bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial single-cell mass spectrometry defines zonation of the hepatocyte proteome
Authors: Rosenberger Florian A. , Thielert Marvin , Strauss Maximilian T. , Schweizer Lisa , Ammar Constantin , Mädler Sophia C. , Metousis Andreas , Skowronek Patricia , Wahle Maria , Madden Katherine , Gote-Schniering Janine , Semenova Anna , Schiller Herbert B. , Rodriguez Edwin , Nordmann Thierry M. , Mund Andreas , Mann Matthias 
Published: October 2023

AbstractSingle-cell proteomics by mass spectrometry is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed mass spectrometry. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a cell slice. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics and spatial omics technologies.
The role of corporate social responsibility and government incentives in installing industrial wastewater treatment plants: SEM-ANN deep learning approach
Authors: Mustafa Sohaib , Long Ying , Rana Sehrish 
Published: October 2023

AbstractContaminated industrial wastewater is one of the severe causes of health diseases. The wastewater treatment trend in developing countries is less, and governments are not strictly pursuing the wastewater management protocols adopted by firms. To study the intention to install wastewater treatment plants at the firm level and provide policy suggestions to the developing countries’ governments, we have collected a cross-sectional dataset from manufacturing firms. We have presented an integrated model based on the theory of planned behaviour and tested our proposed model by implying SEM-ANN deep learning techniques. Results revealed that Environmental knowledge, installation cost, firm reputation, and corporate social responsibility positively influence firm management’s intention to install wastewater treatment plants, but awareness of the risk associated with contaminated wastewater has a negative influence. On the other hand, Government incentives do not influence the process. In addition, our study has found that firm size moderates the relationship between explained and exploratory variables. Our study provided valuable insight into the available literature and provided some policy suggestions to developing countries' governments to cope with water scarcity and health issues caused by contaminated industrial wastewater.
A deep learning model to triage and predict adenocarcinoma on pancreas cytology whole slide imaging
Authors: Sohn Andrew , Miller Daniel , Ribeiro Efrain , Shankar Nakul , Ali Syed , Hruban Ralph , Baras Alexander 
Published: October 2023

AbstractPancreatic fine-needle aspirations are the gold-standard diagnostic procedure for the evaluation of pancreatic ductal adenocarcinoma. A suspicion for malignancy can escalate towards chemotherapy followed by a major surgery and therefore is a high-stakes task for the pathologist. In this paper, we propose a deep learning framework, MIPCL, that can serve as a helpful screening tool, predicting the presence or absence of cancer. We also reproduce two deep learning models that have found success in surgical pathology for our cytopathology study. Our MIPCL significantly improves over both models across all evaluated metrics (F1-Score: 87.97% vs 88.70% vs 91.07%; AUROC: 0.9159 vs. 0.9051 vs 0.9435). Additionally, our model is able to recover the most contributing regions on the slide for the final prediction. We also present a dataset curation strategy that increases the number of training examples from an existing dataset, thereby reducing the resource burden tied to collecting and scanning additional cases.
Preparation, characterization, and life cycle assessment of banana rachis-recycled high-density polyethylene composites
Authors: Cabrera Demis , Baykara Haci , Riofrio Ariel , Cornejo Mauricio , Cáceres Julio 
Published: October 2023

AbstractAgro-industrial wastes are sustainable resources that have advantages as a reinforcement for polymeric matrices. This study examined the use of banana rachis fiber (BRF) in reinforcing the recycled high-density polyethylene (rHDPE) matrix. For this purpose, polymer composites with 5–20 wt% of BRF were prepared by the extrusion process using a twin-screw extruder and followed a hot press method. The structure of rHDPE/BRF composites and their characteristic peaks of degradation were successfully identified by the Fourier-transformed infrared spectroscopy and thermogravimetric analysis techniques, respectively, revealing a good dispersion of BRF in rHDPE. Differential scanning calorimetry results of the composites demonstrated that melt enthalpy decreases as the amount of BRF increases. XRD diffractograms revealed a crystallinity reduction of rHDPE due to the increase of fiber within the polymer matrix, which is reflected in the characteristic peaks' intensity decrease of HDPE. Variation in thermal and chemical properties with the addition of BRF in rHDPE was successfully evaluated in this study. Life cycle assessment for 1 kg composite production has also been evaluated. The banana rachis-rHDPE composite materials reduce the overall environmental impacts when the filler concentration increases.
Early-melting snowpatch plant communities are transitioning into novel states
Authors: Morgan John , Walker Zac 
Published: October 2023

AbstractSnowpatch plant community distribution and composition are strongly tied to the duration of long-lasting snow cover in alpine areas; they are vulnerable to global climatic changes that result in warmer temperatures and longer growing seasons. We used a revisitation study to quantify early-melting snowpatch floristic and functional diversity change in southern Australia, and document shrub size-class distributions over time to detect evidence for their encroachment into snowpatches, a key prediction with climatic change. Early-melting snowpatch vegetation has declined in areal extent, changed in species composition, and shrub and tussock grass cover has increased, but changes in functional trait diversity were less clear. Species gains, particularly by non-clonal species, accounted for most of the floristic change observed. Shrub recruitment was ongoing by most shrub species. Biotic differentiation is occurring; many early-melting snowpatches are transitioning to a novel state with changed composition and taller vegetation structure, but there is little evidence for species loss having occurred. Given enough time, however, the long-term loss of species is likely (i.e. biotic homogenisation) if taller shrubs outcompete short-statured snowpatch species. Our results provide evidence that this alpine ecosystem is forming a novel community with an uncertain future.
Preliminary in-silico analysis of vascular graft implantation configuration and surface modification
Authors: Prather Ray , Pourmoghadam Yashar , Fadhli Joseph , Al-Mousily Faris , Pourmoghadam Kamal 
Published: October 2023

AbstractVascular grafts are used to reconstruct congenital cardiac anomalies, redirect flow, and offer vascular access. Donor tissue, synthetic, or more recently tissue-engineered vascular grafts each carry limitations spanning compatibility, availability, durability and cost. Synthetic and tissue-engineered grafts offer the advantage of design optimization using in-silico or in-vitro modeling techniques. We focus on an in-silico parametric study to evaluate implantation configuration alternatives and surface finishing impact of a novel silicon-lined vascular graft. The model consists of a synthetic 3D-generic model of a graft connecting the internal carotid artery to the jugular vein. The flow is assumed unsteady, incompressible, and blood is modeled as a non-Newtonian fluid. A comparison of detached eddy turbulence and laminar modeling to determine the required accuracy needed found mild differences mainly dictated by the roughness level. The conduit walls are modeled as non-compliant and fixed. The shunt configurations considered, are straight and curved with varied surface roughness. Following a grid convergence study, two shunt configurations are analyzed to better understand flow distribution, peak shear locations, stagnation regions and eddy formation. The curved shunt was found to have lower peak and mean wall-shear stress, while resulting in lower flow power system and decreased power loss across the graft. The curved smooth surface shunt shows lower peak and mean wall-shear stress and lower power loss when compared to the straight shunt.
A coordinate-based meta-analysis of human amygdala connectivity alterations related to early life adversities
Authors: Kraaijenvanger Eline J. , Banaschewski Tobias , Eickhoff Simon B. , Holz Nathalie E. 
Published: October 2023

AbstractBy affecting core neurobiological systems early in development, early life adversities (ELAs) might confer latent vulnerability to future psychopathologies. This coordinate-based meta-analysis aims to identify significant convergent alterations in functional connectivity of the amygdala related to ELAs across resting-state and task-based fMRI-studies. Five electronic databases were systematically searched until 22 October 2020, retrieving 49 eligible studies (n = 3162 participants). Convergent alterations in functional connectivity related to ELAs between the amygdala and the anterior cingulate cortex (ACC) and left hippocampus were found. Sub-analyses based on hemisphere and direction showed that connectivity seeded in the right amygdala was affected and, moreover, revealed that connectivity with ACC was decreased. Analyses based on paradigm and age showed that amygdala-ACC coupling was altered during resting state and that amygdala–left hippocampus connectivity was mostly affected during task-based paradigms and in adult participants. While both regions showed altered connectivity during emotion processing and following adverse social postnatal experiences such as maltreatment, amygdala-ACC coupling was mainly affected when ELAs were retrospectively assessed through self-report. We show that ELAs are associated with altered functional connectivity of the amygdala with the ACC and hippocampus. As such, ELAs may embed latent vulnerability to future psychopathologies by systematically affecting important neurocognitive systems.
Novel computational and drug design strategies for inhibition of human papillomavirus-associated cervical cancer and DNA polymerase theta receptor by Apigenin derivatives
Authors: Akash Shopnil , Bayıl Imren , Hossain Md. Saddam , Islam Md. Rezaul , Hosen Md. Eram , Mekonnen Amare Bitew , Nafidi Hiba-Allah , Bin Jardan Yousef A. , Bourhia Mohammed , Bin Emran Talha 
Published: October 2023

AbstractThe present study deals with the advanced in-silico analyses of several Apigenin derivatives to explore human papillomavirus-associated cervical cancer and DNA polymerase theta inhibitor properties by molecular docking, molecular dynamics, QSAR, drug-likeness, PCA, a dynamic cross-correlation matrix and quantum calculation properties. The initial literature study revealed the potent antimicrobial and anticancer properties of Apigenin, prompting the selection of its potential derivatives to investigate their abilities as inhibitors of human papillomavirus-associated cervical cancer and DNA polymerase theta. In silico molecular docking was employed to streamline the findings, revealing promising energy-binding interactions between all Apigenin derivatives and the targeted proteins. Notably, Apigenin 4′-O-Rhamnoside and Apigenin-4′-Alpha-l-Rhamnoside demonstrated higher potency against the HPV45 oncoprotein E7 (PDB ID 2EWL), while Apigenin and Apigenin 5-O-Beta-d-Glucopyranoside exhibited significant binding energy against the L1 protein in humans. Similarly, a binding affinity range of − 7.5 kcal/mol to − 8.8 kcal/mol was achieved against DNA polymerase theta, indicating the potential of Apigenin derivatives to inhibit this enzyme (PDB ID 8E23). This finding was further validated through molecular dynamic simulation for 100 ns, analyzing parameters such as RMSD, RMSF, SASA, H-bond, and RoG profiles. The results demonstrated the stability of the selected compounds during the simulation. After passing the stability testing, the compounds underwent screening for ADMET, pharmacokinetics, and drug-likeness properties, fulfilling all the necessary criteria. QSAR, PCA, dynamic cross-correlation matrix, and quantum calculations were conducted, yielding satisfactory outcomes. Since this study utilized in silico computational approaches and obtained outstanding results, further validation is crucial. Therefore, additional wet-lab experiments should be conducted under in vivo and in vitro conditions to confirm the findings.
Evidence for an emotional adaptive function of dreams: a cross-cultural study
Authors: Samson David R. , Clerget Alice , Abbas Noor , Senese Jeffrey , Sarma Mallika S. , Lew-Levy Sheina , Mabulla Ibrahim A. , Mabulla Audax Z. P. , Miegakanda Valchy , Borghese Francesca , Henckaerts Pauline , Schwartz Sophie , Sterpenich Virginie , Gettler Lee T. , Boyette Adam , Crittenden Alyssa N. , Perogamvros Lampros 
Published: October 2023

AbstractThe function of dreams is a longstanding scientific research question. Simulation theories of dream function, which are based on the premise that dreams represent evolutionary past selective pressures and fitness improvement through modified states of consciousness, have yet to be tested in cross-cultural populations that include small-scale forager societies. Here, we analyze dream content with cross-cultural comparisons between the BaYaka (Rep. of Congo) and Hadza (Tanzania) foraging groups and Global North populations, to test the hypothesis that dreams in forager groups serve a more effective emotion regulation function due to their strong social norms and high interpersonal support. Using a linear mixed effects model we analyzed 896 dreams from 234 individuals across these populations, recorded using dream diaries. Dream texts were processed into four psychosocial constructs using the Linguistic Inquiry and Word Count (LIWC-22) dictionary. The BaYaka displayed greater community-oriented dream content. Both the BaYaka and Hadza exhibited heightened threat dream content, while, at the same time, the Hadza demonstrated low negative emotions in their dreams. The Global North Nightmare Disorder group had increased negative emotion content, and the Canadian student sample during the COVID-19 pandemic displayed the highest anxiety dream content. In conclusion, this study supports the notion that dreams in non-clinical populations can effectively regulate emotions by linking potential threats with non-fearful contexts, reducing anxiety and negative emotions through emotional release or catharsis. Overall, this work contributes to our understanding of the evolutionary significance of this altered state of consciousness.
High-intensity interval training attenuates development of autoimmune encephalomyelitis solely by systemic immunomodulation
Authors: Goldberg Yehuda , Segal Shir , Hamdi Liel , Nabat Hanan , Fainstein Nina , Mediouni Efrat , Asis Yarden , Theotokis Paschalis , Salamotas Ilias , Grigoriadis Nikolaos , Katz Abram , Ben-Hur Tamir , Einstein Ofira 
Published: October 2023

AbstractThe impact of high-intensity interval training (HIIT) on the central nervous system (CNS) in autoimmune neuroinflammation is not known. The aim of this study was to determine the direct effects of HIIT on the CNS and development of experimental autoimmune encephalomyelitis (EAE). Healthy mice were subjected to HIIT by treadmill running and the proteolipid protein (PLP) transfer EAE model was utilized. To examine neuroprotection, PLP-reactive lymph-node cells (LNCs) were transferred to HIIT and sedentary (SED) mice. To examine immunomodulation, PLP-reactive LNCs from HIIT and SED donor mice were transferred to naïve recipients and analyzed in vitro. HIIT in recipient mice did not affect the development of EAE following exposure to PLP-reactive LNCs. HIIT mice exhibited enhanced migration of systemic autoimmune cells into the CNS and increased demyelination. In contrast, EAE severity in recipient mice injected with PLP-reactive LNCs from HIIT donor mice was significantly diminished. The latter positive effect was associated with decreased migration of autoimmune cells into the CNS and inhibition of very late antigen (VLA)-4 expression in LNCs. Thus, the beneficial effect of HIIT on EAE development is attributed solely to systemic immunomodulatory effects, likely because of systemic inhibition of autoreactive cell migration and reduced VLA-4 integrin expression.
Using wasps as a tool to restore a functioning vine grape mycobiota and preserve the mycobial “terroir”
Authors: Di Paola Monica , Gori Agnese , Stefanini Irene , Meriggi Niccolò , Renzi Sonia , Nenciarini Stefano , Cerasuolo Benedetta , Moriondo Marco , Romoli Riccardo , Pieraccini Giuseppe , Baracchi David , Turillazzi Francesco , Turillazzi Stefano , Cavalieri Duccio 
Published: October 2023

AbstractIn the last one-hundred years, the exponential expansion of wine making has artificialized the agricultural landscape as well as its microbial diversity, spreading human selected Saccharomyces cerevisiae strains. Evidence showed that social wasps can harbor a significant fraction of the yeast phenotypic diversity of a given area of wine production, allowing different strains to overwinter and mate in their gut. The integrity of the wasp-yeast ecological interaction is of paramount importance to maintain the resilience of microbial populations associated to wine aromatic profiles. In a field experiment, we verified whether Polistes dominula wasps, reared in laboratory and fed with a traceable S. cerevisiae strain, could be a useful tool to drive the controlled yeast dispersion directly on grapes. The demonstration of the biotechnological potential of social insects in organic wine farming lays the foundations for multiple applications including maintenance of microbial biodiversity and rewilding vineyards through the introduction of wasp associated microbiomes.
Integrating operant behavior and fiber photometry with the open-source python library Pyfiber
Authors: Conlisk Dana , Ceau Matias , Fiancette Jean-François , Winke Nanci , Darmagnac Elise , Herry Cyril , Deroche-Gamonet Véronique 
Published: October 2023

AbstractDespite the popularity of fiber photometry (FP), its integration with operant behavior paradigms is progressing slowly. This can be attributed to the complex protocols in operant behavior – resulting in a combination of diverse non-predictable behavioral responses and scheduled events, thereby complicating data analysis. To overcome this, we developed Pyfiber, an open-source python library which facilitates the merge of FP with operant behavior by relating changes in fluorescent signals within a neuronal population to behavioral responses and events. Pyfiber helps to 1. Extract events and responses that occur in operant behavior, 2. Extract and process the FP signals, 3. Select events of interest and align them to the corresponding FP signals, 4. Apply appropriate signal normalization and analysis according to the type of events, 5. Run analysis on multiple individuals and sessions, 6. Collect results in an easily readable format. Pyfiber is suitable for use with many different fluorescent sensors and operant behavior protocols. It was developed using Doric lenses FP systems and Imetronic behavioral systems, but it possesses the capability to process data from alternative systems. This work sets a solid foundation for analyzing the relationship between different dimensions of complex behavioral paradigms with fluorescent signals from brain regions of interest.
Time-series analysis of transcriptomic changes due to permethrin exposure reveals that Aedes aegypti undergoes detoxification metabolism over 24 h
Authors: Mack Lindsey K. , Attardo Geoffrey M. 
Published: October 2023

AbstractInsecticide resistance is a multifaceted response and an issue across taxa. Aedes aegypti, the mosquito that vectors Zika, dengue, chikungunya, and yellow fever, demonstrates high levels of pyrethroid resistance across the globe, presenting a challenge to public health officials. To examine the transcriptomic shifts across time after exposure to permethrin, a 3’Tag-Seq analysis was employed on samples 6, 10, and 24 h after exposure along with controls. Differential expression analysis revealed significant shifts in detoxifying enzymes and various energy-producing metabolic processes. These findings indicate significant alterations in gene expression associated with key energy mobilization pathways within the system. These changes encompass a coordinated response involving lipolysis, beta-oxidation, and the citric acid cycle, required for the production of energetic molecules such as ATP, NADH, NADPH, and FADH. These findings highlight a complex interplay of metabolic processes that may have broader implications for understanding insect physiology and response to environmental stimuli. Among the upregulated detoxifying enzymes are cytochrome P450s, glutathione s-transferases and peroxidases, and ATP-binding cassette transporters. Additionally, eight heat shock genes or genes with heat shock domains exhibit the highest fold change across time. Twenty-four hours after exposure, samples indicate a global downregulation of these processes, though principal component analysis suggests lasting signatures of the response. Understanding the recovery response to insecticide exposure provides information on possible new genetic and synergist targets to explore.
An ultra-fast method for designing holographic phase shifting surfaces
Authors: Biswas Akash , Zekios Constantinos L. , Georgakopoulos Stavros V. 
Published: October 2023

AbstractHolographic phase-shifting surfaces (PSSs) have been proven to offer a cost-effective solution for enabling passive arrays to mechanically steer their beams toward desired directions. However, even though the principle of operation of PSSs is straightforward, designing a PSS is very challenging, because it involves an extremely high computational time, which in turn limits their usage and development. Notably, traditional design approaches of PSSs, withNnumber of layers that haveMdifferent variations of conductive patches, need$$M^N$$MNfull-wave simulations to be properly characterized. To address these challenges that are associated with the design of PSSs and reduce the needed computational effort, we present here a semi-numerical approach that enables the efficient design of holographic PSSs. Specifically, by representing anN-layer PSS unit-cell asNcascaded networks, where each network represents one layer of the PSS that hasMdifferent designs of sub-wavelength resonators, we only need to conduct$$N \times M$$N×Mfull-wave simulations to collect all the required data needed to analyze the performance of the PSS. In turn, by utilizing the multiplication property of ABCD parameters we can evaluate very efficiently all the$$M^N$$MNdifferent combinations that characterize our PSS. To validate the accuracy of our design methodology, a 1-D beam steerable antenna system is designed that is comprised of a circularly polarized holographic metasurface antenna (HMA) and a hybrid PSS, both operating at 30 GHz. Comparisons between our semi-numerical results, full-wave simulations, and measurements demonstrate an angular error of less than$$0.7^{\circ }$$0.7∘.