Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Ambient Air Pollution on Hemostasis and Inflammation

Background Air pollution has consistently been associated with increased morbidity and mortality due to respiratory and cardiovascular disease. Underlying biological mechanisms are not entirely clear, and hemostasis and inflammation are suggested to be involved. Objectives Our aim was to study the association of the variation in local concentrations of airborne particulate matter (PM) with aerodynamic diameter < 10 μm, carbon monoxide, nitrogen monoxide, nitrogen dioxide, and ozone with platelet aggregation, thrombin generation, fibrinogen, and C-reactive protein (CRP) levels in healthy individuals. Methods From 40 healthy volunteers, we collected 13 consecutive blood samples within a 1-year period and measured light-transmittance platelet aggregometry, thrombin generation, fibrinogen, and CRP. We performed regression analysis using generalized additive models to study the association between the hemostatic and inflammatory variables, and local environmental concentrations of air pollutants for time lags within 24 hr before blood sampling or 24–96 hr before blood sampling. Results In general, air pollutants were associated with platelet aggregation [average, +8% per interquartile range (IQR), p < 0.01] and thrombin generation (average, +1% per IQR, p < 0.05). Platelet aggregation was not affected by in vitro incubation of plasma with PM. We observed no relationship between any of the air pollutants and fibrinogen or CRP levels. Conclusions Air pollution increased platelet aggregation as well as coagulation activity but had no clear effect on systemic inflammation. These prothrombotic effects may partly explain the relationship between air pollution and the risk of ischemic cardiovascular disease.
Lower Bounds on the Correlation Property for OFDM Sequences with Spectral-Null Constraints

Sequences with specific autocorrelation (AC) and cross-correlation (CC) properties are crucial components in radar and wireless communications. In this paper, we derive the theoretical bounds on the AC and CC for OFDM sequences with constraints of spectral nulls, e.g., the mandatory nulls on the DC sub-carrier and guardbands in OFDM systems. The bounds and trade-off limits are provided for the properties of sequences, including the peak AC and CC levels, the cardinality of the sequence set, the sequence length, and the temporal length of the low correlation zone. We also investigate the trade-offs of correlations among sequence sets. The presented trade-off limits can serve as guidelines for applications where the performance measures or design criteria are related to the peak AC and CC levels.
DPM1, the Catalytic Subunit of Dolichol-phosphate Mannose Synthase, Is Tethered to and Stabilized on the Endoplasmic Reticulum Membrane by DPM3*

Dolichol-phosphate mannose (DPM) synthase is required for synthesis of the glycosylphosphatidylinositol (GPI) anchor, N-glycan precursor, protein O-mannose, and C-mannose. We previously identified DPM3, the third component of this enzyme, which was co-purified with DPM1 and DPM2. Here, we have established mutant Chinese hamster ovary (CHO) 2.38 cells that were defective in DPM3. CHO2.38 cells were negative for GPI-anchored proteins, and microsomes from these cells showed no detectable DPM synthase activity, indicating that DPM3 is an essential component of this enzyme. A coiled-coil domain near the C terminus of DPM3 was important for tethering DPM1, the catalytic subunit of the enzyme, to the endoplasmic reticulum membrane and, therefore, was critical for enzyme activity. On the other hand, two transmembrane regions in the N-terminal portion of DPM3 showed no specific functions. DPM1 was rapidly degraded by the proteasome in the absence of DPM3. Free DPM1 was strongly associated with the C terminus of Hsc70-interacting protein (CHIP), a chaperone-dependent E3 ubiquitin ligase, suggesting that DPM1 is ubiquitinated, at least in part, by CHIP.
Self-Organization of the Neuron Collective of Optimal Complexity

The optimal complexity of neural networks is achieved when the self-organization principles is used to eliminate the contradictions existing in accor dance with the K. Godel’s theor em a bout incompleteness of the systems based on axiomatics. The principle of S. Beer’s exterior addition the Heuristic Group Method of Data Handling by A. Ivakhnenko realized is used.
The Role of MicroRNAs in Regulatory T Cells and in the Immune Response

The discovery of microRNA (miRNA) is one of the major scientific breakthroughs in recent years and has revolutionized current cell biology and medical science. miRNAs are small (19~25nt) noncoding RNA molecules that post-transcriptionally regulate gene expression by targeting the 3' untranslated region (3'UTR) of specific messenger RNAs (mRNAs) for degradation of translation repression. Genetic ablation of the miRNA machinery, as well as loss or degradation of certain individual miRNAs, severely compromises immune development and response, and can lead to immune disorders. Several sophisticated regulatory mechanisms are used to maintain immune homeostasis. Regulatory T (Treg) cells are essential for maintaining peripheral tolerance, preventing autoimmune diseases and limiting chronic inflammatory diseases. Recent publications have provided compelling evidence that miRNAs are highly expressed in Treg cells, that the expression of Foxp3 is controlled by miRNAs and that a range of miRNAs are involved in the regulation of immunity. A large number of studies have reported links between alterations of miRNA homeostasis and pathological conditions such as cancer, cardiovascular disease and diabetes, as well as psychiatric and neurological diseases. Although it is still unclear how miRNA controls Treg cell development and function, recent studies certainly indicate that this topic will be the subject of further research. The specific circulating miRNA species may also be useful for the diagnosis, classification, prognosis of diseases and prediction of the therapeutic response. An explosive literature has focussed on the role of miRNA. In this review, I briefly summarize the current studies about the role of miRNAs in Treg cells and in the regulation of the innate and adaptive immune response. I also review the explosive current studies about clinical application of miRNA.
Habitat Predicts Levels of Genetic Admixture in Saccharomyces cerevisiae

Genetic admixture can provide material for populations to adapt to local environments, and this process has played a crucial role in the domestication of plants and animals. The model yeast, Saccharomyces cerevisiae, has been domesticated multiple times for the production of wine, sake, beer, and bread, but the high rate of admixture between yeast lineages has so far been treated as a complication for population genomic analysis. Here, we make use of the low recombination rate at centromeres to investigate admixture in yeast using a classic Bayesian approach and a locus-by-locus phylogenetic approach. Using both approaches, we find that S. cerevisiae from stable oak woodland habitats are less likely to show recent genetic admixture compared with those isolated from transient habitats such as fruits, wine, or human infections. When woodland yeast strains do show recent genetic admixture, the degree of admixture is lower than in strains from other habitats. Furthermore, S. cerevisiae populations from oak woodlands are genetically isolated from each other, with only occasional migration between woodlands and local fruit habitats. Application of the phylogenetic approach suggests that there is a previously undetected population in North Africa that is the closest outgroup to the European S. cerevisiae, including the domesticated Wine population. Careful testing for admixture in S. cerevisiae leads to a better understanding of the underlying population structure of the species and will be important for understanding the selective processes underlying domestication in this economically important species.
Mapping Above-Ground Biomass by Integrating Optical and SAR Imagery: A Case Study of Xixi National Wetland Park, China

Wetlands are important ecosystems as they are known as the “kidney of the earth”. Particularly, urban wetlands play an important role in providing both natural and social beneficial services. However, urban wetlands are suffering from various human impacts, such as excessive land use conversion, air and water pollution, especially those in developing countries undergoing rapid industrialization and urbanization. Therefore, it is of great necessity to derive timely biomass information for optimal design, management and protection of urban wetlands. In this paper, we develop a set of models for estimating above ground biomass (AGB) in Xixi National Wetland Park in Hangzhou, China by using optical images and Synthetic Aperture Radar (SAR) images. A series of vegetation indices (VIs) derived from optical data is introduced along with spectral data. The modeling methods consist of (1) curve estimation; (2) linear regression for multivariable model; (3) Back Propagation Neural Network (BPNN) modeling. Curve estimation is a combination of linear and nonlinear regressions. It is applied to generate AGB models from a single variable including Normalized Difference Vegetation Index (NDVI) and radar backscatter coefficient. The models are then compared via three accuracy metrics. According to the results, SAR models generally show better accuracy than optical models and BPNN models show the greatest accuracy among all the models. The BPNN model from the combination of Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and European Remote-Sensing Satellite-2 (ERS-2) SAR (Synthetic Aperture Radar) image has the least root mean square (RMSE, 0.396 kg/m2), least mean absolute error (MAE, 0.256 kg/m2) and the greatest correlation coefficient (0.974). The results indicate that AGB can be estimated by integrating optical and SAR imagery. Four maps of AGB are derived to illustrate the distribution of AGB in the study area. The total AGB in the study area is estimated to be between 165,000 and 210,000 kg/m2.
Blockade of Interleukin-12 Function by Protein Vaccination Attenuates Atherosclerosis

Background—Interleukin-12 (IL-12) has been identified as a key inducer of a type 1 T-helper cell cytokine pattern, which is thought to contribute to the development of atherosclerosis. We sought to study the role of IL-12 in atherosclerosis by inhibition of IL-12 using a newly developed vaccination technique that fully blocks the action of IL-12. Methods and Results—LDL receptor–deficient (LDLr−/−) mice were vaccinated against IL-12 by 5 intramuscular injections of IL-12–PADRE complex in combination with adjuvant oil-in-water emulsion (low dose)/MPL/QS21 every 2 weeks. Two weeks thereafter, atherogenesis was initiated in the carotid artery by perivascular placement of silicone elastomer collars. IL-12 vaccination resulted in the induction of anti–IL-12 antibodies that functionally blocked the action of IL-12 as determined in an IL-12 bioassay. Blockade of IL-12 by vaccination of LDLr−/− mice resulted in significantly reduced (68.5%; P<0.01) atherogenesis compared with control mice without a change in serum cholesterol levels. IL-12 vaccination also resulted in a significant decrease in intima/media ratios (66.7%; P<0.01) and in the degree of stenosis (57.8%; P<0.01). On IL-12 vaccination, smooth muscle cell and collagen content in the neointima increased 2.8-fold (P<0.01) and 4.2-fold (P<0.01), respectively. Conclusions—Functional blockade of endogenous IL-12 by vaccination resulted in a significant 68.5% reduction in atherogenesis in LDLr−/− mice. Vaccination against IL-12 also improved plaque stability, from which we conclude that the blockade of IL-12 by vaccination may be considered a promising new strategy in the treatment of atherosclerosis.
A Meta-Analysis of Interventions for Struggling Readers in Grades 4–12

This meta-analysis synthesizes the literature on interventions for struggling readers in Grades 4 through 12 published between 1980 and 2011. It updates Scammacca et al.’s analysis of studies published between 1980 and 2004. The combined corpus of 82 study-wise effect sizes was meta-analyzed to determine (a) the overall effectiveness of reading interventions studied over the past 30 years, (b) how the magnitude of the effect varies based on student, intervention, and research design characteristics, and (c) what differences in effectiveness exist between more recent interventions and older ones. The analysis yielded a mean effect of 0.49, considerably smaller than the 0.95 mean effect reported in 2007. The mean effect for standardized measures was 0.21, also much smaller than the 0.42 mean effect reported in 2007. The mean effects for reading comprehension measures were similarly diminished. Results indicated that the mean effects for the 1980–2004 and 2005–2011 groups of studies were different to a statistically significant degree. The decline in effect sizes over time is attributed at least in part to increased use of standardized measures, more rigorous and complex research designs, differences in participant characteristics, and improvements in the school’s “business-as-usual” instruction that often serves as the comparison condition in intervention studies.
Optimal Control of Wireless Networks with Finite Buffers

This paper considers network control for wireless networks with finite buffers. We investigate the performance of joint flow control, routing, and scheduling algorithms which achieve high network utility and deterministically bounded backlogs inside the network. Our algorithms guarantee that buffers inside the network never overflow. We study the tradeoff between buffer size and network utility and show that if internal buffers have size (N-1)/&#949; then a high fraction of the maximum utility can be achieved, where &#949; captures the loss in utility and N is the number of network nodes. The underlying scheduling/routing component of the considered control algorithms requires ingress queue length information (IQI) at all network nodes. However, we show that these algorithms can achieve the same utility performance with delayed ingress queue length information. Numerical results reveal that the considered algorithms achieve nearly optimal network utility with a significant reduction in queue backlog compared to the existing algorithm in the literature. Finally, we discuss extension of the algorithms to wireless networks with time-varying links.
Position and distance specificity are important determinants of cis-regulatory motifs in addition to evolutionary conservation

Computational discovery of cis-regulatory elements remains challenging. To cope with the high false positives, evolutionary conservation is routinely used. However, conservation is only one of the attributes of cis-regulatory elements and is neither necessary nor sufficient. Here, we assess two additional attributes—positional and inter-motif distance specificity—that are critical for interactions between transcription factors. We first show that for a greater than expected fraction of known motifs, the genes that contain the motifs in their promoters in a position-specific or distance-specific manner are related, both in function and/or in expression pattern. We then use the position and distance specificity to discover novel motifs. Our work highlights the importance of distance and position specificity, in addition to the evolutionary conservation, in discovering cis-regulatory motifs.
Spoken document summarization using relevant information

Extractive summarization usually automatically selects indicative sentences from a document according to a certain target summarization ratio, and then sequences them to form a summary. In this paper, we investigate the use of information from relevant documents retrieved from a contemporary text collection for each sentence of a spoken document to be summarized in a probabilistic generative framework for extractive spoken document summarization. In the proposed methods, the probability of a document being generated by a sentence is modeled by a hidden Markov model (HMM), while the retrieved relevant text documents are used to estimate the HMM's parameters and the sentence's prior probability. The results of experiments on Chinese broadcast news compiled in Taiwan show that the new methods outperform the previous HMM approach.
Lamin B Counteracts the Kinesin Eg5 to Restrain Spindle Pole Separation during Spindle Assembly*

Lamin B is a component of the membranous spindle matrix isolated from Xenopus egg extracts, and it is required for proper spindle morphogenesis. Besides lamin B, the spindle matrix contains spindle assembly factors (SAFs) such as Eg5 and dynein which are known to regulate microtubule organization and SAFs known to promote microtubule assembly such as Maskin and XMAP215. Because lamin B does not bind directly to microtubules, it must affect spindle morphogenesis indirectly by influencing the function of spindle matrix-associated SAFs. Using different assays in Xenopus egg extracts, we found that depleting lamin B caused formation of elongated and multipolar spindles, which could be reversed by partially inhibiting the kinesin Eg5, revealing an antagonistic relationship between Eg5 and lamin B. However, lamin B only very weakly antagonizes Eg5 in mediating poleward microtubule-flux based on fluorescence speckle microscopy. Depleting lamin B led to a very small but statistically significant increase in flux. Furthermore, flux reduction caused by partial Eg5 inhibition is only slightly reversed by removing lamin B. Because lamin B does not bind to Eg5, our studies suggest two nonexclusive mechanisms by which lamin B can indirectly antagonize Eg5. It could function in a network that restricts Eg5-driven microtubule sliding only when microtubules come into transient contact with the network. Lamin B could also function to sequester microtubule polymerization activities within the spindle. Without lamin B, increased microtubule assembly caused by the released SAFs would lead to excessive microtubule sliding that results in formation of elongated and multipolar spindles.
STBCs using capacity achieving designs from cyclic division algebras

It is known that the Alamouti code is the only complex orthogonal design (COD) which achieves capacity and that only for the case of two transmit and one receive antennas. M.O. Damen et al. (see IEEE Trans. Inform. Theory, vol.48, no.3, p.753-60, 2002) gave a design for 2 transmit antennas, which achieves capacity for any number of receive antennas, calling it an information lossless STBC. We construct capacity achieving designs using cyclic division algebras for an arbitrary number of transmit and receive antennas. For the STBCs obtained using these designs, we present simulation results for those numbers of transmit and receive antennas for which Damen et al. also gave results, and show that our STBCs perform better than their's.
Golden Code with Low Complexity Sphere Decoder

Golden code is one of the algebraic space-time codes, which has the full rate, full diversity with the better performance than other codes. Sphere decoding (SD) algorithm can achieve near ML performance with moderate complexity. We proposed the modified complex sphere decoding algorithm based on Schnorr-Euchner strategy (SE-CSD) including sorting the order of the system that can reduce the computational effort than general sphere decoding algorithm over the range of SNRs. Combining Golden code with low complexity SE-CSD can obtain perfect performance than other solutions.
Simplified erasure/list decoding

We consider the problem of erasure/list decoding using certain classes of simplified decoders. Specifically, we assume a class of erasure/list decoders, such that a codeword is in the list if its likelihood is larger than a threshold. This class of decoders both approximates the optimal decoder of Forney, and also includes the following simplified subclasses of decoding rules: The first is a function of the output vector only, but not the codebook (which is most suitable for high rates), and the second is a scaled version of the maximum likelihood decoder (which is most suitable for low rates). We provide singleletter expressions for the exact random coding exponents of any decoder in these classes, operating over a discrete memoryless channel. For each class of decoders, we find the optimal decoder within the class, in the sense that it maximizes the erasure/list exponent, under a given constraint on the error exponent. We establish the optimality of the simplified decoders of the first and second kind for low and high rates, respectively.
Meniscal calcification, pathogenesis and implications

Purpose of reviewThe purpose of this review is to discuss recent advances in the understanding of the nature of meniscal calcification and its relationships with meniscal degeneration and cartilage lesions in osteoarthritis. Recent findingsCalcium crystals are universally present in hyaline articular cartilage, as well as the meniscus of the knee of end-stage osteoarthritis patients. Osteoarthritis meniscal cells display a distinct gene-expression profile different from normal meniscal cells, have elevated expression of ankylosis progressive analog (ANKH) and ectonucleotide pyrophosphatase/phosphodiesterase1 (ENPP1) and produce more calcium minerals than normal meniscal cells in vitro. Meniscal calcification is positively associated with meniscal degeneration, which is an early event in the development of osteoarthritis and correlates with cartilage lesions and clinical osteoarthritis scores. Phosphocitrate is a potent calcification inhibitor of osteoarthritis meniscal cell-mediated calcium deposition. Its effect on preventing meniscal degeneration and the molecular mechanisms underlying its disease-modifying activity in osteoarthritis remains elusive. SummaryRecent findings support a pathogenic role of meniscal calcification in osteoarthritis. Meniscal calcification, similar to meniscal degeneration, is a predisposing factor for cartilage lesions. Meniscal calcification is a new target for the development of therapeutic disease-modifying drugs for osteoarthritis.
PubTator: a web-based text mining tool for assisting biocuration

Manually curating knowledge from biomedical literature into structured databases is highly expensive and time-consuming, making it difficult to keep pace with the rapid growth of the literature. There is therefore a pressing need to assist biocuration with automated text mining tools. Here, we describe PubTator, a web-based system for assisting biocuration. PubTator is different from the few existing tools by featuring a PubMed-like interface, which many biocurators find familiar, and being equipped with multiple challenge-winning text mining algorithms to ensure the quality of its automatic results. Through a formal evaluation with two external user groups, PubTator was shown to be capable of improving both the efficiency and accuracy of manual curation. PubTator is publicly available at http://www.ncbi. nlm.nih. gov/CBBresearch/Lu/Demo/PubTator/.