bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distinct dynamics of mRNA LNPs in mice and nonhuman primates revealed by in vivo imaging
Authors: Lemdani Katia , Marlin Romain , Mayet Céline , Perkov Vladimir , Pascal Quentin , Ripoll Manon , Relouzat Francis , Dhooge Nina , Bossevot Laetitia , Dereuddre-Bosquet Nathalie , Dargazanli Gihad , Thibaut-Duprey Kevin , Haensler Jean , Chapon Catherine , Prost Christine , Le Grand Roger 
Published: June 2024

AbstractThe characterization of vaccine distribution to relevant tissues after in vivo administration is critical to understanding their mechanisms of action. Vaccines based on mRNA lipid nanoparticles (LNPs) are now being widely considered against infectious diseases and cancer. Here, we used in vivo imaging approaches to compare the trafficking of two LNP formulations encapsulating mRNA following intramuscular administration: DLin-MC3-DMA (MC3) and the recently developed DOG-IM4. The mRNA formulated in DOG-IM4 LNPs persisted at the injection site, whereas mRNA formulated in MC3 LNPs rapidly migrated to the draining lymph nodes. Furthermore, MC3 LNPs induced the fastest increase in blood neutrophil counts after injection and greater inflammation, as shown by IL-1RA, IL-15, CCL-1, and IL-6 concentrations in nonhuman primate sera. These observations highlight the influence of the nature of the LNP on mRNA vaccine distribution and early immune responses.
Rationally seeded computational protein design of ɑ-helical barrels
Authors: Albanese Katherine I. , Petrenas Rokas , Pirro Fabio , Naudin Elise A. , Borucu Ufuk , Dawson William M. , Scott D. Arne , Leggett Graham. J. , Weiner Orion D. , Oliver Thomas A. A. , Woolfson Derek N. 
Published: June 2024

AbstractComputational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix–turn–helix–turn–helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression in Escherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.
Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics
Authors: Waman Vaishali P. , Ashford Paul , Lam Su Datt , Sen Neeladri , Abbasian Mahnaz , Woodridge Laurel , Goldtzvik Yonathan , Bordin Nicola , Wu Jiaxin , Sillitoe Ian , Orengo Christine A. 
Published: June 2024

AbstractThe COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein–protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.
In vivo brain estrogen receptor density by neuroendocrine aging and relationships with cognition and symptomatology
Authors: Mosconi Lisa , Nerattini Matilde , Matthews Dawn C. , Jett Steven , Andy Caroline , Williams Schantel , Yepez Camila Boneu , Zarate Camila , Carlton Caroline , Fauci Francesca , Ajila Trisha , Pahlajani Silky , Andrews Randolph , Pupi Alberto , Ballon Douglas , Kelly James , Osborne Joseph R. , Nehmeh Sadek , Fink Matthew , Berti Valentina , Dyke Jonathan P. , Brinton Roberta Diaz 
Published: June 2024

Abstract17β-estradiol, the most biologically active estrogen, exerts wide-ranging effects in brain through its action on estrogen receptors (ERs), influencing higher-order cognitive function and neurobiological aging. However, our knowledge of ER expression and regulation by neuroendocrine aging in the living human brain is limited. This in vivo brain 18F-fluoroestradiol (18F-FES) Positron Emission Tomography (PET) study of healthy midlife women reveals progressively higher ER density over the menopause transition in estrogen-regulated networks. Effects were independent of age, plasma estradiol and sex hormone binding globulin, and were highly consistent, correctly classifying all women as being postmenopausal or premenopausal. Higher ER density in target regions was associated with poorer memory performance for both postmenopausal and perimenopausal groups, and predicted presence of self-reported mood and cognitive symptoms after menopause. These findings provide novel insights on brain ER density modulation by female neuroendocrine aging, with clinical implications for women’s health.
Enhancing structural diversity through chemical engineering of Ambrosia tenuifolia extract for novel anti-glioblastoma compounds
Authors: Adessi Tonino G. , Wagner Paula M. , Bisogno Fabricio R. , Nicotra Viviana E. , Guido Mario E. , García Manuela E. 
Published: June 2024

AbstractNatural products are an unsurpassed source of leading structures in drug discovery. The biosynthetic machinery of the producing organism offers an important source for modifying complex natural products, leading to analogs that are unattainable by chemical semisynthesis or total synthesis. In this report, through the combination of natural products chemistry and diversity-oriented synthesis, a diversity-enhanced extracts approach is proposed using chemical reactions that remodel molecular scaffolds directly on extracts of natural resources. This method was applied to subextract enriched in sesquiterpene lactones from Ambrosia tenuifolia (Fam. Asteraceae) using acid media conditions (p-toluenesulfonic acid) to change molecular skeletons. The chemically modified extract was then fractionated by a bioguided approach to obtain the pure compounds responsible for the anti-glioblastoma (GBM) activity in T98G cell cultures. Indeed, with the best candidate, chronobiological experiments were performed to evaluate temporal susceptibility to the treatment on GBM cell cultures to define the best time to apply the therapy. Finally, bioinformatics tools were used to supply qualitative and quantitative information on the physicochemical properties, chemical space, and structural similarity of the compound library obtained. As a result, natural products derivatives containing new molecular skeletons were obtained, with possible applications as chemotherapeutic agents against human GBM T98G cell cultures.
Foraging dives of southern right whales (Eubalaena australis) in relation to larger zooplankton size prey availability in Golfo Nuevo, Península Valdés, Argentina
Authors: D’Agostino Valeria C. , Nocera Ariadna C. , Abernathy Kyler , Wilson Alex Muñoz , Coscarella Mariano A. , Degrati Mariana 
Published: June 2024

AbstractSouthern right whales (SRWs, Eubalaena australis) have been observed feeding both at and below the surface (< 10 m) in Golfo Nuevo (42°42′ S, 64°30′ W), Península Valdés, Argentina, an area traditionally recognized as calving ground. In addition, we documented diving feeding behavior in SRWs during their stay in this gulf, which has not been previously described. We assessed this behavior using suction-cup-attached video-imaging tags (CRITTERCAMs) on individual whales. A total of eight CRITTERCAM deployments were successful, and feeding events were documented in all SRWs successfully equipped with CRITTERCAMs. The highest speeds occurred during the ascent phase, and the average diving time was 6 min 45 s ± 3 min 41 s for SRWs. Concurrently, zooplankton samples were collected from the subsurface and bottom of the water in areas where tagged whales dived to assess differences in composition, abundance, and biomass. Copepods dominated the upper layer, while euphausiids were more abundant in the deeper sample. Furthermore, zooplankton total biomass was five times higher at depth (2515.93 mg/m3) compared to the subsurface (500.35 mg/m3). Differences in zooplankton characteristics between depths, combined with CRITTERCAM videos, indicated that SRWs exploit high concentrations of organisms near the seafloor during daytime feeding dives. This study provides baseline insights into how SRWs utilize Península Valdés during their stay in the area.
A novel naturally superoleophilic coconut oil-based foam with inherent hydrophobic properties for oil and grease sorption
Authors: Tomon Tomas Ralph B. , Omisol Christine Joy M. , Aguinid Blessy Joy M. , Sabulbero Karyl Xyrra L. , Alguno Arnold C. , Malaluan Roberto M. , Lubguban Arnold A. 
Published: June 2024

AbstractAbsorption methods using polyurethane foams (PUFs) have recently gained popularity in treating oil spills. However, conventional petroleum-based PUFs lack selectivity and are commonly surface-modified using complicated processes that require toxic and harmful solvents to enhance their hydrophobicity and oil sorption capacities. In this paper, a novel naturally superoleophilic foam with inherent hydrophobic properties has been developed through the conventional one-shot foaming method with the integration of coconut oil-based polyol. This bio-based polyol was explicitly handpicked as it is chiefly saturated, highly abundant, and inexpensive. The foam is characterized by an oil sorption capacity range of 14.89–24.65 g g−1 for different types of oil, equivalent to 578–871 times its weight. Its hydrophobic behavior is expressed through a water contact angle of ~ 139°. The foam also showcased excellent chemical stability and high recyclability without a significant loss in absorption capacity after 20 cycles. The incorporation of the coconut oil-based polyol is also shown to improve the morphological, mechanical, and thermal behavior of the foam. It can be inferred from these findings that this novel material holds great potential for revolutionizing sorbents, pioneering a more sustainable and eco-friendly functional material produced via a facile method.
Reduced graphene oxide/zinc oxide composite as an electrochemical sensor for acetylcholine detection
Authors: Pitiphattharabun Siraprapa , Auewattanapun Krittin , Htet Thura Lin , Thu Myo Myo , Panomsuwan Gasidit , Techapiesancharoenkij Ratchatee , Ohta Jun , Jongprateep Oratai 
Published: June 2024

AbstractAcetylcholine (ACh) plays a pivotal role as a neurotransmitter, influencing nerve cell communication and overall nervous system health. Imbalances in ACh levels are linked to neurodegenerative diseases, such as Alzheimer's and Parkinson's. This study focused on developing electrochemical sensors for ACh detection, utilizing graphene oxide (GO) and a composite of reduced graphene oxide and zinc oxide (rGO/ZnO). The synthesis involved modified Hummers' and hydrothermal methods, unveiling the formation of rGO through deoxygenation and the integration of nano-sized ZnO particles onto rGO, as demonstrated by XPS and TEM. EIS analysis also revealed the enhancement of electron transfer efficiency in rGO/ZnO. Cyclic voltammograms of the electrode, comprising the rGO/ZnO composite in ACh solutions, demonstrated prominent oxidation and reduction reactions. Notably, the composite exhibited promise for ACh detection due to its sensitivity, low detection threshold, reusability, and selectivity against interfering compounds, specifically glutamate and gamma-aminobutyric acid. The unique properties of rGO, such as high specific surface area and electron mobility, coupled with ZnO's stability and catalytic efficiency, contributed to the composite's potential in electrochemical sensor applications. This research, emphasizing the synthesis, fabrication, and characterization of the rGO/ZnO composite, established itself as a reliable platform for detecting the acetylcholine neurotransmitter.
Integrating behavioural thermoregulatory strategy into the animal personality framework using the common lizard, Zootoca vivipara as a model
Authors: Horváth Gergely , Sos Tibor , Bóné Gábor , Lőrincz Csanád Endre , Pap Péter László , Herczeg Gábor 
Published: June 2024

AbstractThe study of consistent between-individual behavioural variation in single (animal personality) and across two or more behavioural traits (behavioural syndrome) is a central topic of behavioural ecology. Besides behavioural type (individual mean behaviour), behavioural predictability (environment-independent within-individual behavioural variation) is now also seen as an important component of individual behavioural strategy. Research focus is still on the ‘Big Five’ traits (activity, exploration, risk-taking, sociability and aggression), but another prime candidate to integrate to the personality framework is behavioural thermoregulation in small-bodied poikilotherms. Here, we found animal personality in thermoregulatory strategy (selected body temperature, voluntary thermal maximum, setpoint range) and ‘classic’ behavioural traits (activity, sheltering, risk-taking) in common lizards (Zootoca vivipara). Individual state did not explain the between-individual variation. There was a positive behavioural type—behavioural predictability correlation in selected body temperature. Besides an activity—risk-taking syndrome, we also found a risk-taking—selected body temperature syndrome. Our results suggest that animal personality and behavioural syndrome are present in common lizards, both including thermoregulatory and ‘classic’ behavioural traits, and selecting high body temperature with high predictability is part of the risk-prone behavioural strategy. We propose that thermoregulatory behaviour should be considered with equal weight to the ‘classic’ traits in animal personality studies of poikilotherms employing active behavioural thermoregulation.
3D microscopic reconstruction of pearls using combined optical microscopy and photogrammetry
Authors: Edeline Paul-Emmanuel , Leclercq Mickaël , Le Luyer Jérémy , Droit Arnaud , Chabrier Sébastien 
Published: June 2024

AbstractIn this study, we introduce an affordable and accessible method that combines optical microscopy and photogrammetry to reconstruct 3D models of Tahitian pearls. We present a novel device designed for acquiring microscopic images around a sphere using translational displacement stages and outline our method for reconstructing these images. We successfully created 3D models of two individual pearl rings, each representing 6.3% of the pearl’s surface. Additionally, we generated a combined model representing 10.3% of the pearl’s surface. This showcases the potential for reconstructing entire pearls with appropriate instrumentation. We emphasize that our approach extends beyond pearls and spherical objects and can be adapted for various object types using appropriate acquisition devices. We provide a proof of concept demonstrating the feasibility of 3D photogrammetry using optical microscopy. Consequently, our method offers a practical and cost-effective alternative for generating 3D models at a microscopic scale, particularly when detailed internal structure information is unnecessary.
Effects of field releases of Neoseiulus barkeri on Megalurothrips usitatus abundance and arthropod diversity
Authors: Chi YuanMing , Yu Chen , Feng MingYue , Shu Kai , Zhu YiLin , Shi WangPeng 
Published: June 2024

AbstractMegalurothrips usitatus (Bagnall) (Thysanoptera: Thripidae) is an important pest in Vigna unguiculata (L.) Walp. Neoseiulus barkeri (Hughes) (Acari: Phytoseiidae) is widely used for control of pest mites and insects worldwide. We evaluated its effect on M. usitatus when predators (N. barkeri) or insecticides (Spinetoram) were applied in the fields. Neoseiulus barkeri Hughes consumed 80% of M. usitatus prey offered within 6 h, and predation showed Type III functional response with prey density. The maximum consumption of N. barkeri was 27.29 ± 1.02 individuals per d per arena (1.5 cm diameter), while the optimal prey density for the predatory mite was 10.35 ± 0.68 individuals per d per arena (1.5 cm diameter). The developmental duration of N. barkeri fed with M. usitatus was significantly shorter than those fed with the dried fruit mite, Carpoglyphus lactis (L.) (Acari: Astigmata). In field trials, the efficiency of N. barkeri against M. usitatus was not significantly different from that of applications of the insecticide spinetoram. Biodiversity of other insects in treated fields was assessed, and there were 21 insect species in garden plots treated with N. barkeri releases. The total abundance (N), Shannon’s diversity index (H), Pielou’s evenness index (J) and Simpson’s diversity index (D) of the garden plots treated with predatory mites were all significantly higher than that in the garden plots treated with spinetoram, where we found no species of predators or parasitoids and 7 herbivores. Our results show that N. barkeri is a potential means to control M. usitatus while preserving arthropod diversity at the level of treated gardens.
Automatic classification of normal and abnormal cell division using deep learning
Authors: Delgado-Rodriguez Pablo , Sánchez Rodrigo Morales , Rouméas-Noël Elouan , Paris François , Munoz-Barrutia Arrate 
Published: June 2024

AbstractIn recent years, there has been a surge in the development of methods for cell segmentation and tracking, with initiatives like the Cell Tracking Challenge driving progress in the field. Most studies focus on regular cell population videos in which cells are segmented and followed, and parental relationships annotated. However, DNA damage induced by genotoxic drugs or ionizing radiation produces additional abnormal events since it leads to behaviors like abnormal cell divisions (resulting in a number of daughters different from two) and cell death. With this in mind, we developed an automatic mitosis classifier to categorize small mitosis image sequences centered around one cell as “Normal” or “Abnormal.” These mitosis sequences were extracted from videos of cell populations exposed to varying levels of radiation that affect the cell cycle’s development. We explored several deep-learning architectures and found that a network with a ResNet50 backbone and including a Long Short-Term Memory (LSTM) layer produced the best results (mean F1-score: 0.93 ± 0.06). In the future, we plan to integrate this classifier with cell segmentation and tracking to build phylogenetic trees of the population after genomic stress.
Sedentary behaviour among elderly patients after total knee arthroplasty and its influencing factors
Authors: Ni Xuan , Shi Juan , Hu Qing , Li Ai , Zeng Xing , Gu Yajing 
Published: June 2024

AbstractTo understand the status of sedentary behaviour in elderly patients after total knee arthroplasty and analyse its influencing factors so as to provide a reference for developing targeted interventions. Conveniently selected elderly patients undergoing total knee arthroplasty (> 6 months) in a tertiary hospital in Jiangsu Province were investigated using a general information questionnaire, the Charlson Comorbidity Index, patients’ self-reported sedentary behaviour information, the WOMAC Score, The Groningen Orthopaedic Social Support Scale, and Lee’s Fatigue. The median daily sedentary time was 5.5 h (4.5 h, 6.625 h) in 166 elderly patients after total knee arthroplasty, of whom 82 (49.40%) showed sedentary behaviour (≥ 6 h per day). Logistic regression analysis showed that being retired/unemployed (OR = 8.550, 95% CI 1.732–42.207, P = 0.0084), having a CCI score ≥ 3 (OR = 9.018, 95% CI 1.288–63.119, P < 0.0001), having high WOMAC scores (OR = 1.783, 95% CI 1.419–2.238, P < 0.0001), having a high social support score (OR = 1.155, 95% CI 1.031–1.294, P = 0.0130), and having a fatigue score ≥ 5 (OR = 4.848, 95% CI 1.084–21.682, P = 0.0389) made patients more likely to be sedentary. The sedentary time of elderly patients after total knee arthroplasty is long, and sedentary behaviour is common among them. Healthcare professionals should develop targeted sedentary behaviour interventions based on the influencing factors of sedentary behaviour in order to reduce the occurrence of sedentary behaviour in elderly patients after total knee arthroplasty.
Using an adaptive modeling framework to identify avian influenza spillover risk at the wild-domestic interface
Authors: Prosser Diann J. , Kent Cody M. , Sullivan Jeffery D. , Patyk Kelly A. , McCool Mary-Jane , Torchetti Mia Kim , Lantz Kristina , Mullinax Jennifer M. 
Published: June 2024

AbstractThe wild to domestic bird interface is an important nexus for emergence and transmission of highly pathogenic avian influenza (HPAI) viruses. Although the recent incursion of HPAI H5N1 Clade 2.3.4.4b into North America calls for emergency response and planning given the unprecedented scale, readily available data-driven models are lacking. Here, we provide high resolution spatial and temporal transmission risk models for the contiguous United States. Considering virus host ecology, we included weekly species-level wild waterfowl (Anatidae) abundance and endemic low pathogenic avian influenza virus prevalence metrics in combination with number of poultry farms per commodity type and relative biosecurity risks at two spatial scales: 3 km and county-level. Spillover risk varied across the annual cycle of waterfowl migration and some locations exhibited persistent risk throughout the year given higher poultry production. Validation using wild bird introduction events identified by phylogenetic analysis from 2022 to 2023 HPAI poultry outbreaks indicate strong model performance. The modular nature of our approach lends itself to building upon updated datasets under evolving conditions, testing hypothetical scenarios, or customizing results with proprietary data. This research demonstrates an adaptive approach for developing models to inform preparedness and response as novel outbreaks occur, viruses evolve, and additional data become available.