Miracle-dz/UniFAR-FTUs huggingface dataset:
Lactate and glycine—potential MR biomarkers of prognosis in estrogen receptor‐positive breast cancers

Breast cancer is a heterogeneous disease with a variable prognosis. Clinical factors provide some information about the prognosis of patients with breast cancer; however, there is a need for additional information to stratify patients for improved and more individualized treatment. The aim of this study was to examine the relationship between the metabolite profiles of breast cancer tissue and 5‐year survival. Biopsies from breast cancer patients (n = 98) were excised during surgery and analyzed by high‐resolution magic angle spinning MRS. The data were analyzed by multivariate principal component analysis and partial least‐squares discriminant analysis, and the findings of important metabolites were confirmed by spectral integration of the metabolite peaks. Predictions of 5‐year survival using metabolite profiles were compared with predictions using clinical parameters. Based on the metabolite profiles, patients with estrogen receptor (ER)‐positive breast cancer (n = 71) were separated into two groups with significantly different survival rates (p = 0.024). Higher levels of glycine and lactate were found to be associated with lower survival rates by both multivariate analyses and spectral integration, and are suggested as biomarkers for breast cancer prognosis. Similar metabolic differences were not observed for ER‐negative patients, where survivors could not be separated from nonsurvivors. Predictions of 5‐year survival of ER‐positive patients using metabolite profiles gave better and more robust results than those using traditional clinical parameters. The results imply that the metabolic state of a tumor may provide additional information concerning breast cancer prognosis. Further studies should be conducted in order to evaluate the role of MR metabolomics as an additional clinical tool for determining the prognosis of patients with breast cancer. Copyright © 2012 John Wiley & Sons, Ltd.
Control of Cell Lineage-specific Development and Transcription by Bhlh–pas Proteins

We dance round in a ring and suppose But the secret sits in the middle and knows Robert Frost The Secret Sits The basic–helix–loop–helix-PAS (bHLH–PAS) proteins comprise a prominent class of transcriptional regulators that control a variety of developmental and physiological events including neurogenesis, tracheal and salivary duct formation, toxin metabolism, circadian rhythms, response to hypoxia, and hormone receptor function. The bHLH–PAS proteins have a number of similarities with other bHLH protein subfamilies (Littlewood and Evan 1995). bHLH–PAS proteins usually function as di-meric DNA-binding protein complexes; although some bHLH–PAS proteins can form homodimers, the most common functional unit is comprised of heterodimers. These heterodimers consist of one partner that is broadly expressed, and another whose expression or function is restricted spatially, temporally, or by the presence of in-ducers. Just as other vertebrate and invertebrate bHLH proteins control cell lineage specification (Weintraub et The combi-natorial and interactive properties of bHLH–PAS proteins provide a variety of potential mechanisms to control their function as transcriptional regulators, which may help explain their widespread use in complex biological events. The purpose of this review is to describe characteristics of the bHLH–PAS protein subfamily, in particular, how bHLH–PAS proteins control lineage-specific gene transcription and development of the Dro-sophila CNS midline cells and respiratory system, and to discuss the evolutionary implications of the bHLH–PAS/ Arnt regulatory cassette. The underlying mechanisms employed by the bHLH–PAS developmental regulatory proteins discussed here may prove to be common in both vertebrates and invertebrates, and provide a general understanding into how regulatory proteins control the formation of cell lineages. bHLH–PAS proteins share a conserved sequence structure The sequence organization of bHLH–PAS proteins is remarkably similar (Fig. 1). The bHLH domain is located near the amino terminus. The basic region binds DNA and the HLH domain promotes dimerization. These residues are followed closely by the PAS domain. The car-boxy-terminal residues contain transcriptional activation domains (Franks and Crews 1994; Jain et al. 1994; Li et al. 1994) or repression domains (Moffett et al. 1997). The unique feature of bHLH–PAS proteins is the PAS domain, named for the first three proteins identified with this motif: the Drosophila Period (Per), human Arnt, and Drosophila Single-minded (Sim) (Nambu et al. 1991). The PAS domain found in bHLH–PAS proteins is ∼260–310 amino acids long (Crews et al. 1988) (Fig. 1); it is subdivided into two well-conserved regions, PAS-A and PAS-B, separated by a poorly conserved spacer. Within both …
Convolutional Compressed Sensing Using Deterministic Sequences

In this paper, a new class of orthogonal circulant matrices built from deterministic sequences is proposed for convolution-based compressed sensing (CS). In contrast to random convolution, the coefficients of the underlying filter are given by the discrete Fourier transform of a deterministic sequence with good autocorrelation. Both uniform recovery and non-uniform recovery of sparse signals are investigated, based on the coherence parameter of the proposed sensing matrices. Many examples of the sequences are investigated, particularly the Frank-Zadoff-Chu (FZC) sequence, the m-sequence and the Golay sequence. A salient feature of the proposed sensing matrices is that they can not only handle sparse signals in the time domain, but also those in the frequency and/or or discrete-cosine transform (DCT) domain.
Long‐lasting facilitation of excitatory postsynaptic potentials in the rat hippocampus by acetylcholine.

1. The effects of acetylcholine (ACh) on excitatory postsynaptic potentials (EPSPs) evoked by stimulating Schaffer‐commissural afferents and on ionophoretically applied L‐glutamate ligands, were investigated in CA1 neurones of hippocampal slices using current‐ and voltage‐clamp techniques. 2. ACh produced a transient suppression followed by a long‐lasting facilitation of EPSPs. The facilitation was also seen in Cs(+)‐filled cells under voltage‐clamp conditions. Both suppressing and facilitating effects were blocked by atropine. 3. All components of the EPSP were reduced in the initial phase of ACh action, while only the slow component was enhanced during the later phase. The facilitation was blocked by an N‐methyl‐D‐aspartate (NMDA) receptor antagonist, d‐2‐amino‐5‐phosphonovalerate (2‐APV) and by hyperpolarization. 4. ACh also facilitated responses to ionophoretically applied NMDA in voltage‐clamped, Cs(+)‐filled cells in Ba2(+)‐treated slices. ACh facilitated responses to L‐glutamate which was blocked by 2‐APV. ACh failed to affect responses to kainate or quisqualate. 5. We conclude that ACh, acting on muscarinic receptors, exerts a primary effect in the hippocampus to specifically amplify NMDA receptor‐mediated synaptic responses and thereby facilitate EPSPs.
Nonnegative Tensor Factorization for Continuous EEG Classification

In this paper we present a method for continuous EEG classification, where we employ nonnegative tensor factorization (NTF) to determine discriminative spectral features and use the Viterbi algorithm to continuously classify multiple mental tasks. This is an extension of our previous work on the use of nonnegative matrix factorization (NMF) for EEG classification. Numerical experiments with two data sets in BCI competition, confirm the useful behavior of the method for continuous EEG classification.
Polymeric materials from natural resources - emerging as the times require

derived from non-renewable fossil oil. Environmental pollution has to be inevitably generated during their production. Besides, discards of the endproducts are hard to be degraded. For keeping in step with societal concerns on energy crisis and ecological problems, reduction in the usage of petrol-based materials becomes more and more important. As a result, natural polymers are receiving increasing attention. Since the traditional natural polymers (e.g., silk, rubber, etc.) cannot meet the tremendous needs of application in terms of species or properties, great efforts have to be continuously made to develop new polymers from natural resources. Compared to the non-degradable polymers from renewable resources, the materials that emulate the performance of petrol-based polymers while keeping biodegradability seem to be more promising. In fact, bio-based polymers have been under investigation for many years. Both chemical and microbial approaches proved to be feasible to convert natural substances. The successful examples in this aspect are cellulose plastics (from cotton, woods, etc.), polylactide (PLA, from corn, sugarcane, etc.), polyhydroxyalkanoate (PHA, from glucose), starch plastics and soybean plastics, etc. As mentioned above, however, many biodegradable polymers are based on food and feed, which are not cost-effective enough at present. Their applications have to be confined to some specific areas with high added value. In this context, manufacturing affordable and fully biodegradable polymers from annually renewable resources except food and feed coupled with low-cost processing techniques are critical. Attempts in this direction have been started, like plasticized wood sawdust, plant fibers reinforced plasticized wood sawdust, plasticized plant fibers, etc. Although achievements in the field of green polymers are far from satisfactory, the new opportunities that were found during research and development have demonstrated it is a challenging job to invent new species with balanced performance. Interdisciplinary studies based on tight collaboration among scientists and governmental supports are prerequisites for overcoming the difficulties. Moreover, enterprises should be actively involved because they will gain benefit from production and usage of these new materials in the long term.
PAC Learning Mixtures of Gaussians with No Separation Assumption

We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kearns et al. [12]. Here the task is to construct a hypothesis mixture of Gaussians that is statistically indistinguishable from the actual mixture generating the data; speciﬁcally, the KL divergence should be at most (cid:178) . In this scenario, we give a poly( n/(cid:178) ) time algorithm that learns the class of mixtures of any constant number of axis-aligned Gaussians in R n . Our algorithm makes no assumptions about the separation between the means of the Gaussians, nor does it have any dependence on the minimum mixing weight. This is in contrast to learning results known in the “clustering” model, where such assumptions are unavoidable. Our algorithm relies on the method of moments, and a subalgorithm developed in [8] for a discrete mixture-learning problem.
Rabs and other small GTPases in ciliary transport

The non‐motile primary cilium is a single, microtubule‐based hair‐like projection that emanates from most, if not all, non‐dividing mammalian cells. Enriched in a variety of signalling receptors and accessories, the cilium mediates crucial sensory and regulatory functions during development and postnatal tissue homoeostasis. Maintenance of ciliary morphology and function requires continuous IFT (intraflagellar transport), and recent findings have shed light on some molecular details of how ciliogenesis is dependent on targeted exocytic membrane trafficking from the Golgi. The ARL [Arf (ADP ribosylation factor)‐related] small GTPase Arf4 functions in TGN (trans‐Golgi network) sorting of cilia‐targeted rhodopsin into carrier vesicles, while Arl6 (Arf‐like 6) and Arl13b regulate aspects of ciliary transport and IFT. Ciliogenesis and ciliary functions are also regulated by small Rabs. Rab8a, in conjunction with Rab11a, and via its interaction with a multitude of proteins associated with the ciliary basal body and axoneme/membrane, appears to be critical for ciliogenesis. Rab8's close homologue Rab10 may also play a ciliogenic role in some cells. Rab23, the depletion or inactivation of which affects cilia formation, may regulate specific ciliary protein targeting and turnover, particularly those involved in Shh (Sonic hedgehog) signalling. Recent findings have also implicated Ran, a small GTPase better known for nuclear import, in ciliary targeting of the KIF17 motor protein. We highlight and discuss recent findings on how Rabs and other small GTPases mediate ciliogenesis and ciliary traffic.
Knowledge and Information Systems REGULAR PAPER

Tensor representation is helpful to reduce the small sample size problem in discriminative subspace selection. As pointed by this paper, this is mainly because the structure information of objects in computer vision research is a reasonable constraint to reduce the number of unknown parameters used to represent a learning model. Therefore, we apply this information to the vector-based learning and generalize the vector-based learning to the tensor-based learning as the supervised tensor learning (STL) framework, which accepts tensors as input. To obtain the solution of STL, the alternating projection optimization procedure is developed. The STL framework is a combination of the convex optimization and the operations in multilinear algebra. The tensor representation helps reduce the overfitting problem in vector-based learning. Based on STL and its alternating projection optimization procedure, we generalize support vector machines, minimax probability machine, Fisher discriminant analysis, and distance metric learning, to support tensor machines, tensor minimax probability machine, tensor Fisher discriminant analysis, and the multiple distance metrics learning, respectively. We also study the iterative procedure for feature extraction within STL. To examine the effectiveness of STL, we implement the tensor minimax probability machine for image classification. By comparing with minimax probability machine, the tensor version reduces the overfitting problem. D. Tao (B) · X. Li · S. J. Maybank School of Computer Science and Information Systems, Birkbeck, University of London, London, UK E-mail: dacheng.tao@gmail.com X. Wu Department of Computer Science, University of Vermont, Burlington, VT, USA W. Hu National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, P.R. China
Insertional depth-dependent intracochlear pressure changes in a model of cochlear implantation

Abstract Conclusion: Over time, a homogenous increase in intracochlear pressure was seen in every experiment. Significant reductions in terms of amplitude variation and insertion depth were observed over time, using the one-point-supported insertion method. The frequency of peaks between the thirds was significantly lower when using the two-points-supported insertion method. Objectives: The preservation of residual hearing and minimization of intracochlear trauma are two of the major goals in modern cochlear implantation (CI) surgery. It is assumed that intracochlear pressure measurements yield information about the intracochlear behavior of the electrode itself in the cochlea. The aim of this study was to investigate temporal intracochlear fluid pressure changes using two different kinds of insertion conditions. Method: Cochlear implantations with the Advanced Bionics IJ® electrode were performed in an artificial cochlear model with a constant insertional speed of 0.5 mm/s provided by a linear actor. Amplitude pressure changes and number of pressure peaks were evaluated for every part. Result: Intracochlear fluid pressure changes are assumed to affect the preservation of residual hearing and should be minimized. The stability and reduction of movement of a lateral wall IJ® electrode increase at deeper insertion and affect intracochlear fluid pressure amplitude.
Moisture‐induced effects on the tensile mechanical properties and glass‐transition temperature of poly(vinyl alcohol) films

In this study, the effect of sorbed water on the tensile mechanical properties of noncrosslinked, thermally treated poly(vinyl alcohol) (PVA) films was studied. The Young's modulus, elongation at break, and tensile strength of the PVA films equilibrated at different relative humidities (0–86%) are reported, together with the depression of the glass transition of the polymer at each equilibrating humidity, as determined by temperature-modulated differential scanning calorimetry. The results indicate that drastic changes in the tensile properties were correlated with the transition of the hydrated polymer from the glassy to the rubbery state. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011
Karakteristik Fisik Bubuk Kopi Arabika Hasil Penggilingan Mekanis dengan Penambahan Jagung dan Beras Ketan

Size reduction applied on Arabica Coffee bean may change its physical properties, where these properties are utilized for designing process including packaging and appliances for further processes. This research aims to investigate physical characteristics of Arabica coffee powder with addition of corn and rice milled through mechanical process. This experiment used two mechanical mills including hammer mill and disc mill. Before it is milled, coffee was mixed with other materials including corn and rice. Parameters observed were yield, moisture content, bulk density, and angle of respose, particle uniformity index, fineness modulus, and the average particle dimensions. Based on the results obtained, it was revealed that moisture content of each test still meet SNI standard with the maximum of 7%. Bulk density of coffee powder resulted using disc mill was higher compared with hammer mill. However, particle generated from milling process may be categorized as powder with medium cohesiveness based on its angle of repose. Dimensional average particle is proportional to the fineness modulus of coffee powder produced. Highest fineness modulus obtained from coffee powder without additives, and using a hammer mill is equal to 4.37 with the highest average dimensions of 2.05 mm, while the lowest fineness modulus that the coffee powder without any additional ingredients milled with a hammer mill is equal to 4.22, with the lowest average dimensions of 1.94 mm.
Development of a Fluorescence-based Trypanosoma cruzi CYP51 Inhibition Assay for Effective Compound Triaging in Drug Discovery Programmes for Chagas Disease

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life threatening global health problem with only two drugs available for treatment (benznidazole and nifurtimox), both having variable efficacy in the chronic stage of the disease and high rates of adverse drug reactions. Inhibitors of sterol 14α-demethylase (CYP51) have proven effective against T. cruzi in vitro and in vivo in animal models of Chagas disease. Consequently two azole inhibitors of CYP51 (posaconazole and ravuconazole) have recently entered clinical development by the Drugs for Neglected Diseases initiative. Further new drug treatments for this disease are however still urgently required, particularly having a different mode of action to CYP51 in order to balance the overall risk in the drug discovery portfolio. This need has now been further strengthened by the very recent reports of treatment failure in the clinic for both posaconazole and ravuconazole. To this end and to prevent enrichment of drug candidates against a single target, there is a clear need for a robust high throughput assay for CYP51 inhibition in order to evaluate compounds active against T. cruzi arising from phenotypic screens. A high throughput fluorescence based functional assay using recombinantly expressed T. cruzi CYP51 (Tulahuen strain) is presented here that meets this requirement. This assay has proved valuable in prioritising medicinal chemistry resource on only those T. cruzi active series arising from a phenotypic screening campaign where it is clear that the predominant mode of action is likely not via inhibition of CYP51.
Molecular Interplay between microRNA-34a and Sirtuin1 in Hyperglycemia-Mediated Impaired Angiogenesis in Endothelial Cells: Effects of Metformin

Impaired angiogenesis is a prominent risk factor that contributes to the development of diabetes-associated cardiovascular disease. MicroRNAs (miRNAs), small noncoding RNAs, are implicated as important regulators of vascular function, including endothelial cell differentiation, proliferation, and angiogenesis. In silico analysis and in vitro studies indicate that silent information regulator 1 (SIRT1) is a potential target for endothelial cell–specific miRNAs. In this study, we investigated the molecular crosstalk between miR-34a, the protein product of SIRT1 (sirtuin1), and the antidiabetic drug, metformin, in hyperglycemia-mediated impaired angiogenesis in mouse microvascular endothelial cells (MMECs). MMECs were cultured, transfected with either a miR-34a inhibitor or mimic in normal glucose (11 mM) or high glucose (HG, 40 mM) in the presence or absence of metformin. The expression of miR-34a, sirtuin1, and their signaling targets was evaluated. miR-34a expression is upregulated in a hyperglycemic milieu and parallels changes in the expression of sirtuin1, post-translational modification of endothelial nitric oxide synthase (phospho/acetylation), as well as an impairment in angiogenesis. The presence of metformin, or the inhibition of miR-34a using an anti–miR-34a inhibitor, increases the expression of sirtuin1 and attenuates the impairment in angiogenesis in HG-exposed MMECs. In contrast, overexpression of a miR-34a mimic prevents metformin-mediated protection. These data indicate that miR-34a, via the regulation of sirtuin1 expression, has an anti-angiogenic action in MMECs, which can be modulated by metformin. In summary, miR-34a represents both a target whereby metformin mediates its vasculoprotective actions and also a potential therapeutic target for the prevention/treatment of diabetic vascular disease.
Parallel Passive Testing of System Protocols - Towards a Real-time Exhaustive Approach

Passive testing has proved to be a powerful technique for protocol system fault detection by observing its input/output behaviors yet without interrupting its normal operations. Various techniques for passive testing on Extended Finite State Machine (EFSM) exist such as by invariants and by interval determination, which are not very costy in terms of complexity but that also don’t detect every errors. To improve the fault detection capabilities a backward checking method was proposed. It analyzes in a backward fashion the input/output trace from passive testing and its past. It effectively checks both the control and data portion of a protocol system and is able to detect every errors, but with a higher complexity. The purpose of the present paper is then to propose possible parallel algorithms and architectures to improve the backward passive testing approach by narrowing down its maximal time complexity and transforming it into the first real-time exhaustive passive testing approach. We present the backward algorithm and its parallel versions, study their complexity, and report results on various communication and routing protocols.
Information-limiting correlations ” 1 Supplemental Modeling

Contents Page 1. Notation 1 2. A recurrent network of integrate and fire neurons 2 3. A feedforward network of non-leaky integrate and fire neurons 15 4. Information for a " pure " f f component 17 5. Detecting differential correlations 24 6. Empirically estimating information 27