Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel inhibitory action of tunicamycin homologues suggests a role for dynamic protein fatty acylation in growth cone-mediated neurite extension

In neuronal growth cones, the advancing tips of elongating axons and dendrites, specific protein substrates appear to undergo cycles of posttranslational modification by covalent attachment and removal of long-chain fatty acids. We show here that ongoing fatty acylation can be inhibited selectively by long-chain homologues of the antibiotic tunicamycin, a known inhibitor of N-linked glycosylation. Tunicamycin directly inhibits transfer of palmitate to protein in a cell-free system, indicating that tunicamycin inhibition of protein palmitoylation reflects an action of the drug separate from its previously established effects on glycosylation. Tunicamycin treatment of differentiated PC12 cells or dissociated rat sensory neurons, under conditions in which protein palmitoylation is inhibited, produces a prompt cessation of neurite elongation and induces a collapse of neuronal growth cones. These growth cone responses are rapidly reversed by washout of the antibiotic, even in the absence of protein synthesis, or by addition of serum. Two additional lines of evidence suggest that the effects of tunicamycin on growth cones arise from its ability to inhibit protein long-chain acylation, rather than its previously established effects on protein glycosylation and synthesis. (a) The abilities of different tunicamycin homologues to induce growth cone collapse very systematically with the length of the fatty acyl side- chain of tunicamycin, in a manner predicted and observed for the inhibition of protein palmitoylation. Homologues with fatty acyl moieties shorter than palmitic acid (16 hydrocarbons), including potent inhibitors of glycosylation, are poor inhibitors of growth cone function. (b) The tunicamycin-induced impairment of growth cone function can be reversed by the addition of excess exogenous fatty acid, which reverses the inhibition of protein palmitoylation but has no effect on the inhibition of protein glycosylation. These results suggest an important role for dynamic protein acylation in growth cone- mediated extension of neuronal processes.
Crk1, a Novel Cdc2-Related Protein Kinase, Is Required for Hyphal Development and Virulence in Candida albicans

ABSTRACT Both mitogen-activated protein kinases and cyclin-dependent kinases play a role in hyphal development in Candida albicans. Using an oligonucleotide probe-based screen, we have isolated a new member of the Cdc2 kinase subfamily, designated Crk1 (Cdc2-related kinase). The protein sequence of Crk1 is most similar to those ofSaccharomyces cerevisiae Sgv1 and human Pkl1/Cdk9. InS. cerevisiae, CRK1 suppresses some, but not all, of the defects associated with an sgv1 mutant. Deleting both copies of CRK1 in C. albicansslows growth slightly but leads to a profound defect in hyphal development under all conditions examined. crk1/crk1mutants are impaired in the induction of hypha-specific genes and are avirulent in mice. Consistent with this, ectopic expression of the Crk1 kinase domain (CRK1N) promotes filamentous or invasive growth in S. cerevisiae and hyphal development in C. albicans. The activity of Crk1 inS. cerevisiae requires Flo8 but is independent of Ste12 and Phd1. Similarly, Crk1 promotes filamentation through a route independent of Cph1 and Efg1 in C. albicans. RAS1V13 can also activate filamentation in acph1/cph1 efg1/efg1 double mutant. Interestingly,CRK1N produces florid hyphae in ras1/ras1strains, while RAS1V13 generates feeble hyphae in crk1/crk1 strains.
Bag-of-visual-words expansion using visual relatedness for video indexing

Bag-of-visual-words (BoW) has been popular for visual classification in recent years. In this paper, we propose a novel BoW expansion method to alleviate the effect of visual word correlation problem. We achieve this by diffusing the weights of visual words in BoW based on visual word relatedness, which is rigorously defined within a visual ontology. The proposed method is tested in video indexing experiment on TRECVID-2006 video retrieval benchmark, and an improvement of 7% over the traditional BoW is reported.
Performance improvement of geographically distributed cosimulation by hierarchically grouped messages

To improve the performance of geographically distributed cosimulation, we propose a concept called hierarchically grouped message. The concept improves cosimulation performance, preserving the cosimulation accuracy, by hierarchically grouping messages transferred between simulators in a short period of simulated time into a single physical message, thereby reducing the number of physical messages. Applying the concept to hybrid and optimistic cosimulation, we can reduce the number of rollbacks as well as the communication overhead accompanying the message transfer. Experimental results show the efficiency of the proposed method for practical examples in an internationally distributed cosimulation environment.
Performance Limits of Fair-Access in Sensor Networks with Linear and Selected Grid Topologies

This paper investigates fundamental performance limits of medium access control (MAC) protocols for multi-hop sensor networks. A unique aspect of this study is the modeling of a fair-access criterion requiring that sensors have an equal rate of frame delivery to the base station. Tight upper bounds on network utilization and tight lower bounds on minimum time between samples are derived for fixed linear and grid topologies. The significance of these bounds is two-fold: First, they are universal, i.e., they hold for any MAC protocol. Second, they are provably tight, i.e., they can be achieved by a version of time division multiple access (TDMA) protocol that is self-clocking, and therefore does not require system-wide clock synchronization. The paper also examines the implication of the end-to-end performance bounds regarding the traffic rate and sensing time interval of individual sensors.
Assessing proteinuria in chronic kidney disease: protein-creatinine ratio versus albumin-creatinine ratio.

BACKGROUND Quantification of proteinuria is important in the assessment of chronic kidney disease (CKD). The aim of this study was to investigate the optimal test to identify significant proteinuria. METHODS We retrospectively assessed the relationship between total protein:creatinine ratio (TPCR), albumin:creatinine ratio (ACR) and 24-h urine total protein in 6842 patients with CKD focusing on performance at thresholds of 0.5 and 1 g/day of proteinuria. RESULTS The relationship between ACR and TPCR is non-linear. TPCR is highly correlated with 24-h urine protein (Spearman's rho = 0.91), though ACR also performs well (rho = 0.84). Using receiver-operator characteristic curve analysis, TPCR outperforms ACR at predicting 0.5 g/day [area under the curve (AUC) 0.967 vs 0.951, P < 0.001] and 1 g/day of proteinuria (AUC 0.968 vs 0.947, P = 0.004). A TPCR threshold of 100 mg/mmol had a higher sensitivity (94% vs 79%) but lower specificity (88% vs 95%) than an ACR of 70 mg/mmol to predict 1 g/day of total proteinuria. To achieve comparable sensitivity, the ACR threshold falls to 17.5 mg/mmol, with lower specificity than TPCR (69.8%). Sensitivity of TPCR rose with increasing age, and in females: to achieve 95% sensitivity in a man <49 years, requires a TPCR of 65 mg/mmol, compared to 179 mg/mmol in a woman >79 years. Non-albumin proteinuria was a lower proportion of total proteinuria in patients receiving angiotensin-converting enzyme inhibitors or angiotensin receptor blockade than in those who were not (P < 0.001). CONCLUSIONS TPCR is a more sensitive screening test than ACR to predict clinically relevant proteinuria. The diagnostic performance of both tests varies substantially with age and gender, and should be taken into consideration when interpreting results. Total proteinuria cannot be adequately predicted from ACR, and our results suggest that caution is appropriate before utilizing ACR in patients with non-diabetic CKD.
Sparse Poisson Noisy Image Deblurring

Deblurring noisy Poisson images has recently been a subject of an increasing amount of works in many areas such as astronomy and biological imaging. In this paper, we focus on confocal microscopy, which is a very popular technique for 3-D imaging of biological living specimens that gives images with a very good resolution (several hundreds of nanometers), although degraded by both blur and Poisson noise. Deconvolution methods have been proposed to reduce these degradations, and in this paper, we focus on techniques that promote the introduction of an explicit prior on the solution. One difficulty of these techniques is to set the value of the parameter, which weights the tradeoff between the data term and the regularizing term. Only few works have been devoted to the research of an automatic selection of this regularizing parameter when considering Poisson noise; therefore, it is often set manually such that it gives the best visual results. We present here two recent methods to estimate this regularizing parameter, and we first propose an improvement of these estimators, which takes advantage of confocal images. Following these estimators, we secondly propose to express the problem of the deconvolution of Poisson noisy images as the minimization of a new constrained problem. The proposed constrained formulation is well suited to this application domain since it is directly expressed using the antilog likelihood of the Poisson distribution and therefore does not require any approximation. We show how to solve the unconstrained and constrained problems using the recent alternating-direction technique, and we present results on synthetic and real data using well-known priors, such as total variation and wavelet transforms. Among these wavelet transforms, we specially focus on the dual-tree complex wavelet transform and on the dictionary composed of curvelets and an undecimated wavelet transform.
Detection of Insider Attacks in Cloud Based e-Healthcare Environment

In recent years, Cloud computing has been receiving great attention from various business and research organizations as it promises to provide large storage facilities and highly managed remote services. Due to its characteristics like on-demand self service, rapid elasticity, ubiquitous network access and resource pooling, it shows high potential for providing e-Healthcare solutions. It can offer various financial and functional benefits to e-Healthcare which includes providing storage flexibility for the rapidly growing healthcare data, reduced cost, better accessibility, improved quality of care and enhancement in medical research. However at the same time, it faces many technical challenges like privacy, reliability, security etc. In the Cloud based ehealthcare environment where the patient's data is transferred between entities, maintaining the security of data becomes a priority. Cryptographic techniques can only provide a secure channel of communication but it fails to provide security at end points. Security attacks may be accomplished by the malicious insider at the end points. A malicious insider may modify the patient's data resulting in a false examination. The paper provides a detective approach for such attacks in the healthcare organizations. Our work is focused with the detection of insider attacks for preventing false examination of patient's health records and assuring the accountability of data usage. Watermarking can be used for detection of modification by an insider attack but does not provide accountability of data usage. Hence our approach combines the functionalities of cryptographic techniques and watermarking together with an accountability framework for providing transparency of patient's data usage.
Integration of mass spectrometry and RNA‐Seq data to confirm human ab initio predicted genes and lncRNAs

MS/MS has been used to improve genome annotation in various organisms. The classical approach is to construct comprehensive theoretical peptide database with six frame translation model from the whole ORF of a genome and search against this database with real MS/MS spectra. In this work we took a more focused approach, we constructed a database containing only peptides from the ab initio predicted genes from current human genome annotation, and all theoretical peptides from currently annotated lncRNAs, and searched such a database with MS/MS data from human Hela cell line. The purpose of this design is to find translation evidence for ab initio predicted genes and to rule out possible wrongly defined lncRNAs in a systematic proteogenomics effort. To validate proteogenomics results, we integrated RNA‐Seq data analysis for the same Hela cell line which generated MS/MS data, and performed MRM experiment on self‐cultured Hela cell line samples. Six peptides were found to support ab initio predicted genes with both RNA‐Seq and MRM validations, while none was found to support a translated lncRNA. This workflow could be flexibly applied to other human samples and datasets to help further improve human gene annotation.
Ieee Transactions on Pattern Analysis and Machine Intelligence 1 Dense Subgraph Partition of Positive Hypergraphs

—In this paper, we present a novel partition framework, called dense subgraph partition (DSP), to automatically, precisely and efficiently decompose a positive hypergraph into dense subgraphs. A positive hypergraph is a graph or hypergraph whose edges, except self-loops, have positive weights. We first define the concepts of core subgraph, conditional core subgraph, and disjoint partition of a conditional core subgraph, then define DSP based on them. The result of DSP is an ordered list of dense subgraphs with decreasing densities, which uncovers all underlying clusters, as well as outliers. A divide-and-conquer algorithm, called min-partition evolution, is proposed to efficiently compute the partition. DSP has many appealing properties. First, it is a nonparametric partition and it reveals all meaningful clusters in a bottom-up way. Second, it has an exact and efficient solution, called min-partition evolution algorithm. The min-partition evolution algorithm is a divide-and-conquer algorithm, thus time-efficient and memory-friendly, and suitable for parallel processing. Third, it is a unified partition framework for a broad range of graphs and hypergraphs. We also establish its relationship with the densest k-subgraph problem (DkS), an NP-hard but fundamental problem in graph theory, and prove that DSP gives precise solutions to DkS for all k in a graph-dependent set, called critical k-set. To our best knowledge, this is a strong result which has not been reported before. Moreover, as our experimental results show, for sparse graphs, especially web graphs, the size of critical k-set is close to the number of vertices in the graph. We test the proposed partition framework on various tasks, and the experimental results clearly illustrate its advantages.
Serie Research Memoranda The Relation Between Unemployment and the Interest Rate : Application of an ARX Approach

In Bierens (1987) a Granger causal relation was found between unemployment and the interest rate for the Netherlands. In Bierens and Broersma (1990) this relation was confinned for a number of important industrial countries, with an ARMAX modeling strategy, using monthly data. In this paper we investigate whether there exists a similar Granger causal relation between unemployment and the interest rate when we apply an ARX modeling approach, based on the VAR methodology of Sims (1980), with quarterly data. The idea is that a VAR model can be considered as a system of ARX models. We also stress the importance of misspecification analysis, in order to design a model which adequately represents the DGP giving rise to the observed data. It appears that with this modeling approach, the relation also holds for the USA, Canada, Japan, Germany, the UK, France and the Netherlands. For all countries the interest rate is the main explanatory variable, together with the growth rate of industrial production. We also conducted an impulse response analysis to the VAR's of the variables of the consecutive countries. A unit shock in the interest rate had a positive impact on unemployment, with a lag of about one to two years. Finally, we also present a number of economie theories which can explain these findings of which the managerial theory of Baumol (1959), with a flexible labor effort rate seems very realistic.
Bhattacharyya distance-based irregular pyramid method for image segmentation

This paper proposes a new unsupervised image segmentation method by using Bhattacharyya distance-based irregular pyramid, termed as ‘BDIP’ algorithm. The proposed BDIP algorithm obtains a suboptimal labelling solution under the condition that the number of segments is not manually given. It hierarchically builds each level of the irregular pyramid, with the result that the final segments emerge as they are represented by single nodes at certain levels. The BDIP algorithm employs Bhattacharyya distance to estimate the intra-level similarity at higher pyramidal levels so as to improve the accuracy and robustness to noise. Furthermore, an adaptive neighbour search method is proposed such that the BDIP algorithm can self-determine the number of segments. This method considers not only the graphic constraint, but also the similarity constraint in the sense that a candidate node is selected as a neighbour of the centre node if there is no boundary evidence between these two nodes. With the pyramidal accumulation, this evaluation is aggregated into the approximately global evidence, based on which the number of segments can be self-determined. Experimental results have shown that this proposed BDIP algorithm outperforms other benchmark segmentation algorithms in terms of segmentation accuracy, labelling cost and robustness to noise.
Starry Night

The above picture is starry night by Vincent Van Gogh. The picture actual painting is 73.7 cm tall, but the width is not given. The above picture is to scale, meaning that the ratio of height to width of the above picture is the same as the ratio of height to width of the actual panting. 1) Use a ruler to calculate the height to length (in cm) ratio of the above picture. Use this to calculate the actual width of the painting in cm.
Simultaneous transfer of tumorigenic and metastatic phenotypes by transfection with genomic DNA from a human cutaneous squamous cell carcinoma

High‐molecular‐weight genomic DNA isolated from a human cutaneous squamous cell carcinoma (AS) was assayed for its ability to induce tumorigenic transformation of NIH 3T3 cells. Subcutaneous injection of NIH 3T3 cells cotransfected with DNAs from AS tumor and pSV2‐neo plasmid not only induced tumors at the site of injection, but also metastasized spontaneously to the lungs in 100% of nude mice injected. DNA isolated from a representative primary tumor and a metastasis was again used in a second round of transfection. Injection of secondary transfectants into nude mice again resulted in induction of both subcutaneous tumors and spontaneous long metastases. Southern blot hybridization with ras‐specific probes revealed that DNA from both primary tumors and metastases induced by AS tumor DNA contained highly amplified Ha‐ras oncogene. Furthermore, DNAs from secondary tumors and metastases induced by DNA from a primary tumor and a metastasis also contained similar highly amplified Ha‐ras oncogene. These results suggest that the amplified Ha‐ras oncogene may be responsible for induction of both tumorigenic and metastatic phenotypes in NIH 3T3 cells transfected with DNA from AS tumor.
Participatory design of an orientation aid for amnesics

We present the participatory design and evaluation of an orientation aid for individuals who have anterograde amnesia. Our design team included six amnesics who have extreme difficulty storing new memories. We describe the methods we used to enable the participation of individuals with such severe cognitive impairments. Through this process, we have conceived, designed, and developed the OrientingTool, a software application for Personal Digital Assistants that can be used by amnesics to orient themselves when feeling lost or disoriented. Two complementary studies were conducted to evaluate the effectiveness of this tool in ecologically valid contexts. Our findings suggest that the OrientingTool can improve an amnesic's independence and confidence in managing situations when disoriented, and that participatory design may be productively used with participants who have significant cognitive disabilities.
Estimates of biological variation in routinely measured biochemical analytes in clinically healthy dogs.

BACKGROUND The degree of biological variation in routinely measured concentrations and activities of biochemical analytes has not been well defined in client-owned pet dogs. OBJECTIVES The aim of this study was to define indices of biological variation and, where appropriate, indices of individuality and critical change values for routinely measured serum biochemical analytes in a group of clinically healthy dogs owned and housed privately. METHODS A prospective cohort study was conducted. Serum samples obtained from clinically healthy adult dogs at varying intervals over a 12-week period were analyzed. For each sample, a panel of 14 analytes was measured. Three levels of outlier analyses were applied (analytical, intra-individual, and inter-individual), followed by nested ANOVA to calculate intra-individual, inter-individual, and analytical coefficients of variation (CV(I), CV(G), and CV(A), respectively). RESULTS Specimens from 11 dogs were analyzed. Individuality indices ranged from 0.9 for glucose and total triglyceride concentrations to 3.4 for ALT activity. Analytical variation (CV(A) ) was > ½ CV(I) for 9/14 analytes, failing to meet criteria for acceptable analytical variation when defining critical change values. Where analyzer performance was acceptable, critical change values ranged from 26.4% for glucose concentration to 84.0% for total triglyceride concentration. CONCLUSIONS Many frequently measured analytes included in routine serum biochemical panels have high individuality. Thus, use of standard reference intervals to monitor changes over time in an individual is likely to miss meaningful biological change.
Information and communication technology in learning development and rehabilitation

Introduction There is still no evidence to base interventions on neuropsychological rehabilitation or cognitive stimulation related with learning development. There are two main problems to solve. The first is the sustainability of the clinical interventions. The second one is the lack of evidence. This is not derived at all from a lack of studies but to methodological difficulties finding trials suitable for meta-analysis. This is a real hazard for translational research because of the difficulties of developers in testing new designs and showing efficacy, and also for the development of the body of knowledge, making difficult to find main theories and design appropriate experiments. Description of care ICTs have profoundly modified this scenario. Advances in communication technologies allow delivery of intensive, personalized, monitored neuropsychological intervention, through telerehabilitation platforms, and cognitive neuroscience based content, to guide plastic changes towards the recovery of more appropriate behaviour. Advances in information technologies have provide new possibilities to assess efficacy, opening new pathways to knowledge discovery from databases generated from clinical practice. Conclusion Institute Guttmann, from its initiative PREVIRNEC, is pioneering the application of this dual approach, bridging knowledge to the end user through communication technologies (internet) and extracting implicit knowledge (efficacy on neuropsychological rehabilitation) from data generated from each intervention.