bluuebunny/crossref_metadata_2025_split huggingface dataset:
Food fraud threats in UK post-harvest seafood supply chains; an assessment of current vulnerabilities
Authors: Lawrence Sophie , Elliott Christopher , Huisman Wim , Dean Moira , van Ruth Saskia 
Published: May 2024

AbstractSeafood fraud is commonly reported on food fraud databases and deceptive practices are highlighted by numerous studies, with impacts on the economy, health and marine conservation. Food fraud assessments are a widely accepted fraud mitigation and prevention activity undertaken to identify possible points of deception within a supply chain. This study aims to understand the food fraud vulnerability of post-harvest seafood supply chains in the UK and determine if there are differences according to commodity, supply chain node, business size and certification status. The SSAFE food fraud vulnerability assessment tool was used to assess 48 fraud factors relating to opportunities, motivations and controls. The analysis found seafood supply chains to have a medium vulnerability to food fraud, with the highest perceived vulnerability in technical opportunities. Certification status was a stronger determinant of vulnerability than any other factor, particularly in the level of controls, a factor that also indicated a higher perceived level of vulnerability in smaller companies and the food service industry. This paper also reviews historic food fraud trends in the sector to provide additional insights and the analysis indicates that certain areas of the supply chain, including uncertified prawn supply chains, salmon supply chains and food service companies, may be at higher risk of food fraud. This study conducts an in-depth examination of food fraud vulnerability relating to the UK and for seafood supply chains and contributes to a growing body of literature identifying areas of vulnerability and resilience to food related criminality within the global food system.
A geographically disaggregated approach to integrate low-carbon technologies across local electricity networks
Authors: Few Sheridan , Djapic Predrag , Strbac Goran , Nelson Jenny , Candelise Chiara 
Published: May 2024

AbstractMeeting climate targets requires widespread deployment of low-carbon technologies such as distributed photovoltaics, heat pumps and electric vehicles. Without mitigating actions, changing power flows associated with these technologies would adversely impact some local networks. The extent of these impacts, and the optimal means of avoiding them, remains unclear. Here we use local-level data and network simulation to estimate variation in future network upgrade costs in over 40,000 geographical regions comprising all of Great Britain. We find that costs vary substantially between localities, and are typically highest in urban areas, and areas with highest deployment of heat pumps and electric vehicles. We estimate reductions in required upgrades associated with local flexibility, which vary substantially between localities. We show that using geographically disaggregated data to inform flexibility deployment across the country could reduce network upgrade costs by hundreds of millions of pounds relative to an approach that treats localities as homogeneous.
Evolutionary–developmental (evo-devo) dynamics of hominin brain size
Authors: González-Forero Mauricio 
Published: May 2024

AbstractBrain size tripled in the human lineage over four million years, but why this occurred remains uncertain. Here, to study what caused this brain expansion, I mathematically model the evolutionary and developmental (evo-devo) dynamics of hominin brain size. The model recovers (1) the evolution of brain and body sizes of seven hominin species starting from brain and body sizes of the australopithecine scale, (2) the evolution of the hominin brain–body allometry and (3) major patterns of human development and evolution. I show that the brain expansion recovered is not caused by direct selection for brain size but by its genetic correlation with developmentally late preovulatory ovarian follicles. This correlation is generated over development if individuals experience a challenging ecology and seemingly cumulative culture, among other conditions. These findings show that the evolution of exceptionally adaptive traits may not be primarily caused by selection for them but by developmental constraints that divert selection.
Deep history of cultural and linguistic evolution among Central African hunter-gatherers
Authors: Padilla-Iglesias Cecilia , Blanco-Portillo Javier , Pricop Bogdan , Ioannidis Alexander G. , Bickel Balthasar , Manica Andrea , Vinicius Lucio , Migliano Andrea Bamberg 
Published: May 2024

AbstractHuman evolutionary history in Central Africa reflects a deep history of population connectivity. However, Central African hunter-gatherers (CAHGs) currently speak languages acquired from their neighbouring farmers. Hence it remains unclear which aspects of CAHG cultural diversity results from long-term evolution preceding agriculture and which reflect borrowing from farmers. On the basis of musical instruments, foraging tools, specialized vocabulary and genome-wide data from ten CAHG populations, we reveal evidence of large-scale cultural interconnectivity among CAHGs before and after the Bantu expansion. We also show that the distribution of hunter-gatherer musical instruments correlates with the oldest genomic segments in our sample predating farming. Music-related words are widely shared between western and eastern groups and likely precede the borrowing of Bantu languages. In contrast, subsistence tools are less frequently exchanged and may result from adaptation to local ecologies. We conclude that CAHG material culture and specialized lexicon reflect a long evolutionary history in Central Africa.
Human ventromedial prefrontal cortex is necessary for prosocial motivation
Authors: Lockwood Patricia L. , Cutler Jo , Drew Daniel , Abdurahman Ayat , Jeyaretna Deva Sanjeeva , Apps Matthew A. J. , Husain Masud , Manohar Sanjay G. 
Published: May 2024

AbstractVentromedial prefrontal cortex (vmPFC) is vital for decision-making. Functional neuroimaging links vmPFC to processing rewards and effort, while parallel work suggests vmPFC involvement in prosocial behaviour. However, the necessity of vmPFC for these functions is unknown. Patients with rare focal vmPFC lesions (n = 25), patients with lesions elsewhere (n = 15) and healthy controls (n = 40) chose between rest and exerting effort to earn rewards for themselves or another person. vmPFC damage decreased prosociality across behavioural and computational measures. vmPFC patients earned less, discounted rewards by effort more, and exerted less force when another person benefited, compared to both control groups. Voxel-based lesion mapping revealed dissociations between vmPFC subregions. While medial damage led to antisocial behaviour, lateral damage increased prosocial behaviour relative to patients with damage elsewhere. vmPFC patients also showed reduced effort sensitivity overall, but reward sensitivity was limited to specific subregions. These results reveal multiple causal contributions of vmPFC to prosocial behaviour, effort and reward.
Dissecting cell membrane tension dynamics and its effect on Piezo1-mediated cellular mechanosensitivity using force-controlled nanopipettes
Authors: Lüchtefeld Ines , Pivkin Igor V. , Gardini Lucia , Zare-Eelanjegh Elaheh , Gäbelein Christoph , Ihle Stephan J. , Reichmuth Andreas M. , Capitanio Marco , Martinac Boris , Zambelli Tomaso , Vassalli Massimo 
Published: May 2024

AbstractThe dynamics of cellular membrane tension and its role in mechanosensing, which is the ability of cells to respond to physical stimuli, remain incompletely understood, mainly due to the lack of appropriate tools. Here, we report a force-controlled nanopipette-based method that combines fluidic force microscopy with fluorescence imaging for precise manipulation of the cellular membrane tension while monitoring the impact on single-cell mechanosensitivity. The force-controlled nanopipette enables control of the indentation force imposed on the cell cortex as well as of the aspiration pressure applied to the plasma membrane. We show that this setup can be used to concurrently monitor the activation of Piezo1 mechanosensitive ion channels via calcium imaging. Moreover, the spatiotemporal behavior of the tension propagation is assessed with the fluorescent membrane tension probe Flipper-TR, and further dissected using molecular dynamics modeling. Finally, we demonstrate that aspiration and indentation act independently on the cellular mechanobiological machinery, that indentation induces a local pre-tension in the membrane, and that membrane tension stays confined by links to the cytoskeleton.
NG2 glia protect against prion neurotoxicity by inhibiting microglia-to-neuron prostaglandin E2 signaling
Authors: Liu Yingjun , Guo Jingjing , Matoga Maja , Korotkova Marina , Jakobsson Per-Johan , Aguzzi Adriano 
Published: May 2024

AbstractOligodendrocyte-lineage cells, including NG2 glia, undergo prominent changes in various neurodegenerative disorders. Here, we identify a neuroprotective role for NG2 glia against prion toxicity. NG2 glia were activated after prion infection in cerebellar organotypic cultured slices (COCS) and in brains of prion-inoculated mice. In both model systems, depletion of NG2 glia exacerbated prion-induced neurodegeneration and accelerated prion pathology. Loss of NG2 glia enhanced the biosynthesis of prostaglandin E2 (PGE2) by microglia, which augmented prion neurotoxicity through binding to the EP4 receptor. Pharmacological or genetic inhibition of PGE2 biosynthesis attenuated prion-induced neurodegeneration in COCS and mice, reduced the enhanced neurodegeneration in NG2-glia-depleted COCS after prion infection, and dampened the acceleration of prion disease in NG2-glia-depleted mice. These data unveil a non-cell-autonomous interaction between NG2 glia and microglia in prion disease and suggest that PGE2 signaling may represent an actionable target against prion diseases.
Multi-source remote sensing-based landslide investigation: the case of the August 7, 2020, Gokseong landslide in South Korea
Authors: Choi Shin-Kyu , Ramirez Ryan Angeles , Lim Hwan-Hui , Kwon Tae-Hyuk 
Published: May 2024

AbstractLandslides pose a growing concern worldwide, emphasizing the need for accurate prediction and assessment to mitigate their impact. Recent advancements in remote sensing technology offer unprecedented datasets at various scales, yet practical applications demand further case studies to fully integrate these technologies into landslide analysis. This study presents a case study approach to fully leverage variety of multi-source remote sensing technologies for analyzing the characteristics of a landslide. The selected case is a landslide with a long runout debris flow that occurred in Gokseong County, South Korea, on August 7, 2020. The chosen multi-source technologies encompass digital photogrammetry using RGB and multi-spectral imageries, 3D point clouds acquired by light detection and ranging (LiDAR) mounted on an unmanned aerial vehicle (UAV), and satellite interferometric synthetic aperture radar (InSAR). The satellite InSAR analysis identifies the initial displacement, triggered by rainfall and later transforming into a debris flow. The utilization of digital photogrammetry, employing UAV-RGB and multi-spectral image data, precisely delineates the extent affected by the landslide. The landslide encompassed a runout distance of 678 m, featuring an initiation zone characterized by an average slope of 35°. Notably, the eroded and deposited areas measured 2.55 × 104 m2 and 1.72 × 104 m2, respectively. The acquired UAV-LiDAR data further reveal the eroded and deposited landslide volumes approximately measuring 5.60 × 104 m3 and 1.58 × 104 m3, respectively. This study contributes a valuable dataset on a rainfall-induced landslide with a long runout debris flow, underscoring the effectiveness of multi-source remote sensing technology in monitoring and comprehending complex landslide events.
Metabolomic-derived endotypes of age-related macular degeneration (AMD): a step towards identification of disease subgroups
Authors: Mendez Kevin , Lains Ines , Kelly Rachel S. , Gil João , Silva Rufino , Miller John , Vavvas Demetrios G. , Kim Ivana , Miller Joan , Liang Liming , Lasky-Su Jessica A. , Husain Deeba 
Published: May 2024

AbstractAge-related macular degeneration (AMD) is a leading cause of blindness worldwide, with a complex pathophysiology and phenotypic diversity. Here, we apply Similarity Network Fusion (SNF) to cluster AMD patients into putative metabolomics-derived endotypes. Using a discovery cohort of 163 AMD patients from Boston, US, and a validation cohort of 214 patients from Coimbra, Portugal, we identified four distinct metabolomics-derived endotypes with varying retinal structural and functional characteristics, confirmed across both cohorts. Patients clustered into Endotype 1 exhibited a milder form of AMD and were characterized by low levels of amino acids in specific metabolic pathways. Meanwhile, patients clustered into both Endotype 3 and 4 were associated with more severe AMD and exhibited low levels of fatty acid metabolites and elevated levels of sphingomyelins and fatty acid metabolites, respectively. These preliminary findings indicate that metabolomics-derived endotyping may offer a refined strategy for categorizing AMD patients based on their specific pathophysiological underpinnings, rather than relying solely on traditional observational clinical indicators.
Coupling control technology of anchoring and unloading in deep intense-mining and large-deformation roadway: a case study
Authors: Wang En , Yin Shuaifeng , Kang Qingtao , Zhao Xubo , Lan Qiankun , Sheng Hongyuan , Liang Huiyang 
Published: May 2024

AbstractIn order to control the deformation of surrounding rock in deep high-stress and intense-mining roadways, taking a deep coal roadway with continuous deformation as an example, the characteristics of crustal stress, coal strength, and mining influence of roadway are obtained by underground tests. The combined failure mechanism of coal roadway surrounding-rock is revealed by differential stress of deep and shallow anchor cables. We propose that the improvement of surrounding rock control for coal roadway is adopting the coupling control technology of anchoring and unloading. The stress distribution and evolution laws of lateral surrounding rock of unloading holes are obtained by numerical simulation and theoretical calculation, and reasonable unloading-hole spacing of 4.0 m is comprehensively determined. A mechanical model of roadway roof beam under fixed support at both ends is constructed and the important role of anchor cable beam-truss in controlling the stability of coal roadway is obtained. The rationality of coupling control technology of anchoring and unloading and parameters has been verified by engineering test and mine pressure observation, providing technical references for surrounding rock control in deep intense-mining and large-deformation roadways.
Exploring the pathways of drug repurposing and Panax ginseng treatment mechanisms in chronic heart failure: a disease module analysis perspective
Authors: Xie Chengzhi , Zhang Ying , Zhu Baochen , Yang Lin , Ren Jianxun , Lang Na 
Published: May 2024

AbstractChronic Heart Failure (CHF) is a significant global public health issue, with high mortality and morbidity rates and associated costs. Disease modules, which are collections of disease-related genes, offer an effective approach to understanding diseases from a biological network perspective. We employed the multi-Steiner tree algorithm within the NeDRex platform to extract CHF disease modules, and subsequently utilized the Trustrank algorithm to rank potential drugs for repurposing. The constructed disease module was then used to investigate the mechanism by which Panax ginseng ameliorates CHF. The active constituents of Panax ginseng were identified through a comprehensive review of the TCMSP database and relevant literature. The Swiss target prediction database was utilized to determine the action targets of these components. These targets were then cross-referenced with the CHF disease module in the STRING database to establish protein–protein interaction (PPI) relationships. Potential action pathways were uncovered through Gene Ontology (GO) and KEGG pathway enrichment analyses on the DAVID platform. Molecular docking, the determination of the interaction of biological macromolecules with their ligands, and visualization were conducted using Autodock Vina, PLIP, and PyMOL, respectively. The findings suggest that drugs such as dasatinib and mitoxantrone, which have low docking scores with key disease proteins and are reported in the literature as effective against CHF, could be promising. Key components of Panax ginseng, including ginsenoside rh4 and ginsenoside rg5, may exert their effects by targeting key proteins such as AKT1, TNF, NFKB1, among others, thereby influencing the PI3K-Akt and calcium signaling pathways. In conclusion, drugs like dasatinib and midostaurin may be suitable for CHF treatment, and Panax ginseng could potentially mitigate the progression of CHF through a multi-component-multi-target-multi-pathway approach. Disease module analysis emerges as an effective strategy for exploring drug repurposing and the mechanisms of traditional Chinese medicine in disease treatment.
HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer
Authors: Kapil Ansh , Spitzmüller Andreas , Brieu Nicolas , Haneder Susanne , Shumilov Anatoliy , Meier Armin , Cecchi Fabiola , Barkell Alice , Harder Nathalie , Mittermaier Katrin , Hidalgo-Sastre Ana , Alleze Regina , Schick Markus , Schmidt Günter , Sade Hadassah , Tsuchihashi Zenta , Suto Fumitaka , Gustavson Mark , Barrett J. Carl , Carroll Danielle 
Published: May 2024

AbstractMany targeted cancer therapies rely on biomarkers assessed by scoring of immunohistochemically (IHC)-stained tissue, which is subjective, semiquantitative, and does not account for expression heterogeneity. We describe an image analysis-based method for quantitative continuous scoring (QCS) of digital whole-slide images acquired from baseline human epidermal growth factor receptor 2 (HER2) IHC-stained breast cancer tissue. Candidate signatures for patient stratification using QCS of HER2 expression on subcellular compartments were identified, addressing the spatial distribution of tumor cells and tumor-infiltrating lymphocytes. Using data from trastuzumab deruxtecan-treated patients with HER2-positive and HER2-negative breast cancer from a phase 1 study (NCT02564900; DS8201-A-J101; N = 151), QCS-based patient stratification showed longer progression-free survival (14.8 vs 8.6 months) with higher prevalence of patient selection (76.4 vs 56.9%) and a better cross-validated log-rank p value (0.026 vs 0.26) than manual scoring based on the American Society of Clinical Oncology / College of American Pathologists guidelines. QCS-based features enriched the HER2-negative subgroup by correctly predicting 20 of 26 responders.
A novel combinatorial approach using sulforaphane- and withaferin A-rich extracts for prevention of estrogen receptor-negative breast cancer through epigenetic and gut microbial mechanisms
Authors: Rahman Mohammad Mijanur , Wu Huixin , Tollefsbol Trygve O. 
Published: May 2024

AbstractEstrogen receptor-negative [ER(−)] mammary cancer is the most aggressive type of breast cancer (BC) with higher rate of metastasis and recurrence. In recent years, dietary prevention of BC with epigenetically active phytochemicals has received increased attention due to its feasibility, effectiveness, and ease of implementation. In this regard, combinatorial phytochemical intervention enables more efficacious BC inhibition by simultaneously targeting multiple tumorigenic pathways. We, therefore, focused on investigation of the effect of sulforaphane (SFN)-rich broccoli sprouts (BSp) and withaferin A (WA)-rich Ashwagandha (Ash) combination on BC prevention in estrogen receptor-negative [ER(−)] mammary cancer using transgenic mice. Our results indicated that combinatorial BSp + Ash treatment significantly reduced tumor incidence and tumor growth (~ 75%) as well as delayed (~ 21%) tumor latency when compared to the control treatment and combinatorial BSp + Ash treatment was statistically more effective in suppressing BC compared to single BSp or Ash intervention. At the molecular level, the BSp and Ash combination upregulated tumor suppressors (p53, p57) along with apoptosis associated proteins (BAX, PUMA) and BAX:BCL-2 ratio. Furthermore, our result indicated an expressional decline of epigenetic machinery HDAC1 and DNMT3A in mammary tumor tissue because of combinatorial treatment. Interestingly, we have reported multiple synergistic interactions between BSp and Ash that have impacted both tumor phenotype and molecular expression due to combinatorial BSp and Ash treatment. Our RNA-seq analysis results also demonstrated a transcriptome-wide expressional reshuffling of genes associated with multiple cell-signaling pathways, transcription factor activity and epigenetic regulations due to combined BSp and Ash administration. In addition, we discovered an alteration of gut microbial composition change because of combinatorial treatment. Overall, combinatorial BSp and Ash supplementation can prevent ER(−) BC through enhanced tumor suppression, apoptosis induction and transcriptome-wide reshuffling of gene expression possibly influencing multiple cell signaling pathways, epigenetic regulation and reshaping gut microbiota.
Predicting the stereoselectivity of chemical reactions by composite machine learning method
Authors: Chung Jihoon , Li Justin , Saimon Amirul Islam , Hong Pengyu , Kong Zhenyu 
Published: May 2024

AbstractStereoselective reactions have played a vital role in the emergence of life, evolution, human biology, and medicine. However, for a long time, most industrial and academic efforts followed a trial-and-error approach for asymmetric synthesis in stereoselective reactions. In addition, most previous studies have been qualitatively focused on the influence of steric and electronic effects on stereoselective reactions. Therefore, quantitatively understanding the stereoselectivity of a given chemical reaction is extremely difficult. As proof of principle, this paper develops a novel composite machine learning method for quantitatively predicting the enantioselectivity representing the degree to which one enantiomer is preferentially produced from the reactions. Specifically, machine learning methods that are widely used in data analytics, including Random Forest, Support Vector Regression, and LASSO, are utilized. In addition, the Bayesian optimization and permutation importance tests are provided for an in-depth understanding of reactions and accurate prediction. Finally, the proposed composite method approximates the key features of the available reactions by using Gaussian mixture models, which provide suitable machine learning methods for new reactions. The case studies using the real stereoselective reactions show that the proposed method is effective and provides a solid foundation for further application to other chemical reactions.