Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Spray-dried Hydroxyapatite-5-Fluorouracil Granules on Cell Lines Derived from Tissues of Mesenchymal Origin

In our previous work we described the preparation and characterization of spray dried hydroxyapatite micro granules loaded with 5-fluorouracil (5-FU). These loaded particles are used as a model drug delivery system (DDS). In this study we examined the in vitro response of two cell lines derived from different tissues to 5-FU loaded granules (LG). Both cell lines, either L929 cells of a mouse fibroblast lineage or cells originating from a rat osteosarcoma (ROS 17/2.8) showed a dose dependent decrease in cell proliferation in response to 5-FU-, either dissolved in the culture medium or loaded onto particles. The response of the two cell lines to loaded and nonloaded particles was different. The effect of LG and of a corresponding concentration of free 5-FU was practically the same for the ROS 17/2.8 cells indicating that ROS 17/2.8 cells were not affected by the carrier material. In contrast, L929 cells showed a slight decrease in cell proliferation also in the presence of granules not loaded with 5-FU. This is thought to be attributed to the inhibition of mitogenesis by phosphocitrates, already demonstrated in fibroblasts. In summary, we found that the loaded 5-FU kept its effectivity after the spray drying process and that the response towards the granules varied with cell type. This is the first step towards a tissue specific DDS.
Evolutionary perspectives on the fetal origins hypothesis

The fetal origins hypothesis, or Barker hypothesis, is both stimulating and challenging for evolutionary human biologists. While evidence of a correlation between conditions around the time of birth and later health outcomes has been presented before, the more recent evidence of a connection between fetal growth and chronic disease risk later in life has attracted considerable attention among epidemiologists and human biologists. Several themes that are fundamental to human biology emerge from an engagement with the fetal origins hypothesis. Among them are the tension between concepts of pathology, constraint, and adaptation; the importance of a life history perspective that embraces the notion of trade‐offs; the question of environmental predictability; and the mechanisms of energy mobilization and allocation. Bringing the insights of evolutionary biology to bear on the fetal origins hypothesis illustrates the value of the field now known as evolutionary medicine. Am. J. Hum. Biol. 17:113–118, 2005. © 2004 Wiley‐Liss, Inc.
Apprentissage de métrique appliqué à la classification de textes par méthodes à noyaux

Résumé – Dans cet article, nous proposons une méthode pour l’optimisation de la métrique d’un classifieur textuel à noyaux. Contrairement aux techniques populaires existantes, notre approche ne nécessite pas la définition explicite de règles sémantiques. Etant donné un ensemble d’apprentissage, l’algorithme proposé permet d’optimiser la matrice sémantique, sans qu’il soit nécessaire d’exhiber celle-ci. Les résultats expérimentaux montrent l’efficacité et l’utilité de la méthode proposée en classification de textes par SVM (Support Vector Machines).
INTELLIGENT BIOMETRIC SIGNATURE VERIFICATION SYSTEM INCORPORATING NEURAL NETWORK

In this paper, the practical development of a novel but yet simple, low cost and userfriendly PC-based biometric technique to verify human signature is presented. The system is based on data acquired from time duration, pen position and pressure signals of handwritten signatures. A preprocessing stage of the acquired signature signals involving the use of a number of common feature extraction techniques is rigorously highlighted. An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. The results of the study showed that the system is effective and promising in identifying correct human signatures presented to the system.
Katariina Mankinen NEUROPSYCHOLOGICAL PERFORMANCE AND FUNCTIONAL MRI FINDINGS IN CHILDREN WITH NON-LESIONAL TEMPORAL LOBE EPILEPSY

The purpose of the present work was to investigate whether children with non-lesional temporal lobe epilepsy (TLE) have deficits in neuropsychological performance and whether the possible deficits can be investigated using functional magnetic resonance imaging (fMRI). In this population-based study, 21 children aged 8-15 with non-lesional TLE and a normal intelligence quotient were evaluated and compared with 21 healthy, ageand gender-matched controls. Neuropsychological assessments, clinical examinations, electroencephalography (EEG) and structural and functional MRI were performed on all the subjects. Three fMRI methods were used: resting-state regional homogeneity, resting-state functional connectivity and task-induced blood oxygenation level-dependent activation. The patients with non-lesional TLE showed good neuropsychological performance on average, although the girls were found to have significant problems in several neuropsychological tests. The deficits were not restricted to elements of performance involving the classical temporal lobe memory system but were also found in tests requiring frontal and parietal lobe functioning. Early onset of epilepsy and duration of epilepsy had significant negative effects on neuropsychological performance. All the fMRI methods detected significant functional differences between the TLE patients and the healthy controls, not only in the temporal lobes but also in broad networks extending to the frontal, parietal and thalamic areas. These differences seemed to differ markedly in location between the TLE patients depending on the interictal EEG findings. Neuropsychological performance results were supported by the fMRI findings, implying that TLE should be regarded as a widespread disruption of the brain networks and not just malfunction of a single region in the brain within these networks. This needs to be taken into consideration when evaluating learning abilities among TLE patients even at an early stage in epilepsy.
ECG classification based on sparse constrained nonnegative-matrix factorization and decision tree

In this paper, several data dimensionality reduction methods are compared. Then an ECG classification method is proposed, which employs the sparse decomposition of Nonnegative Matrix Factorization (SCNMF) for data dimensionality reduction, and Decision Tree for signal classification. The experimental results, in which five common heart diseases in the MIT-BIH database are used, indicate that the overall accuracy by the proposed ECG classification method reaches more than 99%. In addition, the employed data dimensionality reduction method can better retain the useful raw information and can save storage space.
Block Unification IF-conversion for High Performance Architectures

Graphics Processing Units accelerate data-parallel graphic calculations using wide SIMD vector units. Compiling programs to use the GPU's SIMD architectures require converting multiple control flow paths into a single stream of instructions. IF-conversion is a compiler transformation, which converts control dependencies into data dependencies, and it is used by vectorizing compilers to eliminate control flow and enable efficient code generation. In this work we enhance the IF-conversion transformation by using a block unification method to improve the currently used block flattening method. Our experimental results demonstrate that our IF-conversion method is effective in reducing the number of predicated instructions and in boosting kernel execution speed.
A massively parallel strategy for STR marker development, capture, and genotyping

Short tandem repeat (STRs or microsatellites) variants, are highly polymorphic markers that facilitate powerful, high-precision population genetic analyses. STRs are especially valuable in conservation and ecological genetic research, yielding detailed information on population structure and short-term demographic flux. However, STR marker development and analysis by conventional PCR-based methods imposes a workflow bottleneck and is suboptimal for noninvasive sampling strategies such as fecal DNA recovery. While massively parallel sequencing has not previously been leveraged for scalable, efficient STR recovery, here we present a pipeline for developing STR markers directly from high-throughput shotgun sequencing data without requiring a reference genome assembly, and a methodological approach for highly parallel recovery of enriched STR loci. We first employed our approach to design and capture a panel of 5,000 STR loci from a test group of diademed sifakas (Propithecus diadema, n=3), endangered Malagasy rainforest lemurs, and we report extremely efficient recovery of targeted loci—97.3-99.6% of STRs characterized with ≥10x non-redundant coverage. Second, we tested our STR capture strategy on a P. diadema fecal DNA preparation, and report robust initial results and methodological suggestions for future implementations. In addition to STR targets, this approach also generates large, genome-wide single nucleotide polymorphism (SNP) panels from regions flanking the STR loci. Our method provides a cost-effective and highly scalable solution for rapid recovery of large STR and SNP datasets in any species without need for a reference genome, and can be used even with suboptimal DNA, which is more easily acquired in conservation and ecological genetic studies. Data Deposition Raw sequencing data are available under Study Accession numbers SRP073167 (genomic shotgun data for Oberon and Tatiana) and SRP076225 (targeted re-sequencing data) from the NCBI Sequence Read Archive. BaitSTR software is available at Github (core BaitSTR programs: https://github.com/aakrosh/BaitSTR; BaitSTR_type.pl companion script for genotyping and block manipulation: https://github.com/lkistler/BaitSTR_type).
Potential impact of fireworks on respiratory health

The world-wide use of fireworks with their consequent detrimental effect on the air quality is widely recognized with elevated ambient air levels of particulate matter and its several metallic components and gases identified in several studies carried out during such events. Exposed individuals may be at risk following inhalation of such produced pollutants. This review focuses on the impact of fireworks on air quality and the potential effect of fireworks on the respiratory system of healthy individuals as well as those suffering from underlying respiratory diseases, particularly asthma and chronic obstructive pulmonary disease (COPD). This applies not only to spectators including children but also to pyrotechnicians themselves. An extensive Medline search revealed that a strong evidence of the impact of fireworks on respiratory health is lacking in susceptible as well as healthy individuals with no formal studies on COPD or asthma, other than a few case reports in the latter. The implementation of global strategies to control the use of fireworks and hence improve air quality could possibly reduce their likely detrimental effect on human respiratory health in exposed individuals, but clearly a more targeted research is needed.
Awake craniotomy anesthetic management using dexmedetomidine, propofol, and remifentanil

Introduction Awake craniotomy allows continuous monitoring of patients’ neurological functions during open surgery. Anesthesiologists have to sedate patients in a way so that they are compliant throughout the whole surgical procedure, nevertheless maintaining adequate analgesia and anxiolysis. Currently, the use of α2-receptor agonist dexmedetomidine as the primary hypnotic–sedative medication is increasing. Methods Nine patients undergoing awake craniotomy were treated with refined monitored anesthesia care (MAC) protocol consisting of a combination of local anesthesia without scalp block, low-dose infusion of dexmedetomidine, propofol, and remifentanil, without the need of airways management. Results The anesthetic protocol applied in our study has the advantage of decreasing the dose of each drug and thus reducing the occurrence of side effects. All patients had smooth and rapid awakenings. The brain remained relaxed during the entire procedure. Conclusion In our experience, this protocol is safe and effective during awake brain surgery. Nevertheless, prospective randomized trials are necessary to confirm the optimal anesthetic technique to be used.
Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data

Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence) and two data matrices (amino acids or the first two codon positions) yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast.
Spatial sketch to compose internet images with RealSense 3D camera

Digital content creation become an indispensable part of our lives. In addition, massive internet images provide us abundant creation material. To construct a computer-aided graphics creation system, interaction and convenience are the critical factors. With somatosensory interactive technology, we can interact with our devices in a more natural and intuitive way, and gain immersive experience at the same time. In this paper, we present a sketch driven image creation system by retrieving and composing internet images automatically. These images are retrieved according simple freehand sketch annotated with text labels. With the help of RealSense depth camera, user only need to make various hand gestures to draw the sketch in spatial and tag with the text labels by speech. Then our system will complete a series of tasks to generate image automatically, thus it greatly reduce the burden of painting and increase the fun and interactive friendliness.
Aging, cognitive decline and hearing loss: outcomes of auditory rehabilitation in older adults.

Introduction. Restoring a sensory function in older adults might allow a significant improvement in their cognitive status. Although specific clinical conditions could compromise management and drastically reduce the chance of acceptable outcomes, auditory rehabilitation with cochlear implants or hearing aids still remains one of the most effectiveness procedure. Advances in research and technology suggest a functional “adaptation” in central processes that could influence other related or not strictly related activities, such as memory and working memory, frontal and pre-frontal processes, orientation, calculation, logic and executive functions. Since the link between hearing loss and cognitive decline has been clarified, scientific community is currently finding out the lacking evidence of effectiveness of auditory rehabilitation in reducing or counteracting cognitive decline. Material and Methods. Hearing impaired patients with more than 65 years of age, affected with mild to profound hearing loss were enrolled in the present study; complete audiological assessment and cognitive status evaluation were performed in order to define personal scores for comparison in longitudinal testing after different auditory rehabilitation. A control group was created for statistical purposes and made of cases matched per age and clinical status, without hearing loss and cognitive decline. Different subgroups were created to reduce heterogeneity in terms of entity of hearing loss, duration of auditory deprivation, type of auditory rehabilitation and training. A follow up of 6-12 months has been carried out for selected patients. Results. To date, 77 subjects have been included in the present study and divided in 5 different groups based on types and degree of hearing loss. Statistical analyses with t-student test and fisher exact test, shows a significant difference in depression and cognitive status scores before and after auditory rehabilitation. In addition there are no differences between the control group (20 subjects) and patients who have a good outcomes after auditory training and rehabilitation. Discussion. Auditory rehabilitation shows significant effectiveness even among older adults with different degrees of hearing loss, and positive improvements are detectable in terms of social isolation, depression and cognitive performances. In future research, it will be crucially important to unravel how sensory abilities are linked to cognitive functioning in aging. Conventional medical assessment is often not enough to assess older people with multiple comorbidities. In the end, a multidisciplinary approach is still the best option, and geriatrics should include specific sensorineural investigations to manage elderly patients who are generally at risk of cognitive decline and hearing loss.
An integrated learning algorithm for rule induction

This document describes the hierarchical agglomerative cluster algorithm Pnc 2 in the context of direct generation of If-Then rules for classification tasks. As an agglomerative cluster algorithm, the Pnc 2 initializes each learn data tuple as a single cluster. Then, if a merge test is passed, iteratively always those two clusters with the same output value are merged, that are closest to each other. The merge test transforms the generalized cluster into a rule and evaluates it by a kind of hitrate. The rule’s premise is the cuboid, that encloses the input vectors of all learn data tuples merged in the cluster. This representation suffers in high dimensional input spaces due to the COD problem and thus a special mechanism is used to extend the cuboid during the merge test. A heterogenous normalized and weighted Minkowski overlap metric is used to be able to process mixed continuous and nominal inputs. An integrated bagging component can improve accuracy and also reduces the time complexity for a learn data sample with N data tuples from O(N ) to approximately O(N). The size of the learned rule set can be further reduced by applying a context sensitive feature selection, that individually removes the unnecessary inputs from each rule’s premise. The algorithm can also be viewed as an instance based learning algorithm, namely as an exemplar-based generalization approach. Thus the idea of the k-nearestneighbor algorithm (knn), to base the decision on several surrounding learn data tuples, can be transferred to improve the prediction accuracy. The number of free parameters of the Pnc 2 is been reduced in a preliminary study with some development benchmarks. Then the Pnc 2 is compared experimentally with the most similar existing algorithms, namely with the Nge, the Rise and, of course, with the knn algorithm. All remaining free parameters of the Pnc 2 are tuned using cross-validation or similar approaches within the respective learn data samples. The Pnc 2 outperforms the Nge algorithms and its variants and reaches better or comparative accuracies as the knn or the RISE algorithm with typically much smaller ruleset/model sizes. Acknowledgement The Pnc 2 cluster algorithm was developed while I was a scholarship holder in the post graduate research program Modelling and Model-Based Design of Complex Technological Systems at the Chair of Electrical Control Engineering at the University of Dortmund, Germany. My research project was initiated by Prof. Dr. rer. nat. H. Kiendl. The post graduate research program was founded by the Deutsche Forschungsgemeinschaft (DFG). Note The Pnc 2 Rule Induction System is a free Windows software tool, that is using the Pnc 2 cluster algorithm to automatically induce rules from a given data sample. Additionally a DOS command line version will be available soon. The kernels are written in ANSI C++, they are well documented and should easily be compiled for different operating systems. You may download the program at http://www.newty. de/pnc2/index.html.
Structural basis for HLA-DQ2-mediated presentation of gluten epitopes in celiac disease

Celiac disease, also known as celiac sprue, is a gluten-induced autoimmune-like disorder of the small intestine, which is strongly associated with HLA-DQ2. The structure of DQ2 complexed with an immunogenic epitope from gluten, QLQPFPQPELPY, has been determined to 2.2-Å resolution by x-ray crystallography. The glutamate at P6, which is formed by tissue transglutaminase-catalyzed deamidation, is an important anchor residue as it participates in an extensive hydrogen-bonding network involving Lys-β71 of DQ2. The gluten peptide–DQ2 complex retains critical hydrogen bonds between the MHC and the peptide backbone despite the presence of many proline residues in the peptide that are unable to participate in amide-mediated hydrogen bonds. Positioning of proline residues such that they do not interfere with backbone hydrogen bonding results in a reduction in the number of registers available for gluten peptides to bind to MHC class II molecules and presumably impairs the likelihood of establishing favorable side-chain interactions. The HLA association in celiac disease can be explained by a superior ability of DQ2 to bind the biased repertoire of proline-rich gluten peptides that have survived gastrointestinal digestion and that have been deamidated by tissue transglutaminase. Finally, surface-exposed proline residues in the proteolytically resistant ligand were replaced with functionalized analogs, thereby providing a starting point for the design of orally active agents for blocking gluten-induced toxicity.