfulness, the five-factor personality scale, and predisposition to arousability.
The Role of Government in MSMEs:The Empowerment of MSMEs During the Free Trade Era in Indonesia

As the era of globalisation has progressed, the free-trade paradigm – in which the role of government in every aspect of economic development is minimised, replaced by the power of the free market – has inevitably spread across countries throughout the world. Despite the positive outcomes that can be obtained from the idea of free liberalisation in achieving economic growth and opportunities, this paper will propose that governments must continue to have a strong role in their countries’ economies, particularly in developing countries such as Indonesia. This argument is justified on the basis of the threat that free trade poses to some informal sectors called micro and small and medium enterprises (MSMEs), which have commonly shown low levels of competitiveness in the global market. Thus their very survival heavily depends on government involvement. The Indonesian government has launched many policies to help SMEs become and remain more competitive; for example, the Technology for Regions Program (Iptekda), which combines state support and a market-based approach for MSMEs’ empowerment. This paper conducts a case study of the Iptekda program for the empowerment of MSMEs in Malang Raya. The research will address two issues: why government intervention is still required for MSE capacity-building; and how the program may help MSMEs improve their capacity and competitiveness. To answer these questions, this paper will apply a qualitative approach that uses in-depth interview with the owners of five MSMEs. The results reveal that MSMEs benefit from the program in terms of improved productivity, marketing and insights into MSMEs as an economic sector. The research limitation is that it consists solely of qualitative findings; the findings need to be combined with quantitative data for more-reliable results. Replication of this study using larger samples and a broader geographic base is suggested for promoting programs to empower MSMEs in Indonesia.
Molecular dynamics simulation of the liquid–vapor interface: The Lennard-Jones fluid

In this work we present new molecular dynamics simulation results for the liquid–vapor interface of the pure Lennard-Jones fluid. Our aims were further investigations on the simulation setup and the simulation parameters to obtain reliable data for the coexisting densities as well as for the surface tension. The influence of the cut-off distance to the interfacial properties is investigated and long-range corrections to both the dynamics and the surface tension are applied. It is found that the saturated liquid densities from the surface simulations agree with those from the NpT+test particle method within 1% for sufficiently large simulation boxes; the saturated vapor densities agree within 4%. In order to obtain reliable values for the surface tension, cut-off radii of at least 5 molecular diameters supplemented by a tail correction are required.