bluuebunny/crossref_metadata_2025 huggingface dataset:
Mammals, birds and non-avian reptiles have signature proportions of numbers of neurons across their brain structures: Numbers of neurons increased differently with endothermy in birds and mammals
Authors: Herculano-Houzel Suzana
Published: June 2022

Modern mammals, birds, and non-avian reptiles have shared developmental and evolutionary origins in the ancestral amniotes of 300 million years ago. A previous analysis of a newly completed dataset on the cellular composition of the major parts of the brain of 242 amniote species, generated using the same cell counting method, the isotropic fractionator, argued for changes in the body-brain relationship in amniote evolution (Kverkova et al., 2022), but did not explore how the brains of amniotes diverged in their neuronal composition. Here I show, using the same dataset but focusing instead on the cellular composition of the brains regardless of body mass and phylogenetic relatedness, that the brains of extant mammalian, avian, and non-avian reptile species are characterized by signature proportions of numbers of neurons across the pallium, the cerebellum, and the rest of brain. An increase to a higher, fixed proportion of 4.5 neurons in the cerebellum to every neuron in the rest of brain, with variable numbers of pallial neurons, characterizes the avian brain compared to other reptiles, whereas mammalian brains are characterized by an average 4 neurons in the cerebellum to every neuron in the pallium regardless of numbers of neurons in the rest of brain, which also differs from the proportion in most non-avian reptilian brains of 1.4 neurons in the pallium and 0.5 neuron in the cerebellum to every neuron in the rest of brain. Thus, the independent evolution of endothermy in birds and mammals occurred with dramatic increases in numbers of neurons in all brain structures that differed markedly between birds and mammals. Additionally, there are marked continuities in the scaling of extant amniote brains that allow for the neuronal composition of the brain of ancestral amniotes to be estimated. Using these similarities in the neuronal scaling rules between living mammals and non-avian reptiles, I provide scaling relationships that allow predicting the composition of early mammaliaform and synapsid brains in amniote evolution, and I propose a simple model of amniote brain evolution that accounts for the diversity of modern mammalian, avian, and non-avian reptilian brains with only a few clade-shifting events in brain connectivity between cerebral cortex and cerebellum in mammals and between the cerebellum and rest of brain in birds, building on the increased availability of energy supply to the brain associated with the evolution of the increased oxidative and cardiovascular capacities that underlie endothermy.
A minimal-complexity light-sheet microscope maps network activity in 3D neuronal systems
Authors: Wysmolek Paulina M , Kiessler Filippo D , Salbaum Katja A , Shelton Elijah R , Sonntag Selina M , Serwane Friedhelm
Published: June 2022

In vitrosystems mimicking brain regions, brain organoids, are revolutionizing the neuroscience field. However, characterization of their electrical activity has remained a challenge as this requires readout at millisecond timescale in 3D at single-neuron resolution. While custom-built microscopes used with genetically encoded sensors are now opening this door, a full 3D characterization of organoid neural activity has not been performed yet, limited by the combined complexity of the optical and the biological system. Here, we introduce an accessible minimalistic light-sheet microscope to the neuroscience community. Designed as an add-on to a standard inverted microscope it can be assembled within one day. In contrast to existing simplistic setups, our platform is suited to record volumetric calcium traces. We successfully extracted 4D calcium traces at high temporal resolution by using a lightweight piezo stage to allow for 5Hz volumetric scanning combined with a processing pipeline for true 3D neuronal trace segmentation. As a proof of principle, we created a 3D connectivity map of a stem cell derived neuron spheroid by imaging its activity. Our fast, low complexity setup empowers researchers to study the formation of neuronal networksin vitrofor fundamental and neurodegeneration research.
E-Cigarette Synthetic Cooling Agent WS-23 and Nicotine Aerosols Differentially Modulate Airway Epithelial Cell Responses
Authors: Manevski Marko , Devadoss Dinesh , Yogeswaran Shaiesh , Rahman Irfan , Chand Hitendra S.
Published: June 2022

Electronic cigarette (e-cig) aerosol/vape exposures are strongly associated with pulmonary dysfunctions, and the airway epithelial cells (AECs) of respiratory passages play a pivotal role in understanding this association. However, not much is known about the effect of synthetic cooling agents such as WS-23 on AECs. WS-23 is a synthetic menthol-like cooling agent widely used to enhance the appeal of e-cigs and to suppress the harshness and bitterness of other e-cig constituents. Using primary human AECs, we compared the effects of aerosolized WS-23 with propylene glycol/vegetable glycerin (PG/VG) vehicle control and nicotine aerosol exposures. AECs treated with 3% WS-23 aerosols showed a significant increase in viable cell numbers compared to PG/VG-vehicle aerosol exposed cells and cell growth was comparable following 2.5% nicotine aerosol exposure. AEC inflammatory factors, IL-6 and ICAM-1 levels were significantly suppressed by WS-23 aerosols compared to PG/VG-controls. When differentiated AECs were challenged with WS-23 aerosols, there was a significant increase in MUC5AC+ goblet cells with no discernible change in SCGB1A1+ secretory cells. Compared to PG/VG-controls, WS-23 or nicotine aerosols presented with increased goblet cell numbers, but there was no synergistic effect of WS-23+nicotine combination exposure. Thus, WS-23 and nicotine aerosols modulate the AEC responses and induce goblet cell hyperplasia, which could impact the airway physiology and susceptibility to respiratory diseases.
The interaction between coping styles with relationship breakdowns, loss, and conflict and the frequency of self-harm thoughts and behaviours: a longitudinal analysis of 21,581 UK adults
Authors: Paul Elise , Fancourt Daisy
Published: June 2022

Background

Relationship breakdowns or conflict are frequent precipitants for self-harm thoughts and behaviours, but the majority who experience these stressful life events do not think about or engage in self-harm. Understanding factors that attenuate or exacerbate this risk is therefore needed. The aim of this paper is to investigate whether relationship breakdowns, loss, and conflict lead to more frequent self-harm thoughts and behaviours. We also examine whether coping styles and neuroticism, posited by diathesis-stress models of suicide risk to interact with these events, attenuate or exacerbate the risk for self-harm thoughts and behaviours from these events.

Methods

This study utilised data collected during the COVID-19 pandemic, which acted as a natural experiment by leading to a greater prevalence of relationship breakdowns than usual. Data from 21,581 adults who participated in the UCL COVID-19 Social Study between 28 February 2021 and 4 April 2022 were utilised. Poisson regression models which controlled for socio-demographics and a diagnosed mental health condition were used to examine the impact of four predictor variables (separation or divorce, family problem, an ‘other’ relationship breakdown [e.g., friend or colleague], and the death of a close relative or friend) with the number of times self-harm thoughts and behaviours were reported over the study period. Interactions between these events and coping styles (problem-focused, emotion-focused, socially supported, and avoidant coping) were also examined.

Results

Variables representing relationship breakdowns, loss, and conflict were associated with an increased frequency of self-harm thoughts (incidence rate ratio [RRR] range: 1.04 to 1.77) and behaviours (RRR range: 1.48 to 1.96). The use of more avoidant coping strategies (e.g., substance use, denial) increased the risk for both outcomes but unexpectedly attenuated associations between predictor variables and self-harm thoughts. Socially supported coping increased the likelihood of both outcomes, but not in sensitivity analyses which excluding ‘venting’ from the scale. Problem-focused coping strategies (e.g., active planning) attenuated the impact of separation or divorce and having had a family problem on the frequency of self-harm behaviours.

Conclusions

Findings underscore the importance of interpersonal loss and conflict for the frequency of thinking about and engaging in self-harm and suggest that the magnitude of these associations may depend on different coping styles.
VirPool: Model-Based Estimation of SARS-CoV-2 Variant Proportions in Wastewater Samples
Authors: Gafurov Askar , Baláž Andrej , Amman Fabian , Boršová Kristína , Čabanová Viktória , Klempa Boris , Bergthaler Andreas , Vinař Tomáš , Brejová Broňa
Published: June 2022

Background

The genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the delta variant B.1.617.2 or omicron variant B.1.1.529). Proportions of these variants in a population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample.

Results

We propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluated the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of alpha and delta variants.

Conclusions

VirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.

Availability

VirPool is an open source software available at https://github.com/fmfi-compbio/virpool.
Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy
Authors: Inkster Amy M. , Konwar Chaini , Peñaherrera Maria S. , Brain Ursula , Khan Almas , Price E. Magda , Schuetz Johanna M. , Portales-Casamar Élodie , Burt Amber , Marsit Carmen J. , Vaillancourt Cathy , Oberlander Tim F. , Robinson Wendy P.
Published: June 2022

Background

Selective serotonin reuptake inhibitors (SSRIs) for treatment of prenatal maternal depression have been associated with neonatal neurobehavioral disturbances, though the molecular mechanisms remain poorly understood.In uteroexposure to SSRIs may affect DNA methylation (DNAme) in the human placenta, an epigenetic mark that is established during development and is associated with gene expression.

Methods

Chorionic villus samples from 64 human placentas were profiled with the Illumina MethylationEPIC BeadChip; clinical assessments of maternal mood and SSRI treatment records were collected at multiple time points during pregnancy. Case distribution was 20 SSRI-exposed cases and 44 SSRI non-exposed cases. Maternal depression was defined using a mean maternal Hamilton Depression score >8 to indicate symptomatic depressed mood (“maternally-depressed”), and we further classified cases into SSRI-exposed, maternally-depressed (n=14); SSRI-exposed, not maternally-depressed (n=6); SSRI non-exposed, maternally-depressed (n=20); and SSRI non-exposed, not maternally-depressed (n=24). For replication, Illumina 450K DNAme profiles were obtained from 34 additional cases from an independent cohort (n=17 SSRI-exposed, n=17 SSRI non-exposed).

Results

No CpGs were differentially methylated at FDR < 0.05 comparing SSRI-exposed to non-exposed placentas, in a model adjusted for mean maternal Hamilton Depression score, or in a model restricted to maternally-depressed cases with and without SSRI exposure. However, at a relaxed threshold of FDR < 0.25, five CpGs were differentially methylated (|Δβ| > 0.03) by SSRI exposure status. Four were covered by the replication cohort measured by the 450K array, but none replicated. No CpGs were differentially methylated (FDR < 0.25) comparing maternally depressed to not depressed cases. In sex-stratified analyses for SSRI-exposed versus non-exposed cases (females n=31; males n=33), three additional CpGs in females, but none in males, were differentially methylated at the relaxed FDR < 0.25 cut-off.

Conclusions

We did not observe large-scale alterations of DNAme in placentas exposed to maternal SSRI treatment compared to placentas with no SSRI exposure. We also found no evidence for altered DNAme in maternal depression-exposed versus depression non-exposed placentas. This novel work in a prospectively-recruited cohort with clinician-ascertained SSRI exposure and mood assessments would benefit from future replication.
Fc-modified SARS-CoV-2 neutralizing antibodies with therapeutic effects in two animal models
Authors: Takeshita Masaru , Fukuyama Hidehiro , Kamada Katsuhiko , Matsumoto Takehisa , Makino-Okamura Chieko , Uchikubo-Kamo Tomomi , Tomabechi Yuri , Hanada Kazuharu , Moriyama Saya , Takahashi Yoshimasa , Ishigaki Hirohito , Nakayama Misako , Nguyen Cong Thanh , Kitagawa Yoshinori , Itoh Yasushi , Imai Masaki , Maemura Tadashi , Furusawa Yuri , Ueki Hiroshi , Iwatsuki-Horimoto Kiyoko , Ito Mutsumi , Yamayoshi Seiya , Kawaoka Yoshihiro , Shirouzu Mikako , Ishii Makoto , Saya Hideyuki , Kondo Yasushi , Kaneko Yuko , Suzuki Katsuya , Fukunaga Koichi , Takeuchi Tsutomu ,   the Keio Donner Project
Published: June 2022

The use of therapeutic neutralizing antibodies against SARS-CoV-2 infection has been highly effective. However, there remain few practical antibodies against viruses that are acquiring mutations. In this study, we created 494 monoclonal antibodies from COVID-19–convalescent patients, and identified antibodies that exhibited comparable neutralizing ability to clinically used antibodies in the neutralization assay using pseudovirus and authentic virus including variants of concerns. These antibodies have different profiles against various mutations, which were confirmed by cell-based assay and cryo-electron microscopy. To prevent antibody-dependent enhancement, N297A modification was introduced, and showed a reduction of lung viral RNAs by therapeutic administration in a hamster model. In addition, an antibody cocktail consisting of three antibodies was also administered therapeutically to a macaque model, which resulted in reduced viral titers of swabs and lungs and reduced lung tissue damage scores. These results showed that our antibodies have sufficient antiviral activity as therapeutic candidates.
Plant community stability is associated with a decoupling of prokaryote and fungal soil networks
Authors: in ‘t Zandt Dina , Kolaříková Zuzana , Cajthaml Tomáš , Münzbergová Zuzana
Published: June 2022

Soil microbial networks play a crucial role in plant community stability. However, we lack knowledge on the network topologies associated with stability and the pathways shaping these networks. In a 13-year mesocosm experiment, we determined links between plant community stability and soil microbial networks. We found that plant communities on soil abandoned from agricultural practices 60 years prior to the experiment promoted destabilising properties and were associated with coupled prokaryote and fungal soil networks. This coupling was mediated by strong interactions of plants and microbiota with soil resource cycling. Conversely, plant communities on natural grassland soil exhibited a high stability, which was associated with decoupled prokaryote and fungal soil networks. This decoupling was mediated by a large variety of past plant community pathways shaping especially fungal networks. We conclude that plant community stability is associated with a decoupling of prokaryote and fungal soil networks and mediated by plant-soil interactions.
Structural polymorphism of amyloid fibrils in cardiac transthyretin amyloidosis revealed by cryo-electron microscopy
Authors: Nguyen Binh An , Afrin Shumaila , Singh Virender , Ahmed Yasmin , Pedretti Rose , del Carmen Fernandez-Ramirez Maria , Benson Merrill Douglas , Sawaya Michael , Singh Preeti , Cao Qin , Boyer David , Pope Alexander , Wydorski Pawel , Kumar Siddharth , Chhapra Farzeen , Eisenberg David , Saelices Lorena
Published: June 2022

The deposition of amyloidogenic transthyretin (ATTR) in ATTR amyloidosis leads to an unexplained variety of clinical phenotypes, including cardiomyopathy. In brain amyloid conditions, there is an apparent association between the clinical phenotype and the amyloid fibril structure. Here, we question this phenotype-structure association in cardiac amyloidoses by determining the cryo-electron microscopy structures of fibrils extracted from the hearts of seven ATTR amyloidosis patients. We found that, in contrast to brain fibrils, cardiac ATTR fibrils display a structural polymorphism that is not genotype-specific, can co-exist within the same individual, and is independent of the cardiac phenotype. This polymorphism challenges the current paradigm of “one disease equals one fibril fold” proposed in tauopathies and synucleinopathies, and questions whether a similar structural heterogeneity occurs in other amyloidoses.

One-Sentence Summary

Unlike brain amyloid fibrils, cardiac ATTR fibrils are polymorphic independent of genotype and even within the same patient.
Microbial community dynamics during a harmful Chrysochromulina leadbeateri bloom in northern Norway
Authors: Aalto Nerea J. , Schweitzer Hannah , Grann-Meyer Erlend , Krsmanovic Stina , Svenning Jon B. , Dalheim Lars , Petters Sebastian , Ingebrigtsen Richard , Hulatt Chris J. , Bernstein Hans C.
Published: June 2022

A harmful algae bloom occurred in late spring 2019 across multiple, interconnected fjords and bays in northern Norway. The event was caused by the haptophyte Chrysochromulina leadbeateri and led to severe fish mortality at several salmon aquaculture facilities. This study reports on the spatial and temporal succession dynamics of the holistic marine microbiome associated with this bloom by relating all detectable 18S and 16S rRNA gene ASVs to the relative abundance of the C. leadbeateri focal taxon. A k-medoids clustering enabled inferences on how the causative focal taxon co-bloomed with diverse groups of bacteria and microeukaryotes. These co-blooming patterns showed high temporal variability and were distinct between two geographically separated time series stations during the regional harmful algae bloom. The distinct blooming patterns observed with respect to each station were poorly connected to environmental conditions suggesting that other factors, such as biological interactions, may be at least as important in shaping the dynamics of this type of harmful algae bloom. A deeper understanding of microbiome succession patterns during these rare but destructive events will help guide future efforts to forecast deviations from the natural bloom cycles of the northern Norwegian coastal marine ecosystems that are home to intensive aquaculture activities.
MuDoGeR: Multi-Domain Genome Recovery from metagenomes made easy
Authors: Nunes da Rocha Ulisses , Kasmanas Jonas Coelho , Kallies René , Saraiva Joao Pedro , Brizola Toscan Rodolfo , Štefanič Polonca , Bicalho Marcos Fleming , Correa Felipe Borim , Baştürk Merve Nida , Fousekis Efthymios , Barbosa Luiz Miguel Viana , Plewka Julia , Probst Alexander , Baldrian Petr , Stadler Peter ,   CLUE-TERRA consortium
Published: June 2022

Several frameworks that recover genomes from Prokaryotes, Eukaryotes, and viruses from metagenomes exist. For those with little bioinformatics experience, it is difficult to evaluate quality, annotate genes, dereplicate, assign taxonomy and calculate relative abundance and coverage from genomes belonging to different domains. MuDoGeR is a user-friendly tool accessible for non-bioinformaticians that make genome recovery from metagenomes of Prokaryotes, Eukaryotes, and viruses alone or in combination easy. By testing MuDoGeR using 574 metagenomes and 24 genomes, we demonstrated users could run it in a few samples or high-throughput. MuDoGeR is an open-source software available at https://github.com/mdsufz/MuDoGeR.
Designing β-hairpin peptide macrocycles for antibiotic potential
Authors: Randall Justin R. , DuPai Cory D. , Cole T. Jeffrey , Davidson Gillian , Groover Kyra E. , Wilke Claus O. , Davies Bryan W.
Published: June 2022

Peptide macrocycles are a rapidly emerging new class of therapeutic, yet the design of their structure and activity remains challenging. This is especially true for those with β-hairpin structure due to weak folding properties and a propensity for aggregation. Here we use proteomic analysis and common antimicrobial features to design a large peptide library with macrocyclic β-hairpin structure. Using an activity-driven high-throughput screen we identify dozens of peptides killing bacteria through selective membrane disruption and analyze their biochemical features via machine learning. Active peptides contain a unique constrained structure and are highly enriched for cationic charge with arginine in their turn region. Our results provide a synthetic strategy for structured macrocyclic peptide design and discovery, while also elucidating characteristics important for β-hairpin antimicrobial peptide activity.

Brief Summary

We design, screen, and computationally analyze a synthetic macrocyclic β-hairpin peptide library for antibiotic potential.
Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection
Authors: Farjo Mireille , Koelle Katia , Martin Michael A. , Gibson Laura L. , Walden Kimberly K.O. , Rendon Gloria , Fields Christopher J. , Alnaji Fadi G. , Gallagher Nicholas , Luo Chun Huai , Mostafa Heba H. , Manabe Yukari C. , Pekosz Andrew , Smith Rebecca L. , McManus David D. , Brooke Christopher B.
Published: June 2022

The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we deep sequenced saliva and nasal samples collected daily from immune and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both naïve and immune individuals appeared largely stochastic; however, we identified clear mutational hotspots within the viral genome, consistent with selection and differing between naïve and immune individuals. In rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of virus between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.
Increased levels of circulating neurotoxic metabolites in patients with mild Covid19
Authors: Santiago-Mujika Estibaliz , Heinrich Kevin , George Sonia , Capan Colt D , Forton Cameron , Madaj Zachary , Burmeister Amanda R , Sims Matthew , Pospisilik J Andrew , Brundin Patrik , Graham Stewart F , Brundin Lena
Published: June 2022

SARS-CoV-2 corona virus causes a multi-faceted and poorly defined clinical and pathological phenotype involving hyperinflammation, cytokine release, and long-term cognitive deficits, with an undefined neuropathological mechanism. Inflammation increases the activity of the kynurenine pathway, which is linked to neurodegenerative and psychiatric disorders. We sought to determine whether the kynurenine pathway is impacted in patients with mild COVID-19, leading to elevated neurotoxic metabolites in blood, and whether such changes are associated with pro-inflammatory cytokines. Serum samples were taken from 150 patients and analyzed by ELISA and ultra-high performance liquid chromatography (UHPLC). The data were analyzed using multiple linear regression models adjusted for age and sex. We found increased levels of kynurenine, quinolinic acid and 3-hydroxykynurenine in serum from patients with mild COVID-19, together with increased levels of IL-6, ICAM-1, VCAM-1 and neopterin. The levels of neurotoxic metabolites were significantly associated with key inflammatory cytokines including IL-6 and TNFα. The COVID-19 risk-factor hypertension was associated with the highest levels of neurotoxic metabolites in plasma. These neuroactive metabolites could be part of the pathological mechanisms underlying cognitive impairment during and post-COVID and should be explored as potential biomarkers for long-COVID symptoms.
Incidental discovery of acute myeloid leukemia during liquid biopsy of a lung cancer patient
Authors: Nkosi Dingani , Miller Caroline A. , Jajosky Audrey N. , Oltvai Zoltán N.
Published: June 2022

Liquid biopsy is considered an alternative to standard next-generation sequencing (NGS) of solid tumor samples when biopsy tissue is inadequate for testing or when testing of a peripheral blood sample is preferred. A common assumption of liquid biopsies is that the NGS data obtained on circulating cell-free DNA is a high-fidelity reflection of what would be found by solid tumor testing. Here, we describe a case that challenges this widely held assumption. A patient diagnosed with lung carcinoma showed pathogenic IDH1 and TP53 mutations by liquid biopsy NGS at an outside laboratory. Subsequent in-house NGS of a metastatic lymph node fine-needle aspiration (FNA) sample revealed two pathogenic EGFR mutations. Morphologic and immunophenotypic assessment of the patient's blood sample identified acute myeloid leukemia, with in-house NGS confirming and identifying pathogenic IDH1, TP53, and BCOR mutations, respectively. This case, together with a few similar reports, demonstrates that caution is needed when interpreting liquid biopsy NGS results, especially if they are inconsistent with the presumptive diagnosis. Our case suggests that routine parallel sequencing of peripheral white blood cells would substantially increase the fidelity of the obtained liquid biopsy results.
A de novo start-loss in EFTUD2 associated with mandibulofacial dysostosis with microcephaly: case report
Authors: Kohailan Muhammad , Al-Saei Omayma , Padmajeya Sujitha , Aamer Waleed , Elbashir Najwa , Al-Shabeeb Akil Ammira , Kamboh Abdul-Rauf , Fakhro Khalid
Published: June 2022

Mandibulofacial dysostosis with microcephaly (MFDM) is a rare genetic disorder inherited in an autosomal dominant pattern. Major characteristics include developmental delay, craniofacial malformations such as malar and mandibular hypoplasia, and ear anomalies. Here, we report a 4.5-yr-old female patient with symptoms fitting MFDM. Using whole-genome sequencing, we identified a de novo start-codon loss (c.3G > T) in the EFTUD2. We examined EFTUD2 expression in the patient by RNA sequencing and observed a notable functional consequence of the variant on gene expression in the patient. We identified a novel variant for the development of MFDM in humans. To the best of our knowledge, this is the first report of a start-codon loss in EFTUD2 associated with MFDM.
Does excessive degrees of financial depth push hyper-inflation?
Authors: Subramaniam Yogeeswari , Masron Tajul Ariffin
Published: June 2022

Purpose

Using an innovative threshold estimation technique, this paper provides new evidence on the relationship between finance and inflation with distinct levels of finance.

Design/methodology/approach

The sample consisted of 10 high inflation countries using time series data for the period of 1992–2020. These 10 countries recorded the world's highest inflation rates in 2017.

Findings

The findings demonstrate that there is a threshold effect on the finance–inflation relationship. Whilst the effects of finance are consistently positive for below and above the threshold models, financial depth above the threshold tends to aggravate the inflation level.

Practical implications

These results disclose that financial depth could be the cause of high inflation in the top 10 countries and thus, is not necessarily welcome as too rapid of a price increase may in turn reverse the prospect of economic growth. Searching and strategizing for the optimal level of financing is crucial in facilitating price stability and economic growth.

Originality/value

The authors believe that the effect of financial depth on inflation is characterised by being desirable to certain extent and undesirable if over-financing is beyond the optimum level. Therefore, in this study, the authors have introduced the threshold modelling as the potential strategy to connect financial depth and inflation.
Prediction of construction accident outcomes based on an imbalanced dataset through integrated resampling techniques and machine learning methods
Authors: Koc Kerim , Ekmekcioğlu Ömer , Gurgun Asli Pelin
Published: June 2022

Purpose

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Design/methodology/approach

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

Findings

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

Practical implications

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Social implications

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

Originality/value

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.
COVID-19 and the reimaging of compassionate release
Authors: James Jennifer E. , Foe Meghan , Desai Riya , Rangan Apoorva , Price Mary
Published: June 2022

Purpose

The purpose of this paper is to provide a historical overview of compassionate release policies in the USA and describe how these policies have been used during the COVID-19 pandemic. The authors then describe how these programs have been shaped by COVID-19 and could be reimagined to address the structural conditions that make prisons potentially life limiting for older adults and those with chronic illness.

Design/methodology/approach

This paper is primarily descriptive, offering an overview of the history of compassionate release policies before and during the COVID-19 pandemic. The authors augmented this description by surveying state Departments of Corrections about their utilization of compassionate release during 2019 and 2020. The findings from this survey were combined with data collected via Freedom of Information Act Requests sent to state Departments of Corrections about the same topic.

Findings

The findings demonstrate that while the US federal prison system saw a multifold increase in the number of individuals released under compassionate release policies in 2020 compared to 2019, most US states had modest change, with many states maintaining the same number, or even fewer, releases in 2020 compared with 2019.

Originality/value

This paper provides both new data and new insight into compassionate release utilization during the COVID-19 pandemic and offers new possibilities for how compassionate release might be considered in the future.
Assessing challenges to the mobile wallet usage in India: an interpretive structural modelling approach
Authors: Rana Nripendra P. , Luthra Sunil , Rao H. Raghav
Published: June 2022

Purpose

Mobile-based payment is increasing exponentially but in the developing country like India, consumers’ perception is highly positive in daily cash transaction. The purpose of this research is to identify and examine the important challenges for mobile wallet (m-wallet) implementation in India. In the wake of COVID-19, one of the transmission mechanisms of this virus has been the coins and paper money passed between a buyer and a seller. As such m-wallet considered as a convenience of payment has become a necessity in light of the pandemic.

Design/methodology/approach

The authors explored 19 unique sets of challenges selected from the literature and collected data from 14 experts from private sector, multinational corporations and mixed private and public partnership who have significant knowledge and experience of mobile payment implementation and use in their respective organisations. Also, the authors have used Interpretive Structural Modelling (ISM) methodology in developing a hierarchal model for the identified challenges. The authors implemented Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis to classify the identified challenges.

Findings

The ISM-based framework is divided into nine different hierarchical levels. “Lack of strong regulatory compliance (Ch6)” has been recognised as the most important challenge, which inhibited the mobile wallet implementation, whereas “Perception of customers about the value of using mobile wallets (Ch11)” is the most dependent critical challenge. There are seven hierarchical layers in between the top and the bottom level with the varied number of challenges based on their driving and dependence power.

Originality/value

This is the first research to the best of our knowledge that has not only comprehensively reviewed the m-wallet literature but also employed a unique ISM-MICMAC-based approach to develop a framework of challenges for the m-wallet implementation.
New South Wales drug courts: once a novelty – today, its business as usual
Authors: Clarke Amanda Ann
Published: June 2022

Purpose

The purpose of this research is to considers the degree to which drug courts (DCs) in New South Wales (NSW) adhere to the ten key components (TKCs), which were developed by the National Association of Drug Court Professionals, as a model practice for implementing DCs.

Design/methodology/approach

This study relied upon semi-structured interviews conducted with 21 professionals who work in the DC field from NSW. The sample represented various stakeholders responsible for the delivery of drug court programs (DCPs) in NSW. A qualitative analysis was conducted, this analysis uncovered practices adopted by the DC that go beyond those that were standardised in the closed-ended questions but nevertheless fell within the TKCs. The qualitative analyses added weight to the results determined by the descriptive statistics.

Findings

The results confirm that DCs in NSW adhere to the TKCs that describe successful DCPs internationally. In spite of this, several key components accomplished higher adherence rates than others. What can be said is that over 60% of the component’s benchmarks achieved the 80% target determined by the writer.

Research limitations/implications

The key components that have lower adherence rates are anticipated and must not be interpreted as undesirable results. DCs are encouraged to modify their programme characteristics to ensure further adherence to the specified benchmarks. To this extent, high regard is given to the practices adopted and identified through the qualitative data analysis.

Practical implications

The recommendations made to DCs in NSW are consistent with implementing model DCPs as defined by the National Association of Drug Court Professionals in 1997.

Originality/value

The TKCs are fundamentally standards for implementation and open an opportunity for discussion and are open for opportunity and examination. In theory and practice, each DC may interpret and implement the TKCs differently. In this regard, there is value in gaining an appreciation of pw DCs are interpreting the TKCs and applying them. It is business as usual at DCs; however, this research has demonstrated that there is no lack of innovation when it comes to DC in NSW implementing the TKCs.
Post-COVID-19 strategic sourcing decisions for escorting stakeholders’ expectations and supplier performance in construction project works
Authors: Sahu Atul Kumar , M. Prabhu , Rao K.T. Vigneswara
Published: June 2022

Purpose

The occurrence of COVID-19 has impacted the wide-reaching dimensions of manufacturing, materials, procurement, management, etc., and has loaded disruptions in the wide range of supply chain (SC) activities. The impact of COVID-19 has twisted supplier performance and influenced stakeholders’ thinking towards selecting supplier sources and making strategic sourcing decision for convinced arrangement of construction management (CM) resources. Nowadays, suppliers are intently evaluated by stakeholders in post-COVID-19 phase to induce agile availability of CM resources. Accordingly, this paper aims to demonstrate competent CM dimensions under post COVID-19 scenario for ease managing construction projects by the stakeholders.

Design/methodology/approach

The authors have implicated Grey Sets Theory along with decision-making trial and evaluation laboratory (DEMATEL) technique for understanding significant outcomes. Varieties of diverse decision aspects responsible for strategically influencing supplier sourcing decision is projected under post COVID-19 scenario for handling construction projects by the stakeholders.

Findings

This study investigated sustainable construction management dimensions (SCMD) at the stage of resource deliveries and client aspirations under post COVID-19 situation. The study demonstrated “Lead time” as the most crucial, “Product Range” as the second and “Customers dealings and relationship” as the third crucial aspect considering by the stakeholders for selecting supplier sources based on the attainment of performance score of 0.1338, 0.1273 and 0.1268, respectively. It is found that high lead time stimulates the stakeholders to divert their orders to other competent supplier sources holding a low degree of lead time as compared.

Research limitations/implications

The present study rollovers its existence by serving critical thinking, conceptual modelling, criteria identification and evaluation under CM domain for drafting effectual strategies by the suppliers. The study investigated the impact of COVID-19 on stakeholders’ decision-making and enlisted SCMD that strategically stimulated them in choosing supplier sourcing decision.

Originality/value

The present study realizes the insights of stakeholders in the post COVID-19 scenario related to the supplier sources based on performance score. The study quantified sustainable supplier attribute for construction work and practices. The study analysed the expectations of the stakeholders purchasing different varieties of construction materials from supplier sources for civil works in the post COVID-19 scenario.
Equitable post-disaster relief distribution: a robust multi-objective multi-stage optimization approach
Authors: Soghrati Ghasbeh Sogand , Pourmohammadzia Nadia , Rabbani Masoud
Published: June 2022

Purpose

This paper aims to address a location-distribution-routing problem for distributing relief commodities during a disaster under uncertainty by creating a multi-stage model that can consider information updates during the disaster. This model aims to create a relief network that chooses distribution centers with the highest value while maximizing equity and minimizing response time.

Design/methodology/approach

A hybrid algorithm of adaptive large neighborhood search (ALNS) and multi-dimensional local search (MDLS) is introduced to solve the problem. Its results are compared to ALNS and an augmented epsilon constraint (AUGMECON) method.

Findings

The results show that the hybrid algorithm can obtain high-quality solutions within reasonable computation time compared to the exact solution. However, while it yields better solutions compared to ALNS, the solution is obtained in a little longer amount of time.

Research limitations/implications

In this paper, the uncertain nature of some key features of the relief operations problem is not discussed. Moreover, some assumptions assumed to simplify the proposed model should be verified in future studies.

Practical implications

In order to verify the effectiveness of the designed model, a case study of the Sarpol Zahab earthquake in 2017 is illustrated and based on the results and the sensitivity analyses, some managerial insights are listed to help disaster managers make better decisions during disasters.

Originality/value

A novel robust multi-stage linear programming model is designed to address the location-distribution-routing problem during a disaster and to solve this model an efficient hybrid meta-heuristic model is developed.
Pricing strategies for online hotel searching: a fuzzy inference system procedure
Authors: Ahmadi Seyedeh Asra , Ghasemi Peiman
Published: June 2022

Purpose

Hotels are considered one of the keys to tourism industry, without which it is impossible to visualize this industry. Setting the proper price for hotels has always been a nuisance for the decision makers because of its direct relationship with the demand for hotels. Thus, in the current study a Stackelberg game between the government (leader) and the hotels (follower) has been presented to determine the optimal price under competitive conditions. The selected hotels are different with respect to energy consumption and the environmental impact. Thus, the government makes efforts to control their prices with incentives and tariffs.

Design/methodology/approach

The fuzzy inference system (FIS) has also been applied to forecast the hotel demand. Therefore, first off, the demand forecast criteria have been chosen by the experts and in the continuation, it has been screened by fuzzy Delphi approach. Finally, the quantity of hotel demand is computed by the Mamdani inference system. A mathematical model has been presented for determining the optimal sequencing of hotels and minimizing the searches to find a hotel.

Findings

A case study based on the data extracted from online travel agencies (OTAs) has been presented to validate the proposed model. The results demonstrate that by the ranking position increase, the number of the tourists decreases and the higher the star number of a hotel, the lower its ranking position.

Originality/value

Considering the energy saving and environmental impacts in hotel pricing and considering the government's intervention in hotel revenues regarding the incentives and tariffs are the innovations of the present study.
Unravelling the relationship between trust in government and voluntary adoption of preventative behaviour through health belief model: a cross-culture study
Authors: Sarwar Farhan , Imam Hassan , Jameel Hafiz Tahir , Panatik Siti Aisyah , Brannen Donald E.
Published: June 2022

Purpose

Despite the established relationship between the public's trust in government and their adoption of preventive behaviour, lesser is known about the underlying mechanism that explains trust in government—preventive behaviour nexus. This study adopted the health belief model to propose five types of health perceptions as a mediator between trust in government and the public's voluntary adoption of recommended preventions for COVID-19.

Design/methodology/approach

To collect primary quantitative data, a web survey was conducted using snowball sampling from Malaysia (N = 343) and Pakistan (N = 321). Measures were adopted from the existing studies. Structural equation modelling-partial least square through SmartPLS was used to analyse the proposed framework and hypotheses testing.

Findings

Results revealed that trust is a significant predictor of perceived barriers, benefits and self-efficacy in both countries. Mediation analysis indicated that perceived benefits and self-efficacy to be mediators in both samples. In the Pakistani sample, perceived barriers were also a mediator. Importance-performance analysis showed that the Malaysian public has a greater trust in their government to tackle the pandemic issue, while the trust was a relatively more important predictor of voluntary precautionary behaviour in Pakistan. A full mediation model depicted that coping health belief are an imperative link between trust and prevention.

Originality/value

Although developing the public's trust is related to good governance and public opinion, during a health crisis, authorities can effectively utilize the communication media and design interventions to influence health appraisals leading to higher adoption of prevention.
Evaluating Facebook as aids for learning Japanese: learners' perspectives
Authors: Leung Tin Nok , Hui Yin Ming , Luk Canon K.L. , Chiu Dickson K.W. , Ho Kevin K.W.
Published: June 2022

Purpose

This study analyses the advantages and weaknesses of using Facebook to aid the learning of Japanese as a foreign language.

Design/methodology/approach

A questionnaire survey was conducted to collect data from 100 Hong Kong Japanese language learners (who are generally fluent in Chinese and English), ranging from total amateur to advanced learners (Japanese Language Proficiency Test (JLPT) qualified at different levels).

Findings

The authors' results suggest that the advantages of using Facebook to help learn Japanese include: (1) serving as a free-of-charge, casual, and convenient learning platform; (2) enriching learners' knowledge beyond the language learning and (3) encouraging interactive and collaborative learning with other users for practicing the language. However, the low credibility and unstructured educational materials posted on Facebook and being easily distracted by other Facebook feeds are the major weaknesses of learning a language through Facebook. Furthermore, the authors' result shows that Facebook is especially effective for Japanese learning when learners fall into either one of the following groups: young, female, or intermediate (N2/3) learners.

Originality/value

Scant studies focus on the aid of learning Japanese via Facebook, especially Hong Kong learners' perceptions, or generally in the East. Therefore, this study aims to fill this research gap. The authors' findings will facilitate the students, teachers, and language institutions from Hong Kong and other countries to improve the students' effectiveness in learning and teaching Japanese.