Miracle-dz/UniFAR-FTUs huggingface dataset:
The Production and Characterization of Novel Heavy-Chain Antibodies Against the Tandem Repeat Region of MUC1 Mucin

Camelidae are known to produce immunoglobulins (Igs) devoid of light chains and constant heavy-chain domains (CH1). Antigen-specific fragments of these heavy-chain IgGs (VHH) are of great interest in biotechnology applications. This paper describes the first example of successfully raised heavy-chain antibodies in Camelus dromedarius (single-humped camel) and Camelus bactrianus (two-humped camel) against a MUC1 related peptide that is found to be an important epitope expressed in cancerous tissue. Camels were immunized against a synthetic peptide corresponding to the tandem repeat region of MUC1 mucin and cancerous tissue preparation obtained from patients suffering from breast carcinoma. Three IgG subclasses with different binding properties to protein A and G were purified by affinity chromatography. Both conventional and heavy-chain IgG antibodies were produced in response to MUC1-related peptide. The elicited antibodies could react specifically with the tandem repeat region of MUC1 mucin in an enzyme linked immunosorbant assay (ELISA). Anti-peptide antibodies were purified after passing antiserum over two affinity chromatography columns. Using ELISA, immunocytochemistry and Western blotting, the interaction of purified antibodies with different antigens was evaluated. The antibodies were observed to be selectively bound to antigens namely: MUC1 peptide (tandem repeat region), human milk fat globule membrane (HMFG), deglycosylated human milk fat globule membrane (D-HMFG), homogenized cancerous breast tissue and a native MUC1 purified from ascitic fluid. Ka values of specific polyclonal anti-peptide antibodies were estimated in C. dromedarius and C. bactrianus, as 7 × 1010 M− 1 and 1.4 × 1010 M− 1 respectively.
Development of new nuclear markers and characterization of single nucleotide polymorphisms in kelp gull (Larus dominicanus)

The present study seeks to develop nuclear markers for the kelp gull (Larus dominicanus). We hereby report the characterization of 12 independent nuclear introns, where 104 single nucleotide polymorphisms (SNPs) in 8138 sequenced base pairs were observed. These SNP markers are the first to be designed for genotyping a gull species. The markers will provide useful tools for understanding which processes act or acted upon kelp gulls to cause their low genetic variability in mitochondrial DNA. In addition, these markers open a new opportunity for population genetic and evolutionary studies in the Laridae group.
Matrin 3: Chromosomal distribution and protein interactions

Matrin 3 (matr3), an abundant protein of the internal nuclear matrix, has been linked to a variety of functional events. As a step toward defining its multifunctional nature, we have studied the association of matr3 with chromosome territories and identified potential interacting proteins. A similar staining pattern of matr3 was observed in fixed WI38 fibroblast cells and in live HeLa cells using a matr3‐GFP construct. Matr3 was detected throughout autosomal and the active X chromosome territories. Conversely, matr3 was strikingly excluded from the inactive X chromosome as well as within both the perinuclear and perinucleolar heterochromatin. Yeast two hybrid analysis identified matr3 interactions with 33 unique nuclear localized proteins and also revealed its propensity for self association. A majority of these proteins are involved in RNA metabolism and chromatin remodeling while others function in protein translation, DNA replication/repair and apoptosis. Further analysis of a selection of these proteins and scaffold attachment factor A (SAFA) by co‐localization and co‐immunoprecipitation experiments using HeLa cells confirmed their interactions with matr3. J. Cell. Biochem. 108: 125–133, 2009. © 2009 Wiley‐Liss, Inc.
Overexpression of hsa-miR-125b during osteoblastic differentiation does not influence levels of Runx2, osteopontin, and ALPL gene expression

Multipotent mesenchymal stromal cells (MSCs) were first isolated from bone marrow and then from various adult tissues including placenta, cord blood, deciduous teeth, and amniotic fluid. MSCs are defined or characterized by their ability to adhere to plastic, to express specific surface antigens, and to differentiate into osteogenic, chondrogenic, adipogenic, and myogenic lineages. Although the molecular mechanisms that control MSC proliferation and differentiation are not well understood, the involvement of microRNAs has been reported. In the present study, we investigated the role of miR-125b during osteoblastic differentiation in humans. We found that miR-125b increased during osteoblastic differentiation, as well as Runx2 and ALPL genes. To study whether the gain or loss of miR-125b function influenced osteoblastic differentiation, we transfected MSCs with pre-miR-125b or anti-miR-125b and cultured the transfected cells in an osteoblastic differentiation medium. After transfection, no change was observed in osteoblastic differentiation, and Runx2, OPN, and ALPL gene expression were not changed. These results suggest that the gain or loss of miR-125b function does not influence levels of Runx2, OPN, and ALPL during osteoblastic differentiation.
Screening of 214 Single Nucleotide Polymorphisms in 44 Candidate Cancer Susceptibility Genes: A Case–Control Study on Gastric and Colorectal Cancers in the Japanese Population

OBJECTIVES:Single nucleotide polymorphisms (SNPs) have potential as markers for identifying genes responsible for common diseases and for personalized medicine. To investigate the association between polymorphisms and gastrointestinal (gastric and colorectal) cancer, we performed a hospital-based case–control study in Japan.METHODS:We screened a total of 214 SNPs in 44 candidate genes by using a mass spectrometry-based technique (MassARRAY; Sequenom, Inc., San Diego, CA). In this study, 153 patients and 302 controls for gastric cancer and 121 patients and 245 controls for colorectal cancer were matched with regard to age, sex, and residential area. Genes were selected based on their possible interactions with the environment and lifestyle, and the candidate genes constitute those encoding xenobiotic metabolism enzymes, DNA repair enzymes, and other stress-related proteins. Each polymorphism was tested in controls to ensure its fit with Hardy–Weinberg equilibrium. Odds ratios (OR) and 95% confidence intervals (CI) were calculated by conditional logistic regression analysis to estimate the association between genetic polymorphisms and the risk of gastric and colorectal cancers.RESULTS:Twenty-one SNPs in nine genes were associated with the risk of gastric cancer (P < 0.05) and 15 SNPs in nine genes were associated with the risk of colorectal cancer (P < 0.05). CONCLUSIONS:The findings of the present study will be the basis for future large-scale association studies of gene–environment factors using the candidate gene approach for the Japanese population.
Genomics A Novel Germline Mutation in BAP 1 Predisposes to Familial Clear-Cell Renal Cell Carcinoma

Renal cell carcinoma (RCC) clusters in some families. Familial RCC arises from mutations in several genes, including the von Hippel-Lindau (VHL) tumor suppressor, which is also mutated in sporadic RCC. However, a significant percentage of familial RCC remains unexplained. Recently, we discovered that the BRCA1-associated protein-1 (BAP1) gene is mutated in sporadic RCC. The BAP1 gene encodes a nuclear deubiquitinase and appears to be a classic two-hit tumor suppressor gene. Somatic BAP1 mutations are associated with high-grade, clear-cell RCC (ccRCC) and poor patient outcomes. To determine whether BAP1 predisposes to familial RCC, the BAP1 gene was sequenced in 83 unrelated probands with unexplained familial RCC. Interestingly, a novel variant (c.41T>A; p.L14H) was uncovered that cosegregated with the RCC phenotype. The p.L14H variant targets a highly conserved residue in the catalytic domain, which is frequently targeted by missense mutations. The family with the novel BAP1 variant was characterized by early-onset ccRCC, occasionally of high Fuhrman grade, and lacked other features that typify VHL syndrome. These findings suggest that BAP1 is an early-onset familial RCC
Efficient Algorithms for Budget-Constrained Markov Decision Processes

Discounted, discrete-time, discrete state-space, discrete action-space Markov decision processes (MDPs) form a classical topic in control, game theory, and learning, and as a result are widely applied, increasingly, in very large-scale applications. Many algorithms have been developed to solve large-scale MDPs. Algorithms based on value iteration are particularly popular, as they are more efficient than the generic linear programming approach, by an order of magnitude in the number of states of the MDP. Yet in the case of budget constrained MDPs, no more efficient algorithm than linear programming is known. The theoretically slower running times of linear programming may limit the scalability of constrained MDPs piratically; while, theoretically, it invites the question of whether the increase is somehow intrinsic. In this technical note we show that it is not, and provide two algorithms for budget-constrained MDPs that are as efficient as value iteration. Denoting the running time of value iteration by VI, and the magnitude of the input by U, for an MDP with m expected budget constraints our first algorithm runs in time O(poly(m, log U) · VI). Given a pre-specified degree of precision, η, for satisfying the budget constraints, our second algorithm runs in time O(log m · poly(log U) · (1/η2) · VI), but may produce solutions that overutilize each of the m budgets by a multiplicative factor of 1 + η. In fact, one can substitute value iteration with any algorithm, possibly specially designed for a specific MDP, that solves the MDP quickly to achieve similar theoretical guarantees. Both algorithms restrict attention to constrained infinite-horizon MDPs under discounted costs.
Learning Deep Generative Models With Discrete Latent Variables

There have been numerous recent advancements on learning deep generative models with latent variables thanks to the reparameterization trick that allows to train deep directed models effectively. However, since reparameterization trick only works on continuous variables, deep generative models with discrete latent variables still remain hard to train and perform considerably worse than their continuous counterparts. In this paper, we attempt to shrink this gap by introducing a new architecture and its learning procedure. We develop a hybrid generative model with binary latent variables that consists of an undirected graphical model and a deep neural network. We propose an efficient two-stage pretraining and training procedure that is crucial for learning these models. Experiments on binarized digits and images of natural scenes demonstrate that our model achieves close to the state-of-the-art performance in terms of density estimation and is capable of generating coherent images of natural scenes.
Critical methods and user generated content: the iPhone on YouTube

Sites like YouTube offer vast sources of data for studies of human computer interaction. However, they also present a number of methodological challenges. This paper offers an example study of the initial reception of the iPhone 3G through YouTube. It begins with a quantitative account of the overall shape of the most frequently viewed returns for an iPhone 3G" search. A content analysis of the first hundred videos then explores the returns categorized by genre. Comments on the most popular video "Will It Blend"are analysed using grounded theory. It is argued that social science methods are not sufficient for a rich understanding of such material. The paper concludes with an analysis of"Will it Blend"that draws on cultural and critical theory. It is argued that a multi-methodological approach is necessary to exploit such data and also to address the challenges of next generation Human Computer Interaction (HCI).
A viewpoint-based case-based reasoning approach utilising an enterprise architecture ontology for experience management

ABSTRACT The accessibility of project knowledge obtained from experiences is an important and crucial issue in enterprises. This information need about project knowledge can be different from one person to another depending on the different roles he or she has. Therefore, a new ontology-based case-based reasoning (OBCBR) approach that utilises an enterprise ontology is introduced in this article to improve the accessibility of this project knowledge. Utilising an enterprise ontology improves the case-based reasoning (CBR) system through the systematic inclusion of enterprise-specific knowledge. This enterprise-specific knowledge is captured using the overall structure given by the enterprise ontology named ArchiMEO, which is a partial ontological realisation of the enterprise architecture framework (EAF) ArchiMate. This ontological representation, containing historical cases and specific enterprise domain knowledge, is applied in a new OBCBR approach. To support the different information needs of different stakeholders, this OBCBR approach has been built in such a way that different views, viewpoints, concerns and stakeholders can be considered. This is realised using a case viewpoint model derived from the ISO/IEC/IEEE 42010 standard. The introduced approach was implemented as a demonstrator and evaluated using an application case that has been elicited from a business partner in the Swiss research project.
Bovine ncRNAs Are Abundant, Primarily Intergenic, Conserved and Associated with Regulatory Genes

It is apparent that non-coding transcripts are a common feature of higher organisms and encode uncharacterized layers of genetic regulation and information. We used public bovine EST data from many developmental stages and tissues, and developed a pipeline for the genome wide identification and annotation of non-coding RNAs (ncRNAs). We have predicted 23,060 bovine ncRNAs, 99% of which are un-annotated, based on known ncRNA databases. Intergenic transcripts accounted for the majority (57%) of the predicted ncRNAs and the occurrence of ncRNAs and genes were only moderately correlated (r = 0.55, p-value<2.2e-16). Many of these intergenic non-coding RNAs mapped close to the 3′ or 5′ end of thousands of genes and many of these were transcribed from the opposite strand with respect to the closest gene, particularly regulatory-related genes. Conservation analyses showed that these ncRNAs were evolutionarily conserved, and many intergenic ncRNAs proximate to genes contained sequence-specific motifs. Correlation analysis of expression between these intergenic ncRNAs and protein-coding genes using RNA-seq data from a variety of tissues showed significant correlations with many transcripts. These results support the hypothesis that ncRNAs are common, transcribed in a regulated fashion and have regulatory functions.
Non-Major Histocompatibility Complex Control of Antibody Isotype and Th1 versus Th2 Cytokines during Experimental Infection of Mice with Mycobacterium avium

ABSTRACT Infection of different strains of mice withMycobacterium avium has revealed genetic control of the immunoglobulin isotype induced and of the balance between Th1 and Th2 cytokines. Female BALB/c or C57BL/10 mice were infected intranasally with 105M. avium organisms. The antibody response was measured over 18 weeks by enzyme-linked immunosorbent assay and Western blotting, while numbers of cytokine-producing cells were assessed at 12 to 15 weeks by ELISPOT assay. Upon infection, C57BL/10 mice produced a clear Th1 response with strong gamma interferon (IFN-γ) production, no interleukin-4 (IL-4), and almost entirely immunoglobulin G2a (IgG2a) antibody. In contrast, BALB/c mice developed T cells producing IL-4, as well as those producing IFN-γ, while the antibody response was a mixture of IgG1 and IgG2a. Antibodies from BALB/c mice were also able to recognize a greater range of antigens than were C56BL/10 mice. B10D2 mice, which carry the BALB/c major histocompatibility complex haplotype on a C57BL/10 background, followed the C57BL/10 cytokine pattern. Mice infected withListeria monocytogenes did not show a similar response dichotomy.
CURVE is the Institutional Repository for Coventry University Designing games for older adults : an affordance based approach

The main purpose of this study is to determine the game principles that need to be adopted in order to create an enjoyable and engaging game experience for older adults, whilst ensuring that the purpose of the game, encouraging upper limb mobility, is respected. The study reported in this paper involved a group of older adults who played and gave feedback on an early game prototype which feed into the design modification process. Each player’s action capabilities were measured and taken into account in the design process. This helped ensure that opportunities for action that the game afforded were adapted to players’ need. Keywords—game design; older adults; kinect; engagement; user centred design; affordance
Post-translational control of genetic circuits using Potyvirus proteases

Genetic engineering projects often require control over when a protein is degraded. To this end, we use a fusion between a degron and an inactivating peptide that can be added to the N-terminus of a protein. When the corresponding protease is expressed, it cleaves the peptide and the protein is degraded. Three protease:cleavage site pairs from Potyvirus are shown to be orthogonal and active in exposing degrons, releasing inhibitory domains and cleaving polyproteins. This toolbox is applied to the design of genetic circuits as a means to control regulator activity and degradation. First, we demonstrate that a gate can be constructed by constitutively expressing an inactivated repressor and having an input promoter drive the expression of the protease. It is also shown that the proteolytic release of an inhibitory domain can improve the dynamic range of a transcriptional gate (200-fold repression). Next, we design polyproteins containing multiple repressors and show that their cleavage can be used to control multiple outputs. Finally, we demonstrate that the dynamic range of an output can be improved (8-fold to 190-fold) with the addition of a protease-cleaved degron. Thus, controllable proteolysis offers a powerful tool for modulating and expanding the function of synthetic gene circuits.
Biologic determinants of tumor recurrence in stage II colon cancer: validation study of the 12-gene recurrence score in cancer and leukemia group B (CALGB) 9581.

PURPOSE A greater understanding of the biology of tumor recurrence should improve adjuvant treatment decision making. We conducted a validation study of the 12-gene recurrence score (RS), a quantitative assay integrating stromal response and cell cycle gene expression, in tumor specimens from patients enrolled onto Cancer and Leukemia Group B (CALGB) 9581. PATIENTS AND METHODS CALGB 9581 randomly assigned 1,713 patients with stage II colon cancer to treatment with edrecolomab or observation and found no survival difference. The analysis reported here included all patients with available tissue and recurrence (n = 162) and a random (approximately 1:3) selection of nonrecurring patients. RS was assessed in 690 formalin-fixed paraffin-embedded tumor samples with quantitative reverse transcriptase polymerase chain reaction by using prespecified genes and a previously validated algorithm. Association of RS and recurrence was analyzed by weighted Cox proportional hazards regression. RESULTS Continuous RS was significantly associated with risk of recurrence (P = .013) as was mismatch repair (MMR) gene deficiency (P = .044). In multivariate analyses, RS was the strongest predictor of recurrence (P = .004), independent of T stage, MMR, number of nodes examined, grade, and lymphovascular invasion. In T3 MMR-intact (MMR-I) patients, prespecified low and high RS groups had average 5-year recurrence risks of 13% (95% CI, 10% to 16%) and 21% (95% CI, 16% to 26%), respectively. CONCLUSION The 12-gene RS predicts recurrence in stage II colon cancer in CALGB 9581. This is consistent with the importance of stromal response and cell cycle gene expression in colon tumor recurrence. RS appears to be most discerning for patients with T3 MMR-I tumors, although markers such as grade and lymphovascular invasion did not add value in this subset of patients.
Cross-lingual geo-parsing for non-structured data

A geo-parser automatically identifies location words in a text. We have generated a geo-parser specifically to find locations in unstructured Spanish text. Our novel geo-parser architecture combines the results of four parsers: a lexico-semantic Named Location Parser, a rules-based building parser, a rules-based street parser, and a trained Named Entity Parser. Each parser has different strengths: the Named Location Parser is strong in recall, and the Named Entity Parser is strong in precision, and building and street parser finds buildings and streets that the others are not designed to do. To test our Spanish geo-parser performance, we compared the output of Spanish text through our Spanish geo-parser, with that same Spanish text translated into English and run through our English geo-parser. The results were that the Spanish geo-parser identified toponyms with an F1 of . 796, and the English geo-parser identified toponyms with an F1 of . 861 (and this is despite errors introduced by translation from Spanish to English), compared to an F1 of . 114 from a commercial off-the-shelf Spanish geo-parser. Results suggest (1) geo-parsers should be built specifically for unstructured text, as have our Spanish and English geo-parsers, and (2) location entities in Spanish that have been machine translated to English are robust to geo-parsing in English.
Incremental Multiple Kernel Learning for object recognition

A good training dataset, representative of the test images expected in a given application, is critical for ensuring good performance of a visual categorization system. Obtaining task specific datasets of visual categories is, however, far more tedious than obtaining a generic dataset of the same classes. We propose an Incremental Multiple Kernel Learning (IMKL) approach to object recognition that initializes on a generic training database and then tunes itself to the classification task at hand. Our system simultaneously updates the training dataset as well as the weights used to combine multiple information sources. We demonstrate our system on a vehicle classification problem in a video stream overlooking a traffic intersection. Our system updates itself with images of vehicles in poses more commonly observed in the scene, as well as with image patches of the background, leading to an increase in performance. A considerable change in the kernel combination weights is observed as the system gathers scene specific training data over time. The system is also seen to adapt itself to the illumination change in the scene as day transitions to night.
An Integrated approach for the Secure Transmission of Images based on DNA Sequences

As long as human beings exist on this earth, there will be confidential images intended for limited audience. These images have to be transmitted in such a way that no unauthorized person gets knowledge of them. DNA sequences play a vital role in modern cryptography and DNA sequence based cryptography renders a helping hand for transmission of such confidential images over a public insecure channel as the intended recipient alone can decipher them. This paper outlines an integrated encryption scheme based on DNA sequences and scrambling according to magic square of doubly even order pattern. Since there is negligible correlation between the original and encrypted image this method is robust against any type of crypt attack.