Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple sclerosis in Chile

So far as we know this series of 68 cases is one of the first clinical accounts of multiple sclerosis in South America. Average age of onset was 30.7 years and female:male ratio was 2:1. The most frequent initial symptom was motor impairment and less frequent was visual loss. Most affected site of involvement in established cases was the optic nerve. There were no familial cases. The severity of the disease in Chile proved to be the same as elsewhere. No characteristic clinical pattern peculiar to the region emerged.
Neuroprotective potential of escitalopram against behavioral, mitochondrial and oxidative dysfunction induced by 3-nitropropionic acid

Background Huntington’s disease (HD) is a neurodegenerative syndrome that leads to marked decline in cognitive functioning along with uncharacteristic body movements called chorea. There exists no therapeutic agent to address the disease.3-Nitropropionic acid (3-NP) which is a suicide inhibitor of succinate dehydrogenase and a well-known experimental model to study Huntington’s disease, causes substantial impairment in gait and memory through oxidative and neuronal damage. Purpose In the present study protective effect of escitalopram against 3-NP induced neurotoxicity was explored. Methods Adult female Wistar ratswere subjected to per oral administration of 2 different doses of escitalopram (10 and 20 mg/kg) for 12 days followed by intraperitoneal injection of 3-NP (20 mg/kg) on the last four days. Results Intraperitoneal injection of 3-NP lead to significant induction of HD like symptoms in rats such as impaired memory, reduced locomotor activity, hind limb impairment, decreased body weight, oxidative damage and mitochondrial dysfunction. Treatment with 2 different dose of escitalopram helped reverse the mitochondrial enzyme dysfunction along with reversal of behavioural and biochemical anomaly induced by 3-NP. Further, histopathological examination confirmed the neuroprotective potential of escitalopram against 3-NP induced pathological lesions. Conclusion The results obtained thus substantiate the claim that escitalopram might play an antioxidant and neuroprotective role against 3-NP induced alterations in rats and can prove to be a promising candidate for the management of HD.
Domain adduced state tying for cross-domain acoustic modelling

In situations when automatic speech recognition (ASR) systems are rapidly deployed for a new task, the availability of within-domain training data may be limited. In such cases one needs to build the ASR system from other, possibly out-of-domain databases. We refer to the process of building ASR systems for one task domain using data from other domains as cross-domain modelling or CDM. Conventional CDM-based systems perform poorly because the disparity between the triphonetic distributions of the training and test domains is not well accounted for. In this paper we describe two techniques to impose the acousticphonetic structure of the task domain on acoustic models built from out-of-domain data. The first technique, called Extrinsic CDM, combines decision tree structures obtained from a database close in domain to the task domain with acoustic models that are trained from a third less domain-relevant database. In the second technique, called Intrinsic CDM, the task domain data is used to impose the triphonetic distribution of the task domain on the decision trees built from an out-of-domain large database. Both these techniques result in acoustic models which perform better than conventional CDM models.
H5N1 Avian Influenza Virus Induces Apoptotic Cell Death in Mammalian Airway Epithelial Cells

ABSTRACT In recent years, the highly pathogenic avian influenza virus H5N1 has raised serious worldwide concern about an influenza pandemic; however, the biology of H5N1 pathogenesis is largely unknown. To elucidate the mechanism of H5N1 pathogenesis, we prepared primary airway epithelial cells from alveolar tissues from 1-year-old pigs and measured the growth kinetics of three avian H5 influenza viruses (A/Crow/Kyoto/53/2004 [H5N1], A/Duck/Hong Kong/342/78 [H5N2], and A/Duck/Hong Kong/820/80 [H5N3]), the resultant cytopathicity, and possible associated mechanisms. H5N1, but not the other H5 viruses, strongly induced cell death in porcine alveolar epithelial cells (pAEpC), although all three viruses induced similar degrees of cytopathicity in chicken embryonic fibroblasts. Intracellular viral growth and the production of progeny viruses were comparable in pAEpC infected with each H5 virus. In contrast, terminal deoxynucleotidyltransferase-mediated dUTP-biotin nick end labeling-positive cells were detected only in H5N1-infected pAEpC, and the activities of caspases 3, 8, and 9 were significantly elevated in pAEpC infected with H5N1, but not with H5N2 and H5N3. These results suggest that only H5N1 induces apoptosis in pAEpC. H5N1 cytopathicity was inhibited by adding the caspase inhibitor z-VAD-FMK; however, there were no significant differences in viral growth or release of progeny viruses. Further investigations using reverse genetics demonstrated that H5N1 hemagglutinin protein plays a critical role in inducing caspase-dependent apoptosis in infected pAEpC. H5N1-specific cytopathicity was also observed in human primary airway epithelial cells. Taken together, these data suggest that avian H5N1 influenza virus leads to substantial cell death in mammalian airway epithelial cells due to the induction of apoptosis.
Circadian Rhythms in Socializing Propensity

Using large-scale interaction data from a virtual world, we show that people’s propensity to socialize (forming new social connections) varies by hour of the day. We arrive at our results by longitudinally tracking people’s friend-adding activities in a virtual world. Specifically, we find that people are most likely to socialize during the evening, at approximately 8 p.m. and 12 a.m., and are least likely to do so in the morning, at approximately 8 a.m. Such patterns prevail on weekdays and weekends and are robust to variations in individual characteristics and geographical conditions.
Exercise-Induced Coronary Artery Vasodilation Is Not Impaired by Stent Placement

Background—Stenting has proved beneficial for treating threatened closure and reducing restenosis after balloon angioplasty. However, the implantation of a coronary metallic prosthesis has been related to impaired vasomotion distal to the stent as assessed by acetylcholine infusion. Thus, the purpose of the present study was to determine the vasomotion of stented coronary arteries and to assess its influence on the vasomotion of adjacent vessel segments during bicycle exercise. Methods and Results—Biplane quantitative coronary angiography was performed at rest and during bicycle exercise in 26 patients with coronary artery disease. Twelve patients had single vessel disease with stable angina pectoris (controls; group 1). Fourteen patients underwent coronary stenting for therapeutic reasons and were studied 10±3 months after the intervention (group 2). Minimal luminal area, stent area, and proximal and distal vessel areas were determined. In controls (group 1), vasoconstriction of the stenotic artery (− 29±4%;P <0.001) was observed during exercise, whereas the normal segment showed vasodilation (15±4%;P <0.05). In group 2, vasomotion of the stented segment was eliminated (0±1%), whereas the proximal and distal segments showed exercise-induced vasodilation (8±2% and 11±3%, respectively;P <0.005), which was not different from control segments (10±2%). Sublingual nitroglycerin was associated with maximal vasodilation of the proximal and distal vessel segments (30±8% and 38±13%, respectively;P <0.005). Conclusions—In contrast to the vasoconstriction of vessels in control patients, normal vasodilation of proximal and distal segments occurred during the physiological stress of exercise in patients with coronary stent placement. As expected, vasomotion was abolished in the stented region.
Association between abdominal obesity and fracture risk: a prospective study.

CONTEXT Higher body weight is associated with greater bone mineral density (BMD) and lower fracture risk. However, the relationship between abdominal fat mass (aFM) and fracture risk is unclear because of limited prospective data. The present study sought to examine the association between aFM, BMD, and fracture risk. METHODS The study was designed as a prospective investigation, in which a sample of 1126 participants (360 men and 766 women) aged 50 years or older had been continuously followed up for an average of 5 years. The mean age of participants was 71 years (range, 57-94 years). At baseline, BMD at the femoral neck and lumbar spine and aFM were measured by dual-energy X-ray absorptiometry. The incidence of low-trauma and nonpathological fractures was ascertained prospectively from X-ray reports. RESULTS During the follow-up period, 19 men and 107 women had sustained a fracture. In women, each 1-kg lower aFM was associated with a 50% higher risk of fracture (hazard ratio [HR], 1.50; 95% confidence interval [CI], 1.10-2.05) after adjustment for age, femoral neck BMD, falls, stature, physical activity, and prior fracture. Subgroup analysis by fracture type found that the association was mainly observed in clinical vertebral fracture (HR, 1.96; 95% CI, 1.22-3.13). In men, although there was no statistically significant association between aFM and fracture risk (HR, 1.15; 95% CI, 0.58-2.25), the strength of this finding is affected negatively by the low number of fractures. CONCLUSIONS Lower abdominal fat was significantly associated with an higher fracture risk in women.
Bandwidth Optimization in 802.15.4 Networks through Evolutionary Slot Assignment

Traditional Wireless Sensor Networks (WSNs) based on carrier sense methods for channel access suffer from reduced bandwidth utilization, increase energy consumptions and latency problems in networks with high traffic. In this work, a novel Evolutionary Slot Assignment (ESA) algorithm has been developed to increase the throughput of large wireless mesh networks with no centralized controller. In the presented scheme, the sensor nodes self-adapt to the traffic patterns of the network by selecting transmission slots using evolutionary learning methods. Each sensor node evolves an independent transmission schedule. Unlike traditional evolutionary methods, fitness evaluation of every node impacts fitness of every other sensor node in the network. The ESA algorithm has been simulated using Network Simulator-2 and compared with the IEEE 802.15. 4 CSMA-CA, a Static Slot Assignment (SSA) and a Random Slot Assignment schemes (RSA). Results show a remarkable improvement in the network throughput using the proposed ESA method as opposed to other compared methods.
Sperm competitiveness in frogs: slow and steady wins the race

When sperm compete to fertilize available ova, selection is expected to favour ejaculate traits that contribute to a male's fertilization success. While there is much evidence to show that selection favours increased numbers of sperm, only a handful of empirical studies have examined how variation in sperm form and function contributes to competitive fertilization success. Here, we examine selection acting on sperm form and function in the externally fertilizing myobatrachid frog, Crinia georgiana. Using in vitro fertilization techniques and controlling for variation in the number of sperm contributed by males in competitive situations, we show that males with a greater proportion of motile sperm, and motile sperm with slower swimming velocities, have an advantage when competing for fertilizations. Sperm morphology and the degree of genetic similarity between putative sires and the female had no influence on competitive fertilization success. These unusual patterns of selection might explain why frog sperm typically exhibit relatively slow swimming speeds and sustained longevity.
Evaluation of the Effect of Improper Segmentation on Word Spotting

Word spotting is an important recognition task in historical document analysis. In most cases methods are developed and evaluated assuming perfect word segmentations. In this paper we propose an experimental framework to quantify the effect of goodness of word segmentation has on the performance achieved by word spotting methods in identical unbiased conditions. The framework consists of generating systematic distortions on segmentation and retrieving the original queries from the distorted dataset. We apply the framework on the George Washington and Barcelona Marriage Dataset and on several established and state-of-the-art methods. The experiments allow for an estimate of the end-to-end performance of word spotting methods.
Brain mechanism of cognitive conflict in a guessing Chinese logogriph task

To investigate the neural substrates of cognitive conflict in high-level thought processing, we recorded event-related potentials while participants thought about the logogriph answers. We identified three states after the answers were provided: (1) the answer given was just what the participants initially guessed (No-aha answer). (2) Participants could understand the answer given correctly although they had not got the answer themselves (Aha answer). (3) Participants could not understand the correct answer offered (Uncomprehended answer). Results showed that, relative to the No-aha answer, the Aha and Uncomprehended answers elicited more negative event-related potential deflections between 250 and 400 ms. The dipole analysis localized the generator of the difference waves (Aha minus No-aha answer) to the anterior cingulate cortex. Thus, it might reflect the cognitive conflict center between familiar and new ways of processing the logogriphs.
Efficient K-Shot Learning with Regularized Deep Networks

Feature representations from pre-trained deep neural networks have been known to exhibit excellent generalization and utility across a variety of related tasks. Fine-tuning is by far the simplest and most widely used approach that seeks to exploit and adapt these feature representations to novel tasks with limited data. Despite the effectiveness of fine-tuning, it is often sub-optimal and requires very careful optimization to prevent severe over-fitting to small datasets. The problem of sub-optimality and overfitting, is due in part to the large number of parameters used in a typical deep convolutional neural network. To address these problems, we propose a simple yet effective regularization method for fine-tuning pre-trained deep networks for the task of k-shot learning. To prevent overfitting, our key strategy is to cluster the model parameters while ensuring intra-cluster similarity and inter-cluster diversity of the parameters, effectively regularizing the dimensionality of the parameter search space. In particular, we identify groups of neurons within each layer of a deep network that shares similar activation patterns. When the network is to be fine-tuned for a classification task using only k examples, we propagate a single gradient to all of the neuron parameters that belong to the same group. The grouping of neurons is non-trivial as neuron activations depend on the distribution of the input data. To efficiently search for optimal groupings conditioned on the input data, we propose a reinforcement learning search strategy using recurrent networks to learn the optimal group assignments for each network layer. Experimental results show that our method can be easily applied to several popular convolutional neural networks and improve upon other state-of-the-art fine-tuning based k-shot learning strategies by more than 10%.
Cooperation in neighbor discovery

Neighbor discovery is a fundamental task in wireless networks in order to find potential communication partners, discover services, and to efficiently access the wireless resource. In this paper we focus on the passive neighbor discovery in multi-channel environments. We present different discovery approaches with low computational complexity that utilize cooperation between devices by exchanging discovery results in order to improve the discovery process. Furthermore, we present an optimized discovery approach that uses multiple transceivers and evaluate the bounds on the performance under idealized conditions. We analyze the impact of different network parameters such as number of channels and number of neighbors on the discovery times of the developed approaches by using a simulative evaluation. By putting the discovery times achievable with the cooperative or “gossiping” approaches into perspective with the multi-transceiver results, we can quantify the value of cooperation in terms of numbers of transceivers.
Boundary-Based Measures for Evaluation of Color Image Segmentation

The present paper addresses the problem of image segmentation evaluation by comparing four different approaches. We are introducing a new method of salient object recognition with very good results relative to other already known object detection methods. We developed a simple evaluation framework in order to compare the results of our method with other segmentation methods. The experimental results offer a complete basis for parallel analysis with respect to the precision of our algorithm, rather than the individual efficiency.
Epigenetic Silencing of MicroRNA-34b/c Plays an Important Role in the Pathogenesis of Malignant Pleural Mesothelioma

Purpose: Malignant pleural mesothelioma (MPM) is an aggressive tumor with a dismal prognosis. Unlike other malignancies, TP53 mutations are rare in MPM. Recent studies have showed that altered expression of microRNA (miRNA) is observed in human malignant tumors. In this study, we investigated the alterations of miR-34s, a direct transcriptional target of TP53, and the role of miR-34s on the pathogenesis of MPM. Experimental Design: Aberrant methylation and expression of miR-34s were examined in MPM cell lines and tumors. miR-34b/c was transfected to MPM cells to estimate the protein expression, cell proliferation, invasion, and cell cycle. Results: Aberrant methylation was present in 2 (33.3%) of 6 MPM cell lines and 13 (27.7%) of 47 tumors in miR-34a and in all 6 MPM cell lines (100%) and 40 (85.1%) of 47 tumors in miR-34b/c. Expression of miR-34a and 34b/c in all methylated cell lines was reduced and restored with 5-aza-2′-deoxycytidine treatment. Because epigenetic silencing was the major event in miR-34b/c, we investigated the functional role of miR-34b/c in MPM. miR-34b/c–transfected MPM cells with physiologic miR-34b/c expression exhibited antiproliferation with G1 cell cycle arrest and suppression of migration, invasion, and motility. The forced overexpression of miR-34b/c, but not p53, showed a significant antitumor effect with the induction of apoptosis in MPM cells. Conclusions: We show that the epigenetic silencing of miR-34b/c by methylation is a crucial alteration and plays an important role in the tumorigenesis of MPM, suggesting potential therapeutic options for MPM. Clin Cancer Res; 17(15); 4965–74. ©2011 AACR.
Age-dependent intrathecal opioid escalation in chronic noncancer pain patients.

BACKGROUND Age and gender may exert important influences on opioid responsiveness and chronic pain. These effects have not been explored in the setting of chronic intrathecal (IT) opioid therapy. The objective of this study was to evaluate the effect of age and sex on IT opioid requirements during the first year after implantation of an intrathecal drug delivery system (IDDS) in chronic noncancer pain patients. DESIGN Retrospective study. METHODS AND PATIENT POPULATION: In this retrospective study, 135 chronic noncancer pain patients consecutively implanted with IDDSs for opioid therapy had their first year postimplant records examined. RESULTS Similar pain relief was achieved at 12 months after implant in both age groups. Relative to the dose at implant, younger patients had significantly higher rates of IT opioid dose escalation compared with older patients at 12 months (750 ± 450% in patients ≤50 years old vs 195 ± 120% in patients >50 years old, P < 0.001). Oral opioid consumption was significantly decreased at 12 months in the older patient population (140 ± 89 to 62 ± 35 mg/day at 12 months, P < 0.001, n = 85), while in the younger patient group, there was no change in oral opioid consumption (128 ± 81 mg/day to 105 ± 140 mg/day at 12 months, P = 0.65, n = 50). Gender-based analysis (55% males and 45% females) revealed similar reductions in pain scores during the first year postimplant. Oral opioid consumption was significantly higher in females (126 ± 138 mg) vs males (79 ± 89 mg) at 12 months postimplant; however, IT opioid dose escalation at 12 months postimplant was not statistically different between males and females. CONCLUSION IT opioid dose escalation occurs more steeply in the younger (under 50 years old) IDDS patient population without a concomitant significant decrease in oral consumption of opioids. Age-dependent changes may have important clinical implications on the effectiveness of IT opioid therapy in noncancer pain and its potential complications.
Knowledge refinement to debug and maintain a tablet formulation system

Knowledge refinement tools have commonly been applied to diagnostic applications. The paper considers the refinement of a design application. It explores the differences in knowledge content and problem solving steps for design rather than diagnosis systems, and investigates additional refinement operators. Although the problem solving task itself tends to be more complex, this in fact puts more constraints on the results of the problem solving and so the evidence on which the refinement is based can be more rich. Results are provided for a real tablet formulation system, TFS, and experience is reported for two types of refinement tasks: debugging to correct faulty problem solving of an early version of TFS; maintenance of TFS when the formulation task is altered by a change in company policy.
Logic Channels: a coordination approach to distributed programming

In this paper, we present a new coordination model and a small set of programming notations for distributed programming that can be integrated in very different programming languages (imperative, declarative or object oriented). Used together, they allow the development of distributed programs in a compositional way, by assembling different independent pieces of (possibly preexisting and heterogeneous) code. This approach is in the spirit of many other similar proposals such as Linda, PCN, CC++, etc., but it allows multiparadigm and multilingual integration and provides a powerful set of concurrent programming techniques, inherited from Concurrent Logic Languages (CLLs) that can be efficiently implemented in distributed systems. The coordination model is based on Logic Channels; these are an evolution of the concept of shared logic variable used in CLLs that, with the same expressive power, can be more efficiently implemented in distributed systems.
Using traffic prediction models for providing predictive traveller information

As a subsystem of an Intelligent Transportation System (ITS), an Advanced Traveller Information System (ATIS) disseminates real-time traffic information to travellers. To help travellers better make their route choice decisions, there is a strong need to predict traffic congestion and disseminate the predicted congestion information to travellers. This paper offers some insights and predictions on how ATIS information provision is becoming more pervasive due to recent advances in telecommunication systems. The paper also discusses how ATIS systems will likely evolve based on the experiences of Information Service Providers (ISP) and ATIS modelling specialists. Then, it reviews four types of prediction models: 1) simulation models; 2) dynamic traffic assignment (DTA) models; 3) statistical models; and 4) heuristic models. The functional requirements and capabilities of the four types of prediction models are discussed and summarised. Furthermore, a comprehensive prediction procedure is presented, which combines the four types of prediction models.