bluuebunny/crossref_metadata_2025_split huggingface dataset:
Funding Community Health Activities: An Experiment Comparing Health Foundation's Priorities to Those of Public Health Agencies, Hospitals, and Nonprofit Organizations
Authors: Rozier Michael D. , Banaszak-Holl Jane , Kiessling Karalyn A. , Singh Simone R. 
Published: December 2021

Context:
Health foundations provide significant financial resources for community health. Foundation priorities, therefore, can play a key role in setting community agenda, but little is known about the criteria foundations use to prioritize projects.

Objective:
To understand the priorities that guide decision makers in health foundations and compare those priorities with what is known about nonprofit hospitals, public health, and community-based nonprofits.

Design:
An online survey with a discrete choice experiment and open-ended questions, asking respondents to choose between different types of community health projects based on project characteristics.

Setting:
Survey respondents were employed by health foundations located in the United States.

Participants:
Respondents were leaders at health foundations (n = 173), the majority of which (56.2%) worked at foundations with assets greater than $50 million. These respondents were compared with an earlier survey (n = 561) from nonprofit hospitals, public health, and community-based nonprofits.

Main Outcome Measures:
A conditional logit model was used to estimate how various project characteristics led to greater or lesser support of a given health project. Open-ended questions aided interpretation. A two sample t test was used to compare groups.

Results:
Foundation decision makers placed the greatest value on programs with coalitions of community partners, programs with a growing or existing base of evidence for effectiveness, and programs that focus on social determinants of health. These priorities are similar to those of community nonprofits, public health departments, and health systems. However, foundation leaders are more willing to fund interventions with longer time horizons and interventions that are not yet fully evidence-based. Foundations are also less interested in clinical care and more interested in advocacy programs.

Conclusion:
Cooperation in funding and implementation is essential to community health improvement, and major organizations could benefit from everyone clearly articulating their priorities. There are good reasons to intentionally foster both similarities and differences in priorities across organizations.
Generation and Use of Evidence by Local Health Departments: The Role of Leader Attributes
Authors: Hearld Larry R. , Kelly Reena Joseph , Tafili Aurora 
Published: December 2021

Objective:
The purpose of this study was to examine whether certain types of leaders were associated with the degree to which local health departments (LHDs) generate and use evidence to inform their service offering.

Design:
Pooled, cross-sectional analysis using 4 waves (2010, 2013, 2016, and 2019) of the National Profiles of Local Health Departments sponsored by the National Association of County and City Health Officials (NACCHO). Univariate analysis was used to assess the extent to which LHDs were generating and using evidence to improve the health of their local communities and whether this changed over time. Multinomial logistic regression models were used to examine the relationships between LHD leader attributes and the extent to which LHDs were generating and using evidence.

Participants:
Between 1496 and 2087 (varied by survey round) LHDs from throughout the United States.

Main Outcome Measure(s):
Two outcome variables pertaining to the generation of evidence: (1) how recently an LHD completed a community health assessment and (2) how recently an LHD completed a community health improvement plan. A third outcome variable reflected how extensively an LHD used the Community Guide, a compendium of evidence-based findings.

Results:
In 2010, 25.1% and 41.4% of all LHDs had not completed a community health assessment or a community health improvement plan, respectively; by 2019, those figures declined significantly to 14.6% and 24.7%. Similarly, in 2010, 61.7% of all LHDs were not using the Community Guide; by 2019, that percentage declined significantly to 42.5%. Multivariable analysis revealed that leader experience was a more robust correlate of evidence generation and use by LHDs than leader education.

Conclusions:
While LHDs' generation and use of evidence have grown over the past decade, there is room for improvement. Local health department leader attributes—education and experience—highlight targeted opportunities to fill gaps in the use of evidence-based public health practices.
Conjunctival epithelial cells resist productive SARS-CoV-2 infection
Authors: Jackson Robert M , Hatton Catherine F , Spegarova Jarmila Stremenova , Georgiou Maria , Collin Joseph , Stephenson Emily , Verdon Bernard , Haq Iram J , Hussain Rafiqul , Coxhead Jonathan M , Mudhar Hardeep-Singh , Wagner Bart , Hasoon Megan , Davey Tracey , Rooney Paul , Anjam Khan C.M. , Ward Chris , Brodlie Malcolm , Haniffa Muzlifah , Hambleton Sophie , Armstrong Lyle , Figueiredo Francisco , Queen Rachel , Duncan Christopher J A , Lako Majlinda 
Published: December 2021

AbstractAlthough tropism of SARS-CoV-2 for respiratory tract epithelial cells is well established, an open question is whether the conjunctival epithelium is also a target for SARS-CoV-2. Conjunctival epithelial cells, which express viral entry receptors ACE2 and TMPRSS2, constitute the largest exposed epithelium of the ocular surface tissue, and may represent a relevant viral entry route. To address this question, we generated an organotypic air-liquid-interface model of conjunctival epithelium, composed of progenitor, basal and superficial epithelial cells and fibroblasts, which could be maintained successfully up to day 75 of differentiation. Using single-cell RNA Seq, with complementary imaging and virological assays, we observed that while all conjunctival cell types were permissive to SARS-CoV-2 genome expression, a productive infection did not ensue. The early innate immune response to SARS-CoV-2 infection in conjunctival cells was characterised by a robust autocrine and paracrine NF-Kβ activity, without activation of antiviral interferon signalling. Collectively, these data enrich our understanding of SARS-CoV-2 infection at the human ocular surface, with potential implications for the design of preventive strategies and conjunctival transplants.
dynamAedes: a unified modelling framework for invasiveAedesmosquitoes
Authors: Da Re Daniele , Van Bortel Wim , Reuss Friederike , Müller Ruth , Boyer Sebastien , Montarsi Fabrizio , Ciocchetta Silvia , Arnoldi Daniele , Marini Giovanni , Rizzoli Annapaola , L’Ambert Gregory , Lacour Guillaume , Koenraadt Constantianus J.M. , Vanwambeke Sophie O. , Marcantonio Matteo 
Published: December 2021

AbstractMosquito species belonging to the genusAedeshave attracted the interest of scientists and public health officers for their invasive species traits and efficient capacity of transmitting viruses affecting humans. Some of these species were brought outside their native range by human activities such as trade and tourism, and colonised new regions thanks to a unique combination of eco-physiological traits.Considering mosquito physiological and behavioural traits to understand and predict the spatial and temporal population dynamics is thus a crucial step to develop strategies to mitigate the local densities of invasiveAedespopulations.Here, we synthesised the life cycle of four invasiveAedesspecies (Ae. aegypti,Ae. albopictus,Ae. japonicusandAe. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R packagedynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability, by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data.Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on species biology which could be applied to the management of invasiveAedespopulations as well as for more theoretical ecological inquiries.
Draft Genome of Cochliopodium minus (Amoebozoa): Insights into Its Complex Sexual Behavior, Across Domain Gene Acquisitions and Metazoan Type Signaling
Authors: Tekle Yonas I. , Wang Fang , Tran Hanh , Hayes T. Danielle , Ryan Joseph F. 
Published: December 2021

AbstractTo date, genomic analyses in amoebozoans have been mostly limited to model organisms or medically important lineages. Consequently, the vast diversity of Amoebozoa genomes remain unexplored. A draft genome of Cochliopodium minus, an amoeba characterized by extensive cellular and nuclear fusions, is presented. C. minus has been a subject of recent investigation for its unusual sexual behavior. Cochliopodium’s sexual activity occurs during vegetative stage making it an ideal model for studying sexual development, which is sorely lacking in the group. Here we generate a C. minus draft genome assembly. From this genome, we detect a substantial number of lateral gene transfer (LGT) instances from bacteria (15%), archaea (0.9%) and viruses (0.7%) the majority of which are detected in our transcriptome data. We identify the complete meiosis toolkit genes in the C. minus genome, as well as the absence of several key genes involved in plasmogamy and karyogamy. Comparative genomics of amoebozoans reveals variation in sexual mechanism exist in the group. Similar to complex eukaryotes, C. minus (some amoebae) possesses Tyrosine kinases and duplicate copies of SPO11. We report a first example of alternative splicing in a key meiosis gene and draw important insights on molecular mechanism of sex in C. minus using genomic and transcriptomic data.
Understanding Harmonic Structures Through Instantaneous Frequency
Authors: Fabus Marco S. , Woolrich Mark W. , Warnaby Catherine W. , Quinn Andrew J. 
Published: December 2021

ABSTRACTThe analysis of harmonics and non-sinusoidal waveform shape in neurophysiological data is growing in importance. However, a precise definition of what constitutes a harmonic is lacking. In this paper, we propose a rigorous definition of when to consider signals to be in a harmonic relationship based on an integer frequency ratio, constant phase, and a well-defined joint instantaneous frequency. We show this definition is linked to extrema counting and Empirical Mode Decomposition (EMD). We explore the mathematics of our definition and link it to results from analytic number theory. This naturally leads to us to define two classes of harmonic structures, termed strong and weak, with different extrema behaviour. We validate our framework using both simulations and real data. Specifically, we look at the harmonics structure in the FitzHugh-Nagumo model and the non-sinusoidal hippocampal theta oscillation in rat local field potential data. We further discuss how our definition helps to address mode splitting in EMD. A clear understanding of when harmonics are present in signals will enable a deeper understanding of the functional and clinical roles of non-sinusoidal neural oscillations.
Quantifying defensive behavior and threat response through integrated headstage accelerometry
Authors: Younk Rebecca , Widge Alik S 
Published: December 2021

AbstractBackgroundDefensive and threat-related behaviors are common targets of investigation, because they model aspects of human mental illness. These behaviors are typically quantified by video recording and post hoc analysis. Those quantifications can be laborious and/or computationally intensive.Depending on the analysis method, the resulting measurements can be noisy or inaccurate. Other defensive behaviors, such as suppression of operant reward seeking, require extensive animal pre-training.New MethodWe demonstrate a method for quantifying defensive behavior (immobility or freezing) by 3-axis accelerometry integrated with an electrophysiology headstage. We tested multiple pre-processing and smoothing methods, and correlated them against two common methods for quantification: freezing as derived from standard video analysis, and suppression of operantly shaped bar pressing. We assessed these three methods’ ability to track defensive behavior during a standard threat conditioning and extinction paradigm.ResultsThe best approach to tracking defensive behavior from accelerometry was Gaussian filter smoothing of the first derivative (change score or jerk). Behavior scores from this method reproduced canonical conditioning and extinction curves at the group level. At the individual level, timepoint-to-timepoint correlations between accelerometry, video, and bar press metrics were statistically significant but modest (largest r=0.53, between accelerometry and bar press).Comparison with existing methodsThe integration with standard electrophysiology systems and relatively lightweight signal processing may make accelerometry particularly well suited to detect behavior in resource-constrained or real-time applications. At the same time, there were modest cross-correlations between all three methods for quantifying defensive behavior.ConclusionsAccelerometry analysis allows researchers already using electrophysiology to assess defensive behaviors without the need for additional behavioral measures or video. The similarities in behavioral tracking and modest correlations between each metric suggest that each measures a distinct aspect of defensive behavior. Accelerometry is a viable alternative to current defensive measurements, and its non-overlap with other metrics may allow a more sophisticated dissection of threat responses in future experiments.HighlightsA novel method to assess defensive behavior and immobility based on headstage accelerometryCompatible with readily available, open-source neurophysiology systemsProvides behavioral insights without the need for video analysis software and with relatively minimal processing, suitable for rapid closed-loop experiments
Anti-SARS-CoV-2 human antibodies retaining neutralizing activity against SARS-CoV-2 B.1.1.529 (omicron)
Authors: Imbrechts Maya , Kerstens Winnie , Rasulova Madina , Vercruysse Thomas , Maes Wim , Ampofo Louanne , Ven Karen , Lammertyn Jeroen , Vanhoorelbeke Karen , Callewaert Nico , Neyts Johan , Dallmeier Kai , Declerck Paul , Thibaut Hendrik Jan , Geukens Nick 
Published: December 2021

AbstractSARS-CoV-2 B.1.1.529, designated omicron, was recently identified as a new variant of concern by WHO and is rapidly replacing SARS-CoV-2 delta as the most dominant variant in many countries. Unfortunately, because of the high number of mutations present in the spike of SARS-CoV-2 omicron, most monoclonal antibodies (mAbs) currently approved for treatment of COVID-19 lose their in vitro neutralizing activity against this variant. We recently described a panel of human anti-SARS-CoV-2 mAbs that potently neutralize SARS-CoV-2 Wuhan, D614G and variants alpha, beta, gamma and delta. In this work, we evaluated our mAb panel for potential in vitro activity against SARS-CoV-2 delta and omicron. Three mAbs from our panel retain neutralizing activity against both delta and omicron, with mAb 3B8 still resulting in complete neutralization at a concentration as low as 0.02 μg/ml for both variants. Overall, our data indicate that mAb 3B8 may have the potential to become a game-changer in the fight against the continuously evolving SARS-CoV-2.
Coagulation Factor IIIa (f3a) Knockdown in Zebrafish Leads to Defective Angiogenesis and Mild Bleeding Phenotype
Authors: Subramaniam Saravanan , Liu Jiandong , Fletcher Craig , Ramchandran Ramani , Weiler Hartmut 
Published: December 2021

AbstractAimTissue factor (TF), an initiator of the extrinsic coagulation pathway, is crucial for embryogenesis, as mice lacking TF are embryonically lethal (E10.5). This lethality may be attributed to defects in vascular development and circulatory failure, suggesting additional roles for TF in embryonic development beyond coagulation. In this study, we characterized the role of one of the TF paralogs (f3a) using a zebrafish model.MethodsTo understand the TF evolution across different species, we performed molecular phylogenetic and sequence homology analysis. The expression of f3a during embryonic developmental stages was determined by RT-PCR. Endothelial-specific transgenic lines of zebrafish (flk1:egfp-NLS/kdrl:mCherry-CAAX) was used to image the vascular development. The role of f3a during embryonic development was investigated by mRNA knockdown using Morpholinos (MO), an antisense-based oligonucleotide strategy. The f3a morphants were examined at 52 hpf for defects in morphological appearance, bleeding, and vascular patterning.ResultsSpatiotemporal expression of f3a by qPCR revealed expression in all developmental stages, suggesting that f3a transcripts are both maternally and zygotically expressed. High expression of f3a from 28 hpf to 36 hpf confirmed the role of in the development of the yolk sac, circulation, and fins. f3a MO-injected embryos showed morphological abnormalities, including shorter body lengths and crooked tails. O-dianisidine staining showed f3a MO-injected embryos exhibited bleeding in the trunk (5.44%) and head (9.52%) regions. Using endothelial-specific transgenic lines of zebrafish (flk1:egfp-NLS/kdrl:mCherry-CAAX), imaging of caudal vein plexus, which forms immediately following the onset of circulation and sprouting, showed a 3-fold decrease in f3a morphants versus controls at 48 hpf, suggesting a potential role for f3a in flow-induced angiogenesis.Conclusionf3a is essential for angiogenesis, in addition to its involvement in hemostasis.Key Pointsf3a knockdown by antisense morpholino oligonucleotide (MO)-approach shows bleeding phenotype.f3a is essential for angiogenesis, in addition to its involvement in hemostasis.
A vascularized 3D model of the human pancreatic islet for ex vivo study of immune cell-islet interaction
Authors: Bender R. Hugh F. , O’Donnell Benjamen T. , Shergill Bhupinder , Pham Brittany Q. , Juat Damie J. , Hatch Michaela S. , Shirure Venktesh S. , Wortham Matthew , Nguyen-Ngoc Kim-Vy , Jun Yesl , Gaetani Roberto , Christman Karen L. , Teyton Luc , George Steven C. , Sander Maike , Hughes Christopher C.W. 
Published: December 2021

ABSTRACTInsulin is an essential regulator of blood glucose homeostasis that is produced exclusively by β cells within the pancreatic islets of healthy individuals. In those affected by diabetes, immune inflammation, damage, and destruction of islet β cells leads to insulin deficiency and hyperglycemia. Current efforts to understand the mechanisms underlying β cell damage in diabetes rely on in vitro-cultured cadaveric islets. However, isolation of these islets involves removal of crucial matrix and vasculature that supports islets in the intact pancreas. Unsurprisingly, these islets demonstrate reduced functionality over time in standard culture conditions, thereby limiting their value for understanding native islet biology. Leveraging a novel, vascularized micro-organ (VMO) approach, we have recapitulated elements of the native pancreas by incorporating isolated human islets within a three-dimensional matrix nourished by living, perfusable blood vessels. Importantly, these islets show long-term viability and maintain robust glucose-stimulated insulin responses. Furthermore, vessel-mediated delivery of immune cells to these tissues provides a model to assess islet-immune cell interactions and subsequent islet killing — key steps in type 1 diabetes pathogenesis. Together, these results establish the islet-VMO as a novel, ex vivo platform for studying human islet biology in both health and disease.
Flexible and efficient simulation-based inference for models of decision-making
Authors: Boelts Jan , Lueckmann Jan-Matthis , Gao Richard , Macke Jakob H. 
Published: December 2021

AbstractInferring parameters of computational models that capture experimental data is a central task in cognitive neuroscience. Bayesian statistical inference methods usually require the ability to evaluate the likelihood of the model—however, for many models of interest in cognitive neuroscience, the associated likelihoods cannot be computed effciently. Simulation-based inference (SBI) offers a solution to this problem by only requiring access to simulations produced by the model. Here, we provide an effcient SBI method for models of decision-making. Our approach, Mixed Neural Likelihood Estimation (MNLE), trains neural density estimators on model simulations to emulate the simulator, and is designed to capture both the continuous (e.g., reaction times) and discrete (choices) data of decision-making models. The likelihoods of the emulator can then be used to perform Bayesian parameter inference on experimental data using standard approximate inference methods like Markov Chain Monte Carlo sampling. We demonstrate MNLE on two variants of the drift-diffusion model (DDM) and compare its performance to a recently proposed method for SBI on DDMs, called Likelihood Approximation Networks (LANs, Fengler et al. 2021). We show that MNLE is substantially more effcient than LANs: it achieves similar likelihood accuracy with six orders of magnitude fewer training simulations, and is substantially more accurate than LANs when both are trained with the same budget. This enables researchers to train MNLE on custom-tailored models of decision-making, leading to fast iteration of model design for scientific discovery.
Stain-free nucleus identification in holographic learning flow cyto-tomography
Authors: Pirone Daniele , Lim Joowon , Merola Francesco , Miccio Lisa , Mugnano Martina , Bianco Vittorio , Cimmino Flora , Visconte Feliciano , Montella Annalaura , Capasso Mario , Iolascon Achille , Memmolo Pasquale , Psaltis Demetri , Ferraro Pietro 
Published: December 2021

AbstractQuantitative Phase Imaging (QPI) has gained popularity because it can avoid the staining step, which in some cases is difficult or impossible. However, QPI does not provide the well-known specificity to various parts of the cell (e.g., organelles, membrane). Here we show a novel computational segmentation method based on statistical inference that bridges the gap between the specificity of Fluorescence Microscopy (FM) and the label-free property of QPI techniques to identify the cell nucleus. We demonstrate application to stain-free cells reconstructed through the holographic learning and in flow cyto-tomography modality. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus-like regions can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal FM data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting the three-dimensional (3D) intracellular specificity directly from the phase-contrast data in a typical flow cytometry configuration.