bluuebunny/crossref_metadata_2025 huggingface dataset:
Semantic Analysis for Conversational Datasets: Improving Their Quality Using Semantic Relationships
Authors: Krommyda Maria , Kantere Verena
Published: November 2020

As more and more datasets become available, their utilization in different applications increases in popularity. Their volume and production rate, however, means that their quality and content control is in most cases non-existing, resulting in many datasets that contain inaccurate information of low quality. Especially, in the field of conversational assistants, where the datasets come from many heterogeneous sources with no quality assurance, the problem is aggravated. We present here an integrated platform that creates task- and topic-specific conversational datasets to be used for training conversational agents. The platform explores available conversational datasets, extracts information based on semantic similarity and relatedness, and applies a weight-based score function to rank the information based on its value for the specific task and topic. The finalized dataset can then be used for the training of an automated conversational assistance over accurate data of high quality.
Wong–Zakai approximations and long term behavior of stochastic FitzHugh–Nagumo system
Authors: Qin Ling , Ma Dandan , Shu Ji
Published: November 2020

This paper is concerned with the Wong–Zakai approximations given by a stationary process via the Wiener shift and their associated long term behavior of stochastic FitzHugh–Nagumo system driven by white noise. We prove the existence and uniqueness of pullback random attractors for the approximate system under much weaker conditions than the original system. When the system is driven by additive white noise, we also prove the convergence of solutions of Wong–Zakai approximations and the upper semicontinuity of random attractors of the approximate random system as the size of approximation approaches zero.
Engineering edge-exposed MoS2 nanoflakes anchored on the 3D cross-linked carbon frameworks for enhanced lithium storage
Authors: Huang Peng , Wu Yang , Wang Xinxin , Chen Peng , Li Shuigen , Ding Yuan-Li
Published: November 2020

High-rate capability and long cycle life are currently the two most major challenges for high-power rechargeable batteries such as lithium-ion batteries (LIBs), sodium-ion batteries (SIBs). Developing electroactive materials with high-efficiency electron/ion transport network and robust mechanical stability is a key. Herein, we have successfully designed and fabricated 3D cross-linked nitrogen-doped carbon nanosheet frameworks with good interconnection and hierarchical nanostructures, and simultaneously decorated edge-enriched molybdenum disulfide (MoS[Formula: see text] nanoflakes inside the whole carbon scaffold via a salt template assisted confinement pyrolysis strategy, yielding the unique 3D carbon scaffold/MoS2 hybrids. In such a design, such hybrids not only facilitate lithium diffusion kinetics and efficient utilization of MoS2nanoflakes owing to much exposed edges and well interconnection between active components and carbon frameworks, but also provide highly efficient electron/ion transport pathway. When evaluated as anode for lithium storage, the obtained products show superior rate capability of 284 mAh g[Formula: see text] up to 5 A g[Formula: see text] and long-term cycling stability. This work demonstrates an efficient solution to design and construct a high-efficiency electron/ion transport network for high-power applications for energy storage devices.
Constant-approximation for minimum weight partial sensor cover
Authors: Liu Siwen , Du Hongmin W.
Published: November 2020

Consider a set of homogeneous wireless sensors, [Formula: see text] with nonnegative weight [Formula: see text] for each sensor [Formula: see text]. Let [Formula: see text] be a set of target points. Given a integer [Formula: see text], we study the minimum weight partial sensor cover problem, that is, find the minimum total weight subset of sensors covering at least [Formula: see text] target points in [Formula: see text]. In this paper, we show the existence of polynomial-time constant-approximation for this problem.
Majority bad number
Authors: Anandha Prabhavathy S.
Published: November 2020

A two-valued function [Formula: see text] defined on the vertices of a graph [Formula: see text] is a majority bad dominating function, briefly (MBDF) if the sum of its function values over at least half the closed neighborhoods is at most one. That is, for at least half the vertices [Formula: see text], [Formula: see text], where [Formula: see text] consists of [Formula: see text] and every vertex adjacent to [Formula: see text]. The majority bad domination number of a graph [Formula: see text] is denoted by [Formula: see text] and is defined as [Formula: see text]. In this paper, we initiate the study of majority bad number in graphs.
A malaria model with Caputo–Fabrizio and Atangana–Baleanu derivatives
Authors: Abboubakar Hamadjam , Kumar Pushpendra , Rangaig Norodin A. , Kumar Sachin
Published: November 2020

In this paper, we study two fractional models in the Caputo–Fabrizio sense and Atangana–Baleanu sense, in which the effects of malaria infection on mosquito biting behavior and attractiveness of humans are considered. Using Lyapunov theory, we prove the global asymptotic stability of the unique endemic equilibrium of the integer-order model, and the fractional models, whenever the basic reproduction number [Formula: see text] is greater than one. By using fixed point theory, we prove existence, and conditions of the uniqueness of solutions, as well as the stability and convergence of numerical schemes. Numerical simulations for both models, using fractional Euler method and Adams–Bashforth method, respectively, are provided to confirm the effectiveness of used approximation methods for different values of the fractional-order [Formula: see text].
Significant Applications of Machine Learning for COVID-19 Pandemic
Authors: Kushwaha Shashi , Bahl Shashi , Bagha Ashok Kumar , Parmar Kulwinder Singh , Javaid Mohd , Haleem Abid , Singh Ravi Pratap
Published: November 2020

Machine learning is an innovative approach that has extensive applications in prediction. This technique needs to be applied for the COVID-19 pandemic to identify patients at high risk, their death rate, and other abnormalities. It can be used to understand the nature of this virus and further predict the upcoming issues. This literature-based review is done by searching the relevant papers on machine learning for COVID-19 from the databases of SCOPUS, Academia, Google Scholar, PubMed, and ResearchGate. This research attempts to discuss the significance of machine learning in resolving the COVID-19 pandemic crisis. This paper studied how machine learning algorithms and methods can be employed to fight the COVID-19 virus and the pandemic. It further discusses the primary machine learning methods that are helpful during the COVID-19 pandemic. We further identified and discussed algorithms used in machine learning and their significant applications. Machine learning is a useful technique, and this can be witnessed in various areas to identify the existing drugs, which also seems advantageous for the treatment of COVID-19 patients. This learning algorithm creates interferences out of unlabeled input datasets, which can be applied to analyze the unlabeled data as an input resource for COVID-19. It provides accurate and useful features rather than a traditional explicitly calculation-based method. Further, this technique is beneficial to predict the risk in healthcare during this COVID-19 crisis. Machine learning also analyses the risk factors as per age, social habits, location, and climate.
Closing note for the HCI education forum
Authors: Grandhi Sukeshini
Published: November 2020

HCI education reflects the continual evolution of HCI, embracing the changing landscapes of technology, infrastructure, and technology use. This forum aims to provide a platform for HCI educators, practitioners, researchers, and students to share their perspectives, reflections, and experiences related to HCI education.
--- Sukeshini A. Grandhi, Editor
IS Reappraisal and Technology Adaptation Behaviors
Authors: Weinert Christoph , Maier Christian , Laumer Sven , Weitzel Tim
Published: November 2020

Employees have to adapt to newly implemented information systems (IS) because they are often perceived as radical changes or disruptions. To understand such adaptation behavior, IS research suggests that employees first appraise the new IS and second perform technology adaptive behaviors. However, while the psychology literature indicates that adaptation is a continuous process unfolding over time, previous IS literature treats adaptation towards IS implementation as a rather singular, noniterative process. As firms continue to implement IS, an understanding of reappraisal and the influence of technology adaptation behavior is vital to ensure successful implementations. Therefore, the present paper investigates reappraisal and the influences of four different technology adaptation behaviors. We conducted a longitudinal study and used hierarchical linear modeling (HLM) to validate our research model. The findings reveal that employees reappraise the newly implemented IS over time regarding perceived opportunity, threat, and controllability and demonstrate that technology adaption behaviors influence such reappraisal. One specific finding is that employees might get into positive or negative reappraisal loops. We thereby contribute to research by extending the adaptation behavior literature and add a new piece of the puzzle to understand how employees adapt towards newly implemented IS over time.
What Do We Really Know About Adaptation at Range Edges?
Authors: Angert Amy L. , Bontrager Megan G. , Ågren Jon
Published: November 2020

Recent theory and empirical evidence have provided new insights regarding how evolutionary forces interact to shape adaptation at stable and transient range margins. Predictions regarding trait divergence at leading edges are frequently supported. However, declines in fitness at and beyond edges show that trait divergence has sometimes been insufficient to maintain high fitness, so identifying constraints to adaptation at range edges remains a key challenge. Indirect evidence suggests that range expansion may be limited by adaptive genetic variation, but direct estimates of genetic constraints at and beyond range edges are still scarce. Sequence data suggest increased genetic load in edge populations in several systems, but its causes and fitness consequences are usually poorly understood. The balance between maladaptive and positive effects of gene flow on fitness at range edges deserves further study. It is becoming increasingly clear that characterizations about degree of adaptation based solely on geographical peripherality are unsupported.
The Roles of Fluid Hydrodynamics, Mass Transfer, Rust Layer and Macro-Cell Current on Flow Accelerated Corrosion of Carbon Steel in Oxygen Containing Electrolyte
Authors: Liu Liang , Xu Yunze , Zhu Yesen , Wang Xiaona , Huang Yi
Published: November 2020

The flow accelerated corrosion (FAC) of EH 36 carbon steel in the oxygen containing flowing electrolyte is studied using multi-electrode array arranged in a jet rig system. The FAC of the working electrodes (WEs) under both uncoupled and coupled conditions are investigated in conjunction with computational fluid dynamics (CFD) simulation. Results show that a higher mass transfer rate would lead to a higher FAC rate when the WEs are uncoupled. The rust layer could retard the oxygen diffusion, resulting in the FAC rate decreasing. The mass transfer process and the distribution of the rust layer are significantly influenced by the fluid hydrodynamics. However, when the WEs are coupled together, serious FAC damage would occur on the WEs where lower mass transfer rates are registered. The macro-cell currents would become the main lead of FAC propagation at coupled conditions.
Dihydroceramides: their emerging physiological roles and functions in cancer and metabolic diseases
Authors: Lachkar Floriane , Ferré Pascal , Foufelle Fabienne , Papaioannou Alexandra
Published: November 2020

Dihydroceramides (DhCers) are a type of sphingolipids that for a long time were regarded as biologically inactive. They are metabolic intermediates of the de novo sphingolipid synthesis pathway, and are converted into ceramides (Cers) with the addition of a double bond. Ceramides are abundant in tissues and have well-established biological functions. On the contrary, dihydroceramides are less prevalent, and despite their hitherto characterization as inert lipids, studies of the past decade began to unravel their implication in various biological processes distinct from those involving ceramides. These processes include cellular stress responses and autophagy, cell growth, pro-death or pro-survival pathways, hypoxia, and immune responses. In addition, their plasma concentration has been related to metabolic diseases and shown as a long-term predictor of type 2 diabetes onset. They are thus important players and potential biomarkers in pathologies ranging from diabetes to cancer and neurodegenerative diseases. The purpose of this mini-review is to highlight the emergence of dihydroceramides as a new class of bioactive sphingolipids by reporting recent advances on their biological characterization and pathological implications, focusing on cancer and metabolic diseases.
Assessment of individual and standardized glucagon kinetics in healthy humans
Authors: Laurenti Marcello C. , Vella Adrian , Adams Jon D. , Schembri Wismayer Daniel J. , Egan Aoife M. , Dalla Man Chiara
Published: November 2020

State-of-the-art measurement of insulin secretion in humans is accomplished by deconvolution of peripheral C-peptide concentrations using population-derived parameters of C-peptide kinetics. In contrast, knowledge of the kinetic parameters of glucagon in humans is lacking so that measurement of glucagon secretion to date is largely qualitative. This series of experiments enabled measurement of glucagon kinetics in 51 subjects, and subsequently, stepwise linear regression was used to correlate these parameters with anthropometric characteristics. This enabled the development of a population-based model using anthropometric characteristics to predict the volume of distribution and the rate of clearance. This is a necessary first step in the development of a model to quantitate of glucagon secretion and action (and its contribution to glucose tolerance) in large populations.
Characterization of Oral Microbiome and Exploration of Potential Biomarkers in Patients with Pancreatic Cancer
Authors: Sun Haiyang , Zhao Xia , Zhou Yanxia , Wang Jun , Ma Rui , Ren Xi , Wang Huaizhi , Zou Lingyun
Published: November 2020

Pancreatic cancer (PC) is highly malignant and lacks an effective therapeutic schedule, hence that early diagnosis is of great importance to achieve a good prognosis. Oral bacteria have been proved to be associated with pancreatic cancer, but the specific mechanism has not been comprehensively illustrated. In our study, thirty‐seven saliva samples in total were collected with ten from PC patients, seventeen from benign pancreatic disease (BPD) patients, and ten from healthy controls (HC). The oral bacterial community of HC, PC, and BPD groups was profiled by 16S rDNA high‐throughput sequencing and bioinformatic methods. As shown by Simpson, Inverse Simpson, Shannon and Heip, oral microbiome diversity of HC, BPD and PC groups is in increasing order with the BPD and PC groups significantly higher than the HC group. Principal coordinate analysis (PCoA) suggested that grouping by PC, BPD and HC was statistically significant. The linear discriminant analysis effect size (LEfSe) identified high concentrations of Fusobacterium periodonticum and low concentrations of Neisseria mucosa as specific risk factors for PC. Furthermore, predicted functions showed changes such as RNA processing and modification as well as the pathway of NOD‐like receptor signaling occurred in both PC and HC groups. Conclusively, our findings have confirmed the destruction of oral bacterial community balance among patients with PC and BPD and indicated the potential of Fusobacterium periodonticum and Neisseria mucosa as diagnostic biomarkers of PC.
A New Collaborative Filtering Recommendation Method Based on Transductive SVM and Active Learning
Authors: Wang Xibin , Dai Zhenyu , Li Hui , Yang Jianfeng
Published: November 2020

In the collaborative filtering (CF) recommendation applications, the sparsity of user rating data, the effectiveness of cold start, the strategy of item information neglection, and user profiles construction are critical to both the efficiency and effectiveness of the recommendation algorithm. In order to solve the above problems, a personalized recommendation approach combining semisupervised support vector machine and active learning (AL) is proposed in this paper, which combines the benefits of both TSVM (Transductive Support Vector Machine) and AL. Firstly, a “maximum-minimum segmentation” of version space-based AL strategy is developed to choose the most informative unlabeled samples for human annotation; it aims to choose the least data which is enough to train a high-quality model. And then, an AL-based semisupervised TSVM algorithm is proposed to make full use of the distribution characteristics of unlabeled samples by adding a manifold regularization into objective function, which is helpful to make the proposed algorithm to overcome the traditional drawbacks of TSVM. Furthermore, during the procedure of recommendation model construction, not only user behavior information and item information, but also demographic information is utilized. Due to the benefits of the above design, the quality of unlabeled sample annotation can be improved; meanwhile, both the data sparsity and cold start problems are alleviated. Finally, the effectiveness of the proposed algorithm is verified based on UCI datasets, and then it is applied to personalized recommendation. The experimental results show the superiority of the proposed method in both effectiveness and efficiency.
Mathematical Modeling of Echinococcosis in Humans, Dogs, and Sheep
Authors: Birhan Getachew Bitew , Munganga Justin Manango W. , Hassan Adamu Shitu
Published: November 2020

In this paper, a model for the transmission dynamics of cystic echinococcosis in the dog, sheep, and human populations is developed and analyzed. We first model and analyze the predator-prey interaction model in these populations; then, we propose a mathematical model of the transmission dynamics of cystic echinococcosis. We calculate the basic reproduction number

R

0

and prove that the disease-free equilibrium is globally asymptotically stable, and hence, the disease dies out if

R

0

>
1

. We further show that the endemic equilibrium is globally asymptotically stable, and hence, the disease persists if

R

0

<
1

. Numerical simulations are performed to illustrate our analytic results. We give sensitivity analysis of the key parameters and give strategies that are helpful to control the transmission of cystic echinococcosis, from which the most sensitive parameter is the transmission rate of Echinococcus’ eggs from the environment to sheep (

β

es

). Thus, the effective controlling strategies are associated with this parameter.
The Effect of PVP Molecular Weight on Dissolution Behavior and Physicochemical Characterization of Glycyrrhetinic Acid Solid Dispersions
Authors: Sui Xiaoyu , Chu Yan , Zhang Jie , Zhang Honglian , Wang Huiyu , Liu Tingting , Han Cuiyan
Published: November 2020

The effect of polyvinylpyrrolidone (PVP) as glycyrrhetic acid (GA) solid dispersions carrier at different molecular weights on the dissolution behavior and physicochemical properties was investigated. PVP-GA-SDs prepared with all four molecular weight PVPs displayed good enhancement of dissolution rate and equilibrium solubility compared with pure drug and corresponding physical mixtures. The results showed that the enhancement effect of molecular weight on dissolution rate and equilibrium solubility follows

PVP
 
K
30
>
PVP
 
K
60
>
PVP
 
K
17
>
PVP
 
K
15

. In addition, the dissolution rate and solubility of the SDs with a carrier-drug ratio of 8 : 1 were better than the samples of 4 : 1. The DSC and XRD patterns showed that the crystallization of GA in SDs prepared by PVP K30 and PVP K60 was significantly inhibited, and both were transformed to amorphous. Based on FTIR and Raman detection, a hydrogen-bond between PVP and drug molecules is formed. SEM results showed that there were no significant differences in the appearance of SDs prepared with four PVPs, and no crystalline morphology of GA was seen. In conclusion, the findings of this study demonstrated that the dissolution performance of the PVP-GA-SDs prepared by the solvent method is related to the molecular weight of PVP, and the change in the molecular weight of PVP does not cause a monotonic change in dissolution of GA. The samples with PVP K30 as the carrier have the best dissolution performance.
Shift the Photocatalytic Activity of P25 TiO2 Nanoparticles toward the Visible Region upon Surface Modification with Organic Hybrid of Phosphotungstate
Authors: Taghdiri Mehdi , Dadari Doolabi Shahrban
Published: November 2020

In this study, a visible-light-driven P25 TiO2 was prepared upon surface modification with a colored organic hybrid of phosphotungstic acid that makes titanium dioxide suitable for photocatalytic degradation of organic pollutants under visible and sunlight irradiation. Visible shifting of the photocatalytic activity of surface-modified TiO2 was examined by studying the decolorization of methylene blue (MB) and rhodamine B (RhB). The results show that colored TiO2 is, unlike bare TiO2, a good photocatalyst in the degradation of dyes under visible and sunlight irradiation. Surface-modified Al2O3 and reduced graphene oxide (RGO) with organic hybrid of phosphotungstate failed to degrade RhB under sunlight irradiation, which prove the role of TiO2 in the photochemical process.
Large-Scale Internetwork Functional Connectivity Mediates the Relationship between Serum Triglyceride and Working Memory in Young Adulthood
Authors: Wang Chunli , Cai Huanhuan , Sun Xuetian , Si Li , Zhang Min , Xu Yuanhong , Qian Yinfeng , Zhu Jiajia
Published: November 2020

Previous research has demonstrated that serum lipid profile is associated with cognitive function as well as brain structure and function in middle-aged, elderly, and clinical populations. However, the nature and extent of lipids-brain-cognition relationships in young adulthood are largely unknown. In this study, 157 healthy young adults underwent resting-state functional MRI scans. Functional connectivity between and within 14 functional networks were calculated using independent component analysis. Peripheral venous blood samples were collected to measure serum lipids. Working memory was assessed using a 3-back task. Linear regression, correlation, and mediation analyses were conducted to test for potential associations between serum lipids, inter- and intranetwork functional connectivity, and working memory performance. We found that higher serum triglyceride (TG) level was correlated with stronger connectivity between left frontoparietal and ventral attention networks, between right frontoparietal and dorsal attention networks, between right frontoparietal and dorsal sensorimotor networks, between right frontoparietal and lateral visual networks, and between salience (SN) and ventral sensorimotor (vSMN) networks, as well as lower connectivity between posterior default mode and left frontoparietal networks, between left frontoparietal and medial visual networks, and between ventral attention and dorsal sensorimotor networks. In addition, higher SN-vSMN connectivity was related to lower 3-back accuracy. More importantly, the relationship between serum TG and 3-back accuracy was mediated by SN-vSMN connectivity. Our findings not only may expand existing knowledge regarding serum lipids-brain-cognition relations from the perspective of large-scale functional network organization but also may inform a translational conceptualization of how to improve cognitive function through regulating serum lipids.
Targeting TSH and IGF-1 Receptors to Treat Thyroid Eye Disease
Authors: Neumann Susanne , Krieger Christine C. , Gershengorn Marvin C.
Published: November 2020

Graves’ disease (GD) is an autoimmune disease caused in part by thyroid-stimulating antibodies (TSAbs) that activate the thyroid-stimulating hormone receptor (TSHR). In Graves’ hyperthyroidism (GH), TSAbs cause persistent stimulation of thyroid cells leading to continuous thyroid hormone synthesis and secretion. Thyroid eye disease (TED), also called Graves’ orbitopathy, is an orbital manifestation of GD. We review the important roles of the TSHR and the insulin-like growth factor 1 receptor (IGF-1R) in the pathogenesis of TED and discuss a model of TSHR/IGF-1R crosstalk that considers two pathways initiated by TSAb activation of TSHR in the eye, an IGF-1R-independent and an IGF-1R-dependent signaling pathway leading to hyaluronan (HA) secretion in orbital fibroblasts. We discuss current and future therapeutic approaches targeting the IGF-1R and TSHR. Teprotumumab, a human monoclonal anti-IGF-1R-blocking antibody, has been approved as an effective treatment in patients with TED. However, as the TSHR seems to be the primary target for TSAbs in patients with GD, future therapeutic interventions directly targeting the TSHR, e.g. blocking antibodies and small molecule antagonists, are being developed and have the advantage to inhibit the IGF-1R-independent as well as the IGF-1R-dependent component of TSAb-induced HA secretion. Antigen-specific immunotherapies using TSHR peptides to reduce serum TSHR antibodies are being developed also. These TSHR-targeted strategies also have the potential to treat both GH and TED with the same drug. We propose that combination therapy targeting TSHR and IGF-1R may be an effective and better tolerated treatment strategy for TED.
Factors Facilitating Early Emotion Understanding Development: Contributions to Individual Differences
Authors: Ogren Marissa , Johnson Scott P.
Published: November 2020

Children’s emotion understanding is crucial for healthy social and academic development. The behaviors influenced by emotion understanding in childhood have received much attention, but less focus has been placed on factors that may predict individual differences in emotion understanding, the principal issue addressed in the current review. A more thorough understanding of the developmental underpinnings of this skill may allow for better prediction of emotion understanding, and for interventions to improve emotion understanding early in development. Here, we present theoretical arguments for the substantial roles of three aspects of children’s environments in the development of emotion understanding: family expressiveness, discussions about emotions, and language development, and we discuss how these are interrelated. Ultimately, this may aid in predicting the effects of environmental influences on the development of emotion understanding more broadly and the mechanisms by which they do so.
Multiple Microbleeds: A Serious Neurological Manifestation in a Critically Ill COVID-19 Patient
Authors: Haroon Khawaja Hassan , Patro Satya Narayana , Hussain Suhail , Zafar AbdulAziz , Muhammad Ahmad
Published: November 2020

Coronavirus disease 2019 (COVID-19) is a viral illness caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is worldwide emerging evidence of multisystem involvement including different neurological manifestations in COVID-19 patients. As a result, healthcare systems worldwide are not only experiencing diagnostic but also therapeutic and prognostic challenges with COVID-19-related complications. Cerebral microbleeds and leukoencephalopathy have been described in COVID-19 patients; although the mechanism remains unknown, possibilities include endotheliitis with thrombotic microangiopathy, excessive inflammation, prolonged respiratory failure, and hypoxemia. We describe here the clinical, radiological, and laboratory findings as well as the 90-day outcome of a 72-year-old gentleman who presented with severe SARS-CoV-2 infection, leading to diffuse cerebral microhemorrhages and ischemic infarct causing severe morbidity. He was tested positive for COVID-19 confirmed by reverse transcriptase polymerase chain reaction.
Assessment of Heterogeneity in Heart Failure–Related Meta-Analyses
Authors: Khan Muhammad Shahzeb , Li Lin , Yasmin Farah , Khan Safi U. , Bajaj Navkaranbir S. , Pandey Ambarish , Murad M. Hassan , Fonarow Gregg C. , Butler Javed , Vaduganathan Muthiah
Published: November 2020

Background:

Assessment of heterogeneity in meta-analyses is critical to ensure the consistency of pooled results. Therefore, we sought to assess the evaluation and reporting of heterogeneity in heart failure (HF) meta-analyses.

Methods:

Study level meta-analyses pertaining to HF were selected from January 2009 to July 2019, published in 11 high impact factor journals. We tabulated the overall proportion of the meta-analyses reporting statistical heterogeneity and specific metrics and methods employed to quantify and explore heterogeneity.

Results:

Of 126 HF meta-analyses (612 outcomes), heterogeneity was reported for 422 outcomes (68.9 %) in 108 meta-analyses. Out of the 422 outcomes reporting statistical heterogeneity, 137 outcomes (32.5%) had no observable heterogeneity: (
I
2
=0%), 40 outcomes (9.5%) had low heterogeneity (
I
2
<25%), 76 outcomes (18%) had moderate heterogeneity (
I

2

=25%–50%), and 169 outcomes (40%) had high heterogeneity (
I
2
>50%). Reporting of statistical heterogeneity was not significantly associated with year of publication, funding source, disclosure information, or the type of studies pooled. Sensitivity analysis (n=68) was the most common statistical technique employed to evaluate the source of heterogeneity followed by subgroup analyses (n=59) and meta-regression (n=40).

Conclusions:

Despite being an essential component of meta-analyses, heterogeneity was not reported for nearly 30% of outcomes and variably handled in contemporary HF meta-analyses. As meta-analyses increase across HF science, interpreting and handling of heterogeneity should be standardized.
Deliberating the Diagnostic Dilemma of Heart Failure With Preserved Ejection Fraction
Authors: Ho Jennifer E. , Redfield Margaret M. , Lewis Gregory D. , Paulus Walter J. , Lam Carolyn S.P.
Published: November 2020

There is a lack of consensus on how we define heart failure with preserved ejection fraction (HFpEF), with wide variation in diagnostic criteria across society guidelines. This lack of uniformity in disease definition stems in part from an incomplete understanding of disease pathobiology, phenotypic heterogeneity, and natural history. We review current knowledge gaps and existing diagnostic tools and algorithms. We present a simple approach to implement these tools within the constraints of the current knowledge base, addressing separately (1) hospitalized individuals with rest congestion, where diagnosis is more straightforward; and (2) individuals with exercise intolerance, where diagnosis is more complex. Here, a potential role for advanced or provocative testing, including evaluation of hemodynamic responses to exercise is considered. More importantly, we propose focus areas for future studies to develop accurate and feasible diagnostic tools for HFpEF, including animal models that recapitulate human HFpEF, and human studies that both address a fundamental understanding of HFpEF pathobiology, and new diagnostic approaches and tools, as well. In sum, there is an urgent need to more accurately define the syndrome of HFpEF to inform diagnosis, patient selection for clinical trials, and, ultimately, future therapeutic approaches.
Nighttime Blood Pressure Phenotype and Cardiovascular Prognosis
Authors: Kario Kazuomi , Hoshide Satoshi , Mizuno Hiroyuki , Kabutoya Tomoyuki , Nishizawa Masafumi , Yoshida Tetsuro , Abe Hideyasu , Katsuya Tomohiro , Fujita Yumiko , Okazaki Osamu , Yano Yuichiro , Tomitani Naoko , Kanegae Hiroshi ,   On behalf of the JAMP Study Group
Published: November 2020

Background:

Ambulatory and home blood pressure (BP) monitoring parameters are better predictors of cardiovascular events than are office BP monitoring parameters, but there is a lack of robust data and little information on heart failure (HF) risk. The JAMP study (Japan Ambulatory Blood Pressure Monitoring Prospective) used the same ambulatory BP monitoring device, measurement schedule, and diary-based approach to data processing across all study centers and determined the association between both nocturnal hypertension and nighttime BP dipping patterns and the occurrence of cardiovascular events, including HF, in patients with hypertension.

Methods:

This practitioner-based, nationwide, multicenter, prospective, observational study included patients with at least 1 cardiovascular risk factor, mostly hypertension, and free of symptomatic cardiovascular disease at baseline. All patients underwent 24-hour ambulatory BP monitoring at baseline. Patients were followed annually to determine the occurrence of primary end point cardiovascular events (atherosclerotic cardiovascular disease and HF).

Results:

A total of 6,359 patients (68.6±11.7 years of age, 48% men) were included in the final analysis. During a mean±SD follow-up of 4.5±2.4 years, there were 306 cardiovascular events (119 stroke, 99 coronary artery disease, 88 HF). Nighttime systolic BP was significantly associated with the risk of atherosclerotic cardiovascular disease and HF (hazard ratio adjusted for demographic and clinical risk factors per 20-mm Hg increase: 1.21 [95% CI, 1.03–1.41],
P
=0.017; and 1.36 [95% CI, 1.08–1.71],
P
=0.009, respectively). Disrupted circadian BP rhythm (riser pattern, nighttime BP higher than daytime BP) was significantly associated with higher overall cardiovascular disease risk (1.48 [95% CI, 1.05–2.08];
P
=0.024), and especially HF (2.45 [95% CI, 1.34–4.48];
P
=0.004) compared with normal circadian rhythm.

Conclusions:

Nighttime BP levels and a riser pattern were independently associated with the total cardiovascular event rate, in particular for HF. These findings suggest the importance of antihypertensive strategies targeting nighttime systolic BP.

Registration:

URL:
https://www.umin.ac.jp/ctr/
; Unique identifier: UMIN000020377.
It Comes As a Shock
Authors: Klomjit Nattawat , Lerman Amir , Lerman Lilach O.
Published: November 2020

Chronic kidney disease is a global health care burden, yet clinically-proven treatments are limited. Low-intensity shockwave, which utilizes ≈10% of the energy levels used in clinically indicated shockwave lithotripsy, is a promising technique to ameliorate ischemia and regenerate tissues. It has been demonstrated to improve healing in tissues such as bone, muscle, myocardium, and kidney via several mechanisms, particularly through promoting neovascularization. Low-intensity shockwave stimulates mechanoreceptors located primarily in endothelial and proximal tubular cells and subsequently upregulates vascular endothelial growth factors. This, in turn, promotes angiogenesis and ameliorates renal hypoxia, inflammation, and fibrosis, and ultimately preserves renal function. Furthermore, low-intensity shockwave can stimulate release of homing factors to attract endothelial progenitor or stem cells into injured kidneys for tissue repair. These effects may be beneficial in several kidney disease models, including renal artery stenosis, diabetic kidney disease, and various chronic kidney diseases, although most studies reported to date have been performed in animal models. Because of its low energy intensity, the procedure is relatively tolerable and safe, yet, more clinical studies are needed to establish its efficacy beyond currently existing strategies. Therefore, low-intensity shockwave therapy emerges as an alternative therapeutic approach that may offer a promising noninvasive intervention for treating renal diseases.

Registration—

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT02515461; NCT03602807; and NCT03445247.
MicroRNA-133a-Dependent Inhibition of Proximal Tubule Angiotensinogen by Renal TNF (Tumor Necrosis Factor)
Authors: Hao Shoujin , Salzo Joseph , Zhao Hong , Hao Mary , Darzynkiewicz Zbigniew , Ferreri Nicholas R.
Published: November 2020

We showed that intrarenal suppression of TNF (tumor necrosis factor) production under low salt (LS) conditions increases renal cortical AGT (angiotensinogen) mRNA and protein expression. Intrarenal injection of murine recombinant TNF attenuated increases of AGT in mice ingesting LS. Moreover, AGT mRNA and protein expression increased ≈6-fold and 2-fold, respectively, in mice ingesting LS that also received an intrarenal injection of a lentivirus construct that specifically silenced TNF in the kidney (U6-TNF-ex4). Silencing of TNF under normal salt and high salt (HS) conditions also resulted in increased AGT expression. Since renal TNF production decreases in response to LS and increases in response to HS, the data suggest that alterations in TNF production under these conditions modulate the degree of AGT expression. We also tested the hypothesis that TNF inhibits intrarenal AGT expression by a mechanism involving miR-133a. Expression of miR-133a decreased in mice given LS and increased in response to HS for 7 days. Intrarenal silencing of TNF reversed the effects of HS on miR-133a-dependent AGT expression. In contrast, intrarenal TNF administration increased miR-133a expression in the kidney. Collectively, the data suggest that miR-133a is a salt-sensitive microRNA that inhibits AGT in the kidney and is increased by TNF. The HS-induced increase in blood pressure observed following silencing of TNF was markedly reduced upon intrarenal administration of miR-133a suggesting that intrinsic effects of TNF in the kidney to limit the blood pressure response to HS include an increase in miR-133a, which suppresses AGT expression.
Cytosolic PSD-95 interactor alters functional organization of neural circuits and AMPA receptor signaling independent of PSD-95 binding
Authors: Rodriguez Ana R. , Anderson Erin D. , O’Neill Kate M. , McEwan Przemyslaw P. , Vigilante Nicholas F. , Kwon Munjin , Akum Barbara F. , Stawicki Tamara M. , Meaney David F. , Firestein Bonnie L.
Published: November 2020

Cytosolic PSD-95 interactor (cypin) regulates many aspects of neuronal development and function, ranging from dendritogenesis to synaptic protein localization. While it is known that removal of postsynaptic density protein-95 (PSD-95) from the postsynaptic density decreases synaptic N-methyl-D-aspartate (NMDA) receptors and that cypin overexpression protects neurons from NMDA-induced toxicity, little is known about cypin’s role in AMPA receptor clustering and function. Experimental work shows that cypin overexpression decreases PSD-95 levels in synaptosomes and the PSD, decreases PSD-95 clusters/μm2, and increases mEPSC frequency. Analysis of microelectrode array (MEA) data demonstrates that cypin or cypinΔPDZ overexpression increases sensitivity to CNQX (cyanquixaline) and AMPA receptor-mediated decreases in spike waveform properties. Network-level analysis of MEA data reveals that cypinΔPDZ overexpression causes networks to be resilient to CNQX-induced changes in local efficiency. Incorporating these findings into a computational model of a neural circuit demonstrates a role for AMPA receptors in cypin-promoted changes to networks and shows that cypin increases firing rate while changing network functional organization, suggesting cypin overexpression facilitates information relay but modifies how information is encoded among brain regions. Our data show that cypin promotes changes to AMPA receptor signaling independent of PSD-95 binding, shaping neural circuits and output to regions beyond the hippocampus.
Diatom genus Planothidium (Bacillariophyta) from streams and rivers in California, USA: diversity, distribution and autecology

Authors: STANCHEVA ROSALINA , KRISTAN NATHANIEL V. , KRISTAN III WILLIAM B. , SHEATH ROBERT G.
Published: November 2020

The diatom genus Planothidium from streams and rivers in California was studied by applying the most current species designations. Twenty Planothidium taxa were identified in total, including a previously undescribed species, Planothidium californicum. Extensive light and scanning electron microscopic documentation is provided to support consistent further identification of the taxa for the local stream bioassessment. The most common and abundant species, recorded across the entire state, were P. frequentissimum, P. lanceolatum, P. victorii, P. cryptolanceolatum, P. amphibium, and P. minutissimum. Species ranges and species-weighted averages for the main anthropogenic stressors, i.e. chloride, conductivity, dissolved organic carbon, total nitrogen and total phosphorus were determined for the eleven most common Planothdium taxa. Statistically significant differences among species weighted averages were determined by randomization test. Of these eleven species, P. delicatulum, P. robustum, P. engelbrechtii, P. frequentissimum and P. victorii had the highest weighted averages along the chloride and conductivity gradients. P. potapovae, Planothidium sp. 1, P. amphibium, and P. engelbrechtii had narrow nutrient ranges and lowest weighted averages for total nitrogen and phosphorus, making them significantly different from P. delicatulum which had highest total nitrogen average and from P. minutissimum, associated with highest total phosphorus average level. Given that there were differences in associations with environmental variables between recently described species, it is important to use the new taxonomy when using diatoms in bioassessment work.
Revision of the French Polycirridae (Annelida, Terebelliformia), with descriptions of eight new species
Authors: LAVESQUE NICOLAS , HUTCHINGS PAT , DAFFE GUILLEMINE , LONDOÑO-MESA MARIO H.
Published: November 2020

Polycirridae from French waters are revised based on material available in French marine stations and newly collected specimens. This work is the third part of the Spaghetti Project aiming to revise French species of “Spaghetti” terebellid worms. It describes eight new species using both morphological (for all species) and molecular (for some species) tools: Amaeana gremarei n. sp., Polycirrus catalanensis n. sp., P. glasbyi n. sp., P. gujanensis n. sp., P. idex n. sp., P. nogueirai n. sp., P. pennarbedae n. sp. and P. readi n. sp., in addition to a previously described species. An identification key for European species of Polycirridae is also provided.
An annotated checklist of crickets, grasshoppers and their allies (Orthoptera) in Slovakia
Authors: KRIŠTÍN ANTON , JARČUŠKA BENJAMÍN , KAŇUCH PETER
Published: November 2020

The first annotated checklist of ensiferan and caeliferan Orthoptera of Slovakia is presented. Altogether, we found 129 species (59 Ensifera, 70 Caelifera) in the fauna of Slovakia, based on a critical revision of museum collections, all records published since 1826 and our own unpublished data from mapping in 1994–2019 (~2000 sites located in 97.5% of the mapping grid cells). Forty-four species reach the limit of their distributional range within the country, and 31 have their northern limit there. Four species are endemic to Slovakia. In total, 11 species were erroneously reported from the country and are not included in this checklist. The relatively rich species spectrum reflects the diversity of habitats in an area of about 50 thousand km2 and elevations from 94 to 2,655 masl. We found 30 species exclusive for the Pannonian and 18 for the Alpine biogeographical region in the study area. We emphasize changes compared to previous species lists published in 1977 and 1999, when nine species were first recorded after 1999, and eight other species have been missing for more than 50 years. Distributional patterns, accompanied by site maps, are commented for 42 species. Taxonomic, nomenclatural and zoogeographical problems are discussed for a further 23 species. Based on the actual IUCN Red List criteria, we assessed all 129 species. The species were red-listed as follows: regional extinct (Celes variabilis), critically endangered (Isophya beybienkoi, I. costata, Poecilimon fussii, Pachytrachis gracilis, Saga pedo, Paracaloptenus caloptenoides, Acrotylus insubricus, Stenobothrus fischeri), endangered (Poecilimon intermedius, Gampsocleis glabra, Pholidoptera frivaldszkyi, Myrmeleotettix antennatus), vulnerable (nine species), near threatened (18) and data deficient (12). A brief account of the Orthoptera research history in Slovakia is outlined.
A new species of Foenatopus Smith (Hymenoptera: Stephanidae) from Andaman Islands, India
Authors: BINOY C. , KUMAR P. GIRISH , DUBEY ANIL KUMAR
Published: November 2020

The family Stephanidae Leach, 1815, is cosmopolitan, yet a group of infrequently encountered parasitoids with 364 described extant species in 13 genera (Aguiar et al. 2010; Binoy et al. 2020) and nine species in four extinct genera (Aguiar 2004; Aguiar et al. 2013; Engel & Huang 2017) worldwide. The Indian Stephanidae was recently revised (Binoy et al. 2020), recognising a total of 30 species in four extant genera viz., Foenatopus Smith, Megischus Brullé, Parastephanellus Enderlein and Stephanus Jurine.
A new Eocene soldier beetle (Cantharidae) of the genus †Cacomorphocerus Schaufuss, 1892 from Baltic amber
Authors: FANTI FABRIZIO , PANKOWSKI MAXIMILIAN G.
Published: November 2020

Recent studies of extinct soldier beetles have generated an immense amount of new information. Scientists have described various new species of †Cacomorphocerus Schaufuss, 1892, confirming the remarkable diversification and evolution of this genus and the Cantharidae family during the Eocene. In the present work, we describe a new species from Baltic amber. Cacomorphocerus marki sp. nov., is the first species of Cacomorphocerus discovered with filiform 11-segmented antennae. Based on inclusions in Baltic and Rovno amber, it now appears certain that the genus Cacomorphocerus and the tribe Cacomorphocerini Fanti & Kupryjanowicz, 2018 evolved and subsequently went extinct in Europe during the Eocene. Known for more than 100 years from a single species, the genus is now known to be far more morphologically diversified thanks to these recent discoveries.
On the putatively incorrect identification and “redescription” of Paratropis elicioi Dupérré 2015 (Paratropididae, Araneae) with the description of two new sympatric species from Ecuador
Authors: DUPÉRRÉ NADINE , TAPIA ELICIO
Published: November 2020

Paratropis elicioi was described in 2015 from specimens collected in Ecuador. Both sexes were described, scientific illustrations of all relevant morphological characters were provided. Perafán et al. (2019) claimed to redescribe Paratropis elicioi from specimens collected in Colombia, without examining the holotype or paratype. Evidence that the description published by Perafán et al. 2019 is not Paratropis elicioi is presented. Two new sympatric species are described: P. otonga sp. n. and P. pristirana sp. n.