An analysis of the linkage between legislators’ behavior and electoral support: The case of the Filipino labor emigrants and the Congress of the Philippines [védés előtt]

This dissertation investigates one of the most popular phenomena - labor emigration, specifically zeroing on its impact on the legislative process by looking at the linkage between the behavior of legislators in terms of their performance as to the number of legislative measures they file in Congress, and the support of the overseas Filipinos including the Filipino Labor Emigrants (FLES) or Overseas Filipino Workers (OFWs) in terms of the number of votes they cast for the legislators. This dissertation advances the hypothesis that, the more legislative measures legislators file in Congress that will benefit the FLEs or OFWs, the more votes they will get from this sector of the Philippine society, much more so if such legislative initiatives are publicized

Coherent manipulation of three-qubit states in a molecular single-ion magnet

We study the quantum spin dynamics of nearly isotropic Gd3+ ions entrapped in polyoxometalate molecules and diluted in crystals of a diamagnetic Y3+ derivative. The full energy-level spectrum and the orientations of the magnetic anisotropy axes have been determined by means of continuous-wave electron paramagnetic resonance experiments, using X-band (9-10 GHz) cavities and on-chip superconducting waveguides and 1.5-GHz resonators. The results show that seven allowed transitions between the 2S+1 spin states can be separately addressed. Spin coherence T2 and spin-lattice relaxation T1 rates have been measured for each of these transitions in properly oriented single crystals. The results suggest that quantum spin coherence is limited by residual dipolar interactions with neighbor electronic spins. Coherent Rabi oscillations have been observed for all transitions. The Rabi frequencies increase with microwave power and agree quantitatively with predictions based on the spin Hamiltonian of the molecular spin. We argue that the spin states of each Gd3+ ion can be mapped onto the states of three addressable qubits (or, alternatively, of a d=8-level "qudit"), for which the seven allowed transitions form a universal set of operations. Within this scheme, one of the coherent oscillations observed experimentally provides an implementation of a controlled-controlled-NOT (or Toffoli) three-qubit gate

Functional microRNA screening using a comprehensive lentiviral human microRNA expression library

ABSTRACT: BACKGROUND: MicroRNAs (miRNAs) are a class of small regulatory RNAs that target sequences in messenger RNAs (mRNAs) to inhibit their protein output. Dissecting the complexities of miRNA function continues to prove challenging as miRNAs are predicted to have thousands of targets, and mRNAs can be targeted by dozens of miRNAs. RESULTS: To systematically address biological function of miRNAs, we constructed and validated a lentiviral miRNA expression library containing 660 currently annotated and 422 candidate human miRNA precursors. The miRNAs are expressed from their native genomic backbone, ensuring physiological processing. The arrayed layout of the library renders it ideal for high-throughput screens, but also allows pooled screening and hit picking. We demonstrate its functionality in both short- and long-term assays, and are able to corroborate previously described results of well-studied miRNAs. CONCLUSIONS: With the miRNA expression library we provide a versatile tool for the systematic elucidation of miRNA function.

Feature Extraction and Random Forest to Identify Sheep Behavior from Accelerometer Data

Sensor technologies play an essential part in the agricultural community and many other scientific and commercial communities. Accelerometer signals and Machine Learning techniques can be used to identify and observe behaviours of animals without the need for an exhaustive human observation which is labour intensive and time consuming. This study employed random forest algorithm to identify grazing, walking, scratching, and inactivity (standing, resting) of 8 Hebridean ewes located in Cheshire, Shotwick in the UK. We gathered accelerometer data from a sensor device which was fitted on the collar of the animals. The selection of the algorithm was based on previous research by which random forest achieved the best results among other benchmark techniques. Therefore, in this study, more focus was given to feature engineering to improve prediction performance. Seventeen features from time and frequency domain were calculated from the accelerometer measurements and the magnitude of the acceleration. Feature elimination was utilised in which highly correlated ones were removed, and only nine out of seventeen features were selected. The algorithm achieved an overall accuracy of 99.43% and a kappa value of 98.66%. The accuracy for grazing, walking, scratching, and inactive was 99.08%, 99.13%, 99.90%, and 99.85%, respectively. The overall results showed that there is a significant improvement over previous methods and studies for all mutually exclusive behaviours. Those results are promising, and the technique could be further tested for future real-time activity recognition

Sensor data classification for the indication of lameness in sheep

Lameness is a vital welfare issue in most sheep farming countries, including the UK. The pre-detection at the farm level could prevent the disease from becoming chronic. The development of wearable sensor technologies enables the idea of remotely monitoring the changes in animal movements which relate to lameness. In this study, 3D-acceleration, 3D-orientation, and 3D-linear acceleration sensor data were recorded at ten samples per second via the sensor attached to sheep neck collar. This research aimed to determine the best accuracy among various supervised machine learning techniques which can predict the early signs of lameness while the sheep are walking on a flat field. The most influencing predictors for lameness indication were also addressed here. The experimental results revealed that the Decision Tree classifier has the highest accuracy of 75.46%, and the orientation sensor data (angles) around the neck are the strongest predictors to differentiate among severely lame, mildly lame and sound classes of sheep

Rapid Accumulation of CD14+CD11c+ Dendritic Cells in Gut Mucosa of Celiac Disease after in vivo Gluten Challenge

Of antigen-presenting cells (APCs) expressing HLA-DQ molecules in the celiac disease (CD) lesion, CD11c(+) dendritic cells (DCs) co-expressing the monocyte marker CD14 are increased, whereas other DC subsets (CD1c(+) or CD103(+)) and CD163(+)CD11c(-) macrophages are all decreased. It is unclear whether these changes result from chronic inflammation or whether they represent early events in the gluten response. We have addressed this in a model of in vivo gluten challenge.Treated HLA-DQ2(+) CD patients (n = 12) and HLA-DQ2(+) gluten-sensitive control subjects (n = 12) on a gluten-free diet (GFD) were orally challenged with gluten for three days. Duodenal biopsies obtained before and after gluten challenge were subjected to immunohistochemistry. Single cell digests of duodenal biopsies from healthy controls (n = 4), treated CD (n = 3) and untreated CD (n = 3) patients were analyzed by flow cytometry.In treated CD patients, the gluten challenge increased the density of CD14(+)CD11c(+) DCs, whereas the density of CD103(+)CD11c(+) DCs and CD163(+)CD11c(-) macrophages decreased, and the density of CD1c(+)CD11c(+) DCs remained unchanged. Most CD14(+)CD11c(+) DCs co-expressed CCR2. The density of neutrophils also increased in the challenged mucosa, but in most patients no architectural changes or increase of CD3(+) intraepithelial lymphocytes (IELs) were found. In control tissue no significant changes were observed.Rapid accumulation of CD14(+)CD11c(+) DCs is specific to CD and precedes changes in mucosal architecture, indicating that this DC subset may be directly involved in the immunopathology of the disease. The expression of CCR2 and CD14 on the accumulating CD11c(+) DCs indicates that these cells are newly recruited monocytes

MiR-17-92 cluster is associated with 13q gain and c-myc expression during colorectal adenoma to adenocarcinoma progression

Background:MicroRNAs are small non-coding RNA molecules, which regulate central mechanisms of tumorigenesis. In colorectal tumours, the combination of gain of 8q and 13q is one of the major factors associated with colorectal adenoma to adenocarcinoma progression. Functional studies on the miR-17-92 cluster localised on 13q31 have shown that its transcription is activated by c-myc, located on 8q, and that it has oncogenic activities. We investigated the contribution of the miR-17-92 cluster during colorectal adenoma to adenocarcinoma progression.Methods:Expression levels of the miR-17-92 cluster were determined in 55 colorectal tumours and in 10 controls by real-time RT-PCR. Messenger RNA c-myc expression was also determined by real-time RT-PCR in 48 tumours with array comparative genomic hybridisation (aCGH) data available.Results:From the six members of the miR-17-92 cluster, all except miR-18a, showed significant increased expression in colorectal tumours with miR-17-92 locus gain compared with tumours without miR-17-92 locus gain. Unsupervised cluster analysis clustered the tumours based on the presence of miR-17-92 locus gain. Significant correlation between the expression of c-myc and the six miRNAs was also found.Conclusion:Increased expression of miR-17-92 cluster during colorectal adenoma to adenocarcinoma progression is associated to DNA copy number gain of miR17-92 locus on 13q31 and c-myc expression. © 2009 Cancer Research UK

Gliadin Peptide P31-43 Localises to Endocytic Vesicles and Interferes with Their Maturation

BACKGROUND: Celiac Disease (CD) is both a frequent disease (1:100) and an interesting model of a disease induced by food. It consists in an immunogenic reaction to wheat gluten and glutenins that has been found to arise in a specific genetic background; however, this reaction is still only partially understood. Activation of innate immunity by gliadin peptides is an important component of the early events of the disease. In particular the so-called "toxic" A-gliadin peptide P31-43 induces several pleiotropic effects including Epidermal Growth Factor Receptor (EGFR)-dependent actin remodelling and proliferation in cultured cell lines and in enterocytes from CD patients. These effects are mediated by delayed EGFR degradation and prolonged EGFR activation in endocytic vesicles. In the present study we investigated the effects of gliadin peptides on the trafficking and maturation of endocytic vesicles. METHODS/PRINCIPAL FINDINGS: Both P31-43 and the control P57-68 peptide labelled with fluorochromes were found to enter CaCo-2 cells and interact with the endocytic compartment in pulse and chase, time-lapse, experiments. P31-43 was localised to vesicles carrying early endocytic markers at time points when P57-68-carrying vesicles mature into late endosomes. In time-lapse experiments the trafficking of P31-43-labelled vesicles was delayed, regardless of the cargo they were carrying. Furthermore in celiac enterocytes, from cultured duodenal biopsies, P31-43 trafficking is delayed in early endocytic vesicles. A sequence similarity search revealed that P31-43 is strikingly similar to Hrs, a key molecule regulating endocytic maturation. A-gliadin peptide P31-43 interfered with Hrs correct localisation to early endosomes as revealed by western blot and immunofluorescence microscopy. CONCLUSIONS: P31-43 and P57-68 enter cells by endocytosis. Only P31-43 localises at the endocytic membranes and delays vesicle trafficking by interfering with Hrs-mediated maturation to late endosomes in cells and intestinal biopsies. Consequently, in P31-43-treated cells, Receptor Tyrosine Kinase (RTK) activation is extended. This finding may explain the role played by gliadin peptides in inducing proliferation and other effects in enterocytes from CD biopsies

Exome-wide somatic mutation characterization of small bowel adenocarcinoma

Small bowel adenocarcinoma (SBA) is an aggressive disease with limited treatment options. Despite previous studies, its molecular genetic background has remained somewhat elusive. To comprehensively characterize the mutational landscape of this tumor type, and to identify possible targets of treatment, we conducted the first large exome sequencing study on a population-based set of SBA samples from all three small bowel segments. Archival tissue from 106 primary tumors with appropriate clinical information were available for exome sequencing from a patient series consisting of a majority of confirmed SBA cases diagnosed in Finland between the years 2003-2011. Paired-end exome sequencing was performed using Illumina HiSeq 4000, and OncodriveFML was used to identify driver genes from the exome data. We also defined frequently affected cancer signalling pathways and performed the first extensive allelic imbalance (Al) analysis in SBA. Exome data analysis revealed significantly mutated genes previously linked to SBA (TP53, KRAS, APC, SMAD4, and BRAF), recently reported potential driver genes (SOX9, ATM, and ARID2), as well as novel candidate driver genes, such as ACVR2A, ACVR1B, BRCA2, and SMARCA4. We also identified clear mutation hotspot patterns in ERBB2 and BRAF. No BRAF V600E mutations were observed. Additionally, we present a comprehensive mutation signature analysis of SBA, highlighting established signatures 1A, 6, and 17, as well as U2 which is a previously unvalidated signature. Finally, comparison of the three small bowel segments revealed differences in tumor characteristics. This comprehensive work unveils the mutational landscape and most frequently affected genes and pathways in SBA, providing potential therapeutic targets, and novel and more thorough insights into the genetic background of this tumor type.Peer reviewe