Miracle-dz/UniFAR-FTUs huggingface dataset:
The novel combination of dual mTOR inhibitor AZD2014 and pan-PIM inhibitor AZD1208 inhibits growth in acute myeloid leukemia via HSF pathway suppression

Mammalian target of rapamycin (mTOR) signaling is a critical pathway in the biology of acute myeloid leukemia (AML). Proviral integration site for moloney murine leukemia virus (PIM) serine/threonine kinase signaling takes part in various pathways exerting tumorigenic properties. We hypothesized that the combination of a PIM kinase inhibitor with an mTOR inhibitor might have complementary growth-inhibitory effects against AML. The simultaneous inhibition of the PIM kinase by pan-PIM inhibitor AZD1208 and of mTOR by selective mTORC1/2 dual inhibitor AZD2014 exerted anticancer properties in AML cell lines and in cells derived from primary AML samples with or without supportive stromal cell co-culture, leading to suppressed proliferation and increased apoptosis. The combination of AZD1208 and AZD2014 rapidly activated AMPKα, a negative regulator of translation machinery through mTORC1/2 signaling in AML cells; profoundly inhibited AKT and 4EBP1 activation; and suppressed polysome formation. Inhibition of both mTOR and PIM counteracted induction of heat-shock family proteins, uncovering the master negative regulation of heat shock factor 1 (HSF1), the dominant transcription factor controlling cellular stress responses. The novel combination of the dual mTOR inhibitor and pan-PIM inhibitor synergistically inhibited AML growth by effectively reducing protein synthesis through heat shock factor pathway suppression.
Differentiation Between Somatic and Cognitive/Affective Components in Commonly Used Measurements of Depression in Patients with Chronic Low-Back Pain: Let's Not Mix Apples and Oranges

Patients with chronic low-back pain are frequently diagnosed as depressed. However, many of the neurovegetative signs of depression may also result from pain. The purpose of the present study was 1) to investigate the relationship between commonly used measurements of depression and pain perception; and 2) to examine the utility of differentiating between somatic signs and cognitive/affective symptoms of depression in patients with chronic low-back pain. The Beck Depression Inventory and the Hamilton Psychiatric Rating Scale for Depression were divided into cognitive/affective and somatic subscales. These measures, as well as the Minnesota Multiphasic Personality Inventory, were administered to 111 patients with chronic low-back pain. Analyses revealed significant correlations between depression scores and self-reported pain intensity. The cognitive/affective subscale of the Beck Depression Inventory resulted in the only nonsignificant correlation with pain intensity. These findings suggest that commonly used measurements of depression are confounded with pain symptomatology and that the cognitive/affective category of the Beck Depression Inventory may prove to be a more accurate measurement of depression in patients with chronic low-back pain.
Migration and distribution of two populations of hippocampal granule cell precursors during the perinatal and postnatal periods

Methacrylate‐embedded sections and short‐survival thymidine radiograms of the hippocampal dentate gyrus were examined in perinatal and postnatal rats in order to trace the site of origin and migration of the precursors of granule cells and study the morphogenesis of the granular layer. The densely packed, spindle‐shaped cells of the secondary dentate matrix (a derivative of the primary dentate neuroepithelium) stream in a subpial position towards the granular layer of the internal dentate limb during the perinatal and early postnatal periods. By an accretionary process, the crest of the granular layer forms on day E21 and on the subsequent days the granular layer of the internal dentate limb expands progressively in a lateral direction. Granule cells differentiation, as judged by the transformation of polymorph, darkly staining small cells into rounder, lightly staining larger granule cells, follows the same gradient from the external dentate limb to the internal dentate limb. The secondary dentate matrix is in a process of dissolution by day P5. This matrix is the source of what will later become the outer shell of the granular layer composed of early generated granule cells. The thicker inner shell of the granular layer, formed during the infantile and juvenile periods, derives from an intrinsic, tertiary germinal matrix. On day E22, the dentate migration of the secondary dentate matrix becomes partitioned into two components: (a) the subpial component of extradentate origin, referred to in this context as the first dentate migration, and (b) the second dentate migration. The latter is distributed in the basal polymorph layer throughout the entire dentate gyrus and is henceforth recognized as the tertiary dentate matrix. The tertiary dentate matrix is prominent between days P3 and P10. It is postulated that the great increase in granule cell population during the infantile period is principally due to cells derived from this intrinsic matrix of the dentate gyrus. Between days P20 and P30 the tertiary dentate matrix disappears in the basal polymorph layer and henceforth proliferative cells become largely confined to the subgranular zone at the base of the granular layer. The subgranular zone is the source of granule cells produced during the juvenile and adult periods.
An Analytical Approach for Soft Error Rate Estimation of SRAM-Based FPGAs

SRAM-based FPGAs are increasingly becoming more popular in applications where high dependability, low cost, and fast time-tomarket are important constraints. However, these devices are more susceptible to single-event upsets (SEUs) compared ASIC designs. The error models of SRAM-based due to SEUs are more complicated than those of ASICs since soft-errors in the configuration memory result in permanent errors in the user application. In this work, we investigate different error models for SRAM-based FPGAs due to soft errors and present analytical soft error rate estimation for these devices.
Empirical potential function for simplified protein models: Combining contact and local sequence–structure descriptors

An effective potential function is critical for protein structure prediction and folding simulation. Simplified protein models such as those requiring only Cα or backbone atoms are attractive because they enable efficient search of the conformational space. We show residue‐specific reduced discrete‐state models can represent the backbone conformations of proteins with small RMSD values. However, no potential functions exist that are designed for such simplified protein models. In this study, we develop optimal potential functions by combining contact interaction descriptors and local sequence–structure descriptors. The form of the potential function is a weighted linear sum of all descriptors, and the optimal weight coefficients are obtained through optimization using both native and decoy structures. The performance of the potential function in a test of discriminating native protein structures from decoys is evaluated using several benchmark decoy sets. Our potential function requiring only backbone atoms or Cα atoms have comparable or better performance than several residue‐based potential functions that require additional coordinates of side‐chain centers or coordinates of all side‐chain atoms. By reducing the residue alphabets down to size 10 for contact descriptors, the performance of the potential function can be further improved. Our results also suggest that local sequence–structure correlation may play important role in reducing the entropic cost of protein folding. Proteins 2006. © 2006 Wiley‐Liss, Inc.
Spectrally Constrained Waveform Design [sp Tips&Tricks]

In active sensing, transmitters emit probing waveforms into the environment. The probing waveforms interact with scatters that reflect distorted copies of the waveforms. Receivers then measure the distorted copies to infer information about the environment. The choice of the probing waveform is important because it affects slant range resolution, Doppler tolerance, clutter, and electronic countermeasures. A traditional performance metric for the probing waveform is the ambiguity function, which describes the correlation between the waveform and a delayed and (narrow-band) Doppler shifted copy of the same waveform [1]. The direct synthesis of a waveform given a desired ambiguity function is exceedingly difficult [2]. Often designers focus on optimizing only the waveform's autocorrelation function (which is the zero Doppler cut of the ambiguity function). Any method that optimizes the autocorrelation function is implicitly performing spectral shaping by trying to flatten the passband of the waveform's spectrum [1], [2].
Extracting spatially and spectrally coherent regions from multispectral images

Extracting spectrally homogeneous regions as features from hyperspectral and multispectral raster data has unique challenges when accurate shape preservation is a priority. We tackle this task by representing neighborhoods that contain heterogeneously classified pixels as a graph. We then use graph-cut based combinatorial optimization to eliminate spuriously classified pixels. After the region of interest is uniformly classified, we use a vectorization step to extract it as a feature.
Pulmonary embolism rule-out criteria (PERC) in pulmonary embolism—revisited: A systematic review and meta-analysis

Objectives To perform a systematic review and meta-analysis including all the current studies to assess the accuracy of pulmonary embolism rule-out criteria (PERC) in ruling out pulmonary embolism (PE). Methods We conducted a comprehensive search of the major databases (Ovid Medline In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Ovid PsycInfo, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews and Scopus) and references of potentially eligible articles and conference proceedings of major emergency medicine organisations through May 2012. We included all original research studies conducted in emergency departments on diagnostic performance of PERC. Two reviewers independently identified the eligible studies and extracted data. Sensitivity, specificity and likelihood ratios were calculated using contingency tables. Results 12 studies including 13 cohorts (three retrospective, 10 prospective) were included, comprising of 14 844 patients from six countries. 12 cohorts were urban and one was rural. Pooled (95% CI) sensitivity, specificity, positive and negative likelihood ratio were 0.97 (0.96 to 0.98), 0.22 (0.22 to 0.23), 1.22 (1.16 to 1.29) and 0.17 (0.13 to 0.23), respectively. The pooled (95% CI) diagnostic OR was 7.4 (5.5–9.8). On meta-regression analysis, there was no significant difference between PE prevalence and PERC diagnostic performance (coefficient (SE) of −0.032 (0.022), p=0.173) or on relative diagnostic OR (0.97, 95% CI 0.92 to 1.02). Significant heterogeneity was observed in specificity (I2=97.4%) and positive likelihood ratio (I2=89.1%). Conclusions Because of the high sensitivity and low negative likelihood ratio, PERC rule can be used confidently in clinically low probability population settings.
Routing Policy Specification Language (RPSL)

RPSL allows a network operator to be able to specify routing policies at various levels in the Internet hierarchy; for example at the Autonomous System (AS) level. At the same time, policies can be specified with sufficient detail in RPSL so that low level router configurations can be generated from them. RPSL is extensible; new routing protocols and new protocol features can be introduced at any time.
Outcome of ABCA4 microarray screening in routine clinical practice

Purpose To retrospectively analyze the clinical characteristics of patients who were screened for mutations with the ATP-binding cassette transporter gene ABCA4 (ABCA4) microarray in a routine clinical DNA diagnostics setting. Methods We performed a retrospective analysis of the medical charts of 65 patients who underwent an ABCA4 microarray screening between the years 2002 and 2006. An additional denaturing gradient gel electrophoresis (DGGE) was performed in these patients if less than two mutations were found with the microarray. We included all patients who were suspected of autosomal recessive Stargardt disease (STGD1), autosomal recessive cone–rod dystrophy (arCRD), or autosomal recessive retinitis pigmentosa at the time of microarray request. After a retrospective analysis of the clinical characteristics, the patients who were suspected of STGD1 were categorized as having either a typical or atypical form of STGD1, according to the age at onset, fundus appearance, fluorescein angiography, and electroretinography. The occurrence of typical clinical features for STGD1 was compared between patients with different numbers of discovered mutations. Results Of the 44 patients who were suspected of STGD1, 26 patients (59%) had sufficient data available for a classification in either typical (six patients; 23%) or atypical (20 patients; 77%) STGD1. In the suspected STGD1 group, 59% of all expected pathogenic alleles were found with the ABCA4 microarray. DGGE led to the finding of 12 more mutations, resulting in an overall detection rate of 73%. Thirty-one percent of patients with two or three discovered ABCA4 mutations met all typical STGD1 criteria. An age at onset younger than 25 years and a dark choroid on fluorescein angiography were the most predictive clinical features to find ABCA4 mutations in patients suspected of STGD1. In 18 patients suspected of arCRD, microarray screening detected 22% of the possible pathogenic alleles. Conclusions In addition to confirmation of the diagnosis in typical STGD1, ABCA4 microarray screening is usually requested in daily clinical practice to strengthen the diagnosis when the disease is atypical. This study supports the view that the efficiency and accuracy of ABCA4 microarray screening are directly dependent upon the clinical features of the patients who are screened.
Multiple view reconstruction of people

This work presents a unified framework for model-based and model-free reconstruction of people from multiple camera views in a studio environment. Shape and appearance of the reconstructed model are optimised simultaneously based on multiple view silhouette, stereo and feature correspondence. A priori knowledge of surface structure is introduced as regularisation constraints. Model-based reconstruction assumes a known generic lutmanoid model a priori, which is fitted to the multi-view observations to produce a structured representation for animation. Model-free reconstruction makes no priori assumptions on scene geometry allowing the reconstruction of complex dynamic scenes. Results are presented for reconstruction of sequences of people from multiple views. The model-based approach produces a consistent structured representation, which is robust in the presence of visual ambiguities. This overcomes limitations of existing visual-hull and stereo techniques. Model-free reconstruction allows high-quality novel view-synthesis with accurate reproduction of the detailed dynamics for hair and loose clothing. Multiple view optimisation achieves a visual quality comparable to the captured video without visual artefacts due to misalignment of images.
Two apextrin-like proteins mediate extracellular and intracellular bacterial recognition in amphioxus

Significance Microbial specific pathogen-associated molecular patterns (PAMPs) constitute a key feature by which a host organism detects the presence of microbes and mounts specific immune responses. Here, we report the discovery of two proteins (bjALP1 and 2) that interact with muramyl dipeptide, a pan-bacterial specific PAMP via a novel pattern recognition domain ApeC. Our studies have revealed that bjALP1 is a secreted immune effector, whereas bjALP2 functions as an intracellular pattern recognition receptor (PRR), both having an important role in protecting the host from microbial pathogens. Specifically, bjAPL1 functions in the extracellular space to reduce the harmful effect of pathogenic microbes, whereas bjALP2 functions as a PRR that serves as a sentinel for intracellular bacterial invasion. Animals exploit different germ-line-encoded proteins with various domain structures to detect the signature molecules of pathogenic microbes. These molecules are known as pathogen-associated molecular patterns (PAMPs), and the host proteins that react with PAMPs are called pattern recognition proteins (PRPs). Here, we present a novel type of protein domain structure capable of binding to bacterial peptidoglycan (PGN) and the minimal PGN motif muramyl dipeptide (MDP). This domain is designated as apextrin C-terminal domain (ApeC), and its presence was confirmed in several invertebrate phyla and subphyla. Two apextrin-like proteins (ALP1 and ALP2) were identified in a basal chordate, the Japanese amphioxus Branchiostoma japonicum (bj). bjALP1 is a mucosal effector secreted into the gut lumen to agglutinate the Gram-positive bacterium Staphylococcus aureus via PGN binding. Neutralization of secreted bjALP1 by anti-bjALP1 monoclonal antibodies caused serious damage to the gut epithelium and rapid death of the animals after bacterial infection. bjALP2 is an intracellular PGN sensor that binds to TNF receptor-associated factor 6 (TRAF6) and prevents TRAF6 from self-ubiquitination and hence from NF-κB activation. MDP was found to compete with TRAF6 for bjALP2, which released TRAF6 to activate the NF-κB pathway. BjALP1 and bjALP2 therefore play distinct and complementary functions in amphioxus gut mucosal immunity. In conclusion, discovery of the ApeC domain and the functional analyses of amphioxus ALP1 and ALP2 allowed us to define a previously undocumented type of PRP that is represented across different animal phyla.
"Zázemí" a "bojiště" v usilování o spravedlnost: textová analýza odborářské, feministické a lidskoprávní mediální komunikace*

The study is a computer-assisted text analysis of corpora obtained from the web pages of nine volunteer, non-governmental organisations and interest groups. The analysis encompasses three areas of justice claims: trade unions (the relationship between employers and employees), feminism (the relationship be- tween men and women), and human rights (the relationship between citizens, foreign nationals, and the state). The aim of the study, based on Foucaultian con- cepts, is to determine whether media communications are structured by the for- mative impact of the discourse of claim-making or justice. The main findings re- late both to the content and the structure of textual production. First, the organ- isations examined do not make frequent use of normatively loaded words in their statements. The matter of justice is implicit in their texts. Second, the struc- ture of the statements, represented by the thirty most frequently used words, ex- hibits a common pattern in all three areas studied. At the one end of the 'state- ment spectrum', there are words referring to the social situation of the contest- ing actors ('background'), while at the opposite end, words used in reference to their 'battlefield' (claim-making, bargaining and decision making) appear. This polar structure supports the hypothesis that the media communications of se- lected activist groups are influenced by the discourse of claim-making or justice. Sociologický casopis/Czech Sociological Review, 2006, Vol. 42, No. 2: 269-290
Comparison of sparse least squares support vector regressors trained in primal and dual

In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this paper we develop sparse LS SVRs trained in the dual form in the empirical feature space. Namely, first the support vectors that span the reduced empirical feature space are selected by the Cholesky factorization and LS SVR is trained in the dual form by solving a set of linear equations. We compare the computational cost of the LS SVRs in the primal and dual form and clarify that if the dimension of the reduced empirical feature space is almost equal to the number of training data, the dual form is faster. But the primal form is computationally more stable and for the large margin parameter the coefficient matrix of the dual form becomes near singular. By computer experiments using some benchmarkdata sets we verify the above results.
Microcontroller based DC-DC Cascode Buck-Boost Converter

In this paper DC-DC Cascode Buck-Boost Converter is proposed by using two buck-boost converter. The structure of the proposed convert is very simple and the switching operation is done by using one active switch IGBT. The Buck-Boost Converters are named as higher semi stage and lower semi stage. The input DC supply to the lower semi stage converter is given by means of the input DC supply and the input to the higher semi stage is given by means of DC supply and the output voltage of the lower semi stage converter. Thus overall output voltage is given by the output sum of individual semi stage converters by cascode. Hence, from this Cascode DC-DC Converter can achieve a very high output voltage gain in a single stage without having an extreme high duty ratio. The input pulse to the active switch IGBT is given by Arduino. The operating principle and steady analysis are discussed in detail in this paper and also the voltage gain is compared with the conventional Boost converter, Buck-Boost converter and Cuk converter. The dynamic analysis of complete circuit is analyzed and MATLAB/Simulink simulation is done and finally to verify the proposed cascode converter laboratory experiment of 50W has been implemented to test both the simulation and experimental result.
Using Syntactic Dependencies to Solve Coreferences

This paper describes the structure of the LTH coreference solver used in the closed track of the CoNLL 2012 shared task (Pradhan et al., 2012). The solver core is a mention classifier that uses Soon et al. (2001)'s algorithm and features extracted from the dependency graphs of the sentences. This system builds on Bjorkelund and Nugues (2011)'s solver that we extended so that it can be applied to the three languages of the task: English, Chinese, and Arabic. We designed a new mention detection module that removes pleonastic pronouns, prunes constituents, and recovers mentions when they do not match exactly a noun phrase. We carefully redesigned the features so that they reflect more complex linguistic phenomena as well as discourse properties. Finally, we introduced a minimal cluster model grounded in the first mention of an entity. We optimized the feature sets for the three languages: We carried out an extensive evaluation of pairs of features and we complemented the single features with associations that improved the CoNLL score. We obtained the respective scores of 59.57, 56.62, and 48.25 on English, Chinese, and Arabic on the development set, 59.36, 56.85, and 49.43 on the test set, and the combined official score of 55.21.