bluuebunny/crossref_metadata_2025 huggingface dataset:
Mediation of mammalian olfactory response by presence of odor-evoked potassium current
Authors: Hagerty Samantha , Pustovyy Oleg , Globa Ludmila , Vodyanoy Vitaly , Singletary Melissa
Published: October 2024

It is well understood that odorants interact with specialized G-protein coupled receptors embedded in the ciliary membrane of olfactory sensory neurons (OSN) which initiates a voltage-generating intracellular cascade of signal transduction events that can be recorded at the epithelial level as an electroolfactogram (EOG). While the depolarizing excitatory pathway in vertebrates involving cyclic adenosine monophosphate (cAMP)-induced Na+/Ca2+ influx and calcium-induced Cl− efflux is well established, there is evidence of potassium-associated inhibitory currents that correspond with cellular activation. While several Ca2+-dependent feedback mechanisms contribute to cellular deactivation which have been commonly attributed to these inhibitory currents, the frequently observed positive ionic conductance prior to excitatory depolarization have led many to suggest an additional earlier inhibitory mechanism at the receptor level that may be independent of downstream calcium influx. Due to conflicting conclusions, the role and mechanism behind Ca2+-independent inhibitory currents in olfactory cells is not fully understood. We investigated the functional and temporal involvement of potassium channels in odor transduction by comparing electroolfactogram (EOG) recordings in rat olfactory epithelia following ion channel inhibition and targeted activation of downstream components with or without potassium-blocking. Several K+-channel blocking agents (4-Aminopyridine, charybdotoxin, & iberiotoxin) demonstrated a diminished pre-action potential positive current that corresponded with reduced excitatory response to odor stimulation that was recovered when blockers were removed. We further assessed EOG responses in the absence of odor or with odor response enhancing zinc nanoparticles. Chemically eliciting membrane excitation in the absence of odor stimulation with a phosphodiesterase inhibitor, 3-isobutyl-1-methylxanthine (IBMX), in combination with K+-channel inhibition, further indicated potassium channel activation precedes excitatory events and is independent of cAMP-induced calcium influx. These results support previous findings of odor-activated inhibitory potassium currents that may play a functional role in subsequent G-protein activity.
Friend or foe? Early life adversity to improve farmed animal welfare
Authors: Campbell Dana L. M.
Published: October 2024

Early life experiences can have lasting impacts on an animal’s development. Extensive research evidence aligns across both human and non-human rodent and primate laboratory animals showing negative impacts of early life adversity such as impairments in neurological and behavioural development. Farmed animals experience a range of adversities across their production lifetimes, often early in life, including species atypical social groupings, invasive husbandry procedures, and transport. Correspondingly, farmed animals also demonstrate a wide range of impairments such as stereotypic, injurious, and other abnormal behaviours. An individual, however, needs to experience adversity to be able to develop resilience and coping mechanisms that facilitate dealing with challenges later in life. Not all individuals will experience stress vulnerability following adversity, with some individuals instead developing stress resilience. This mini review collates evidence on the positive effects of early life adversity on improving adaptability in farmed species, both terrestrial and aquatic. While evidence across farmed animal species is currently much less than for humans, laboratory rodents or non-human primates, similar patterns emerge where mild adversity early in life, can improve the adaptability of the animal in the face of future stressors. Many views of optimised welfare posit that farmed animals should be housed in as natural environments as possible to limit many of the typical adversities they face. However, strategic mild exposure to early life adversity may facilitate improved animal welfare under intensive commercial farming conditions. Future research into this area could provide management tools to better predict and promote stress resilience over stress vulnerability.
CRISPR-Cas9/Cas12a systems for efficient genome editing and large genomic fragment deletions in Aspergillus niger
Authors: Yuan Guoliang , Deng Shuang , Czajka Jeffrey J. , Dai Ziyu , Hofstad Beth A. , Kim Joonhoon , Pomraning Kyle R.
Published: October 2024

CRISPR technology has revolutionized fungal genetic engineering by accelerating the pace and expanding the feasible scope of experiments in this field. Among various CRISPR-Cas systems, Cas9 and Cas12a are widely used in genetic and metabolic engineering. In filamentous fungi, both Cas9 and Cas12a have been utilized as CRISPR nucleases. In this work we first compared efficacies and types of genetic edits for CRISPR-Cas9 and -Cas12a systems at the polyketide synthase (albA) gene locus in Aspergillus niger. By employing a tRNA-based gRNA polycistronic cassette, both Cas9 and Cas12a have demonstrated equally remarkable editing efficacy. Cas12a showed potential superiority over Cas9 protein when one gRNA was used for targeting, achieving an editing efficiency of 86.5% compared to 31.7% for Cas9. Moreover, when employing two gRNAs for targeting, both systems achieved up to 100% editing efficiency for single gene editing. In addition, the CRISPR-Cas9 system has been reported to induce large genomic deletions in various species. However, its use for engineering large chromosomal segments deletions in filamentous fungi still requires optimization. Here, we engineered Cas9 and -Cas12a-induced large genomic fragment deletions by targeting various genomic regions of A. niger ranging from 3.5 kb to 40 kb. Our findings demonstrate that targeted engineering of large chromosomal segments can be achieved, with deletions of up to 69.1% efficiency. Furthermore, by targeting a secondary metabolite gene cluster, we show that fragments over 100 kb can be efficiently and specifically deleted using the CRISPR-Cas9 or -Cas12a system. Overall, in this paper, we present an efficient multi-gRNA genome editing system utilizing Cas9 or Cas12a that enables highly efficient targeted editing of genes and large chromosomal regions in A. niger.
Effective and new technologies in kidney tissue engineering
Authors: Rayat Pisheh Hossein , Haghdel Mobin , Jahangir Mahboube , Hoseinian Monireh Sadat , Rostami Yasuj Shaghayegh , Sarhadi Roodbari Ali
Published: October 2024

Kidney disease encompasses a wide spectrum of conditions, ranging from simple infections to chronic kidney disease. When the kidneys are unable to filter blood and remove waste products, these abnormalities can lead to kidney failure. In severe cases of kidney failure, kidney transplantation is considered the only definitive treatment. Worldwide, the World Health Organization (WHO) repeatedly emphasizes the importance of organ donation and increasing transplantation rates. Many countries implement national programs to promote the culture of organ donation and improve patient access to kidney transplantation. The extent to which this procedure is performed varies across countries and is influenced by several factors, including the volume of organ donation, medical infrastructure, access to technology and health policies. However, a kidney transplant comes with challenges and problems that impact its success. Kidney tissue engineering is a new approach that shows promise for repairing and replacing damaged kidney tissue. This article reviews recent advances in kidney tissue engineering, focusing on engineered structures such as hydrogels, electrospinning, 3D bioprinting, and microfluidic systems. By mimicking the extracellular environment of the kidney, these structures provide suitable conditions for the growth and development of kidney cells. The role of these structures in the formation of blood vessels, the mimicry of kidney functions and the challenges in this field were also discussed. The results of this study show that kidney tissue engineering has high potential for treating kidney diseases and reducing the need for kidney transplantation. However, to achieve clinical application of this technology, further research is required to improve the biocompatibility, vascularization and long-term performance of engineered tissues.
Current advances in the development of microRNA-integrated tissue engineering strategies: a cornerstone of regenerative medicine
Authors: Castañón-Cortés Luis Germán , Bravo-Vázquez Luis Alberto , Santoyo-Valencia Grecia , Medina-Feria Sara , Sahare Padmavati , Duttaroy Asim K. , Paul Sujay
Published: October 2024

Regenerative medicine is an innovative scientific field focused on repairing, replacing, or regenerating damaged tissues and organs to restore their normal functions. A central aspect of this research arena relies on the use of tissue-engineered scaffolds, which serve as structural supports that mimic the extracellular matrix, providing an environment that orchestrates cell growth and tissue formation. Remarkably, the therapeutic efficacy of these scaffolds can be improved by harnessing the properties of other molecules or compounds that have crucial roles in healing and regeneration pathways, such as phytochemicals, enzymes, transcription factors, and non-coding RNAs (ncRNAs). In particular, microRNAs (miRNAs) are a class of tiny (20–24 nt), highly conserved ncRNAs that play a critical role in the regulation of gene expression at the post-transcriptional level. Accordingly, miRNAs are involved in a myriad of biological processes, including cell differentiation, proliferation, and apoptosis, as well as tissue regeneration, angiogenesis, and osteogenesis. On this basis, over the past years, a number of research studies have demonstrated that miRNAs can be integrated into tissue-engineered scaffolds to create advanced therapeutic platforms that precisely modulate cellular behavior and offer a controlled and targeted release of miRNAs to optimize tissue repair and regeneration. Therefore, in this current review, we discuss the most recent advances in the development of miRNA-loaded tissue-engineered scaffolds and provide an overview of the future outlooks that should be aborded in this area of study in order to lay the groundwork for the clinical translation of these tissue engineering approaches.
Interleukin-1 receptor-dependent and -independent caspase-1 activity in retinal cells mediated by receptor interacting protein 2
Authors: Coughlin Brandon A. , Christian Barbara , Trombley Brett , Mohr Susanne
Published: October 2024

Introduction

Inflammation and cell death play an important role in the pathogenesis of diabetic retinopathy. Previously we observed sustained activation of pro-inflammatory caspase-1 in retinas of diabetic animals and patients. In this study, we aimed to look at mechanisms underlying chronic caspase-1 activation in vitro and in vivo.

Methods

Non-diabetic and diabetic wild type and IL-1 receptor (IL-1R1) knockout mice were used for in vivo experiments. Diabetes was induced using STZ (streptozotocin). Human Müller cells were used for in vitro studies. Cells were treated with either 5 mM or 25 mM glucose or interleukin-1beta (IL-1β) in the presence or absence of IL-1 receptor antagonist (IL-1ra) or siRNA against RIP2 (receptor interacting protein-2) for up to 96 h. Outcome measurements to assess Müller cell functions included measurements of caspase-1 activity using a fluorescence peptide substrate, production of IL-1β by Elisa, and cell death using trypan blue exclusion assays.

Results

Our in vivo results demonstrate that caspase-1 activation progresses from an IL-1R1 independent mechanism at 10 weeks of diabetes to an IL-1R1 dependent mechanism at 20 weeks indicating that feedback through IL-1R1 is crucial for sustained caspase-1 activity in retinas of mice. A similar hyperglycemia-mediated caspase-1/IL-1β/IL-1R1 feedback signaling was detected in vitro in human Müller cells which was prevented by treatment with IL-1ra. Our data also indicate that hyperglycemia induces caspase-1 activation initially but IL-1β sustains caspase-1 activation via caspase-1/IL-1β/IL-1R1 feedback and we identified RIP2 as mediator for both hyperglycemia- and IL-1β-induced caspase-1 activation. Activation of caspase-1/IL-1β/IL-1R1 feedback signaling caused Müller cell death which was prevented by RIP2 knockdown.

Discussion

We conclude that any intervention in caspase-1/IL-1β/IL-1R1 feedback signaling presents novel therapeutic options for the treatment of diabetic retinopathy.
Revisiting the role of MicroRNAs in the pathogenesis of idiopathic pulmonary fibrosis
Authors: Zhou Zhimin , Xie Yuhong , Wei Qianru , Zhang Xinyue , Xu Zhihao
Published: October 2024

Idiopathic pulmonary fibrosis (IPF) is a prevalent chronic pulmonary fibrosis disease characterized by alveolar epithelial cell damage, fibroblast proliferation and activation, excessive extracellular matrix deposition, and abnormal epithelial-mesenchymal transition (EMT), resulting in tissue remodeling and irreversible structural distortion. The mortality rate of IPF is very high, with a median survival time of 2–3 years after diagnosis. The exact cause of IPF remains unknown, but increasing evidence supports the central role of epigenetic changes, particularly microRNA (miRNA), in IPF. Approximately 10% of miRNAs in IPF lung tissue exhibit differential expression compared to normal lung tissue. Diverse miRNA phenotypes exert either a pro-fibrotic or anti-fibrotic influence on the progression of IPF. In the context of IPF, epigenetic factors such as DNA methylation and long non-coding RNAs (lncRNAs) regulate differentially expressed miRNAs, which in turn modulate various signaling pathways implicated in this process, including transforming growth factor-β1 (TGF-β1)/Smad, mitogen-activated protein kinase (MAPK), and phosphatidylinositol-3-kinase/protein kinase B (PI3K/AKT) pathways. Therefore, this review presents the epidemiology of IPF, discusses the multifaceted regulatory roles of miRNAs in IPF, and explores the impact of miRNAs on IPF through various pathways, particularly the TGF-β1/Smad pathway and its constituent structures. Consequently, we investigate the potential for targeting miRNAs as a treatment for IPF, thereby contributing to advancements in IPF research.
In-situ monitoring of polymer mechanochemistry: what can be learned from small molecule systems
Authors: Willis-Fox Niamh
Published: October 2024

Using mechanical energy to drive chemical transformations is an exciting prospect to improve the sustainability of chemical reactions and to produce products not achievable by more traditional methods. In-situ monitoring of reaction pathways and chemical transformations is vital to deliver the reproducible results required for scale up to realize the potential of mechanochemistry beyond the chemistry lab. This mini review will discuss the recent advances in in-situ monitoring of ball milling and polymer mechanochemistry, highlighting the potential for shared knowledge for scale up.
Epigallocatechin gallate protects mice from Salmonella enterica ser. Typhimurium infection by modulating bacterial virulence through quorum sensing inhibition
Authors: Cheng Guoqiang , Jian Shanqiu , Li Wen , Yan Liangchun , Chen Tiezhu , Cheng Tingting , Liu Zongxiu , Ye Gang , Tang Huaqiao , Zhang Li
Published: October 2024

Salmonella enterica ser. Typhimurium is a common pathogen that poses a considerable public health threat, contributing to severe gastrointestinal diseases and widespread foodborne illnesses. The virulence of S. Typhimurium is regulated by quorum sensing (QS) and the type III secretion system (T3SS). This study investigated the inhibitory effects and anti-QS activity of epigallocatechin gallate (EGCG), which is a bioactive ingredient found in green tea, on the virulence of S. Typhimurium. In vitro bacterial experiments demonstrated that EGCG inhibited the production of autoinducers, biofilm formation, and flagellar activity by downregulating the expression of AI-1, AI-2, Salmonella pathogenicity islands (SPI)-1, SPI-2, and genes related to flagella, fimbriae, and curli fibers. In a mouse model of S. Typhimurium-induced enteritis, EGCG considerably reduced intestinal colonization by S. Typhimurium and alleviated intestinal damage. In conclusion, EGCG protects the intestines of mice infected with S. Typhimurium by inhibiting QS-induced virulence gene expression, demonstrating its potential as a therapeutic agent for controlling S. Typhimurium infections.
Artificial intelligence literacy among university students—a comparative transnational survey
Authors: Mansoor Hasan M. H. , Bawazir Ala , Alsabri Mustafa Abdulraheem , Alharbi Ahmed , Okela Abdelmohsen Hamed
Published: October 2024

Artificial intelligence (AI) literacy is a crucial aspect of media and information literacy (MIL), regarded not only as a human right but also as a fundamental requirement for societal advancement and stability. This study aimed to provide a comprehensive, cross-border perspective on AI literacy levels by surveying 1,800 university students from four Asian and African nations. The findings revealed significant disparities in AI literacy levels based on nationality, scientific specialization, and academic degrees, while age and gender did not show notable impacts. Malaysian participants scored significantly higher on the AI literacy scale than individuals from other countries. The results indicated that various demographic and academic factors influenced respondents’ perceptions of AI and their inclination to utilize it. Nationality and academic degree were identified as the most influential factors, followed by scientific specialization, with age and gender exerting a lesser influence. The study highlights the necessity of focusing research efforts on the detailed dimensions of the AI literacy scale and examining the effects of previously untested intervening variables. Additionally, it advocates for assessing AI literacy levels across different societal segments and developing the appropriate measurements.
Behavioural ethogram to inform ex-situ initiatives for a critically endangered bird – the case of the Plains-wanderer
Authors: Van Sluys Monique , Pauligk Yvette , Burns Alicia , O’Riordan Mark , Matkovics Richard , Hartnett Chris , Pitcher Benjamin J.
Published: October 2024

A thorough understanding of behaviour is essential to a species recovery effort, not only to inform management and husbandry decisions, but critically, to ensure optimum survival of released animals and their offspring. The endangered Plains-wanderer, endemic to Australia and the only extant member of its family, is a bird of great conservation significance. Despite their phylogenetic uniqueness and conservation status, very little is known about their basic behavioural ecology. As part of the National Recovery efforts, an ex-situ breeding program was established to create an insurance population with the aim of releasing zoo-bred birds into their natural range. Such programs provide unique opportunities to conduct detailed behavioural and ecological studies. However, such studies are dependent on a comprehensive understanding of basic behaviour and associated social interactions, as well as a common vocabulary across institutions when it comes to describing patterns of behaviour. Therefore, a detailed ethogram is a vital first step. Here we have collated initial behavioural observations and descriptions from three main breeding institutions to create a unified ethogram across sites, with the aim of facilitating future research endeavours. Ultimately a systematic understanding of behaviour will not only improve management and conservation initiatives, but also the understanding of adaptability to potential threats going forward.
Using reinforcement learning to autonomously identify sources of error for agents in group missions
Authors: Utimula Keishu , Hayaschi Ken-taro , Bihl Trevor J. , Hongo Kenta , Maezono Ryo
Published: October 2024

When deploying agents to execute a mission with collective behavior, it is common for accidental malfunctions to occur in some agents. It is challenging to distinguish whether these malfunctions are due to actuator failures or sensor issues based solely on interactions with the affected agent. However, we humans know that if we cause a group behavior where other agents collide with a suspected malfunctioning agent, we can monitor the presence or absence of a positional change and identify whether it is the actuator (position changed) or the sensor (position unchanged) that is broken. We have developed artificial intelligence that can autonomously deploy such “information acquisition strategies through collective behavior” using machine learning. In such problems, the goal is to plan collective actions that result in differences between the hypotheses for the state [e.g., actuator or sensor]. Only a few of the possible collective behavior patterns will lead to distinguishing between hypotheses. The evaluation function to maximize the difference between hypotheses is therefore sparse, with mostly flat values across most of the domain. Gradient-based optimization methods are ineffective for this, and reinforcement learning becomes a viable alternative. By handling this maximization problem, our reinforcement learning surprisingly gets the optimal solution, resulting in collective actions that involve collisions to differentiate the causes. Subsequent collective behaviors, reflecting this situation awareness, seemed to involve other agents assisting the malfunctioning agent.
The role of gut microbiome in mediating the effect of inflammatory bowel disease on hypertension: a two-step, two-sample Mendelian randomization study
Authors: Bao Wei , Zhang Yan , Huang Xiao-Jia , Gu Ning
Published: October 2024

Objective

Investigating the causal connection that exists between inflammatory bowel disease (IBD) and hypertension (HT). To gain a deeper insight into the correlation among IBD, gut microbiota, and HT, we conducted a two-step, two-sample Mendelian randomization study.

Methods

An investigation of genome-wide association study (GWAS) summary-level data was utilized to conduct a two-sample Mendelian randomization (MR) analysis of genetically predicted inflammatory bowel disease: (12,882cases, 21,770controls) on Systolic/Diastolic blood pressure (N = 2,564). Subsequently, two-step MR analyses revealed that the relationship between IBD and SBP was partly mediated by Faecalicatena glycyrrhizinilyticum. The robustness of the findings was confirmed through several sensitivity assessments.

Results

This MR study showed that increase in genetically predicted IBD was associated with higher risk of genetically predicted SBP (OR: 1.08, 95% CI: 1.01–1.16, P < 0.05) and DBP (OR: 1.09, 95% CI: 1.02–1.17, P < 0.05), respectively. Inverse variance weighted (IVW) MR analysis also showed that increase in genetically predicted IBD was associated with higher abundance Faecalicatena glycyrrhizinilyticum (OR: 1.03, 95% CI: 1.01–1.04, P < 0.05), which subsequently associated with increased SBP risk (OR: 1.42, 95% CI: 1.06–1.9, P < 0.05). Faecalicatena glycyrrhizinilyticum abundance in stool was responsible for mediating 11% of the genetically predicted IBD on SBP.

Conclusion

The research proposed a causal link between Inflammatory Bowel Disease (IBD) and Hypertension (HT), with a little percentage of the impact being influenced by Faecalicatena glycyrrhizinilyticum in stool. Mitigating gut microbiome may decrease the heightened risk of hypertension in people with inflammatory bowel disease.
Assessing the relative importance of vitamin D deficiency in cardiovascular health
Authors: Rubab Maira , Kelleher John D.
Published: October 2024

Previous research has suggested a potential link between vitamin D (VD) deficiency and adverse cardiovascular health outcomes, although the findings have been inconsistent. This study investigates the association between VD deficiency and cardiovascular disease (CVD) within the context of established CVD risk factors. We utilized a Random Forest model to predict both CVD and VD deficiency risks, using a dataset of 1,078 observations from a rural Chinese population. Feature importance was evaluated using SHapley Additive exPlanations (SHAP) to discern the impact of various risk factors on the model’s output. The results showed that the model for CVD prediction achieved a high accuracy of 87%, demonstrating robust performance across precision, recall, and F1 score metrics. Conversely, the VD deficiency prediction model exhibited suboptimal performance, with an accuracy of 52% and lower precision, recall, and F1 scores. Feature importance analysis indicated that traditional risk factors such as systolic blood pressure, diastolic blood pressure, age, body mass index, and waist-to-hip ratio significantly influenced CVD risk, collectively contributing to 70% of the model’s predictive power. Although VD deficiency was associated with an increased risk of CVD, its importance in predicting CVD risk was notably low. Similarly, for VD deficiency prediction, CVD risk factors such as systolic blood pressure, glucose levels, diastolic blood pressure, and body mass index emerged as influential features. However, the overall predictive performance of the VD deficiency prediction model was weak (52%), indicating the absence of VD deficiency-related risk factors. Ablation experiments confirmed the relatively lower importance of VD deficiency in predicting CVD risk. Furthermore, the SHAP partial dependence plot revealed a nonlinear relationship between VD levels and CVD risk. In conclusion, while VD deficiency appears directly or indirectly associated with increased CVD risk, its relative importance within predictive models is considerably lower when compared to other risk factors. These findings suggest that VD deficiency may not warrant primary focus in CVD risk assessment and prevention strategies, however, further research is needed to explore the causal relationship between VD deficiency and CVD risk.
Inhibition of angiogenesis and regenerative lung growth in Lepob/ob mice through adiponectin-VEGF/VEGFR2 signaling
Authors: Hunyenyiwa Tendai , Kyi Priscilla , Scheer Mikaela , Joshi Mrudula , Gasparri Mario , Mammoto Tadanori , Mammoto Akiko
Published: October 2024

Introduction

Obesity is associated with impairment of wound healing and tissue regeneration. Angiogenesis, the formation of new blood capillaries, plays a key role in regenerative lung growth after unilateral pneumonectomy (PNX). We have reported that obesity inhibits angiogenesis. The effects of obesity on post-PNX lung vascular and alveolar regeneration remain unclear.

Methods

Unilateral PNX is performed on Lepob/ob obese mice to examine vascular and alveolar regeneration.

Results

Regenerative lung growth and expression of vascular endothelial growth factor (VEGF) and its receptor VEGFR2 induced after PNX are inhibited in Lepob/ob obese mice. The levels of adiponectin that exhibits pro-angiogenic and vascular protective properties increase after unilateral PNX, while the effects are attenuated in Lepob/ob obese mice. Post-PNX regenerative lung growth and increases in the levels of VEGF and VEGFR2 are inhibited in adiponectin knockout mice. Adiponectin stimulates angiogenic activities in human lung endothelial cells (ECs), which is inhibited by decreasing the levels of transcription factor Twist1. Adiponectin agonist, AdipoRon restores post-PNX lung growth and vascular and alveolar regeneration in Lepob/ob obese mice.

Discussion

These findings suggest that obesity impairs lung vascular and alveolar regeneration and adiponectin is one of the key factors to improve lung regeneration in obese people.
Big data and AI for gender equality in health: bias is a big challenge
Authors: Joshi Anagha
Published: October 2024

Artificial intelligence and machine learning are rapidly evolving fields that have the potential to transform women's health by improving diagnostic accuracy, personalizing treatment plans, and building predictive models of disease progression leading to preventive care. Three categories of women's health issues are discussed where machine learning can facilitate accessible, affordable, personalized, and evidence-based healthcare. In this perspective, firstly the promise of big data and machine learning applications in the context of women's health is elaborated. Despite these promises, machine learning applications are not widely adapted in clinical care due to many issues including ethical concerns, patient privacy, informed consent, algorithmic biases, data quality and availability, and education and training of health care professionals. In the medical field, discrimination against women has a long history. Machine learning implicitly carries biases in the data. Thus, despite the fact that machine learning has the potential to improve some aspects of women's health, it can also reinforce sex and gender biases. Advanced machine learning tools blindly integrated without properly understanding and correcting for socio-cultural sex and gender biased practices and policies is therefore unlikely to result in sex and gender equality in health.
Phase behavior analysis of methane confined in nanopores using molecular simulation
Authors: Bi Ran , Hao Mingqiang , Wan Yang , Pan Yuewei , Chen Fangxuan
Published: October 2024

Interest in the phase behavior of hydrocarbons in shale reservoirs has grown in recent years. Petroleum fluid phase behavior has been observed to differ significantly between conventional reservoirs and shale reservoirs. Within shale reservoirs, notable surface-fluid interactions can lead to non-uniform molecule distribution and an alteration in fluid phase behavior, primarily caused by the existence of nano-scale porous materials. In this work, we study the phase behavior of methane in single cylindrical pore models. We apply the gauge Gibbs ensemble Monte Carlo (gauge-GEMC) simulation technique to investigate the phase behavior of methane in 4–10 nm single nanopores and calculate the saturation pressures at various temperatures using the grand canonical Monte Carlo (GCMC) simulation technique. A shift in the phase diagram has been found for methane in nanopores. As pore size decreases, the shift becomes more significant.
Evaluation of the ArcIOPS sea ice forecasts during 2021–2023
Authors: Liang Xi , Tian Zhongxiang , Zhao Fu , Li Ming , Liu Na , Li Chunhua
Published: October 2024

The operational sea ice forecasts from the Arctic Ice Ocean Prediction System (ArcIOPS) during 2021–2023 are validated against satellite-retrieved sea ice concentration and drift data, in situ and reanalyzed sea ice thickness data. The results indicate that the ArcIOPS has a reliable capacity on the Arctic sea ice forecasts for the future 7 days. Over the validation period, the root mean square error (RMSE) of the ArcIOPS sea ice concentration forecasts at a lead time of up to 168 h ranges between 8% and 20%, and the integrated ice edge error (IIEE) is lower than 1.6 × 106 km2 with respect to the Hai Yang 2B (HY-2B) sea ice concentration data. Compared to the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS), sea ice volume evolution from the ArcIOPS forecasts is closer to that derived from the CS2SMOS sea ice thickness observations, which have been assimilated into the ArcIOPS. Sea ice thickness comparisons at three locations in the Beaufort Sea between the ArcIOPS forecasts and in situ mooring observations also prove that the sea ice thickness forecasts are credible, which sets a solid basis for supporting ice-breaker navigation in the Arctic thick ice zone. The sea ice drift deviations between the ArcIOPS forecasts and the National Snow and Ice Data Center (NSIDC) data are lower than 4 cm/s in most of the months. Future work will emphasize on developing multi-variable data assimilation scheme and fully coupled air‒ice‒ocean forecasting system for the Arctic sea ice forecasts.
The CERIC method plus social collaborative annotation improves critical reading of the primary literature in an interdisciplinary graduate course
Authors: Bjorn Genevive
Published: October 2024

Background

Innovative approaches to graduate education that foster interdisciplinary learning are necessary, given the expansion of interdisciplinary research (IDR) and its ability to explore intricate issues and cutting-edge technology.

Purpose

This study examines an intervention to develop critical reading skills of the primary literature (CRPL), which are often assumed and unaided by formal instruction in graduate education (GE) yet are crucial for academic success and adapting to new research fields.

Methods

This study applied mixed methods and a pre-post design to assess the effectiveness of a CRPL intervention among 24 doctoral students from diverse fields engaging in the interdisciplinary field of science policy research. The intervention was a 4-week online course with explicit instruction in a categorical reading approach, the CERIC method (claim, evidence, reasoning, implications, and context), combined with social collaborative annotation (SCA) to facilitate low-stakes, peer-based discourse practice. It examined how participation changed participants’ CRPL skills and self-perceptions.

Results

The intervention significantly improved CRPL, t(23) = 13.6, p < 0.0001; research self-efficacy, t(23) = 4.9, p < 0.0001; and reading apprehension, t(23) = 4.3, p < 0.0001. Qualitative findings corroborated these findings and highlighted the importance of explicit CRPL instruction and the value of reading methods applicable to IDR. These results aligned with sociocultural and social cognitive theories and underscored the role of discourse and social engagement in learning critical reading, which is traditionally viewed as a solitary activity.

Conclusion

The findings present a valid and innovative model for developing CRPL skills in interdisciplinary GE. This approach provides a model for scaffolding CRPL that can be adapted to IDR contexts more broadly.

Implications

The study findings call for revising graduate curricula to incorporate explicit CRPL instruction with peer-based discourse, emphasizing integrations in higher education anywhere students encounter primary literature. The findings advocate for formal and informal adoption of the reviewed methods, offering a significant contribution to interdisciplinary GE pedagogy.
Understanding science teachers’ TPACK for virtual lab adoption in rural schools in South Africa: a mixed-methods approach
Authors: Shambare Brian , Jita Thuthukile
Published: October 2024

Introduction

This paper reports on a sequential explanatory mixed-methods study that assessed technological, pedagogical and content knowledge (TPACK) competency among life sciences teachers in the context of virtual lab adoption in rural schools in South Africa.

Methods

Drawing from TPACK framework as the study’s theoretical foundation, data gathered through questionnaires (N = 186) and in-depth semi-structured interviews (N = 4) were analysed using descriptive and thematic analysis.

Results

The study uncovered a ubiquitous deficiency in TPACK competency among the participating life sciences teachers. The teachers demonstrated significant expertise in conventional areas such as content knowledge (CK), pedagogical knowledge (PK), and pedagogical content knowledge (PCK), mainly influenced by teaching experience. However, they exhibited a noticeable gap in technology-related TPACK domains, including technological knowledge (TK), technological pedagogical knowledge (TPK), and overall TPACK proficiency.

Discussion

This paper aspires to address a significant gap in educational research by spotlighting the often-overlooked rural teaching contexts. In addition, the paper advocates for tailored professional development initiatives to enhance teachers’ overall TPACK proficiency. Such initiatives are crucial for empowering teachers to integrate technology into their teaching and improve learning outcomes effectively.
The lack of STEM vocations and gender gap in secondary education students
Authors: Hernández-Pérez Mariana , Alonso-Sánchez José A. , Hernández-Castellano Pedro M. , Quevedo-Gutiérrez Eduardo G.
Published: October 2024

The gender gap in STEM vocations among high school students still remains a troubling reality. Several studies indicate that students in general have less interest in science and technology subjects, and this disparity is even more distinguishable among female students. In fact, the aforementioned gender gap in STEM begins to manifest itself at an early age and worsens during adolescence. Some of the multiple causes include cultural factors, gender stereotypes, and lack of female role models. Therefore, it is essential to promote gender equality and encourage inclusion and diversity in the educational environment as a key measure to reduce the gap. This is why in this study comprehensive research was carried out to analyse the factors that contribute to the gender gap in STEM careers. To this end, a survey was conducted of approximately 1,000 secondary education students from a range of centres in the Canary Islands. The survey yielded insights into the direct influence of close references on students and the lack of female role models. This allowed the identification of effective measures to increase women’s participation in these fields. One of the suggested solutions is the implementation of practical workshops, in which female figures play a key role. These workshops are used to demonstrate to students that there are numerous role models nearby who can motivate and encourage them to explore and develop their interest in the field of science and technology. By providing said opportunities and role models, our aim is to build their confidence and provide them with the necessary tools to take advantage of all the opportunities that the STEM field has to offer.
Enhancing methods engineering education with a digital platform: usability and educational impact on industrial engineering students
Authors: Escobar-Castillejos David , Sigüenza-Noriega Iñaki , Noguez Julieta , Escobar-Castillejos Daisy , Berumen-Glinz Lorena Alexandra
Published: October 2024

Introduction

Work study aims to comprehend the potential of human work by assessing the duration of tasks and identifying methods for reducing them to enhance productivity and efficiency. On the other hand, methods engineering analyzes job processes to determine the most efficient and cost-effective techniques, resulting in improved operations. These areas are essential in the field of industrial engineering. Traditionally, they are taught using printed manuals and classroom-based instruction. Nevertheless, these conventional strategies frequently encounter difficulties engaging students and generating solid comprehension of the topics.

Methods

This study involved the development of a digital platform to improve methods engineering education. The platform adapts the curriculum of the methods engineering course offered at Universidad Panamericana. Each laboratory's practice includes detailed instructions and tasks for students to complete. Upon finishing, students submit their reports, which the professor then assesses. If the report meets the required standards, it is approved; otherwise, students must repeat the activities. An experience system serves as a tracker for course completion and keeps track of the student's progress.

Results

An experimental group of 26 students who responded to Doll and Torkzadeh's end-user computer satisfaction survey tested the platform. Participants responded positively, particularly regarding the platform's accuracy (73.08% high satisfaction), ease of use (majority rated 5 for user-friendliness), and timeliness (majority satisfied with up-to-date information). However, the format dimension received mixed ratings, indicating areas for improvement. Additionally, participants appreciated the platform's ability to track progress and motivate the completion of laboratories, with 61.54% finding the content relevant and valuable for learning methods engineering concepts.

Discussion

The results suggest that integrating digital platforms into educational settings could significantly enhance educational settings, particularly in engineering courses where conventional approaches struggle to maintain student interest and engagement. Participants' positive responses support digital platforms' potential to complement and improve teaching methods. Future research will focus on integrating adaptive learning and generating micro-credentials to certify student expertise.
Embracing LLM Feedback: the role of feedback providers and provider information for feedback effectiveness
Authors: Ruwe Theresa , Mayweg-Paus Elisabeth
Published: October 2024

Feedback is an integral part of learning in higher education and is increasingly being provided to students via modern technologies like Large Language Models (LLMs). But students’ perception of feedback from LLMs vs. feedback from educators remains unclear even though it is an important facet of feedback effectiveness. Further, feedback effectiveness can be negatively influenced by various factors; For example, (not) knowing certain characteristics about the feedback provider may bias a student’s reaction to the feedback process. To assess perceptions of LLM feedback and mitigate the negative effects of possible biases, this study investigated the potential of providing provider-information about feedback providers. In a 2×2 between-subjects design with the factors feedback provider (LLM vs. educator) and provider-information (yes vs. no), 169 German students evaluated feedback message and provider perceptions. Path analyses showed that the LLM was perceived as more trustworthy than an educator and that the provision of provider-information led to improved perceptions of the feedback. Furthermore, the effect of the provider and the feedback on perceived trustworthiness and fairness changed when provider-information was provided. Overall, our study highlights the importance of further research on feedback processes that include LLMs due to their influential nature and suggests practical recommendations for designing digital feedback processes.
Challenges and best practices in training teachers to utilize artificial intelligence: a systematic review
Authors: Aljemely Yousef
Published: October 2024

Introduction

The utilization of artificial intelligence is becoming a hot debate among researchers, academicians, and practitioners. Educational institutions are also training teachers to utilize AI in teaching. However, there is a dearth of investigation on the training of teachers to utilize AI. Therefore, this systematic review aims to highlight the challenges and best practices in training teachers to utilize AI. Strict inclusion and exclusion criteria were set to shortlist the relevant studies for review.

Methods

The review synthesized 10 studies focusing on the importance of AI, AI usage by teachers, challenges faced by teachers and trainers, and best practices that could be adopted by trainers.

Results

The results highlighted teachers lack the motivation for AI utilization and it is the biggest challenge faced by the trainers. Therefore, the training programs should be motivating, customized, and highlight the importance of AI. Moreover, the training sessions should also provide a trial of the latest AI technologies to the teachers so that they can get hands-on experience.

Discussion

This review can help AI trainers design customized training programs for teachers by keeping in mind the challenges faced by them. An effective training program can be designed if a trainer is aware of potential challenges faced by trainees. Thus, this research has not only discussed the challenges but also provided guidelines for AI trainers training teachers.
Exposing postdocs to multiple institutional types: a PROMISE-ing intervention to prepare biomedical faculty
Authors: Cresiski Robin H. , Ugarte Fadel , Harris LaKeisha , Clark Jessica K.
Published: October 2024

Biomedical faculty positions require experience as a postdoctoral scholar (or “postdoc”). However, there is a current misalignment with postdoctoral training and workforce needs within higher education. The majority of postdocs are trained to be research faculty while completing fellowships at research-intensive universities, despite the fact that the majority of US higher educational institutions (where these postdocs may be employed) focus on undergraduate education. This leads to postdoctoral scholars not having the opportunity to gain exposure to different institutional types where they could be employed. Importantly, they also lack the opportunity to build a network or receive mentorship from faculty at non-R1 institutions. This may be particularly true of underrepresented scholars. In this brief report, we describe the practice of the NSF-funded PROMISE Academy Alliance to bridge this training gap and support greater preparation for faculty careers at an array of institutional types by leveraging collaboration within a state university system. A survey of PROMISE Academy Fellows about their structured experiences engaging with other campuses (e.g., campus tours, workshops, speaking opportunities) reveals that visits to other campuses within the state system are informative and impactful, both on their research and their employment interests. The positive findings can hopefully inspire easy-to-implement changes in postdoctoral support across other university systems or regional consortia.
Multi-objective-based economic dispatch and loss reduction in the presence of electric vehicles considering different optimization techniques
Authors: Hmingthanmawia David , Deb Subhasish , Datta Subir , Singh Ksh. Robert , Cali Umit , Ustun Taha Selim
Published: October 2024

Currently, electric vehicles (EVs) are the most liked mode for green transportation. However, the vehicle-to-grid (V2G) technology can reduce the peak demand on the power grid, which is an efficient way to encourage the integration of EVs. This paper proposes a multi-objective-based economic dispatch management including EVs to minimize the generator cost and active power loss. The entire system is retained for keeping in mind the economic operation of the whole system. Then, EVs are introduced to the system, taking into account vehicle requirements and load demands and considering EV constraints. The target of the proposed work is to demonstrate how effectively large-scale EVs can participate in valley filling and peak load shaving along with multi-objective-based cost and loss reduction. The proposed optimization problem is employed in an IEEE 30-bus system. The multi-objective grasshopper optimization algorithm and the ant-lion optimization are compared to observe the minimum cost and total loss of the system. The results show that the total generation cost and power loss of the system decrease due to the V2G mode of operation. In addition, EVs provide an alternative method for dealing with peak load, while filling the off-peak hours effectively. The total generation cost and power loss for 24 h using MOGOA without implementation of EVs are 8,757.128 $/hr and 65.28509 MW, respectively, and with EVs, the total generation cost and power loss for 24 h are 8,617.077 $/hr and 55.65349 MW, respectively. Thus, with the implementation of EVs, the total generation cost reduced by 1.59% and the total power loss reduced by 14.75%, and with MOALO, the total generation cost and power loss for 24 h without EVs are 8,977.077 $/hr and 44.20877 MW, respectively, and with EVs, the total generation cost and power loss for 24 h are 8,923.529 $/hr and 41.69524 MW, respectively. Thus, with the implementation of EVs, the total generation cost reduced by 0.59% and the total power loss reduced by 5.68%. The analysis of the results demonstrates how effectively EVs in the V2G mode can reduce the dependency over the grid power during the time of peak load demand.