bluuebunny/crossref_metadata_2025_split huggingface dataset:
eDNA provides accurate and precise estimates of abundance by integrating bioenergetics and particle mass-balance
Authors: Beaulieu J , Yates MC , Fraser DJ , Cristescu ME , Derry AM 
Published: December 2024

AbstractAnthropogenic activities have led to an unprecedented crisis in freshwater biodiversity loss. The capacity to monitor the abundance of wild populations is critical to conserving biodiversity, but conventional physical specimen collection methods are invasive, costly, and labour-intensive. Environmental DNA (eDNA) offers a promising alternative, being easy to sample, with studies under controlled laboratory conditions showing consistent correlations between eDNA concentration and abundance. However, applying eDNA to monitor abundance remains contentious, as eDNA particle dynamics and the ecology of eDNA production can decouple this relationship in natural ecosystems. To address this, we integrated bioenergetics and mass-balance frameworks to relate eDNA concentrations to freshwater fish populationabundanceestimated through conventional mark-recapture in Brook Trout (Salvelinus fontinalis) across nine Rocky Mountains lakes, five of which underwent size-selectively harvest over two years. Our integrated framework improved the variance explained in eDNA concentrations from 24% to 71%. The integrated model accurately distinguished most abundance estimates across populations and sampling periods, detecting both natural and harvest-induced reductions in abundance within several populations. This study is the first to empirically integrate the DNA production ecology and particle dynamics, demonstrating that properly accounting for ‘the ecology of eDNA’ enables rapid, accurate abundance quantification. We also discuss future research and applications of eDNA in light of these results.Significance statementAddressing the unprecedented freshwater biodiversity crisis requires cost- and time-effective methods for estimating abundance and biomass. Our study empirically demonstrates the potential of eDNA for rapid and accurate assessment of abundance in natural populations by integrating hydrology, chemistry and bioenergetics into a mass-balance modelling framework. Through a replicated whole-ecosystem experiment, we show that eDNA not only detects differences in fish abundance and biomass across populations, but also captures natural and experimentally induced abundance changes within populations. Our modeling approach enables eDNA to generate abundance and biomass estimates comparable in precision and accuracy to high-quality mark-recapture methods.
Performance Evaluation of Ciprofloxacin loaded Micellar Bioconjugate Carrier for Eradication of Bacterial Biofilms
Authors: Gupta Chandrika , Ghosh Sudip Kumar , Sen Ramkrishna 
Published: December 2024

AbstractThis study reports the utilization of a Curcumin-Exopolysaccharide (Cur-EPS) micellar bioconjugate comprising acid-labile ester bond as a carrier for ciprofloxacin (Cip) to improve its ability to eradicate mature bacterial biofilms. The most significant attributes of Cip-loaded Cur-EPS micelles, including hydrodynamic particle size, polydispersity index (PDI), and encapsulation efficiency (EE), were statistically optimized to be 305.43 ± 1.47 nm, 0.38 ± 1.23, and 84.50 ± 2.01 %, respectively. At an acidic pH of 5.6, the pH-responsive release of Cip from Cur-EPS micelles was 82.51 ± 2.95 % over a duration of 100 h, but it was reduced to 39.10 ± 1.55 % at a pH of 7.4 over the same period. This pH-dependent Cip release may be attributed to the destabilisation of Cur-EPS micelles due to hydrolysis of the succinic acid linker in the acidic pH range. Thus, the acidic pH microenvironment of biofilms formed by pathogenic bacterial strains, such as methicillin resistantStaphylococcus aureus(MRSA) andPseudomonas aeruginosa, enhances the pH-responsive release of Cip from Cur-EPS micelles, thereby leading to the eradication of mature biofilms. This enhanced antibiofilm effect of Cip-Cur-EPS, in contrast to the free form of Cip, was evident from the significant decrease in the biofilm biomass. Furthermore, mature biofilms that formed on the surface of the urinary catheter were almost eradicated when treated in vitro with Cip-Cur-EPS for 72 h in the presence of artificial urine media (AUM). Moreover, Cip-Cur-EPS could also eradicate the biofilms formed byP. aeruginosaand MRSA in a catheterized bladder model employing recirculated artificial urine. Overall, this study demonstrated the antibiofilm potential of Cip-Cur-EPS micelles, rendering them suitable therapeutic agents for addressing biofilm-associated infections in clinical settings.Graphical abstract
Unraveling the Genetic Complexity of InvasiveLoniceraspp.: Evidence of Hybridization from Nuclear and Chloroplast Genome Analysis
Authors: Osier Michael V. , Borrego Eli J. , Tran Samantha V. , Hudson André O. 
Published: December 2024

AbstractMembers of theLoniceragenus, commonly known as honeysuckles, encompass both native and invasive species in North America, the latter posing significant ecological challenges. Invasive honeysuckles can disrupt native ecosystems by outcompeting local flora, altering habitats, and affecting wildlife populations. Effective management and control of these species are critical but hindered by the difficulty of accurate identification due to overlapping morphological traits. Traditional control measures recommended by government agencies, such as cutting, burning, and chemical treatments, have proven only partially effective, sometimes complicated by misidentification of species.The morphological identification of invasive honeysuckles is notoriously challenging. Key distinguishing features are often subtle, variable, and sometimes only discernible during specific developmental stages, complicating field identification efforts. This taxonomic ambiguity underscores the urgent need for more precise identification methods that transcend conventional morphological assessments.In this study, we explore the molecular identity of a Lonicera isolate collected from the Finger Lakes region of Western New York. Through detailed genetic analysis, we demonstrate that the specimen likely possesses maternal inheritance fromLonicera tataricawhile the majority of its nuclear genome is associated withLonicera insulara. Both species are prevalent in the region and known for their invasive potential.Our findings highlight the utility of molecular techniques as a complementary tool for species identification within the Lonicera genus. By providing a clearer genetic framework for distinguishing between morphologically similar species, this approach can enhance conservation strategies, inform management decisions, and improve ecological restoration efforts. As invasive species continue to threaten biodiversity, integrating molecular diagnostics with traditional methods offers a promising path toward more effective environmental stewardship.
Long-Term Reactivation of Multiple Sub-Assemblies in the Hippocampus and Prefrontal Cortex
Authors: Tatsuno Masami , Fellous Jean-Marc 
Published: December 2024

AbstractIn resting or sleep periods following a task, neurons in various parts of the brain become reactivated, with firing patterns often similar to that during the task. This reactivation plays an essential role in memory consolidation. However, detecting these reactivating episodes has been challenging because not all neurons recorded may be directly relevant to the memory being consolidated. Here, we propose a novel spike train clustering (STC) method for detecting groups of neurons (clusters) with partial synchronous firing. From a mechanistic standpoint, the correlated activity of an ensemble can arise from neuronal interactions within the recorded local ensemble, common external inputs, or both. To quantify these contributions, we propose to use information geometry (IG) by taking advantage of its capacity for orthogonal decomposition of neural interactions. We analyzed simultaneous single unit activity from rat medial prefrontal cortex (mPFC) and area CA1 of the hippocampus when animals explored novel objects and when they slept before and after the exploration. We demonstrate that multiple reactivations by different subsets of neurons (clusters) occurred. Those reactivations could extend over 11 hours, the entire recording duration of post-task rest after the exploration epoch. Long-lasting reactivation was not detected when all neurons were included as a single cluster in the analysis. We also showed that pairwise interactions in reactivating clusters tended to be more strongly modified than in non-reactivating ones. In addition, the pairwise interactions of the reactivating clusters in CA1 were strongly modulated by the task experience but not in the mPFC. These results indicate that hippocampal reactivation following novel experience is likely to be induced within the hippocampal circuits. In contrast, mPFC reactivation is likely to be driven by external inputs, possibly in part from the hippocampus.
Periplasmic serine protease Prc is responsible for amyloid subunit CsgA degradation and proteostasis inEscherichia coli
Authors: Sugimoto Shinya , Terasawa Yurika , Tani Naoki , Yamanaka Kunitoshi , Kinjo Yuki 
Published: December 2024

AbstractEscherichia colisynthesizes curli amyloid fibers extracellularly during biofilm formation and host colonization. The proteostasis network regulates the major curli subunit, CsgA, to prevent intracellular amyloid aggregation, yet the degradation mechanism remains elusive. Here, through a comprehensive investigation employing genetically engineeredE. coli, multi-copy-suppressor screening, and biochemical analyses, we identify periplasmic serine protease Prc as a key player in CsgA degradation. Prc directly degrades CsgA through internal cleavage, differing from canonical tail-specific proteases. Although the bacterial HtrA homologs DegP and DegQ exhibit limited CsgA degradation activity in vitro in the presence of the suicide activator YjfN, deletion of these proteases did not affect native CsgA degradation in vivo. Instead, Prc, in coordination with the periplasmic chaperone CsgC, prevents the periplasmic accumulation of CsgA amyloid-like aggregates. Additionally, disruptions in secretion efficiency and proteolytic systems reducecsgoperon expression through activation of the Rcs and Cpx two-component systems. These findings reveal a dual-layered strategy employed byE. colito prevent intracellular accumulation of extracellular amyloids at both protein degradation and transcriptional regulation levels. This study provides insights into the mechanisms ensuring cellular homeostasis during curli biogenesis.
KAT8 facilitates the proliferation of cancer cells through enhancing E7 function in HPV-associated cervical cancer
Authors: Xu Anli , Yang Xiaoming , Zhao Junwei , Kong Shujun , Tang Qing , Li Xiangzhi , Qu Hongmei , Wang Guoyun 
Published: December 2024

AbstractPersistent human papillomavirus (HPV) infection serves as the principal etiological factor in cervical cancer, with the oncoprotein E7, encoded by the virus, playing a key role in tumorigenesis. Despite this, targeted therapeutic strategies against E7 remain underexplored. KAT8, a lysine acetyltransferase, significantly contributes to oncogenesis through the regulation of transcription. However, its involvement in cervical cancer remains inadequately characterized. This study employs HPV18-positive HeLa and HPV16-positive SiHa cell lines to investigate how KAT8 modulates E7 expression and function in cervical cancer cells. Upon KAT8 knockdown, a marked reduction in cell viability is observed, alongside a downregulation of E7 expression. This is associated with elevated levels of retinoblastoma protein (pRb) and decreased E2F1 expression, indicating that KAT8 depletion inhibits E7 expression, resulting in E2F1 inactivation and cell cycle arrest. Furthermore, KAT8 is found to directly bind to the promoter regions of the HPV18 LCR, enhancing transcription of the HPV18 E7 gene. This study also demonstrates that KAT8 is essential for the acetylation of E7, and plays a critical role in facilitating the interaction between pRb/E2F1 and E7 in cervical cancer cells. In conclusion, these results highlight KAT8 as a key driver of cervical cancer progression, promoting HPV E7 expression and its associated oncogenic signaling pathways.
Fluctuation-Driven Synergy, Redundancy, Signal to Noise Ratio and Error Correction in Protein Allostery
Authors: Erman Burak 
Published: December 2024

AbstractThis study explores the relationship between residue fluctuations and molecular communication in proteins, emphasizing the role of these dynamics in allosteric regulation. We employ computational tools including the Gaussian Network Model, mutual information, and interaction information, to analyze how stochastic interactions among residues contribute to functional interactions while also introducing noise. Our approach is based on the postulate that residues experience continuous stochastic bombardment from impulses generated by their neighbors, forming a complex network characterized by small-world scaling topology. By mapping these interactions through the Kirchhoff matrix framework, we demonstrate how conserved correlations enhance signaling pathways and provide stability against noise-like fluctuations. Notably, we highlight the importance of selecting relevant eigenvalues to optimize the signal-to-noise ratio in our analyses, a topic that has yet to be thoroughly investigated in the context of residue fluctuations. This work underscores the significance of viewing proteins as adaptive information processing systems, and emphasizes the fundamental mechanisms of biological information processing. The basic idea of this paper is the following: Given two interacting residues on an allosteric path, what are the contributions of the remaining residues on this interaction. This naturally leads to the concept of synergy, redundancy and noise in proteins, which we analyze in detail for three proteins CheY, Tyrosine Phosphatase and β-Lactoglobulin.
Evaluating the evaluation: policies and practices involved in assessing school principals’ effectiveness
Authors: Alajmi Munirah , AlShammari Iqbal 
Published: December 2024

PurposeThis study investigated public school principals’ perceptions of the policies and practices involved in their evaluation. The processes, impacts and challenges of the principals’ evaluation practices were identified within the Kuwaiti context.Design/methodology/approachThe data for this qualitative study were drawn from semi-structured interviews with 32 Kuwaiti government high school principals.FindingsThese findings point to inefficient evaluation policies and practices that do not determine the level of effectiveness of school principals. In addition, the results identify limited awareness of the system of principals’ evaluations among school districts.Research limitations/implicationsThis study is limited to the perceptions of government school principals in Kuwait, and the results are based on semi-structured interviews with school principals.Practical implicationsThis study presents implications for policymakers and school principals to improve principals’ evaluation processes and impacts, especially in educationally centralized systems.Originality/valueThe novelty and significance of the present study reside in the scarcity of research undertaken on the evaluation of school principals despite the importance of their position. Furthermore, there is a tendency to prioritize the assessment of learners and teachers while disregarding the evaluation and methodologies used to evaluate school principals. Hence, the objective of this study is to address this gap, specifically within a centralized educational framework.
Have new post-pandemic perspectives affected collaboration, sharing and risk decision-making in the supply chain?
Authors: Vivaldini Mauro , de Sousa Paulo Renato 
Published: December 2024

PurposeTo explain the perception of post-pandemic managers concerning two critical factors of collaborative management in the supply chain – information exchange and risk sharing – and how these factors affect risk management (RM) and decision-making.Design/methodology/approachThis study used correlational research supported by information collected through a survey applied to 243 companies. We analysed adherence to a theoretical model proposed through structural equation modelling. This method made it possible to examine multiple dependency and independence relationships between latent variables through observed variables.FindingsCollaborative management was strongly perceived as influencing the exchange of information, while risk sharing demonstrated only a weak influence. Exchanging information about the consequences of RM had a representative impact, while risk sharing indicated little influence. Risk sharing should thus possibly be viewed more carefully in terms of its relationship with supply chain management, as it had a restrictive impact on decision-making.Originality/valueThe experience of the COVID-19 pandemic may have changed the perception and ways companies relate to and manage their risks. This change may have affected collaboration, sharing and RM while imposing new perspectives and transforming managers’ decision-making behaviour. Given the limitations of research with this focus, the moment is opportune to explore and better understand the effects of this event on management.
Enhanced identification of equipment failures from descriptive accident reports using language generative model
Authors: Ray Unmesa , Arteaga Cristian , Ahn Yonghan , Park JeeWoong 
Published: December 2024

PurposeEquipment failure is a critical factor in construction accidents, often leading to severe consequences. Therefore, this study addresses two significant gaps in construction safety research: (1) effectively using historical data to investigate equipment failure and (2) understanding the classification of equipment failure according to Occupational Safety and Health Administration (OSHA) standards.Design/methodology/approachOur research utilized a multi-stage methodology. We curated data from the OSHA database, distinguishing accidents involving equipment failures. Then we developed a framework using generative artificial intelligence (AI) and large language models (LLMs) to minimize manual processing. This framework employed a two-step prompting strategy: (1) classifying narratives that describe equipment failures and (2) analyzing these cases to extract specific failure details (e.g. names, types, categories). To ensure accuracy, we conducted a manual analysis of a subset of reports to establish ground truth and tested two different LLMs within our approach, comparing their performance against this ground truth.FindingsThe tested LLMs demonstrated 95% accuracy in determining if narratives describe equipment failures and 73% accuracy in extracting equipment names, enabling automated categorical identifications. These findings highlight LLMs’ promising identification accuracy compared to manual methods.Research limitations/implicationsThe research’s focus on equipment data not only validates the research framework but also highlights its potential for broader application across various accident categories beyond construction, extending into any domain with accessible accident narratives. Given that such data are essential for regulatory bodies like OSHA, the framework’s adoption could significantly enhance safety analysis and reporting, contributing to more robust safety protocols industry-wide.Practical implicationsUsing the developed approach, the research enables us to use accident narratives, a reliable source of accident data, in accident analysis. It provides deeper insights than traditional data types, enabling a more detailed understanding of accidents at an unprecedented level. This enhanced understanding can significantly inform and improve worker safety training, education and safety policies, with the potential for broader applications across various safety-critical domains.Originality/valueThis research presents a novel approach to analyzing construction accident reports using AI and LLMs, significantly reducing manual processing time while maintaining high accuracy. By identifying equipment failures more efficiently, our work lays the groundwork for developing targeted safety protocols, contributing to overall safety improvements in construction practices and advancing data-driven analysis processes.
I see therefore we are: the potential for aggregating individual future visions into a collective imaginary through artificial intelligence (AI)
Authors: Symons Jessica 
Published: December 2024

Purpose
This analysis draws on ethnographic research in a Northern UK city where a series of engagement activities produced hand-drawn sketches about the future. This paper shows how different groups revealed contradictory aspirations for the area with growth-focused politicians and planners projecting affluent prosperity rather than the modest, family-oriented social stability sought by local people.

Design/methodology/approach
Reconciling multiple perspectives is the greatest challenge of civic leadership. This paper considers how the emerging potential of artificial intelligence (AI) could support a structured imagining process for masterplanners to aggregate aspirational sketches at scale and so develop a closer relationship between citizen ideas for the future and civic decision makers’ own strategies and action plans.

Findings
This paper argues for a collective intelligence paradigm that aggregates individual futures thinking at city scale. Urban masterplanning strategies provide an organising structure to allow a city to emerge as a flourishing of multiple aspirations all at once.

Research limitations/implications
Rather than having individualism or collectivism as binary alternatives, generative AI offers an intriguing process for combining individual aspirations into a pluralist endeavour.

Practical implications
Engaging with citizens on the ground, in their homes and community spaces is the only way to uncover what is important to them. Ethnography provides that.

Social implications
Although AI’s use of aggregated data is collective, intelligence comes from nuanced and ethnographic engagement with the data.

Originality/value
The principle of the emergent city (Symons 2017) provides a conceptual approach to amalgamating the individual with the collective.