bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring conventional and emerging dehydration technologies for slurry/liquid food matrices and their impact on porosity of powders: A comprehensive review
Authors: Sultana Afroza , Aghajanzadeh Sara , Thibault Bruno , Ratti Cristina , Khalloufi Seddik 
Published: April 2024

AbstractThe contribution of dehydration to the growing market of food powders from slurry/liquid matrices is inevitable. To overcome the challenges posed by conventional drying technologies, several innovative approaches have emerged. However, industrial implementation is limited due to insufficient information on the best‐suited drying technologies for targeted products. Therefore, this review aimed to compare various conventional and emerging dehydration technologies (such as active freeze, supercritical, agitated thin‐film, and vortex chamber drying) based on their fundamental principles, potential applications, and limitations. Additionally, this article reviewed the effects of drying technologies on porosity, which greatly influence the solubility, rehydration, and stability of powder. The comparison between different drying technologies enables informed decision‐making in selecting the appropriate one. It was found that active freeze drying is effective in producing free‐flowing powders, unlike conventional freeze drying. Vortex chamber drying could be considered a viable alternative to spray drying, requiring a compact chamber than the large tower needed for spray drying. Freeze‐dried, spray freeze‐dried, and foam mat‐dried powders exhibit higher porosity than spray‐dried ones, whereas supercritical drying produces nano‐porous interconnected powders. Notably, several factors like glass transition temperature, drying technologies, particle aggregation, agglomeration, and sintering impact powder porosity. However, some binders, such as maltodextrin, sucrose, and lactose, could be applied in controlled agglomeration to enhance powder porosity. Further investigation on the effect of emerging technologies on powder properties and their commercial feasibility is required to discover their potential in liquid drying. Moreover, utilizing clean‐label drying ingredients like dietary fibers, derived from agricultural waste, presents promising opportunities.
Multiple dimensions of phyllostomid bat biodiversity across ecosystems of the Orinoco Llanos
Authors: Farneda F. Z. , Otálora‐Ardila A. , Meyer C. F. J. , López‐Arévalo H. F. , Gómez‐Posada C. , Polanía J. 
Published: April 2024

AbstractUnderstanding the impacts of habitat conversion on species assemblages across multiple biodiversity dimensions (taxonomic, functional, and phylogenetic) and spatial scales is pivotal for implementing effective conservation strategies. Here, we surveyed phyllostomid bats using mist nets in riparian and unflooded forests, flooded savannahs, and conventional rice fields to investigate how changes in habitat quality affect multifaceted diversity from two Colombian farming systems in the Orinoco Llanos: traditional farmlands with high‐intensity agriculture (mainly rice production) and Civil Society Nature Reserves with greater ecosystem protection. We used a unified framework based on Hill numbers for quantifying bat taxonomic, functional, and phylogenetic diversity and modeled the relationship of these diversity facets with landscape variables (habitat cover and patch density) across three spatial scales (0.5, 1.5, 3 km) using Bayesian generalized linear mixed‐effect models. Our results indicate that increasing human activity toward rice monocultures representative of traditional farmlands negatively affected all diversity facets. In contrast, forested habitats associated mainly with riparian forests within private reserves contained higher taxonomic, functional, and phylogenetic diversity than savannahs and rice fields. However, the differences between riparian forests and rice crops were significant only for phylogenetic diversity, indicating loss of evolutionary history after habitat conversion. At the landscape scale, forest cover was a significant predictor for functional (0.5‐ and 3‐km scale) and phylogenetic diversity (0.5 km), and bats responded negatively at the 3‐km scale to rice patch density from a functional diversity perspective. Increasing habitat quality through preserving forest cover and patches should minimize the harmful effects of habitat conversion on multidimensional bat biodiversity. Furthermore, the conservation of riparian forests and the creation of more wildlife‐friendly farming, as practiced in the reserves, should be prioritized to ensure high levels of bat taxonomic, functional, and phylogenetic diversity across Orinoco countryside landscapes.
The enigmatic interplay of immune cells and abnormal spermatozoa through Mendelian randomization
Authors: Zheng Fuchun , Li Sheng , Wang Zhipeng , Xiong Situ , Liu Jiahao , Yang Lin , Yuan Yuyang , Zeng Jin , Liu Xiaoqiang , Xu Songhui , Chen Ru , Fu Bin 
Published: April 2024

AbstractPurposeAbnormal spermatozoa significantly impact reproductive health, affecting fertility rates, potentially prolonging conception time, and increasing the risk of miscarriages. This study employs Mendelian randomization to explore their potential link with immune cells, aiming to reveal their potential causal association and wider implications for reproductive health.MethodsWe conducted forward and reverse Mendelian randomization analyses to explore the potential causal connection between 731 immune cell signatures and abnormal spermatozoa. Using publicly available genetic data, we investigated various immune signatures such as median fluorescence intensities (MFI), relative cell (RC), absolute cell (AC), and morphological parameters (MP). Robustness was ensured through comprehensive sensitivity analyses assessing consistency, heterogeneity, and potential horizontal pleiotropy. The MR study produced a statistically significant p‐value of .0000684, Bonferroni‐corrected for the 731 exposures.ResultsThe Mendelian randomization analysis revealed strong indications of a reciprocal relationship between immune cell pathways and sperm integrity. When examining immune cell exposure, a potential causal link with abnormal sperm was observed in 35 different types of immune cells. Conversely, the reverse Mendelian randomization results indicated that abnormal sperm might causally affect 39 types of immune cells. These outcomes suggest a potential mutual influence between alterations in immune cell functionality and the quality of spermatozoa.ConclusionThis study highlights the close link between immune responses and sperm development, suggesting implications for reproductive health and immune therapies. Further research may offer crucial insights into male fertility and immune disorders.
Editorial: Sequencing rescue therapy for acute severe ulcerative colitis—Ready for revision?
Authors: Derikx L. A. A. P. , Hoentjen F. 
Published: April 2024

LINKED CONTENTThis article is linked to García et al papers. To view these articles, visithttps://doi.org/10.1111/apt.17938andhttps://doi.org/10.1111/apt.17993
Real‐Time Neural Materials using Block‐Compressed Features
Authors: Weinreich C. , De Oliveira L. , Houdard A. , Nader G. 
Published: April 2024

AbstractNeural materials typically consist of a collection of neural features along with a decoder network. The main challenge in integrating such models in real‐time rendering pipelines lies in the large size required to store their features in GPU memory and the complexity of evaluating the network efficiently. We present a neural material model whose features and decoder are specifically designed to be used in real‐time rendering pipelines. Our framework leverages hardware‐based block compression (BC) texture formats to store the learned features and trains the model to output the material information continuously in space and scale. To achieve this, we organize the features in a block‐based manner and emulate BC6 decompression during training, making it possible to export them as regular BC6 textures. This structure allows us to use high resolution features while maintaining a low memory footprint. Consequently, this enhances our model's overall capability, enabling the use of a lightweight and simple decoder architecture that can be evaluated directly in a shader. Furthermore, since the learned features can be decoded continuously, it allows for random uv sampling and smooth transition between scales without needing any subsequent filtering. As a result, our neural material has a small memory footprint, can be decoded extremely fast adding a minimal computational overhead to the rendering pipeline.
Surface‐aware Mesh Texture Synthesis with Pre‐trained 2D CNNs
Authors: Kovács Áron Samuel , Hermosilla Pedro , Raidou Renata G. 
Published: April 2024

AbstractMesh texture synthesis is a key component in the automatic generation of 3D content. Existing learning‐based methods have drawbacks—either by disregarding the shape manifold during texture generation or by requiring a large number of different views to mitigate occlusion‐related inconsistencies. In this paper, we present a novel surface‐aware approach for mesh texture synthesis that overcomes these drawbacks by leveraging the pre‐trained weights of 2D Convolutional Neural Networks (CNNs) with the same architecture, but with convolutions designed for 3D meshes. Our proposed network keeps track of the oriented patches surrounding each texel, enabling seamless texture synthesis and retaining local similarity to classical 2D convolutions with square kernels. Our approach allows us to synthesize textures that account for the geometric content of mesh surfaces, eliminating discontinuities and achieving comparable quality to 2D image synthesis algorithms. We compare our approach with state‐of‐the‐art methods where, through qualitative and quantitative evaluations, we demonstrate that our approach is more effective for a variety of meshes and styles, while also producing visually appealing and consistent textures on meshes.
Detection of multi‐class lung diseases based on customized neural network
Authors: Ali Azmat , Wang Yulin , Shi Xiaochuan 
Published: April 2024

AbstractIn the medical image processing domain, deep learning methodologies have outstanding performance for disease classification using digital images such as X‐rays, magnetic resonance imaging (MRI), and computerized tomography (CT). However, accurate diagnosis of disease by medical personnel can be challenging in certain cases, such as the complexity of interpretation and non‐availability of expert personnel, difficulty at pixel‐level analysis, etc. Computer‐aided diagnostic (CAD) systems with proper training have shown the potential to enhance diagnostic accuracy and efficiency. With the exponential growth of medical data, CAD systems can analyze and extract valuable information by assisting medical personnel during the disease diagnostic process. To overcome these challenges, this research introduces CX‐RaysNet, a novel deep‐learning framework designed for the automatic identification of various lung disease classes in digital chest X‐ray images. The core novelty of the CX‐RaysNet framework lies in the integration of both convolutional and group convolutional layers, along with the usage of small filter sizes and the incorporation of dropout regularization. This phenomenon helps us optimize the model's ability to distinguish minute features that reveal different lung diseases. Additionally, data augmentation techniques are implemented to augment the training and testing datasets, which enhances the model's robustness and generalizability. The performance evaluation of CX‐RaysNet reveals promising results, with the proposed model achieving a multi‐class classification accuracy of 97.25%. Particularly, this study represents the first attempt to optimize a model specifically for low‐power embedded devices, aiming to improve the accuracy of disease detection while minimizing computational resources.
Postmarket safety communications on drugs approved in Japan: A 25‐year analysis
Authors: Tanaka Yusuke , Tanaka Mototsugu , Miyazawa Haruna , Terashima Ryohei , Miyazawa Makoto , Ikuma Mutsuhiro , Tomita Yoshihiko 
Published: April 2024

AbstractDrug safety communications (DSCs) are essential tools for communicating important postmarket serious drug safety information to healthcare professionals and patients. Previous studies characterized DSCs issued by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA); however, knowledge about the activities of the Pharmaceuticals and Medical Devices Agency (PMDA)/the Ministry of Health, Labor and Welfare (MHLW) is limited. This study characterized DSCs by the PMDA/MHLW in comparison with previously reported DSCs by the FDA and the EMA. We retrospectively analyzed 37 DSCs of 41 adverse drug reactions (ADRs) for 33 drugs in Japan from 1997 to 2022. Most DSCs were related to non‐oncology drugs (30/37, 81.1%), and the median (interquartile range) time from approval to DSC issuance was 19 (10–51) months. Notably, the regulatory review reports and the latest labels before DSC issuance did not describe 16/28 (57.1%) and 12/37 (32.4%) of the ADRs related to DSCs, respectively. Most DSCs resulted in label revisions (36/37, 97.3%) and seven drugs were eventually withdrawn. Some DSC characteristics are similar among the PMDA/MHLW, the FDA, and the EMA; however, the number, contents, and range of new safety issues addressed by DSCs differ among the three jurisdictions. Our study emphasized the importance of continuous efforts to gather postmarket drug safety information because substantial ADRs that led to DSCs were recognized after approval and were associated with critical label revisions and withdrawals. Future studies are required to address global challenges for regulatory harmonization of safety‐related regulatory actions.
The relationship between attachment representations and minimal intergroup bias in preschool‐aged children
Authors: Misch Antonia , Kramer Andrea , Paulus Markus 
Published: April 2024

AbstractAttachment theory proposes that young children's experiences with their caregivers has a tremendous influence on how children navigate their social relationships. By the end of early childhood, intergroup contexts play an important role in their social life and children build strong ties to their ingroups. Although both domains relate to the same psychological processes—children's affective ties to others—surprisingly very little research has addressed how children's attachment relates to their intergroup attitudes and behavior. In this study, we investigate the link. For that purpose, 5‐year‐old children (n = 100) first underwent the German Attachment Story Completion Task (GEV‐B). Then we allocated children into minimal groups based on T‐Shirt color and assessed their intergroup attitudes and intergroup behavior. Results showed that while most children showed a strong and robust ingroup bias in their attitudes and behavior, children with an insecure‐ambivalent attachment representation treated in‐ and outgroup similarly. Overall, this study provides novel perspectives on the relationship between children's attachment representation and their interactions in the social world.Research Highlights
This study provides novel insights into the relationship between children's attachment security and the development of intergroup bias in a minimal group context
Children with secure, insecure‐avoidant and disorganized attachment representation showed a strong intergroup bias in explicit attitudes and behavior
Children with insecure‐ambivalent attachment representation displayed no intergroup bias
Insecure‐ambivalent attachment representations might be detrimental to the formation of ingroup attachment
Cross‐sectional, case‐control and longitudinal associations between exposure to glucagon‐like peptide‐1 receptor agonists and the dispensing of antidepressants
Authors: Almeida Osvaldo P. , Fong Zheng , Hill Almeida Lydia M. , Sanfilippo Frank M. , Page Amy , Etherton‐Beer Christopher 
Published: April 2024

AbstractAimTo determine if the dispensing of glucagon‐like peptide (GLP)‐1 receptor agonists is associated with increased dispensing of antidepressants.Materials and MethodsWe used cross‐sectional, case‐control and retrospective cohort study designs to examine the association between dispensed GLP‐1 receptor agonists and antidepressants between 2012 and 2022 in the 10% random sample of the Australian Pharmaceutical Benefits Scheme (PBS) data. PBS‐listed GLP‐1 receptor agonists, exenatide, dulaglutide and semaglutide were the exposures. Outcomes were the odds ratio [ORs; 99% confidence interval (CI)] and hazard ratio (99% CI) of being dispensed any antidepressant. Analyses were adjusted for demographic measures and the dispensing of medicines to manage cardiovascular diseases or anxiety/insomnia. Statistical tests were two‐sided at the 1% level of significance.ResultsIn total, 358 075 of 1 746 391 individuals were dispensed antidepressants, and 8495 of the 24 783 dispensed a GLP‐1 receptor agonist were also dispensed an antidepressant in 2022 (OR 1.44; 99% CI 1.38‐1.50); 24 103 of the 1 746 391 participants had been dispensed a GLP‐1 receptor agonist between 2012 and 2021, and of these 8083 were dispensed antidepressants in 2022 (OR 1.52; 99% CI 1.46‐1.59). The 2012 cohort included 1 213 316 individuals who had not been dispensed antidepressants that year. The hazard ratio of being dispensed an antidepressant between 2013 and 2022 following the dispensing of a GLP‐1 receptor agonist was 1.19 (99% CI 1.12‐1.27). Additional analyses restricting the time of exposure confirmed these associations for all PBS‐listed GLP‐1 receptor agonists.ConclusionsIndividuals exposed to GLP‐1 receptor agonists are at greater risk of being dispensed antidepressants. The possible impact of GLP‐1 receptor agonists on the mood of consumers requires ongoing vigilance and further research.
A supported education programme implemented in youth mental health services: Outcomes and lessons from the first year of COVID‐disrupted delivery
Authors: Nicholas Jennifer , Ardill‐Young Oliver , Levy Philippa , Pearce Katie , Chinnery Gina , Sim Esther , Scully Alana , Ottavio Antonia , Curtis Jackie , Killackey Eóin 
Published: April 2024

AbstractAimEducational attainment is consistently highly valued by young people with mental ill health, yet maintenance and completion of education is a challenge. This paper reports on the implementation of a supported education programme for youth mental health.MethodsBetween 10 October 2019 and 10 October 2020, a supported education programme was delivered within primary and tertiary youth mental health services. A description of the programme, context, and adjustments required due to COVID‐19 is presented, and the educational outcomes of young people referred to the programme were explored. Two case studies are also presented.ResultsThe programme received 71 referrals over this period, of which 70.4% had not yet completed secondary school and 68% were experiencing multiple mental health conditions. Overall outcomes were positive, with 47.5% of the 40 young people who chose to engage with the programme maintaining or re‐engaging with education. However, the remainder of those who engaged withdrew from the programme, often reporting challenges due to COVID‐19 such as social isolation or increased uncertainty. Additionally, a number of young people declined or disengaged from the programme to focus on employment.ConclusionThis report of the experience of integrating a supported employment programme in Australian youth mental health services reinforces the need for such support, and provides preliminary evidence for its successful implementation as part of routine care. The disengagement in response to COVID‐19 highlights the real‐world challenges of the pandemic, while young people's voicing of employment goals indicates the need for combined educational and vocational support—to assist transition and progression between these goals.
Relationship between brain white matter damage and grey matter atrophy in hereditary spastic paraplegia types 4 and 5
Authors: Tu Yuqing , Liu Ying , Fan Shuping , Weng Jiaqi , Li Mengcheng , Zhang Fan , Fu Ying , Hu Jianping 
Published: April 2024

AbstractBackground and purposeWhite matter (WM) damage is the main target of hereditary spastic paraplegia (HSP), but mounting evidence indicates that genotype‐specific grey matter (GM) damage is not uncommon. Our aim was to identify and compare brain GM and WM damage patterns in HSP subtypes and investigate how gene expression contributes to these patterns, and explore the relationship between GM and WM damage.MethodsIn this prospective single‐centre cohort study from 2019 to 2022, HSP patients and controls underwent magnetic resonance imaging evaluations. The alterations of GM and WM patterns were compared between groups by applying a source‐based morphometry approach. Spearman rank correlation was used to explore the associations between gene expression and GM atrophy patterns in HSP subtypes. Mediation analysis was conducted to investigate the interplay between GM and WM damage.ResultsTwenty‐one spastic paraplegia type 4 (SPG4) patients (mean age 50.7 years ± 12.0 SD, 15 men), 21 spastic paraplegia type 5 (SPG5) patients (mean age 29.1 years ± 12.8 SD, 14 men) and 42 controls (sex‐ and age‐matched) were evaluated. Compared to controls, SPG4 and SPG5 showed similar WM damage but different GM atrophy patterns. GM atrophy patterns in SPG4 and SPG5 were correlated with corresponding gene expression (ρ = 0.30, p = 0.008, ρ = 0.40, p < 0.001, respectively). Mediation analysis indicated that GM atrophy patterns were mediated by WM damage in HSP.ConclusionsGrey matter atrophy patterns were distinct between SPG4 and SPG5 and were not only secondary to WM damage but also associated with disease‐related gene expression.Clinical trial registration no. NCT04006418.
Soil recalcitrant but not labile organic nitrogen mineralization contributes to microbial nitrogen immobilization and plant nitrogen uptake
Authors: Chen Shending , Elrys Ahmed S. , Yang Wenyan , Du Siwen , He Mengqiu , Cai Zucong , Zhang Jinbo , Müller Christoph 
Published: April 2024

AbstractSoil organic nitrogen (N) mineralization not only supports ecosystem productivity but also weakens carbon and N accumulation in soils. Recalcitrant (mainly mineral‐associated organic matter) and labile (mainly particulate organic matter) organic materials differ dramatically in nature. Yet, the patterns and drivers of recalcitrant (MNrec) and labile (MNlab) organic N mineralization rates and their consequences on ecosystem N retention are still unclear. By collecting MNrec (299 observations) and MNlab (299 observations) from 57 15N tracing studies, we found that soil pH and total N were the master factors controlling MNrec and MNlab, respectively. This was consistent with the significantly higher rates of MNrec in alkaline soils and of MNlab in natural ecosystems. Interestingly, our analysis revealed that MNrec directly stimulated microbial N immobilization and plant N uptake, while MNlab stimulated the soil gross autotrophic nitrification which discouraged ammonium immobilization and accelerated nitrate production. We also noted that MNrec was more efficient at lower precipitation and higher temperatures due to increased soil pH. In contrast, MNlab was more efficient at higher precipitation and lower temperatures due to increased soil total N. Overall, we suggest that increasing MNrec may lead to a conservative N cycle, improving the ecosystem services and functions, while increasing MNlab may stimulate the potential risk of soil N loss.