bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are children with disabilities more likely to be malnourished than children without disabilities? Evidence from the Multiple Indicator Cluster Surveys in 30 countries
Authors: Rotenberg Sara , Chen Shanquan , Hunt Xanthe , Smythe Tracey , Kuper Hannah 
Published: September 2023

AbstractIntroductionA key Sustainable Development Goal target is to eliminate all forms of malnutrition. Existing evidence suggests children with disabilities are at greater risks of malnutrition, exclusion from nutrition programmes, and mortality from severe acute malnutrition than children without disabilities. However, there is limited evidence on the nutritional outcomes of children with disabilities in large-scale global health surveys.MethodsWe analysed Multiple Indicator Cluster Survey (MICS) data from 30 low and middle-income countries (LMICs) to compare nutritional outcomes for children aged 2-4 years with and without disabilities. We estimated the adjusted prevalence ratios for stunting, wasting, and underweight comparing children with and without disabilities by country and sex, using quasi-Poisson models with robust standard errors. We accounted for the complex survey design, wealth quintile, location, and age in the analyses. We meta-analysed these results to create an overall estimate for each of these outcomes.ResultsOur analyses included 229,621 children aged 2-4 across 30 countries, including 15,071 children with disabilities (6.6%). Overall, children with disabilities were more likely to be stunted (aRR: 1.16, 95% C.I.: 1.11 -1.20), wasted (aRR: 1.28, 95% C.I.: 1.18 – 1.39), and underweight (aRR: 1.33, 95% C.I.: 1.17, 1.51) than children without disabilities. These patterns were observed in both girls and boys with disabilities, compared to those without.ConclusionChildren with disabilities are significantly more likely to experience all forms of malnutrition, making it critical to accelerate efforts to improve disability-inclusion within nutrition programmes. Ending all forms of malnutrition will not be achievable without a focus on disability.Key MessagesWhat is already known on this topicPrior research has shown children with disabilities in low-and middle-income countries have higher prevalence of stunting, wasting, and underweight and worse outcomes and mortality from severe acute malnutrition.What this study addsWe show that children with disabilities, overall and by sex, have significantly higher rates of stunting, wasting, and underweight than children without disabilities.This study adds to the existing evidence on disability-based inequities in nutritional outcomes from nationally representative, internationally-comparable household surveys in multiple countries.How this study might affect research, practice, or policyA twin-track approach is needed to ensure children with disabilities are reached in mainstream nutrition programmes, as well as having their specific and additional needs met through targeted programmes.Without sufficient focus on disability, it will be impossible to achieve SDG2, to end all forms of child nutrition, or meet global child mortality reduction targets.
A synthetic peptide mimic killsCandida albicansand synergistically prevents infection
Authors: Schaefer Sebastian , Vij Raghav , Sprague Jakob L. , Austermeier Sophie , Dinh Hue , Judzewitsch Peter R. , Seemann Eric , Qualmann Britta , Cain Amy K. , Corrigan Nathaniel , Gresnigt Mark S. , Boyer Cyrille , Lenardon Megan D. , Brunke Sascha 
Published: September 2023

AbstractMore than two million people worldwide are affected by life-threatening, invasive fungal infections annually.Candidaspecies are the most common cause of nosocomical, invasive fungal infections and are associated with mortality rates above 40%. Despite the increasing incidence of drug-resistance, the development of novel antifungal formulations has been limited. Here we investigate the antifungal mode of action and therapeutic potential of positively charged, synthetic peptide mimics to combat infections byCandida albicans. These synthetic polymers cause stress to the endoplasmic reticulum and affect protein glycosylation, a distinct mode of action compared to currently approved antifungal drugs. The most promising polymer composition caused damage to the mannan layer of the cell wall, with additional membrane-disrupting activity. The synergistic combination of the polymer with caspofungin prevented infection of human epithelial cellsin vitro, improved fungal clearance by human macrophages, and significantly increased host survival in aGalleria mellonellamodel of systemic candidiasis. Additionally, prolonged exposure ofC. albicansto the synergistic combination of polymer and caspofungin did not lead to the evolution of resistant strainsin vitro. Together, this work highlights the enormous potential of these synthetic peptide mimics to be used as novel antifungal formulations as well as adjunctive antifungal therapy.
Minimal epistatic networks from integrated sequence and mutational protein data
Authors: Cocco Simona , Posani Lorenzo , Monasson Rémi 
Published: September 2023

AbstractPredicting the functional effects of mutations to a wild-type protein sequence is a major computational challenge. We introduce here a computationally efficient procedure to identify the few, most informative epistatic links between residues in a protein, integrating sequence data and functional measurements with mutational scans. Our approach shows performances comparable to state-of-the-art deep networks, while requiring much less parameters and being hence much more interpretable. The selected network links mostly focus on the protein functional sites, adapt to thein vitroorin vivofunction experimentally tested, and are not necessary related to structural contacts.
Qualitative rather than quantitative phosphoregulation shapes the end of meiosis I in budding yeast
Authors: Celebic Dunja , Polat Irem , Legros Véronique , Chevreux Guillaume , Wassmann Katja , Touati Sandra A 
Published: September 2023

AbstractExit from mitosis is brought about by dramatic changes in the phosphoproteome landscape. A drop in Cyclin-dependent kinase (Cdk), the master regulatory kinase, and activation of counteracting phosphatases such as Cdc14 in budding yeast, results in ordered substrate dephosphorylation, allowing entry into a new cell cycle and replication licensing. In meiosis however, two cell divisions have to be executed without intermediate DNA replication, implying that global phosphorylation and dephosphorylation have to be adapted to the challenges of meiosis. Using a global time-resolved phosphoproteomics approach in budding yeast, we compared the phosphoproteome landscape between mitotic exit and the transition from meiosis I to meiosis II. We found that unlike exit from mitosis, Cdk phosphomotifs remain mostly stably phosphorylated at the end of meiosis I, whereas a majority of Cdk-unrelated motifs are reset by dephosphorylation. However, inducing an artificial drop of Cdk at metaphase of meiosis I leads to ordered substrate dephosphorylation, comparable to mitosis, indicating that phosphoregulation of substrates at the end of meiosis I is thus mainly qualitatively rather than quantitatively ordered.
Surface-engineered extracellular vesicles to modulate antigen-specific T cell expansion for cancer immunotherapy
Authors: Lyu Xiabing , Yamano Tomoyoshi , Imai Shota , Le Toan Van , Bolidong Dilireba , Ueda Makie , Warashina Shota , Mukai Hidefumi , Hayashi Seigo , Matoba Kazutaka , Nishino Taito , Hanayama Rikinari 
Published: September 2023

AbstractExtracellular vesicles (EVs), including exosomes, are emerging as novel mediators of cell-cell communications, involved in various processes such as immune activation and immunosuppression. Despite the recent development of several EVs-based cancer immunotherapies, their clinical efficacy remained limited. Here, using fusion with tetraspanin as one of the EV engineering techniques, we created antigen-presenting extracellular vesicles (AP-EVs) to reproduce the functional characteristics of professional antigen-presenting cells (APCs). AP-EVs were also equipped with surface-bound IL-2, a feature not inherent to APCs, which facilitated selective delivery of IL-2 to antigen-specific CD8+T cells. AP-EVs were engineered to express a peptide-major histocompatibility class I (pMHCI) complex, a costimulatory CD80 molecule, and IL-2, allowing the simultaneous presentation of multiple immune modulators to antigen-specific CD8+T cells. This promoted the clonal expansion and differentiation of antigen-specific cytotoxic T lymphocytes, leading to potent anticancer immune responses. Combination therapy with AP-EVs and anti-PD-1 demonstrated enhanced anticancer immunity against established tumors compared with anti-PD-1 monotherapy. Our engineered EVs represent a novel effective strategy for cancer immunotherapy.
Stability metrics behave predictably across data qualities but are sensitive to community size
Authors: O’Brien Duncan A , Clements Christopher F 
Published: September 2023

AbstractModern biodiversity monitoring is generating increasingly multidimensional representations of wildlife populations and ecosystems. It is therefore appealing for conservation and environmental governance to combine that information into single measure of ecosystem or population health. Stability represents a desirable feature of ecosystems that supports this aim, measured through resistance, recovery, and variability. In deterministic mathematical systems, the Jacobian matrix is a common characteristic used to quantify resistance and resilience and whilst historically it has been challenging to estimate from empirical data, recent work has proposed a suite of metrics capable of reconstructing it for a real-world community using time series data. Here we assess the robustness of three Jacobian metrics and two variability estimating stability metrics to varying time series lengths and data qualities based on that seen in real-world wildlife time series. Using Lotka–Volterra equations, we generate short time series (to match global biodiversity datasets such as the Living Planet Index and BIOTIME) and introduce sampling error corruptions (to mimic varying search efforts) to validate metric performance in empirical data. The robustness stability metrics generally improved with time series length and search effort in the anticipated manner. However, number of species dramatically altered metric capability, with larger communities decreasing the reliability of stability metric trends. Overall, stability metrics behave predictably across realistic data corruptions. Generic stability estimation is therefore possible from abundance time series alone, and we suggest that, given the increasing availability of multivariate community data, focussing on Jacobian estimates is a plausible ecosystem condition indicator.
Enzyme Structure Correlates With Variant Effect Predictability
Authors: van der Flier Floris , Estell David , Pricelius Sina , Dankmeyer Lydia , van Stigt Thans Sander , Mulder Harm , Otsuka Rei , Goedegebuur Frits , Lammerts Laurens , Staphorst Diego , van Dijk Aalt D.J. , de Ridder Dick , Redestig Henning 
Published: September 2023

AbstractProtein engineering increasingly relies on machine learning models to computationally pre-screen promising novel candidates. Although machine learning approaches have proven effective, their performance on prospective screening data leaves room for improvement; prediction accuracy can vary greatly from one protein variant to the next. So far, it is unclear what characterizes variants that are associated with large prediction error. In order to establish whether structural characteristics influence predictability, we created a combinatorial variant dataset for an enzyme, that can be partitioned into subsets of variants with mutations at positions exclusively belonging to a particular structural class. By training four different variant effect prediction (VEP) models on structurally partitioned subsets of our data, we found that predictability strongly depended on all four structural characteristics we tested; buriedness, number of contact residues, proximity to the active site and presence of secondary structure elements. These same dependencies were found in various single mutation enzyme variant datasets, with effect directions being specific to the assay. Most importantly, we found that these dependencies are highly alike for all four models we tested, indicating that there are specific structure and function determinants that are insufficiently accounted for by popular existing approaches. Overall, our findings suggest that significant improvements can be made to VEP models by exploring new inductive biases and by leveraging different data modalities of protein variants, and that stratified dataset design can highlight areas of improvement for machine learning guided protein engineering.
Post-pandemic opportunities for F&B green supply chains and supply chain viability: the moderate effect of blockchains and big data analytics
Authors: Kholaif Moustafa Mohamed Nazief Haggag Kotb , Sarwar Bushra , Xiao Ming , Poliak Milos , Giovando Guido 
Published: September 2023

PurposeThis study aims to explore the pandemic's opportunities for enhancing the environmental practices of the food and beverages green supply chains and its effect on the supply chains' viability by exploring the relationship between fear and uncertainty of COVID-19, food and beverages green supply chain management (F&B-GSCM) and supply chains’ viability based on the two dimensions (robustness and resilience) and examine the moderating effect of innovative technology adoption like big data analysis (BDA) capabilities and blockchain technologies (BCT) on this relationship.Design/methodology/approachThis study adopted partial least squares structural equation modeling (PLS-SEM) on a sample of 362 F&B small and medium enterprises (SMEs)’ managers in the Egyptian market for data analysis and hypothesis testing.FindingsThe empirical results show that the fear and uncertainty of the pandemic have a significant positive effect on green supply chain management (GSCM). Also, BDA moderates the relationship between fear and uncertainty of COVID-19 and GSCM. However, BCT do not moderate that relationship. Similarly, GSCM positively affects supply chain viability dimensions (robustness and resilience). In addition, F&B-GSCM significantly mediates the relationship between fear and uncertainty of COVID-19 and supply chain viability dimensions (robustness and resilience).Practical implicationsFood and beverages (F&B) managers could develop a consistent strategy for applying BCT and BDA to provide clear information and focus on their procedures to meet their stakeholders' needs during COVID-19. Governments and managers should develop a consistent strategy to apply food and beverages supply chains (F&B SCs)' green practices to achieve F&B SCs' resilience and robustness, especially during the pandemic.Originality/valueThe Egyptian F&B SCs have been linked directly with many European countries as a main source of many basic food and agriculture products, which have been affected lately by the pandemic. Based on the “social-cognitive,” “stakeholder” and “resource-based view” theories, this study sheds light on the optimistic side of the COVID-19 pandemic, as it also brings the concepts of F&B-GSCM, SC resilience, SC robustness and innovative technologies back into the light, which helps in solving F&B SC issues and helps to achieve their viability.
A review on minimum quantity lubrication (MQL) assisted machining processes using mono and hybrid nanofluids
Authors: Singh Talwinder , Singh Chandan Deep , Singh Rajdeep 
Published: September 2023

Purpose
Because many cutting fluids contain hazardous chemical constituents, industries and researchers are looking for alternative methods to reduce the consumption of cutting fluids in machining operations due to growing awareness of ecological and health issues, government strict environmental regulations and economic pressures. Therefore, the purpose of this study is to raise awareness of the minimum quantity lubrication (MQL) technique as a potential substitute for environmental restricted wet (flooded) machining situations.

Design/methodology/approach
The methodology adopted for conducting a review in this study includes four sections: establishment of MQL technique and review of MQL machining performance comparison with dry and wet (flooded) environments; analysis of the past literature to examine MQL turning performance under mono nanofluids (M-NF); MQL turning performance evaluation under hybrid nanofluids (H-NF); and MQL milling, drilling and grinding performance assessment under M-NF and H-NF.

Findings
From the extensive review, it has been found that MQL results in lower cutting zone temperature, reduction in cutting forces, enhanced tool life and better machined surface quality compared to dry and wet cutting conditions. Also, MQL under H-NF discloses notably improved tribo-performance due to the synergistic effect caused by the physical encapsulation of spherical nanoparticles between the nanosheets of lamellar structured nanoparticles when compared with M-NF. The findings of this study recommend that MQL with nanofluids can replace dry and flood lubrication conditions for superior machining performance.

Practical implications
Machining under the MQL regime provides a dry, clean, healthy and pollution-free working area, thereby resulting the machining of materials green and environmentally friendly.

Originality/value
This paper describes the suitability of MQL for different machining operations using M-NF and H-NF.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2023-0131/
Using machine learning to investigate consumers' emotions: the spillover effect of AI defeating people on consumers' attitudes toward AI companies
Authors: Ma Yongchao Martin , Dai Xin , Deng Zhongzhun 
Published: September 2023

PurposeThe purpose of this study is to investigate consumers' emotional responses to artificial intelligence (AI) defeating people. Meanwhile, the authors investigate the negative spillover effect of AI defeating people on consumers' attitudes toward AI companies. The authors also try to alleviate this spillover effect.Design/methodology/approachUsing four studies to test the hypotheses. In Study 1, the authors use the fine-tuned Bidirectional Encoder Representations from the Transformers algorithm to run a sentiment analysis to investigate how AI defeating people influences consumers' emotions. In Studies 2 to 4, the authors test the effect of AI defeating people on consumers' attitudes, the mediating effect of negative emotions and the moderating effect of different intentions.FindingsThe authors find that AI defeating people increases consumers' negative emotions. In terms of downstream consequences, AI defeating people induces a spillover effect on consumers' unfavorable attitudes toward AI companies. Emphasizing the intention of helping people can effectively mitigate this negative spillover effect.Practical implicationsThe authors' findings remind governments, policymakers and AI companies to pay attention to the negative effect of AI defeating people and take reasonable steps to alleviate this negative effect. The authors help consumers rationally understand this phenomenon and correctly control and reduce unnecessary negative emotions in the AI era.Originality/valueThis paper is the first study to examine the adverse effects of AI defeating humans. The authors contribute to research on the dark side of AI, the outcomes of competition matches and the method to analyze emotions in user-generated content (UGC).
The service attributes of robo-advisors: a choice-based conjoint analysis
Authors: Hou Jian-Ren , Li Yen-Hsi , Kankham Sarawut 
Published: September 2023

PurposeAs an alternative to hiring financial specialists or investment consultants, robo-advisors offer financially automated investment services. This study aims to investigate how robo-advisors' service attributes, risk attitude and financial self-efficacy influence customers' choice preferences of adopting robo-advisors.Design/methodology/approachTwo hundred fifty-one online surveys were used to collect data, and choice-based conjoint analysis was conducted.FindingsResults show that increasing annual fees negatively impact customers' choice preferences. Promotion, general investment education and additional human assistance have a positive impact. Furthermore, risk-seeking and risk-averse customers require more human assistance than risk-neutral customer and customers with high levels of financial self-efficacy prefer more general investment education and additional human assistance than those with lower levels. In addition, customers in the older age group prefer promotion, general investment education and additional human assistance, while wealthy customers prefer lower annual fees, higher general investment education and more additional human assistance compared to middle-class and low-income groups.Originality/valueThis study contributes to robo-advisor providers to provide appropriate service attributes for each customer group.
Sustainable performance, conditional conservatism and audit fees
Authors: Kammoun Ines , Khoufi Walid 
Published: September 2023

Purpose
This paper aims to examine the effect of conditional conservatism on audit fees and whether the firm’s engagement in sustainable practices moderates the relationship between conditional conservatism and audit fees.

Design/methodology/approach
Using a sample of 3,767 firm-year observations from 14 European Union countries over the period of 2006–2019, the authors adopt the ordinary least square estimator to perform a panel data analysis of the effect of conditional conservatism on audit fees, and the moderating role of the environmental, social and governance (ESG) scores on the relationship between conditional conservatism and audit fees.

Findings
The authors find that conditional conservatism has a significant negative effect on audit fees, suggesting that auditors charge lower audit fees on more conservative clients. The authors also find that firms engaging in ESG actions, whether combined or individual, pay higher audit fees. More interestingly, the authors provide evidence that the negative effect of conditional conservatism on audit fees is mitigated only when ESG performance is considered in combination. This implies that firms exhibiting less commitment to ESG sustainability practices are prone to paying reduced audit fees when engaged in more conservative reporting. The findings remain robust after conducting a battery of tests.

Practical implications
The findings of this study have practical implications for several parties, including companies, auditors and regulators. This study emphasizes the potential benefit associated with using conservative accounting practices in terms of shaping downward the amount of audit fees. However, it also highlights the importance of considering the additional audit costs associated with higher ESG scores when making decisions about implementing sustainable practices.

Originality/value
Unlike prior studies that investigate the direct impact of sustainable practices on audit fees, the present work contributes to the literature on the benefits and costs of ESG by examining the moderating role of ESG performance in the association between audit fees and conditional conservatism. To the best of the authors’ knowledge, this study is the first to examine this relationship. Theoretically, the research integrates the theories of audit risk and agency to provide a more comprehensive understanding of the drivers of audit fees.