bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brain aging, Alzheimer's disease, and the role of stem cells in primate comparative studies
Authors: August Isabel , Semendeferi Katerina , Marchetto Maria Carolina 
Published: August 2022

AbstractAlzheimer's disease (AD) is a progressive neurodegenerative disease that is ultimately fatal. Currently, millions of Americans are living with AD, and this number is predicted to grow with increases in the aging population. Interestingly, despite the prevalence of AD in human populations, the full AD phenotype has not been observed in any nonhuman primate (NHP) species, and it has been suggested that NHPs are immune to neurodegenerative diseases such as AD.Here, we review the typical age‐related changes and pathologies in humans along with the neuropathologic changes associated with AD, and we place this information in the context of the comparative neuropathology of NHPs. We further propose the use of induced pluripotent stem cell technology as a way of addressing initial molecular processes and changes that occur in neurons and glia (in both humans and NHPs) when exposed to AD‐inducing pathology prior to cell death.
Contribution of tillers to maize yield stability at low plant density
Authors: Massigoge Ignacio , Ross Fernando , Fernández Javier A. , Echarte Laura , Ciampitti Ignacio A. , Cerrudo Anibal 
Published: August 2022

AbstractOne of the main challenges of using low plant densities in restrictive and variable environments is to maximize the use of resources in better‐than‐expected years. In this context, tillering could be an alternative to increase reproductive and vegetative plasticity. The objectives of this study were to (a) characterize the correlation between environmental conditions, tiller traits, crop grain yield, and grain yield advantages due to tillers; (b) determine the grain yield response to tillering (i.e., grain yield difference between tillered and nontillered crops) for a wide range of environments; and (c) to evaluate the effect of tiller presence on grain yield of the main shoot, considering its effect on the apical and subapical ears. Tillered and nontillered crops were evaluated under rainfed conditions during two seasons (2018–2019 and 2019–2020). These experiments were carried out at 11 sites in the southern Argentinean Pampas, varying sowing date (22 Oct. to 5 Dec.), plant density (2–3 plants m−2), genotype (AX7784 and AX7761), and soil depth. Grain yield (3.2–11.9 Mg ha−1) was correlated with tillers productivity, mainly explained by postflowering precipitations. The contribution of tillers to grain yield was more proportional than their consequent yield depression at the main shoot. Tillers either increased (3 sites) or maintained (8 sites) grain yield, and their contribution increased as the environment improved without any detrimental effect in the most restrictive environments. Tillering has the potential for increasing resource (radiation, water, nitrogen) use efficiency under low plant density strategies adopted for restrictive environments.
Cell geometry distinguishes migration‐associated heterogeneity in two‐dimensional systems
Authors: Varankar Sagar S , Hari Kishore , Kartika Sharon , Bapat Sharmila A , Jolly Mohit Kumar 
Published: August 2022

AbstractIn vitro migration assays are a cornerstone of cell biology and have found extensive utility in research. Over the past decade, several variations of the two‐dimensional (2D) migration assay have improved our understanding of this fundamental process. However, the ability of these approaches to capture the functional heterogeneity during migration and their accessibility to inexperienced users has been limited. We downloaded published time‐lapse 2D cell migration data sets and subjected them to feature extraction with the Fiji software. We used the “Analyze Particles” tool to extract 10 cell geometry features (CGFs), which were grouped into “shape,” “size,” and “position” descriptors. Next, we defined the migratory status of cells using the “MTrack2” plugin. All data obtained from Fiji were further subjected to rigorous statistical analysis with R version 4.0.2. We observed consistent associative trends between size and shape descriptors and validated our observations across four independent data sets. We used these descriptors to identify and characterize “nonmigrator (NM)” and “migrator (M)” subsets. Statistical analysis allowed us to identify considerable heterogeneity in the NM subset. Interestingly, differences in 2D‐packing appeared to affect CGF trends and heterogeneity within the migratory subsets. We developed an analytical pipeline using open source tools, to identify and morphologically characterize functional migratory subsets from label‐free, time‐lapse imaging data. Our quantitative approach identified heterogeneity between nonmigratory cells and predicted the influence of 2D‐packing on migration.
Sulfur‐Decorated Ni−N−C Catalyst for Electrocatalytic CO2 Reduction with Near 100 % CO Selectivity
Authors: Lu Song , Zhang Yang , Mady Mohamed F. , Egwu Eleri Obinna , Mekonnen Tucho Wakshum , Mazur Michal , Li Ang , Lou Fengliu , Gu Minfen , Yu Zhixin 
Published: August 2022

AbstractDeveloping highly efficient electrocatalysts for electrochemical CO2 reduction (ECR) to value‐added products is important for CO2 conversion and utilization technologies. In this work, a sulfur‐doped Ni−N−C catalyst is fabricated through a facile ion‐adsorption and pyrolysis treatment. The resulting Ni−NS−C catalyst exhibits higher activity in ECR to CO than S‐free Ni−N−C, yielding a current density of 20.5 mA cm−2 under −0.80 V versus a reversible hydrogen electrode (vs. RHE) and a maximum CO faradaic efficiency of nearly 100 %. It also displays excellent stability with negligible activity decay after electrocatalysis for 19 h. A combination of experimental investigations and DFT calculations demonstrates that the high activity and selectivity of ECR to CO is due to a synergistic effect of the S and Ni−NX moieties. This work provides insights for the design and synthesis of nonmetal atom‐decorated M−N−C‐based ECR electrocatalysts.
The deep multichannel discrete‐time cellular neural network model for classification
Authors: Abtioglu Emrah , Yalcin Mustak Erhan 
Published: August 2022

SummaryHigh latency and power consumption are two major problems that need to be addressed in convolutional neural networks (CNN). In this paper, the convolutional layer is replaced with a discrete‐time cellular neural network (CellNN) to overcome these problems. Multiple configurations of CellNNs are trained in a framework called TensorFlow to classify objects from the CIFAR‐10 database. Effects of the number of iterations, the number of channels, batch normalization, and activation functions on the classification accuracies are presented. It is shown that TensorFlow is a tool that is capable of training discrete‐time CellNNs. Although the accuracies of the proposed networks on CIFAR‐10 are slightly lesser than the existing CNNs, with reduced parameters and multiply‐accumulates (MACs), power consumption and computation time of our networks will be less than CNNs.
Enhanced resolution of marine viruses with violet side scatter
Authors: Zhao Yuan , Zhao Yanchu , Zheng Shan , Zhao Li , Zhang Wuchang , Xiao Tian , Grégori Gérald 
Published: August 2022

AbstractMarine viruses make up an essential compartment of the marine ecosystem. They are the most abundant organisms and represent one of the biggest sources of unknown biodiversity. Viruses also have an important impact on bacterial and algal mortality in the ocean, and as such have a major influence on microbial diversity and biogeochemical cycling. However, little is known about the abundance and distribution patterns of viruses across the oceans and seas. Over the last 20 years, flow cytometry has been the technique of choice to detect and count the viral particles in natural samples. Nevertheless, due to their small size, the detection of marine viruses is still extremely challenging. In this article we describe how a new generation of flow cytometer which uses the side scatter (SSC) of violet photons from a 405 nm laser beam helps to improve the resolution for detecting marine viruses. To the best of our knowledge, this is the first report where virioplankton has been detected in aquatic samples using flow cytometry with a 405 nm violet SSC instead of a 488 nm blue SSC.
Cytomorphology of spindle cell/sclerosing rhabdomyosarcoma, including MYOD1 (LI22R) mutation result
Authors: Rekhi Bharat , Dodd Leslie , Dharavath Bhaskar , Dutt Amit 
Published: August 2022

AbstractSpindle cell/sclerosing rhabdomyosarcoma (RMS), characterized by MYOD1 (L122R) mutation in a subset of cases is a newly described subtype of RMS. Presently, there is no documentation of cytomorphological features, especially of sclerosing RMS. Case 1: A 24‐year‐old male presented with pain and swelling in his wrist for a one‐year duration. MRI revealed a well‐defined soft tissue lesion measuring 5.3 cm, encasing the lower end of the ulna. Fine‐needle aspiration cytology (FNAC) smears revealed clusters of tumor cells with round to oval to spindle‐shaped nuclei, scant to moderate amount of cytoplasm with the wisps of the metachromatic stroma. Histopathological examination revealed a malignant tumor comprising cells with polygonal to spindle‐shaped nuclei, arranged in a sclerotic stroma. Immunohistochemically, the tumor cells were positive for desmin, myogenin, and MYOD1. A diagnosis of sclerosing RMS was offered. Furthermore, the tumor revealed MYOD1 (L122R) mutation. Case 2: A 43‐year‐old male presented with a 4‐month history of “nasal stuffiness” and pressure. Imaging revealed a poorly defined infiltrative lesion in his nasal cavity. FNAC smears revealed loose and tightly cohesive clusters of malignant cells with oval to spindle‐shaped nuclei, a moderate amount of ill‐defined bluish to finely vacuolated cytoplasm, and focal streak artifact with interspersed stromal fragments. Histopathological examination revealed a malignant tumor composed of oval to spindle‐shaped nuclei, embedded in a variably hyalinized stroma. Immunohistochemically, the tumor cells were positive for desmin, and myogenin. Diagnosis of spindle cell/sclerosing RMS was offered. The present study constitutes one of the first documentation of cytomorphological features of two rare cases of spindle cell/sclerosing RMS. The differential diagnoses and treatment‐related implications are presented.
Comparison of six surrogate insulin resistance indexes for predicting the risk of incident stroke: The Rural Chinese Cohort Study
Authors: Zhao Yang , Zhang Jinli , Chen Chuanqi , Qin Pei , Zhang Ming , Shi Xuezhong , Yang Yongli , Lu Jie , Sun Liang , Hu Dongsheng 
Published: August 2022

AbstractBackground and PurposeSome cheap and easily used operated indexes of insulin resistance (IR) were currently available. We aimed to evaluate the association of six surrogate indexes of IR with incident stroke and to compare their predictive capacity.MethodsWe analysed data from 14,595 eligible study participants from the Rural Chinese Cohort Study. Modified Poisson regression models were used to estimate relative risks (RRs) and 95% confidence intervals (95% CIs) of incident stroke associated with the visceral adiposity index (VAI), the Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), triglyceride‐glucose (TyG), TyG‐body mass index, and TyG‐waist circumference. The receiver operator characteristic curve was used to compare the ability of the abovementioned IR indexes to predict stroke.ResultsDuring a median follow‐up of 6 years, 786 newly diagnosed stroke cases were identified. The levels of six surrogate indexes of IR were all significantly higher in the stroke population than in the non‐stroke population (p < 0.001). Compared with quartile 1, the multivariable adjusted RRs (95% CIs) of incident stroke for quartile 4 were 2.01 (1.47–2.76), 1.62 (1.28, 2.04), 1.64 (1.28–2.09), and 1.92 (1.50–2.45) for CVAI, VAI, LAP, and TyG, respectively. Significant dose–response associations were also found between surrogate IR indexes and risk of stroke. The area under the curves|areas under the curves for CVAI (0.674) was significantly greater than for other indexes (TyG‐WC:0.622, TyG:0.614, LAP:0.606, TyG‐BMI:0.598, and VAI:0.577) (p < 0.001).ConclusionsSix surrogate indexes of IR were independently associated with incident stroke. The CVAI may be the most suitable index for stroke prediction.
Long‐term effects of artificial nighttime lighting and trophic complexity on plant biomass and foliar carbon and nitrogen in a grassland community
Authors: Anic Vinka , Gaston Kevin J. , Davies Thomas W. , Bennie Jonathan 
Published: August 2022

AbstractThe introduction of artificial nighttime lighting due to human settlements and transport networks is increasingly altering the timing, intensity, and spectra of natural light regimes worldwide. Much of the research on the impacts of nighttime light pollution on organisms has focused on animal species. Little is known about the impacts of daylength extension due to outdoor lighting technologies on wild plant communities, despite the fact that plant growth and development are under photoperiodic control. In a five‐year field experiment, artificial ecosystems (“mesocosms”) of grassland communities both alone or in combination with invertebrate herbivores and predators were exposed to light treatments that simulated street lighting technologies (low‐pressure sodium, and light‐emitting diode [LED]‐based white lighting), at ground‐level illuminance. Most of the plant species in the mesocosms did not exhibit changes in biomass accumulation after 5 years of exposure to the light treatments. However, the white LED treatment had a significant negative effect on biomass production in the herbaceous species Lotus pedunculatus. Likewise, the interaction between the white LED treatment and the presence of herbivores significantly reduced the mean shoot/root ratio of the grass species Holcus lanatus. Artificial nighttime lighting had no effect on the foliar carbon or nitrogen in most of the grassland species. Nevertheless, the white LED treatment significantly increased the leaf nitrogen content in Lotus corniculatus in the presence of herbivores. Long‐term exposure to artificial light at night had no general effects on plant biomass responses in experimental grassland communities. However, species‐specific and negative effects of cool white LED lighting at ground‐level illuminance on biomass production and allocation in mixed plant communities are suggested by our findings. Further studies on the impacts of light pollution on biomass accumulation in plant communities are required as these effects could be mediated by different factors, including herbivory, competition, and soil nutrient availability.
Guidelines for model adaptation: A study of the transferability of a general seagrass ecosystem Dynamic Bayesian Networks model
Authors: Hatum Paula Sobenko , McMahon Kathryn , Mengersen Kerrie , Wu Paul Pao‐Yen 
Published: August 2022

AbstractIn general, it is not feasible to collect enough empirical data to capture the entire range of processes that define a complex system, either intrinsically or when viewing the system from a different geographical or temporal perspective. In this context, an alternative approach is to consider model transferability, which is the act of translating a model built for one environment to another less well‐known situation. Model transferability and adaptability may be extremely beneficial—approaches that aid in the reuse and adaption of models, particularly for sites with limited data, would benefit from widespread model uptake. Besides the reduced effort required to develop a model, data collection can be simplified when transferring a model to a different application context. The research presented in this paper focused on a case study to identify and implement guidelines for model adaptation. Our study adapted a general Dynamic Bayesian Networks (DBN) of a seagrass ecosystem to a new location where nodes were similar, but the conditional probability tables varied. We focused on two species of seagrass (Zostera noltei and Zostera marina) located in Arcachon Bay, France. Expert knowledge was used to complement peer‐reviewed literature to identify which components needed adjustment including parameterization and quantification of the model and desired outcomes. We adopted both linguistic labels and scenario‐based elicitation to elicit from experts the conditional probabilities used to quantify the DBN. Following the proposed guidelines, the model structure of the general DBN was retained, but the conditional probability tables were adapted for nodes that characterized the growth dynamics in Zostera spp. population located in Arcachon Bay, as well as the seasonal variation on their reproduction. Particular attention was paid to the light variable as it is a crucial driver of growth and physiology for seagrasses. Our guidelines provide a way to adapt a general DBN to specific ecosystems to maximize model reuse and minimize re‐development effort. Especially important from a transferability perspective are guidelines for ecosystems with limited data, and how simulation and prior predictive approaches can be used in these contexts.
Functional traits underlying performance variations in the overwintering of the cosmopolitan invasive plant water hyacinth (Eichhornia crassipes) under climate warming and water drawdown
Authors: Huang Xiaolong , Ke Fan , Li Qisheng , Zhao Yu , Guan Baohua , Li Kuanyi 
Published: August 2022

AbstractReports of the Intergovernmental Panel on Climate Change (IPCC) indicate that temperature rise is still the general trend of the global climate in the 21st century. Invasive species may benefit from the increase in temperature, as climate can be viewed as a resource, and the increase in the available resources favors the invasibility of invasive species. This study aimed to assess the overwintering growth of the cosmopolitan invasive plant water hyacinth (Eichhornia crassipes) at its northern boundary. Using E. crassipes as a model plant, a cross‐year mesocosm experiment was conducted to determine 17 plant functional traits, including growth, morphological, root topological, photosynthetic, and stoichiometric traits, under climate warming (ambient, temperature rises of 1.5°C and 3.0°C), and water drawdown or water withdrawal (water depths of 1, 10, and 20 cm) treatments. The overwintering growth of E. crassipes was facilitated by climate warming and proper water drawdown, and climate warming played a leading role. A temperature rises of 3.0°C and a water depth of 10 cm were the most suitable conditions for the overwintering and rooting behavior of the plant. Controlling the temperature to within 1.5°C, an ambitious goal for China, still facilitated the overwintering of E. crassipes. With climate warming, the plant can overwinter successfully, which possibly assists it in producing and spreading new ramets in the vernal flood season. The new rooting behavior induced by ambient low temperature may be viewed as a unique growth adaptation strategy for a niche change, as it helps these plants invade empty niches left by dead free‐floating plants on the water surface following winter freezes. With continued global warming, the distribution of the plant may expand northward, and eradication of the plant during the winter water drawdown period may be a more effective strategy.
Improving measurements of the falling trajectory and terminal velocity of wind‐dispersed seeds
Authors: Zhu Jinlei , Buchmann Carsten M. , Schurr Frank M. 
Published: August 2022

AbstractSeed dispersal by wind is one of the most important dispersal mechanisms in plants. The key seed trait affecting seed dispersal by wind is the effective terminal velocity (hereafter “terminal velocity”, Vt), the maximum falling speed of a seed in still air. Accurate estimates of Vt are crucial for predicting intra‐ and interspecific variation in seed dispersal ability. However, existing methods produce biased estimates of Vt for slow‐ or fast‐falling seeds, fragile seeds, and seeds with complex falling trajectories. We present a new video‐based method that estimates the falling trajectory and Vt of wind‐dispersed seeds. The design involves a mirror that enables a camera to simultaneously record a falling seed from two perspectives. Automated image analysis then determines three‐dimensional seed trajectories at high temporal resolution. To these trajectories, we fit a physical model of free fall with air resistance to estimate Vt. We validated this method by comparing the estimated Vt of spheres of different diameters and materials to theoretical expectations and by comparing the estimated Vt of seeds to measurements in a vertical wind tunnel. Vt estimates closely match theoretical expectations for spheres and vertical wind tunnel measurements for seeds. However, our Vt estimates for fast‐falling seeds are markedly higher than those in an existing trait database. This discrepancy seems to arise because previous estimates inadequately accounted for seed acceleration. The presented method yields accurate, efficient, and affordable estimates of the three‐dimensional falling trajectory and terminal velocity for a wide range of seed types. The method should thus advance the understanding and prediction of wind‐driven seed dispersal.
Cupric Halide‐Promoted Stereoselective Intramolecular Cis‐Addition to Construct (Z)‐Chloro(bromo)benzo[c,d]indoles
Authors: Diao Hanying , Liu Li , Wang Jin , Lin Yanfei , Zhao Xiangyuan , Zeng Heyang , Shi Senlei , Gao Wei , Yang Long , Du Guanben , Zhang Lianpeng 
Published: August 2022

AbstractA convenient and efficient method for one pot synthesis of polysubstituted (Z)‐halobenzo[c,d]indoles from 8‐alkynyl‐1‐naphthylamine derivatives using CuCl2 and CuBr2 as the halogenated reagents has been developed. In this protocol, both (Z)‐chloro and bromobenzo[c,d] indole derivatives can be obtained in moderate to good yields by copper halide‐promoted stereoselective intramolecular cis‐addition annulation reactions. A novel fluorescent molecule with AIE properties was constructed via Suzuki coupling reaction and its optical properties was investigated, which made them possible candidates for optoelectronic conjugated materials.
Uncertainty: Nothing is more certain
Authors: Cripps Sally , Durrant‐Whyte Hugh 
Published: August 2022

AbstractThis articles discusses the importance and types of uncertainty in environmental science. Uncertainty is categorized into four types, three of which are familiar to statisticians and one of which is introduced by the authors as knowledge uncertainty. The article claims that the Bayesian paradigm is a logically consistent mechanism, and a useful framework for decision makers in environmental science, to manage and quantify the first three types of uncertainty. However knowledge uncertainty, common in environmental sciences, requires more detailed thought and more nuanced management strategies for robust decision making in the environment. The article concludes with the observation that only if we acknowledge the uncertainty inherent in inferring complex quantities from data can we make robust and explainable policy decisions that build trust with the public.