bluuebunny/crossref_metadata_2025 huggingface dataset:
The evolution of a counter-defense mechanism in a virus constrains its host range
Authors: Srikant Sriram , Guegler Chantal K. , Laub Michael T.
Published: April 2022

Bacteria use diverse immunity mechanisms to defend themselves against their viral predators, bacteriophages. In turn, phages can acquire counter-defense systems, but it remains unclear how such mechanisms arise and what factors constrain viral evolution. Here, we experimentally evolved T4 phage to overcome a phage-defensive toxin-antitoxin system, toxIN, in E. coli. Through recombination, T4 rapidly acquires segmental amplifications of a previously uncharacterized gene, now named tifA, encoding an inhibitor of the toxin, ToxN. These amplifications subsequently drive large deletions elsewhere in T4’s genome to maintain a genome size compatible with capsid packaging. The deleted regions include accessory genes that help T4 overcome defense systems in alternative hosts. Thus, our results reveal a trade-off in viral evolution; the emergence of one counter-defense mechanism can lead to loss of other such mechanisms, thereby constraining host range. We propose that the accessory genomes of viruses reflect the integrated evolutionary history of the hosts they infected.

Highlights

Experimentally evolved T4 to overcome E. coli toxIN, a phage-defensive TA system

Discovered TifA, a phage-encoded protein inhibitor of ToxN

Amplification of the tifA locus drives large deletions elsewhere in the T4 genome

Deleted genes in evolved T4 clones include those necessary to infect alternative hosts
IL-33 priming and antigenic stimulation synergistically promote the transcription of proinflammatory cytokine and chemokine genes in human skin mast cells
Authors: Gao Junfeng , Li Yapeng , Guan Xiaoyu , Mohammed Zahraa , Gomez Gregorio , Hui Yvonne , Zhao Dianzheng , Oskeritzian Carole A. , Huang Hua
Published: April 2022

Background

Antigenic stimulation through cross-linking the IgE receptor and epithelial cell-derived cytokine IL-33 are potent stimuli of mast cell (MC) activation. Moreover, IL-33 primes a variety of cell types, including MCs to respond more vigorously to external stimuli. However, target genes induced by the combined IL-33 priming and antigenic stimulation have not been investigated in human skin mast cells (HSMCs) in a genome-wide manner. Furthermore, epigenetic changes induced by the combined IL-33 priming and antigenic stimulation have not been evaluated.

Results

We found that IL-33 priming of HSMCs enhanced their capacity to promote transcriptional synergy of theIL1BandCXCL8genes by 16- and 3-fold, respectively, in response to combined IL-33 and antigen stimulation compared to without IL-33 priming. We identified the target genes in IL-33-primed HSMCs in response to the combined IL-33 and antigenic stimulation using RNA sequencing (RNA-seq). We found that the majority of genes synergistically upregulated in the IL-33-primed HSMCs in response to the combined IL-33 and antigenic stimulation were predominantly proinflammatory cytokine and chemokine genes. Moreover, the combined IL-33 priming and antigenic stimulation increase chromatin accessibility in the synergy target genes but not synergistically. Transcription factor binding motif analysis revealed more binding sites for NF-κB, AP-1, GABPA, and RAP1 in the induced or increased chromatin accessible regions of the synergy target genes.

Conclusions

Our study demonstrates that IL-33 priming greatly potentiates MCs’ ability to transcribe proinflammatory cytokine and chemokine genes in response to antigenic stimulation, shining light on how epithelial cell-derived cytokine IL-33 can cause exacerbation of skin MC-mediated allergic inflammation.
Infection with Listeria monocytogenes alters the placental transcriptome and eicosanome
Authors: Conner Kayla N. , Holman Derek , Lydic Todd , Hardy Jonathan W.
Published: April 2022

Introduction

Placental infection and inflammation are risk factors for adverse pregnancy outcomes, including preterm labor. However, the mechanisms underlying these outcomes are poorly understood.

Methods

To study this response, we have employed a pregnant mouse model of placental infection caused by the bacterial pathogen Listeria monocyogenes, which infects the human placenta. Through in vivo bioluminescence imaging, we confirm the presence of placental infection and quantify relative infection levels. Infected and control placentas were collected on embryonic day 18 for RNA sequencing to evaluate gene expression signatures associated with infection by Listeria.

Results

We identified an enrichment of genes associated with eicosanoid biosynthesis, suggesting an increase in eicosanoid production in infected tissues. Because of the known importance of eicosanoids in inflammation and timing of labor, we quantified eicosanoid levels in infected and uninfected placentas using semi-targeted mass spectrometry. We found a significant increase in the concentrations of several key eicosanoids: leukotriene B4, lipoxin A4, prostaglandin A2, prostaglandin D2, and eicosatrienoic acid.

Discussion

Our study provides a likely explanation for dysregulation of the timing of labor following placental infection. Further, our results suggest potential biomarkers of placental pathology and targets for clinical intervention.
Vaeda computationally annotates doublets in single-cell RNA sequencing data
Authors: Schriever Hannah , Kostka Dennis
Published: April 2022

Motivation

Single-cell RNA sequencing (scRNA-seq) continues to expand our knowledge by facilitating the study of transcriptional heterogeneity at the level of single cells. Despite this technology’s utility and success in biomedical research, technical artifacts are present in scRNA-seq data. Doublets/multiplets are a type of artifact that occurs when two or more cells are tagged by the same barcode, and therefore they appear as a single cell. Because this introduces non-existent transcriptional profiles, doublets can bias and mislead downstream analysis. To address this limitation computational methods to annotate and remove doublets form scRNA-seq datasets are needed.

Results

We introduce vaeda, a new approach for computational annotation of doublets in scRNA-seq data. Vaeda integrates a variational auto-encoder and Positive-Unlabeled learning to produce doublet scores and binary doublet calls. We apply vaeda, along with seven existing doublet annotation methods, to sixteen benchmark datasets and find that vaeda performs competitively in terms of doublet scores and doublet calls. Notably, vaeda outperforms other python-based methods for doublet annotation. All together, vaeda is a robust and competitive method for scRNA-seq doublet annotation and may be of particular interest in the context of python-based workflows.

Availability

Vaeda is available at https://github.com/kostkalab/vaeda

Contact

kostka@pitt.edukostka@pitt.edu
Violation of the fluctuation-response relation from a linear model of hair bundle oscillations
Authors: Berger Florian , Hudspeth A. J.
Published: April 2022

Spontaneous hair-bundle oscillations have been proposed to underlie the ear’s active process, which amplifies acoustic signals, sharpens frequency selectivity, and broadens the dynamic range. Although this activity is critical for proper hearing, we know very little about its energetics and its nonequilibrium properties. Systems obey fluctuation-response relations, whose violation signals nonequilibrium conditions. Here we demonstrate the violation of the fluctuation-response relation of a linear model for hair bundle oscillations. Combining analytical results with experimental data, we estimate that an energy of at least 146kBTis dissipated per oscillatory cycle, implying a power output of about 5aW. Our model indicates that this dissipation attains a minimum at a certain characteristic frequency. For high frequencies, we derive a linear scaling behavior of this dissipated energy with the characteristic frequency.
The one-step preparation and corrosion resistance of a Ca–Mn–Zn ternary phosphate conversion coating on magnesium alloy AZ91D
Authors: Yang Jun , Zhang Pei , Su Lihuizi , Yan Fuan , Yong Zhou
Published: April 2022

Purpose

The aim of this work was to propose a method to prepare composite phosphate conversion coating (CPCC), including ternary phosphate conversion coating (TPCC) and binary phosphate conversion coatings (BPCC), with one-step chemical conversion and to reveal and compare the corrosion resistance between TPCC and BPCC.

Design/methodology/approach

In this work, a calcium–manganese–zinc (Ca–Mn–Zn) TPCC was prepared on the surface of magnesium alloy (MA) AZ91D with one-step chemical conversion method; for Ca-Mn-Zn@TPCC, its microstructure was characterized with scanning electron microscope observation and scanning tunneling microscope detection, and its composition was characterized with energy dispersion spectroscopy and X-ray photoelectron spectroscopy analyses. Particularly, the corrosion resistance of Ca-Mn-Zn@TPCC and its comparison with Ca–Mn, Ca–Zn and Mn–Zn BPCCs were clarified with electrochemical and immersion measurements.

Findings

Ca-Mn-Zn@TPCC, which was composed of Ca, Mn, Zn, P and O, exhibited a mud-shaped with cracks microstructure, and the average crack width, terrain fluctuation and coating thickness were 0.61 µm, 23.78 nm and 2.47 µm, respectively. Ca-Mn-Zn@TPCC provided good corrosion resistance to MA AZ91D; in NaCl solution, the total degradation of Ca-Mn-Zn@TPCC consumed eight days; corrosion products with poor adhesion peeled out from Ca-Mn-Zn@TPCC-coated MA AZ91D spontaneously. Besides, the corrosion resistance of Ca-Mn-Zn@TPCC was better than that of Ca-Mn@BPCC, Ca-Zn@BPCC or Mn-Zn@BPCC.

Originality/value

The successful preparation of Ca-Mn-Zn@TPCC on MA AZ91D surface confirmed the proposed method to prepare CPCC with one-step chemical conversion was feasible; at the same time, it was further confirmed that for phosphate conversion coating, ternary coating had better corrosion resistance than binary coating did.
A comprehensive performance optimization method for the honeycomb buffer of a legged-type lander
Authors: Wang Hui , He Tianyu , Wang Chunjie
Published: April 2022

Purpose

In the field of planetary exploration, the legged-type lander is a common landing buffer device. There are two important performance metrics for legged-type landers: the energy absorption capacity and landing stability. In this paper, a novel method is proposed to optimize the honeycomb buffer of a legged-type lander. Optimization design variables are the dimension parameters of honeycomb and the objective functions are the evaluation parameters of the above two performance metrics.

Design/methodology/approach

A multi-body dynamic model of a lander and a finite-element model of the metal honeycomb are established. Based on the simulation results of the finite-element model and the quartic polynomial, the surrogate models are established to evaluate the energy absorption capacity of honeycomb. Considering both the multi-body dynamic model and the surrogate models, the study designed the optimization flow of dimension parameters of honeycomb. Besides, the non-dominated sorting genetic algorithm II is used for iterative calculation.

Findings

Images of surrogate models show the monotonous functional relationship between the honeycomb’s energy absorption characteristics and its dimension parameters. Optimization results show an apparent contradiction among the objective functions. Besides, according to the simulation results, this method can significantly improve the comprehensive performance of the lander.

Originality/value

The novel method can effectively reduce the cost of honeycomb compression tests and improve the lander’s design. Therefore, it can be used for optimizing buffers of other types of legged-type landers.
Explaining the alienation of megaproject environmental responsibility behavior: a fuzzy set qualitative comparative analysis study in China
Authors: Xie Linlin , Xu Ting , Ju Tianhao , Xia Bo
Published: April 2022

Purpose

The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the fuzzy set qualitative comparative analysis (fsQCA) method, this study explored the combined effect of antecedent factors on alienation of MER behavior.

Design/methodology/approach

Based on the fraud triangle theory and literature review, eight influencing factors associated with the alienation of MER behavior were first identified. Subsequently, the fuzzy-set qualitative comparative analysis was used in this study to reveal configurations influencing alienation of MER behavior.

Findings

The study found nine configurations of MER behavioral alienation antecedent factors, integrated into three types of driving modes, i.e. “economic pressure + learning effect,” “institutional defect + moral rejection,” and “information asymmetry + economic pressure + expectation pressure.”

Originality/value

By analyzing the configuration effects of various induced conditions, this study puts forward a comprehensive analysis framework to solve the alienation of MER behavior in the megaprojects and a practical strategy to control alienation of MER behavior.
Coping strategies and social support are associated with post-traumatic stress disorder symptoms in Saudi paramedics
Authors: Alshahrani Khalid , Johnson Judith , O’Connor Daryl B.
Published: April 2022

Purpose

Three main objectives of this study were as follows: (1) To estimate the prevalence rate of post-traumatic stress disordered (PTSD) symptoms among Saudi paramedics, (2) To investigate which types of coping strategies were associated with PTSD symptoms among Saudi paramedics, (3) To explore which sources of social support were associated with PTSD symptoms among Saudi paramedics.

Design/methodology/approach

Data were collected from 217 paramedics working in the Saudi Red Crescent Authority from September to December 2019. Participants completed questionnaires measuring PTSD symptoms (the Screen of Post-Traumatic Stress Disorders; SPTSD), passive and active coping strategies (Brief COPE Scale; BC), and three forms of social support: support from friends, family and organizational support. Associations between coping strategies, social support and PTSD symptoms were investigated using correlational analyses, hierarchical linear regression and binary logistic regression.

Findings

46% of participants experienced one or more PTSD symptom, 28.6% scored above the cut-off for partial PTSD and 17.5% scored above the cut-off for full PTSD. PTSD symptoms were significantly positively correlated with passive coping and negatively associated with both family and friends support. Passive coping was positively associated with a greater risk of meeting criteria for PTSD.

Originality/value

The current findings suggest that interventions to help reduce PTSD in Saudi paramedics should include strategies to reduce passive coping. Future research is urgently required to help understand the psychological, social and work-related factors that contribute to these high levels of PTSD.
Historic public paths in rural areas: engine of development and origin of new conflicts
Authors: Moscoso-Sánchez David , Nasarre-Sarmiento José María , Trujillo-Carmona Manuel , González-Fernández Manuel T. , Luque-Gil Ana , Sánchez-Sanz Víctor , Vidal-González Pablo
Published: April 2022

Purpose

In this article, the authors analyse a complex social process affecting historic public paths in rural areas in southern Spain. Despite the fact that urban populations are demanding the enhancement of this type of natural heritage for tourism, sports and recreational use, some parts of the network have been abandoned or usurped.

Design/methodology/approach

The study is multidisciplinary, comprising three interlinked studies. The cartographic study comprises an inventory of public paths in rural areas based on administrative sources. The legal study analyses local, regional and national regulations governing agricultural, environmental, heritage, sports and tourism uses of the infrastructure. The sociological study analyses social discourses on the uses of public paths, and identifies conflicts between farmers, landowners, environmentalists, sportspeople and tourists.

Findings

The preliminary results identified an important public paths network in Andalusia, approximately 160,000 km. The legal study found that there are laws regulating use, although local authorities do not monitor compliance or provide solutions to enhance management. The sociological study determined the attribution of environmental, cultural and economic value to public paths, but also the existence of conflicts between rural and urban populations.

Research limitations/implications

Given that this is ongoing research, only state of the art and some preliminary albeit sufficiently consistent results are presented.

Practical implications

The results could help to guide public policy and governance of public paths.

Social implications

Public paths promote rural development and a green/sustainable economy.

Originality/value

The research results and conclusions are original.
A bibliometric and visual analysis of hospitality and tourism marketing research from 2000–2020
Authors: Liu Juan , Wei Wei , Zhong Meiying , Cui Yaqi , Yang Shuang , Li Haiyan
Published: April 2022

Purpose

This study aimed to bibliometrically and visually analyze and review hospitality and tourism marketing studies published from 2000–2020.

Design/methodology/approach

A total of 3,942 articles collected from the databases of Social Science Citation Index (SSCI) and Science Citation Index Expanded (SCI-E) in the Web of Science (WoS) along with their references were used for analyses. The bibliometric software HistCiteTM and literature measurement visualization tools, VOSviewer and CiteSpace, were employed to analyze the selected articles.

Findings

The results of the study demonstrated top influential scholars and institutions, intellectual structure and emerging trends of the study topics, and future research opportunities in the field of hospitality and tourism marketing.

Research limitations/implications

First, academic influence of a scholar was evaluated by citations of his/her publications, which did not take the order of authorship into consideration. Second, this study was restricted to the English language journals. Third, other types of published documents related to the studied field such as review papers were not considered by this research.

Originality/value

In comparison to traditional qualitative analysis such as content analysis, bibliometric analysis is a more objective approach to vividly demonstrate trends and performance of a research field, offers unique insights for its advancement with wider inclusiveness of a larger amount of data.
Peer workers disseminating lived experience research: a perfect match?
Authors: Honey Anne , Boydell Katherine , Clissold Nathan , Coniglio Francesca , Do Trang Thuy , Dunn Leonie , Fuller Candice Jade , Gill Katherine , Glover Helen , Hines Monique , Scanlan Justin Newton , Tooth Barbara , Wagner Darren
Published: April 2022

Purpose

This paper aims to explore the use of lived experience research in peer work.

Design/methodology/approach

A suite of user-friendly and engaging lived experience research resources was introduced to consumers by peer workers. In-depth interviews were conducted with 33 consumer participants and five peer workers about their experiences. The data were analysed using qualitative content analysis.

Findings

The role of the peer workers appeared critical in ensuring that participants, despite their varied needs, preferences and backgrounds, derived optimum benefit from each resource. Features in resource delivery that promoted a positive experience included presenting the resources in the context of an existing relationship, providing clear explanations, going through resources together, encouraging reflection, taking enough time; and flexible delivery. Peer workers viewed the resources as potentially useful in their everyday peer work and as a valuable addition to their peer work toolkit.

Practical implications

The benefit of lived experience research to consumers is likely to be optimised by supportive and thoughtful delivery of the resources. Peer workers have the skills and are in an ideal position to do this. Bringing lived experience research to consumers provides peer workers with a potentially unique and helpful approach for supporting and promoting recovery and is congruent with their overall practice.

Originality/value

Lived experience research has the potential to benefit consumers directly but is rarely brought to their attention. This paper is the first to examine the potential role of peer workers in introducing learnings from lived experience research to consumers.
System-based barriers for seaports in contributing to Sustainable Development Goals
Authors: Katuwawala Hansini Charupraba , Bandara Yapa Mahinda
Published: April 2022

Purpose

The main purpose of this paper is to identify the reasons for the stagnant behaviour of seaports contributing towards Sustainable Development Goals (SDGs).

Design/methodology/approach

Global seaport sustainability practices that correspond with SDGs were identified through an extensive literature review. In total, five focus interviews were carried out with port managers in Sri Lanka to identify the existing knowledge about seaport sustainability, and the reasons for disparities between the global standards and country-level port sustainability practices. Data collected from a questionnaire survey of 55 seaport terminal managers in Sri Lanka were analysed using exploratory factor analysis (EFA) and thematic analysis.

Findings

Deficient collaborative policies, structural and managerial constraints, market constraints and the absence of a well-established SDG-driven global port framework were identified as significant barriers for seaports to contribute towards SDGs.

Social implications

Identifying barriers in implementing sustainable practices in ports help the responsible authorities tackle them. Hence, seaports in return and the wider society benefit from the spillover effects of port operations aligning to SDGs.

Originality/value

This paper provides port organizations insights on the barriers needing to be addressed in their operational and management systems to best incorporate practices aligning to SDGs in seaports.
Working with the chaos in an adult inpatient mental health setting: the role of an integrated therapies team
Authors: Cotter Pádraig , Papasileka Eirini , Eugster Mario , Chauhan Varsha , Garcha Eshia , Kunkler Marie , Brooks Michelle , Otvos Iulia , Srithar Abberaame , Pujol Irene , Sarafi Christina , Hughes Tom
Published: April 2022

Purpose

The purpose of this study is to outline a process-oriented psychology informed view of the impact of ever-increasing acuity within an adult inpatient system and conceptualise how an integrated therapies team (ITT) can work with the chaos that this brings.

Design/methodology/approach

A reflective scientist-practitioner based approach was used over a two-year period.

Findings

Several factors lead to “chaos” in an inpatient unit, including societal inequality, the trauma and adversity it creates and the impact of this at a systemic, interpersonal and intrapersonal level. Chaos is one means of coping and can dominate inpatient working, whereas understanding the underlying distress is often marginalised. Developing an ITT can support working with chaos. The ITT holds the therapeutic perspective for the wider multi-disciplinary team (MDT) and therapeutic and facilitation skills are central to how it operates. Processing the chaos and working with the underlying distress is its overarching function.

Practical implications

Developing an ITT offers a robust structure for evolving inpatient MDT working to cope with increasing acuity in a psychologically informed way.

Social implications

The chaos in question is often viewed as patients’ issue but from a collectivist perspective it is something that all members of society are responsible for.

Originality/value

To the best of the authors’ knowledge, this is the first paper to conceptualise the chaos on an inpatient ward as a process needed by the system as a way of coping and propose the addition of an ITT to inpatient working.
Financial fair play and competitive balance in European football: a long term perspective
Authors: Serrano Raúl , Acero Isabel , Farquhar Stuart , Espitia Escuer Manuel Antonio
Published: April 2022

Purpose

The paper analyzes the effects of financial fair play (FFP) in the competitive balance of European football industry throughout a long-term perspective.

Design/methodology/approach

The authors analyze the evolution of the competitive balance in the European football industry through a time-series analysis from season 1992/93 to 2018/19.

Findings

Results indicate an industry by nature dominated by a few clubs showing a general stationary behavior. FFP has had very little impact in local competitions. Just in some leagues, such as the Spanish, German, and French leagues, we can observe an increase in the imbalance in some indicators, but these results are not very robust. The improvement on the financial situation happens especially in a small group of firms that coincide with the big leagues with a strong European market orientation and strict local financial control standards.

Research limitations/implications

Although the study covered 17 European Leagues, there are several leagues not accounted for and thus results should be generalized with caution.

Practical implications

The authors observe heterogeneity of the results of FFP in the competitive balance, associated to how the standard has been implemented in each market. This opens opportunities to study and deepen the local codes and their influence, especially in the recommendations of future financial control standards.

Originality/value

The authors’ main contribution to the literature is to examine the impact of the FFP rules in the competitive balance utilizing a very broad study of 17 European markets with a rich and unusual overview and long-term perspective.
Ratio‐Euler deconvolution and its applications
Authors: Huang Liang , Zhang Henglei , Li Chun‐Feng , Feng Jie
Published: April 2022

Euler deconvolution of potential field data is widely applied to obtain the location of concealed sources automatically. A lot of improvements have been proposed to eliminate the dependence of Euler deconvolution on the structural index that are based on the use of high‐order derivatives of the potential field and, therefore, sensitive to data noise. We describe the elimination of the dependence on the Ratio‐Euler method, which is based on the original Euler deconvolution function. The proposed method does not involve high‐order derivatives. Testing on simulated and field data indicates that the proposed method has better noise resistance than the existing Tilt‐Euler method, which is based on high‐order derivatives. The proposed method is first applied to the ground magnetic data from Weigang iron deposit, Eastern China. It reveals that the ore body could be approximated by a horizontal prism with a considerable vertical extent with a top depth of 55 m, which are very close to the information obtained from drill holes. In addition, the proposed method works well in estimating the depth to a cavity centre from the ground gravity anomaly.
Hedging Bets; British Business Lobbying in the European Union post‐Brexit
Authors: Coen David , Katsaitis Alexander
Published: April 2022

In Brexit's aftermath, appreciating how UK business will interact with Brussels is vital to understanding the mechanics of future economic and trade relations. Drawing from work on corporate political activity, the article outlines changes that UK business lobbying faces in Brussels post‐Brexit, focussing on three key aspects: (i) changes at the institutional‐systemic level; (ii) variance across policy fields; (iii) engagement with other organisations. The article discusses potential strategic responses for UK business and argues that lobbying for UK private interests will become a costlier and more complicated enterprise. While policy making access via political doors will become harder, demand for reliable technical expertise allows UK business to maintain its presence and influence in regulatory policy areas. Targeted lobbying and diversified mobilisation offer the safest way forward for UK business lobbying in Brussels.
The amount of skeletal muscle mass is associated with arterial stiffness in hemodialysis patients
Authors: Ulgen Cansu , Ozturk Ilyas , Sahin Murat , Guzel Fatma Betul , Oguz Ayten , Altunoren Orcun , Gungor Ozkan
Published: April 2022

Introduction

Sarcopenia was determined to be associated with increased arterial stiffness in the nondialysis patient population, but there is no available data on this subject in dialysis patients.

Methods

A total of 79 patients were included in the study. Sarcopenia was diagnosed according to the EWSGOP‐2 criteria. Arterial stiffness was measured noninvasively with a mobile‐O‐Graph device.

Results

Skeletal muscle mass was observed to be positively correlated with weight, body mass index, creatinine, and uric acid, while negatively correlated with augmentation index. There was a correlation between augmentation index and sodium, phosphorus, systolic blood pressure, diastolic blood pressure, cardiac index, muscle percentage, fat percentage, and skeletal muscle mass. When the determinants of augmentation index in the linear regression analysis were viewed, just the systolic blood pressure and skeletal muscle mass were observed to be the determinant.

Conclusion

Decreased skeletal muscle mass contributes to increased arterial stiffness in hemodialysis patients.
Combating climate change: Dismantling the spatial and temporal assumptions of the core and periphery
Authors: Knox‐Hayes Janelle
Published: April 2022

In this commentary, I examine the implications of core periphery relationship with respect to challenges, implications, and responses to climate change. As authors in the special issue have demonstrated with respect to economic growth, the core‐periphery dynamic is challenged in climate change. Climate change is disrupting the fundamental conditions of human life. Its impacts are also profoundly unequal and the risks of climate change compound. Climate change exacerbates existing inequities by placing further burdens on communities that are already vulnerable. While some individuals and communities will have resources to adapt to or avoid the worst impacts of climate change, others will find their homes becoming uninhabitable, their livelihoods vanishing, and their health and security threatened. Sea level rise alone will create up to one billion climate refugees by the year 2100.
Age prediction of green turtles with an epigenetic clock
Authors: Mayne Benjamin , Mustin Walter , Baboolal Vandanaa , Casella Francesca , Ballorain Katia , Barret Mathieu , Vanderklift Mathew A. , Tucker Anton D. , Korbie Darren , Jarman Simon , Berry Oliver
Published: April 2022

Age is a fundamental life history attribute that is used to understand the dynamics of wild animal populations. Unfortunately, most animals do not have a practical or nonlethal method to determine age. This makes it difficult for wildlife managers to carry out population assessments, particularly for elusive and long‐lived fauna such as marine turtles. In this study, we present an epigenetic clock that predicts the age of marine turtles from skin biopsies. The model was developed and validated using DNA from known‐age green turtles (Chelonia mydas) from two captive populations, and mark‐recapture wild turtles with known time intervals between captures. Our method, based on DNA methylation levels at 18 CpG sites, was highly accurate with a median absolute error of 2.1 years (4.7% of maximum age in data set). This is the first epigenetic clock developed for a reptile and illustrates their broad applicability across a broad variety of vertebrate species. It has the potential to transform marine turtle management through a nonlethal and inexpensive method to provide key life history information.
Evaluation of the NANDA International, Inc. diagnostic classification in Spain: Development and validation of the EVALUAN‐I tool
Authors: Rodríguez‐Suárez Claudio Alberto , Hernández‐De Luis María Naira , Mariscal‐Crespo María Isabel , Camacho‐Bejarano Rafaela
Published: April 2022

Purpose

To develop and validate a tool to evaluate the NANDA International, Inc. diagnostic classification.

Methods

The tool, EVALUAN‐I, was validated in a non‐probabilistic sample (N = 460) on Spanish Registered Nurses (September–December 2019) in two phases. First, design and construct the instrument in three steps: (1) literature review to define the construct focusing on the orientation toward nursing concepts and theoretical foundations, the level of scientific evidence, the structural configuration, the applicability, the nurses’ clinical reasoning skills, and the attitudes toward nursing diagnosis, (2) substantiation of the questionnaire items and design according to the criteria for a diagnostic classification, (3) expert test to establish the face validity and content validity. The second phase revolved around (4) conducting a pilot test and measuring the temporal stability (test‐retest) and Cohen's kappa coefficient; assessing psychometric properties by measuring (5) reliability (internal consistency using Cronbach alpha and interfactor correlation) and (6) construct validity (exploratory and confirmatory factor analysis). The manuscript follows the STROBE checklist. The study was approved by the Research Ethics Committee with registration number 2019‐190‐1.

Findings

EVALUAN‐I displayed moderate test‐retest stability, adequate construct validity, and excellent reliability. The confirmatory factor analysis provided evidence about the configuration of EVALUAN‐I in relation to nine analytical dimensions: clinical competence, nurses’ reasoning skills, attitudes towards nursing diagnosis, discipline's central concepts, classification's contents, physiopathological attributes, level of scientific evidence, diagnostic precision, and conceptual correspondence between terminologies.

Conclusions

EVALUAN‐I is a valid and reliable instrument, which can be used to improve the epistemological, normative, and intuitive configuration of NANDA International, Inc. in a structured, systematic manner.

Implications for Nursing Practice

Comprehensive evaluation of NANDA International, Inc. in different clinical settings around the world using a validated instrument, like EVALUAN‐I, would allow strengths and weaknesses to be identified and contribute to the classification's development and practical application.
Using machine learning to predict heavy drinking during outpatient alcohol treatment
Authors: Roberts Walter , Zhao Yize , Verplaetse Terril , Moore Kelly E. , Peltier MacKenzie R. , Burke Catherine , Zakiniaeiz Yasmin , McKee Sherry
Published: April 2022

Background

Accurate clinical prediction supports the effective treatment of alcohol use disorder (AUD) and other psychiatric disorders. Traditional statistical techniques have identified patient characteristics associated with treatment outcomes. However, less work has focused on systematically leveraging these associations to create optimal predictive models. The current study demonstrates how machine learning can be used to predict clinical outcomes in people completing outpatient AUD treatment.

Method

We used data from the COMBINE multisite clinical trial (n = 1383) to develop and test predictive models. We identified three priority prediction targets, including (1) heavy drinking during the first month of treatment, (2) heavy drinking during the last month of treatment, and (3) heavy drinking between weekly/bi‐weekly sessions. Models were generated using the random forest algorithm. We used “leave sites out” partitioning to externally validate the models in trial sites that were not included in the model training. Stratified model development was used to test for sex differences in the relative importance of predictive features.

Results

Models predicting heavy alcohol use during the first and last months of treatment showed internal cross‐validation area under the curve (AUC) scores ranging from 0.67 to 0.74. AUC was comparable in the external validation using data from held‐out sites (AUC range = 0.69 to 0.72). The model predicting between‐session heavy drinking showed strong classification accuracy in internal cross‐validation (AUC = 0.89) and external test samples (AUC range = 0.80 to 0.87). Stratified analyses showed substantial sex differences in optimal feature sets.

Conclusion

Machine learning techniques can predict alcohol treatment outcomes using routinely collected clinical data. This technique has the potential to greatly improve clinical prediction accuracy without requiring expensive or invasive assessment methods. More research is needed to understand how best to deploy these models.
Robust Approach to Combining Multiple Markers to Improve Surrogacy
Authors: Wang Xuan , Parast Layla , Han Larry , Tian Lu , Cai Tianxi
Published: April 2022

Identifying effective and valid surrogate markers to make inference about a treatment effect on long-term outcomes is an important step in improving the efficiency of clinical trials. Replacing a long-term outcome with short-term and/or cheaper surrogate markers can potentially shorten study duration and reduce trial costs. There is sizable statistical literature on methods to quantify the effectiveness of a single surrogate marker. Both parametric and nonparametric approaches have been well developed for different outcome types. However, when there are multiple markers available, methods for combining markers to construct a composite marker with improved surrogacy remain limited. In this paper, building on top of the optimal transformation framework of Wang et al. (2020), we propose a novel calibrated model fusion approach to optimally combine multiple markers to improve surrogacy. Specifically, we obtain two initial estimates of optimal composite scores of the markers based on two sets of models with one set approximating the underlying data distribution and the other directly approximating the optimal transformation function. We then estimate an optimal calibrated combination of the two estimated scores which ensures both validity of the final combined score and optimality with respect to the proportion of treatment effect explained by the final combined score. This approach is unique in that it identifies an optimal combination of the multiple surrogates without strictly relying on parametric assumptions while borrowing modeling strategies to avoid fully nonparametric estimation which is subject to the curse of dimensionality. Our identified optimal transformation can also be used to directly quantify the surrogacy of this identified combined score. Theoretical properties of the proposed estimators are derived, and the finite sample performance of the proposed method is evaluated through simulation studies. We further illustrate the proposed method using data from the Diabetes Prevention Program study.
Nonparametric and Semiparametric Estimation with Sequentially Truncated Survival Data
Authors: Betensky Rebecca A. , Qian Jing , Hou Jingyao
Published: April 2022

In observational cohort studies with complex sampling schemes, truncation arises when the time to event of interest is observed only when it falls below or exceeds another random time, that is, the truncation time. In more complex settings, observation may require a particular ordering of event times; we refer to this as sequential truncation. Estimators of the event time distribution have been developed for simple left-truncated or right-truncated data. However, these estimators may be inconsistent under sequential truncation. We propose nonparametric and semiparametric maximum likelihood estimators for the distribution of the event time of interest in the presence of sequential truncation, under two truncation models. We show the equivalence of an inverse probability weighted estimator and a product limit estimator under one of these models. We study the large sample properties of the proposed estimators and derive their asymptotic variance estimators. We evaluate the proposed methods through simulation studies and apply the methods to an Alzheimer's disease study. We have developed an R package, seqTrun, for implementation of our method.
Machine learning approaches and their applications in drug discovery and design
Authors: Priya Sonal , Tripathi Garima , Singh Dev Bukhsh , Jain Priyanka , Kumar Abhijeet
Published: April 2022

This review is focused on several machine learning approaches used in chemoinformatics. Machine learning approaches provide tools and algorithms to improve drug discovery. Many physicochemical properties of drugs like toxicity, absorption, drug‐drug interaction, carcinogenesis, and distribution have been effectively modeled by QSAR techniques. Machine learning is a subset of artificial intelligence, and this technique has shown tremendous potential in the field of drug discovery. Techniques discussed in this review are capable of modeling non‐linear datasets, as well as big data of increasing depth and complexity. Various machine learning‐based approaches are being used for drug target prediction, modeling the structure of drug target, binding site prediction, ligand‐based similarity searching, de novo designing of ligands with desired properties, developing scoring functions for molecular docking, building QSAR model for biological activity prediction, and prediction of pharmacokinetic and pharmacodynamic properties of ligands. In recent years, these predictive tools and models have achieved good accuracy. By the use of more related input data, relevant parameters, and appropriate algorithms, the accuracy of these predictions can be further improved.
Intracardiac masses in a giant right atrium: Tumors or thrombus?
Authors: Wu Wenqian , Fan Qianqian , Chen Yan , Fang Lingyun , Xie Mingxing
Published: April 2022

The coexist of primary angiosarcoma and thrombosis is a rare clinical entity. A 46‐year‐old male was presented with multiple right atrial (RA) masses. Two different vascular patterns in these masses were identified by contrast echocardiography. The possibility of coexistence of malignant tumors and thrombus in RA was implicated, which was further confirmed by computed tomography, magnetic resonance imaging, positron emission tomography/computer tomography, and pathologic examination. This case highlights the advantages of contrast echocardiography in the differential diagnosis of cardiac masses.
Dynamic Bayesian networks for stratification of disease progression in amyotrophic lateral sclerosis
Authors: Gromicho Marta , Leão Tiago , Oliveira Santos Miguel , Pinto Susana , Carvalho Alexandra M. , Madeira Sara C. , De Carvalho Mamede
Published: April 2022

Background and purpose

Progression rate is quite variable in amyotrophic lateral sclerosis (ALS); thus, tools for profiling disease progression are essential for timely interventions. The objective was to apply dynamic Bayesian networks (DBNs) to establish the influence of clinical and demographic variables on disease progression rate.

Methods

In all, 664 ALS patients from our database were included stratified into slow (SP), average (AP) and fast (FP) progressors, according to the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS‐R) rate of decay. The sdtDBN framework was used, a machine learning model which learnt optimal DBNs with both static (gender, age at onset, onset region, body mass index, disease duration at entry, familial history, revised El Escorial criteria and C9orf72) and dynamic (ALSFRS‐R scores and sub‐scores, forced vital capacity, maximum inspiratory pressure, maximum expiratory pressure and phrenic amplitude) variables.

Results

Disease duration and body mass index at diagnosis are the foremost influences amongst static variables. Disease duration is the variable that better discriminates the three groups. Maximum expiratory pressure is the respiratory test with prevalent influence on all groups. ALSFRS score has a higher influence on FP, but lower on AP and SP. The bulbar sub‐score has considerable influence on FP but limited on SP. Limb function has a more decisive influence on AP and SP. The respiratory sub‐score has little influence in all groups. ALSFRS‐R questions 1 (speech) and 9 (climbing stairs) are the most influential in FP and SP, respectively.

Conclusions

The sdtDBN analysis identified five variables, easily obtained during clinical evaluation, which are the most influential for each progression group. This insightful information may help to improve prognosis and care.
Rapid auditory processing and medial geniculate nucleus anomalies in Kiaa0319 knockout mice
Authors: Perrino Peter A. , Chasse Renee Y. , Monaco Anthony P. , Molnár Zoltán , Velayos‐Baeza Antonio , Fitch R. Holly
Published: April 2022

Developmental dyslexia is a common neurodevelopmental disorder characterized by difficulties in reading and writing. Although underlying biological and genetic mechanisms remain unclear, anomalies in phonological processing and auditory processing have been associated with dyslexia. Several candidate risk genes have also been identified, with KIAA0319 as a main candidate. Animal models targeting the rodent homolog (Kiaa0319) have been used to explore putative behavioral and anatomic anomalies, with mixed results. For example after downregulation of Kiaa0319 expression in rats via shRNA, significant adult rapid auditory processing impairments were reported, along with cortical anomalies reflecting atypical neuronal migration. Conversely, Kiaa0319 knockout (KO) mice were reported to have typical adult auditory processing, and no visible cortical anomalies. To address these inconsistencies, we tested Kiaa0319 KO mice on auditory processing tasks similar to those used previously in rat shRNA knockdown studies. Subsequent neuroanatomic analyses on these same mice targeted medial geniculate nucleus (MGN), a receptive communication‐related brain structure. Results confirm that Kiaa0319 KO mice exhibit significant auditory processing impairments specific to rapid/brief stimuli, and also show significant volumetric reductions and a shift toward fewer large and smaller neurons in the MGN. The latter finding is consistent with post mortem MGN data from human dyslexic brains. Combined evidence supports a role for KIAA0319 in the development of auditory CNS pathways subserving rapid auditory processing functions critical to the development of speech processing, language, and ultimately reading. Results affirm KIAA0319 variation as a possible risk factor for dyslexia specifically via anomalies in central acoustic processing pathways.