bluuebunny/crossref_metadata_2025 huggingface dataset:
Identifying variation in GP referral rates: an observational study of outpatient headache referrals
Authors: Biggin Fran , Davies Quinta , Howcroft Timothy , Emsley Hedley , Knight Jo
Published: February 2022

Objective

To identify GP surgeries with unexpected rates of referral to specialist services, using headache referrals to outpatient neurology as an example. Identifying surgeries with unexpectedly high or low referral rates allows for further investigation and potential support to be targeted where it is most likely to be effective.

Methods

This is a retrospective observational study using routinely collected and open-source data. Data was collected from a single consultant outpatient neurology clinic and 202 GP surgeries across seven CCGs in the Northwest of England. The number of headache referrals from each GP surgery during a study period of 3 ¼ years was used as the primary outcome in a poisson model. The standardised residuals from this model were then used to identify GP surgeries that were likely to have referred unexpected patient numbers for headaches to an outpatient neurology clinic during the study period.

Results

We identified four GP surgeries with unexpected numbers of referrals. This model also showed that there were two main predictors of headache referral, namely other neurology referrals and the distance of the GP surgery from the outpatient clinic.

Conclusion

GP surgeries with unexpected numbers of referrals to specialist services were identified using a flexible methodology. This methodology was demonstrated using headache referrals but could be adapted to any type of referral or geographical area.
Factors associated with higher levels of grief and support needs among people bereaved during the pandemic: Results from a national online survey
Authors: Selman LE , Farnell D J J , Longo M , Goss S , Torrens-Burton A , Seddon K , Mayland C R , Machin L , Byrne A , Harrop E J
Published: February 2022

Background

The COVID-19 pandemic has affected millions of people’s experiences of bereavement. We aimed to identify risk factors for grief and support needs.

Methods

Online survey of people bereaved in the UK (deaths 16 March 2020-2 January 2021), recruited via media, social media, national associations/organisations. Grief was assessed using the Adult Attitude to Grief (AAG) scale, which calculates an overall index of vulnerability (IOV) (range 0-36). Practical and emotional support needs were assessed in 13 domains.

Results

711 participants, mean age 49.5 (SD 12.9, range 18-90). 628 (88.6%) were female. Mean age of the deceased 72.2 (SD 16.1). 311 (43.8%) deaths were from confirmed/suspected COVID-19. Mean IOV was 20.41 (95% CI = 20.06 to 20.77). 28.2% exhibited severe vulnerability (IOV ≥ 24). In six support domains relating to psycho-emotional support, 50% to 60% of respondents reported high/fairly high levels of need. Grief and support needs increased strongly for close relationships with the deceased (versus more distant) and with reported social isolation and loneliness (P < 0.001), whereas they reduced with age of the deceased above 40 to 50. Other risk factors were place of death and reduced support from health professionals after death (P < 0.05).

Conclusions

High overall levels of vulnerability in grief and support needs were observed. Relationship with the deceased, age of the deceased, and social isolation and loneliness are potential indicators of those at risk of even higher vulnerability in grief and support needs. Healthcare professional support after death is associated with more positive bereavement outcomes.
Time to reinfection and vaccine breakthrough SARS-CoV-2 infections: a retrospective cohort study
Authors: Molani Sevda , Baumgartner Andrew M. , Hwang Yeon Mi , Duvvuri Venkata R. , Goldman Jason D. , Hadlock Jennifer J.
Published: February 2022

Background

It is important to understand how BNT162b2, mRNA-1273, and JNJ-78436735 COVID-19 vaccines, as well as prior infection, protect against breakthrough cases and reinfections. Real world evidence on acquired immunity from vaccines, and from SARS-CoV-2 infection, can help public health decision-makers understand disease dynamics and viral escape to inform resource allocation for curbing the spread of pandemic.

Methods

This retrospective cohort study presents demographic information, survival functions, and probability distributions for 2,627,914 patients who received recommended doses of COVID-19 vaccines, and 63,691 patients who had a prior COVID-19 infection. In addition, patients receiving different vaccines were matched by age, sex, ethnic group, state of residency, and the quarter of the year in 2021 the COVID-19 vaccine was completed, to support survival analysis on pairwise matched cohorts.

Findings

Each of the three vaccines and infection-induced immunity all showed a high probability of survival against breakthrough or reinfection cases (mRNA-1273: 0.997, BNT162b2: 0.997, JNJ-78436735: 0.992, previous infection: 0.965 at 180 days). The incidence rate of reinfection among those unvaccinated and previously infected was higher than that of breakthrough among the vaccinated population (reinfection: 0.9%; breakthrough:0.4%). In addition, 280 vaccinated patients died (0.01% all-cause mortality) within 21 days of the last vaccine dose, and 5898 (3.1 %) died within 21 days of a positive COVID-19 test.

Conclusions

Despite a gradual decline in vaccine-induced and infection-induced immunity, both acquired immunities were highly effective in preventing breakthrough and reinfection. In addition, for unvaccinated patients with COVID-19, those who did not die within 90 days of their initial infection (9565 deaths, 5.0% all-cause mortality rate), had a comparable asymptotic pattern of breakthrough infection as those who acquired immunity from a vaccine. Overall, the risks associated with COVID-19 infection are far greater than the marginal advantages of immunity acquired by prior infection.
Spatio-temporal monitoring of lake fish spawning activity using environmental DNA metabarcoding
Authors: Di Muri C. , Lawson Handley L. , Bean C. W. , Benucci M. , Harper L. R. , James B. , Li J. , Winfield I. J. , Hänfling B.
Published: February 2022

Determining the timing and location of fish reproductive events is crucial for the implementation of correct management and conservation schemes. Conventional methods used to monitor these events are often unable to assess the spawning activity directly or can be invasive and therefore problematic. This is especially the case when threatened fish populations are the study subject, such as the Arctic charr (Salvelinus alpinus L.) populations in Windermere (Cumbria, UK). Arctic charr populations have been studied in this lake since the 1940s, and the locations and characteristics of spawning grounds have been described in detail using techniques such as hydroacoustics, as well as physical and visual surveys of the lake bottom. Here, in conjunction with established netting surveys, we added an environmental DNA (eDNA) metabarcoding approach to assess the spatial distribution of Arctic charr in the lake throughout the year to test whether this tool could allow us to identify spawning locations and activity. Sampling was carried out between October 2017 and July 2018 at three locations in the lake, covering putative and known spawning sites. eDNA metabarcoding provided accurate spatial and temporal characterisation of Arctic charr spawning events. Peaks of Arctic charr read counts from eDNA metabarcoding were observed during the spawning season and at specific locations of both putative and known spawning sites. Net catches of mature Arctic charr individuals confirmed the association between the Arctic charr spawning activity and the peaks of eDNA metabarcoding read counts. This study demonstrates the ability of eDNA metabarcoding to effectively and efficiently characterize the spatial and temporal nature of fish spawning in lentic systems.
NGS data reveals the phyllosphere microbiome of wheat plants infected by the fungal pathogen Zymoseptoria tritici
Authors: Barroso-Bergada Didac , Massot Marie , Vignolles Noémie , d’Arcier Julie Faivre , Chancerel Emilie , Guichoux Erwan , Walker Anne-Sophie , Vacher Corinne , Bohan David A. , Laval Valérie , Suffert Frédéric
Published: February 2022

The fungal pathogen Zymoseptoria tritici is the causal agent of Septoria tritici blotch (STB), a major wheat disease in Western Europe. Microorganisms inhabiting wheat leaves might act as beneficial, biocontrol or facilitating agents that could limit or stimulate the development of Z. tritici. Improving our understanding of microbial communities in the wheat phyllosphere would lead to new insights into STB management. This resource announcement provides fungal and bacterial metabarcoding datasets obtained by sampling wheat leaves differing in the presence of symptoms caused by Z. tritici. Tissues were sampled from three wheat commercial varieties on three sampling dates during a cropping season. Weeds around wheat fields were sampled as well. In total, more than 450 leaf samples were collected. The pathogen Z. tritici was quantified using qPCR. We provide the raw metabarcoding datasets, the Amplicon Sequence Variant (ASV) tables obtained after bioinformatic processing, the metadata associated to each sample (sampling date, wheat variety and tissue health condition), a preliminary descriptive analysis of the data, and the code used for bioinformatic and descriptive statistical analysis.
Glycan shield of the ebolavirus envelope glycoprotein GP
Authors: Peng W. , Rayaprolu V. , Parvate A.D. , Pronker M.F. , Hui S. , Parekh D. , Shaffer K. , Yu X. , Saphire E.O. , Snijder J.
Published: February 2022

The envelope glycoprotein GP of the ebolaviruses is essential for host cell attachment and entry. It is also the primary target of the protective and neutralizing antibody response in both natural infection and vaccination. GP is heavily glycosylated with up to 17 predicted N-linked sites, numerous O-linked glycans in its disordered mucin-like domain (MLD), and three predicted C-linked mannosylation sites. Glycosylation of GP is important for host cell attachment to cell-surface lectins, as well as GP stability and fusion activity. Moreover, it has been shown to shield GP from neutralizing activity of serum antibodies. Here, we use mass spectrometry-based glycoproteomics to profile the site-specific glycosylation patterns of ebolavirus GP. We detect up to 16 unique O-linked glycosylation sites in the mucin-like domain, as well as two O-linked sites in the head and glycan cap domains of the receptor-binding GP1 subunit. Multiple O-linked glycans are observed at the S/T residues of N-linked glycosylation sequons, suggesting possible crosstalk between the two types of modifications. We also confirmed the presence of C-mannosylation at W288 in the context of trimeric GP. We find heterogenous, complex N-linked glycosylation at the majority of predicted sites as expected. By contrast, the two conserved sites N257 and N563 are enriched in unprocessed high-mannose and hybrid glycans, suggesting a role in host-cell attachment via DC-SIGN/L-SIGN. We discuss our findings in the context of antibody recognition to show how glycans contribute to and restrict neutralization epitopes. This information on how N-, O-, and C-linked glycans together build the heterogeneous glycan shield of GP can guide future immunological studies and functional interpretation of ebolavirus GP-antibody interactions.
Non-synaptic alterations in striatal excitability and cholinergic modulation in a SAPAP3 mouse model of compulsive motor behavior
Authors: Malgady Jeffrey M. , Baez Alexander , Jimenez Kimberly , Hobel Zachary B. , Prager Eric M. , Zhang Qiangge , Feng Guoping , Plotkin Joshua L.
Published: February 2022

Deletion of the OCD-associated gene SAP90/PSD-95-associated protein 3 (Sapap3), which encodes a postsynaptic anchoring protein at corticostriatal synapses, causes OCD-like motor behaviors in mice. While corticostriatal synaptic dysfunction is central to this phenotype, the striatum efficiently adapts to pathological changes, often in ways that expand upon the original circuit impairment. Here we show that SAPAP3 deletion causes non-synaptic and pathwayspecific alterations in dorsolateral striatum circuit function. While somatic excitability was elevated in striatal projection neurons (SPNs), dendritic excitability was exclusively enhanced in direct pathway SPNs. Layered on top of this, cholinergic modulation was altered in opposing ways: striatal cholinergic interneuron density and evoked acetylcholine release were elevated, while basal muscarinic modulation of SPNs was reduced. These data describe how SAPAP3 deletion alters the striatal landscape upon which impaired corticostriatal inputs will act, offering a basis for how pathological synaptic integration and unbalanced striatal output underlying OCD-like behaviors may be shaped.
Identification of functional Spo0A residues critical for sporulation in Clostridioides difficile
Authors: DiCandia Michael A. , Edwards Adrianne N. , Jones Joshua B. , Swaim Grace L. , Mills Brooke D. , McBride Shonna M.
Published: February 2022

Clostridioides difficile is an anaerobic, Gram-positive pathogen that is responsible for C. difficile infection (CDI). To survive in the environment and spread to new hosts, C. difficile must form metabolically-dormant spores. The formation of spores requires activation of the transcription factor Spo0A, which is the master regulator of sporulation in all endospore-forming bacteria. Though the sporulation initiation pathway has been delineated in the Bacilli, including the model spore-former Bacillus subtilis, the direct regulators of Spo0A in C. difficile remain undefined. C. difficile Spo0A shares highly conserved protein interaction regions with the B. subtilis sporulation proteins Spo0F and Spo0A, although many of the interacting factors present in B. subtilis are not encoded in C. difficile. To determine if comparable Spo0A residues are important for C. difficile sporulation initiation, site-directed mutagenesis was performed at conserved receiver domain residues and the effects on sporulation were examined. Mutation of residues important for homodimerization and interaction with both positive and negative regulators of B. subtilis Spo0A and Spo0F impacted C. difficile Spo0A function. The data also demonstrated that mutation of many additional conserved residues altered C. difficile Spo0A activity, even when the corresponding Bacillus interacting proteins are not apparent in the C. difficile genome. Finally, the conserved aspartate residue at position 56 of C. difficile Spo0A was determined to be the phosphorylation site that is necessary for Spo0A activation. The finding that Spo0A interacting motifs maintain functionality suggests that C. difficile Spo0A interacts with yet unidentified proteins that regulate its activity and control spore formation.
High-throughput widefield fluorescence imaging of 3D samples using deep learning for 2D projection image restoration
Authors: Forsgren Edvin , Edlund Christoffer , Oliver Miniver , Barnes Kalpana , Sjögren Rickard , Jackson Timothy R.
Published: February 2022

Fluorescence microscopy has become a core tool for visualizing and quantifying the spatial and temporal dynamics of complex biological processes. Thanks to its low cost and ease-of-use, widefield fluorescent imaging remains one of the most widely used fluorescence microscopy imaging modalities. To accomplish imaging of 3D samples, conventional fluorescence imaging entails acquiring a sequence of 2D images spaced along the z-dimension, typically called a z-stack. Oftentimes, the next step is to project the 3D volume into a single 2D image, as 3D image data can be cumbersome to manage and challenging to analyze and interpret, effectively limiting the utlity of z-dimensional information. Furthermore, z-stack acquisition is often time-consuming and consequently may induce photodamage to the biological sample, which are both major hurdles for its application in experiments that require high-throughput, such as drug screening. As an alternative to z-stacks, axial sweep acquisition schemes have been proposed to circumvent these drawbacks and offers potential of 100-fold faster image acquisition for 3D-samples compared to z-stack acquisition but unfortunately results in blurry, low-quality raw 2D z-projected images. We propose a novel workflow to combine axial z-sweep acquisition with deep learning-based image restoration, ultimately enabling high-throughput and high-quality imaging of complex 3D-samples using 2D projection images. To demonstrate the capabilities of our proposed workflow, we apply it to live-cell imaging of 3D tumor spheroids and find we can produce high-fidelity images appropriate for quantitative analysis. Therefore, we conclude that combining axial z-sweep image acquisition with deep learning-based image restoration enables high-throughput and high-quality fluorescence imaging of complex 3D biological samples.
PBRM1 BD2 and BD4 associate with RNA to facilitate chromatin association
Authors: De Silva Saumya M. , Sood Surbhi , Dhiman Alisha , Mercedes Kilsia F. , Henen Morkos A. , Vögeli Beat , Dykhuizen Emily C. , Musselman Catherine A.
Published: February 2022

PBRM1 is a subunit of the PBAF chromatin remodeling complex, which is mutated in 40-50% of clear cell renal cell carcinoma patients. It is thought to largely function as a chromatin binding subunit of the PBAF complex, but the molecular mechanism underlying this activity is not fully known. PBRM1 contains six tandem bromodomains which are known to cooperate in binding of nucleosomes acetylated at histone H3 lysine 14 (H3K14ac). Here we demonstrate that the second and fourth bromodomains from PBRM1 also bind nucleic acids, selectively associating with double stranded RNA elements. Disruption of the RNA binding pocket is found to compromise PBRM1 chromatin binding and inhibit PBRM1-mediated cellular growth effects.
Can DyeCycling break the photobleaching limit in single-molecule FRET?
Authors: Vermeer Benjamin , Schmid Sonja
Published: February 2022

Biomolecular systems, such as proteins, crucially rely on dynamic processes at the nanoscale. Detecting biomolecular nanodynamics is therefore key to obtaining a mechanistic understanding of the energies and molecular driving forces that control biomolecular systems. Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique to observe in real-time how a single biomolecule proceeds through its functional cycle involving a sequence of distinct structural states. Currently, this technique is fundamentally limited by irreversible photobleaching, causing the untimely end of the experiment and thus, a prohibitively narrow temporal bandwidth of ≤ 3 orders of magnitude. Here, we introduce ‘DyeCycling’, a measurement scheme with which we aim to break the photobleaching limit in single-molecule FRET. We introduce the concept of spontaneous dye replacement by simulations, and as an experimental proof-of-concept, we demonstrate the intermittent observation of a single biomolecule for one hour with a time resolution of milliseconds. Theoretically, DyeCycling can provide >100-fold more information per single molecule than conventional smFRET. We discuss the experimental implementation of DyeCycling, its current and fundamental limitations, and specific biological use cases. Given its general simplicity and versatility, DyeCycling has the potential to revolutionize the field of time-resolved smFRET, where it may serve to unravel a wealth of biomolecular dynamics by bridging from milliseconds to the hour range.
ACh signaling modulates activity of the GABAergic signaling network in the basolateral amygdala and behavior in stress-relevant paradigms
Authors: Mineur Yann S. , Mose Tenna N. , Maibom Kathrine Lefoli , Pittenger Steven T. , Soares Alexa R. , Wu Hao , Huang Yaqing , Picciotto Marina R
Published: February 2022

Balance between excitatory and inhibitory (E/I) signaling is important for maintaining homeostatic function in the brain. Indeed, dysregulation of inhibitory GABA interneurons in the amygdala has been implicated in human mood disorders. We hypothesized that acetylcholine (ACh) signaling in the basolateral amygdala (BLA) might alter E/I balance resulting in changes in stress-sensitive behaviors. We therefore measured ACh release as well as activity of calmodulin-dependent protein kinase II (CAMKII)-, parvalbumin (PV)-, somatostatin (SOM)- and vasoactive intestinal protein (VIP)-expressing neurons in the BLA of awake, behaving mice. ACh levels and activity of both excitatory and inhibitory BLA neurons increased when animals were actively coping, and decreased during passive coping, in the light-dark box, tail suspension and social defeat. Changes in neuronal activity preceded behavioral state transitions, suggesting that BLA activity may drive the shift in coping strategy. In contrast to exposure to escapable stressors, prolonging ACh signaling with a cholinesterase antagonist changed the balance of activity among BLA cell types, significantly increasing activity of VIP neurons and decreasing activity of SOM cells, with little effect on CaMKII or PV neurons. Knockdown of α7 or β2-containing nAChR subtypes in PV and SOM, but not CaMKII or VIP, BLA neurons altered behavioral responses to stressors, suggesting that ACh signaling through nAChRs on GABA neuron subtypes contributes to stress-induced changes in behavior. These studies show that ACh modulates the GABAergic signaling network in the BLA, shifting the balance between SOM, PV, VIP and CaMKII neurons, which are normally activated coordinately during active coping in response to stress. Thus, prolonging ACh signaling, as occurs in response to chronic stress, may contribute to maladaptive behaviors by shifting the balance of inhibitory signaling in the BLA.
Neuronal growth regulator 1 (NEGR1) promotes synaptic targeting of glutamic acid decarboxylase 65 (GAD65)
Authors: Amanda Tan Rui Ping , Kozlova Irina , Su Feifei , Sah Saroj , Keable Ryan , Hagan D. Walker , Bustamante Sonia , Du Ximing , Osborne Brenna , Turner Nigel , Clemens Kelly J. , Begg Denovan , Phelps Edward A. , Yang Hongyuan , Leshchyns’ka Iryna , Sytnyk Vladimir
Published: February 2022

Neuronal growth regulator 1 (NEGR1) is a glycosylphosphatidylinositol-anchored cell adhesion molecule encoded by an obesity susceptibility gene. We demonstrate that NEGR1 accumulates in GABAergic inhibitory synapses in hypothalamic neurons, a GABA-synthesizing enzyme GAD65 attaches to the plasma membrane, and NEGR1 promotes clustering of GAD65 at the synaptic plasma membrane. GAD65 is removed from the plasma membrane with newly formed vesicles. The association of GAD65 with vesicles results in increased GABA synthesis. In NEGR1 deficient mice, the synaptic targeting of GAD65 is decreased, the GABAergic synapse densities are reduced, and the reinforcing effects of food rewards are blunted. In mice fed a high fat diet, levels of NEGR1 are increased and GAD65 abnormally accumulates at the synaptic plasma membrane. Our results indicate that NEGR1 regulates a previously unknown step required for synaptic targeting and functioning of GAD65, which can be affected by bidirectional changes in NEGR1 levels causing disruptions in the GABAergic signaling controlling feeding behavior.
Whole-genome resequencing of temporally stratified samples reveals substantial loss of haplotype diversity in the highly inbred Scandinavian wolf population
Authors: Viluma Agnese , Flagstad Øystein , Åkesson Mikael , Wikenros Camilla , Sand Håkan , Wabakken Petter , Ellegren Hans
Published: February 2022

Genetic drift can dramatically change allele frequencies in small populations and lead to reduced levels of genetic diversity, including loss of segregating variants. However, there is a shortage of quantitative studies of how genetic diversity changes over time in natural populations, especially on genome-wide scales. Here, we analyzed whole-genome sequences from 76 wolves of a highly inbred Scandinavian population, founded by only one female and two males, sampled over a period of 30 yr. We obtained chromosome-level haplotypes of all three founders and found that 10%–24% of their diploid genomes had become lost after about 20 yr of inbreeding (which approximately corresponds to five generations). Lost haplotypes spanned large genomic regions, as expected from the amount of recombination during this limited time period. Altogether, 160,000 SNP alleles became lost from the population, which may include adaptive variants as well as wild-type alleles masking recessively deleterious alleles. Although not sampled, we could indirectly infer that the two male founders had megabase-sized runs of homozygosity and that all three founders showed significant haplotype sharing, meaning that there were on average only 4.2 unique haplotypes in the six copies of each autosome that the founders brought into the population. This violates the assumption of unrelated founder haplotypes often made in conservation and management of endangered species. Our study provides a novel view of how whole-genome resequencing of temporally stratified samples can be used to visualize and directly quantify the consequences of genetic drift in a small inbred population.
Facebook medical support groups: the communication privacy management perspective
Authors: Avizohar Carmel , Gazit Tali , Aharony Noa
Published: February 2022

Purpose

Exploring the considerations that guide and influence members of Facebook medical support groups to disclose private information.

Design/methodology/approach

The sample included 293 participants, aged 18–85 years, who answered an online survey, 155 members of Facebook medical support groups and 138 members of other Facebook groups.

Findings

Members of medical support groups attach greater importance to privacy policy, give greater value to privacy and reveal more private information, compared to members of other groups. Members of medical support groups tend to feel that they receive more support and feel that the privacy policy preserves their privacy much more. These feelings are associated with greater self-disclosure of groups' members.

Originality/value

The research insights will help medical support groups' members and admins to put into action the fundamental right to privacy and build a set of rules tailored to their individual and group needs.
Cyber resilience in supply chain system security using machine learning for threat predictions
Authors: Yeboah-Ofori Abel , Swart Cameron , Opoku-Boateng Francisca Afua , Islam Shareeful
Published: February 2022

Purpose

Cyber resilience in cyber supply chain (CSC) systems security has become inevitable as attacks, risks and vulnerabilities increase in real-time critical infrastructure systems with little time for system failures. Cyber resilience approaches ensure the ability of a supply chain system to prepare, absorb, recover and adapt to adverse effects in the complex CPS environment. However, threats within the CSC context can pose a severe disruption to the overall business continuity. The paper aims to use machine learning (ML) techniques to predict threats on cyber supply chain systems, improve cyber resilience that focuses on critical assets and reduce the attack surface.

Design/methodology/approach

The approach follows two main cyber resilience design principles that focus on common critical assets and reduce the attack surface for this purpose. ML techniques are applied to various classification algorithms to learn a dataset for performance accuracies and threats predictions based on the CSC resilience design principles. The critical assets include Cyber Digital, Cyber Physical and physical elements. We consider Logistic Regression, Decision Tree, Naïve Bayes and Random Forest classification algorithms in a Majority Voting to predicate the results. Finally, we mapped the threats with known attacks for inferences to improve resilience on the critical assets.

Findings

The paper contributes to CSC system resilience based on the understanding and prediction of the threats. The result shows a 70% performance accuracy for the threat prediction with cyber resilience design principles that focus on critical assets and controls and reduce the threat.

Research limitations/implications

Therefore, there is a need to understand and predicate the threat so that appropriate control actions can ensure system resilience. However, due to the invincibility and dynamic nature of cyber attacks, there are limited controls and attributions. This poses serious implications for cyber supply chain systems and its cascading impacts.

Practical implications

ML techniques are used on a dataset to analyse and predict the threats based on the CSC resilience design principles.

Social implications

There are no social implications rather it has serious implications for organizations and third-party vendors.

Originality/value

The originality of the paper lies in the fact that cyber resilience design principles that focus on common critical assets are used including Cyber Digital, Cyber Physical and physical elements to determine the attack surface. ML techniques are applied to various classification algorithms to learn a dataset for performance accuracies and threats predictions based on the CSC resilience design principles to reduce the attack surface for this purpose.
Robust multifocus deep neural network for progression prediction on patient trajectory data
Authors: Arunkumar K. , Vasundra S.
Published: February 2022

Purpose

Patient treatment trajectory data are used to predict the outcome of the treatment to particular disease that has been carried out in the research. In order to determine the evolving disease on the patient and changes in the health due to treatment has not considered existing methodologies. Hence deep learning models to trajectory data mining can be employed to identify disease prediction with high accuracy and less computation cost.

Design/methodology/approach

Multifocus deep neural network classifiers has been utilized to detect the novel disease class and comorbidity class to the changes in the genome pattern of the patient trajectory data can be identified on the layers of the architecture. Classifier is employed to learn extracted feature set with activation and weight function and then merged on many aspects to classify the undetermined sequence of diseases as a new variant. The performance of disease progression learning progress utilizes the precision of the constituent classifiers, which usually has larger generalization benefits than those optimized classifiers.

Findings

Deep learning architecture uses weight function, bias function on input layers and max pooling. Outcome of the input layer has applied to hidden layer to generate the multifocus characteristics of the disease, and multifocus characterized disease is processed in activation function using ReLu function along hyper parameter tuning which produces the effective outcome in the output layer of a fully connected network. Experimental results have proved using cross validation that proposed model outperforms methodologies in terms of computation time and accuracy.

Originality/value

Proposed evolving classifier represented as a robust architecture on using objective function to map the data sequence into a class distribution of the evolving disease class to the patient trajectory. Then, the generative output layer of the proposed model produces the progression outcome of the disease of the particular patient trajectory. The model tries to produce the accurate prognosis outcomes by employing data conditional probability function. The originality of the work defines 70% and comparisons of the previous methods the method of values are accurate and increased analysis of the predictions.
Prediction and evaluation of fatigue life considering material parameters distribution characteristic
Authors: Liu Xintian , Liu Jiazhi , Wang Haijie , Yang Xiaobing
Published: February 2022

Purpose

To improve the accuracy of parameter prediction for small-sample data, considering the existence of error in samples, the error circle is introduced to analyze original samples.

Design/methodology/approach

The influence of surface roughness on fatigue life is discussed. The error circle can treat the original samples and extend the single sample, which reduces the influence of the sample error.

Findings

The S-N curve obtained by the error circle method is more reliable; the S-N curve of the Bootstrap method is more reliable than that of the Maximum Likelihood Estimation (MLE) method.

Originality/value

The parameter distribution and characteristics are statistically obtained based on the surface roughness, surface roughness factor and intercept constant. The original sample is studied by an error circle and discussed using the Bootstrap and MLE methods to obtain corresponding S-N curves. It provides a more trustworthy basis for predicting the useful life of products.
Measuring the time spent on data curation
Authors: Perry Anja , Netscher Sebastian
Published: February 2022

Purpose

Budgeting data curation tasks in research projects is difficult. In this paper, we investigate the time spent on data curation, more specifically on cleaning and documenting quantitative data for data sharing. We develop recommendations on cost factors in research data management.

Design/methodology/approach

We make use of a pilot study conducted at the GESIS Data Archive for the Social Sciences in Germany between December 2016 and September 2017. During this period, data curators at GESIS - Leibniz Institute for the Social Sciences documented their working hours while cleaning and documenting data from ten quantitative survey studies. We analyse recorded times and discuss with the data curators involved in this work to identify and examine important cost factors in data curation, that is aspects that increase hours spent and factors that lead to a reduction of their work.

Findings

We identify two major drivers of time spent on data curation: The size of the data and personal information contained in the data. Learning effects can occur when data are similar, that is when they contain same variables. Important interdependencies exist between individual tasks in data curation and in connection with certain data characteristics.

Originality/value

The different tasks of data curation, time spent on them and interdependencies between individual steps in curation have so far not been analysed.
Understanding the determinants of users’ continuance intention to buy low-cost airline flights online
Authors: Tam Carlos , Barroso Maria , Cruz-Jesus Frederico
Published: February 2022

Purpose

Low-cost carriers’ (LCC) worldwide market share is gaining momentum. This paper aims to propose using the expectation confirmation model (ECM) combined with brand awareness and image, website quality and visual appeal to evaluate the continuance use intention of low-cost airlines (LCA) websites.

Design/methodology/approach

The empirical approach was based on an online survey of 272 individuals collected in Portugal. The data were analyzed using structural equation modeling.

Findings

Brand awareness, brand image and satisfaction are the variables that best explain continuance intention. The leftover constructs can empirically explain ECM.

Originality/value

This study seeks to understand the significance of brand awareness and image, website quality and visual appeal in LCA websites’ confirmation and continuance use intention. Understanding the influence on confirmation and long-term viability, strategies based on these conclusions are proposed for LCC companies to better promote consumers’ continuance use intention.
Fatigue life optimization for 17-4Ph steel produced by selective laser melting
Authors: Linares Jean-marc , Chaves-Jacob Julien , Lopez Quentin , Sprauel Jean-Michel
Published: February 2022

Purpose

The mechanical characterization of selective laser melting (SLM) parts is an industrial challenge. This paper aims to propose a methodology to control the fatigue life of 17-4Ph stainless steel by selecting the most relevant manufacturing parameters: i.e. laser power, laser travel speed, hatch spacing and laser defocusing.

Design/methodology/approach

A rough and refined design of experiment (DOE) is carried out to target the best combination of process parameters. A response surface model is then constructed to predict the parameter combination that optimizes the fatigue performance.

Findings

This study results show that the fatigue limit of the specimens manufactured by SLM (471.7 MPa at 107 cycles) has reached near 90% of the value found in samples machined from a bar. This demonstrates the applicability of the method proposed to optimize the SLM process and control the fatigue life of 17-4Ph stainless steel. The study results are compared with other research works and provide an increase of 18% to the fatigue limit.

Originality/value

This study showcases a DOE methodology to optimize the SLM parameters to achieve fatigue performance as great as that of solid 17-4Ph stainless steel.
The effect of big data in transforming to learning organization a single-case study in IT sector
Authors: Başak Sena , Kılınç İzzet , Ünal Aslıhan
Published: February 2022

Purpose

The purpose of this paper is to examine the contribution of big data in the transforming process of an IT firm to a learning organization.

Design/methodology/approach

The authors adopted a qualitative research approach to define and interpret the ideas and experiences of the IT firms’ employees and to present them to the readers directly. For this purpose, they followed a single-case study design. They researched on a small and medium enterprise operating in the IT sector in Düzce province, Turkey. This paper used a semi-structured interview and document analysis as data collecting methods. In all, eight interviews were conducted with employees. Brochures and website of the organization were used as data sources for the document analysis.

Findings

As a result of in-depth interviews and document analysis, the authors formed five main themes that describe perception of big data and learning organization concepts, methods and practices adopted in transforming process, usage areas of big data in organization and how the sample organization uses big data as a learning organization. The findings of this paper show that the sample organization is a learning IT firm that has used big data in transforming to learning organization and in maintaining the learning culture.

Research limitations/implications

The findings contribute to literature as it is one of the first studies that examine the influence of big data on the transformation process of an IT firm to a learning organization. The findings reveal that IT firms benefit from the solutions of big data while learning. However, as the design of the research is single-case study, the findings may be specific to the sample organization. Future studies are required that examine the subject in different samples and by different research designs.

Originality/value

In literature, research on how IT firms’ managers and employees use big data in organizational learning process is limited. The authors expect that this paper will shed light on future research that examines the effect of big data on the learning process of the organization.
Maternal liver dysfunction in early pregnancy predisposes to gestational diabetes mellitus independent of preconception overweight: A prospective cohort study
Authors: Chen Xiaotian , Chen Hongyan , Zhang Yi , Jiang Yuan , Wang Yin , Huang Xiangyuan , Wang Dingmei , Li Mengru , Dou Yalan , Sun Xupeng , Huang Guoying , Yan Weili
Published: February 2022

Objective

To evaluate whether the associations of maternal liver dysfunction and liver function biomarkers (LFBs) with gestational diabetes mellitus (GDM) are independent of overweight.

Design

Prospective cohort study.

Methods

A sub‐cohort of pregnant women with seven LFBs examined at 9–13 weeks of gestation and with complete GDM evaluation at mid‐gestation were extracted from the prospective Shanghai Preconception Cohort Study. Associations of liver dysfunction, defined as having any elevated LFB levels, and individual LFB levels with GDM incidence were assessed by adjusting body mass index and other covariates in the multivariable logistic regression model. Odds ratios (ORs) and 95% CI were reported.

Main outcome measures

Incident GDM.

Results

Among 6211 pregnant women, 975 (15.7%) developed GDM. Liver dysfunction was associated with increased odds of GDM (OR 1.63; 95% CI 1.38–1.92). This association persisted after adjustment for BMI (adjusted OR [aOR] 1.37; 95% CI 1.15–1.63). Higher γ‐glutamyl transferase, alanine aminotransferase, alkaline phosphatase, and albumin levels were also linked with GDM (aOR per 1 SD: 1.15, 95% CI 1.08–1.23; 1.10, 1.03–1.17; 1.21, 1.13–1.29 and 1.19, 1.11–1.27, respectively). Similar magnitudes of associations were observed between normal weight and overweight pregnant women.

Conclusion

Maternal liver dysfunction in early pregnancy predisposes women to subsequent GDM, and this association is independent of being overweight preconception. Our findings of an increased risk even in normal‐weight pregnant women adds new mechanistic insights about the pathophysiological role of liver function in GDM aetiology.

Tweetable abstract

Maternal liver dysfunction in early pregnancy is associated with GDM incidence independent of preconception overweight.
Risk factors for RhD immunisation in a high coverage prevention programme of antenatal and postnatal RhIg: a nationwide cohort study
Authors: Slootweg Y. M. , Zwiers C. , Koelewijn J. M. , van der Schoot E. , Oepkes D. , van Kamp I. L. , de Haas M.
Published: February 2022

Objective

To evaluate which risk factors for RhD immunisation remain, despite adequate routine antenatal and postnatal RhIg prophylaxis (1000 IU RhIg) and additional administration of RhIg. The second objective was assessment of the current prevalence of RhD immunisations.

Design

Prospective cohort study.

Setting

The Netherlands.

Population

Two‐year nationwide cohort of alloimmunised RhD‐negative women.

Methods

RhD‐negative women in their first RhD immunised pregnancy were included for risk factor analysis. We compared risk factors for RhD immunisation, occurring either in the previous non‐immunised pregnancy or in the index pregnancy, with national population data derived from the Dutch perinatal registration (Perined).

Results

In the 2‐year cohort, data from 193 women were eligible for analysis. Significant risk factors in women previously experiencing a pregnancy of an RhD‐positive child (n = 113) were: caesarean section (CS) (OR 1.7, 95% CI 1.1–2.6), perinatal death (OR 3.5, 95% CI 1.1–10.9), gestational age >42 weeks (OR 6.1, 95% CI 2.2–16.6), postnatal bleeding (>1000 ml) (OR 2.0, 95% CI 1.1–3.6), manual removal of the placenta (MRP) (OR 4.3, 95% CI 2.0–9.3); these factors often occurred in combination. The miscarriage rate was significantly higher than in the Dutch population (35% versus 12.‐5%, P < 0.001).

Conclusion

Complicated deliveries, including cases of major bleeding and surgical interventions (CS, MRP), must be recognised as a risk factor, requiring estimation of fetomaternal haemorrhage volume and adjustment of RhIg dosing. The higher miscarriage rate suggests that existing RhIg protocols need adjustment or better compliance.

Tweetable abstract

Complicated delivery (caesarean section, manual removal placenta, major bleeding) is the most valid risk factor for RhD immunization despite antenatal and postnatal RhIg.
Predicting the progressive resistance and balance training response of community‐dwelling older adults accessing aged care support services: A stepped‐wedge randomised controlled trial
Authors: Keogh Justin W. L. , Henwood Tim , Hetherington Sharon , Gardiner Paul A. , Tuckett Anthony G. , Rouse Kevin , Swinton Paul
Published: February 2022

Objective

To quantify the variation in body composition, physical function and cognitive health changes resulting from the Muscling Up Against Disability (MUAD) resistance and balance training program and the potential for baseline characteristics to predict the magnitude of training‐related response.

Methods

The study represented a secondary analysis of a stepped‐wedge randomised controlled trial involving 245 community‐dwelling adults receiving Australian Government–funded aged care services who performed 26 weeks of supervised progressive resistance and balance training (PRBT). The primary outcome was the proportion of response that described the number of individuals expected to make any positive change due to the intervention and not external factors.

Results

For all outcomes, the observed average change in the PRBT group was more favourable than the control. Analyses identified that most participants completing the PRBT program would be expected to respond positively to the intervention (86%–99%) with respect to their physical performance (SPPB summary, grip strength, chair stand and isometric knee strength). A smaller proportion completing the PRBT program group would be expected to respond positively in aspects of body composition (45%–60%) or cognitive function (44%–84%). The strongest predictors of positive change were baseline physical function, whereby those with the poorest baseline function experienced the greatest benefits.

Conclusions

This study strongly supports the promotion of PRBT as a standard component of any care plan for community‐dwelling older adults, especially those with low levels of physical function.
Warfarin‐induced skin necrosis after the use of an anticoagulation reversal agent
Authors: Zhang Lois , Truong Kelvin , Chan Linda , Kim Jennifer , Fernandez‐Peñas Pablo
Published: February 2022

Anticoagulant‐induced skin necrosis is a rare and potentially life‐threatening complication of anticoagulant therapy. The majority of cases of anticoagulant‐induced skin necrosis have been attributed to warfarin, known as warfarin‐induced skin necrosis (WISN). The use of anticoagulation reversal agents such as Prothrombinex‐VF in the development of WISN is not a commonly documented phenomenon. The authors present a case of WISN post‐recommencement of warfarin and the use of Prothrombinex‐VF.
Regulatory focus theory: Disentangling goals and strategies
Authors: Vriend Tim , Hamstra Melvyn R. W. , Said Ramzi , Janssen Onne , Jordan Jennifer , Nijstad Bernard A.
Published: February 2022

The purpose of this research was to develop and test the Regulatory Goals and Strategies Questionnaire (RGSQ) to promote conceptual and empirical clarity in the literature on regulatory focus theory (RFT). According to RFT, construing an end‐state as a maximal goal (ideal, gain, and advancement) elicits the adoption of an eager promotion‐focused strategy, whereas construing an end‐state as a minimal goal (ought, non‐loss, and security) elicits the adoption of a vigilant prevention‐focused strategy. This means that promotion‐focused eagerness and prevention‐focused vigilance can be elicited by various goals and that eager and vigilant strategies are in fact separate from goals. However, extant measurement instruments have not treated them as such. The RGSQ was developed to distinguish various maximal and minimal goals and to separate these goals from promotion‐ and prevention‐focused strategies of eagerness and vigilance. Across three studies that combine six samples (total N = 1848), we examined the factor structure and nomological network of the RGSQ (Study 1: four samples of students and adults) and its predictive validity in a task context (Study 2) and working sample (Study 3). Overall, we found support for the RGSQ's validity and demonstrated that the RGSQ operationalizes regulatory focus in accordance with the theory's core assumptions.