bluuebunny/crossref_metadata_2025_split huggingface dataset:
Selective toxicity of functionalised graphene oxide to patients-derived glioblastoma stem cells and minimal toxicity to non-cancerous brain tissue cells
Authors: Costa Pedro M , Mei Kuo-Ching , Kreuzer Martin , Li Yueting , Neveen Hosny A , Grant Vivien , Festy Frederic , Pollard Steven M , Al-Jamal Khuloud T 
Published: June 2020

Abstract
Glioblastoma (GBMs) is an aggressive type of brain tumour, driven by immature neural stem cell-like cells that promote tumour growth and underlie resistance to conventional therapy. The GBM stem cells (GSCs) can exist in quiescent or dormant states and infiltrate widely into surrounding brain tissues, currently incurable with only around one-year median survival. Innovative therapeutic strategies for GBMs are urgently needed. Here we explore functionalized graphene oxide (GO) to assess their value as delivery vehicles for GBM therapeutics. Interactions and cellular responses were assessed in vitro using both classic cell lines and patient derived GSCs. Association between the functionalised GO and established GBM cell lines (serum grown ‘non-stem’ cells) was strong and resulted in decreased cell viability, increased cell oxidative stress, and changes in lipids composition in a concentration-dependent manner. Responses were more moderate in GSCs and were only observed at highest functionalised GO concentrations. However, no significant toxicity was detected in brain astrocytes and endothelial cells. These results indicate selective toxicity to highly proliferative GBM cell lines and patient GSCs, with minimal toxicity to normal neural cells and brain tissue. We conclude that a novel class of GBM-targeting graphene-based nanocarriers could be useful delivery vehicles for GBM therapeutics.
Effect of nitrogen in the properties of diamond-like carbon (DLC) coating on Ti6Al4V substrate
Authors: Almeida L S , Souza A R M , Costa L H , Rangel E C , Manfrinato M D , Rossino L S 
Published: June 2020

Abstract
The great interest in the study of diamond-like carbon films (a-C:H) is justified by its mechanical and tribological properties. However, the high internal stress of the film results in its difficult adhesion to the metallic substrate, which can be solved by nitrogen incorporation in the a-C:H film, allowing a formed film of lower internal stress. The objective of this work is to evaluate the influence of flow (20, 30 and 40sccm), CH4/Ar ratio (90/10 and 70/30) and voltage (400, 500, 600 and 700 V) in the a-C:H formation. For the best condition of the film, we studied the effect of nitrogen incorporation in the hardness and wear resistance of the a-C:H(N), modifying the nitrogen percentage in the treatment at 10% to 60% N2. The treatments were carried out in the Ti6Al4V substrate by DC-PECVD for two hours. For good adhesion of the films on the substrate, a silicon interlayer must be produced. The increase in the voltage above 600 V increases the ID/IG and film thickness, causing its delamination, and the gas ratio did not influence the a-C:H characteristics. The a-C:H film deposited with 30 sccm, 90/10 and 500 V was characterized as a-C:H (hard), with properties such as the hardness of 17 GPa, 30% H, 39% sp3 and ID/IG ratio of 0.58. Since nitrogen reduced the deposition rate, the total gas flow for the production of a-C:H(N) was performed with 40 sccm. The Raman spectra of a-C:H(N) films showed changes in D band intensity and displacement in relation to the nitrogen-free film spectrum, evidencing the incorporation of nitrogen in the film. The XPS analysis showed the linear increase of the nitrogen incorporation in the a-C:H(N) film with the increase of the amount of the N2 gas in the treatment, which caused, in general, a decrease in the amount of C–C sp3 bonding, increasing the adhesion of the film in the substrate and not necessarily the low wear resistance of the formed film.
Microstructure and tensile properties of the different thickness ASSAPH440 high strength steel/DC52D+ZF45 galvanized cold rolled sheet dissimilar metal welding joint by CO2 laser welding for automobile manufacturing
Authors: Luo J , Gao J J , Lin H X , Fan Y H , Ran Y , Yin H , Geng H B 
Published: June 2020

Abstract
In order to adapt to the development trend of a lightweight automobile and meet the safety requirements of key automotive parts, it is necessary to study the relationship between microstructure and mechanical properties of the dissimilar and different thickness materials welded joint. In this work, a dissimilar welded joint of high strength vehicle steel ASSAPH440 with 2.0 mm thickness/galvanized cold rolled sheet DC52D+ZF45 with 2.6 mm thickness formed by CO2 laser welding was studied. The microstructure of the welded joint was analyzed by metallographic structure and mechanical properties were discussed in terms of their tensile strength and microhardness. The results indicated that a high-quality welded joint with an average tensile strength of 643 MPa and an elongation of 22.7% was obtained at a welding speed of 30 mm s−1 and the laser power of 2200 w in CO2 laser welding, the tensile strength of laser welded joint was more than that of the both based metals. The center of the welding seam was composed of slender lath martensite with a few small white pieces of ferrite. The microstructure of the Heat Affected Zone (HAZ) on the DC52D+ZF45 side was smaller than that of the HAZ on the ASSAPH440 side, and its mechanical properties were superior. The highest microhardness was obtained at the center of the cross section of the welding seam, and the microhardness of the welding seam on the DC52D+ZF45 side was higher than that of the welding seam on the ASSAPH440 side. The tensile fracture appeared at the base metal of DC52D+ZF45 steel as a result of the strength of ASSAPH440 was more than that of DC52D+ZF45. The performance of the laser welded joint met the technical requirements of automobile manufacturing engineering.
Inter-annual Climate Variability and Vegetation Dynamic in the Upper Amur (Heilongjiang) River Basin in Northeast Asia
Authors: You Guangyong , Arain M Altaf , Wang Shusen , McKenzie Shawn , Xu Bing , He Yaqian , Wu Dan , Lin Naifeng , Gao Jixi , Jia Xiru 
Published: June 2020

Abstract
Long-term (1982–2013) datasets of climate variables and Normalized Difference Vegetation Index (NDVI) were collected from Climate Research Union (CRU) and GIMMS NDVI3g. By setting the NDVI values below the threshold of 0.2 as 0, NDVI_0.2 was created to eliminate the noise caused by changes of surface albedo during non-growing period. TimeSat was employed to estimate the growing season length (GSL) from the seasonal variation of NDVI. Statistical analyses were conducted to reveal the mechanisms of climate-vegetation interactions in the cold and semi-arid Upper Amur River Basin of Northeast Asia. The results showed that the regional climate change can be summarized as warming and drying. Annual mean air temperature (T) increased at a rate of 0.13 °C per decade. Annual precipitation (P) declined at a rate of 18.22 mm per decade. NDVI had an insignificantly negative trend, whereas, NDVI_0.2 displayed a significantly positive trend (MK test, p < 0.05) over the past three decades. GSL had a significantly positive rate of approximately 2.9 days per decade. Correlation analysis revealed that, NDVI was significantly correlated with amount of P, whereas, GSL was highly correlated with warmth index (WMI), accumulation of monthly T above the threshold of 5°C. Principal regression analysis revealed that the inter-annual variations of NDVI, NDVI_0.2 and GSL were mostly contributed by WMI. Spatially, NDVI in grassland was more sensitive to P, whereas, T was more important in areas of high elevation. GSL in most of the areas displayed high sensitivity to T. This study examined the different roles of climate variables in controlling the vegetation activities. Further studies are needed to reveal the impact of extended GSL on the regional water balance and the water level of regional lakes, providing the habitats for the migratory birds and endangered species.
A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase
Authors: Sohraby Farzin , Javaheri Moghadam Mostafa , Aliyar Masoud , Aryapour Hassan 
Published: June 2020

Abstract

Summary
Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased MD simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased MD simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) MD simulations, in this case a protein–ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nanosecond time scales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.

Availability and implementation
The links of the tutorial and technical documents are accessible in the article.

Supplementary information
Supplementary data are available at Bioinformatics online.
Fast and accurate prediction of partial charges using Atom-Path-Descriptor-based machine learning
Authors: Wang Jike , Cao Dongsheng , Tang Cunchen , Chen Xi , Sun Huiyong , Hou Tingjun 
Published: June 2020

Abstract

Motivation
Partial atomic charges are usually used to calculate the electrostatic component of energy in many molecular modeling applications, such as molecular docking, molecular dynamics simulations, free energy calculations and so forth. High-level quantum mechanics calculations may provide the most accurate way to estimate the partial charges for small molecules, but they are too time-consuming to be used to process a large number of molecules for high throughput virtual screening.

Results
We proposed a new molecule descriptor named Atom-Path-Descriptor (APD) and developed a set of APD-based machine learning (ML) models to predict the partial charges for small molecules with high accuracy. In the APD algorithm, the 3D structures of molecules were assigned with atom centers and atom-pair path-based atom layers to characterize the local chemical environments of atoms. Then, based on the APDs, two representative ensemble ML algorithms, i.e. random forest (RF) and extreme gradient boosting (XGBoost), were employed to develop the regression models for partial charge assignment. The results illustrate that the RF models based on APDs give better predictions for all the atom types than those based on traditional molecular fingerprints reported in the previous study. More encouragingly, the models trained by XGBoost can improve the predictions of partial charges further, and they can achieve the average root-mean-square error 0.0116 e on the external test set, which is much lower than that (0.0195 e) reported in the previous study, suggesting that the proposed algorithm is quite promising to be used in partial charge assignment with high accuracy.

Availability and implementation
The software framework described in this paper is freely available at https://github.com/jkwang93/Atom-Path-Descriptor-based-machine-learning

Supplementary information
Supplementary data are available at Bioinformatics online.
Ocular fixations and presaccadic potentials to explain pareidolias in Parkinson’s disease
Authors: Revankar Gajanan S , Hattori Noriaki , Kajiyama Yuta , Nakano Tomohito , Mihara Masahito , Mori Etsuro , Mochizuki Hideki 
Published: June 2020

Abstract
In Parkinson’s disease, a precursor phenomenon to visual hallucinations presents as ‘pareidolias’ which make ambiguous forms appear meaningful. To evoke and detect pareidolias in patients, a noise pareidolia test was recently developed, although its task-dependent mechanisms are yet to be revealed. When subjected to this test, we hypothesized that patients exhibiting pareidolias would show altered top-down influence of visual processing allowing us to demonstrate the influence of pareidolic illusionary behaviour in Parkinson’s disease patients. To that end, we evaluated eye-movement strategies and fixation-related presaccadic activity on scalp EEG when participants performed the test. Twelve healthy controls and 21 Parkinson’s disease patients, evaluated for cognitive, visuo-spatial and executive functions, took a modified computer-based version of the noise pareidolia test in a free-viewing EEG eye-tracking experiment. Eye-tracking metrics (fixation-related durations and counts) documented the eye movement behaviour employed in correct responses (face/noise) and misperceptions (pareidolia/missed) during early and late visual search conditions. Simultaneously, EEG recorded the presaccadic activity in frontal and parietal areas of the brain. Based on the noise pareidolia test scores, we found certain Parkinson’s disease patients exhibited pareidolias whereas others did not. ANOVA on eye-tracking data showed that patients dwelled significantly longer to detect faces and pareidolias which affected both global and local search dynamics depending on their visuo-perceptual status. Presaccadic activity in parietal electrodes for the groups was positive for faces and pareidolias, and negative for noise, though these results depended mainly on saccade size. However, patients sensitive to pareidolias showed a significantly higher presaccadic potential on frontal electrodes independent of saccade sizes, suggesting a stronger frontal activation for pareidolic stimuli. We concluded with the following interpretations (i) the noise pareidolia test specifically characterizes visuo-perceptual inadequacies in patients despite their wide range of cognitive scores, (ii) Parkinson’s disease patients dwell longer to converge attention to pareidolic stimuli due to abnormal saccade generation proportional to their visuo-perceptual deficit during early search, and during late search, due to time-independent alteration of visual attentional network and (iii) patients with pareidolias show increased frontal activation reflecting the allocation of attention to irrelevant targets that express the pareidolic phenomenon. While the disease per se alters the visuo-perceptual and oculomotor dynamics, pareidolias occur in Parkinson’s disease due to an abnormal top-down modulation of visual processing that affects visual attention and guidance to ambiguous stimuli.
Brain Network Segregation and Glucose Energy Utilization: Relevance for Age-Related Differences in Cognitive Function
Authors: Manza Peter , Wiers Corinde E , Shokri-Kojori Ehsan , Kroll Danielle , Feldman Dana , Schwandt Melanie , Wang Gene-Jack , Tomasi Dardo , Volkow Nora D 
Published: June 2020

AbstractThe human brain is organized into segregated networks with strong within-network connections and relatively weaker between-network connections. This “small-world” organization may be essential for maintaining an energetically efficient system, crucial to the brain which consumes 20% of the body’s energy. Brain network segregation and glucose energy utilization both change throughout the lifespan. However, it remains unclear whether these processes interact to contribute to differences in cognitive performance with age. To address this, we examined fluorodeoxyglucose-positron emission tomography and resting-state functional magnetic resonance imaging from 88 participants aged 18–73 years old. Consistent with prior work, brain network segregation showed a negative association with age across both sensorimotor and association networks. However, relative glucose metabolism demonstrated an interaction with age, showing a negative slope in association networks but a positive slope in sensorimotor networks. Overall, brain networks with lower segregation showed significantly steeper age-related differences in glucose metabolism, compared with highly segregated networks. Sensorimotor network segregation mediated the association between age and poorer spatial cognition performance, and sensorimotor network metabolism mediated the association between age and slower response time. These data provide evidence that sensorimotor segregation and glucose metabolism underlie some age-related changes in cognition. Interventions that stimulate somatosensory networks could be important for treatment of age-related cognitive decline.
Quantitative MRI-Based Analysis Identifies Developmental Limbic Abnormalities in PCDH19 Encephalopathy
Authors: Lenge Matteo , Marini Carla , Canale Edoardo , Napolitano Antonio , De Masi Salvatore , Trivisano Marina , Mei Davide , Longo Daniela , Rossi Espagnet Maria Camilla , Lucenteforte Ersilia ,   PCDH19 Clinical Study Group, Barba Carmen , Specchio Nicola , Guerrini Renzo 
Published: June 2020

Abstract
Protocadherin-19 (PCDH19) is a calcium dependent cell-adhesion molecule involved in neuronal circuit formation with prevalent expression in the limbic structures. PCDH19-gene mutations cause a developmental encephalopathy with prominent infantile onset focal seizures, variably associated with intellectual disability and autistic features. Diagnostic neuroimaging is usually unrevealing. We used quantitative MRI to investigate the cortex and white matter in a group of 20 PCDH19-mutated patients. By a statistical comparison between quantitative features in PCDH19 brains and in a group of age and sex matched controls, we found that patients exhibited bilateral reductions of local gyrification index (lGI) in limbic cortical areas, including the parahippocampal and entorhinal cortex and the fusiform and lingual gyri, and altered diffusivity features in the underlying white matter. In patients with an earlier onset of seizures, worse psychiatric manifestations and cognitive impairment, reductions of lGI and diffusivity abnormalities in the limbic areas were more pronounced. Developmental abnormalities involving the limbic structures likely represent a measurable anatomic counterpart of the reduced contribution of the PCDH19 protein to local cortical folding and white matter organization and are functionally reflected in the phenotypic features involving cognitive and communicative skills as well as local epileptogenesis.
The Laboratory Diagnosis of Coronavirus Disease 2019— Frequently Asked Questions
Authors: Fang Ferric C , Naccache Samia N , Greninger Alexander L 
Published: June 2020

AbstractDiagnostic testing has played and will continue to play a major role in the coronavirus disease 2019 (COVID-19) pandemic. The ability to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in respiratory secretions is essential to determine when an individual is infected and potentially infectious to others. Viral detection is used for the identification, management, and isolation of individual patients. Viral detection is also used to determine when the virus has entered a community and how rapidly it is spreading. As communities attempt to reopen following periods of shutdown, the detection of both SARS-CoV-2 and specific antibodies that recognize the virus will become increasingly important as a means to assess infection and immunity in individuals and communities. Here, we discuss questions commonly asked by clinicians about COVID-19 diagnostic testing.
West Nile Virus–Associated Hospitalizations, California, 2004–2017
Authors: Snyder Robert E , Cooksey Gail Sondermeyer , Kramer Vicki , Jain Seema , Vugia Duc J 
Published: June 2020

Abstract

Background
West Nile virus (WNV) is the most commonly reported mosquito-borne disease in the USA. California reports more WNV disease than any other state.

Methods
We identified WNV-associated hospitalizations from 2004 through 2017 in California and estimated hospitalization incidence using Patient Discharge Data. We described demographic, geographic, and clinical characteristics of WNV hospitalizations; identified risk factors for in-hospital death; and tabulated hospitalization charges.

Results
From 2004 through 2017, 3109 Californians were hospitalized with WNV (median, 214 patients/year; range, 72–449). The majority were male (1983; 63.8%) and aged ≥60 years (1766; 56.8%). The highest median annual hospitalization rate (0.88 hospitalizations/100 000 persons) was in the Central Valley, followed by southern California (0.59 hospitalizations/100 000 persons). Most patients (2469; 79.4%) had ≥1 underlying condition, including hypertension, cardiovascular disease, diabetes, chronic kidney disease, or immunosuppression due to medications or disease. Median hospitalization length of stay was 12 days (interquartile range, 6–23 days). During hospitalization, 1317 (42%) patients had acute respiratory failure and/or sepsis/septic shock, 772 (24.8%) experienced acute kidney failure, and 470 (15.1%) had paralysis; 272 (8.8%) patients died. Nearly 47% (1444) of patients were discharged for additional care. During these 14 years, $838 680 664 (mean $59.9 million/year) was charged for WNV hospitalizations, 73.9% through government payers at a median charge of $142 321/patient.

Conclusions
WNV-associated hospitalizations were substantial and costly in California. Hospitalization incidence was higher in males, elderly persons, and patients with underlying conditions. WNV persists as a costly and severe public health threat in California.
Adam Smith’s view of economic inequality
Authors: Walraevens Benoît 
Published: June 2020

Abstract
Adam Smith has usually been seen as an economist who had a positive view of economic inequalities and who was more concerned with diminishing absolute poverty rather than inequalities. Recently though, Rasmussen (2016; ‘Adam smith on what is wrong with economic inequality, American Political Science Review, vol. 110, no. 2, 342–52’) argued that Smith worried about the effects of extreme inequalities on the morality and happiness of commercial societies. While we do not deny Smith’s worries on this front and provide new evidence here, the aim of this paper was to show that Smith cared more about the causes of inequalities than their level per se, or independently of the former. Interestingly, Smith seems to reconcile fairness with economic efficiency in his plea for the system of natural liberty in which inequalities arise from the efforts, talents and risk-taking of individuals and ultimately benefit the least well-off. Moreover, and contrary to what Rasmussen claims, Smith addresses several contemporary issues such as the links between inequalities, economic growth, social mobility and politics.