Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of Key Processes Underlying Cancer Phenotypes Using Biologic Pathway Analysis

Cancer is recognized to be a family of gene-based diseases whose causes are to be found in disruptions of basic biologic processes. An increasingly deep catalogue of canonical networks details the specific molecular interaction of genes and their products. However, mapping of disease phenotypes to alterations of these networks of interactions is accomplished indirectly and non-systematically. Here we objectively identify pathways associated with malignancy, staging, and outcome in cancer through application of an analytic approach that systematically evaluates differences in the activity and consistency of interactions within canonical biologic processes. Using large collections of publicly accessible genome-wide gene expression, we identify small, common sets of pathways – Trka Receptor, Apoptosis response to DNA Damage, Ceramide, Telomerase, CD40L and Calcineurin – whose differences robustly distinguish diverse tumor types from corresponding normal samples, predict tumor grade, and distinguish phenotypes such as estrogen receptor status and p53 mutation state. Pathways identified through this analysis perform as well or better than phenotypes used in the original studies in predicting cancer outcome. This approach provides a means to use genome-wide characterizations to map key biological processes to important clinical features in disease.
Use of hospitals, physician visits, and hospice care during last six months of life among cohorts loyal to highly respected hospitals in the United States

Abstract Objective To evaluate the use of healthcare resources during the last six months of life among patients of US hospitals with strong reputations for high quality care in managing chronic illness. Design Retrospective cohort study based on claims data from the US Medicare programme. Participants Cohorts receiving most of their hospital care from 77 hospitals that appeared on the 2001 US News and World Report “best hospitals” list for heart and pulmonary disease, cancer, and geriatric services. Main outcome measures Use of healthcare resources in the last six months of life: number of days spent in hospital and in intensive care units; number of physician visits; percentage of patients seeing 10 or more physicians; percentage enrolled in hospice. Terminal care: percentage of deaths occurring in hospital; percentage of deaths occurring in association with a stay in an intensive care unit. Results Extensive variation in each measure existed among the 77 hospital cohorts. Days in hospital per decedent ranged from 9.4 to 27.1 (interquartile range 11.6-16.1); days in intensive care units ranged from 1.6 to 9.5 (2.6-4.5); number of physician visits ranged from 17.6 to 76.2 (25.5-39.5); percentage of patients seeing 10 or more physicians ranged from 16.9% to 58.5% (29.4-43.4%); and hospice enrolment ranged from 10.8% to 43.8% (22.0-32.0%). The percentage of deaths occurring in hospital ranged from 15.9% to 55.6% (35.4-43.1%), and the percentage of deaths associated with a stay in intensive care ranged from 8.4% to 36.8% (20.2-27.1%). Conclusion Striking variation exists in the utilisation of end of life care among US medical centres with strong national reputations for clinical care.
Solving the riddle of glioblastoma

Glioblastoma multiforme (GBM) is the most frequent primary malignant brain tumor in adults and remains incurable. The current standard of care consists of surgery, radiation, and chemotherapy with the alkylating agent temozolomide.1,2 Over the past 30 years, advances in surgery and radiotherapy have done little to increase survival.3 Even with the development of antiangiogenic therapies, targeted small molecule inhibitors, and tumor treatment field therapy, median survival for GBM is less than 2 years for patients with favorable prognostic factors.4
Copy number variations in East-Asian population and their evolutionary and functional implications

Recent discovery of the copy number variation (CNV) in normal individuals has widened our understanding of genomic variation. However, most of the reported CNVs have been identified in Caucasians, which may not be directly applicable to people of different ethnicities. To profile CNV in East-Asian population, we screened CNVs in 3578 healthy, unrelated Korean individuals, using the Affymetrix Genome-Wide Human SNP array 5.0. We identified 144 207 CNVs using a pooled data set of 100 randomly chosen Korean females as a reference. The average number of CNVs per genome was 40.3, which is higher than that of CNVs previously reported using lower resolution platforms. The median size of CNVs was 18.9 kb (range 0.2–5406 kb). Copy number losses were 4.7 times more frequent than copy number gains. CNV regions (CNVRs) were defined by merging overlapping CNVs identified in two or more samples. In total, 4003 CNVRs were defined encompassing 241.9 Mb accounting for ∼8% of the human genome. A total of 2077 CNVRs (51.9%) were potentially novel. Known CNVRs were larger and more frequent than novel CNVRs. Sixteen percent of the CNVRs were observed in ≥1% of study subjects and 24% overlapped with the OMIM genes. A total of 476 (11.9%) CNVRs were associated with segmental duplications. CNVS/CNVRs identified in this study will be valuable resources for studying human genome diversity and its association with disease.
Compressed domain robust hashing for AAC audio

A robust audio hashing algorithm for AAC audio is proposed in this paper. The robust hash is calculated from MDCT-coefficients which are derived by partial decoding of AAC bitstream. There is no complicated transformation in the proposed algorithm, therefore, it is of low computational complexity. The proposed method is highly robust to MDCT-based audio compression. Experimental results also show its high discrimination power and the robustness against content preserved operations.
Java multi-histogram volume rendering framework for medical images

This work extends the multi-histogram volume rendering framework proposed by Kniss et al. [1] to provide rendering results based on the impression of overlaid triangles on a graph of image intensity versus gradient magnitude. The developed method of volume rendering allows for greater emphasis to boundary visualization while avoiding issues common in medical image acquisition. For example, partial voluming effects in computed tomography and intensity inhomogeneity of similar tissue types in magnetic resonance imaging introduce pixel values that will not reflect differing tissue types when a standard transfer function is applied to an intensity histogram. This new framework uses developing technology to improve upon the Kniss multi-histogram framework by using Java, the GPU, and MIPAV, an open-source medical image processing application, to allow multi-histogram techniques to be widely disseminated. The OpenGL view aligned texture rendering approach suffered from performance setbacks, inaccessibility, and usability problems. Rendering results can now be interactively compared with other rendering frameworks, surfaces can now be extracted for use in other programs, and file formats that are widely used in the field of biomedical imaging can be visualized using this multi-histogram approach. OpenCL and GLSL are used to produce this new multi-histogram approach, leveraging texture memory on the graphics processing unit of desktops to provide a new interactive method for visualizing biomedical images. Performance results for this method are generated and qualitative rendering results are compared. The resulting framework provides the opportunity for further applications in medical imaging, both in volume rendering and in generic image processing.
Identification of 11 pH-Regulated Genes inBorrelia burgdorferi Localizing to Linear Plasmids

ABSTRACT When Borrelia burgdorferi is transmitted from the tick vector to the mammalian host, the bacterium experiences alterations in its environment, such as changes in temperature and pH. Previously, we observed numerous alterations in the membrane protein profile whenB. burgdorferi B31 was grown at pH 7.0 compared to pH 8.0. Here we identify 11 genes localizing to linear plasmids that are up-regulated at pH 7.0 relative to pH 8.0 in vitro. Seven genes (bba03, bba24, bba64, bba66, bbe31, bbj41/bbi39 [encoding products that are 99% identical], and bbk01) were indirectly identified by proteomic analysis of membrane proteins. Another gene, bba36, was identified by screening a B. burgdorferi B31 genomic library with cross-adsorbed hyperimmune rabbit serum. Two additional genes, bba65 andbba73, were identified by Northern blot analysis. Genesbba64, bba65, bba66, bbj41/bbi39, and bba73 are members of paralogous gene family 54, and bbe31 is a member of the closely related paralogous gene family 60. Genebba24 is part of a bicistronic operon withbba25 that encodes the well-characterized decorin binding proteins A and B. All 11 genes were transcriptionally regulated, yet the degree of pH regulation varied, with some genes more tightly regulated than others. The regions upstream of these pH-regulated genes appeared to be unrelated, yet many contained dyad repeats ranging from 12 to 25 nucleotides in length that may be involved in the regulation of these genes.
On the use of standards for microarray lossless image compression

The interest in methods that are able to efficiently compress microarray images is relatively new. This is not surprising, since the appearance and fast growth of the technology responsible for producing these images is also quite recent. In this paper, we present a set of compression results obtained with 49 publicly available images, using three image coding standards: lossless JPEG2000, JBIG, and JPEG-LS. We concluded that the compression technology behind JBIG seems to be the one that offers the best combination of compression efficiency and flexibility for microarray image compression.
Sex differences in brain aging: a quantitative magnetic resonance imaging study.

BACKGROUND Little is known about the effect of sex on age-related changes in brain structure. METHODS Quantitative magnetic resonance imaging of the brain was performed in 330 elderly (age range, 66-96 years) volunteers living independently in the community, all of whom were participants in the Cardiovascular Health Study. Blinded measurements of global and regional brain size were made from T1-weighted axial images by means of computer-assisted edge detection and trace methods. High measurement reliabilities were obtained. RESULTS Age-specific changes in brain size were significantly greater in men than women for the peripheral (sulcal) cerebrospinal fluid volume, the lateral (sylvian) fissure cerebrospinal fluid volume, and the parieto-occipital region area. Main effects of age were observed for all the remaining brain regions examined (cerebral hemisphere volume, frontal region area, temporoparietal region area, lateral ventricular volume, and third ventricle volume), but these effects were similar in men and women. Asymmetries in brain structures were not affected by aging in either sex. CONCLUSIONS Our results are generally consistent with the few published studies on sex differences in brain aging and suggest that, for at least some structures, aging effects may be more apparent in men than women. The neurobiological bases and functional correlates of these sex differences require further investigation.
Unfolding and Conformational Distributions during Protein Precipitation

The association of misfolded proteins, or aggregation, is a critical problem in a number of human diseases as well during the expression, refolding, formulation, and delivery of therapeutic proteins. In this study, we investigate lysozyme precipitation with hydrogen exhange using nuclear magnetic resonance (NMR) and mass spectrometry (MS). We show that MS can reveal the presence of conformational distributions, albeit without the detailed structural information afforded by NMR. Further, we find that increases in precipitant concentration alter the structure and composition of precipitates. The selective unfolding of one portion of the protein in these precipitates is correlated with hydrogen exchange patterns observed under nonprecipitating conditions and in other studies of lysozyme.
The Delta-Opioid Receptor Is Sufficient, but Not Necessary, for Spinal Opioid-Adrenergic Analgesic Synergy

Spinal administration of opioid and α2-adrenergic receptor (α2AR) agonists produces analgesia, and agonists interact synergistically when coadministered. The molecular mechanism underlying this synergy is largely unknown. Pharmacological studies have identified both the delta and the mu-opioid receptors (DOR and MOR) as candidate receptors capable of interacting synergistically with α2AR agonists. However, recent studies attribute the antinociceptive effect of DOR agonists to actions at the MOR, calling the role of DOR in opioid-adrenergic synergy into question. Other studies suggesting that DOR is implicated in morphine antinociception raise the possibility that DOR is nonetheless required for morphine synergy with α2AR agonists. This study aimed to determine whether DOR activation is sufficient and necessary to mediate opioid-adrenergic synergistic interactions in the spinal cord. The antinociceptive effects of clonidine, [d-Ala2]-deltorphin II (DeltII), morphine, and [d-Ala2, N-Me-Phe4, Gly-ol5]-enkephalin (DAMGO) were evaluated using the substance P (SP) behavioral assay in wild type (WT) and DOR-knockout (KO) mice. Opioid-adrenergic drug interactions were evaluated after spinal coadministration of clonidine with DeltII, morphine, or DAMGO. Isobolographic analyses of dose-response curves determined whether interactions were synergistic or additive. The absence of DeltII antinociceptive efficacy in DOR-KO confirmed its selectivity in the SP assay. Although DeltII+clonidine interacted synergistically in WT mice, no interaction with clonidine was observed in DOR-KO mice. Clonidine was synergistic with morphine in both mouse strains. DAMGO did not synergize with clonidine in either strain. These findings confirm that although other opioid receptors can interact synergistically with α2AR agonists, DOR is sufficient for spinal opioid-adrenergic interactions.
Formal Specification and Verification of JXTA ' s Core Protocols for peer-to-peer Networks

JXTA protocols describe a platform for peer-to-peer networking, independent of underlying transport protocols, for peer collaboration and message exchange. The JXTA project is an open source initiative and its protocols are informally specified as an exchange of XML-based messages between entities. This paper presents the formal specification and automated verification of its core protocols: the Endpoint Routing Protocol and the Peer Resolver Protocol. These protocols run at the core of the JXTA architecture and are respectively responsible for routing messages between peers and for resolving queries/responses for services and applications. The PROMELA based formal specification serves as input to the SPIN model checker to prove the presence of a logical flaw due to nonprogress cycles.
Learning to Learn Image Classifiers with Informative Visual Analogy

In recent years, we witnessed a huge success of Convolutional Neural Networks on the task of the image classification. However, these models are notoriously data hungry and require tons of training images to learn the parameters. In contrast, people are far better learner who can learn a new concept very fast with only a few samples. The plausible mysteries making the difference are two fundamental learning mechanisms: learning to learn and learning by analogy. In this paper, we attempt to investigate a new human-like learning method by organically combining these two mechanisms. In particular, we study how to generalize the classification parameters of previously learned concepts to a new concept. we first propose a novel Visual Analogy Network Embedded Regression (VANER) model to jointly learn a low-dimensional embedding space and a linear mapping function from the embedding space to classification parameters for base classes. We then propose an out-of-sample embedding method to learn the embedding of a new class represented by a few samples through its visual analogy with base classes. By inputting the learned embedding into VANER, we can derive the classification parameters for the new class.These classification parameters are purely generalized from base classes (i.e. transferred classification parameters), while the samples in the new class, although only a few, can also be exploited to generate a set of classification parameters (i.e. model classification parameters). Therefore, we further investigate the fusion strategy of the two kinds of parameters so that the prior knowledge and data knowledge can be fully leveraged. We also conduct extensive experiments on ImageNet and the results show that our method can consistently and significantly outperform state-of-the-art baselines.
TIE2-expressing monocytes/macrophages regulate revascularization of the ischemic limb

A third of patients with critical limb ischemia (CLI) will eventually require limb amputation. Therapeutic neovascularization using unselected mononuclear cells to salvage ischemic limbs has produced modest results. The TIE2‐expressing monocytes/macrophages (TEMs) are a myeloid cell subset known to be highly angiogenic in tumours. This study aimed to examine the kinetics of TEMs in patients with CLI and whether these cells promote neovascularization of the ischemic limb. Here we show that there are 10‐fold more circulating TEMs in CLI patients, and removal of ischemia reduces their numbers to normal levels. TEM numbers in ischemic muscle are two‐fold greater than normoxic muscle from the same patient. TEMs from patients with CLI display greater proangiogenic activity than TIE2‐negative monocytes in vitro. Using a mouse model of hindlimb ischemia, lentiviral‐based Tie2 knockdown in TEMs impaired recovery from ischemia, whereas delivery of mouse macrophages overexpressing TIE2, or human TEMs isolated from CLI patients, rescued limb ischemia. These data suggest that enhancing TEM recruitment to the ischemic muscle may have the potential to improve limb neovascularization in CLI patients.
Sliding mode control for a model of an electrohydraulic actuator system with discontinuous nonlinear friction

This paper considers the application of sliding mode control (SMC) to a high precision hydrostatic actuation system with nonlinear discontinuous friction. An important consideration in such systems is the oscillations that occur in the system response due to friction for small input signals at cross-over regions where the velocity changes sign. A new model for a high precision hydrostatic actuation system is developed assuming discontinuous and nonlinear friction in the actuator. This model is used in the development of a sliding mode control strategy. A significant result from this study is that the SMC can suppress such oscillations. In addition, the paper introduces for the first time, a linear quadratic approach for defining a discrete-time sliding surface for nonlinear systems. A comparative study involving the application of the proposed SMC versus a gain-scheduled proportional controller is presented. This comparison demonstrates the performance improvements resulting from the SMC and the added robustness of this strategy given large modeling uncertainties
Feature space based image segmentation via density modification

Feature space based approaches have been the most popular ones among those used to perform image segmentation. In this paper, a density modification framework is proposed in order to aid feature space based segmentation in images. The framework embeds a position-dependent property associated with each sample in the feature space of an image into the corresponding density map and hence modifies it. The property association and embedding operations in the framework is implemented using a fuzzy set theory based system devised with cue from beam theory of solid mechanics and the appropriateness of this approach is established. Experimental results of segmentation in images are given to demonstrate the effectiveness of the proposed framework.
N-gram-based Tense Models for Statistical Machine Translation

Tense is a small element to a sentence, however, error tense can raise odd grammars and result in misunderstanding. Recently, tense has drawn attention in many natural language processing applications. However, most of current Statistical Machine Translation (SMT) systems mainly depend on translation model and language model. They never consider and make full use of tense information. In this paper, we propose n-gram-based tense models for SMT and successfully integrate them into a state-of-the-art phrase-based SMT system via two additional features. Experimental results on the NIST Chinese-English translation task show that our proposed tense models are very effective, contributing performance improvement by 0.62 BLUE points over a strong baseline.
Age- and sex-related differences in episodic growth hormone secretion in the rat.

Sequential blood samples were obtained from undisturbed, unrestrained, male and female rats of different ages from intrajugular or intraaortic cannulae implanted 4 days before experimentation. Blood (70–100 μl) was gently withdrawn at 30-min intervals for periods of 6 h. Plasma GH was determined by RIA. In 22-day-old rats, episodic secretion of GH was evident, but plasma GH levels did not exceed 70 ng/ml. In older rats, peak levels of GH were higher and there was a significant difference in the secretory pattern of GH between male and female rats. In male rats, 30, 45, and 90 days old, GH surges in individual animals occurred at regular 3- to 4-h intervals. Peak levels were 200-300 ng/ml and levels between peaks, were mostly <5 ng/ml. The timing of the peaks with respect to clock time was similar in most animals. In 30-day-old rats, peak levels were lower in females than in males. In 45-day-old female rats, GH was secreted episodically, and peak levels were 200-300 ng/ml. However, the interval between pea.
Clinical and Behavioral Correlates of Achieving and Maintaining Glycemic Targets in an Underserved Population With Type 2 Diabetes

OBJECTIVE—In an underserved Latino area, we established a disease-management program and proved its effectiveness. However, many patients still remained above target. This study was designed to evaluate which factors are associated with reaching program goals. RESEARCH DESIGN AND METHODS—This was a randomized, prospective, observational study in which patients enrolled in our program were followed for 2 years with outcomes, measures, and questionnaires assessed at baseline and at 6, 12, and 24 months. RESULTS—Overall, A1C fell by 1%. Adherence to medication was the strongest predictor of reaching the target A1C of <8%; baseline A1C was also predictive. Knowledge scores increased in those who reached target, but the measures of self-efficacy and empowerment did not change for either group. CONCLUSIONS—Diabetes management is effective in a lower-income Latino population. However, adherence was suboptimal even when medications were provided on-site for free. Further research into barriers associated with medication adherence is needed.