bluuebunny/crossref_metadata_2025_split huggingface dataset:
A single intranasal dose of essential oil spray confers modulation of the nasopharyngeal microbiota and short-term inhibition of Mannheimia in feedlot cattle: a pilot study
Authors: Magossi Gabriela , Schmidt Kaycie N. , Winders Thomas M. , Carlson Zachary E. , Holman Devin B. , Underdahl Sarah R. , Swanson Kendall C. , Amat Samat 
Published: January 2024

Abstract Five essential oils (EOs) were previously characterized in vitro and identified as candidate EOs for the development of an intranasal EO spray to mitigate bovine respiratory disease (BRD) pathogens. In the present study, these EOs were evaluated for their potential to (i) reduce BRD pathogens, (ii) modulate nasopharyngeal microbiota, and (iii) influence animal performance, feeding behavior and immune response when a single dose administered intranasally to feedlot cattle. Forty beef steer calves (7–8 months old, Initial body weight = 284 ± 5 kg [SE]) received either an intranasal EO spray (ajowan, thyme, fennel, cinnamon leaf, and citronella) or PBS (Control; n = 20/group) on day 0. Deep nasopharyngeal swabs were collected on days (d) -1, 1, 2, 7, 14, 28, and 42 and processed for 16S rRNA gene sequencing, qPCR, and culturing. Significant effects of EO on community structure (d1), microbial richness and diversity, relative abundance of some dominant phyla (d1, d2, and d14), and the overall interaction network structure of the nasopharyngeal microbiota were detected. The relative abundance of Mannheimia was lower in the EO calves (4.34%) than in Control calves (10.4%) on d2, and M. haemolytica prevalence on d7 as compared to control calves. Feed intake, average daily gain, feeding behavior, and blood cell counts were not affected by EO treatment. Overall, a single intranasal dose of EO spray resulted in moderate modulation of nasopharyngeal microbiota and short-term inhibition of Mannheimia while not influencing animal performance, feeding behavior or immune response. Our study, for the first time, shows the potential use of intranasal EO to mitigate BRD in feedlot cattle.
Singlet fission initiating organic photosensitizations
Authors: Tsuneda Takao , Taketsugu Tetsuya 
Published: January 2024

AbstractThe feasibility of singlet fission (SF) in organic photosensitizers is investigated through spin-flip long-range corrected time-dependent density functional theory. This study focuses on four major organic photosensitizer molecules: benzophenone, boron-dipyrromethene, methylene blue, and rose bengal. Calculations demonstrate that all these molecules possess moderate $$\pi$$
π
-stacking energies and closely-lying singlet (S) and quintet (triplet–triplet, TT) excitations, satisfying the essential conditions for SF: (1) Near-degenerate low-lying S and (TT) excitations with a significant S–T energy gap, and (2) Moderate $$\pi$$
π
-stacking energy of chromophores, slightly higher than solvation energy, enabling dissociation for triplet-state chromophore generation. Moreover, based on the El-Sayed rule, intersystem crossing is found to simultaneously proceed at very slow rates in all these photosensitizers. This is attributed to the fact that the lowest singlet excitation of the monomers partly involves $$n\pi ^*$$

n

π
∗

transitions alongside the main $$\pi \pi ^*$$

π

π
∗

transitions. The proposed mechanisms are strongly substantiated by comparisons with experimental studies.
Tracing the COVID-19 spread pattern in India through a GIS-based spatio-temporal analysis of interconnected clusters
Authors: Gupta Mousumi , Sharma Arpan , Sharma Dhruva Kumar , Nirola Madhab , Dhungel Prasanna , Patel Ashok , Singh Harpreet , Gupta Amlan 
Published: January 2024

AbstractSpatiotemporal analysis is a critical tool for understanding COVID-19 spread. This study examines the pattern of spatial distribution of COVID-19 cases across India, based on data provided by the Indian Council of Medical Research (ICMR). The research investigates temporal patterns during the first, second, and third waves in India for an informed policy response in case of any present or future pandemics. Given the colossal size of the dataset encompassing the entire nation’s data during the pandemic, a time-bound convenience sampling approach was employed. This approach was carefully designed to ensure a representative sample from advancing timeframes to observe time-based patterns in data. Data were captured from March 2020 to December 2022, with a 5-day interval considered for downloading the data. We employ robust spatial analysis techniques, including the Moran’s I index for spatial correlation assessment and the Getis Ord Gi* statistic for cluster identification. It was observed that positive COVID-19 cases in India showed a positive auto-correlation from May 2020 till December 2022. Moran’s I index values ranged from 0.11 to 0.39. It signifies a strong trend over the last 3 years with $$r^2$$

r
2

of 0.74 on order 3 polynomial regression. It is expected that high-risk zones can have a higher number of cases in future COVID-19 waves. Monthly clusters of positive cases were mapped through ArcGIS software. Through cluster maps, high-risk zones were identified namely Kerala, Maharashtra, New Delhi, Tamil Nadu, and Gujarat. The observation is: high-risk zones mostly fall near coastal areas and hotter climatic zones, contrary to the cold Himalayan region with Montanne climate zone. Our aggregate analysis of 3 years of COVID-19 cases suggests significant patterns of interconnectedness between the Indian Railway network, climatic zones, and geographical location with COVID-19 spread. This study thereby underscores the vital role of spatiotemporal analysis in predicting and managing future COVID-19 waves as well as future pandemics for an informed policy response.
Counter-on-chip for bacterial cell quantification, growth, and live-dead estimations
Authors: Rahman K. M. Taufiqur , Butzin Nicholas C. 
Published: January 2024

AbstractQuantifying bacterial cell numbers is crucial for experimental assessment and reproducibility, but the current technologies have limitations. The commonly used colony forming units (CFU) method causes a time delay in determining the actual numbers. Manual microscope counts are often error-prone for submicron bacteria. Automated systems are costly, require specialized knowledge, and are erroneous when counting smaller bacteria. In this study, we took a different approach by constructing three sequential generations (G1, G2, and G3) of counter-on-chip that accurately and timely count small particles and/or bacterial cells. We employed 2-photon polymerization (2PP) fabrication technology; and optimized the printing and molding process to produce high-quality, reproducible, accurate, and efficient counters. Our straightforward and refined methodology has shown itself to be highly effective in fabricating structures, allowing for the rapid construction of polydimethylsiloxane (PDMS)-based microfluidic devices. The G1 comprises three counting chambers with a depth of 20 µm, which showed accurate counting of 1 µm and 5 µm microbeads. G2 and G3 have eight counting chambers with depths of 20 µm and 5 µm, respectively, and can quickly and precisely count Escherichia coli cells. These systems are reusable, accurate, and easy to use (compared to CFU/ml). The G3 device can give (1) accurate bacterial counts, (2) serve as a growth chamber for bacteria, and (3) allow for live/dead bacterial cell estimates using staining kits or growth assay activities (live imaging, cell tracking, and counting). We made these devices out of necessity; we know no device on the market that encompasses all these features.
An AI-based novel system for predicting respiratory support in COVID-19 patients through CT imaging analysis
Authors: Farahat Ibrahim Shawky , Sharafeldeen Ahmed , Ghazal Mohammed , Alghamdi Norah Saleh , Mahmoud Ali , Connelly James , van Bogaert Eric , Zia Huma , Tahtouh Tania , Aladrousy Waleed , Tolba Ahmed Elsaid , Elmougy Samir , El-Baz Ayman 
Published: January 2024

AbstractThe proposed AI-based diagnostic system aims to predict the respiratory support required for COVID-19 patients by analyzing the correlation between COVID-19 lesions and the level of respiratory support provided to the patients. Computed tomography (CT) imaging will be used to analyze the three levels of respiratory support received by the patient: Level 0 (minimum support), Level 1 (non-invasive support such as soft oxygen), and Level 2 (invasive support such as mechanical ventilation). The system will begin by segmenting the COVID-19 lesions from the CT images and creating an appearance model for each lesion using a 2D, rotation-invariant, Markov–Gibbs random field (MGRF) model. Three MGRF-based models will be created, one for each level of respiratory support. This suggests that the system will be able to differentiate between different levels of severity in COVID-19 patients. The system will decide for each patient using a neural network-based fusion system, which combines the estimates of the Gibbs energy from the three MGRF-based models. The proposed system were assessed using 307 COVID-19-infected patients, achieving an accuracy of $$97.72\%\pm 1.57$$

97.72
%
±
1.57

, a sensitivity of $$97.76\%\pm 4.08$$

97.76
%
±
4.08

, and a specificity of $$98.87\%\pm 2.09$$

98.87
%
±
2.09

, indicating a high level of prediction accuracy.
Mean performances, character associations and multi-environmental evaluation of chilli landraces in north western Himalayas
Authors: Singh Thakur Narender , Joshi A. K. , Vikram Amit , Yadav Nitin , Prashar Sakshi 
Published: January 2024

AbstractEven though many varieties have been recommended across agro-climate zones of Himachal Pradesh, yet the information on stability is lacking in this State. Hence, the present investigation was carried out to identify high yielding stable genotypes among various pre-adapted landraces. The material consists of 20 chilli landraces including check i.e. DKC-8. The experiment was laid out in a RCBD. The data were recorded and analyzed to work out mean performances and the inferences were drawn for parameters of variability, correlation coefficients, path coefficients and stability analysis. As per mean performances, CS7 and CS9 were earliest in flowering, CS13 is earliest in days to ripe maturity, CS10 had highest plant height and CS9 had highest average fruit weight and ripe fruit yield plant−1. High PCV and GCV were recorded for ripe fruit yield plant−1. Heritability and genetic advance were recorded maximum for plant height in summer seasons and were recorded maximum for number of ripe fruits plant−1 in winter season. Correlation coefficients showed that number of ripe fruits plant−1 and average ripe fruit weight were positively and significantly correlated with ripe fruit yield plant−1. Path coefficient analysis in summer and winter seasons showed that average ripe fruit weight had the highest positive direct effect on ripe fruit yield plant−1. The pooled data over environments were analyzed to estimate the interaction effects between genotypes × environment. The mean sum of squares due to genotypes, environments and genotypes × environment interaction were significant for all the characteristics. CS1, CS3, CS6, CS10, CS13, CS15 were adapted to all environments, CS7 and CS9 were specifically adapted to favourable environment and CS2 was specifically adapted to unfavorable environment for 50% flowering, landraces CS1, CS2 and CS3were well adapted to all environments for ripe maturity whereas landraces CS6, CS10 and CS19 were well adapted to all environment for number of ripe fruit and ripe fruit yield.
Paclitaxel-induced inhibition of NSCLC invasion and migration via RBFOX3-mediated circIGF1R biogenesis
Authors: Xu Zhanyu , Zheng Liping , Li Shikang 
Published: January 2024

AbstractWe previously reported that circIGF1R is significantly downregulated in non-small cell lung cancer (NSCLC) cells and tissues. It inhibits cancer cell invasion and migration, although the underlying molecular mechanisms remain elusive. The invasion and migration of NSCLC cells was analyzed by routine in vivo and in vitro functional assays. Fluorescent in situ hybridization, luciferase reporter assay, RNA pull-down assay and RNA immunoprecipitation (RIP) assay were performed to explore the molecular mechanisms. Mechanism of action of paclitaxel-induced RBFOX3-mediated inhibition of NSCLC invasion and migration was investigated through in vitro and in vivo experiments.Our study reveals that circIGF1R acts as a Competing Endogenous RNA (ceRNA) for miR-1270, thereby regulating Van-Gogh-like 2 (VANGL2) expression and subsequently inhibiting NSCLC cell invasion and migration via the Wnt pathway. We also found that RNA binding protein fox-1 homolog 3 (RBFOX3) enhances circIGF1R biogenesis by binding to IGF1R pre-mRNA, which in turn suppresses migration and invasion in NSCLC cells. Additionally, the chemotherapeutic drug paclitaxel was shown to impede NSCLC invasion and migration by inducing RBFOX3-mediated circIGF1R biogenesis.RBFOX3 inhibits the invasion and migration of NSCLC cells through the circIGF1R/ miR-1270/VANGL2 axis, circIGF1R has the potential to serve as a biomarker and therapeutic target for NSCLC.
Benzo[a]pyrene disrupts LH/hCG-dependent mouse Leydig cell steroidogenesis through receptor/Gαs protein targeting
Authors: Lazzaretti Clara , Roy Neena , Paradiso Elia , Capponi Chiara , Ferrari Tommaso , Reggianini Francesca , Sperduti Samantha , Perri Carmela , Baschieri Lara , Mascolo Elisa , Varani Manuela , Canu Giulia , Trenti Tommaso , Nicoli Alessia , Morini Daria , Iannotti Francesca , Villani Maria Teresa , Vicini Elena , Simoni Manuela , Casarini Livio 
Published: January 2024

AbstractSteroidogenesis of gonadal cells is tightly regulated by gonadotropins. However, certain polycyclic aromatic hydrocarbons, including Benzo[a]pyrene (BaP), induce reproductive toxicity. Several existing studies have considered higher than environmentally relevant concentrations of BaP on male and female steroidogenesis following long-term exposure. Also, the impact of short-term exposure to BaP on gonadotropin-stimulated cells is understudied. Therefore, we evaluated the effect of 1 nM and 1 µM BaP on luteinizing hormone/choriogonadotropin (LH/hCG)-mediated signalling in two steroidogenic cell models, i.e. the mouse tumor Leydig cell line mLTC1, and the human primary granulosa lutein cells (hGLC) post 8- and 24-h exposure. Cell signalling studies were performed by homogeneous time-resolved fluorescence (HTRF) assay, bioluminescence energy transfer (BRET) and Western blotting, while immunostainings and immunoassays were used for intracellular protein expression and steroidogenesis analyses, respectively. BaP decreased cAMP production in gonadotropin-stimulated mLTC1 interfering with Gαs activation. Therefore, decrease in gonadotropin-mediated CREB phosphorylation in mLTC1 treated with 1 μM BaP was observed, while StAR protein levels in gonadotropin-stimulated mLTC1 cells were unaffected by BaP. Further, BaP decreased LH- and hCG-mediated progesterone production in mLTC1. Contrastingly, BaP failed to mediate any change in cAMP, genes and proteins of steroidogenic machinery and steroidogenesis of gonadotropin-treated hGLC. Our results indicate that short-term exposure to BaP significantly impairs steroidogenic signalling in mLTC1 interfering with Gαs. These findings could have a significant impact on our understanding of the mechanism of reproductive toxicity by endocrine disruptors.
Stochastic biological system-of-systems modelling for iPSC culture
Authors: Zheng Hua , Harcum Sarah W. , Pei Jinxiang , Xie Wei 
Published: January 2024

AbstractLarge-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension bioreactors, resulting in insufficient nutrient supply and extra metabolic waste build-up for the cells located at the core. Since subtle changes in micro-environment can lead to a heterogeneous cell population, a novel Biological System-of-Systems (Bio-SoS) framework is proposed to model cell-to-cell interactions, spatial and metabolic heterogeneity, and cell response to micro-environmental variation. Building on stochastic metabolic reaction network, aggregation kinetics, and reaction-diffusion mechanisms, the Bio-SoS model characterizes causal interdependencies at individual cell, aggregate, and cell population levels. It has a modular design that enables data integration and improves predictions for different monolayer and aggregate culture processes. In addition, a variance decomposition analysis is derived to quantify the impact of factors (i.e., aggregate size) on cell product health and quality heterogeneity.
A revised nomenclature for the lemur family of protein kinases
Authors: Mórotz Gábor M. , Bradbury Neil A. , Caluseriu Oana , Hisanaga Shin-ichi , Miller Christopher C. J. , Swiatecka-Urban Agnieszka , Lenz Heinz-Josef , Moss Stephen J. , Giamas Georgios 
Published: January 2024

AbstractThe lemur family of protein kinases has gained much interest in recent years as they are involved in a variety of cellular processes including regulation of axonal transport and endosomal trafficking, modulation of synaptic functions, memory and learning, and they are centrally placed in several intracellular signalling pathways. Numerous studies have also implicated role of the lemur kinases in the development and progression of a wide range of cancers, cystic fibrosis, and neurodegenerative diseases. However, parallel discoveries and inaccurate prediction of their kinase activity have resulted in a confusing and misleading nomenclature of these proteins. Herein, a group of international scientists with expertise in lemur family of protein kinases set forth a novel nomenclature to rectify this problem and ultimately help the scientific community by providing consistent information about these molecules.
Identifying key players in complex networks via network entanglement
Authors: Huang Yiming , Wang Hao , Ren Xiao-Long , Lü Linyuan 
Published: January 2024

AbstractEmpirical networks exhibit significant heterogeneity in node connections, resulting in a few vertices playing critical roles in various scenarios, including decision-making, viral marketing, and population immunization. Thus, identifying key vertices is a fundamental research problem in Network Science. In this paper, we introduce vertex entanglement (VE), an entanglement-based metric capable of quantifying the perturbations caused by individual vertices on spectral entropy, residing at the intersection of quantum information and network science. Our analytical analysis reveals that VE is closely related to network robustness and information transmission ability. As an application, VE offers an approach to the challenging problem of optimal network dismantling, and empirical experiments demonstrate its superiority over state-of-the-art algorithms. Furthermore, VE also contributes to the diagnosis of autism spectrum disorder (ASD), with significant distinctions in hub disruption indices based on VE between ASD and typical controls, promising a diagnostic role for VE in ASD assessment.
Work–family interference in urban China: gender discrimination and the effects of work–family balance policies
Authors: Xu Yuehua , Zhang Shujie , Li Manyuan , Liu Depeng , Zhao Haichuan , Tang Guiyao 
Published: January 2024

AbstractFamily responsibility discrimination is a form of discrimination against men and women because of their caregiving responsibilities. Unlike prior studies that have predominantly focused on Western contexts, this study shifts attention to observers’ differentiated discrimination against men and women in China involved in work–family interference. The findings across four main experiments (N = 2577) suggest that shouldering family responsibility in the context of both family interference in work and work interference in family would stimulate more discrimination against men in urban China. We also explore whether a firm’s work–family balance policies can mitigate such discrimination. The results demonstrate that such policies mitigate supervisors’ discrimination against men involved in family interference in work but not observers’ discrimination against men involved in work interference in family. Post-hoc experiments and further tests (N = 931) demonstrate the robustness of our findings and show additional insights. Our findings suggest that gender discrimination in non-Western contexts can be very different.
An individual participant data meta-analysis of psychological interventions for preventing depression relapse
Authors: Breedvelt Josefien J. F. , Karyotaki Eirini , Warren Fiona C. , Brouwer Marlies E. , Jermann Françoise , Hollandare Fredrik , Klein Nicola , de Jonge Margo , Klein Daniel N. , Farb Norman , Segal Zindel , Biesheuvel Leliefeld Karolien E. M. , Jarrett Robin , Vittengl Jeffrey , Thase Michael , Ma Helen , Kuyken Willem , Shallcross Amanda J. , van Heeringen Cornelis , Hoorelbeke Kristof , Koster Ernst , Williams Mark , Huijbers Marloes J. , Speckens Anne , Cuijpers Pim , van Oppen Patricia , Gilbody Simon , Bockting Claudi L. 
Published: January 2024

AbstractMajor depressive disorder is a leading cause of disability worldwide; identifying effective strategies to prevent depression relapse is crucial. This individual participant data meta-analysis addresses whether and for whom psychological interventions can be recommended for relapse prevention of major depressive disorder. One- and two-stage individual patient data meta-analyses were conducted on 14 randomized controlled trials (N = 1,720). The relapse risk over 12 months was substantially lower for those who received a psychological intervention versus treatment as usual, antidepressant medication, or evaluation-only control (hazard ratio, 0.60; 95% confidence interval, 0.48–0.74). The number of previous depression episodes moderated the treatment effect, with psychological interventions demonstrating greater efficacy for patients with three or more previous episodes. Our results suggest that adding psychological interventions to current treatment to prevent depression relapse is recommended. For patients at lower risk of relapse, less-intensive approaches may be indicated.