bluuebunny/crossref_metadata_2025 huggingface dataset:
Single cell RNA-sequencing reveals no evidence for meiotic sex chromosome inactivation in the threespine stickleback fish
Authors: Shaw Daniel E. , Ross Wynter D. , Lambert Alexis V. , White Michael A.
Published: November 2024

Sex chromosomes often evolve unique patterns of gene expression in spermatogenesis. In many species, sex-linked genes are downregulated during meiosis in response to asynapsis of the heterogametic sex chromosome pair (meiotic sex chromosome inactivation; MSCI). Our understanding of this process has been limited to a handful of species, including mammals,Drosophila, andC. elegans.Based on findings from these taxa, MSCI has been viewed as likely a conserved process. However, in other groups like teleost fish, our understanding of this process is limited. Teleost fish are a noteworthy group to investigate because sex chromosomes can rapidly evolve between closely related species. Transcriptional profiling of spermatogenesis at the single-cell level is a useful approach to investigate whether MSCI occurs in other species with independently derived sex chromosomes. Here, we investigate whether MSCI occurs in the threespine stickleback fish (Gasterosteus aculeatus), which have an X and Y chromosome that evolved less than 26 million years ago. Using single-cell RNA-seq, we found that the X and Y chromosomes do not have a signature of MSCI, maintaining gene expression across meiosis. Using immunofluorescence, we also show the threespine stickleback do not form a condensed sex body around the X and Y, a conserved feature of MSCI in many species. We did not see patterns of gene content evolution documented in other species with MSCI. Y-linked ampliconic gene families were expressed across multiple stages of spermatogenesis, rather than being restricted to post-meiotic stages, like in mammals. Our work shows MSCI does not occur in the threespine stickleback fish and has not shaped the evolution of the Y chromosome. In addition, the absence of MSCI in the threespine stickleback suggests this process may not be a conserved feature of teleost fish and argues for additional investigation in other species.

Author Summary

As male germ cells enter meiosis, the X and Y chromosome of many species undergo a drastic repression of gene expression. In mammals, this process has been shown to be essential for fertility, and the expression of sex-linked genes can lead to meiotic arrest and cell death. This process has only been studied in a handful of organisms, which limits our understanding how conserved MSCI is across the tree of life. Teleost fish are an understudied group with many examples of independently derived sex chromosomes across closely related species. Here, we investigate whether MSCI occurs in the threespine stickleback fish, using single-cell transcriptional profiling. We found gene expression remains active throughout meiosis on the sex chromosomes, indicating MSCI does not occur. This indicates that MSCI is not a conserved feature of all taxa and is not an inevitable outcome of degenerating Y chromosomes.
Aspirin reduces the mortality risk of Acute Respiratory Failure: an observational study using the MIMIC IV database
Authors: Jiang Zhenhong , Lv Shijin , Zhang Guohu , Fu Zengyan
Published: November 2024

Background

Acute Respiratory Failure (ARF) is a serious complication of various diseases, characterized by a high mortality rate. Aspirin influences cyclooxygenase, which have a crucial role in inflammation, blood clotting, and immune system modulation. ARF is characterized by an uncontrolled inflammatory and pro-coagulant response, but aspirin can mitigate this inflammatory response by inhibiting platelet function, potentially leading to improved outcomes.Numerous studies have produced conflicting data concerning the impact of aspirin on individuals suffering from Acute Respiratory Failure. We performed an analysis of the MIMIC IV database to explore the association between aspirin use and the outcomes in ARF patients, as well as to ascertain the optimal dosing regimen for aspirin treatment.

Materials and methods

ARF patients’ clinical data were extracted from MIMICIV2.2. Propensity score matching was utilized to ensure comparability of baseline characteristics between the group receiving aspirin and the group not receiving aspirin. Subsequently, the link between aspirin and patient death was examined through the application of Kaplan-Meier estimations and Cox proportional hazard regression analyses.

Results

We identified a cohort of 6,663 individuals suffering from ARF from the MIMIC IV database.Following propensity score matching in a sample of 4,008 participants, multivariate Cox proportional hazards analysis revealed a lower hazard of dying within 90 days for those in the aspirin group versus the non-users group (adjusted Hazard Ratio: 0.723; 95% Confidence Interval: 0.652 to 0.802). Additionally, the Kaplan-Meier survival curves indicated that the 90-day survival rate was higher among aspirin users compared to non-users (log-rank test p< 0.001). And the median duration of survival for patients undergoing aspirin therapy was considerably extended compared to those who did not receive it, amounting to 15.60 days versus 10.36 days, respectively In the aspirin group, the median ICU stay length was longer than non-users group (6.93 days vs. 6.08 days, p <0.001).Patients in the aspirin use group had a significantly shorter duration of mechanical ventilation compared to those in the non-aspirin use group(54.95 days vs. 58.00 days, p <0.001).

Conclusion

Aspirin may reduce the 30-day or 90-day mortality risk in ARF patients and also shorten the duration of mechanical ventilation. Aspirin could be an effective medication in the treatment of ARF patients.
Vertical transmission of Dengue virus type-3 and metagenomic virome profiles ofAedes aegyptimosquitoes collected in Kisumu, Kenya
Authors: Wanjiru Tabitha , Bulimo Wallace , Langat Solomon , Kinyua Johnson , Odemba Nicholas , Yalwala Santos , Oullo David , Ochieng Richard , Ngere Francis , Kerich Gladys , Ambale Janet , Achieng Eunice , Abuom David , Egbo Timothy , Johnson Jaree , Ojwang Elly , Eads John , Garges Eric , Eyase Fredrick
Published: November 2024

Aedes aegyptiis the main vector of several arboviruses including chikungunya, dengue, yellow fever and Zika. Beyond arboviruses,Aedes aegyptiharbours insect-specific viruses (ISVs), which can modulate mosquito’s ability to transmit diseases by interfering with viral processes and triggering immune responses. Both arboviruses and ISVs can be transmitted vertically, where viruses are passed from parent to offspring. The lack of systematic molecular and entomological surveillance, has left the diversity of viruses in localAedes aegyptipopulations largely unexplored. This study aimed to characterize the viromes ofAedes aegyptimosquitoes from Kisumu, Kenya, focusing on viral diversity. Immature larvae and pupae were collected from Jua Kali area in Kisumu, reared into adults, and subjected to viral isolation by cell culture and metagenomic next-generation sequencing. RNA extraction, library preparation, and Illumina MiSeq sequencing were performed on CPE positive pools and metagenomic superpools. Initial data analysis was conducted using the CZ-ID platform, with quality control applied using PrinseqLite v0.20.4 to filter low-quality reads and remove adapters. De novo sequence assembly was performed with MEGAHIT v1.2.9, followed by BLAST analysis. Phylogenetic relationships were analyzed using the Maximum Likelihood method. A total of 2,142 femaleAedes aegypti, grouped into 86 pools and 4 superpools, were processed for cell culture and metagenomic next-generation sequencing respectively. Dengue virus type-3 was detected in one of the 86 pool. Additionally, a variety of ISVs were identified, including Iflaviruses related to Tesano Aedes Iflavirus (TeAV), Armigeres Iflavirus, and Negeviruses related to Rabai Virus. An unclassified virus closely related to Korle-Bu Aedes virus was also detected. Our study provides insights into the viral diversity withinAedes aegyptimosquitoes in Kisumu and evidence of natural vertical transmission, specifically transovarial transmission of dengue virus type-3. Ongoing research is imperative to unravel vertical transmission mechanisms and subtleties governing ISV-arbovirus interactions across diverse environmental settings.
Enhanced SNP Genotyping with Symmetric Multinomial Logistic Regression
Authors: Nielsen Malte B. , Eriksen Poul S. , Mogensen Helle S. , Morling Niels , Andersen Mikkel M.
Published: November 2024

In genotyping, determining Single Nucleotide Polymorphisms (SNPs) is standard practice, but it becomes difficult when analysing small quantities of input DNA, as is often required in forensic applications. Existing SNP genotyping methods, such as the HID SNP Genotyper Plugin (HSG) from Thermo Fisher Scientific, perform well with adequate DNA input levels but often produce erroneously called genotypes when DNA quantities are low. To mitigate these errors, genotype quality can be checked with the HSG. However, enforcing the HSG’s quality checks decreases the call rate by introducing more no-calls, and it does not eliminate all wrong calls. This study presents and validates a Symmetric Multinomial Logistic Regression (SMLR) model designed to enhance genotyping accuracy and call rate with small amounts of DNA. Comprehensive bootstrap and cross-validation analyses across a wide range of DNA quantities demonstrate the robustness and efficiency of the SMLR model in maintaining high call rates without compromising accuracy compared to the HSG. For DNA amounts as low as 31.25 pg, the SMLR method reduced the rate of no-calls by 50.0% relative to the HSG while maintaining the same rate of wrong calls, resulting in a call rate of 96.0%. Similarly, SMLR reduced the rate of wrong calls by 55.6% while maintaining the same call rate, achieving an accuracy of 99.775%. The no-call and wrong-call rates were significantly reduced at 62.5–250 pg DNA. The results highlight the SMLR model’s utility in optimising SNP genotyping at suboptimal DNA concentrations, making it a valuable tool for forensic applications where sample quantity and quality may be decreased. This work reinforces the feasibility of statistical approaches in forensic genotyping and provides a framework for implementing the SMLR method in practical forensic settings. The SMLR model applies for genotyping biallelic data with a signal (e.g. reads, counts, or intensity) for each allele. The model can also improve the allele balance quality check.
Enhancing Detection of Polygenic Adaptation: A Comparative Study of Machine Learning and Statistical Approaches Using Simulated Evolve-and-Resequence Data
Authors: Caliendo Cosima , Gerber Susanne , Pfenninger Markus
Published: November 2024

Detecting signals of polygenic adaptation remains a significant challenge in evolutionary biology, as traditional methods often struggle to identify the associated subtle, multi-locus allele-frequency shifts. Here, we introduced and tested several novel approaches combining machine learning techniques with traditional statistical tests to detect polygenic adaptation patterns. We implemented a Naive Bayesian Classifier (NBC) and One-Class Support Vector Machines (OCSVM), and compared their performance against the Fisher’s Exact Test (FET). Furthermore, we combined machine learning and statistical models (OCSVM-FET and NBC-FET), resulting in 5 competing approaches. Using a simulated data set based on empirical evolve-and-resequencingChironomus ripariusgenomic data, we evaluated methods across evolutionary scenarios, varying in generations and numbers of loci under selection. Our results demonstrate that the combined OCSVM-FET approach consistently outperformed competing methods, achieving the lowest false positive rate, highest area under the curve, and high accuracy. The performance peak aligned with the late dynamic phase of adaptation, highlighting the method’s sensitivity to ongoing selective processes and thus for experimental approaches. Furthermore, we emphasize the critical role of parameter tuning, balancing biological assumptions with methodological rigor. Our approach thus offers a powerful tool for detecting polygenic adaptation in pool sequencing data particularly from evolve-and-resequence experiments.

Author’s Summary

Organisms often adapt to environmental changes through polygenic adaptation - a process where multiple genes collectively contribute to evolutionary change. However, detecting these small shifts spread across multiple genes has been a persistent challenge for researchers. We developed new computational methods that combine machine learning with traditional statistical approaches to better detect these subtle genetic changes. Using data from a laboratory evolution experiment with the freshwater midgeChironomus riparius, we tested five different approaches to identify genes under selection. Our results showed that combining the machine learning technique One Class Support Vector Machines with a traditional statistical test (Fisher’s Exact Test) was particularly effective at identifying genes involved in adaptation. This combined approach excelled specifically in detecting ongoing adaptive changes while avoiding false positives. Our method provides a reliable tool for researchers studying evolutionary adaptation, particularly in laboratory evolution experiments where populations are tracked over multiple generations. This advancement facilitates improved understanding of how organisms adapt to new environments, which is increasingly important in the context of rapid environmental changes.
Assessing the impact of temperament on training efficiency inex-situRed Brocket Deer (Mazama americana)
Authors: Gragnanello Lara Caveanha , Cerezo Mariana Parra , Pizzutto Cristiane Schilbach , Paranhos da Costa Mateus José Rodrigues
Published: November 2024

The personality of wild animals has been extensively discussed due to its significant influence onex-situmanagement and conservation methods. However, there is still limited research directly addressing its impact on habituation and conditioning processes, which are essential techniques in conservation centers, zoos, and research institutions. This study aimed to demonstrate how individual personality variation affects training. We conducted the research at the Deer Research and Conservation Center of the Faculty of Agricultural and Veterinary Sciences, São Paulo State University, in Jaboticabal-SP, Brazil, with twelve red brocket deer (Mazama americana). Temperament tests were performed at the beginning of the study, assessing the animals’ reactivity to the presence of an unfamiliar human and during handling procedures. Following these tests, we initiated the processes of habituation and training of the animals. Three deer did not habituate to the trainer’s presence, being not subjected to operant conditioning; and four did it in just seven sessions. Among the nine deer that participated in the conditioning process, only five learned all the commands, representing a success rate of 41.66%. We concluded that more reactive animals, characterized as nervous and agitated, exhibited poorer performance in training. In contrast, less reactive animals, which were calmer and either allowed to approach or approached voluntarily an unfamiliar person, learned the commands more effectively.
Characterizing neuronal and population responses to electrical stimulation in the human hippocampo-cortical network
Authors: van der Plas Mircea , Roux Frederic , Chelvarajah Ramesh , Sawlani Vijay , Staresina Bernhard , Wimber Maria , Rollings David T. , Hanslmayr Simon
Published: November 2024

Direct electrical stimulation (DES) can advance our understanding of the intricate dynamics of the human hippocampo-neocortical network, which underlies complex cognitive processes such as spatial cognition and memory. This knowledge can help Neurotechnology to more effectively interface with this network and improve its functions. Here, we investigated the effects of DES in seven epilepsy patients under medical supervision recording single neuron activity alongside local field potentials to investigate neural responses to single pulses at different levels of granularity. Our results demonstrate that (i) single neurons respond to local electrical stimulation with a stereotypical pattern of short-lived increased excitation, followed by sustained inhibition, (ii) that input into the hippocampus from neocortex takes ∼100 ms, and (iii) that output from the hippocampus to the neocortex is gated by theta phase. These results are vital to inform the optimal choice of parameters for future electrical stimulation studies targeting the human memory system.
Convergent mechanisms, divergent strategies: a comparison of nectar intake between a generalist and a specialized bat species
Authors: Quinche Laura L. , Garzón-Agudelo Felipe , Santana Sharlene E. , López-Arévalo Hugo F. , Rico-Guevara Alejandro
Published: November 2024

Nectar-feeding bats exhibit a range of specialized adaptations that allow them to efficiently extract nectar from flowers. These adaptations include diverse tongue morphological traits and feeding strategies that reflect varying degrees of specialization for nectarivory. While the feeding mechanisms of highly specialized nectar-feeding bats are well-studied, little is known about the feeding behaviors of non-specialized species likePhyllostomus discolor. This study compares the nectar extraction behaviors ofP. discolorand the specializedAnoura geoffroyi, examining morphological and biomechanical adaptations that affect nectar-feeding efficiency and foraging strategies. Using high-speed videography, we analyzed the feeding behaviors of both species, focusing on tongue kinematics, and feeding efficiency. Both species used a brush-tongue lapping technique but exhibited notable behavioral and kinematic differences, resulting in efficiency variations.P. discolorhas a shorter, less flexible tongue thanA. geoffroyi, though its tongue shows similar mobility capacities (licking frequency). UnlikeA. geoffroyi, which hovers to feed,P. discolorlands, allowing for longer visits and greater nectar extraction per visit. However,P. discolordemonstrated lower feeding efficiency, likely due to its reduced tongue specialization for nectarivory. These findings reveal convergence in the general feeding mechanism but highlight differences in morphological and behavioral specialization that affect feeding kinematics and efficiency. Our study illuminates how foraging strategy and tongue morphology impact feeding efficiency, pointing to evolutionary pathways that promote niche differentiation within nectar- feeding bat communities.
Unraveling Microglial Spatial Organization in the Developing Human Brain with DeepCellMap, a Deep Learning Approach Coupled to Spatial Statistics
Authors: Perochon Theo , Krsnik Zeljka , Massimo Marco , Ruchiy Yana , Romero Alejandro Lastra , Mohammadi Elyas , Li Xiaofei , Long Katherine R , Parkkinen Laura , Blomgren Klas , Lagache Thibault , Menassa David A , Holcman David
Published: November 2024

Mapping cellular organization in the developing brain presents significant challenges due to the multidimensional nature of the data, characterized by complex spatial patterns that are difficult to interpret without high-throughput tools. We developed DeepCellMap, a deep-learning-assisted tool that integrates multi-scale image processing with advanced spatial and clustering statistics. This pipeline was designed to map microglial organization during normal and pathological brain development but can be adapted to any cell type. Using DeepCellMap, we capture the morphological diversity of microglia, identify strong coupling between proliferative and phagocytic phenotypes, and show that distinct spatial clusters rarely overlap as human brain development progresses. Additionally, we uncover a novel association between microglia and blood vessels in fetal brains exposed to maternal SARS-CoV-2. These findings offer insights into whether various microglial phenotypes form networks in the developing brain to occupy space, and in conditions involving haemorrhages, whether microglia respond to, or influence changes in blood vessel integrity. DeepCellMap is available as open-source software and is a powerful tool for extracting spatial statistics and analyzing cellular organization in large tissue sections, accommodating various imaging modalities. This platform could open new avenues for studying brain development and related pathologies.
Deep learning super-resolution of paediatric ultra-low-field MRI without paired high-field scans
Authors: Briski Ula , Bourke Niall J. , Donald Kirsten A. , Bradford Layla E. , Williams Simone R. , Zieff Michal R. , Deoni Sean C.L. , Williams Steven C.R. ,   Khula South Africa Study Team, Moran Rosalyn J. , Baljer Levente , Váša František
Published: November 2024

Brain magnetic resonance imaging (MRI) is essential for diagnosis and neurodevelopmental research, but the high cost and infrastructure demands of high-field MRI scanners restrict their use to high-income settings. To address this, more affordable and energy-efficient ultra-low-field MRI scanners have been developed. However, the reduced resolution and signal-to-noise ratio of the resulting scans limit their clinical utility, motivating the development of super-resolution techniques. The current state-of-the-art super-resolution methods require either three anisotropic ultra-low-field scans acquired at different orientations (axial, coronal, sagittal) to reconstruct a higher-resolution image using multi-resolution registration (MRR), or the training of deep learning super-resolution models using paired ultra-low- and high-field scans. Since acquiring three high-quality ultra-low-field scans is not always feasible, and paired high-field data may not be available for the target population, this study explores the efficacy of using a deep learning model, the 3D UNet, to generate higher-resolution brain scans from just one ultra-low-field scan. The model was trained to receive a single ultra-low-field brain scan of 6-month-old infants and produce a scan of MRR quality. Results showed a significant improvement in the quality of output scans compared to input scans, including increased image quality metrics, stronger correlations in tissue volume estimates across participants, and greater Dice overlap of the underlying tissue segmentations to those of target scans. The study demonstrates that the 3D UNet effectively enhances the resolution of ultra-low-field infant MRI scans. Generating higher-resolution brain scans from single ultra-low-field scans, without needing paired high-field data, reduces scanning time and supports wider MRI use in low- and middle-income countries. Additionally, this approach allows for easier model training on a site- and population-specific basis, enhancing adaptability in diverse settings.
Optimizing longitudinal spin relaxation in miniaturized optically pumped magnetometers
Authors: McWilliam A.P. , Dyer S. , Hunter D. , Mrozowski M. , Ingleby S.J. , Sharp O. , Burt D.P. , Griffin P.F. , McGilligan J.P. , Riis E.
Published: December 2024

The microfabrication of cesium vapor cells for optically pumped magnetometry relies on optimization of buffer gas pressure in order to maximize atomic coherence time and sensitivity to external magnetic signals. We demonstrate post-bond nitrogen buffer gas pressure tuning through localized heating of an integrated micropill dispenser. We characterize the variation in the intrinsic longitudinal relaxation rate, γ10, and magnetic sensitivity, as a function of the resulting nitrogen buffer gas pressure. Measurements are conducted by employing an optically pumped magnetometer operating in a free-induction-decay configuration. γ10 is extracted across a range of nitrogen pressures between 60 and 700 torr, measuring a minimum of 140 Hz at 115 torr. In addition, we achieve sensitivities as low as 130 fT/Hz at a bias field amplitude of

about

50

μ

T

. With the optimal nitrogen buffer gas pressure now quantified and achievable post-fabrication, these mass-producible cells can be tailored to suit a variety of sensing applications, ensuring peak magnetometer performance.

Published by the American Physical Society
2024
Fuzzy repetitive scheduling for construction projects considering risk preferences and time-cost tradeoffs
Authors: Zou Xin , Zhang Lihui
Published: November 2024

Purpose

The purpose of this study is to develop a novel approach that addresses time-cost tradeoffs in repetitive construction projects while considering the uncertainty in activity durations and the risk preferences of planners.

Design/methodology/approach

Our study involves work in three aspects. Firstly, it employs triangular fuzzy numbers to represent activity durations in different units, which facilitates the management of scenarios characterized by limited historical data or the presence of ambiguous information. Secondly, it introduces a fuzzy chance-constrained programming model, which is aimed at minimizing the project budget while ensuring that the risks associated with cost overruns and schedule delays are confined to specified limits. Thirdly, it advances an enhanced genetic algorithm, integrating an electromagnetism-like mechanism and a scheduling repair process, to improve the efficiency and effectiveness of the optimization process.

Findings

A real-life street renovation project was analyzed to demonstrate the applicability of the proposed algorithm. The analysis explored three common types of risk preferences: risk-averse, risk-neutral and risk-loving. The results indicate that the proposed algorithm surpasses existing fuzzy repetitive scheduling methods in terms of risk management. It effectively generates schedules that align with the risk preferences of planners and provides worst-case estimates of project performance.

Originality/value

This research makes a significant contribution to the field by developing a fuzzy chance-constrained programming model and an associated optimization algorithm that is specifically designed for time-cost tradeoffs in repetitive construction projects. A key distinction is that this study considers the risk preferences of planners, which sets it apart from previously developed models. As a result, it provides a practical approach for effective risk management.
Fresh start mindset and attitudes toward the banks: the mediating role of optimism judgment bias and face arousal
Authors: Junior Ladeira Wagner , Azhar Mohd , Rasul Tareq , Santini Fernando
Published: November 2024

Purpose

This paper aims to analyze the effects of a fresh start mindset on attitudes toward the banks. Furthermore, we try to predict how optimism judgment bias and arousal can affect the effects of the fresh start mindset through three research questions.

Design/methodology/approach

Three experiments explored the effect of the fresh start mindset in the banking sector. Study 1 collects data in a laboratory. Study 2 is an online experiment. Study 3 collects data in a laboratory through facial movements.

Findings

Our results clarify research gaps in studies regarding financial decisions by demonstrating that a fresh start mindset increases attitudes toward banks. In this way, a fresh start mindset can influence the optimism judgment bias by promoting underlying mechanisms that highlight the change through new paths regardless of past or present, thus promoting positive attitudes. Our results also confirm a hypothesis that stimulation of a new reality can generate arousal in cognitive processing and consumers’ willingness to interact.

Practical implications

Understand how campaigns and nudges around fresh starts can increase marketing campaigns’ success and help customers improve their financial well-being.

Originality/value

Our paper demonstrates how previous studies in the banking sector have neglected the fresh start mindset and offers mechanisms to understand the effects of optimism judgment bias and phasic arousal expression on attitudes toward the banks.
What’s driving them? A qualitative approach to explore women entrepreneurs’ motivations in STEM
Authors: Voss Julia , Butz Benjamin , Ettl Kerstin
Published: December 2024

Purpose

Entrepreneurship and the disciplines of science, technology, engineering and mathematics (STEM) are considered important drivers of innovation. At the same time, the representation of women entrepreneurs in STEM remains low. Despite this disparity, a number of women still choose to start ventures and persist in pursuing their innovations in STEM. This study aims to examine the motivational factors that drive women entrepreneurs to approach and consistently pursue their innovations and ventures in STEM.

Design/methodology/approach

Drawing on the concept of the heterogeneity of motivational factors (Graham and Bonner, 2022) and Social Cognitive Theory (Bandura, 1986, 2001; Wood and Bandura, 1989), 24 semi-structured interviews were conducted with women entrepreneurs in STEM. This approach allowed for an in-depth exploration of the heterogeneous motivational factors influencing women entrepreneurs in STEM.

Findings

The motivations of women entrepreneurs in STEM are multifaceted, interrelated and dynamic. They encompass personal and cognitive, behavioral and environmental factors and partly change over time. This study reveals two levels of heterogeneity: the heterogeneity of women entrepreneurs’ entrepreneurial motivations, and the within-context heterogeneity of women entrepreneurs in STEM themselves.

Originality/value

This study addresses the need for a deeper understanding of women entrepreneurs in STEM. By focusing on nuanced aspects of entrepreneurial motivations that are often overlooked in the existing literature, this research provides valuable insights and discusses implications for theory, policy and education.
The interplay of safety knowledge, attitude and health experience in adoption of protective pesticide behavior: evidence from Pakistani fruit and vegetable farmers
Authors: Imran Muhammad , Mustafa Ghulam , Rehman Shafique Ur , Yasri Yasri
Published: December 2024

Purpose

This study aims to examine the unique and interaction effects of farmers’ pesticide safety knowledge and their past pesticide-related health problems experienced in the adoption of protective pesticide behaviors. The study further aims to explore whether attitude toward pesticide use mediate the relationship between pesticide safety knowledge and protective behaviors.

Design/methodology/approach

Data were collected from 385 Pakistani fruit and vegetable farmers using a cross-sectional survey design and were analyzed using Partial least squares structural equation modeling (PLS-SEM).

Findings

The empirical analysis revealed that pesticide safety knowledge is positively associated with protective behaviors and farmers’ attitude toward pesticide use partially mediates this relationship. The findings further show that past health problems positively influence the adoption of protective pesticide behaviors, which is amplified when pesticide safety knowledge is high.

Research limitations/implications

This study findings have significant implications for policy interventions and agricultural extension programs aimed at promoting safer pesticide use.

Originality/value

This research contributes to the previous literature by presenting an integrative framework of the knowledge-attitude-practice model and protection motivation theory to explore the influence of farmers’ pesticide safety knowledge, past pesticide-related health experiences and attitude toward pesticide use on their adoption of protective pesticide behaviors.
The role of AI-enabled health systems in the Jordanian context: the case of digital contact tracing apps
Authors: Al-Okaily Manaf , Shiyyab Fadi Shehab , Salim Nesreen A. , Al-Rahayfeh Amer
Published: December 2024

Purpose

Digital health or digital healthcare, is a broad, multidisciplinary concept that includes concepts from an intersection between technology and healthcare. Digital health applies digital transformation to the healthcare field, incorporating software, hardware and services. The usefulness of digital health technologies such as digital contact tracing apps (CTAs) depends deeply on the acceptance to use them. Accordingly, the main purpose of this study is to explore the usage of CTAs by integrating the protection motivation theory (PMT) and technology acceptance model (TAM) in the Jordanian context.

Design/methodology/approach

Partial least squares structural equation modelling was employed to test empirically the integrated research model against data collected from 420 respondents, leading to the identification of the important determinants for the usage of CTAs.

Findings

The results reveal that perceived severity and perceived vulnerability have a significant positive impact on the perceived need for CTAs, which, in turn, affects the individuals’ intention to use CTAs. It also reveals that perceived trust in government, perceived privacy and perceived usefulness have a significant positive impact on individuals’ intention to use CTAs, which, in turn, affects the usage of CTAs. In contrast, perceived ease of use did not find any significant relationship, and hence hypothesis H7 was not supported. Lastly, social media awareness has a significant positive impact on perceived usefulness and ease of use.

Originality/value

This study is considered among the first studies in the Jordanian context that integrate the PMT and TAM to gain a better understanding of the critical determinants for the acceptance and usage of CTAs in the context of pandemics.
Gender, anxiety and perceived Islamic values in students’ debt attitudes and behaviour: an ethnographic study of an Indonesian multicultural university
Authors: Rahadi Ashri Putri , Koesrindartoto Deddy Priatmodjo , Wisesa Anggara
Published: December 2024

Purpose

To mitigate debt repayment ability in underbanked borrowers such as students, debt attitude is used as an initial approach. This study aims to focus on how students’ debt attitudes and behaviours are shaped from a cultural point of view.

Design/methodology/approach

Through qualitative research in one of Indonesia’s multicultural universities, ethnography was used to elicit a stable dominant cultural factor that shapes students’ debt attitudes and behaviours.

Findings

Perceived Islamic values were found to induce debt anxiety but to encourage positive coping strategies such as prioritising debt repayment, minimising consumption and spending and avoiding shirking one’s responsibilities.

Research limitations/implications

Debt is a complex issue, and the authors have simply examined the impact of religion on attitudes and behaviours. Nonetheless, other important variables are considered in the literature, such as family and a debt-friendly atmosphere. This research was constrained by time and finance, so it only relates to ITB students. Additionally, understanding why women were more likely to be anxious because of their embracing of debt-related Islamic values from a religious point of view is absent in the literature, and thus requires future investigation.

Practical implications

The findings offer two practical implications. Firstly, this study could improve the credit assessment process to detect debt anxiety more accurately because the causality of anxiety is known. Furthermore, when detecting debt-relax, creditors may demand a higher financial literacy score to minimise non-payment. Secondly, with regard to financial literacy, Indonesians exhibit low levels, with only 32% considered to be financially literate according to the 2020 OECD assessment. By recognising the stable cultural factor influencing debt attitudes and behaviours, educators, creditors and policymakers can enhance financial literacy programme efficiency with participants’ religious values.

Social implications

In the context of limited financial literacy, Islamic values can be beneficial for society because their perception and practice could induce debt anxiety while generating positive anxiety-coping mechanisms identified as anti-debt behaviours.

Originality/value

Previous research has found correlations between religiosity and attitudes, as well as between gender and attitudes, towards debt. However, to the best of the authors’ knowledge, this study is the first to demonstrate that perceived religiosity causes anti-debt attitudes and behaviours, which is more evident in anxiety-prone women. The findings answer the calls of Harrison et al. (2013, 2015), Harrison and Agnew (2016) and Kettley et al. (2008) to understand why women possess an aversion to taking on debt, especially from the point of view of cultural and societal norms, as posited by Meyll and Pauls (2019).
Focused literature review on accreditation and quality assurance: insights and future research agenda
Authors: Kumar Atul , Paliwal Jaiprakash , Singh Mahesh , Pendse Vishwas , Gade Rajesh , Palav Manesh , Raibagkar Shirish
Published: December 2024

Purpose

Accreditation, a proven quality strategy, can help educational institutions at all levels in attaining Sustainable Development Goal 4 (SDG4). The purpose of this study, therefore, is to gain insights from the literature on accreditation and quality assurance and understand the focus areas of existing research. The study also aims at finding out research gaps that would serve as future research agenda.

Design/methodology/approach

A focused literature review methodology was adopted. Based on the search terms “accreditation and quality assurance”, 54 literature items were finally selected for review from standard databases like Scopus, Web of Science and Google Scholar.

Findings

Five overarching focus dimensions emerged from the focused review. These were overview studies, accreditation system-based studies, the role of accreditation in quality assurance, the impact of accreditation on quality assurance and other studies. Major gaps in reviews were also found.

Originality/value

The study provides valuable theoretical and practical insights about accreditation and quality assurance and also lays the road map for future research to address the research gaps.
The ultrastructural and proteomic analysis of mitochondria‐associated endoplasmic reticulum membrane in the midbrain of a Parkinson's disease mouse model
Authors: Liu Jin , Liu Yi , Gao Chao , Pan Hong , Huang Pei , Tan Yuyan , Chen Shengdi
Published: November 2024

Recent studies indicated that the dysregulation of mitochondria‐associated endoplasmic reticulum membrane (MAM) could be a significant hub in the pathogenesis of Parkinson's disease (PD). However, little has been known about how MAM altered in PD. This study was aimed to observe morphological changes and analyze proteomic profiles of MAM in 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐induced PD mouse models. In MPTP‐treated mice, transmission electron microscopy was applied for MAM ultrastructural visualization. Nano ultra‐high performance liquid chromatography‐tandem mass spectrum and bioinformatic analysis were adopted to obtain underlying molecular data of MAM fractions. The loosened, shortened and reduced MAM tethering was found in substantia nigral neurons from MPTP‐treated mice. In midbrain MAM proteomics, 158 differentially expressed proteins (DEPs) were identified between two groups. Specific DEPs were validated by western blot and exhibited significantly statistical changes, aligning with proteomic results. Bioinformatic analysis indicated that membrane, cytoplasm and cell projection were three major localizations for DEPs. Biological processes including metabolism, lipid transport, and immunological and apoptotic signaling pathways were greatly affected. For consensus MAM proteins, the enriched pathway analysis revealed the potential relationship between neurodegenerative diseases and MAM. Several biological processes such as peroxisome function and clathrin‐mediated endocytosis, were clustered, which provided additional insights into the fundamental molecular pathways associated with MAM. In our study, we demonstrated disrupted ER‐mitochondria contacts in an MPTP‐induced PD mouse model. The underlying signatures of MAM were revealed by proteomics and bioinformatic analysis, providing valuable insights into its potential role in PD pathogenesis.
Initiation of Antipsychotics During the First Year After First‐Episode Psychosis: A Population‐Based Study
Authors: Odsbu I. , Hamina A. , Hjellvik V. , Handal M. , Haram M. , Tesli M. , Tanskanen A. , Taipale H.
Published: November 2024

Background

Antipsychotics are recommended after first‐episode psychosis. Knowledge on the current use patterns in real‐world settings is thus important to inform clinical practice. We aimed to describe antipsychotic initiation during 1 year after first‐episode psychosis and its associated factors.

Methods

Population‐based cohort study using linked nationwide health and population registers from Norway. The study population comprised 8052 persons aged 16–45 years with first‐episode psychosis diagnosed in secondary care (ICD‐10 F20, F22–F29) in the period 2011–2019. Initiation of antipsychotic use was defined as being dispensed antipsychotics (ATC N05A, excl. lithium) at least once from −90 to +365 days from secondary care diagnosis of first‐episode psychosis. Antipsychotic polypharmacy during follow‐up was defined as having at least 90 days with overlapping drug use periods modeled using the Prescriptions to Drug Use Periods method. Adjusted risk ratios (aRRs) with 95% confidence intervals (CIs) for the association between socioeconomic and clinical factors and initiation of antipsychotic use were calculated using modified Poisson regression.

Results

In total, 4413 persons (54.8%) initiated antipsychotic use after first‐episode psychosis with proportions ranging from 45.5% in 2012 to 62.1% in 2019. Oral formulations of olanzapine (34.9%), quetiapine (21.2%), and aripiprazole (11.6%) were most common at initiation, whereas long‐acting injectables (LAIs) and clozapine were rarely used. Among the initiators, 13.8% started a polypharmacy period lasting more than 90 days. Factors associated with antipsychotic initiation were lower age (aRR 1.14, 95% CI 1.08–1.21; 26–35 years vs. 36–45 years), higher education (1.11, 1.05–1.18), being employed (1.04, 1.00–1.09), being hospitalized (1.13, 1.09–1.18), being diagnosed late in the study period (1.16, 1.11–1.22; 2017–2019 vs. 2011–2013), or with previously diagnosed bipolar disorder, depression, or anxiety disorders.

Conclusions

The antipsychotic use pattern is largely within the current clinical guideline. Primary non‐compliance and disease severity may explain the socioeconomic and clinical differences related to initiation of antipsychotic use.
Insights into cosmetic ingredients in the late Northern Song dynasty: A case study from the Shijiatang tomb, southern China
Authors: Han Bin , Zheng Duo , Huang Dujun , Wang Jiamin , Wang Lyuting , Zhang Zixin , Jia Xin , Yang Yimin
Published: December 2024

The Song dynasty (970–1279 CE) was an era of a prosperous commodity economy, culture and education in China history, with various descriptions of cosmetic usage. However, archaeological evidence for cosmetic application during this period was rare, which hindered comprehensive understanding. During the excavation of the Shijiatang cemetery, two small and exquisite porcelain containers with suspected cosmetics were unearthed from tomb M50, which belonged to a female with an established social position. In this study, ATR‐FTIR, SEM, GC/MS, Py‐GC/MS and GC‐C‐IRMS were used to characterize the residue inside the container, and the results demonstrate that the residue is made of minerals, non‐ruminant animal adipose fat and plant ingredients. In particular, the detection of arundoin and cylindrin indicates that the herbal medicine plant Bai Mao (Imperata cylindrica) was likely used as a cosmetic ingredient by the noble class of the Song dynasty. This study provides a precious example of cosmetic production in the Song dynasty and, together with the prevalence of cosmetic use described in historical records, suggests a boom in the cosmetics industry during that period. Furthermore, the exploitation of natural herbal ingredients reflects a master of herbal knowledge and a trend to use natural products to aid in maintaining beauty.
In‐field prostate cancer recurrence following radical prostatectomy and salvage radiation
Authors: Martin Austin , Mahmoud Ahmed M. , Britton Cameron J. , Fadel Anthony , Ahmed Mohamed E. , Sharma Vidit , Childs Daniel S. , Johnson Geoffrey B. , Davis Brian J. , Mynderse Lance , Lomas Derek , Woodrum David , Frendl Daniel , Karnes Jeffrey R. , Tollefson Matthew K. , Kwon Eugene D. , Andrews Jack R.
Published: November 2024

Objective

To define the natural history, patterns of recurrence and treatment modalities for local prostate cancer (PCa) recurrence following radical prostatectomy (RP) and radiation therapy (RT), and to investigate factors that could predict metastasis‐free survival (MFS) in this unique patient population.

Methods

We queried a prospectively maintained PCa registry to identify men developing in‐field recurrence (IFR) following RP and RT from 2008 to 2021 at a single institution. IFR was defined as biopsy‐proven recurrent PCa or the presence of persistent positron emission tomography‐avid lesions in the prior radiation field without evidence of metastasis. Cox regression was conducted to determine predictors of MFS. Kaplan–Meier methods were used to calculate MFS, cancer‐specific survival (CSS) and overall survival (OS) for patients in three primary therapy categories: cryoablation, androgen deprivation therapy (ADT) alone, and surveillance.

Results

Of 4575 patients from our registry, 108 (2.3%) with IFR were identified. The median (interquartile range [IQR]) time to IFR from salvage treatment was 78 (50–126) months. A total of 29 patients (26%) were managed with cryoablation, 23 (21%) with ADT, and 28 (25%) with surveillance. The median (IQR) follow‐up was 76 (48–100) months. There were no statistically significant differences in MFS (P = 0.67) or OS (P = 0.07) among the three primary treatment cohorts. Patients treated with ADT or cryoablation had longer CSS compared to patients managed with surveillance (P = 0.047).

Conclusions

We found that IFR may present years after completion of primary treatment for PCa. While curative management strategies may be attempted, local and distant metastatic recurrence is common and often requires systemic therapy.
Association between insulin‐associated gene polymorphisms and new‐onset diabetes mellitus in statin‐treated patients
Authors: Park Minju , Kim Jung Sun , Park Yoon‐A , Lee Da Hoon , Choi Seo‐A , Chang Yoonkyung , Song Tae‐Jin , Gwak Hye Sun , Yee Jeong
Published: November 2024

Background

While statins are effective at managing lipid levels, there is growing evidence for new‐onset diabetes mellitus (NODM). The insulin signalling pathway (ISP) inhibited by statins is one of the potential mechanisms; however, most studies have been limited to in vitro settings. Therefore, this study aimed to identify the genetic associations within the ISP‐related genes and NODM.

Methods

We performed a retrospective analysis of samples collected prospectively from February 2021 to May 2021. Among ISP‐related genes, we selected 11 candidate genes (IGF1, IGF2, IGF1R, INSR, IRS1, IRS2, PIK3CA, PIK3CB, PIK3R1, AKT1 and AKT2). An additional analysis was conducted comparing patients with DM prior to statin therapy and controls to determine whether the single nucleotide polymorphisms (SNPs) are specific to statin.

Results

A total of 602 patients were analysed, including 71 (11.8%) with statin‐induced NODM. After adjustment, IGF1R rs2715439, INSR rs1799817, INSR rs2059807 and PIK3R1 rs3730089 were found to be independently associated with NODM. In an additional analysis, all SNPs that demonstrated an association with statin‐induced NODM lost their significance in patients with DM prior to statin therapy.

Conclusion

This study revealed the ISP‐related genetic effects, specifically involving genes such as INSR, IGF1R and PIK3R1, in the development of statin‐induced NODM. Our findings suggest a potential mechanism of statin‐induced NODM related to ISP‐related genetic variants.