bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence and distribution of Varroa destructor and Nosema spp. in symptomatic honey bee colonies across the USA from 2015 to 2022
Authors: Abban Samuel , Smith Bart , Corona Miguel , Cook Steven C. , Evans Jay D. , Chen Yanping , Alburaki Mohamed 
Published: January 2024

AbstractUSDA-ARS Bee Research Laboratory received symptomatic honey bee (Apis mellifera L.) samples across the United States for disease diagnosis. Here, we present a retrospective study and cartography of ectoparasite Varroa destructor and intracellular microsporidia parasite Nosema spp. These two major parasites were identified in the diseased honey bee samples between 2015 and 2022. Varroa infestation level (VIL) was examined by a wash technique (Mites/100 bees) and calculated as a percentage, while Nosema infection was quantified by microscopical spore count (Million Spores/Bee). Data were analyzed by month, year, state, and by nine geographical climate regions described in the U.S. Of adult bee samples (n = 4039) that were analyzed for Varroa mite infestation, the overall VIL in the U.S. ranged between 0.4 and 30.85%, with an overall national VIL and Varroa prevalence of 8.21% and 85.14%, respectively. Overall monthly data showed VIL constantly exceeded the critical level of 4% except from June to September and reached a maximum of 15% in January and December. Nationwide, VIL significantly (p < 0.001) increased from 2015 to 2018 (1.1–4.7%), plateaued from 2018 to 2021 (4.7–4.5%), followed by a significant decrease in 2022 (3.6%). Significant VIL differences (p < 0.001) were recorded among climate regions, with the highest mite infestation levels in the Upper Midwest region (13.9%) and the lowest in the West region (5.1%). Of adult bee samples (n = 2,994) that were analyzed for Nosema infection, Nosema spore count ranged between (1–16.8) million spores per bee among states, with a national average of 6.8 and a prevalence of 99.7%. The lowest and highest Nosema loads were respectively recorded in the South region (3.1) and Upper Midwest (10.5), a significant difference (p < 0.001). No statistical differences were recorded among the six other climate regions. Overall, VIL and Nosema infection correlated significantly (p < 0.001) with a regression coefficient of (R2 = 0.6). Our data, which originated from ailing bee colonies, showed significantly higher rates of maladies compared to data from healthy colonies obtained by the USDA-APHIS National Honey Bee Survey, demonstrating the role of bee diseases caused by Varroa mite and Nosema in honey bee population declines.
Transcriptomic characterization of the human segmental endotoxin challenge model
Authors: Gress Christina , Litzenburger Tobias , Schmid Ramona , Xiao Ke , Heissig Florian , Muller Meike , Gupta Abhya , Hohlfeld Jens M. 
Published: January 2024

AbstractSegmental instillation of lipopolysaccharide (LPS) by bronchoscopy safely induces transient airway inflammation in human lungs. This model enables investigation of pulmonary inflammatory mechanisms as well as pharmacodynamic analysis of investigational drugs. The aim of this work was to describe the transcriptomic profile of human segmental LPS challenge with contextualization to major respiratory diseases. Pre-challenge bronchoalveolar lavage (BAL) fluid and biopsies were sampled from 28 smoking, healthy participants, followed by segmental instillation of LPS and saline as control. Twenty-four hours post instillation, BAL and biopsies were collected from challenged lung segments. Total RNA of cells from BAL and biopsy samples were sequenced and analysed for differentially expressed genes (DEGs). After challenge with LPS compared with saline, 6316 DEGs were upregulated and 241 were downregulated in BAL, but only one DEG was downregulated in biopsy samples. Upregulated DEGs in BAL were related to molecular functions such as “Inflammatory response” or “chemokine receptor activity”, and upregulated pro-inflammatory pathways such as “Wnt-"/“Ras-"/“JAK-STAT” “-signaling pathway”. Furthermore, the segmental LPS challenge model resembled aspects of the five most prevalent respiratory diseases chronic obstructive pulmonary disease (COPD), asthma, pneumonia, tuberculosis and lung cancer and featured similarities with acute exacerbations in COPD (AECOPD) and community-acquired pneumonia. Overall, our study provides extensive information about the transcriptomic profile from BAL cells and mucosal biopsies following LPS challenge in healthy smokers. It expands the knowledge about the LPS challenge model providing potential overlap with respiratory diseases in general and infection-triggered respiratory insults such as AECOPD in particular.
Public support for more stringent vaccine policies increases with vaccine effectiveness
Authors: Koenig Richard , Savani Manu Manthri , Lee-Whiting Blake , McAndrews John , Banerjee Sanchayan , Hunter Andrew , John Peter , Loewen Peter John , Nyhan Brendan 
Published: January 2024

AbstractUnder what conditions do citizens support coercive public policies? Although recent research suggests that people prefer policies that preserve freedom of choice, such as behavioural nudges, many citizens accepted stringent policy interventions like fines and mandates to promote vaccination during the COVID-19 pandemic—a pattern that may be linked to the unusually high effectiveness of COVID-19 vaccines. We conducted a large online survey experiment (N = 42,417) in the Group of Seven (G-7) countries investigating the relationship between a policy’s effectiveness and public support for stringent policies. Our results indicate that public support for stringent vaccination policies increases as vaccine effectiveness increases, but at a modest scale. This relationship flattens at higher levels of vaccine effectiveness. These results suggest that intervention effectiveness can be a significant predictor of support for coercive policies but only up to some threshold of effectiveness.
Development of an invasion score based on metastasis-related pathway activity profiles for identifying invasive molecular subtypes of lung adenocarcinoma
Authors: Han Tao , Liu Yafeng , Zhou Jiawei , Guo Jianqiang , Xing Yingru , Xie Jun , Bai Ying , Wu Jing , Hu Dong 
Published: January 2024

AbstractThe invasive capacity of lung adenocarcinoma (LUAD) is an important factor influencing patients’ metastatic status and survival outcomes. However, there is still a lack of suitable biomarkers to evaluate tumor invasiveness. LUAD molecular subtypes were identified by unsupervised consistent clustering of LUAD. The differences in prognosis, tumor microenvironment (TME), and mutation were assessed among different subtypes. After that, the invasion-related gene score (IRGS) was constructed by genetic differential analysis, WGCNA analysis, and LASSO analysis, then we evaluated the relationship between IRGS and invasive characteristics, TME, and prognosis. The predictive ability of the IRGS was verified by in vitro experiments. Next, the “oncoPredict” R package and CMap were used to assess the potential value of IRGS in drug therapy. The results showed that LUAD was clustered into two molecular subtypes. And the C1 subtype exhibited a worse prognosis, higher stemness enrichment activity, less immune infiltration, and higher mutation frequency. Subsequently, IRGS developed based on molecular subtypes demonstrated a strong association with malignant characteristics such as invasive features, higher stemness scores, less immune infiltration, and worse survival. In vitro experiments showed that the higher IRGS LUAD cell had a stronger invasive capacity than the lower IRGS LUAD cell. Predictive analysis based on the “oncoPredict” R package showed that the high IRGS group was more sensitive to docetaxel, erlotinib, paclitaxel, and gefitinib. Among them, in vitro experiments verified the greater killing effect of paclitaxel on high IRGS cell lines. In addition, CMap showed that purvalanol-a, angiogenesis-inhibitor, and masitinib have potential therapeutic effects in the high IRGS group. In summary we identified and analyzed the molecular subtypes associated with the invasiveness of LUAD and developed IRGS that can efficiently predict the prognosis and invasive ability of the tumor. IRGS may be able to facilitate the precision treatment of LUAD to some extent.
Investigation, scaffold hopping of novel donepezil-based compounds as anti-Alzhiemer’s agents: synthesis, in-silico and pharmacological evaluations
Authors: Gupta Mohan , Pant Swati , Rana Preeti , Kumar Avinash , Prasun Chakrawarti , Nair Maya S. , Paliwal Sarvesh , Nain Sumitra 
Published: January 2024

AbstractAlzheimer’s disease (AD) is a multifaceted neurodegenerative condition. The pathogenesis of AD is highly intricate and the disease is apparent in the aged population ~ 50–70 years old. Even after > 100 years of research, the root origin of AD and its pathogenesis is unclear, complex and multifaceted. Herein, we have designed and synthesized 9 novel molecules with three different heterocyclic scaffolds namely pyrrolidone-2-one, quinoline & indoline-2-one to imitate and explore the novel chemical space around donepezil. The synthesized molecules were evaluated for their potential as anti-Alzheimer’s agents through in-vitro and in-vivo studies in appropriate animal models. To further understand their interaction with acetylcholinesterase enzyme (AChE), extra-precision docking, and molecular dynamics simulation studies were carried out. As the number of compounds was limited to thoroughly explore the structure–activity relationship, atom-based 3D-quantitative structure–activity relationships (QSAR) studies were carried out to get more insights. All the designed compounds were found to inhibit AChE with IC50 in the micromolar range. From pyrrolidone-2-one series, 6-chloro-N-(1-(1-(3,4-dimethoxybenzyl)-2-oxopyrrolidin-3-yl)piperidin-4-yl)pyridine-3-sulfonamide (9), 2-(1-benzylpiperidin-4-yl)-6,7-dimethoxy-4-(4-methoxyphenyl)quinoline (18) from quinoline series and N-(1-benzylpiperidin-4-yl)-2-(2-oxoindolin-3-yl)acetamide (23) from indolin-2-one series inhibited AChE with an IC50 value of 0.01 µM. Based on other biochemical studies like lipid peroxidation, reduced glutathione, superoxide dismutase, catalase, nitrite, and behavioural studies (Morris water maze), compound 9 was found to be a potent AChE inhibitor which can be further explored as a lead molecule to design more potent and effective anti-Alzheimer’s agents.
Deep learning strategies with CReToNeXt-YOLOv5 for advanced pig face emotion detection
Authors: Nie Lili , Li Bugao , Du Yihan , Jiao Fan , Song Xinyue , Liu Zhenyu 
Published: January 2024

AbstractThis study underscores the paramount importance of facial expressions in pigs, serving as a sophisticated mode of communication to gauge their emotions, physical well-being, and intentions. Given the inherent challenges in deciphering such expressions due to pigs' rudimentary facial muscle structure, we introduced an avant-garde pig facial expression recognition model named CReToNeXt-YOLOv5. The proposed model encompasses several refinements tailored for heightened accuracy and adeptness in detection. Primarily, the transition from the CIOU to the EIOU loss function optimized the training dynamics, leading to precision-driven regression outcomes. Furthermore, the incorporation of the Coordinate Attention mechanism accentuated the model's sensitivity to intricate expression features. A significant innovation was the integration of the CReToNeXt module, fortifying the model's prowess in discerning nuanced expressions. Efficacy trials revealed that CReToNeXt-YOLOv5 clinched a mean average precision (mAP) of 89.4%, marking a substantial enhancement by 6.7% relative to the foundational YOLOv5. Crucially, this advancement holds profound implications for animal welfare monitoring and research, as our findings underscore the model's capacity to revolutionize the accuracy of pig facial expression recognition, paving the way for more humane and informed livestock management practices.
Dataset meta-level and statistical features affect machine learning performance
Authors: Uddin Shahadat , Lu Haohui 
Published: January 2024

AbstractWhat dataset features affect machine learning (ML) performance has primarily been unknown in the current literature. This study examines the impact of tabular datasets' different meta-level and statistical features on the performance of various ML algorithms. The three meta-level features this study considered are the dataset size, the number of attributes and the ratio between the positive (class 1) and negative (class 0) class instances. It considered four statistical features for each dataset: mean, standard deviation, skewness and kurtosis. After applying the required scaling, this study averaged (uniform and weighted) each dataset’s different attributes to quantify its four statistical features. We analysed 200 open-access tabular datasets from the Kaggle (147) and UCI Machine Learning Repository (53) and developed ML classification models (through classification implementation and hyperparameter tuning) for each dataset. Then, this study developed multiple regression models to explore the impact of dataset features on ML performance. We found that kurtosis has a statistically significant negative effect on the accuracy of the three non-tree-based ML algorithms of the Support vector machine (SVM), Logistic regression (LR) and K-nearest neighbour (KNN) for their classical implementation with both uniform and weighted aggregations. This study observed similar findings in most cases for ML implementations through hyperparameter tuning, except for SVM with weighted aggregation. Meta-level and statistical features barely show any statistically significant impact on the accuracy of the two tree-based ML algorithms (Decision tree and Random forest), except for implementation through hyperparameter tuning for the weighted aggregation. When we excluded some datasets based on the imbalanced statistics and a significantly higher contribution of one attribute compared to others to the classification performance, we found a significant effect of the meta-level ratio feature and statistical mean and standard deviation features on SVM, LR and KNN accuracy in many cases. Our findings open a new research direction in understanding how dataset characteristics affect ML performance and will help researchers select appropriate ML algorithms for a possible optimal accuracy outcome.
Transfer of magnetic anisotropy in epitaxial Co/NiO/Fe trilayers
Authors: Szpytma M. , Ślęzak M. , Janus W. , Nayyef H. , Ślęzak T. , Mandziak A. , Zając M. , Wilgocka-Ślęzak D. , Menteş T. O. , Jugovac M. , Locatelli A. , Kozioł-Rachwał A. 
Published: January 2024

AbstractThe magnetic properties of Co(10 Å)/NiO(40 Å)/Fe trilayer epitaxially grown on W(110) substrate were investigated with use of x-ray magnetic linear dichroism (XMLD) and x-ray magnetic circular dichroism (XMCD). We showed that magnetic anisotropy of Fe film that can be controlled by a thickness-driven spin reorientation transition is transferred via interfacial exchange coupling not only to NiO layer but further to ferromagnetic Co overlayer as well. Similarly, a temperature driven spin reorientation of Fe sublayer induces a reorientation of NiO spin orientation and simultaneous switching of the Co magnetization direction. Finally, by element specific XMCD and XMLD magnetic hysteresis loop measurements we proved that external magnetic field driven reorientation of Fe and Co magnetizations as well as NiO Néel vector are strictly correlated and magnetic anisotropy fields of Fe and Co sublayers are identical despite the different crystal structures.
Free light-shape focusing in extreme-ultraviolet radiation with self-evolutionary photon sieves
Authors: Cui Huaiyu , Zhang Xiuping , Li You , Zhao Dongdi , Zhang Junyong , Zhao Yongpeng 
Published: January 2024

AbstractExtreme-ultraviolet (EUV) radiation is a promising tool, not only for probing microscopic activities but also for processing nanoscale structures and performing high-resolution imaging. In this study, we demonstrate an innovative method to generate free light-shape focusing with self-evolutionary photon sieves under a single-shot coherent EUV laser; this includes vortex focus shaping, array focusing, and structured-light shaping. The results demonstrate that self-evolutionary photon sieves, consisting of a large number of specific pinholes fabricated on a piece of Si3N4 membrane, are capable of freely regulating an EUV light field, for which high-performance focusing elements are extremely lacking, let alone free light-shape focusing. Our proposed versatile photon sieves are a key breakthrough in focusing technology in the EUV region and pave the way for high-resolution soft X-ray microscopy, spectroscopy in materials science, shorter lithography, and attosecond metrology in next-generation synchrotron radiation and free-electron lasers.
Ovipositional responses of tortricid moths to sugars, salts and neem oil
Authors: Amat Carles , Prasad Rajendra , Gemeno César 
Published: January 2024

AbstractOviposition is essential in the life history of insects and is mainly mediated by chemical and tactile cues present on the plant surface. Oviposition deterrents or stimulants can modify insect oviposition and be employed in pest control. Relatively few gustatory oviposition stimuli have been described for tortricid moths. In this study the effect of NaCl, KCl, sucrose, fructose and neem oil on the number of eggs laid by Cydia pomonella (L.), Grapholita molesta (Busck) and Lobesia botrana (Dennis & Schifermüller) was tested in laboratory arenas containing filter papers loaded with 3 doses of a given stimulus and solvent control. In general, salts increased oviposition at the mid dose (102 M) and sugars reduced it at the highest dose (103 mM), but these effects depended on the species. Neem oil dramatically reduced the number of eggs laid as the dose increased, but the lowest neem oil dose (0.1% v/v) increased L. botrana oviposition relative to solvent control. Our study shows that ubiquitous plant chemicals modify tortricid moth oviposition under laboratory conditions, and that neem oil is a strong oviposition deterrent. The oviposition arena developed in this study is a convenient tool to test the effect of tastants on the oviposition behavior of tortricid moths.
Development of an optogenetics tool, Opto-RANK, for control of osteoclast differentiation using blue light
Authors: Takada Aiko , Asano Toshifumi , Nakahama Ken-ichi , Ono Takashi , Nakata Takao , Ishii Tomohiro 
Published: January 2024

AbstractOptogenetics enables precise regulation of intracellular signaling in target cells. However, the application of optogenetics to induce the differentiation of precursor cells and generate mature cells with specific functions has not yet been fully explored. Here, we focused on osteoclasts, which play an important role in bone remodeling, to develop a novel optogenetics tool, Opto-RANK, which can manipulate intracellular signals involved in osteoclast differentiation and maturation using blue light. We engineered Opto-RANK variants, Opto-RANKc and Opto-RANKm, and generated stable cell lines through retroviral transduction. Differentiation was induced by blue light, and various assays were conducted for functional analysis. Osteoclast precursor cells expressing Opto-RANK differentiated into multinucleated giant cells on light exposure and displayed upregulation of genes normally induced in differentiated osteoclasts. Furthermore, the differentiated cells exhibited bone-resorbing activities, with the possibility of spatial control of the resorption by targeted light illumination. These results suggested that Opto-RANK cells differentiated by light possess the features of osteoclasts, both morphological and functional. Thus, Opto-RANK should be useful for detailed spatiotemporal analysis of intracellular signaling during osteoclast differentiation and the development of new therapies for various bone diseases.
The application of synthetic antibacterial minerals to combat topical infections: exploring a mouse model of MRSA infection
Authors: Morrison Keith D. , Reiss Meghan B. , Tanner Tanya D. , Gollott Travis R. , Loots Gabriela G. , Collette Nicole M. 
Published: January 2024

AbstractThe development of new antibiotics has stalled, and novel strategies are needed as we enter the age of antibiotic resistance. Certain naturally occurring clays have been shown to be effective in killing antibiotic resistant bacteria. However, these natural clays are too variable to be used in clinical settings. Our study shows that synthetic antibacterial minerals exhibit potent antibacterial activity against topical MRSA infections and increase the rate of wound closure relative to controls. The antibacterial minerals maintain a redox cycle between Fe2+/Fe3+ and the surfaces of pyrite minerals, which act as a semiconductor and produce reactive oxygen species (ROS), while smectite minerals act as a cation exchange reservoir. Acidic conditions are maintained throughout the application of the hydrated minerals and can mitigate the alkaline pH conditions observed in chronic non-healing wounds. These results provide evidence for the strategy of ‘iron overload’ to combat antibiotic resistant infections through the maintained release of Fe2+ and generation of ROS via distinct geochemical reactions that can break the chronic wound damage cycle.
Detection of DNA methylation signatures through the lens of genomic imprinting
Authors: Hubert Jean-Noël , Iannuccelli Nathalie , Cabau Cédric , Jacomet Eva , Billon Yvon , Serre Rémy-Félix , Vandecasteele Céline , Donnadieu Cécile , Demars Julie 
Published: January 2024

AbstractGenomic imprinting represents an original model of epigenetic regulation resulting in a parent-of-origin expression. Despite the critical role of imprinted genes in mammalian growth, metabolism and neuronal function, there is no molecular tool specifically targeting them for a systematic evaluation. We show here that enzymatic methyl-seq consistently outperforms the bisulfite-based standard in capturing 165 candidate regions for genomic imprinting in the pig. This highlights the potential for a turnkey, fully customizable and reliable capture tool of genomic regions regulated by cytosine methylation in any population of interest. For the field of genomic imprinting, it opens up the possibility of detecting multilocus imprinting variations across the genome, with implications for basic research, agrigenomics and clinical practice.
Phase-controlled coherent photons for the quantum correlations in a delayed-choice quantum eraser scheme
Authors: Ham Byoung S. 
Published: January 2024

AbstractThe delayed-choice quantum eraser has been intensively studied for the wave-particle duality of a single photon in an interferometric system over the last decades. Super-resolution has been studied over decades for quantum sensing to overcome the standard quantum limit. For the super-resolution, either quantum features of higher-order entangled photon pairs or classical features of phase-controlled coherent photons have been successfully demonstrated. Here, a method of classically excited super-resolution is presented for the phase-controlled coherent photons in a quarter-wave plate-modified quantum eraser scheme. To support the underlying physics of the super-resolution, nonlocal correlation is also presented with an additional frequency-polarization basis control via selective product-basis measurements.