bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emotional and behavioral problems change the development of cerebellar gray matter volume, thickness, and surface area from childhood to adolescence: A longitudinal cohort study
Authors: Wang Yanpei , Ma Leilei , Chen Rui , Liu Ningyu , Zhang Haibo , Li Yuanyuan , Wang Jiali , Hu Mingming , Zhao Gai , Men Weiwei , Tan Shuping , Gao Jia‐Hong , Qin Shaozheng , He Yong , Dong Qi , Tao Sha 
Published: June 2023

AbstractAimsIncreasing evidence indicates that major neurodevelopmental disorders have potential links to abnormal cerebellar development. However, the developmental trajectories of cerebellar subregions from childhood to adolescence are lacking, and it is not clear how emotional and behavioral problems affect them. We aim to map the developmental trajectories of gray matter volume (GMV), cortical thickness (CT), and surface area (SA) in cerebellar subregions from childhood to adolescence and examine how emotional and behavioral problems change the cerebellar development trajectory in a longitudinal cohort study.MethodThis population‐based longitudinal cohort study used data on a representative sample of 695 children. Emotional and behavioral problems were assessed at baseline and at three annual follow‐ups with the Strengths and Difficulties Questionnaire (SDQ).ResultsUsing an innovative automated image segmentation technique, we quantified the GMV, CT, and SA of the whole cerebellum and 24 subdivisions (lobules I‐VI, VIIB, VIIIA&B, and IX‐X plus crus I‐II) with 1319 MRI scans from a large longitudinal sample of 695 subjects aged 6–15 years and mapped their developmental trajectories. We also examined sex differences and found that boys showed more linear growth, while girls showed more nonlinear growth. Boys and girls showed nonlinear growth in the cerebellar subregions; however, girls reached the peak earlier than boys. Further analysis found that emotional and behavioral problems modulated cerebellar development. Specifically, emotional symptoms impede the expansion of the SA of the cerebellar cortex, and no gender differences; conduct problems lead to inadequate cerebellar GMV development only in girls, but not boys; hyperactivity/inattention delays the development of cerebellar GMV and SA, with left cerebellar GMV, right VIIIA GMV and SA in boys and left V GMV and SA in girls; peer problems disrupt CT growth and SA expansion, resulting in delayed GMV development, with bilateral IV, right X CT in boys and right Crus I GMV, left V SA in girls; and prosocial behavior problems impede the expansion of the SA and lead to excessive CT growth, with bilateral IV, V, right VI CT, left cerebellum SA in boys and right Crus I GMV in girls.ConclusionsThis study maps the developmental trajectories of GMV, CT, and SA in cerebellar subregions from childhood to adolescence. In addition, we provide the first evidence for how emotional and behavioral problems affect the dynamic development of GMV, CT, and SA in the cerebellum, which provides an important basis and guidance for the prevention and intervention of cognitive and emotional behavioral problems in the future.
A neuromarker for deficit syndrome in schizophrenia from a combination of structural and functional magnetic resonance imaging
Authors: Gao Ju , Jiang Rongtao , Tang Xiaowei , Chen Jiu , Yu Miao , Zhou Chao , Wang Xiang , Zhang Hongying , Huang Chengbing , Yang Yong , Zhang Xiaobin , Cui Zaixu , Zhang Xiangrong 
Published: June 2023

AbstractAimDeficit schizophrenia (DS), defined by primary and enduring negative symptoms, has been proposed as a promising homogeneous subtype of schizophrenia. It has been demonstrated that unimodal neuroimaging characteristics of DS were different from non‐deficit schizophrenia (NDS), however, whether multimodal‐based neuroimaging features could identify deficit syndrome remains to be determined.MethodsFunctional and structural multimodal magnetic resonance imaging of DS, NDS and healthy controls were scanned. Voxel‐based features of gray matter volume, fractional amplitude of low‐frequency fluctuations, and regional homogeneity were extracted. The support vector machine classification models were constructed using these features separately and jointly. The most discriminative features were defined as the first 10% of features with the greatest weights. Moreover, relevance vector regression was applied to explore the predictive values of these top‐weighted features in predicting negative symptoms.ResultsThe multimodal classifier achieved a higher accuracy (75.48%) compared with the single modal model in distinguishing DS from NDS. The most predictive brain regions were mainly located in the default mode and visual networks, exhibiting differences between functional and structural features. Further, the identified discriminative features significantly predicted scores of diminished expressivity factor in DS but not NDS.ConclusionsThe present study demonstrated that local properties of brain regions extracted from multimodal imaging data could distinguish DS from NDS with a machine learning‐based approach and confirmed the relationship between distinctive features and the negative symptoms subdomain. These findings may improve the identification of potential neuroimaging signatures and improve the clinical assessment of the deficit syndrome.
A dual‐channel ensembled deep convolutional neural network for facial expression recognition in the wild
Authors: Saurav Sumeet , Saini Ravi , Singh Sanjay 
Published: June 2023

AbstractFacial expression recognition (FER) in the wild is an active and challenging field of research. A system for automatic FER finds use in a wide range of applications related to advanced human–computer interaction (HCI), human–robot interaction (HRI), human behavioral analysis, gaming and entertainment, etc. Since their inception, convolutional neural networks (CNNs) have attained state‐of‐the‐art accuracy in the facial analysis task. However, recognizing facial expressions in the wild with high confidence running on a low‐cost embedded device remains challenging. To this end, this study presents an efficient dual‐channel ensembled deep CNN (DCE‐DCNN) for FER in the wild. Initially, two DCNNs, namely the and , are trained separately on the grayscale and Scharr‐convolved vertical gradient facial images, respectively. The proposed network later integrates the two pre‐trained DCNNs to obtain the dual‐channel integrated DCNN (DCI‐DCNN). Finally, all three neural networks, namely the , , and DCI‐DCNN, are jointly fine‐tuned to get a single dual‐channel‐multi‐output model. The multi‐output model produces three prediction scores for the given input facial image. The prediction scores are thus fused using the max‐voting ensemble scheme to obtain the DCE‐DCNN with the final classification label. On the FER2013, RAF‐DB, NCAER‐S, AffectNet, and CKPlus benchmark FER datasets, the proposed DCE‐DCNN consistently outperforms the two individual DCNNs and numerous state‐of‐the‐art CNNs. Moreover, the network achieves competitive recognition accuracy on all four FER in the wild datasets with reduced memory storage size and parameters. The proposed DCE‐DCNN model with high throughput on resource‐limited embedded devices is suitable for applications that seek real‐time classification of facial expressions in the wild with high confidence.
Advancing protected area effectiveness assessments by disentangling social‐ecological interactions: A case study from the Luangwa Valley, Zambia
Authors: Frietsch Marina , Zafra‐Calvo Noelia , Ghoddousi Arash , Loos Jacqueline 
Published: June 2023

AbstractProtected and conserved areas (PCAs) target at biodiversity conservation and human well‐being, but often reflect low levels of effectiveness. Understanding PCAs social‐ecological systems in which people and nature interact in so‐called social‐ecological interactions is key to understanding the roots of (in)effectiveness, and to leverage change toward resilient and sustainable systems. Despite this potential, social‐ecological interactions in PCAs are commonly neglected in effectiveness evaluations. To address this gap, we elaborated a thorough understanding of the social‐ecological interactions in PCAs through the following steps: In a first step, we extracted from scientific literature which social‐ecological interactions influence the effectiveness of PCAs in general and derived influencing factors which shape those interactions. Based on these insights, we developed an analytical framework, which, in a second step, we applied to a case study in North Luangwa, Zambia. We elucidated three dimensions of social‐ecological interactions occurring in the study area: care (e.g., conservation programs), conflict (e.g., disease transmission), and use (e.g., hunting). We visualized relationships between these interactions and associated key variables in a causal loop diagram. Finally, we drew on the case study in Zambia's Luangwa Valley to propose system‐specific metrics for key variables central to the social‐ecological structure of the study area to make effectiveness measurable. Our approach allows for linking site‐specific social‐ecological interactions to PCA effectiveness. More generally, our findings call for the consideration of the relationships between people and nature when assessing conservation effectiveness.
Field validation as a tool for mitigating uncertainty in species distribution modeling for conservation planning
Authors: Johnson Sara , Molano‐Flores Brenda , Zaya David 
Published: June 2023

AbstractDespite the success of species distribution models (SDMs) in rare species conservation planning, inherent uncertainty in predictions can facilitate misuse or misapplication. Field validation is important as model predictions can vary greatly due to low species prevalence or spatial bias; traits frequently encountered in rare species data. This study outlines an effective SDM approach to map the potential distribution of a Florida endemic plant species, Macbridea alba, which is transferable to other rare species that: (1) utilize presence data to create species distribution maps, (2) conduct field validation to gather independent data, (3) and use independent data for model evaluation and improvement. Independent data was used to assess each model's ability to predict the occurrence of M. alba and identify habitat for conservation and reintroduction efforts. Our study documents that for low prevalence species, models can produce significant variation in optimized threshold and evaluation metrics, which impact outcomes when converting continuous predictions to binary predictions, a common practice in model application. Our species distribution models were useful in finding new populations of M. alba. Field validation is vital to improving model performance, threshold selection, and evaluating model design and should be carefully considered when suggesting model use and application.
Responsible Behavior of Irresponsible Companies: Air Pollution and Charitable Donations of Polluting Companies
Authors: Li Weibing , Chen Siyuan , Zhang Kaixia 
Published: June 2023

AbstractThe relationship between air pollution and charitable donations of companies has received little attention from academia. To make up for this defect, we use a regression discontinuity design based on the spatial discontinuity in air pollution created by China's winter heating policy in the north of Qinling Mountains–Huai River line to examine whether severe air pollution may cause polluting companies to make charitable donations. Our results consistently show that air pollution has a positive impact on the donations of polluting companies, regardless of whether the absolute donations, the relative donations, or the willingness to donate are used to measure donations. A series of robustness tests confirm that this relationship is causal. Furthermore, we find that under severe air pollution, the motivations of polluting companies to implement donation behaviors are to decrease the probability of environmental penalties, reduce environmental pollution costs, and decrease the extent to which air pollution affects company reputations.
Impact of computer‐aided characterization for diagnosis of colorectal lesions, including sessile serrated lesions: Multireader, multicase study
Authors: Kato Shun , Kudo Shin‐ei , Minegishi Yosuke , Miyata Yuki , Maeda Yasuharu , Kuroki Takanori , Takashina Yuki , Mochizuki Kenichi , Tamura Eri , Abe Masahiro , Sato Yuta , Sakurai Tatsuya , Kouyama Yuta , Tanaka Kenta , Ogawa Yushi , Nakamura Hiroki , Ichimasa Katsuro , Ogata Noriyuki , Hisayuki Tomokazu , Hayashi Takemasa , Wakamura Kunihiko , Miyachi Hideyuki , Baba Toshiyuki , Ishida Fumio , Nemoto Tetsuo , Misawa Masashi ,   Collaborators
Published: June 2023

ObjectivesComputer‐aided characterization (CADx) may be used to implement optical biopsy strategies into colonoscopy practice; however, its impact on endoscopic diagnosis remains unknown. We aimed to evaluate the additional diagnostic value of CADx when used by endoscopists for assessing colorectal polyps.MethodsThis was a single‐center, multicase, multireader, image‐reading study using randomly extracted images of pathologically confirmed polyps resected between July 2021 and January 2022. Approved CADx that could predict two‐tier classification (neoplastic or nonneoplastic) by analyzing narrow‐band images of the polyps was used to obtain a CADx diagnosis. Participating endoscopists determined if the polyps were neoplastic or not and noted their confidence level using a computer‐based, image‐reading test. The test was conducted twice with a 4‐week interval: the first test was conducted without CADx prediction and the second test with CADx prediction. Diagnostic performances for neoplasms were calculated using the pathological diagnosis as reference and performances with and without CADx prediction were compared.ResultsFive hundred polyps were randomly extracted from 385 patients and diagnosed by 14 endoscopists (including seven experts). The sensitivity for neoplasia was significantly improved by referring to CADx (89.4% vs. 95.6%). CADx also had incremental effects on the negative predictive value (69.3% vs. 84.3%), overall accuracy (87.2% vs. 91.8%), and high‐confidence diagnosis rate (77.4% vs. 85.8%). However, there was no significant difference in specificity (80.1% vs. 78.9%).ConclusionsComputer‐aided characterization has added diagnostic value for differentiating colorectal neoplasms and may improve the high‐confidence diagnosis rate.
Molecular detection of reproductive symbionts and parthenogenesis experiments in Tuta absoluta from Argentina: facing potential for sustainable and specific pest control strategies
Authors: Cagnotti C. , Conte C. , Kramar J. , Lanzavecchia S. , López S. 
Published: June 2023

AbstractTomato leafminer, Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae), is a key pest of tomato crops. Specific and environmentally friendly control strategies against this pest, such as the sterile insect technique (SIT), are under development and sexual reproduction has emerged as a key focal point to ensure its success. In the present study, we analyzed four representative T. absoluta populations from Argentina, focusing on the molecular detection of endosymbionts potentially associated with reproductive abnormalities and on determining whether parthenogenesis can occur under laboratory conditions. Larvae of T. absoluta were collected in commercial tomato plantations from La Plata and Mar del Plata (both in Buenos Aires province), Bella Vista (Corrientes province), and Yuto (Jujuy province). Tuta absoluta adults were evaluated by standard PCR for the presence of reproductive endosymbionts (Wolbachia sp., Spiroplasma sp., Arsenophonus sp., Cardinium sp., and Rickettsia sp.). For parthenogenesis assays, 20–23 virgin females from each T. absoluta geographic population were life‐long isolated in Petri dishes with a tomato leaf. Fecundity, fertility, and female longevity were estimated and compared with results from mated females from each population. Our results showed the presence of a unique endosymbiont (Wolbachia sp. supergroup B, sequence type 41). Fecundity of the unmated females was significantly lower than fecundity of mated females in all T. absoluta populations. In addition, unmated females only laid infertile eggs. In conclusion, the absence of parthenogenesis in T. absoluta from representative geographic populations supports the implementation of SIT and mating disruption as effective control strategies against this pest in Argentina.
Assessing the impact of interfering organic matter on soil metaproteomic workflow
Authors: Waibel Matthias , McDonnell Kevin , Tuohy Maria , Shirran Sally , Synowsky Sylvia , Thornton Barry , Paterson Eric , Brennan Fiona , Abram Florence 
Published: June 2023

AbstractSoil organic matter (SOM) is biologically, chemically, and physically complex. As a major store of nutrients within the soil, it plays an important role in nutrient provision to plants. An enhanced understanding of SOM utilisation processes could underpin better fertiliser management for plant growth, with reduced environmental losses. Metaproteomics can allow the characterisation of protein profiles and could help gain insights into SOM microbial decomposition mechanisms. Here, we applied three different extraction methods to two soil types to recover SOM with different characteristics. Specifically, water‐extractable organic matter, mineral‐associated organic matter and protein‐bound organic matter were targeted with the aim to investigate the metaproteome enriched in those extractions. As a proof‐of‐concept, replicated extracts from one soil were further analysed for peptide identification using liquid chromatography followed by tandem mass spectrometry. We employed a framework for mining mass spectra for both peptide assignment and fragmentation pattern characterisation. Different extracts were found to exhibit contrasting total protein and humic substance content for the two soils investigated. Overall, water extracts displayed the lowest humic substance content (in both soils) and the highest number of peptide identifications (in the soil investigated) with the most frequent peptide hits associated with diverse substrate/ligand binding proteins of Proteobacteria and derived taxa. Our framework also highlighted a strong peptidic signal in unassigned and unmatched spectra, information that is currently not captured by the pipelines employed in this study. Taken together, this work points to specific areas for optimisation in chromatography and mass spectrometry to adequately characterise SOM‐associated metaproteomes.
Pupal RNA interference methods for analyzing adult development in stag beetles
Authors: Hagiwara Jin , Nozawa Leon , Ohtsu Itsuki , Shinohara Tadashi , Gotoh Hiroki 
Published: June 2023

AbstractHolometabolous insects dramatically change their morphology via molt, both from larva to pupa and from pupa to adult. In nonmodel insects, RNA interference (RNAi) is a strong tool for analyzing gene function during postembryonic development. In many cases, larval RNAi is effective for analyzing genes involved in morphogenesis via metamorphosis. However, RNAi of genes involved in development sometimes results in lethality before animals metamorphose to pupae and/or adults, making it impossible to analyze their function during the pupal period. In this study, we establish a pupal RNAi system in the stag beetle Dorcus rectus. We selected the genes white and scarlet for RNAi knockdown to investigate appropriate injection timing and position. Both genes are known to be involved in eye pigmentation. By using these candidate genes, we demonstrate the potential of pupal RNAi in this experimental system. This method will be useful for analyzing pupal‐specific morphogenesis including fine‐shaping of the enlarged male mandible in this species.
Celebrating Nicaea
Authors: Durber Susan 
Published: June 2023

AbstractWhy should Christians from churches of the Reformation be marking the 1700th anniversary of Nicaea? Some Christians from such churches regard Nicaea as emblematic of Christianity's “fall” from the radical and subversive faith of Jesus’ teaching, miracles, and welcome to become an abstract and theological discourse dependent not on the Bible but on Greek philosophy. Some ask why they should pay any attention to a long ago gathering of male bishops or let that gathering, rather than simply the Bible and their own personal faith experience, shape their understanding of Christianity. In this paper, the author, herself from a church often inclined to such Protestant critiques of Nicaea, suggests a more open approach and a positive understanding of Nicaea for today's church.
St Cyril of Alexandria and the Council of Nicaea
Authors: Serapion Metropolitan , Refela Macarius 
Published: June 2023

AbstractIn commemorating the Council of Nicaea, we are not looking solely at the document that it produced, nor simply the words contained in a manuscript, but the lived tradition that produced it and continues to refine our understanding. This article will therefore explore how in the century that followed the Council of Nicaea, St Cyril of Alexandria, in seeking to combat Nestorianism, in which Christ is asserted to have had distinct human and divine persons, and Mary denied the status of Theotokos (mother of God), argued not on the basis of the literal wording of the Creed of Nicaea, but on the lived tradition that produced it and continues to refine our understanding of it.
“Light from Light”
Authors: Munkholt Christensen Maria 
Published: June 2023

AbstractThis article examines the phrase “light from light” in the 4th‐century Nicene and Nicene‐Constantinopolitan creeds. The article begins by presenting the earliest use of light as a metaphor for Christ and his agency, as well as examples of similar language outside “orthodox” Christianity. It goes on to examine the meaning and use of “light from light” in the orthodox creeds and the debates that accompanied them before discussing the more popular use of “light from light” in Late antiquity/Byzantine piety. The article concludes by considering the contemporary potential in the formulation “light from light.”