Miracle-dz/UniFAR-FTUs huggingface dataset:
The Goodpasture antigen is expressed in the human thymus.

BACKGROUND Autoimmunity to kidney antigens causes membranous nephropathy and Goodpasture's disease and very likely is pivotal in many other glomerular diseases. We investigated the potential for central tolerance to the best-characterized kidney autoantigen, the NC1 domain of the alpha3 chain of type IV collagen [alpha3(IV)NC1], which is the target of autoimmune attack in Goodpasture's disease. METHODS Indirect immunofluorescence on human thymus and polymerase chain reaction (PCR) and Southern blot analysis of cDNA reverse transcribed from RNA extracted from human thymus and kidney. RESULTS Indirect immunofluorescence on human thymus demonstrated the presence of alpha3(IV)NC1 in all six thymus samples examined. The homologous collagen IV chain, alpha5(IV)NC1, also was detected with a similar intra-thymic distribution. Strikingly, thymic alpha3 and alpha5 localized around and within Hassall's corpuscles in the thymic medulla, which are structures implicated in T cell apoptosis and possibly negative selection. In contrast, alpha1(IV)NC1 localized to the basement membranes of interlobular septa and blood vessels, as is typical of collagen IV chains situated outside the thymus. Reverse transcription-polymerase chain reaction (RT-PCR) confirmed the presence of mRNA encoding alpha3(IV)NC1 and alpha5(IV)NC1 in thymic tissue establishing that the antigens were likely to have been synthesized locally. CONCLUSIONS The results demonstrate that alpha3(IV)NC1 is expressed in the human thymus, and therefore should be available for induction of alpha3(IV)NC1-specific tolerance. This observation has the important implication that patients' alpha3(IV)NC1-specific, autoreactive T cells are more likely to recognize cryptic epitopes that are not adequately presented by thymic antigen-presenting cells (APC) than the major antigen-derived epitopes generally identified by conventional approaches.
Growth expectations for side activities in rural areas

– The purpose of this article is to examine growth expectations and factors influencing growth of side activities in rural areas. , – Data were collected in the rural areas of 36 Dutch municipalities by means of a detailed survey. This resulted in 260 response cases. The analysis consists of a descriptive account of respondents' intentions to expand a side activity and a logistic regression explaining growth expectations of these activities. , – The main conclusion is that although growth is not expected in a large number of side activities, there is a group of owners who clearly aspire to expand the scale of their activities. Their personal aspirations and aspirations for economic well‐being are the most common motivations. These characteristics also have a bearing on the future growth of side activities and consequently their impact on rural development. , – Since this article examines growth expectations and not actual growth, the findings cannot be interpreted directly in terms of economic impact on rural development. , – Scholars and policy makers have paid little attention to side activities in rural areas and specifically to their growth potential. This article enhances our understanding of the growth expectations of those who carry out side activities and shows the potential of such activities in diversifying and revitalizing rural areas.
Effects of larval crowding on development time, survival and weight at metamorphosis in Aedes aegypti (Diptera: Culicidae)

The effects of larval crowding on survival, weight at metamorphosis and development time were assessed in the dengue mosquito, Aedes aegypti L. , under a controlled environment. Larval cohorts were bred at 7 different densities (4, 8, 16, 32, 64, 128 and 256 larvae / 175 ml pot), while keeping constant water volume and food amount and quality, under controlled temperature and photoperiod. Natural detritus, mainly leaves, obtained from containers naturally colonized by A. aegypti, were used as a source of nutrients for larvae. Development time, mortality, mass at metamorphosis, and total biomass were recorded for each density. Development time ranged from 4 to 23 days in males, and from 5 to 24 in females, whereby larvae took longer to develop at 64 (females) and 128 (males) larvae per recipient. At high densities
Effects of BMI and abdominal volume on the accuracy of step count obtained from a tri-axial accelerometer

Accelerometers are widely accepted as practical wearable devices capable of measuring and assessing physical activity. These devices may, however, be subject to errors which could impact on their ability to acquire an accurate step count. A limited number of studies have examined the effects of body mass index (BMI) on the accuracy of accelerometers functioning as step counters. It has been suggested that BMI may not be the best indicator of adiposity. The aim of the present study was to assess the effects of BMI and abdominal volume on the accuracy of a step count obtained from a tri-axial accelerometer. Accelerometers were placed directly onto the skin at the chest, waist and lower back of 12 participants. Participants then walked on a motorized treadmill at 0.89m/s and 1.34m/s. Analysis of the results indicated that BMI and abdominal volume did not affect the accuracy of the step count obtained from accelerometers under any conditions. Walking speed, however, had a significant effect with step count accuracy decreasing at the slower speed.
Probabilistic kernel regression models

We introduce a class of exible conditional probability models and techniques for classi cation regression problems Many existing methods such as generalized linear models and support vector machines are subsumed under this class The exibility of this class of techniques comes from the use of kernel functions as in support vector machines and the generality from dual formulations of stan dard regression models
A limitation of the Cognitive Reflection Test: familiarity

The Cognitive Reflection Test (CRT; Frederick, 2005) is a frequently used measure of cognitive vs. intuitive reflection. It is also a frequently found entertaining ‘test’ on the Internet. In a large age-stratified community-based sample (N = 2,272), we analyzed the impact of having already performed the CRT or any similar task in the past. Indeed, we found that 44% of participants had experiences with these tasks, which was reflected in higher CRT scores (Cohen’s d = 0.41). Furthermore, experienced participants were different from naïve participants in regard to their socio-demographics (younger, higher educated, fewer siblings, more likely single or in a relationship than married, having no children). The best predictors of a high CRT score were the highest educational qualification (4.62% explained variance) followed by the experience with the task (3.06%). Therefore, we suggest using more recent multi-item CRTs with newer items and a more elaborated test construction.
TorontoCity: Seeing the World with a Million Eyes

In this paper we introduce the TorontoCity benchmark, which covers the full greater Toronto area (GTA) with 712.5km2 of land, 8439km of road and around 400, 000 buildings. Our benchmark provides different perspectives of the world captured from airplanes, drones and cars driving around the city. Manually labeling such a large scale dataset is infeasible. Instead, we propose to utilize different sources of high-precision maps to create our ground truth. Towards this goal, we develop algorithms that allow us to align all data sources with the maps while requiring minimal human supervision. We have designed a wide variety of tasks including building height estimation (reconstruction), road centerline and curb extraction, building instance segmentation, building contour extraction (reorganization), semantic labeling and scene type classification (recognition). Our pilot study shows that most of these tasks are still difficult for modern convolutional neural networks.
Event-Weighted Tests for Detecting Periodicity in Photon Arrival Times

This paper treats the problem of detecting periodicity in a sequence of photon arrival times, which occurs, for example, in attempting to detect gamma-ray pulsars. A particular focus is on how auxiliary information, typically, source intensity, background intensity, and incident angles and energies associated with each photon arrival, should be used to maximize the detection power. We construct a class of likelihood-based tests, score tests, which give rise to event weighting in a principled and natural way, and derive expressions quantifying the power of the tests. These results can be used to compare the efficacies of different weight functions, including cuts in energy and incident angle. The test is targeted toward a template for the periodic light curve, and we quantify how deviation from that template affects the power of detection.
Extraskeletal Myxoid Chondrosarcoma of the Head and Neck: A Case Report

Extraskeletal myxoid chondrosarcomas are rare, soft tissue tumors with a characteristic histologic appearance. The majority of these tumors occur in the extremities. To our knowledge, this is the first reported case in the head and neck. As a group, extraskeletal myxoid chondrosarcomas behave in a less aggressive manner than do other forms of chondrosarcomas, but their clinical course can vary considerably. Surgery is the treatment of choice, and adjuvant radiotherapy or chemotherapy should be considered for cases that display a more cellular pattern and a less conspicuous myxoid matrix.
Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data.
Parental smoking, maternal alcohol, coffee and tea consumption during pregnancy and childhood malignant central nervous system tumours: the ESCALE study (SFCE)*

Parental smoking and maternal alcohol and caffeinated beverage consumption are prevalent exposures which may play a role, either directly or through their influence on metabolism, in the aetiology of childhood malignant central nervous system (CNS) tumours. The hypothesis was investigated in the Epidemiological Study on childhood Cancer and Leukemia ESCALE study, a national population-based case–control study carried out in France in 2003–2004. The study included 209 incident cases of CNS tumours and 1681 population-based controls, frequency matched with the cases by age and sex. The data were collected through a standardized telephone interview of the biological mothers. No association between maternal smoking during pregnancy and CNS tumours [odds ratio (OR): 1.1 (0.8–1.6)] was observed. Paternal smoking during the year before birth was associated with CNS tumours (P for trend=0.04), particularly astrocytomas [OR: 3.1 (1.3–7.6)]. Maternal alcohol consumption during pregnancy was not associated with CNS tumours. Associations between ependymomas and the highest consumption of coffee [OR: 2.7 (0.9–8.1)] and tea [OR: 2.5 (1.1–5.9)] were observed. A strong association between CNS tumours and the highest maternal consumption of both coffee and tea during pregnancy was observed [OR: 4.4 (1.5–13)]. The results constitute additional evidence for a role of paternal smoking and suggest that maternal coffee and tea consumption during pregnancy may also increase the risk of CNS tumours. The study does not suggest an increased risk of CNS tumours related to alcohol consumption during pregnancy.
Continual Learning with Deep Generative Replay

Attempts to train a comprehensive artificial intelligence capable of solving multiple tasks have been impeded by a chronic problem called catastrophic forgetting. Although simply replaying all previous data alleviates the problem, it requires large memory and even worse, often infeasible in real world applications where the access to past data is limited. Inspired by the generative nature of hippocampus as a short-term memory system in primate brain, we propose the Deep Generative Replay, a novel framework with a cooperative dual model architecture consisting of a deep generative model ("generator") and a task solving model ("solver"). With only these two models, training data for previous tasks can easily be sampled and interleaved with those for a new task. We test our methods in several sequential learning settings involving image classification tasks.
A fast and efficient computer aided diagnostic system to detect tumor from brain magnetic resonance imaging

In this work, a simple and efficient CAD (computer‐aided diagnostic) system is proposed for tumor detection from brain magnetic resonance imaging (MRI). Poor contrast MR images are preprocessed by using morphological operations and DSR (dynamic stochastic resonance) technique. The appropriate segmentation of MR images plays an important role in yielding the correct detection of tumor. On examination of three views of brain MRI, it was visible that the region of interest (ROI) lies in the middle and its size ranges from 240 × 240 mm2 to 280 × 280 mm2. The proposed system makes effective use of this information and identifies four blocks from the desired ROI through block‐based segmentation. Texture and shape features are extracted for each block of all MRIs in the training set. The range of these feature values defines the threshold to distinguish tumorous and nontumorous MRIs. Features of each block of an MRI view are checked against the threshold. For a particular feature, if a block is found tumorous in a view, then the other views are also checked for the presence of tumor. If corresponding blocks in all the views are found to be tumorous, then the MRI is classified as tumorous. This selective block processing technique improves computational efficiency of the system. The proposed technique is well adaptive and fast, and it is compared with well‐known existing techniques, like k‐means, fuzzy c‐means, etc. The performance analysis based on accuracy and precision parameters emphasizes the effectiveness and efficiency of the proposed work.
The impact of climate, CO2, nitrogen deposition and land use change on simulated contemporary global river flow

We investigated how climate, rising atmospheric CO2 concentration, increasing anthropogenic nitrogen deposition and land use change influenced continental river flow over the period 1948–2004 using the Community Land Model version 4 (CLM4) with coupled river transfer model (RTM), a global river routing scheme. The model results indicate that the global mean river flow shows significant decreasing trend and climate forcing likely functions as the dominant controller of the downward trend during the study period. Nitrogen deposition and land use change account for about 5% and 2.5% of the decrease in simulated global scale river flow, respectively, while atmospheric CO2 accounts for an upward trend. However, the relative role of each driving factor is heterogeneous across regions in our simulations. The trend in river flow for the Amazon River basin is primarily explained by CO2, while land use change accounts for 27.4% of the downward trend in river flow for the Yangtze rive basin. Our simulations suggest that to better understand the trends of river flow, it is not only necessary to take into account the climate, but also to consider atmospheric composition, carbon‐nitrogen interaction and land use change, particularly for regional scales.
High tumour contamination of leukaphereses in patients with small cell carcinoma of the lung: a comparison of immunocytochemistry and RT-PCR

In small-cell lung carcinoma (SCLC) tumour cell contamination of leukaphereses is unknown. The present study was performed to define appropriate markers for reverse transcriptase polymerase chain reaction (RT-PCR), then to assess the contamination rate of leukaphereses and corresponding bone marrow samples. Immunocytochemistry (ICC) and RT-PCR methods were also compared. Among the 33 patients included, analyses were performed in 16 who had multiple leukaphereses and 17 who had only bone marrow. Leukapheresis products and bone marrow were analysed by ICC using several specific monoclonal antibodies against neural-cell adhesion molecule (N-CAM), epithelial glycoprotein (EGP-40) and cytokeratins (CK). Samples were also analyzed by RT-PCR for expression for N-CAM, synaptophysin, neuron-specific enolase, chromogranin, cytokeratin-18/-19, CEA, EGP-40, apomucin type 1 (MUC-1) and human endothelial cell-specific molecule (ESM-1). Using ICC staining, contaminating tumour cells were detected in 34% of leukaphereses (27% in patients with limited disease and 43% in those with extensive disease). N-CAM was the most reliable marker for detection of contamination. For RT-PCR, CK-19 and CEA were the only appropriate markers. Positive signal rate in leukaphereses increased to 78% (89% for patients with limited disease and 67% for extensive disease). In bone marrow, both techniques were in agreement whereas in leukaphereses, RT-PCR was better than ICC. A high rate of tumour cell contamination was demonstrated not only in bone marrow but also in leukaphereses from SCLC patients. The most appropriate technique was RT-PCR mainly in patients with limited disease. © 2001 Cancer Research Campaign http://www.bjcancer. com
GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery

Advances in remote sensing technologies have made it possible to use high-resolution visual data for weather observation and forecasting tasks. We propose the use of multi-layer neural networks for understanding complex atmospheric dynamics based on multichannel satellite images. The capability of our model was evaluated by using a linear regression task for single typhoon coordinates prediction. A specific combination of models and different activation policies enabled us to obtain an interesting prediction result in the northeastern hemisphere (ENH).
Randomized Trial of Apneic Oxygenation during Endotracheal Intubation of the Critically Ill.

RATIONALE Hypoxemia is common during endotracheal intubation of critically ill patients and may predispose to cardiac arrest and death. Administration of supplemental oxygen during laryngoscopy (apneic oxygenation) may prevent hypoxemia. OBJECTIVES To determine if apneic oxygenation increases the lowest arterial oxygen saturation experienced by patients undergoing endotracheal intubation in the intensive care unit. METHODS This was a randomized, open-label, pragmatic trial in which 150 adults undergoing endotracheal intubation in a medical intensive care unit were randomized to receive 15 L/min of 100% oxygen via high-flow nasal cannula during laryngoscopy (apneic oxygenation) or no supplemental oxygen during laryngoscopy (usual care). The primary outcome was lowest arterial oxygen saturation between induction and 2 minutes after completion of endotracheal intubation. MEASUREMENTS AND MAIN RESULTS Median lowest arterial oxygen saturation was 92% with apneic oxygenation versus 90% with usual care (95% confidence interval for the difference, -1.6 to 7.4%; P = 0.16). There was no difference between apneic oxygenation and usual care in incidence of oxygen saturation less than 90% (44.7 vs. 47.2%; P = 0.87), oxygen saturation less than 80% (15.8 vs. 25.0%; P = 0.22), or decrease in oxygen saturation greater than 3% (53.9 vs. 55.6%; P = 0.87). Duration of mechanical ventilation, intensive care unit length of stay, and in-hospital mortality were similar between study groups. CONCLUSIONS Apneic oxygenation does not seem to increase lowest arterial oxygen saturation during endotracheal intubation of critically ill patients compared with usual care. These findings do not support routine use of apneic oxygenation during endotracheal intubation of critically ill adults. Clinical trial registered with www.clinicaltrials. gov (NCT 02051816).
The Recognition of N-Glycans by the Lectin ArtinM Mediates Cell Death of a Human Myeloid Leukemia Cell Line

ArtinM, a d-mannose-binding lectin from Artocarpus heterophyllus (jackfruit), interacts with N-glycosylated receptors on the surface of several cells of hematopoietic origin, triggering cell migration, degranulation, and cytokine release. Because malignant transformation is often associated with altered expression of cell surface glycans, we evaluated the interaction of ArtinM with human myelocytic leukemia cells and investigated cellular responses to lectin binding. The intensity of ArtinM binding varied across 3 leukemia cell lines: NB4>K562>U937. The binding, which was directly related to cell growth suppression, was inhibited in the presence of Manα1-3(Manα1-6)Manβ1, and was reverted in underglycosylated NB4 cells. ArtinM interaction with NB4 cells induced cell death (IC50 = 10 µg/mL), as indicated by cell surface exposure of phosphatidylserine and disruption of mitochondrial membrane potential unassociated with caspase activation or DNA fragmentation. Moreover, ArtinM treatment of NB4 cells strongly induced reactive oxygen species generation and autophagy, as indicated by the detection of acidic vesicular organelles in the treated cells. NB4 cell death was attributed to ArtinM recognition of the trimannosyl core of N-glycans containing a ß1,6-GlcNAc branch linked to α1,6-mannose. This modification correlated with higher levels of N-acetylglucosaminyltransferase V transcripts in NB4 cells than in K562 or U937 cells. Our results provide new insights into the potential of N-glycans containing a β1,6-GlcNAc branch linked to α1,6-mannose as a novel target for anti-leukemia treatment.