bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ambient air pollution and cardiovascular disease rate an ANN modeling: Yazd-Central of Iran
Authors: Jalili Mahrokh , Ehrampoush Mohammad Hassan , Mokhtari Mehdi , Ebrahimi Ali Asghar , Mazidi Faezeh , Abbasi Fariba , Karimi Hossein 
Published: August 2021

AbstractThis study was aimed to investigate the air pollutants impact on heart patient's hospital admission rates in Yazd for the first time. Modeling was done by time series, multivariate linear regression, and artificial neural network (ANN). During 5 years, the mean concentrations of PM10, SO2, O3, NO2, and CO were 98.48 μg m−3, 8.57 ppm, 19.66 ppm, 18.14 ppm, and 4.07 ppm, respectively. The total number of cardiovascular disease (CD) patients was 12,491, of which 57% and 43% were related to men and women, respectively. The maximum correlation of air pollutants was observed between CO and PM10 (R = 0.62). The presence of SO2 and NO2 can be dependent on meteorological parameters (R = 0.48). Despite there was a positive correlation between age and CD (p = 0.001), the highest correlation was detected between SO2 and CD (R = 0.4). The annual variation trend of SO2, NO2, and CO concentrations was more similar to the variations trend in meteorological parameters. Moreover, the temperature had also been an effective factor in the O3 variation rate at lag = 0. On the other hand, SO2 has been the most effective contaminant in CD patient admissions in hospitals (R = 0.45). In the monthly database classification, SO2 and NO2 were the most prominent factors in the CD (R = 0.5). The multivariate linear regression model also showed that CO and SO2 were significant contaminants in the number of hospital admissions (R = 0.46, p = 0.001) that both pollutants were a function of air temperature (p = 0.002). In the ANN nonlinear model, the 14, 12, 10, and 13 neurons in the hidden layer were formed the best structure for PM, NO2, O3, and SO2, respectively. Thus, the Rall rate for these structures was 0.78–0.83. In these structures, according to the autocorrelation of error in lag = 0, the series are stationary, which makes it possible to predict using this model. According to the results, the artificial neural network had a good ability to predict the relationship between the effect of air pollutants on the CD in a 5 years' time series.
Environmental complexity positively impacts affective states of broiler chickens
Authors: Anderson M. G. , Campbell A. M. , Crump A. , Arnott G. , Jacobs L. 
Published: August 2021

AbstractAffective state can bias an animal’s judgement. Animals in positive affective states can interpret ambiguous cues more positively (“optimistically”) than animals in negative affective states. Thus, judgement bias tests can determine an animal’s affective state through their responses to ambiguous cues. We tested the effects of environmental complexity and stocking density on affective states of broiler chickens through a multimodal judgement bias test. Broilers were trained to approach reinforced locations signaled by one color and not to approach unreinforced locations signaled by a different color. Trained birds were tested for latencies to approach three ambiguous cues of intermediate color and location. Broilers discriminated between cues, with shorter latencies to approach ambiguous cues closest to the reinforced cue than cues closest to the unreinforced cue, validating the use of the test in this context. Broilers housed in high-complexity pens approached ambiguous cues faster than birds in low-complexity pens–an optimistic judgement bias, suggesting the former were in a more positive affective state. Broilers from high-density pens tended to approach all cues faster than birds from low-density pens, possibly because resource competition in their home pen increased food motivation. Overall, our study suggests that environmental complexity improves broilers’ affective states, implying animal welfare benefits of environmental enrichment.
Discrete mission planning algorithm for air-sea integrated search model
Authors: Yu Yixiong 
Published: August 2021

AbstractThe selection of optimal search effort for air-sea integrated search has become the most concerned issue for maritime search and rescue (MSAR) departments. Helicopters play an important role in maritime search because of their strong maneuverability and hovering ability. In this work, the requirements of maritime search were analyzed, from which a global optimization model with quantitative constraints for vessels and aircraft was developed by setting the least search time as single-objective optimization problem; then the improved Dinkelbach algorithm was used to solve the continuous programming problem, and the discrete mission planning algorithm was used to improve the calculation accuracy of search time and area. A case study shows that the errors in calculating search time and area decrease from 12–18 min to 36 s and from 76.5 to 0.45 n mile2, respectively. The results obtained from the discrete mission planning algorithm can provide better guidance for MASR departments in selecting optimal search scheme.
In vitro investigation of the impact of pulsatile blood flow on the vascular architecture of decellularized porcine kidneys
Authors: Corridon Peter R. 
Published: August 2021

AbstractA method was established using a scaffold-bioreactor system to examine the impact pulsatile blood flow has on the decellularized porcine kidney vascular architecture and functionality. These scaffolds were subjected to continuous arterial perfusion of whole blood at normal physiological (650 ml/min and 500 ml/min) and pathophysiological (200 ml/min) rates to examine dynamic changes in venous outflow and micro-/macrovascular structure and patency. Scaffolds subjected to normal arterial perfusion rates observed drops in venous outflow over 24 h. These reductions rose from roughly 40% after 12 h to 60% after 24 h. There were no apparent signs of clotting at the renal artery, renal vein, and ureter. In comparison, venous flow rates decreased by 80% to 100% across the 24 h in acellular scaffolds hypoperfused at a rate of 200 ml/min. These kidneys also appeared intact on the surface after perfusion. However, they presented several arterial, venous, and ureteral clots. Fluoroscopic angiography confirmed substantial alterations to normal arterial branching patterns and patency, as well as parenchymal damage. Scanning electron microscopy revealed that pulsatile blood perfusion significantly disrupted glomerular microarchitecture. This study provides new insight into circumstances that limit scaffold viability and a simplified model to analyze conditions needed to prepare more durable scaffolds for long-term transplantation.
Modelling menstrual cycle length in athletes using state-space models
Authors: de Paula Oliveira Thiago , Bruinvels Georgie , Pedlar Charles R , Moore Brian , Newell John 
Published: August 2021

AbstractThe ability to predict an individual’s menstrual cycle length to a high degree of precision could help female athletes to track their period and tailor their training and nutrition correspondingly. Such individualisation is possible and necessary, given the known inter-individual variation in cycle length. To achieve this, a hybrid predictive model was built using data on 16,524 cycles collected from a sample of 2125 women (mean age 34.38 years, range 18.00–47.10, number of menstrual cycles ranging from 4 to 53). A mixed-effect state-space model was fitted to capture the within-subject temporal correlation, incorporating a Bayesian approach for process forecasting to predict the duration (in days) of the next menstrual cycle. The modelling procedure was split into three steps (1) a time trend component using a random walk with an overdispersion parameter, (2) an autocorrelation component using an autoregressive moving-average model, and (3) a linear predictor to account for covariates (e.g. injury, stomach cramps, training intensity). The inclusion of an overdispersion parameter suggested that $$26.36\%$$

26.36
%

$$[23.68\%,29.17\%]$$

[
23.68
%
,
29.17
%
]

of cycles in the sample were overdispersed. The random walk standard deviation for a non-overdispersed cycle is $$27.41 \pm 1.05$$

27.41
±
1.05

[1.00, 1.09] days while under an overdispersed cycle, the menstrual cycle variance increase in 4.78 [4.57, 5.00] days. To assess the performance and prediction accuracy of the model, each woman’s last observation was used as test data. The root mean square error (RMSE), concordance correlation coefficient and Pearson correlation coefficient (r) between the observed and predicted values were calculated. The model had an RMSE of 1.6412 days, a precision of 0.7361 and overall accuracy of 0.9871. In conclusion, the hybrid model presented here is a helpful approach for predicting menstrual cycle length, which in turn can be used to support female athlete wellness.
Pollen antigens and atmospheric circulation driven seasonal respiratory viral outbreak and its implication to the Covid-19 pandemic
Authors: Wallace Michael G. , Wang Yifeng 
Published: August 2021

AbstractThe patterns of respiratory virus illness are expressed differently between temperate and tropical climates. Tropical outbreaks often peak in wet seasons. Temperate outbreaks typically peak during the winter. The prevailing causal hypotheses focus on sunlight, temperature and humidity variations. Yet no consistent factors have been identified to sufficiently explain seasonal virus emergence and decline at any latitude. Here we demonstrate close connections among global-scale atmospheric circulations, IgE antibody enhancement through seasonal pollen inhalation, and respiratory virus patterns at any populated latitude, with a focus on the US. Pollens emerge each Spring, and the renewed IgE titers in the population are argued to terminate each winter peak of respiratory illness. Globally circulated airborne viruses are postulated to subsequently deposit across the Southern US during lower zonal geostrophic winds each late Summer. This seasonally refreshed viral load is postulated to trigger a new influenza outbreak, once the existing IgE antibodies diminish to a critical value each Fall. Our study offers a new and consistent explanation for the seasonal diminishment of respiratory viral illnesses in temperate climates, the subdued seasonal signature in the tropics, the annually circulated virus phenotypes, and the northerly migration of influenza across the US every year. Our integrated geospatial and IgE hypothesis provides a new perspective for prediction, mitigation and prevention of the outbreak and spread of seasonal respiratory viruses including Covid-19 pandemic.
A combined generalized Warblet transform and second order synchroextracting transform for analyzing nonstationary signals of rotating machinery
Authors: Wei Kai , Jing Xuwen , Li Bingqiang , Kang Chao , Dou Zhenhuan , Liu Jinfeng , Chen Yu , Zheng Hainan 
Published: August 2021

AbstractIn recent years, considerable attention has been paid in time–frequency analysis (TFA) methods, which is an effective technology in processing the vibration signal of rotating machinery. However, TFA techniques are not sufficient to handle signals having a strong non-stationary characteristic. To overcome this drawback, taking short-time Fourier transform as a link, a TFA methods that using the generalized Warblet transform (GWT) in combination with the second order synchroextracting transform (SSET) is proposed in this study. Firstly, based on the GWT and SSET theories, this paper proposes a method combining the two TFA methods to improve the TFA concentration, named GWT–SSET. Secondly, the method is verified numerically with single-component and multi-component signals, respectively. Quantized indicators, Rényi entropy and mean relative error (MRE) are used to analyze the concentration of TFA and accuracy of instantly frequency (IF) estimation, respectively. Finally, the proposed method is applied to analyze nonstationary signals in variable speed. The numerical and experimental results illustrate the effectiveness of the GWT–SSET method.
Isolation of viable Babesia bovis merozoites to study parasite invasion
Authors: Hakimi Hassan , Asada Masahito , Ishizaki Takahiro , Kawazu Shinichiro 
Published: August 2021

AbstractBabesia parasite invades exclusively red blood cell (RBC) in mammalian host and induces alterations to host cell for survival. Despite the importance of Babesia in livestock industry and emerging cases in humans, their basic biology is hampered by lack of suitable biological tools. In this study, we aimed to develop a synchronization method for Babesia bovis which causes the most pathogenic form of bovine babesiosis. Initially, we used compound 2 (C2), a specific inhibitor of cyclic GMP-dependent protein kinase (PKG), and a derivative of C2, ML10. While both inhibitors were able to prevent B. bovis egress from RBC and increased percentage of binary forms, removal of inhibitors from culture did not result in a synchronized egress of parasites. Because using PKG inhibitors alone was not efficient to induce a synchronized culture, we isolated viable and invasive B. bovis merozoites and showed dynamics of merozoite invasion and development in RBCs. Using isolated merozoites we showed that BbVEAP, VESA1-export associated protein, is essential for parasite development in the RBC while has no significant role in invasion. Given the importance of invasion for the establishment of infection, this study paves the way for finding novel antigens to be used in control strategies against bovine babesiosis.
Majority scoring with backward elimination in PLS for high dimensional spectrum data
Authors: Alenezi Freeh N. 
Published: August 2021

AbstractVariable selection is crucial issue for high dimensional data modeling, where sample size is smaller compared to number of variables. Recently, majority scoring of filter measures in PLS (MS-PLS) is introduced for variable selection in high dimensional data. Filter measures are not greedy for optimal performance, hence we have proposed majority scoring with backward elimination in PLS (MSBE-PLS). In MSBE-PLS we have considered variable importance on projection (VIP) and selectivity ratio (SR). In each iteration of backward elimination in PLS variables are considered influential if they were selected by both filter indicator. The proposed method is implemented for corn’s and diesel’s content prediction. The corn contents include protein, oil, starch and moisture while diesel contents include boiling point at 50% recovery, cetane number, density, freezing temperature of the fuel, total aromatics, and viscosity. The proposed method outperforms in terms of RMSE when compared with reference methods. In addition to validating the spectrum models, data properties are also examined for explaining prediction behaviors. Moreover, MSBE-PLS select the moderate number of influential variables, hence it presents the parsimonious model for predicting contents based on spectrum data.
Hurricanes as an enabler of Amazon fires
Authors: Tsui Enoch Yan Lok , Toumi Ralf 
Published: August 2021

AbstractA teleconnection between North Atlantic tropical storms and Amazon fires is investigated as a possible case of compound remote extreme events. The seasonal cycles of the storms and fires are in phase with a maximum around September and have significant inter-annual correlation. Years of high Amazon fire activity are associated with atmospheric conditions over the Atlantic which favour tropical cyclones. We propose that anomalous precipitation and latent heating in the Caribbean, partly caused by tropical storms, leads to a thermal circulation response which creates anomalous subsidence and enhances surface solar heating over the Amazon. The Caribbean storms and precipitation anomalies could thus promote favourable atmospheric conditions for Amazon fire.
Anytime collaborative brain–computer interfaces for enhancing perceptual group decision-making
Authors: Bhattacharyya Saugat , Valeriani Davide , Cinel Caterina , Citi Luca , Poli Riccardo 
Published: August 2021

AbstractIn this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.
Target identification of hepatic fibrosis using Pien Tze Huang based on mRNA and lncRNA
Authors: Zhu Jinhang , Zhang Di , Wang Ting , Chen Zhiliang , Chen Luan , Wu Hao , Huai Cong , Sun Jing , Zhang Na , Wei Muyun , Hong Fei , Qin Shengying 
Published: August 2021

AbstractHepatic fibrosis is a spontaneous wound-healing response triggered by chronic liver injury. Pien Tze Huang (PZH), a traditional Chinese herbal medicine, has been widely used to treat various hepatic diseases in Asia. We used a CCl4-induced mouse model to establish a PZH group of hepatic fibrosis mice treated with PZH and a control group of hepatic fibrosis mice without any treatment. We performed RNA-seq and mass spectrometry sequencing to investigate the mechanism of the PZH response in hepatic fibrosis and identified multiple differentially expressed transcripts (DETs) and proteins (DEPs) that may be drug targets of PZH. Liver functional indices, including serum albumin (ALB), alanine aminotransferase (ALT) and aspartate aminotransferase (AST), were significantly decreased in the PZH treatment group (P < 0.05) in the eighth week. Hematoxylin–eosin (HE), Masson and Sirius red staining demonstrated that PZH significantly inhibited infiltration of inflammatory cells and collagen deposition. A total of 928 transcripts and 138 proteins were differentially expressed in PZH-treated mice compared to the control group. Gene Ontology (GO) enrichment analysis suggested that PZH may alleviate liver injury and fibrosis by enhancing the immune process. Taken together, our results revealed that multiple DETs and DEPs may serve as drug targets of PZH in hepatic fibrosis patient in future clinical practice.
The retinoid X receptor α modulator K-80003 suppresses inflammatory and catabolic responses in a rat model of osteoarthritis
Authors: Li Hua , Li Xiaofan , Yang Boyu , Su Junnan , Cai Shaofang , Huang Jinmei , Hu Tianfu , Chen Lijuan , Xu Yaping , Li Yuhang 
Published: August 2021

AbstractOsteoarthritis (OA), a most common and highly prevalent joint disease, is closely associated with dysregulated expression and modification of RXRα. However, the role of RXRα in the pathophysiology of OA remains unknown. The present study aimed to investigate whether RXRα modulator, such as K-80003 can treat OA. Experimental OA was induced by intra-articular injection of monosodium iodoacetate (MIA) in the knee joint of rats. Articular cartilage degeneration was assessed using Safranin-O and fast green staining. Synovial inflammation was measured using hematoxylin and eosin (H&E) staining and enzyme-linked immunosorbent assay (ELISA). Expressions of MMP-13, ADAMTS-4 and ERα in joints were analyzed by immunofluorescence staining. Western blot, RT-PCR and co-Immunoprecipitation (co-IP) were used to assess the effects of K-80003 on RXRα-ERα interaction. Retinoid X receptor α (RXRα) modulator K‐80003 prevented the degeneration of articular cartilage, reduced synovial inflammation, and alleviated osteoarthritic pain in rats. Furthermore, K-80003 markedly inhibited IL-1β‐induced p65 nuclear translocation and IκBα degradation, and down-regulate the expression of HIF-2α, proteinases (MMP9, MMP13, ADAMTS-4) and pro-inflammatory factors (IL-6 and TNFα) in primary chondrocytes. Additionally, knockdown of ERα with siRNA blocked these effects of K-80003 in chondrocytes. In conclusion, RXRα modulators K-80003 suppresses inflammatory and catabolic responses in OA, suggesting that targeting RXRα‐ERα interaction by RXRα modulators might be a novel therapeutic approach for OA treatment.
Detection of fusion gene transcripts in the blood samples of prostate cancer patients
Authors: Yu Yan-Ping , Liu Silvia , Nelson Joel , Luo Jian-Hua 
Published: August 2021

AbstractProstate cancer remains one of the most lethal cancers for men in the United States. The study aims to detect fusion transcripts in the blood samples of prostate cancer patients. We analyzed nine fusion transcripts including MAN2A1-FER, SLC45A2-AMACR, TRMT11-GRIK2, CCNH-C5orf30, mTOR-TP53BP1, KDM4-AC011523.2, TMEM135-CCDC67, LRRC59-FLJ60017 and Pten-NOLC1147 in the blood samples from 147 prostate cancer patients and 14 healthy individuals, using Taqman RT-PCR and Sanger’s sequencing. Similar analyses were also performed on 25 matched prostate cancer samples for matched-sample evaluation. Eighty-two percent blood samples from the prostate cancer patients were positive for MAN2A1-FER transcript, while 41.5% and 38.8% blood samples from the prostate cancer patients were positive for SLC45A2-AMACR and Pten-NOLC1, respectively. CCNH-c5orf30 and mTOR-TP53BP1 had low detection rates, positive in only 5.4% and 4% of the blood samples from the prostate cancer patients. Only 2 blood samples were positive for KDM4B-AC011523.2 transcript. Overall, 89.8% patients were positive for at least one fusion transcript in their blood samples. The statistical analysis showed varied sensitivity of fusion transcript detection in the blood based on the types of fusions. In contrast, the blood samples from all healthy individuals were negative for the fusion transcripts. Detection of fusion transcripts in the blood samples of the prostate cancer patients may be a fast and cost-effective way to detect prostate cancer.
Doxycycline promotes proteasome fitness in the central nervous system
Authors: Jenkins Edmund Charles , O’Connell Matthew J. , Manfredi Giovanni , Germain Doris 
Published: August 2021

AbstractSeveral studies reported that mitochondrial stress induces cytosolic proteostasis in yeast and C. elegans. Notably, inhibition of mitochondrial translation with doxcycyline decreases the toxicity of β-amyloid aggregates, in a C. elegans. However, how mitochondrial stress activates cytosolic proteostasis remains unclear. Further whether doxycycline has this effect in mammals and in disease relevant tissues also remains unclear. We show here that doxycycline treatment in mice drastically reduces the accumulation of proteins destined for degradation by the proteasome in a CNS region-specific manner. This effect is associated with the activation of the ERα axis of the mitochondrial unfolded protein response (UPRmt), in both males and females. However, sexually dimorphic mechanisms of proteasome activation were observed. Doxycycline also activates the proteasome in fission yeast, where ERα is not expressed. Rather, the ancient ERα-coactivator Mms19 regulates this response in yeast. Our results suggest that the UPRmt initiates a conserved mitochondria-to-cytosol stress signal, resulting in proteasome activation, and that this signal has adapted during evolution, in a sex and tissue specific-manner. Therefore, while our results support the use of doxycycline in the prevention of proteopathic diseases, they also indicate that sex is an important variable to consider in the design of future clinical trials using doxycycline.