bluuebunny/crossref_metadata_2025 huggingface dataset:
Selection efficacy differs between lifestages in the haploid-diploidMarchantia polymorphasubsp.ruderalis
Authors: Shen Tianyu , Gadient Philippe , Goodrich Justin , Becher Hannes
Published: September 2024

Ploidy has profound effects on evolution. Perhaps the most compelling effect is related to dominance: In cells with more than one genome copy, the effects of non-dominant deleterious variants are ‘masked’ to some extent, leading to a reduction in the efficacy of selection. This, in turn, leads to increased levels of nucleotide diversity, and it may also affect nucleotide substitution rates.

To test this predicted association between ploidy and the efficacy of selection, we studied genome scale per-gene patterns of genetic diversity and divergence in the genome of the haploid-diploid bryophyte Marchantia. We treated lifestage gene expression bias as a continuous covariate and accounted for genomic autocorrelation patterns using smoothing splines in a general additive regression model (GAM) framework.

Consistent with a lower efficacy of purifying selection, we found increased levels of sequence diversity, Watterson’sθ, and net divergence at non-degenerate sites in genes with diploid-biased gene expression. These genes also showed reduced levels of codon usage bias. In addition, we found chromosome 5 to be an outlier with overall decreased levels of diversity, the site-frequency spectrum skewed towards common alleles, and increased linkage disequilibrium.

In this study, we show the utility of generalized additive models in population genomics, and we present evidence for a ploidy associated difference in the efficacy of selection. We discuss parallels to the evolution of (diploid) sex chromosomes and why the patterns observed are unlikely to be mediated by masking.
ATP Regeneration from Pyruvate in the PURE System
Authors: Yadav Surendra , Perkins Alexander J. P. , Liyanagedera Sahan B. W. , Bougas Anthony , Laohakunakorn Nadanai
Published: September 2024

The ‘Protein synthesis Using Recombinant Elements’ (‘PURE’) system is a minimal biochemical system capable of carrying out cell-free protein synthesis using defined enzymatic components. This study extends PURE by integrating an ATP regeneration system based on pyruvate oxidase, acetate kinase, and catalase. The new pathway generates acetyl phosphate from pyruvate, phosphate, and oxygen, which is used to rephosphorylate ATP in situ. Successful ATP regeneration requires a high initial concentration of∼10 mM phosphate buffer, which surprisingly does not affect the protein synthesis activity of PURE. The pathway can function independently or in combination with the existing creatine-based system in PURE; the combined system produces up to 233µg/ml of mCherry, an enhancement of 78% compared to using the creatine system alone. The results are reproducible across multiple batches of homemade PURE, and importantly also generalise to commercial systems such as PURExpress®from New England Biolabs. These results demonstrate a rational bottom-up approach to engineering PURE, paving the way for applications in cell-free synthetic biology and synthetic cell construction.
Development of a machine-learning model for therapeutic efficacy prediction of preoperative treatment for esophageal cancer using single nucleotide variants of autophagy-related genes
Authors: Miyawaki Yutaka , Hirasaki Masataka , Kamakura Yasuo , Kawasaki Tomonori , Baba Yasutaka , Sato Tetsuya , Yamasaki Satoshi , Fukushima Hisayo , Uranishi Kousuke , Makino Yoshinori , Sato Hiroshi , Hamaguchi Tetsuya
Published: September 2024

Neoadjuvant chemotherapy with cisplatin + 5-fluorouracil followed by radical surgery is the standard treatment for stage II and III esophageal cancers. Although, a more potent regimen comprising cisplatin + 5-fluorouracil with docetaxel, has shown superiority in overall survival compared to the cisplatin + 5-fluorouracil regimen, it involves worsening of Grade 3 or higher adverse events due to docetaxel. Based on these reports, this study aimed to construct a prognostic system for cisplatin + 5-fluorouracil regimens, particularly for locally advanced cancers, to guide selection of neoadjuvant chemotherapy. Biopsy specimens from 82 patients who underwent a cisplatin + 5-fluorouracil regimen plus radical surgery at Saitama Medical University International Medical Center between May 2012 and June 2020 were analyzed. Variants in 56 autophagy- and esophageal cancer-related genes were identified using targeted enrichment sequencing. Overall, 13 single nucleotide variants, including eight non-synonymous group single nucleotide variants predicting recurrence were identified using Fisher’s exact test with recurrence as a two-group event, which showed a significant difference (p < 0.05). Additionally, machine learning was used to predict recurrence using 21 features, including eight patient backgrounds. The results showed that the Naive Bayes was highly reliable with an accuracy of 0.88 and Area Under the Curve of 0.9. Thus, we constructed a machine learning model to predict recurrence in patients with esophageal cancer treated with a cisplatin + 5-fluorouracil regimen. We believe that our results will provide useful guidance for the selection of neoadjuvant adjuvant chemotherapy, including the avoidance of docetaxel.
AlteredArabidopsis thalianasugar metabolism affects exudation, immune responses, and plant-microbe interactions
Authors: Siffert Alexandra , Sasse Joëlle
Published: September 2024

Sugars are critical for plant growth, development, and environmental interactions. They have multiple roles as nutrients for plants, associated beneficial and pathogenic microbes, and as signaling compounds for immunity. We characterize the interconnectedness of these functions by analyzing sugar metabolism and transporter mutant lines. We find that in these lines, root-derived compounds, exudates, are significantly altered in comparison with wild-type not only for carbohydrates, but also for lipids, organic acids, and defense compounds. Quantification of sugar exudation reveals more carbon release during the day than at night, altered sugar exudation in mutant lines, and an opposite exudation pattern with elevated exudation at night forpgm1, a line deficient in starch synthesis. Sugar levels in exudates and tissues did not correlate, suggesting a controlled mode of exudation for sugars. Altered sugar levels have functional consequences: mutant lines exhibit increased resistance against the pathogenPseudomonas syringaeand harbor altered numbers of microbes on roots. Day- and nighttime exudates of mutant lines impact the growth of single microbes such as an inability to grow forBacillus subtilis. Exogenous sugar alters the production of reactive oxygen species in a plant development-dependent manner with opposite effects at 9 days and 14 days. An RNAseq experiment reveals candidate genes potentially involved in this regulation. Our data highlight that sugar metabolism is intricately linked with other metabolite pathways. Alteration of single genes in central carbon metabolism profoundly alters plant immune responses and plant-microbe interactions.
CUP-SHAPED COTYLEDON2 activatesMIR319Ctranscription and promotes cell proliferation in Arabidopsis leaf primordia
Authors: Shankar Naveen , Gupta Abhishek , Roy Somsree , Mane Vishwadeep , Hamant Olivier , Nath Utpal
Published: September 2024

The microRNA miR319 regulates leaf shape and size in diverse plant species by reducing the level of the target transcripts that encode JAW-TCP proteins, the transcription factors (TF) which commit the proliferating pavement cells to differentiation. Expression ofMIR319C, one of the three miR319-producing genes in Arabidopsis, is expressed throughout the incipient leaf primordia, and the expression domain gets restricted to the base at later stages, partly due to the direct action of JAW-TCPs. However, the factors that activate and maintainMIR319Cexpression in leaf primordia are yet unknown. Here, we report the CUP-SHAPED COTYLEDON2 (CUC2) transcription factor as a direct activator ofMIR319Ctranscription. In a yeast one-hybrid (Y1H) screen, we identified several NAC domain TFs as potential regulators ofMIR319C. Subsequent ex vivo binding and transactivation assays suggested that CUC2 may bind to distal promoter region ofMIR319C. Mutants with compromisedCUC2andMIR319Cactivities exhibited smaller leaf areas and reduced pavement cell numbers due to early cell proliferation-to-differentiation transition. Morphometric analysis of higher orderCUC2andMIR319loss-of-function mutants highlighted the crucial role of theCUC2-MIR319module in promoting leaf cell proliferation and indicated functional redundancy among the threeMIR319genes in regulating JAW-TCP levels during leaf growth. Additionally, the phenotypes of mutants with alteredCUC2andMIR319/JAW-TCPactivities demonstrated thatCUC2enhances leaf size through theMIR319C-JAW-TCPpathway. Overall, our findings uncovered a novel role for CUC2 in promoting cell proliferation by activatingMIR319Ctranscription in the leaf primordia.
GENETIC DIVERSITY OFT. B. RHODESIENSESERUM RESISTANCE ASSOCIATED GENE IN MALAWIAN ISOLATES
Authors: Nambala Peter , Claucus Calorine , Noyes Harry , MacLeod Annette , Namulondo Joyce , Nyangiri Oscar , Musaya Janelisa , Matovu Enock , Alibu Pius Vincent , Nerima Barbara , Chammudzi Priscilla , Mulindwa Julius
Published: September 2024

Background

Human African Trypanosomiasis (HAT) is a health burden in most remote areas of Sub-Saharan Africa. Only 2 species of the Trypanosome parasites, namely,T. b. rhodesienseandT. b. gambiensecan establish infection in humans whereas other trypanosome parasites are lysed by human serum APOL-1 protein. The mechanism ofT. b. gambienseresistance to APOL-1 activity is complex and involves several parasite factors. On the other hand,T. b. rhodesienseevades the lytic activity of APOL-1 by intracellular expression of aSerum Resistance Associated(SRA) gene that binds to APOL-1 when uptaken by the parasite thereby disabling APOL-1 from causing cellular membrane rupture. APOL-1 has 2 variants, namely, APOL-1 G1 and APOL-1 G2 with the later having mutations on the SRA binding sites which restores APOL-1 lytic activity in parasite lysis assays. This phenomenon remains elusive in clinical setting as limited data is available. In the present study we investigated the genetic diversity ofT. b. rhodesienseSRA gene and APOL-1 genotypes in Malawian r-HAT clinical phenotypes.

Methods

T. b. rhodesienseSRA gene from Malawi endemic HAT samples (n= 77) as well as from Zambia and Uganda (n= 13) was amplified by PCR and PCR products were commercially sequenced. APOL-1 variants were identified by restriction fragment length polymorphism (RFLP) after a PCR amplification (n= 61).

Results and conclusion

Sequencing data revealed a heterozygosity of the SRA gene within MalawiT. b. rhodesienseisolates. Malawian SRA gene was genetically different from some isolates in Uganda and Zambia. Contrary to the current understanding that APOL-1 G2 variants are immune toT. b. rhodesienseinfection, severe cases of r-HAT in G2 individuals were identified. This study has brought new insight in understanding the determinants of r-HAT severity.
Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model
Authors: Li Xintao , Liu Sibei
Published: September 2024

Background

Readmissions among Medicare beneficiaries are a major problem for the US healthcare system from a perspective of both healthcare operations and patient caregiving outcomes. Our study analyzes Medicare hospital readmissions using LSTM networks with feature engineering to assess feature contributions.

Design

The 21002 senior patient admission data from MIMIC-III clinical database at Beth Israel Deaconess Medical Center.is utilized in the study We selected variables from admission-level data, inpatient medical history and patient demography. The baseline model is a logistic-regression model based on the LACE index, and the LSTM model is designed to capture temporal dynamic in the data from admission-level and patient-level data. We leveraged Area Under the Curve metric, precision and recall to evaluate the model’s performance.

Results

The LSTM model outperformed the logistic regression baseline, accurately leveraging temporal features to predict readmission. The major features were the Charlson Comorbidity Index, hospital length of stay, the hospital admissions over the past 6 months or the number of medications before discharge, while demographic variables were less impactful

Limitations

The use of a single-center database from the MIMIC-III database limits the generalizability of the findings. Additionally, the exclusion for specific chronic conditions and external factors limit the model’s ability to capture the complexities of chronic diseases.

Conclusions

This work suggests that LSTM networks offers a more promising approach to improve Medicare patient readmission prediction. It captures temporal interactions in patient databases, enhancing current prediction models for healthcare providers.

Implications

Adoption of predictive models into clinical practice may be more effective in identifying Medicare patients to provide early and targeted interventions to improve patient outcomes.

Highlights

Improved Prediction:Our LSTM model outperforms the logistic regression model with LACE index in predicting Medicare patient readmissions.

Feature Contribution:Feature engineering ranks variables base on the impact, deprioritizing the importance of patient demographic variables, highlighting the importance of patients’ chronic diseases in leading hospitalizations and guiding targeted interventions to prevent senior hospital readmissions for healthcare providers.

Effective Use of Data:Our LSTM model incorporates with time-series data from MIMIC-III database to enhance the accuracy of all-cause hospital readmission predictions, especially for the high-risk patients.

Actionable Insights:The result demonstrates the utilization of deep learning model in healthcare decision-making to reduce hospital readmissions for seniors.
eYoung men’s experiences of violence and poverty and the relationship to sexually transmissible HIV: a cross sectional study from rural South Africa
Authors: Gibbs Andrew , Chirwa Esnat , Harling Guy , Chimbindi Natsayi , Dreyer Jaco , Herbst Carina , Okesola Nonhlanhla , Behuhuma Osee , Mthiyane Nondumiso , Baisley Kathy , Zuma Thembelihle , Smit Theresa , McGrath Nuala , Sherr Lorraine , Seeley Janet , Shahmanesh Maryam
Published: September 2024

Background

Young (ages 18-35 years) men are inadequately engaged in HIV prevention and treatment globally, including in South Africa, increasing the likelihood of them having sexually transmissible HIV (i.e. living with HIV but with high viral loads). We sought to understand how men’s experiences of poverty and violence, impacted on transmissible HIV, directly or indirectly via mental health and substance misuse.

Setting

Rural communities in northern KwaZulu-Natal, South Africa.

Methods

Cross-sectional population-based random selection (September 2018-June 2019), assessing transmissible HIV (living with HIV and viral load ≥400 copies/mL) via dried blood spots, and socio-demographic data. Structural equation models (SEM), assessed direct and indirect pathways from food insecurity and violence experience to transmissible-HIV, with mediators common mental disorders, alcohol use, gender inequitable attitudes and perceptions of life chances.

Results

2,086 young (ages 18-36 years) men and 8.6%(n=178) men had transmissible HIV. In SEM no direct pathways between food insecurity, or violence experience, and transmissible HIV. Poor mental health and alcohol use mediated the relationship between violence experience and food insecurity and transmissible HIV. Life chances also mediated the food insecurity to transmissible HIV pathway.

Conclusions

There was a high level of transmissible HIV in a representative sample of young men. The analysis highlights the need to address both the proximate ‘drivers’ poor mental health and substance misuse, as well as the social contexts shaping these among young men, namely poverty and violence experience. Building holistic interventions that adequately engage these multiple challenges is critical for improving HIV among young men.
Evaluating the kidney disease progression using a comprehensive patient profiling algorithm: A hybrid clustering approach
Authors: Al-Mamun Mohammad A. , Jeun Ki Jin , Brothers Todd , Asare Ernest , Shawwa Khaled , Ahmed Imtiaz
Published: September 2024

Background

Among 35.5 million U.S. adults with chronic kidney disease (CKD), more than 557,000 are on dialysis with incurred cost ranges from $97,373 to $102,206 per patient per year. Acute kidney injury (AKI) can lead to an approximate ninefold increased risk for developing CKD. Significant knowledge gaps exist in understanding AKI to CKD progression. We aimed to develop and test a hybrid clustering algorithm to investigate the clinical phenotypes driving AKI to CKD progression.

Methods

This retrospective observational study utilized data from 90,602 patient electronic health records (EHR) from 2010 to 2022. We classified AKI into three groups: Hospital Acquired AKI (HA-AKI), Community Acquired AKI (CA-AKI), and No-AKI. We developed a custom phenotypic disease and procedure network and a complementary variable clustering to examine risk factors among three groups. The algorithm identified top three matched clusters.

Results

Among 58,606 CKD patients, AKI group had a higher prevalence of heart failure (21.1%) and Type 2 Diabetes (45.3%). The No-AKI group had a higher comorbidity burden compared to AKI group, with average comorbidities of 2.84 vs. 2.04; p < 0.05; 74.6% vs. 53.6%. Multiple risk factors were identified in both AKI cohorts including long-term opiate analgesic use, atelectasis, history of ischemic heart disease, and lactic acidosis. The comorbidity network in HA-AKI patients was more complex compared to the No-AKI group with higher number of nodes (64 vs. 55) and edges (645 vs. 520). The HA-AKI cohort had several conditions with higher degree and betweenness centrality including high cholesterol (34, 91.10), chronic pain (33, 103.38), tricuspid insufficiency (38, 113.37), osteoarthritis (34, 56.14), and removal of GI tract components (37, 68.66) compared to the CA-AKI cohort.

Conclusion

Our proposed custom patient profiling algorithm identifies AKI phenotypes based on comorbidities and medical procedures, offering a promising approach to identify early risk factors for CKD using large EHR data.
Evolving cartilage strain with pain progression and gait: a longitudinal study post-ACL reconstruction at six and twelve months
Authors: Miller Emily Y. , Lowe Timothy , Zhu Hongtian , Lee Woowon , Argote Pablo F. , Dresdner Danielle , Kelly James , Frank Rachel M. , McCarty Eric , Bravman Jonathan , Stokes Daniel , Emery Nancy C. , Neu Corey P.
Published: September 2024

Background

Anterior cruciate ligament (ACL) injuries are prevalent musculoskeletal conditions often resulting in long-term degenerative outcomes such as osteoarthritis (OA). Despite surgical advances in ACL reconstruction, a significant number of patients develop OA within ten years post-surgery, providing a patient population that may present early markers of cartilage degeneration detectable using noninvasive imaging.

Purpose

This study aims to investigate the temporal evolution of cartilage strain and relaxometry post-ACL reconstruction using displacement under applied loading MRI and quantitative MRI. Specifically, we examined the correlations between MRI metrics and pain, as well as knee loading patterns during gait, to identify early candidate markers of cartilage degeneration.

Materials and Methods

Twenty-five participants (female/male = 15/10; average age = 25.6 yrs) undergoing ACL reconstruction were enrolled in a prospective longitudinal cohort study between 2022 and 2023. MRI scans were conducted at 6- and 12-months post-surgery, assessing T2, T2*, and T1ρ relaxometry values, and intratissue cartilage strain. Changes in pain were evaluated using standard outcome scores, and gait analysis assessed the knee adduction moment (KAM). Regressions were performed to evaluate relationships between MRI metrics in cartilage contact regions, patient-reported pain, and knee loading metrics.

Results

Increases in axial and transverse strains in the tibial cartilage were significantly correlated with increased pain, while decreases in shear strain were associated with increased pain. Changes in strain metrics were also significantly related to KAM at12 months.

Conclusions

Changes in cartilage strain and relaxometry are related to heightened pain and altered knee loading patterns, indicating potential early markers of osteoarthritis progression. These findings underscore the importance of using advanced MRI for early monitoring in ACL-reconstructed patients to optimize treatment outcomes, while also highlighting KAM as a modifiable intervention through gait retraining that may positively impact the evolution of cartilage health and patient pain.

Key Results

Increased axial and transverse strains in the tibial cartilage from 6 to 12 months post-ACL reconstruction were significantly correlated with increased pain, suggesting evolving changes in cartilage biomechanical properties over time.

Decreases in shear strain in inner femoral and central tibial cartilage regions were linked to increased pain, indicating alterations in joint loading patterns.

Decreases in shear strain in the inner femoral cartilage were significantly associated with decreased 12-month knee adduction moment (KAM), a surrogate for medial cartilage knee loading during walking.
Accounting for partner notification in epidemiological birth-death models
Authors: Zhukova Anna , Gascuel Olivier
Published: September 2024

Phylodynamics bridges the gap between classical epidemiology and pathogen genome sequence data by estimating epidemiological parameters from time-scaled pathogen phylogenetic trees. The models used in phylodynamics typically assume that the sampling procedure is independent between infected individuals. However, this assumption does not hold for many epidemics, in particular for such sexually transmitted infections as HIV-1, for which partner notification schemes are included in health policies of many countries.

We developed an extension of phylodynamic multi-type birth-death (MTBD) models with partner notification (PN), and a simulator to generate trees under MTBD and MTBD-PN models. We proposed a non-parametric test for detecting partner notification in pathogen phylogenetic trees. Its application to simulated data showed that it is both highly specific and sensitive. For the simplest representative of the MTBD-PN family, the BD-PN model, we solved the differential equations and proposed a closed form solution for the likelihood function. We implemented it in a program, which estimates the model parameters and their confidence intervals from phylogenetic trees. It performed accurate estimations on simulated data, and detected partner notification in HIV-1 B epidemics in Zurich and the UK. Importantly, we showed that not accounting for partner notification when it is present leads to bias in parameter estimation with the BD model, while BD-PN parameter estimator performs well both in presence and in absence of partner notification.

Our PN test, MTBD-PN tree simulator and BD-PN parameter estimator are freely available atgithub.com/evolbioinfo/treesimulatorandgithub.com/evolbioinfo/bdpn.

Author summary

Phylodynamic models can estimate epidemiological parameters such as the number of secondary infectionsRefrom pathogen phylogenetic trees (i.e., genealogies, inferred from pathogen genomic sequences). These models do not account for partner notification (contact tracing), and instead assume that detection of new cases is independent between infected individuals. However, especially for sexually transmitted infections, partner notification plays an important role and is included in health policies of many countries.

We developed a phylodynamic model accounting for partner notification and a test for the detection of partner notification in pathogen phylogenetic trees. Our test and epidemiological parameter estimator showed good performance both on simulated and real data. We detected the presence of partner notification in the HIV-1 B epidemics in Zurich and the UK, and corrected the previous parameter estimates made without accounting for partner notification.
Efficacy of Molnupiravir in reducing the risk of severe outcome in patients with SARS-CoV-2 infection: a real-life full-matched case-control study (SAVALO Study)
Authors: Gentile Ivan , Scotto Riccardo , Scirocco Maria Michela , Di Brizzi Francesco , Cuccurullo Federica , Silvitelli Maria , Ametrano Luigi , Alfè Francesco Antimo , Pietroluongo Daria , Irace Irene , Chiariello Mariarosaria , De Felice Noemi , Severino Simone , Viceconte Giulio , Schiano Moriello Nicola , Maraolo Alberto Enrico , Buonomo Antonio Riccardo , Giaccone Agnese ,   Federico II COVID team
Published: September 2024

Introduction

Molnupiravir (MNP) is an orally administered prodrug which prevents disease progression in patients at high risk for severe COVID-19. We conducted a real-life case-control study on a cohort of outpatients, with Omicron SARS-CoV-2 infection to assess the effectiveness of MNP in reducing the occurrence of hospital admission, admission in intensive care unit (ICU) and death at day 28.

Materials and methods

Cases were enrolled among SARS-CoV-2 positive subjects that sought medical care during the first five days of symptoms from January 1st, 2022, to December 31st, 2022, and received MNP. Control participants were selected from a regional database among those who tested positive during the study period and did not receive antiviral treatment for SARS-CoV-2.

Results

1382 patients were included (cases: 146, controls: 1236). Vaccinated patients showed lower risk of mortality and composite outcome (at least one among hospital admission, admission in ICU and all-cause death) compared to unvaccinated ones (0.6% vs 7.8%, p<0.001 and 2% vs 7.8%, p=0.001 respectively). After full-matching propensity score, MNP-treated subjects showed a lower incidence of composite outcome, while no effect was observed on the single outcomes. In the subgroup analysis according to the vaccination status, MNP proved effective in preventing all the outcomes among unvaccinated patients, while showed to reduce the risk of ICU admission both in vaccinated and unvaccinated patients.

Conclusions

Treatment with MNP proved effective in reducing the risk of composite outcome among outpatients with SARS-CoV-2 infection. The beneficial effect of MNP treatment in reducing progression is more pronounced in unvaccinated patients.
Contrasting Effects of Cytoskeleton Disruption on Plasma Membrane Receptor Dynamics: Insights from Single-Molecule Analyses
Authors: Rohr Leander , Rausch Luiselotte , Harter Klaus , zur Oven-Krockhaus Sven
Published: September 2024

Traditional models such as the fluid mosaic model or the lipid raft hypothesis have shaped our understanding of plasma membrane (PM) organization. However, recent discoveries have extended these paradigms by pointing to the existence of micro- and nanodomains. Here, we investigated the role of the cytoskeleton in general and whether the picket fence model, established in animal cells, is transferable to the plant cell system. By using single-particle tracking photoactivated localization microscopy (sptPALM) in combination with genetically encoded enzymatic tools for the targeted disruption of the cytoskeleton, we studied the dynamics and nanoscale organization of a selection of PM receptor-like kinases (RLKs) and receptor-like proteins (RLPs). Our findings show that the disintegration of actin filaments leads to decreased diffusion, more restrictive motion patterns, and enlarged clusters, whereas the disintegration of microtubules results in increased diffusion, more unconstrained diffusive behavior, and decreased cluster sizes of the tested RLKs and RLPs. These results underscore the potential unique regulatory functions of cytoskeleton components in plants and suggest an altered mechanism compared to the picket fence model of the animal cell system. Our qualitative data can serve as the foundation for further investigations aimed at developing a comprehensive and refined model of protein dynamics and organization in plant cells.
Use of Maize (Zea maysL.) Mutator Transposon-Induced Mutants of theBonnMuResource for Forward and Reverse Genetics Studies
Authors: Win Yan Naing , Pöschel Martin , Stöcker Tyll , Du Xuelian , Klaus Alina , Braun Ben Wilhelm , Lukas Linnéa , Brox Alexa , Schoof Heiko , Hochholdinger Frank , Marcon Caroline
Published: September 2024

TheBonnMuresource represents a tagged collection of maize (Zea maysL.)Mutator(Mu) transposon-induced mutants, designed for functional genomics studies. Here, we describe the use of theBonnMucollection for identifying and characterizing mutations. Specifically, we describe workflows for use in both reverse and forward genetics strategies in maize. For reverse genetics, users first acquire aBonnMuF2stock of interest based on data accessible at the Maize Genetics and Genomics Database (MaizeGDB). We provide details here for their subsequent propagation and for the confirmation ofMuinsertions by genotyping via PCR, with the ultimate goal of establishing genotype–phenotype relationships of interest. For forward genetics studies, we describe a workflow that involves a combined approach of Mutant-Seq (Mu-Seq) and bulked segregant RNA-seq (BSR-Seq), to identify the causal gene underlying a mutant phenotype of interest.
BonnMu: A Resource for Functional Genomics in Maize (Zea maysL.)
Authors: Marcon Caroline , Win Yan Naing , Du Xuelian , Hochholdinger Frank
Published: September 2024

TheBonnMuresource is a public transposon-tagged population designed for reverse and forward genetics studies in maize (Zea maysL.). The resource was created by crossing an activeMutator(Mu) transposon line into different inbred lines to induce insertional mutations. The resulting F1generation was self-pollinated to generate segregatingBonnMuF2stocks. TheMu-taggedBonnMuF2stocks have insertions in 83% of all annotated maize gene models, andMuinsertion positions and photos of the seedling phenotypes of the segregatingBonnMuF2stocks are deposited in the Maize Genetics and Genomics Database (MaizeGDB), with seeds available to the community. Here, we discuss the creation, expansion, and application of theBonnMuresource for identifying and characterizing mutations induced byMutransposons, which represents a useful tool for functional genomics studies in maize.
Block encodings of discrete subgroups on a quantum computer
Authors: Lamm Henry , Li Ying-Ying , Shu Jing , Wang Yi-Lin , Xu Bin
Published: September 2024

We introduce a block encoding method for mapping discrete subgroups to qubits on a quantum computer. This method is applicable to general discrete groups, including crystal-like subgroups such as BI of SU(2) and V of SU(3). We detail the construction of primitive gates—the inversion gate, the group multiplication gate, the trace gate, and the group Fourier gate—utilizing this encoding method for BT and for the first time BI group. We also provide resource estimations to extract the gluon viscosity. The inversion gates for BT and BI are benchmarked on the quantum computer with estimated fidelities of 40−4+5% and 4−3+5%, respectively.

Published by the American Physical Society
2024
How CSR communication and value co-creation shape consumer well-being and brand love in the post-COVID-19 pandemic: evidence from the UK
Authors: Chang Shing-Wan , Berwanger Gabriel Alexander Dos Santos
Published: September 2024

Purpose

Drawing upon the service-dominant logic (S-D logic) and elaboration likelihood model (ELM), this paper provides an integrative model to investigate how argument quality and source credibility of CSR communication affects customer value co-creation behavior, resulting in increased brand trust. Additionally, it unveils how brand trust and the perception of COVID-19 risk influence both brand love and subjective well-being.

Design/methodology/approach

The data of this study were collected through survey questionnaire from 304 coffee shop customers using convenience sampling and tested using the partial least squares structural equation modeling (PLS-SEM) technique to validate its model.

Findings

The research findings confirm the positive association between source credibility and customer value co-creation (i.e. customer participation and citizenship behavior). By contrast, argument quality is revealed to have a significantly positive effect on customer citizenship behavior (CCB) but a non-significant effect on customer participation behavior (CPB). Additionally, the study identifies that customer value co-creation behavior significantly promotes brand trust. Finally, findings indicate that brand trust and the perception of COVID-19 risk significantly influence brand love and subjective well-being.

Originality/value

This study contributes to the literature on CSR communication and S-D logic and provides new insights for marketers and advertisers to manage brands in the post-pandemic scenario through CSR communications. Furthermore, this study theoretically extends the ELM model to the CSR communication research. Finally, this study expands the relevant literature by clarifying the relationships between the perception of COVID-19 risk, brand love and subjective well-being.
Forecasting the outcomes of construction contract disputes using machine learning techniques
Authors: Un Buse , Erdis Ercan , Aydınlı Serkan , Genc Olcay , Alboga Ozge
Published: September 2024

Purpose

This study aims to develop a predictive model using machine learning techniques to forecast construction dispute outcomes, thereby minimizing economic and social losses and promoting amicable settlements between parties.

Design/methodology/approach

This study develops a novel conceptual model incorporating project characteristics, root causes, and underlying causes to predict construction dispute outcomes. Utilizing a dataset of arbitration cases in Türkiye, the model was tested using five machine learning algorithms namely Logistic Regression, Support Vector Machines, Decision Trees, K-Nearest Neighbors, and Random Forest in a Python environment. The performance of each algorithm was evaluated to identify the most accurate predictive model.

Findings

The analysis revealed that the Support Vector Machine algorithm achieved the highest prediction accuracy at 71.65%. Twelve significant variables were identified for the best model namely, work type, root causes, delays from a contractor, extension of time, different site conditions, poorly written contracts, unit price determination, penalties, price adjustment, acceptances, delay of schedule, and extra payment claims. The study’s results surpass some existing models in the literature, highlighting the model’s robustness and practical applicability in forecasting construction dispute outcomes.

Originality/value

This study is unique in its consideration of various contract, dispute, and project attributes to predict construction dispute outcomes using machine learning techniques. It uses a fact-based dataset of arbitration cases from Türkiye, providing a robust and practical predictive model applicable across different regions and project types. It advances the literature by comparing multiple machine learning algorithms to achieve the highest prediction accuracy and offering a comprehensive tool for proactive dispute management.
The interrelationships between emotional intelligence, achievement motivation and students’ employability: exploring the mediating effect of self-efficacy
Authors: Li Xiang , Pu Ruihui , Phakdeephirot Nutteera
Published: September 2024

Purpose

This research examines the mediating effect of self-efficacy among interrelationships of emotional intelligence, achievement motivation and students’ employability in the Chinese higher education institutions. This study was primarily conducted by applying the social cognitive theory to explain the beliefs and abilities of being employed for university students and influenced by their achievement motivation.

Design/methodology/approach

A survey approach was employed to collect the samples of 585 final-year college students using the convenience sampling method from 5 different Chinese higher education institutions. The structural equation modeling (SEM) approach was used as the data analysis method.

Findings

The result significantly supported the positive effect of emotional intelligence (ß = 0.298, p < 0.001) and achievement motivation (ß = 0.307, p < 0.001) on students’ employability. Furthermore, the results also showed that self-efficacy significantly had a mediating effect between achievement motivation and employability (ß = 0.119, CI95%: 0.062, 0.195) among college students. However, the study confirmed that self-efficacy was not associated with the relationship between emotional intelligence and employability (ß = 0.029, CI95%: −0.003, 0.075).

Originality/value

This research clarifies and highlights that psychological variables have highly correlated with the employability outcomes of university students. The findings also hold significant value and practical implications for the governments, colleges, and students that enhancing employability should be through targeted interventions. This study sets the stage for future research exploring potential mediators of motivation and other essential factors that may influence among the existing relationship.
Bringing academic disciplines together to focus on literacy: a secondary school case study
Authors: Michel Daryl Allan
Published: September 2024

Purpose

The purpose of this qualitative study was to bring together teachers from different academic disciplines to engage them in lesson study (LS) cycles with a focus on literacy.

Design/methodology/approach

This research employed a qualitative case study and occurred in one secondary school along the Texas (USA) and Mexico border. Ten teachers representing six academic disciplines participated in eight LS cycles to reflect on their knowledge of literacy, including when, if at all, they integrated literacy when planning and teaching lessons. About 20 students shared their impressions, feelings and thoughts about the lessons.

Findings

Teachers learned that literacy standards exist in each academic discipline and that integrating reading and writing during lessons allowed for more increased dialogue between/among teachers and students. The principal learned that teachers from all academic disciplines need differentiated, sustained professional learning opportunities on how to teach literacy skills.

Originality/value

Teachers often work alone or within their respective academic departments, whereas this project focused on secondary teachers from six academic disciplines taking part in LS cycles with a common focus on literacy. Sustained opportunities for teachers to study their standards and curriculum materials, plan and teach lessons and share perspectives from classroom observations resulted in new knowledge about ways to include literacy in any academic discipline. A schoolwide professional learning community focused on literacy could act as a catalyst for instructional change.
Teleworking and work-family balance in public educational institutions
Authors: Costa Marine Mateus , Alves Filho Antônio , Pessoa-de-Oliveira Ana Katarina
Published: September 2024

Purpose

This article aims to investigate teleworking in public institutions, specifically focussing on the perspectives of technical-administrative employees at a Brazilian federal educational institution.

Design/methodology/approach

The research methodology involved the use of guided semi-structured interviews with public servants. The analysis applied a prior set of categories derived from the advantages and disadvantages of teleworking, as well as the favourable and unfavourable aspects of the interaction between teleworking and family relationships.

Findings

The findings reveal a range of benefits associated with teleworking, primarily an improved quality of life for workers. However, the study also identified significant challenges, including excessive workload, social isolation and difficulties in separating personal and professional life, corroborating with previous studies.

Research limitations/implications

It is crucial to note that the majority of participants in the study have children or dependants, which could potentially influence their teleworking strategies and experiences. This demographic factor may play a significant role in how participants navigate their work-from-home routines and manage their responsibilities, especially during the COVID-19 pandemic.

Practical implications

Working from home presents two sides of the same coin according to the vision of those involved in this type of work. Public organisations should know in depth the challenges faced by their workers to prioritise planning that monitors their workforce and achieve success with teleworking.

Originality/value

The insights from this study provide valuable guidance for the development of evidence-based teleworking policies and practices in public educational institutions.
Research on composite material riveting simulation method for engineering applications
Authors: Niu Chunliang , Liu BingZhuo , Bai Chunfei , Guo Liming , Chen Lei , Tang Jiwu
Published: September 2024

Purpose

In order to improve the efficiency and reliability of simulation analysis for composite riveting structures in engineering products, a comparative study was conducted on different forms of riveting simulation methods.

Design/methodology/approach

Five different rivent simulation models were established using the finite element method, including rigid element CE, flexible element Rbe3 and beam element, and their results were future compared and analyzed.

Findings

Under the given technical parameters, the simulation method of Rbe3 (with holes) + beam can meet the analysis requirements of complex engineering products in terms of the rationality of rivet load distribution, calculation error and relatively efficient modeling.

Originality/value

This study proposes a simulation method for the riveting structure of carbon fiber composite materials for engineering applications. This method can satisfy the simulation analysis requirements of transportation vehicles in terms of modeling time, computational efficiency and accuracy. The research can provide technical support for the riveting process and mechanical analysis between carbon fiber composite components in transportation products.
Digitalization in action sports: blessing or curse?
Authors: Standaert Willem , Mazurova Elena
Published: September 2024

Purpose

This study aims to identify how the use of digital technology for performance and commercial aspects of action sports can both create and destruct value.

Design/methodology/approach

Exploratory research based on 30 interviews with coaches, athletes, judges, federations, fans and sponsoring organizations from Europe, across five action sport disciplines that are included in the Olympic program.

Findings

Value creation of digital technology use related to the performance aspect of action sports fall into two categories: performance enhancement and performance evaluation. Value creation related to the commercialization aspect of action sports relate to specific technologies, in particular a video streaming and a centralized data and engagement platform, as well as to possibilities for betting and making sponsoring more measurable. Notably, such value creation opportunities are also accompanied by possible value destruction, as they interfere with the ethos of action sports (i.e. the unique nature and special culture).

Originality/value

Drawing from service-dominant logic and adopting the value creation/destruction lens, this paper is the first to study how digitalization in the areas of performance and commercialization may further intensify tensions related to the ethos of action sports. Our approach is inclusive in terms of the types of digital technologies, action sport disciplines and stakeholders considered.
The determinants of MNE foreign subsidiaries’ performance: a systematic literature review and future research agenda
Authors: Nguyen Quyen
Published: September 2024

Purpose

Foreign subsidiaries of multinational enterprises (MNEs) operate in complex and competitive international environments, implement market and non-market strategies, manage resources and value-added activities and contribute to the overall performance of their parent firms. Thus, the research question on the determinants of MNE foreign subsidiaries’ performance is of interest to managers and academic researchers. The empirical literature has flourished over the recent decades; however, the domains are fragmented, and the findings are inclusive. The purpose of this study is to systematically review, analyse and synthesize the empirical articles in this area, identify research gaps and suggest a future research agenda.

Design/methodology/approach

This study uses the qualitative content analysis method in reviewing and analysing 150 articles published in 24 scholarly journals during the period 2000–2023.

Findings

The literature uses a variety of theoretical perspectives to examine the key determinants of subsidiary performance which can be grouped into six major domains, namely, home- and host country-level factors; distance between home and host countries; the characteristics of parent firms and of subsidiaries; and governance mechanisms (the establishment modes and ownership strategy, subsidiary autonomy and the use of home country expatriates for transferring knowledge from the headquarters and controlling foreign subsidiaries). A range of objective and subjective indicators are used to measure subsidiary performance. Yet, the research shows a lack of broader integration of theories and presents inconsistent theoretical predictions, inconclusive empirical findings and estimation bias, which hinder our understanding of how the determinants independently and jointly shape the performance of foreign subsidiaries.

Originality/value

This study provides a comprehensive, nuanced and systematic review that synthesizes and clarifies the determinants of subsidiary performance, offers deeper insights from both theoretical, methodological and empirical aspects and proposes some promising avenues for future research directions.