bluuebunny/crossref_metadata_2025 huggingface dataset:
Cerebral oximetry monitoring versus usual care for extremely preterm infants: a detailed statistical analysis plan for the 2-year follow-up of the SafeBoosC-III randomised clinical trial
Authors: Rasmussen Marie Isabel S , Hansen Mathias Lühr , Pellicer Adelina , Gluud Christian , Dempsey Eugene , Mintzer Jonathan , Hyttel-Sørensen Simon , Heuchan Anne Marie , Hagmann Cornelia , Ergenekon Ebru , Dimitriou Gabriel , Pichler Gerhard , Naulaers Gunnar , Tkaczyk Jakub , Fuchs Hans , Fumagalli Monica , Nesargi Saudamini , Fredly Siv , Szczapa Tomasz , Plomgaard Anne Mette , Hansen Bo Mølholm , Olsen Markus Harboe , Jakobsen Janus Christian , Greisen Gorm
Published: December 2024

Background

The SafeBoosC-III trial investigated treatment guided by cerebral oximetry monitoring for the first 72 hours after birth in extremely preterm infants and showed no effects on mortality or severe brain injury at 36 weeks’ postmenstrual age versus usual care. As severe brain injury in the neonatal period is not a strong predictor of long-term neurodevelopmental outcomes, the SafeBoosC-III follow-up study aims to assess the long-term benefits and harms of the experimental intervention versus usual care at two years of corrected age. This detailed statistical analysis plan outlines our approach for analysing outcomes in the SafeBoosC-III follow-up study.

Methods

The co-primary outcomes are 1) a composite of death or moderate-to-severe neurodevelopmental disability and 2) the mean Bayley-III/IV cognitive score. We will employ a 3-tier data model, incorporating routine clinical follow-up, parental questionnaires, and informal assessments to minimize missing data. All randomised participants with available data will be included in all analyses. Mixed-effect linear and logistic regression will be used to analyse the dichotomous and continuous co-primary outcomes, respectively. Sensitivity analyses will be conducted to address missing data and assess the robustness of our findings.

Discussion

The statistical analysis plan aims to ensure transparency and reduce the risk of outcome reporting bias. By including dichotomous and continuous co-primary outcomes, we aim to provide a comprehensive evaluation of the intervention’s effect on long-term benefits and harms.
Improving Mortality Surveillance through Notification of Death at Mbale Regional Referral Hospital, Uganda, October 2023–April 2024
Authors: Ssemanda Innocent , Namulondo Edith , Naziri Carol , Obbo Stephen , Kwesiga Benon , Migisha Richard , Bulage Lilian , Morukileng Job , Ario Alex Riolexus
Published: December 2024

Background

Accurate mortality reporting is crucial for monitoring population health, detecting disease outbreaks, and informing health policies. However, the implementation of medical certification of cause of death remains low in Uganda, with only 3.2% of health facility deaths being notified to the Ministry of Health. Using a quality improvement approach, we aimed to improve mortality reporting through medical certification of cause of death at Mbale Regional Referral Hospital (MRRH) in Uganda from 1% to 80% within 6 months.

Methods

We purposively selected MRRH as one of five regional referral hospitals with the lowest death notifications (0%-20%) during 2022 and 2023. We adopted the existing quality improvement team, which includes medical and non-medical personnel. Focus group discussions identified challenges that informed the root cause analysis. Using the Plan-Do-Study-Act (PDSA) cycle, we generated change ideas (interventions) to address these bottlenecks. We monitored the progress of the interventions with process indicators (number of mentorship sessions conducted, number of review meetings held) and an outcome indicator (proportion of deaths occurring in the hospital notified through the District Health Information System version 2 (DHIS2)) for 6 months. We tracked notifications monthly and analyzed the trend at six months using the Mann-Kendall test.

Results

We conducted 4/6 (67%) mentorship sessions and 7/19 (38%) review meetings and trained 32/50 (64%) nurses. The qualitative findings highlighted key challenges, including lack of knowledge and training, competing priorities and workload, resource constraints, undervaluing the importance of mortality reporting, failure to follow guidelines, and heavy workloads. The interventions included training and mentorship sessions for the staff on properly completing the death notification form, adopting a standardized process for form completion, and conducting bi-monthly review meetings. The proportion of deaths notified through DHIS2 from November 2023 to April 2024 increased from 17% to 65% (p=0.01).

Conclusion

Training of staff, adoption of a standard protocol on notification, and routine review meetings could facilitate death notification and improve mortality surveillance in Uganda enabling more accurate resource allocation for mortality prevention. The target was not met probably because all the staff were not trained, and the review meetings were sub-optimal.
Relaxation-selective Intravoxel Incoherent Motion Imaging of Microvascular Perfusion and Fluid Compartments in the Human Choroid Plexus
Authors: Li Chenyang , Sun Zhe , Zhang Jiangyang , Ge Yulin
Published: December 2024

The choroid plexus (ChP) plays an important role in the glymphatic system of the human brain as the primary source of the cerebrospinal fluid (CSF) production. Development of a non-invasive imaging technique is crucial for studying its function and age-related neurofluid dynamics. This study developed a relaxation-selective intravoxel incoherent motion (IVIM) technique to assess tissue and fluid compartments in the ChP in a prospective cross-sectional study involving 83 middle-aged to elderly participants (age: 61.5 ± 17.1 years old) and 15 young controls (age: 30.7 ± 2.9 years old). Using a 3T MRI scanner, IVIM, FLAIR-IVIM, LongTE-IVIM, and VASO-LongTE-IVIM were employed to measure diffusivity and volume fractions of fluid compartments and evaluate aging effects on microvascular perfusion and interstitial fluid (ISF). FLAIR-IVIM identified an additional ISF compartment with free-water-like diffusivity (2.4 ± 0.9 x10-3mm2/s). Older adults exhibited increased ChP volume (2320 ± 812 mm3vs 1470 ± 403 mm³, p=0.0017), reduced perfusion (6.5 ± 4.7 vs 3.6 ± 2.9 x10⁻³ mm²/s, p=0.0088), decreased ISF volume fraction (0.58 ± 0.09 vs 0.67 ± 0.06, p=0.0042), and lower tissue diffusivity (1.16 ± 0.14 vs 1.29 ± 0.17 x10-3mm²/s, p=0.031) compared to younger adults. Relaxation-selective IVIM may offers enhanced specificity for characterizing age-related changes in ChP structure and fluid dynamics.
Tropical Forest Soil Microbiome Modulates Leaf Heat Tolerance More Strongly Under Warming than Ambient Conditions
Authors: Hernandes Villani Gabriela , Grullon-Penkova Iana F , Bartz Parker , Masanga Joel , Lasky Jesse R , Reed Sasha C , Cavaleri Molly A , Wood Tana E , Bachelot Benedicte
Published: December 2024

Tropical forests are increasingly threatened by climate change. Yet, it is still unclear how tropical plants respond to increasing temperatures. Leaf heat tolerance (LHT) in tropical plants is often at its upper limit, suggesting that climate change might negatively impact tropical forests. We hypothesized that intraspecific variation in this leaf trait might be associated with changes in the soil microbiome, which might also respond to climate. Specifically, we hypothesized that warming would increase LHT through changes in the soil microbiome: this study combined an in-situ tropical warming experiment with a shade house experiment in Puerto Rico. The shade house experiment consisted of growing seedlings of Guarea guidonia, a dominant forest species, under different soil microbiome treatments (reduced arbuscular mycorrhizal fungi, reduced plant pathogens, reduced microbes, and unaltered) and soil inoculum from the field experiment. Heat tolerance was determined using chlorophyll fluorescence (FV/Fm) on individual seedlings in the field and on pooled seedlings by pot in the shade house. We sequenced soil fungal DNA to analyze the impacts of the field and shade house treatments on the soil microbiome. In the field, seedlings from ambient temperature plots showed higher FV/Fm values under high temperatures (0.648 at 46C and 0.067 at 52C) than seedlings from the warming plots (0.535 at 46C and 0.031 at 52C). In the shade house, the soil microbiome treatments, which significantly influenced the fungal community composition, significantly influenced LHT. Reduction in fungal pathogen abundance and diversity altered FV/Fm before T50 for seedlings grown with soil inoculum from the warming plots but after T50 for seedlings grown with soil inoculum from the ambient plots. Our findings emphasize that the soil microbiome might play an important role in modulating the impacts of climate change on plants. Understanding and harnessing this relationship might be vital for mitigating the effects of warming on tropical forests, emphasizing the need for further research on microbial responses to climate change.
Differential control of mycobacteria among COVID-19 patients is associated with CD28+ CD8+ T cells
Authors: Llibre Alba , Siddiqui Henna , Pillaye Jamie , Burel Julie G , Jones Charlotte , Hill Harriet , Faustini Sian E , Windle Ella , Karim Hanfa , Sherry Emma , Green Christopher A , Dedicoat Martin , Stamataki Zania , Cunningham Adam F , O’Shea Matthew K
Published: December 2024

Diseases caused by SARS-CoV-2 andMycobacterium tuberculosis(M.tb) represent two public health emergencies. In severe disease, both pathogens may share a biological niche in the lower respiratory tract. There is significant potential for SARS-CoV-2 andM.tbinfections to be co-present within individuals and enhance or moderate the respective outcomes of either infection. Here, we investigated how whole blood samples, as well as CD4+ and CD8+ T cells, from individuals hospitalised with acute COVID-19 disease respond to mycobacterial challenge. To do this, samples were assessed byex vivomycobacterial growth inhibition assays, immune cell phenotyping by mass cytometry, and whole blood cytokine responses to mycobacterial antigens assessed by flow cytometry. These studies identified a subgroup of COVID-19 patients whose blood had an enhanced capacity to inhibit mycobacterial growth. The ability to control mycobacterial growth was associated with the presence of a nonM.tb-specific CD28+ CD8+ T cell population, with a particular activation status and migratory phenotype. This work improves our understanding of factors involved in mycobacterial control, and may contribute to the design of novel therapies for TB.
L2G: Repurposing Language Models for Genomics Tasks
Authors: Cheng Wenduo , Shen Junhong , Khodak Mikhail , Ma Jian , Talwalkar Ameet
Published: December 2024

Pre-trained language models have transformed the field of natural language processing (NLP), and their success has inspired efforts in genomics to develop domain-specific foundation models (FMs). However, creating high-quality genomic FMs from scratch is resource-intensive, requiring significant computational power and high-quality pre-training data. The success of large language models (LLMs) in NLP has largely been driven by industrial-scale efforts leveraging vast, diverse corpora and massive computing infrastructure. In this work, we aim to bypass the data and computational bottlenecks of creating genomic FMs from scratch and instead propose repurposing existing LLMs for genomics tasks. Inspired by the recently observed ‘cross-modal transfer’ phenomenon – where transformers pre-trained on natural language can generalize to other modalities – we introduce L2G, which adapts a pre-trained LLM architecture for genomics using neural architecture search (NAS) and a novel three-stage training procedure. Remarkably, without requiring extensive pre-training on DNA sequence data, L2G achieves superior performance to fine-tuned genomic FMs and task-specific models on more than half of tasks across multiple genomics benchmarks. In an enhancer activity prediction task, L2G further demonstrates its capacity to identify significant transcription factor motifs. Our work not only highlights the generalizability and efficacy of language models in out-of-domain tasks such as genomics, but also opens new avenues for more efficient and less resource-intensive methodologies in genomic research.
Comparable neural and behavioural performance in dominant and non-dominant hands during grasping tasks
Authors: Eswari Balasubramanian , Balasubramanian Sivakumar , Varadhan SKM
Published: December 2024

Hand dominance has long been associated with differences in neural control and motor performance, with the dominant hand typically exhibiting better coordination in reaching tasks. However, the extent to which this dominance influences performance in finger force control remains unclear. This study aimed to examine the behavioural and neural features of the dominant and non-dominant hands during grasping and lifting tasks in healthy young adults, focusing on the synergy index, EEG band power, and EEG–EMG coherence as key measures. Twenty right-handed adults (mean age = 26.95, STD = 2.68) participated in this study. Participants engaged in an experimental task where they grasped a handle for the initial five seconds, followed by lifting and holding it for an additional five seconds. There were two task conditions: fixed (thumb platform secured) and free (thumb platform movable). They performed 25 trials with both the dominant and non-dominant hands in the two task conditions, with the order of trials and hands block randomized to eliminate potential order effects. Contrary to the dynamic dominance hypothesis, we found statistical equivalence in the synergy index, EEG band power, and EEG–EMG coherence between the dominant and non-dominant hands across both fixed and free task conditions. These findings suggest that both hands are capable of achieving similar levels of performance in tasks emphasizing steady-state force maintenance, despite the typical advantages of the dominant hand in other motor tasks. While task-dependent modulations in behavioural and neural features were observed due to changes in friction, these adjustments were non-different between the dominant and non-dominant hands.
MDSGene update and expansion: Clinical and genetic spectrum ofLRRK2variants in Parkinson’s disease
Authors: Krüger Clara , Lim Shen-Yang , Buhrmann Alissa , Fahrig Fenja L. , Gabbert Carolin , Bahr Natascha , Madoev Harutyun , Marras Connie , Klein Christine , Lohmann Katja
Published: December 2024

Pathogenic variants in theLRRK2gene are one of the most commonly identifiable monogenic causes of Parkinsońs disease (PD, PARK-LRRK2). This systematic MDSGene literature review comprehensively summarizes published demographic, clinical, and genetic findings related to potentially pathogenicLRRK2variants (https://www.mdsgene.org/). Recent insights on LRRK2’s kinase activity have been incorporated for pathogenicity scoring.

Data on 7,885 individuals with 292 different variants were curated, including 3,296 patients with PD carrying 205 different potentially disease-causingLRRK2variants. The initial MDSGene review covered only 724 patients carrying 23 differentLRRK2variants. Missingness of phenotypic data in the literature was high, hampering the identification of detailed genotype-phenotype correlations. Notably, the median age at onset in the patients with available information was 56 years, with approximately one-third having PD onset <50 years. Tremor was the most frequently reported initial symptom and more frequent than reported in other dominantly inherited forms of PD. Of the 205 potentially disease-causing variants, 14 (6.8%) were classified as pathogenic, 8 (3.9%) as likely pathogenic, and the remaining 183 (89.3%) as variants of uncertain significance (VUS). The pathogenic p.G2019S variant was the most frequent pathogenic variant, followed by p.R1441G and p.R1441C, accounting for >80% of patients, with Tunisia, Spain, and Italy contributing about half of patients.

This systematic review represents the largest database on PARK-LRRK2 to date and provides an important resource to improve precision medicine. Given their high frequency, a better interpretation of the pathogenicity of VUS is needed for selection and stratification of patients in clinical trials.
Lineage-associated Human Divergently-Paired Genes (DPGs) Exhibit Regulatory Characteristics and Evolutionary Trends
Authors: Duan Guangya , Zhang Sisi , Tang Bixia , Xiao Jingfa , Zhang Zhang , Cui Peng , Yu Jun , Zhao Wenming
Published: December 2024

Divergently-paired genes (DPGs) represent one of the minimal co-transcriptional units (the rest include tandemly- and convergently-paired genes) of clustered genes; the former and the latter constitute greater than 10% and 75% of the total human genes, respectively. Our previous studies have shown that vertebrate DPGs are more conserved, both organizationally and functionally than invertebrates. Three critical questions remain to be addressed: (1) what are the conserved DPGs over vertebrate lineages, especially among mammals and primates? (2) being bidirectionally transcribed, to what extent do DPGs share their promoter sequences and how mechanistically and stringently are their co-expression regulated within the shared inter-TSS (transcription start site) sequence space? and (3) based on the recently released high-quality human genome assemblies, how do human-associated DPGs distribute over selected primate lineages and what are their possible functional consequences biologically? Our study begins by identifying 1399 human DPGs (12% of all human protein-coding genes), and presents findings from this analysis. First, 1136, 1118, 925, and 830 human DPGs are shared genetically with primates, mammals, avians, and fish, respectively. DPGs are not only functionally enriched toward direct protein-DNA interactions and cell cycle synchronization but also exhibit obvious lineage association, narrow in principle toward synchronization of certain core molecular mechanisms and cellular processes. Second, their inter-TSS distances and expression variables affect both co-expression strength and disparity between the two genes. Finally, our results based on a comparison among the primate DPGs reveal that the human-associated DPGs exhibit intensive diversification in co-expression, duplication, and definite involvement in neural development. Within humans, 55 and 357 DPGs are associated to the Chinese (YAO) and the European (CHM13) assemblies, respectively. Our results offer novel insights into comprehending the structure-function selection of gene clusters over evolutionary time scales, as well as a deeper understanding of the regulatory characteristics of co-expressed neighboring genes.
SegCSR: Weakly-Supervised Cortical Surfaces Reconstruction from Brain Ribbon Segmentations
Authors: Zheng Hao , Chen Xiaoyang , Li Hongming , Chen Tingting , Liang Peixian , Fan Yong
Published: December 2024

Deep learning-based cortical surface reconstruction (CSR) methods heavily rely on pseudo ground truth (pGT) generated by conventional CSR pipelines as supervision, leading to dataset-specific challenges and lengthy training data preparation. We propose a new approach for reconstructing multiple cortical surfaces usingweak supervisionfrom brain MRI ribbon segmentations. Our approach initializes a midthickness surface and then deforms it inward and outward to form the inner (white matter) and outer (pial) cortical surfaces, respectively, by jointly learning diffeomorphic flows to align the surfaces with the boundaries of the cortical ribbon segmentation maps. Specifically, a boundary surface loss drives the initialization surface to the target inner and outer boundaries, and an inter-surface normal consistency loss regularizes the pial surface in challenging deep cortical sulci. Additional regularization terms are utilized to enforce surface smoothness and topology. Evaluated on two large-scale brain MRI datasets, our weakly-supervised method achieves comparable or superior CSR accuracy and regularity to existing supervised deep learning alternatives.
The antigenic landscape of N1 neuraminidase in human influenza A virus strains isolated between 2009 and 2020
Authors: Portela Catani João Paulo , Smet Anouk , Ysenbaert Tine , Amelinck Laura , Chan Yvonne , Tadmor Dan , Davidson Philip , Ray Satyajit , Camire Eric , Han Liqun , Zhang Jianxin , Cortés Guadalupe , Roebke Katherine , Baum Bianca , Hamberger John , Giel-Moloney Maryann , Saelens Xavier , Vogel Thorsten U.
Published: December 2024

The clinical burden caused by influenza can be mitigated by the prophylactic use of seasonal influenza vaccines. Their immunogen composition is revised biannually to optimally match the antigenic drift of the hemagglutinin of circulating influenza virus strains. Antibodies directed against the influenza neuraminidase also correlate with protection against influenza, yet the antigenic evolution of influenza neuraminidase remains underexplored. To evaluate the antigenic diversity of N1 neuraminidase, we generated a panel of immune sera directed against 17 N1 neuraminidases derived from human H1N1 strains that were isolated between 2009 and 2020 and determined its neuraminidase inhibition titers against a panel of 15 HxN1 viruses. The resulting neuraminidase inhibition pattern revealed two antigenic groups that circulated in this period. A machine learning method identified K432E and I321V as key determinants of N1 neuraminidase antigenicity.
Structural and Functional Insights into the Evolution of SARS-CoV-2 KP.3.1.1 Spike Protein
Authors: Feng Ziqi , Huang Jiachen , Baboo Sabyasachi , Diedrich Jolene K. , Bangaru Sandhya , Paulson James C. , Yates John R. , Yuan Meng , Wilson Ian A. , Ward Andrew B.
Published: December 2024

The JN.1-sublineage KP.3.1.1 recently emerged as the globally prevalent SARS-CoV-2 variant, demonstrating increased infectivity and antibody escape. We investigated how mutations and a deletion in the KP.3.1.1 spike protein (S) affect ACE2 binding and antibody escape. Mass spectrometry revealed a new glycan site at residue N30 and altered glycoforms at neighboring N61. Cryo-EM structures showed that the N30 glycan and rearrangement of adjacent residues did not significantly change the overall spike structure, up-down ratio of the receptor-binding domains (RBDs), or ACE2 binding. Furthermore, a KP.3.1.1 S structure with hACE2 further confirmed an epistatic effect between F456L and Q493E on ACE2 binding. Our analysis shows SARS-CoV-2 variants that emerged after late 2023 are now incorporating reversions to residues found in other sarbecoviruses, including the N30 glycan, Q493E, and others. Overall, these results inform on the structural and functional consequences of the KP.3.1.1 mutations, the current SARS-CoV-2 evolutionary trajectory, and immune evasion.
Final state interactions for high energy scattering off atomic electrons
Authors: Plestid Ryan , Wise Mark B.
Published: December 2024

We consider the scattering of high energy leptons off bound atomic electrons focusing primarily on final state interactions between the outgoing energetic electron, and the heavy residual charged “debris” in the final state. These effects are inherently absent from calculations for a free electron at rest. Coulomb exchanges are enhanced by the large number of electrons in the atomic debris, and are unsuppressed by nonrelativistic velocities in the debris. We find that these exchanges can be resummed using operator methods, and cancel at the level of the cross section until at least O(α3). Furthermore, we argue that both final initial state Coulomb exchanges (enhanced by the number of electrons in the atom) do not affect the cross section until at least O(α3). Transverse photon couplings to nonrelativistic electrons are proportional to their small velocities, and rotational invariance suppresses their contribution to O(α3). Our results are relevant for precision experiments involving neutrinos, electrons, positrons, and muons scattering off of atomic electrons in a fixed target.

Published by the American Physical Society
2024
Peristaltic pumping of viscoelastic fluid in a diverging channel: effects of magnetic field and surface roughness
Authors: Kumar Ashvani , Bhardwaj Anjali , Tripathi Dharmendra
Published: December 2024

Purpose

Surface properties (smooth or roughness) play a critical role in controlling the wettability, surface area and other physical and chemical properties like fluid flow behaviour over the rough and smooth surfaces. It is reported that rough surfaces are offering more significant insights as compared to smooth surfaces. The purpose of this study is to examine the effects of surface roughness in the diverging channel on physiological fluid flows.

Design/methodology/approach

A mathematical formulation based on the conservation of mass and momentum equations is developed to derive exact solutions for the physical quantities under the assumption of low Reynolds numbers and long wavelengths, which are appropriate for biological transport scenarios.

Findings

The results reveal that an increase in surface roughness reduces axial velocity and volumetric flow rate while increasing pressure distribution and turbulence in skin friction.

Research limitations/implications

These findings offer valuable insights for biological flow analysis, highlighting the effects of surface roughness, non-uniformity of the channel and magnetic fields.

Practical implications

These findings are very much applicable for designing the pumping devices for transportation of the fluids in non-uniform channels.

Originality/value

This study examines the impact of surface roughness on the peristaltic pumping of viscoelastic (Jeffrey) fluids in diverging channels with transverse magnetic fields.
When to perform cloud seeding for maximum agricultural crop yields? A modeling study
Authors: Misra Arvind Kumar , Agrawal Gauri , Yadav Akash
Published: December 2024

Purpose

Agricultural crops play a crucial role in food security and require commensurating environmental conditions, including adequate rainfall to ensure optimum growth. However, in the recent past, a reduction in the agriculture crop yield has been observed due to the deteriorating rainfall pattern. This paper aims to present a novel mathematical model to analyze the impact of rainfall on the growth of agriculture crops, as well as the impact of cloud seeding for promoting the rainfall, in case of less rainfall to ensure the optimum growth of agriculture crops.

Design/methodology/approach

The authors formulate a mathematical model assuming that the growth of agriculture crops wholly depends on rainfall. Also, agricultural crops can sustain and give optimal yields at a threshold of rainfall, after which rainfall negatively affects the growth rate of agriculture crops. Further, if the agriculture crops get insufficient rain to grow, the authors assume that cloud seeding agents are introduced in the regional atmosphere in proportion to the density of cloud droplets to increase rainfall.

Findings

This research shows that while cloud seeding agents boost crop yield, excessive rainfall poses significant risks on the yield. For any given value of π1 (conversion of cloud droplets into raindrops because of introduced cloud seeding agents), we have identified the threshold value of ϕ (introduction rate of cloud seeding agents into clouds) where crop yield can be maximized.

Research limitations/implications

This model highlights the delicate balance between rainfall and cloud seeding, offering policymakers valuable insights for maximizing agricultural crop yields.

Originality/value

This research provides strategies to mitigate crop loss due to unpredictable rainfall patterns.
Narratives of change: how climate change narratives have evolved since the 1970s
Authors: Kulaeva Zarina
Published: December 2024

Purpose

The purpose of this paper is twofold. First, we map the emerging climate narratives from the 1970s. Second, we examine how these narratives have shaped climate governance in addressing the consequences of climate change. Our analysis is based on a set of 12 interviews with climate change experts from various fields, including climate science, environmental policy, and environmental sustainability. The theoretical framework primarily draws from narrative analysis (Bruner, 1991; Riessman, 2005; Freeman, 2015), with a specific emphasis on its application within climate change studies (Bottici, 2010; Bushell et al., 2015; Fløttum and Gjerstad, 2017).

Design/methodology/approach

The period of analysis starts from the 1970s. A period marked by growing concern and the creation of national and global organizations to address the effects of climate change. Semistructured interviews were conducted with a sample of 12 experts in the field using narrative analysis. We adopted an inductive approach, allowing climate narratives to emerge organically from the interview data, and facilitating the emergence of new topics and perspectives.

Findings

Through interviews with climate experts, this study identifies three key narratives and critical shortcomings related to climate governance. The dominant climate narratives identified are apocalyptic environmentalism, greening capitalism and degrowth. Notably, greening capitalism and degrowth emerge as a dichotomous framework for understanding and interpreting climate change. By exploring these climate narratives, we highlight five critical shortcomings related to climate governance: increasing citizen participation through a bottom-up governance model, reforming the environmental subsidy framework, strengthening the science-policy interface, decoupling economic growth from energy dependence and developing innovative technological models beyond traditional green growth approaches. As a result, climate governance remains confined to these binary frameworks, and the challenges that were promised to be addressed decades ago largely remain unresolved.

Originality/value

The value of this study lies in the fact that, on the one hand, it uses narrative analysis to investigate climate governance, and on the other hand, it does so through interviews with different actors. All this facilitates a holistic approach, and from a 50-year historical perspective, this study traces an evolutionary line of narratives and identifies the critical points of climate governance.
Rethinking the digital divide and associated educational in(equity) in higher education in the context of developing countries: the social justice perspective
Authors: Assefa Yalalem , Gebremeskel Melaku Mengistu , Moges Bekalu Tadesse , Tilwani Shouket Ahmad , Azmera Yibeltal Aemiro
Published: December 2024

Purpose

In today’s educational landscape, technology has become an undeniable force in shaping pedagogical approaches and even the definition of learning itself. But this path contains many obstacles. Within the higher education ecosystem, the digital divide – the disparity in access and use of technology – is proving to be a significant barrier for educational institutions, particularly in developing countries. Hence, the current study attempts to understand the digital divide and its associated consequence on educational in(equity) in higher education, particularly within the context of developing countries.

Design/methodology/approach

Using a systematic review methodological approach, this study illuminates the complex dimensions of the digital divide and its associated educational impact in higher education based on the social justice theoretical perspective.

Findings

Key findings of the study show that the affordability of digital devices, infrastructure limitations and limited digital literacy are the main drivers of the digital divide. It has also been understood that the digital gap impairs teachers’ pedagogical approaches; thereby, this has a detrimental consequence on students’ learning engagement and academic achievement. More severely, the digital divide exacerbates existing educational disparities disproportionately, impacting students particularly from marginalized communities that already face automated inequality.

Originality/value

The study makes some encouraging recommendations for interventions to close the digital divide and reduce its effects on education. These include the implementing of initiatives that minimize access to and use of digital gaps; establishing long-term infrastructure investments to address connectivity issues; and creating adaptable support systems to deal with technical issues. By applying these and related approaches, higher education can bridge the digital divide and promote fair and inclusive learning opportunities, ultimately leading to equitable learning environments for all.
The interplay between technological innovation and human capital development in driving industrial productivity and competitiveness in Africa
Authors: Awode Segun Subair , Oduola Musa Olanrewaju
Published: December 2024

Purpose

This study examines how technological innovation (TECIN) and human capital development (HCD) combine to impact industrial productivity (INPR) and competitiveness in Africa.

Design/methodology/approach

The study used secondary data covering the period from 1996 to 2021 on 36 African countries, in a panel data framework of fixed effect and generalized method of moments techniques.

Findings

The study found that while TECIN negatively affected INPR in Africa, HCD exerted a strong positive influence. The interaction of TECIN and HCD showed a joint positive impact on INPR, emphasizing the role of human capital in mitigating transitional productivity loss tied to new technology assimilation. The results also showed positive individual and combined effects of TECIN and HCD on industrial competitiveness in Africa.

Practical implications

The findings therefore compel the need for implementation of policies that can simultaneously advance TECIN and strengthen HCD for sustainable industrial development in Africa. Governments in African countries need to allocate more resources to research and development to foster home-grown technologies, revamp educational curricula to align with industry needs and emphasize practical skills training, and facilitate technology transfer partnerships to enhance technological capabilities and INPR.

Originality/value

Although previous studies acknowledge the importance of TECIN and HCD for enhancing INPR and competitiveness in Africa, there is a noticeable lack of comprehensive studies that investigated the interplay between TECIN and HCD for industrialization gains.
Assessing organizational cohesion by the maximum caliber method
Authors: Lavanderos Leonardo , Fiol Eduardo , Araya Abelardo
Published: December 2024

Purpose

The aim of this paper is to explore the conditions under which organizational networks achieve high levels of cohesion. It focuses on understanding the roles of interaction cycles, feedback loops and asymmetries in fostering cohesive networks. The study examines how the application of line integrals in closed paths can reveal insights into the cycles and feedback mechanisms influencing cohesion within these networks.

Design/methodology/approach

This research uses the maximum caliber method to quantify organizational cohesion through the analysis of interactivity matrices. This approach integrates temporal dynamics and accounts for the complex interdependencies among actors within the network. The study is supported by a case study analysis, which demonstrates the practical application of these theoretical concepts in a real-world organizational context.

Findings

The application of the maximum caliber method offers a comprehensive understanding of organizational cohesion by effectively capturing the dynamic interactions within the network. The study reveals that cycles and feedback mechanisms within the network significantly affect cohesion, with interaction asymmetries playing a crucial role. The method also enables the identification of actors who contribute positively or negatively to cohesion, providing actionable insights for improving organizational performance.

Originality/value

This paper presents a novel methodological approach to analyzing organizational cohesion, enhancing both the theoretical and practical understanding of network dynamics. The findings provide valuable insights for organizational leaders and researchers, emphasizing the importance of managing interaction patterns to strengthen overall network cohesion and effectiveness. This approach offers a new perspective on measuring and influencing organizational cohesion, with significant implications for strategic management and organizational development.
Adopting artificial intelligence in Kenyan academic libraries: analyzing through the technology-organization-environment framework
Authors: Sang Lucy Jelagat
Published: December 2024

Purpose

The main aim of the paper was to determine the effect of Technology–Organization–Environment (TOE) Framework on adoption of artificial intelligence (AI) in Kenyan academic libraries anchored on diffusion innovation and TOE theories.

Design/methodology/approach

The target population comprised of 517 librarians, deputy librarian, and senior staff from 98 academic libraries from institutions of higher learning in Kenya. The study used stratified and random technique to sample 226 respondents.

Findings

Findings showed that technology factors (relative advantages, compatibility, and complexity) and environmental factors (regulatory environment, competitive pressure, and vendor partnership) positively affect adoption of AI in Kenyan academic libraries. However, organizational factors (firm size, top management support, and organizational readiness) had insignificant effect on adoption of AI in Kenyan academic libraries.

Research limitations/implications

The study underscores the necessity of proactive policy measures and managerial decisions to drive AI adoption in academic libraries. Policymakers must prioritize investments in training and resources to enhance staff readiness and create supportive regulatory environments. Library administrators play a pivotal role in demonstrating leadership support and effectively allocating resources to overcome implementation challenges. Tailoring adoption strategies to individual library needs and fostering collaboration between policymakers and administrators are critical for successful AI integration.

Originality/value

Other studies that have been done on application of AI in academic libraries have taken broader approach but this study narrows its focus to highlighting the pivotal influence of technological factors on AI adoption in academic libraries, recognizing the benefits and obstacles inherent in integration.
Exploring loneliness in Indian married adults: the impact of age and marital quality
Authors: Varyani Kanishka , Sharma Ritu
Published: December 2024

Purpose

The study aims explore the prevalence of lonliness among married adults in India along with examining its association with marital quality and age.

Design/methodology/approach

A total of 1,084 married adults across four age-groups were included in the sample of the study. Semi-structured questionnaire for demographic details with validated psychometric instruments like Marital Quality Scale (MQS) (Shah, 1995) and UCLA Loneliness Scale (version 3) (Russell, 1996) were used to collect the data. The data was analysed using multiple regression, cross-tabulation, chi-square(χ²) and Pearson correlation.

Findings

The study found that 46.4 % of the sample experienced moderately high level of loneliness. The participants in the age group of 31–40 years felt the maximum loneliness. 56.18 % participants of the sample experienced a severely affected marital quality. Strong and significant correlation was observed between marital quality and loneliness (r = 0.526). Negligible correlation was observed between age with loneliness (p > 0.05).

Practical implications

The study suggests the urgent need for interventions to enhance marital quality and should focus more on interpersonal factors such as communication style, conflict resolution, support from the spouse, increasing empathy, sexual satisfaction and intimacy rather than focusing only on demographic variables.

Social implications

The study will facilitate a better understanding of the pressing need to improve marital quality of Indian adults. Emphasizing on improving communication and intimacy in the marriage will improve overall well-being thereby also reducing loneliness.

Originality/value

To the best of the authors’ knowledge, this study is a first of its kind to explore the interrelationship between marital quality and loneliness among such a large sample in India. It also adds to the literature in understanding the dynamics of marital relationship.
Strategic leader or impulsive billionaire: Elon Musk’s early moves to turnaround Twitter
Authors: Frkal Robin , Lewis Michael S.
Published: December 2024

Research methodology

This case was developed using secondary sources, including newspapers, periodicals and academic references.

Case overview/synopsis

This case examines tech billionaire Elon Musk’s early moves after taking over Twitter and whether those moves demonstrated strategic leadership. During the acquisition, many people were torn between whether Musk’s leadership would lead to this company’s turnaround or demise. Musk’s early moves after his acquisition provided evidence for both arguments. He conducted mass firings, insisted on long and intense hours from those who remained, and pursued a subscription model that provided user authentication and allowed most banned accounts back on the platform. Many felt these early moves were chaotic, whereas others thought it was necessary. Did Musk’s early moves demonstrate strategic leadership or impulsive behavior?

Complexity academic level

This case, designed for strategic management or strategic leadership courses at the graduate and undergraduate levels, has been rigorously tested in a classroom setting. It was successfully used with undergraduate business students in a strategic management course, supporting the chapter on strategic leadership.
Strategy to Identify Virulence‐Related Genes of the Pathogenic Fungus Trichosporon asahii Using an Efficient Gene‐Targeting System
Authors: Matsumoto Yasuhiko , Kurakado Sanae , Yamada Tsuyoshi , Sugita Takashi
Published: December 2024

Trichosporon asahii is a pathogenic fungus that causes severe deep‐seated mycosis in immunocompromised patients with neutropenia. Understanding the molecular mechanisms of T. asahii infection will facilitate the development of new therapeutic and preventive strategies. Two main obstacles have prevented the identification of virulence‐related genes in T. asahii using molecular genetic techniques: the lack of experimental animal infection models for easy evaluation of T. asahii virulence and the lack of genetic recombination technology for T. asahii. To address these issues, we developed a silkworm infection model to quantitatively evaluate T. asahii virulence and a genetic recombination method to generate gene‐deficient T. asahii mutants, enabling the identification of virulence factors of T. asahii. In this review, we propose a strategy for identifying virulence‐related factors in T. asahii using a silkworm infection model and an efficient gene‐targeting system.
Enhancing porosity prediction: Integrating seismic inversion utilizing sparse layer reflectivity, and particle swarm optimization with radial basis function neural networks
Authors: Kant Ravi , Kumar Brijesh , Singh Ajay P. , Hema G. , Maurya S. P. , Singh Raghav , Singh K. H. , Sarkar Piyush
Published: December 2024

Seismic inversion, a crucial process in reservoir characterization, gains prominence in overcoming challenges associated with traditional methods, particularly in exploring deeper reservoirs. In this present study, we propose an inversion approach based on modern techniques like sparse layer reflectivity and particle swarm optimization to obtain inverted impedance. The proposed sparse layer reflectivity and particle swarm optimization techniques effectively minimize the error between recorded seismic reflection data and synthetic seismic data. This reduction in error facilitates accurate prediction of subsurface parameters, enabling comprehensive reservoir characterization. The inverted impedance obtained from both methods serves as a foundation for predicting porosity, utilizing a radial basis function neural network across the entire seismic volume. The study identifies a significant porosity zone (>20%) with a lower acoustic impedance of 6000–8500 m/s g cm3, interpreted as a sand channel or reservoir zone. This anomaly, between 1045 and 1065 ms two‐way travel time, provides high‐resolution insights into the subsurface. The particle swarm optimization algorithm shows higher correlation results, with 0.98 for impedance and 0.73 for porosity, compared to sparse layer reflectivity's 0.81 for impedance and 0.65 for porosity at well locations. Additionally, particle swarm optimization provides high‐resolution subsurface insights near well location and across a broader spatial range. This suggests particle swarm optimization's superior potential for delivering higher resolution outcomes compared to sparse layer reflectivity.
From Word Association Tests to Feeling‐Toned Complexes. A Jungian Perspective on Trauma1
Authors: Zoppi Luisa
Published: December 2024

In this paper, I would like to highlight how the view of the psyche as a network of complexes is central to understanding how trauma works and its treatment from a Jungian perspective. Despite Jung’s theory of complexes and his study of the splitting processes of the psyche being at the very core of his understanding of psychic functioning, analytical psychology has struggled to find its proper place in the international debate on trauma. The Word Association Tests (WAT) opened the way to Jung’s first insights on the complex psyche, i.e., a psyche made up of complexes. Currently, the complex is a cornerstone concept in analytical psychology; it is understood as the smallest functional unit of the psychic structure and can become autonomous when there is “a so‐called trauma, an emotional shock or some such thing, that splits off a bit of the psyche” (Jung, 1934, para. 204). The work of Donald Kalsched on trauma and complexes has helped to further the debate on the role of the theory of complexes in Jungian analysis and practice. A clinical case is presented to highlight the functioning of the psyche when facing trauma and how analysis can work with split‐off complexes throughout a whole analytic journey. Furthermore, similarities between the concepts of complexes—as seen in current analytical psychology—and emotional schemas as conceptualized by the Freudian analyst Wilma Bucci (2009) are highlighted.
Probiotic effects of human milk‐derived Lactiplantibacillus plantarum M660 on mice with antibiotic‐associated diarrhoea and constipation
Authors: Li Dandan , Yan Haodong , Yu Junjuan , Huang Yujun , Pan Lina , Kang Wenli , Tang Rongxue , Wang Jiaqi , Qu Hengxian , Wa Yunchao , Chen Xia , Gu Ruixia , Zhang Chenchen
Published: December 2024

Lactiplantibacillus plantarum M660 (M660) was isolated from the human milk of a healthy mother. M660 could survive the simulated gastrointestinal conditions without haemolytic and biogenic amine‐producing ability. The faecal water content was reduced, and the recoveries of the cecum and intestinal barrier were accelerated by M660 in the antibiotic‐associated diarrhoea model. In the constipation model, M660 enhanced intestinal motility, improved serum neurotransmitter levels, and reduced colonic injury. Analysis of gut microbiota showed that M660 increased the abundance of potentially beneficial bacteria and decreased the number of potentially pathogenic bacteria. Overall, M660 could be a probiotic candidate to promote infant health.