The Study of Noncollectivity by the Forward-Backward Multiplicity Correlation Function

We propose a forward-backward multiplicity correlation function $C^N_{FB}$, which is experimentally accessible, to measure the noncollectivity contribution. We find that $C^N_{FB}$ is sensitive to the jet contribution for the particle-rich case. Surprisingly, it will automatically decrease for the particle-rare case. Our study indicates that similar decreasing trend observed previously is mainly driven by particle scarcity instead of jets. The function is studied in Au+Au collision at $\sqrt{s_{NN}}=200$ GeV with a multiphase transport model (AMPT). We find that the jet fraction is about 10% at transverse momentum ($p_T$) around 2.5 GeV/$c$ and reaches up to 30% at 3.5 GeV/$c$. The implication of this study in the investigation of the noncollectivity contribution in elliptic anisotropy parameter $v_2$ is also discussed.Comment: 5 pages, 4 figure

Harmonizing across datasets to improve the transferability of drug combination prediction

Combination treatment has multiple advantages over traditional monotherapy in clinics, thus becoming a target of interest for many high-throughput screening (HTS) studies, which enables the development of machine learning models predicting the response of new drug combinations. However, most existing models have been tested only within a single study, and these models cannot generalize across different datasets due to significantly variable experimental settings. Here, we thoroughly assessed the transferability issue of single-study-derived models on new datasets. More importantly, we propose a method to overcome the experimental variability by harmonizing dose-response curves of different studies. Our method improves the prediction performance of machine learning models by 184% and 1367% compared to the baseline models in intra-study and inter-study predictions, respectively, and shows consistent improvement in multiple cross-validation settings. Our study addresses the crucial question of the transferability in drug combination predictions, which is fundamental for such models to be extrapolated to new drug combination discovery and clinical applications that are de facto different datasets.A machine learning-based method improves the transferability of drug combination predictions across datasets from studies with variable experimental settings, such as the number of doses and dose ranges tested.Peer reviewe

The neural dynamic mechanisms of asymmetric switch costs in a combined Stroop-task-switching paradigm

Switch costs have been constantly found asymmetrical when switching between two tasks of unequal dominance. We used a combined Stroop-task-switching paradigm and recorded electroencephalographic (EEG) signals to explore the neural mechanism underlying the phenomenon of asymmetrical switch costs. The results revealed that a fronto-central N2 component demonstrated greater negativity in word switch (cW) trials relative to word repeat (wW) trials, and both First P3 and P3b components over the parieto-central region exhibited greater positivity in color switch (wC) trials relative to color repeat (cC) trials, whereas a contrasting switch-related fronto-central SP effect was found to have an opposite pattern for each task. Moreover, the time-frequency analysis showed a right-frontal lower alpha band (9-11 Hz) modulation in the word task, whereas a fronto-central upper alpha band (11-13 Hz) modulation was exclusively found in the color task. These results provide evidence for dissociable neural processes, which are related to inhibitory control and endogenous control, contributing to the generation of asymmetrical switch costs

Erosion-deposition patterns and depo-center movements in branching channels at the near-estuary reach of the Yangtze River

Channel evolution and depo-center migrations in braided reaches are significantly influenced by variations in runoff. This study examines the effect of runoff variations on the erosion-deposition patterns and depocenter movements within branching channels of the near-estuary reach of the Yangtze River. We assume that variations in annual mean duration days of runoff discharges, ebb partition ratios in branching channels, and the erosional/depositional rates of entire channels and sub-reaches are representative of variations in runoff intensity, flow dynamics in branching channels, and morphological features in the channels. Our results show that the north region of Fujiangsha Waterway, the Liuhaisha branch of Rugaosha Waterway, the west branch of Tongzhousha Waterway, and the west branch of Langshansha Waterway experience deposition or reduced erosion under low runoff intensity, and erosion or reduced deposition under high runoff intensity, with the depocenters moving upstream and downstream, respectively. Other waterway branches undergo opposite trends in erosion-deposition patterns and depo-center movements as the runoff changes. These morphological changes may be associated with trends in ebb partition ratio as the runoff discharge rises and falls. By flattening the intra-annual distribution of runoff discharge, dam construction in the Yangtze Basin has altered the ebb partition ratios in waterway branches, affecting their erosion-deposition patterns and depo-center movements. Present trends are likely to continue into the future due to the succession of large cascade dams under construction along the upper Yangtze and ongoing climate change

Short-term application of diquafosol ophthalmic solution benefits children with dry eye wearing orthokeratology lens

PurposeThis aim of this study was to evaluate the effect of 3% Diquafosol Ophthalmic Solution (DQS) on children with dry eye from wearing overnight orthokeratology (OrthoK) lenses.MethodsMyopic children aged 8–18 years with dry eye syndrome were enrolled in this prospective observational study, and they were grouped according to their OrthoK treatment history for at least 1 year. All participants received DQS 4 times per day for 1 month. The following indicators were measured at baseline 1 month after treatment: the Dry Eye Questionnaire-5 (DEQ-5), non-invasive tear meniscus height (TMH), non-invasive tear film break-up time (first and average, NIBUT-F and NIBUT-A), meibomian gland score (MG score), conjunctival hyperemia redness score (R-scan), and blink pattern analysis.ResultsA total of 104 participants (189 eyes) including 40 OrthoK wearers (72 eyes) and 64 Orthok candidates (117 eyes) completed the study. Of all, after DQS treatment for 1 month, DEQ-5 scores reduced from 5.54 ± 3.25 to 3.85 ± 2.98 (t = −3.36, p = 0.00). TMH increased from 0.20 ± 0.05 mm to 0.21 ± 0.05 mm (t = 2.59, p = 0.01), NIBUT-F and NIBUT-A were prolonged from 6.67 ± 4.71 s to 10.32 ± 6.19 s and from 8.86 ± 5.25 s to 13.30 ± 6.03 s (all p = 0.00), respectively. R-scan decreased from 0.69 ± 0.28 to 0.50 ± 0.25 (t = −9.01, p = 0.00). Upper MG scores decreased from 1.04 ± 0.32 to 0.97 ± 0.36 (t = −2.14, p = 0.03). Lower MG scores, partial blink rate, partial blinks, and total blinks did not change significantly. Both break-up time (BUT) and R-scan improved significantly after DQS treatment for 1 month (all p = 0.00) in OrthoK candidates and OrthoK wearers. Among the OrthoK wearers, TMH and dry eye symptoms increased significantly (all p = 0.00) but did not increase in OrthoK candidates (p > 0.05). There were no adverse events related to DQS.ConclusionDiquafosol Ophthalmic Solution was effective for children wearing overnight orthokeratology in relieving dry eye symptoms and improving ocular surface parameters, which may help improve children's OrthoK wearing tolerance and compliance

Seroprevalence of avian influenza A (H5N1) virus among poultry workers in Jiangsu Province, China: an observational study

<p>Abstract</p> <p>Background</p> <p>Since 2003 to 06 Jan 2012, the number of laboratory confirmed human cases of infection with avian influenza in China was 41 and 27 were fatal. However, the official estimate of the H5N1 case-fatality rate has been described by some as an over estimation since there may be numerous undetected asymptomatic/mild cases of H5N1 infection. This study was conducted to better understand the real infection rate and evaluate the potential risk factors for the zoonotic spread of H5N1 viruses to humans.</p> <p>Methods</p> <p>A seroepidemiological survey was conducted in poultry workers, a group expected to have the highest level of exposure to H5N1-infected birds, from 3 counties with habitat lakes of wildfowl in Jiangsu province, China. Serum specimens were collected from 306 participants for H5N1 serological test. All participants were interviewed to collect information about poultry exposures.</p> <p>Results</p> <p>The overall seropositive rate was 2.61% for H5N1 antibodies. The poultry number was found associated with a 2.39-fold significantly increased subclinical infection risk after adjusted with age and gender.</p> <p>Conclusions</p> <p>Avian-to -human transmission of avian H5N1 virus remained low. Workers associated with raising larger poultry flocks have a higher risk on seroconversion.</p

Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls

BackgroundThis study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls.MethodsA total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set.ResultsThe final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients.ConclusionThe radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool

Seroprevalence of Pandemic (H1N1) 2009 in Pregnant Women in China: An Observational Study

BACKGROUND: We investigated the seropositive rates and persistence of antibody against pandemic (H1N1) 2009 virus (pH1N1) in pregnant women and voluntary blood donors after the second wave of the pandemic in Nanjing, China. METHODOLOGY/PRINCIPAL FINDINGS: Serum samples of unvaccinated pregnant women (n = 720) and voluntary blood donors (n = 320) were collected after the second wave of 2009 pandemic in Nanjing. All samples were tested against pH1N1 strain (A/California/7/2009) with hemagglutination inhibition assay. A significant decline in seropositive rates, from above 50% to about 20%, was observed in pregnant women and voluntary blood donors fifteen weeks after the second wave of the pandemic. A quarter of the samples were tested against a seasonal H1N1 strain (A/Brisbane/59/2007). The antibody titers against pH1N1 strain were found to correlate positively with those against seasonal H1N1 strain. The correlation was modest but statistically significant. CONCLUSIONS AND SIGNIFICANCE: The high seropositive rates in both pregnant women and voluntary blood donors suggested that the pH1N1 virus had widely spread in these two populations. Immunity derived from natural infection seemed not to be persistent well

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe