Miracle-dz/UniFAR-FTUs huggingface dataset:
Results of surgical resection for progression of brain metastases previously treated by gamma knife radiosurgery.

OBJECTIVE To determine treatment outcome after surgical resection for progressive brain metastases after gamma knife radiosurgery (GKR) and to explore the role of dynamic contrast agent-enhanced perfusion magnetic resonance imaging (MRI) and proton spectroscopic MRI studies (MRS/P) in predicting pathological findings. METHODS Between 1997 and 2002, 32 patients underwent surgical resection for suspected progression of brain metastases from a cohort of 245 patients with brain metastases treated with GKR. Postradiosurgery MRI surveillance was performed at 6 and 12 weeks, and then every 12 weeks after GKR. In some cases, additional MRI scanning with spectroscopy or perfusion (MRS/P) was used to aid differentiation of radiation change from tumor progression. The decision to perform neurosurgical resection was based on MRI or clinical evidence of lesion progression among patients with a Karnofsky performance score of 60 or more and absent or stable systemic disease. RESULTS Thirteen percent (32 out of 245) of patients and 6% (38 out of 611) of lesions required surgical resection after GKR. The median time from GKR to surgical resection was 8.6 months (range, 1.7-27.1 mo). The 6-, 12-, and 24-month actuarial survival from time of GKR was 97, 78, and 47% for the resected patients and 65, 40, and 19% for the nonresected patients (P < 0.0001). The two-year survival rate of patients requiring two resections after GKR was 100% compared with 39% for patients undergoing one resection (P = 0.02). The median survival of resected patients was 27.2 months (range, 7.0-72.5 mo) from the diagnosis of brain metastases, 19.9 months (range, 5.0-60.7 mo) from GKR, and 8.9 months (range, 0.2-53.1 mo) from surgical resection. Tumor was found in 90% of resected specimens and necrosis alone in 10%. MRS/P studies were performed in 15 resected patients. Overall, MRS/P predicted tumor in 11 lesions, confirmed pathologically in nine lesions, and necrosis alone was found in two. The MRS/P predicted necrosis alone in three, whereas pathology revealed viable tumor in two and necrosis in one lesion. CONCLUSION Surgical intervention of progressive brain metastases after GKR in selected patients leads to a meaningful improvement in survival rates. Further studies are necessary to determine the role of MRS/P in the postradiosurgery surveillance of brain metastases.
Time is Brain(stem) in Basilar Artery Occlusion

Background and Purpose— The frequent use of a longer time window for recanalization therapy in patients with basilar artery occlusion (BAO) in daily practice is not supported by any scientific evidence. We investigated the relationship between time to recanalization therapy and functional outcome in BAO with data from the Basilar Artery International Cooperation Study (BASICS). Methods— BASICS is a prospective multicenter registry of patients (n=619) with radiologically confirmed BAO. We analyzed patients receiving intravenous thrombolysis or intra-arterial treatment. Patients were divided into 4 groups based on the interval between estimated time of BAO and start of recanalization therapy: ⩽3 hours (n=134), >3 to ⩽6 hours (n=151), >6 to ⩽9 hours (n=56), and >9 hours (n=68). Primary outcome measure was poor functional outcome (modified Rankin scale score 4–6) after 1 month. We calculated adjusted risk ratios with 95% CIs using Poisson regression analyses with the ⩽3 hours group as the reference group. Results— Patients had an increased risk of poor functional outcome as time to recanalization therapy became longer (⩽3 hours: 62%; >3 to ⩽6 hours: 67% [adjusted risk ratio, 1.06; 0.91–1.25]; >6 to ⩽9 hours: 77% [adjusted risk ratio, 1.26; 1.06–1.51]; >9 hours: 85% [adjusted risk ratio, 1.47; 1.26–1.72]). Conclusions— Early recanalization therapy in patients with BAO is associated with a more favorable outcome with a significant increased chance of a poor outcome when recanalization therapy is started >6 hours after estimated time of BAO.
Novel Translational Control through an Iron-Responsive Element by Interaction of Multifunctional Protein YB-1 and IRP2

ABSTRACT The eukaryotic Y-box-binding protein YB-1 functions in various biological processes, including DNA repair, cell proliferation, and transcriptional and translational controls. To gain further insight into how human YB-1 plays its role in pleiotropic functions, we here used two-hybrid screenings to identify partners of this protein; the results showed that YB-1 itself, iron-regulatory protein 2 (IRP2), and five ribosomal proteins each served as partners to YB-1. We then examined the biological effect of the interaction of YB-1 and IRP2 on translational regulation. Both in vitro binding and coimmunoprecipitation assays showed the direct interaction of YB-1 and IRP2 in the presence of a high concentration of iron. RNA gel shift assays showed that YB-1 reduced the formation of the IRP2-mRNA complex when the iron-responsive element of the ferritin mRNA 5′ untranslated region (UTR) was used as a probe. By using an in vitro translation assay using luciferase mRNA ligated to the ferritin mRNA 5′UTR as a reporter construct, we showed that both YB-1 and IRP2 inhibited the translation of the mRNA. However, coadministration of YB-1 and IRP2 proteins abrogated the inhibition of protein synthesis by each protein. An In vivo coimmunoprecipitation assay showed that IRP2 bound to YB-1 in the presence of iron and a proteasome inhibitor. The direct interaction of YB-1 and IRP2 provides the first evidence of the involvement of YB-1 in the translational regulation of an iron-related protein.
Control of cell division in Streptococcus pneumoniae by the conserved Ser/Thr protein kinase StkP

How the human pathogen Streptococcus pneumoniae coordinates cell-wall synthesis during growth and division to achieve its characteristic oval shape is poorly understood. The conserved eukaryotic-type Ser/Thr kinase of S. pneumoniae, StkP, previously was reported to phosphorylate the cell-division protein DivIVA. Consistent with a role in cell division, GFP-StkP and its cognate phosphatase, GFP-PhpP, both localize to the division site. StkP localization depends on its penicillin-binding protein and Ser/Thr-associated domains that likely sense uncross-linked peptidoglycan, because StkP and PhpP delocalize in the presence of antibiotics that target the latest stages of cell-wall biosynthesis and in cells that have stopped dividing. Time-lapse microscopy shows that StkP displays an intermediate timing of recruitment to midcell: StkP arrives shortly after FtsA but before DivIVA. Furthermore, StkP remains at midcell longer than FtsA, until division is complete. Cells mutated for stkP are perturbed in cell-wall synthesis and display elongated morphologies with multiple, often unconstricted, FtsA and DivIVA rings. The data show that StkP plays an important role in regulating cell-wall synthesis and controls correct septum progression and closure. Overall, our results indicate that StkP signals information about the cell-wall status to key cell-division proteins and in this way acts as a regulator of cell division.
Forward Genetic Analysis of Visual Behavior in Zebrafish

The visual system converts the distribution and wavelengths of photons entering the eye into patterns of neuronal activity, which then drive motor and endocrine behavioral responses. The gene products important for visual processing by a living and behaving vertebrate animal have not been identified in an unbiased fashion. Likewise, the genes that affect development of the nervous system to shape visual function later in life are largely unknown. Here we have set out to close this gap in our understanding by using a forward genetic approach in zebrafish. Moving stimuli evoke two innate reflexes in zebrafish larvae, the optomotor and the optokinetic response, providing two rapid and quantitative tests to assess visual function in wild-type (WT) and mutant animals. These behavioral assays were used in a high-throughput screen, encompassing over half a million fish. In almost 2,000 F2 families mutagenized with ethylnitrosourea, we discovered 53 recessive mutations in 41 genes. These new mutations have generated a broad spectrum of phenotypes, which vary in specificity and severity, but can be placed into only a handful of classes. Developmental phenotypes include complete absence or abnormal morphogenesis of photoreceptors, and deficits in ganglion cell differentiation or axon targeting. Other mutations evidently leave neuronal circuits intact, but disrupt phototransduction, light adaptation, or behavior-specific responses. Almost all of the mutants are morphologically indistinguishable from WT, and many survive to adulthood. Genetic linkage mapping and initial molecular analyses show that our approach was effective in identifying genes with functions specific to the visual system. This collection of zebrafish behavioral mutants provides a novel resource for the study of normal vision and its genetic disorders.
Using posterior-based features in template matching for speech recognition

Given the availability of large speech corpora, as well as the increasing of memory and computational resources, the use of template matching approaches for automatic speech recognition (ASR) have recently attracted new attention. In such template-based approaches, speech is typically represented in terms of acoustic vector sequences, using spectral-based features such as MFCC of PLP, and local distances are usually based on Euclidean or Mahalanobis distances. In the present paper, we further investigate template-based ASR and show (on a continuous digit recognition task) that the use of posterior-based features significantly improves the standard template-based approaches, yielding to systems that are very competitive to state-of-the-art HMMs, even when using a very limited number (e.g., 10) of reference templates. Since those posteriors-based features can also be interpreted as a probability distribution, we also show that using Kullback-Leibler (KL) divergence as a local distance further improves the performance of the template-based approach, now beating state-of-the-art of more complex posterior-based HMMs systems (usually referred to as "Tandem").
A parallel finite element surface fitting algorithm for data mining

A major task in data mining is to develop automatic techniques to process and to detect patterns in very large data sets. Multivariate regression techniques form the core of many data mining applications. A common assumption is that the multivariate data is well approximated by an additive model involving only first and second order interaction terms. In this case high-dimensional nonparametric regression is reduced to the determination of a couple set of first and second order interaction terms, that is the determination of a coupled set of curves and surfaces. Thin plate splines provide a very good method to determine an approximating surface. Obtaining standard thin plate splines requires the solution of a dense linear system of equations of order n, where n is the number of observations. For data mining applications the number of observations is often in the millions, so standard thin plate splines may not be practical. We have developed a finite element approximation of a spline that can handle data sizes with millions of records. The resolution of the finite element method can independently be chosen from the number of observations. The observation data can be read from a secondary storage once, and does not need to be stored in memory. In this paper, we discuss the parallel implementation of this method in an MPI environment.
Video magnification in presence of large motions

Video magnification reveals subtle variations that would be otherwise invisible to the naked eye. Current techniques require all motion in the video to be very small, which is unfortunately not always the case. Tiny yet meaningful motions are often combined with larger motions, such as the small vibrations of a gate as it rotates, or the microsaccades in a moving eye. We present a layer-based video magnification approach that can amplify small motions within large ones. An examined region/layer is temporally aligned and subtle variations are magnified. Matting is used to magnify only region of interest while maintaining integrity of nearby sites. Results show handling larger motions, larger amplification factors and significant reduction in artifacts over state of the art.
Small Ancestry Informative Marker panels for complete classification between the original four HapMap populations

A protocol for the identification of Ancestry Informative Markers (AIMs) from genome-wide Single Nucleotide Polymorphism (SNP) data is proposed. The protocol consists of three main steps: identification of potential positive selection regions via F(ST) extremity measurement, SNP screening via two-stage attribute selection and classification model construction using a Naïve Bayes classifier. The two-stage attribute selection is composed of a newly developed round robin Symmetrical Uncertainty (SU) ranking technique and a wrapper embedded with a Naïve Bayes classifier. The protocol has been applied to the HapMap Phase II data. Two AIM panels, which consist of 10 and 16 SNPs that lead to complete classification between CEU, CHB, JPT and YRI populations, are identified. Moreover, the panels are at least four times smaller than those reported in previous studies. The results suggest that the protocol could be useful in a scenario involving a larger number of populations.
A Web-Based Framework for User-Centred Evaluation of End-User Experience in Adaptive and Personalized E-Learning Systems

The evaluation of interactive adaptive and personalised systems has long been acknowledged as a difficult, complicated and very demanding Endeavour due to the complex nature of these systems. This paper describes a web-based framework for the evaluation of end-user experience in adaptive and personalised e-Learning systems. The benefits of the framework include: i) the provision of an interactive reference and recommendation tool to encourage the evaluation of systems that fulfil certain methodological requirements, ii) the collaborative nature of the framework facilitates the sharing of information among researchers from the information technology, adaptive hypermedia, information retrieval and e-Learning communities, iii) the identification of pitfalls in the evaluation planning process as well as in data analysis, and iv) the translation of presented information into users language of choice. This paper also presents a review of User-Centred Evaluation approaches, methodologies and techniques adopted by current systems and frameworks. The results of this review are analysed. From these results, an architectural design for the framework was specified.
Geometric containers for efficient shortest-path computation

A fundamental approach in finding efficiently best routes or optimal itineraries in traffic information systems is to reduce the search space (part of graph visited) of the most commonly used shortest path routine (Dijkstra's algorithm) on a suitably defined graph. We investigate reduction of the search space while simultaneously retaining data structures, created during a preprocessing phase, of size linear (i.e., optimal) to the size of the graph. We show that the search space of Dijkstra's algorithm can be significantly reduced by extracting geometric information from a given layout of the graph and by encapsulating precomputed shortest-path information in resulted geometric objects (containers). We present an extensive experimental study comparing the impact of different types of geometric containers using test data from real-world traffic networks. We also present new algorithms as well as an empirical study for the dynamic case of this problem, where edge weights are subject to change and the geometric containers have to be updated and show that our new methods are two to three times faster than recomputing everything from scratch. Finally, in an appendix, we discuss the software framework that we developed to realize the implementations of all of our variants of Dijkstra's algorithm. Such a framework is not trivial to achieve as our goal was to maintain a common code base that is, at the same time, small, efficient, and flexible, as we wanted to enhance and combine several variants in any possible way.
- 1-eNormal Estimation in 3 D Discrete Spac

hree-dimensional voxel-based objects are inherently discrete and do not l f maintain any notion of a continuous surface or normal values, which are crucia or the simulation of light behavior. Thus in volume rendering, the normal s vector of the displayed surfaces must be estimated prior to rendering. We urvey several methods for normal estimation and analyze their performance. s One unique method, the context sensitive approach, employs segmentation and egment-bounded operators that are based on object and slope discontinuities in c o order to achieve high fidelity normal estimation for rendering volumetri bjects.
Antiphishing Model with URL & Image based Webpage Matching

is a form of online identity theft associated with both social engineering and technical subterfuge and a major threat to information security and personal privacy. Many anti- phishing solutions, such as content analysis and HTML code analysis, rely on this property to detect fake web pages. However, these techniques failed, as phishers are now composing phishing pages with non-analyzable elements, such as images and flash objects. This paper proposes a new phishing detection scheme based on an URL domain identity & webpage image matching. At first, it identifies the similar authorized URL, using divide rule approach and approximate string matching algorithm. For this similar URL and input URL, the IP addresses will be identified. If their IP addresses doesn't match with each other, then it could be phishing URL and phase-I phishing report will be generated. Then, this suspected URL's webpage snapshot will be treated as an image during phase-II. In phase-II, keypoints will be detected and their features will be extracted. These features will be extracted using CCH descriptor. Then, match this suspected image features with the features of authorized webpage. If this matching crosses threshold value, then this webpage is phishing one. At last, final phishing report will be generated. As the combined approach of URL domain identity and webpage image matching used, it performs better than other existing tools.
Self-Assessment in In-Service Distance Teacher Training

This paper is based on my experience as part of a team that designed and implemented a distance-training course for English teachers in Romania. It begins with an overview of the training program. It outlines the importance of distance training for teachers in the Romanian educational system. Later, it focuses on the importance of developing self-assessment and self-evaluation skills as key elements of distance learning. In this paper, I propose some self-assessment techniques and activities based on theories of adult learning and on the specific features of the distance-training course I helped to develop. The final section of this paper evaluates the successes, failures and effectiveness of self-assessment techniques used, and I share the lessons I learned as a distance trainer. ERIC/CLL
Von der Neuroinflammation zur Neurodegeneration

Zusammenfassung Während die Multiple Sklerose (MS) über mehr als 100 Jahre als Prototyp einer entzündlich-demyelinisierenden Erkrankung des Zentralnervensystems galt, wurde in den letzten Jahren deutlich, dass auch neurodegenerative Prozesse eine ganz entscheidende Rolle in der MS-Pathogenese spielen. Moderne histopathologische und bildgebende Verfahren zeigen schon frühzeitig im Krankheitsverlauf eine signifikante Schädigung neuronaler und axonaler Strukturen nicht nur in den typischen Entmarkungsherden, sondern auch in morphologisch völlig normal erscheinender weißer und grauer Substanz. Die kumulative Zerstörung neuronaler und axonaler Strukturen scheint hauptverantwortlich für die Entstehung eines permanenten neurologischen Defizits zu sein. Damit kann die MS nicht länger als isolierte Erkrankung der weißen Substanz betrachtet werden, sondern betrifft vielmehr das gesamte Zentralnervensystem. Hieraus ergibt sich zwangsläufig die Notwendigkeit, neben den etablierten immunmodulatorischen Therapieverfahren frühzeitig und konsequent eine neuroprotektive und/oder neuroregenerative Behandlung durchzuführen. Voraussetzung hierfür ist ein besseres Verständnis der neurodegenerativen Mechanismen und die Entwicklung suffizienter neuroprotektiver Therapiestrategien.
Response of C3H/HeJ and C3H/HeN mice and their peritoneal macrophages to the toxicity of Chlamydia psittaci elementary bodies

Intravenous injection of toxic doses of Chlamydia psittaci elementary bodies into endotoxin-responsive C3H/HeN mice or endotoxin-nonresponsive C3H/HeJ mice resulted in essentially identical time intervals to death. Inoculation of monolayer cultures of thioglycolate-stimulated peritoneal macrophages from the two strains of mice with 250 elementary bodies per macrophage resulted in immediate host cell toxicity, although the C3H/HeJ macrophages were somewhat less sensitive to elementary body toxicity than were the C3H/HeN macrophages.
The Neuronal Code(s) of the Cerebellum

Understanding how neurons encode information in sequences of action potentials is of fundamental importance to neuroscience. The cerebellum is widely recognized for its involvement in the coordination of movements, which requires muscle activation patterns to be controlled with millisecond precision. Understanding how cerebellar neurons accomplish such high temporal precision is critical to understanding cerebellar function. Inhibitory Purkinje cells, the only output neurons of the cerebellar cortex, and their postsynaptic target neurons in the cerebellar nuclei, fire action potentials at high, sustained frequencies, suggesting spike rate modulation as a possible code. Yet, millisecond precise spatiotemporal spike activity patterns in Purkinje cells and inferior olivary neurons have also been observed. These results and ongoing studies suggest that the neuronal code used by cerebellar neurons may span a wide time scale from millisecond precision to slow rate modulations, likely depending on the behavioral context.
Neural-Fitted TD-Leaf Learning for Playing Othello With Structured Neural Networks

This paper describes a methodology for quickly learning to play games at a strong level. The methodology consists of a novel combination of three techniques, and a variety of experiments on the game of Othello demonstrates their usefulness. First, structures or topologies in neural network connectivity patterns are used to decrease the number of learning parameters and to deal more effectively with the structural credit assignment problem, which is to change individual network weights based on the obtained feedback. Furthermore, the structured neural networks are trained with the novel neural-fitted temporal difference (TD) learning algorithm to create a system that can exploit most of the training experiences and enhance learning speed and performance. Finally, we use the neural-fitted TD-leaf algorithm to learn more effectively when look-ahead search is performed by the game-playing program. Our extensive experimental study clearly indicates that the proposed method outperforms linear networks and fully connected neural networks or evaluation functions evolved with evolutionary algorithms.