bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multivariate pattern analysis of brain structure predicts functional outcome after auditory-based cognitive training interventions
Authors: Kambeitz-Ilankovic Lana , Vinogradov Sophia , Wenzel Julian , Fisher Melissa , Haas Shalaila S. , Betz Linda , Penzel Nora , Nagarajan Srikantan , Koutsouleris Nikolaos , Subramaniam Karuna 
Published: August 2021

AbstractCognitive gains following cognitive training interventions are associated with improved functioning in people with schizophrenia (SCZ). However, considerable inter-individual variability is observed. Here, we evaluate the sensitivity of brain structural features to predict functional response to auditory-based cognitive training (ABCT) at a single-subject level. We employed whole-brain multivariate pattern analysis with support vector machine (SVM) modeling to identify gray matter (GM) patterns that predicted higher vs. lower functioning after 40 h of ABCT at the single-subject level in SCZ patients. The generalization capacity of the SVM model was evaluated by applying the original model through an out-of-sample cross-validation analysis to unseen SCZ patients from an independent validation sample who underwent 50 h of ABCT. The whole-brain GM volume-based pattern classification predicted higher vs. lower functioning at follow-up with a balanced accuracy (BAC) of 69.4% (sensitivity 72.2%, specificity 66.7%) as determined by nested cross-validation. The neuroanatomical model was generalizable to an independent cohort with a BAC of 62.1% (sensitivity 90.9%, specificity 33.3%). In particular, greater baseline GM volumes in regions within superior temporal gyrus, thalamus, anterior cingulate, and cerebellum predicted improved functioning at the single-subject level following ABCT in SCZ participants. The present findings provide a structural MRI fingerprint associated with preserved GM volumes at a single baseline timepoint, which predicted improved functioning following an ABCT intervention, and serve as a model for how to facilitate precision clinical therapies for SCZ based on imaging data, operating at the single-subject level.
RNA-Seq, physiological, and biochemical analysis of burley tobacco response to nitrogen deficiency
Authors: Li Yafei , Chang Dong , Zhang Xiang , Shi Hongzhi , Yang Huijuan 
Published: August 2021

AbstractTo explore the effects of nitrogen deficiency in burley tobacco, two varieties were cultivated and subjected to conditions of sufficient and deficient nitrogen. The natural characteristics of varieties TN90 and TN86 during tobacco cultivation were similar for nitrogen metabolism. Both carbon and nitrogen metabolism were significantly affected by reducing amounts of applied nitrogen. Under nitrogen-deficient conditions, average leaf biomass, root weight, photosynthetic rate (Pn), pigment levels, total nitrogen, and nitrate content of TN86 and TN90 were significantly decreased by 52.88%, 69.19%, 22.65%, 46.80%, 37.42%, and 79.15%, respectively (p < 0.01). Nicotine and soluble reducing sugar contents were significantly decreased by 96.67% and 95.12%, respectively, in TN86 roots (p < 0.01), which was consistent with the reductions in root surf area, average diameter, and root volume. Nitrogen deficiency induced 6318 differentially expressed genes in both TN90 and TN86, which were highly expressed. In total, 428 upregulated genes were analysed and found to be mainly enriched in the MAPK signalling pathway, sesquiterpenoid and triterpenoid biosynthesis, and arginine and proline metabolism. Meanwhile, 213 downregulated genes were analysed and found to be mainly enriched in photosynthesis, nitrogen metabolism, and amino acid biosynthesis. Reduced pigment content and Pn may result in low carbohydrate formation and decreased leaf biomass in burley tobacco under nitrogen-deficient conditions.
Field measurements of a massive Porites coral at Goolboodi (Orpheus Island), Great Barrier Reef
Authors: Smith Adam , Cook Nathan , Cook Kailash , Brown Rachelle , Woodgett Richard , Veron John , Saylor Vicki 
Published: August 2021

AbstractAn exceptionally large coral Porites sp. has been identified and measured at Goolboodi (Orpheus Island), Great Barrier Reef (GBR). This coral was measured in March 2021 during citizen science research of coral reefs in the Palm Islands group. We conducted a literature review and consulted scientists to compare the size, age and health of the Porites with others in the GBR and internationally. This is the largest diameter Porites coral measured by scientists and the sixth highest coral measured in the GBR. The health of the Porites was assessed as very good with over 70% live coral cover and minor percentages of sponge, live coral rock and macroalgae. An estimated age of 421–438 years was calculated based on linear growth models. Manbarra Traditional Owners were consulted and suggested that the Porites be named Muga dhambi (big coral) to communicate traditional knowledge, language and culture to indigenous, tourists, scientists and students.
Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study
Authors: Dabbah Mohammad A. , Reed Angus B. , Booth Adam T. C. , Yassaee Arrash , Despotovic Aleksa , Klasmer Benjamin , Binning Emily , Aral Mert , Plans David , Morelli Davide , Labrique Alain B. , Mohan Diwakar 
Published: August 2021

AbstractThe COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.
Experimental study and modelling of asphaltene deposition on metal surfaces with superhydrophobic and low sliding angle inner coatings
Authors: Haji-Savameri Mohammad , Norouzi-Apourvari Saeid , Irannejad Ahmad , Hemmati-Sarapardeh Abdolhossein , Schaffie Mahin , Mosavi Amir 
Published: August 2021

AbstractInner coatings have emerged as a novel technique to prevent the deposition of paraffin, wax, scale, and corrosion of pipelines during oil production and transport. Few studies addressed this technique for preventing asphaltene deposition. In this study, two superhydrophobic inner coatings, including polytetrafluoroethylene (PTFE) coating and nanosilica coating, were fabricated on metal surfaces and the asphaltene deposition on these coated surfaces was examined. A model oil solution was prepared using asphaltene and heptol and the effect of static and dynamic flow states on the amount of asphaltene deposition on uncoated electrodes, PTFE coated electrodes, and nanosilica coated electrodes were investigated. The results showed that the PTFE coating is more effective in reducing asphaltene deposition than nanosilica coating. The PTFE coating could reduce 56% of the deposition in a static state and more than 70% in a dynamic state at an asphaltene concentration of 2000 ppm. For PTFE coating in a dynamic state, the deposition rate is negligible in long times. In addition, it was found that the type of flow state affects the asphaltene deposition kinetics. The results demonstrate that, in the static state, the nth-order kinetics model, and in the dynamic state, the double exponential models are in best agreement with the experimental data.
Cardiac macrophage subsets differentially regulate lymphatic network remodeling during pressure overload
Authors: Bizou Mathilde , Itier Romain , Majdoubi Mina , Abbadi Dounia , Pichery Estelle , Dutaur Marianne , Marsal Dimitri , Calise Denis , Garmy-Susini Barbara , Douin-Echinard Victorine , Roncalli Jérome , Parini Angelo , Pizzinat Nathalie 
Published: August 2021

AbstractThe lymphatic network of mammalian heart is an important regulator of interstitial fluid compartment and immune cell trafficking. We observed a remodeling of the cardiac lymphatic vessels and a reduced lymphatic efficiency during heart hypertrophy and failure induced by transverse aortic constriction. The lymphatic endothelial cell number of the failing hearts was positively correlated with cardiac function and with a subset of cardiac macrophages. This macrophage population distinguished by LYVE-1 (Lymphatic vessel endothelial hyaluronic acid receptor-1) and by resident macrophage gene expression signature, appeared not replenished by CCR2 mediated monocyte infiltration during pressure overload. Isolation of macrophage subpopulations showed that the LYVE-1 positive subset sustained in vitro and in vivo lymphangiogenesis through the expression of pro-lymphangiogenic factors. In contrast, the LYVE-1 negative macrophage subset strongly expressed MMP12 and decreased the endothelial LYVE-1 receptors in lymphatic endothelial cells, a feature of cardiac lymphatic remodeling in failing hearts. The treatment of mice with a CCR2 antagonist during pressure overload modified the proportion of macrophage subsets within the pathological heart and preserved lymphatic network from remodeling. This study reports unknown and differential functions of macrophage subpopulations in the regulation of cardiac lymphatic during pathological hypertrophy and may constitute a key mechanism underlying the progression of heart failure.
Projected increases in surface melt and ice loss for the Northern and Southern Patagonian Icefields
Authors: Bravo Claudio , Bozkurt Deniz , Ross Andrew N. , Quincey Duncan J. 
Published: August 2021

AbstractThe Northern Patagonian Icefield (NPI) and the Southern Patagonian Icefield (SPI) have increased their ice mass loss in recent decades. In view of the impacts of glacier shrinkage in Patagonia, an assessment of the potential future surface mass balance (SMB) of the icefields is critical. We seek to provide this assessment by modelling the SMB between 1976 and 2050 for both icefields, using regional climate model data (RegCM4.6) and a range of emission scenarios. For the NPI, reductions between 1.5 m w.e. (RCP2.6) and 1.9 m w.e. (RCP8.5) were estimated in the mean SMB during the period 2005–2050 compared to the historical period (1976–2005). For the SPI, the estimated reductions were between 1.1 m w.e. (RCP2.6) and 1.5 m w.e. (RCP8.5). Recently frontal ablation estimates suggest that mean SMB in the SPI is positively biased by 1.5 m w.e., probably due to accumulation overestimation. If it is assumed that frontal ablation rates of the recent past will continue, ice loss and sea-level rise contribution will increase. The trend towards lower SMB is mostly explained by an increase in surface melt. Positive ice loss feedbacks linked to increasing in meltwater availability are expected for calving glaciers.
Synthesis and application of [Zr-UiO-66-PDC-SO3H]Cl MOFs to the preparation of dicyanomethylene pyridines via chemical and electrochemical methods
Authors: Naseri Amir Mohammad , Zarei Mahmoud , Alizadeh Saber , Babaee Saeed , Zolfigol Mohammad Ali , Nematollahi Davood , Arjomandi Jalal , Shi Hu 
Published: August 2021

AbstractA metal–organic framework (MOF) with sulfonic acid tags as a novel mesoporous catalyst was synthesized. The precursor of Zr-UiO-66-PDC was synthesized both via chemical and electrochemical methods. Then, zirconium-based mesoporous metal–organic framework [Zr-UiO-66-PDC-SO3H]Cl was prepared by reaction of Zr-UiO-66-PDC and SO3HCl. The structure of [Zr-UiO-66-PDC-SO3H]Cl was confirmed by FT-IR, PXRD, FE-SEM, TEM, BET, EDX, and Mapping analysis. This mesoporous [Zr-UiO-66-PDC-SO3H]Cl was successfully applied for the synthesis of dicyanomethylene pyridine derivatives via condensation of various aldehyde, 2-aminoprop-1-ene-1,1,3-tricarbonitrile and malononitrile. At the electrochemical section, a green electrochemical method has successfully employed for rapid synthesis of the zirconium-based mesoporous metal–organic framework UiO-66-PDC at room temperature and atmospheric pressure. The synthesized UiO-66-PDC has a uniform cauliflower-like structure with a 13.5 nm mean pore diameter and 1081.6 m2 g−1 surface area. The described catalyst [Zr-UiO-66-PDC-SO3H]Cl was also employed for the convergent paired electrochemical synthesis of dihydropyridine derivatives as an environmentally friendly technique under constant current at 1.0 mA cm−2 in an undivided cell. The proposed method proceeds with moderate to good yields for the model via a cooperative vinylogous anomeric based oxidation.
Assessment of reference genes at six different developmental stages of Schistosoma mansoni for quantitative RT-PCR
Authors: Silveira Gilbert O. , Amaral Murilo S. , Coelho Helena S. , Maciel Lucas F. , Pereira Adriana S. A. , Olberg Giovanna G. O. , Miyasato Patricia A. , Nakano Eliana , Verjovski-Almeida Sergio 
Published: August 2021

AbstractReverse-transcription quantitative real-time polymerase chain reaction (RT-qPCR) is the most used, fast, and reproducible method to confirm large-scale gene expression data. The use of stable reference genes for the normalization of RT-qPCR assays is recognized worldwide. No systematic study for selecting appropriate reference genes for usage in RT-qPCR experiments comparing gene expression levels at different Schistosoma mansoni life-cycle stages has been performed. Most studies rely on genes commonly used in other organisms, such as actin, tubulin, and GAPDH. Therefore, the present study focused on identifying reference genes suitable for RT-qPCR assays across six S. mansoni developmental stages. The expression levels of 25 novel candidates that we selected based on the analysis of public RNA-Seq datasets, along with eight commonly used reference genes, were systematically tested by RT-qPCR across six developmental stages of S. mansoni (eggs, miracidia, cercariae, schistosomula, adult males and adult females). The stability of genes was evaluated with geNorm, NormFinder and RefFinder algorithms. The least stable candidate reference genes tested were actin, tubulin and GAPDH. The two most stable reference genes suitable for RT-qPCR normalization were Smp_101310 (Histone H4 transcription factor) and Smp_196510 (Ubiquitin recognition factor in ER-associated degradation protein 1). Performance of these two genes as normalizers was successfully evaluated with females maintained unpaired or paired to males in culture for 8 days, or with worm pairs exposed for 16 days to double-stranded RNAs to silence a protein-coding gene. This study provides reliable reference genes for RT-qPCR analysis using samples from six different S. mansoni life-cycle stages.
Differential cell counts using center-point networks achieves human-level accuracy and efficiency over segmentation
Authors: Lee Sarada M. W. , Shaw Andrew , Simpson Jodie L. , Uminsky David , Garratt Luke W. 
Published: August 2021

AbstractDifferential cell counts is a challenging task when applying computer vision algorithms to pathology. Existing approaches to train cell recognition require high availability of multi-class segmentation and/or bounding box annotations and suffer in performance when objects are tightly clustered. We present differential count network (“DCNet”), an annotation efficient modality that utilises keypoint detection to locate in brightfield images the centre points of cells (not nuclei) and their cell class. The single centre point annotation for DCNet lowered burden for experts to generate ground truth data by 77.1% compared to bounding box labeling. Yet centre point annotation still enabled high accuracy when training DCNet on a multi-class algorithm on whole cell features, matching human experts in all 5 object classes in average precision and outperforming humans in consistency. The efficacy and efficiency of the DCNet end-to-end system represents a significant progress toward an open source, fully computationally approach to differential cell count based diagnosis that can be adapted to any pathology need.
Prior beta-blocker treatment improves outcomes in out-of-hospital cardiac arrest patients with non-shockable rhythms
Authors: Huang Hui-Chun , Yu Ping-Hsun , Tsai Min-Shan , Chien Kuo-Liong , Chen Wen-Jone , Huang Chien-Hua 
Published: August 2021

AbstractThe prognosis of out of cardiac arrest is poor and most cardiac arrest patients suffered from the non-shockable rhythm especially in patients without pre-existing cardiovascular diseases and medication prescription. Beta-blocker (ß-blocker) therapy has been shown to improve outcomes in cardiovascular diseases such as heart failure, ischemia related cardiac, and brain injuries. Therefore, we investigated whether prior ß-blockers use was associated with reduced mortality in patients with cardiac arrest and non-shockable rhythm. We conducted a population-based retrospective cohort study using multivariate propensity score–based regression to control for differences among patients with cardiac arrest. A total of 104,568 adult patients suffering a non-traumatic and non-shockable rhythm cardiac arrest between 2005 and 2011 were identified. ß-blocker prescription at least 30 days prior to the cardiac arrest event was defines as the ß-blockers group. We chose 12.5 mg carvedilol as the cut-off value and defined greater or equal to carvedilol 12.5 mg per day and its equivalent dose as high-dose group. After multivariate propensity score–based logistic regression analysis, patients with prior ß-blockers use were associated with better 1-year survival [adjusted odds ratio (OR), 1.15, 95% confidence interval (CI) 1.01–1.30; P = 0.031]. Compared to non-ß-blocker use group and prior low-dose ß-blockers use group, prior high-dose ß-blockers use group was associated with higher mechanical ventilator wean success rate (adjusted OR 1.19, 95% CI 1.01–1.41, P = 0.042). In conclusion, prior high dose ß-blockers use was associated with a better 1-year survival and higher weaning rate in patients with non-shockable cardiac arrest.
A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer
Authors: Shannon Nicholas Brian , Tan Laura Ling Ying , Tan Qiu Xuan , Tan Joey Wee-Shan , Hendrikson Josephine , Ng Wai Har , Ng Gillian , Liu Ying , Ong Xing-Yi Sarah , Nadarajah Ravichandran , Wong Jolene Si Min , Tan Grace Hwei Ching , Soo Khee Chee , Teo Melissa Ching Ching , Chia Claramae Shulyn , Ong Chin-Ann Johnny 
Published: August 2021

AbstractOvarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplatin sensitivity was generated using the Genomics of Drug Sensitivity in Cancer and The Cancer Genome Atlas databases. Four potential biomarkers (CYTH3, GALNT3, S100A14, and ERI1) were identified and optimized for immunohistochemistry (IHC). Validation was performed on a cohort of patients (n = 50) treated with surgical resection followed by adjuvant carboplatin. Predictive models were established to predict chemosensitivity. The four biomarkers were also assessed for their ability to prognosticate overall survival in three ovarian cancer microarray expression datasets from The Gene Expression Omnibus. The extreme gradient boosting (XGBoost) algorithm was selected for the final model to validate the accuracy in an independent validation dataset (n = 10). CYTH3 and S100A14, followed by nodal stage, were the features with the greatest importance. The four gene signature had comparable prognostication as clinical information for two-year survival. Assessment of tumour biology by means of gene expression can serve as an adjunct for prediction of chemosensitivity and prognostication. Potentially, the assessment of molecular markers alongside clinical information offers a chance to further optimise therapeutic decision making.
Costs of position, velocity, and force requirements in optimal control induce triphasic muscle activation during reaching movement
Authors: Ueyama Yuki 
Published: August 2021

AbstractThe nervous system activates a pair of agonist and antagonist muscles to determine the muscle activation pattern for a desired movement. Although there is a problem with redundancy, it is solved immediately, and movements are generated with characteristic muscle activation patterns in which antagonistic muscle pairs show alternate bursts with a triphasic shape. To investigate the requirements for deriving this pattern, this study simulated arm movement numerically by adopting a musculoskeletal arm model and an optimal control. The simulation reproduced the triphasic electromyogram (EMG) pattern observed in a reaching movement using a cost function that considered three terms: end-point position, velocity, and force required; the function minimised neural input. The first, second, and third bursts of muscle activity were generated by the cost terms of position, velocity, and force, respectively. Thus, we concluded that the costs of position, velocity, and force requirements in optimal control can induce triphasic EMG patterns. Therefore, we suggest that the nervous system may control the body by using an optimal control mechanism that adopts the costs of position, velocity, and force required; these costs serve to initiate, decelerate, and stabilise movement, respectively.
Dendrimeric HIV-peptide delivery nanosystem affects lipid membranes structure
Authors: Milowska Katarzyna , Rodacka Aleksandra , Melikishvili Sophie , Buczkowski Adam , Pałecz Bartlomiej , Waczulikova Iveta , Hianik Tibor , Majoral Jean Pierre , Ionov Maksim , Bryszewska Maria 
Published: August 2021

AbstractThe aim of this study was to evaluate the nature and mechanisms of interaction between HIV peptide/dendrimer complexes (dendriplex) and artificial lipid membranes, such as large unilayered vesicles (LUV) and lipid monolayers in the air–water interface. Dendriplexes were combined as one of three HIV-derived peptides (Gp160, P24 and Nef) and one of two cationic phosphorus dendrimers (CPD-G3 and CPD-G4). LUVs were formed of 1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine (DMPC) or of a mixture of DMPC and dipalmitoyl-phosphatidylglycerol (DPPG). Interactions between dendriplexes and vesicles were characterized by dynamic light scattering (DLS), fluorescence anisotropy, differential scanning calorimetry (DSC) and Langmuir–Blodgett methods. The morphology of formed systems was examined by transmission electron microscopy (TEM). The results suggest that dendriplexes interact with both hydrophobic and hydrophilic regions of lipid bilayers. The interactions between dendriplexes and negatively charged lipids (DMPC–DPPG) were stronger than those between dendriplexes and liposomes composed of zwitterionic lipids (DMPC). The former were primarily of electrostatic nature due to the positive charge of dendriplexes and the negative charge of the membrane, whereas the latter can be attributed to disturbances in the hydrophobic domain of the membrane. Obtained results provide new information about mechanisms of interaction between lipid membranes and nanocomplexes formed with HIV-derived peptides and phosphorus dendrimers. These data could be important for the choosing the appropriate antigen delivery vehicle in the new vaccines against HIV infection.