bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic evidence for involvement of β2-adrenergic receptor in brown adipose tissue thermogenesis in humans
Authors: Ishida Yuka , Matsushita Mami , Yoneshiro Takeshi , Saito Masayuki , Fuse Sayuri , Hamaoka Takafumi , Kuroiwa Miyuki , Tanaka Riki , Kurosawa Yuko , Nishimura Takayuki , Motoi Midori , Maeda Takafumi , Nakayama Kazuhiro 
Published: April 2024

Abstract
Background
Sympathetic activation of brown adipose tissue (BAT) thermogenesis can ameliorate obesity and related metabolic abnormalities. However, crucial subtypes of the β-adrenergic receptor (AR), as well as effects of its genetic variants on functions of BAT, remains unclear in humans. We conducted association analyses of genes encoding β-ARs and BAT activity in human adults.

Methods
Single nucleotide polymorphisms (SNPs) in β1-, β2-, and β3-AR genes (ADRB1, ADRB2, and ADRB3) were tested for the association with BAT activity under mild cold exposure (19 °C, 2 h) in 399 healthy Japanese adults. BAT activity was measured using fluorodeoxyglucose-positron emission tomography and computed tomography (FDG-PET/CT). To validate the results, we assessed the effects of SNPs in the two independent populations comprising 277 healthy East Asian adults using near-infrared time-resolved spectroscopy (NIRTRS) or infrared thermography (IRT). Effects of SNPs on physiological responses to intensive cold exposure were tested in 42 healthy Japanese adult males using an artificial climate chamber.

Results
We found a significant association between a functional SNP (rs1042718) in ADRB2 and BAT activity assessed with FDG-PET/CT (p < 0.001). This SNP also showed an association with cold-induced thermogenesis in the population subset. Furthermore, the association was replicated in the two other independent populations; BAT activity was evaluated by NIRTRS or IRT (p < 0.05). This SNP did not show associations with oxygen consumption and cold-induced thermogenesis under intensive cold exposure, suggesting the irrelevance of shivering thermogenesis. The SNPs of ADRB1 and ADRB3 were not associated with these BAT-related traits.

Conclusions
The present study supports the importance of β2-AR in the sympathetic regulation of BAT thermogenesis in humans. The present collection of DNA samples is the largest to which information on the donor’s BAT activity has been assigned and can serve as a reference for further in-depth understanding of human BAT function.
miR-124-3p and miR-194-5p regulation of the PI3K/AKT pathway via ROR2 in medulloblastoma progression
Authors: Wang Chen , Fu Runxi , Wang Yunkun , Wei Jia , Yu Ying , Hu Liuhua , Zhang Chenran 
Published: April 2024

AbstractMedulloblastoma (MB), a prevalent pediatric central nervous system tumor, is influenced by microRNAs (miRNAs) that impact tumor initiation and progression. However, the specific involvement of miRNAs in MB tumorigenesis remains unclear. Using single-cell RNA sequencing, we identified ROR2 expression in normal human fetal cerebellum. Subsequent analyses, including immunofluorescence, quantitative real-time PCR (qRT-PCR), and Western blot, assessed ROR2 expression in MB tissues and cell lines. We investigated miR-124-3p and miR-194-5p and their regulatory role in ROR2 expression through the dual-luciferase reporter, qRT-PCR, and western blot assays. Mechanistic insights were gained through functional assays exploring the impact of miR-124-3p, miR-194-5p, and ROR2 on MB growth in vitro and in vivo. We observed significantly reduced miR-124-3p and miR-194-5p expression and elevated ROR2 expression in MB tissues and cell lines. High ROR2 expression inversely correlated with overall survival in WNT and SHH subgroups of MB patients. Functionally, overexpressing miR-124-3p and miR-194-5p and inhibiting ROR2 suppressed in vitro malignant transformation and in vivo tumorigenicity. Mechanistically, miR-124-3p and miR-194-5p synergistically regulated the ROR2/PI3K/Akt pathway, influencing MB progression. Our findings indicate that miR-124-3p and miR-194-5p function as tumor suppressors, inhibiting MB progression via the ROR2/PI3K/Akt axis, suggesting a key mechanism and therapeutic targets for MB patients.
Dynamics of early-stage oxide formation on a Ni-Cr-Mo alloy
Authors: Larsson Alfred , Gericke Sabrina , Grespi Andrea , Koller Volkmar , Eidhagen Josefin , Yue Xiaoqi , Frampton Eleanor , Appelfeller Stephan , Generalov Alexander , Preobrajenski Alexei , Pan Jinshan , Over Herbert , Lundgren Edvin 
Published: April 2024

AbstractCorrosion results in large costs and environmental impact but can be controlled by thin oxide films that passivate the metal surfaces and hinder further oxidation or dissolution in an aqueous environment. The structure, chemistry, and thickness of these oxide films play a significant role in determining their anti-corrosion properties and the early-stage oxidation dynamics affect the properties of the developed oxide. Here, we use in situ X-ray Photoelectron Spectroscopy (XPS) to study the early-stage oxidation of a Ni-Cr-Mo alloy at room temperature and up to 400 °C. Cr and Mo begin to oxidize immediately after exposure to O2, and Cr3+, Mo4+, and Mo6+ oxides are formed. In contrast, Ni does not contribute significantly to the oxide film. A self-limiting oxide thickness, which did not depend on temperature below 400 °C, is observed. This is attributed to the consumption of available Cr and Mo near the surface, which results in an enrichment of metallic Ni under the oxide. The self-limited oxide thickness is 6–8 Å, which corresponds to 3–4 atomic layers of cations in the oxide. At 400 °C, sublimation of Mo6+ oxide is observed, resulting in the formation of an almost pure layer of Cr2O3 on the alloy surface. Lastly, a mechanism is presented that explains the formation of the bi-layer oxide structure observed for Ni-Cr-Mo alloys, which involves the enhanced migration of hexavalent Mo ions in the electric field, which drives mass transport during oxidation according to both the Cabrera Mott model and the Point Defect Model.
Streptomyces umbrella toxin particles block hyphal growth of competing species
Authors: Zhao Qinqin , Bertolli Savannah , Park Young-Jun , Tan Yongjun , Cutler Kevin J. , Srinivas Pooja , Asfahl Kyle L. , Fonesca-García Citlali , Gallagher Larry A. , Li Yaqiao , Wang Yaxi , Coleman-Derr Devin , DiMaio Frank , Zhang Dapeng , Peterson S. Brook , Veesler David , Mougous Joseph D. 
Published: April 2024

AbstractStreptomyces are a genus of ubiquitous soil bacteria from which the majority of clinically utilized antibiotics derive1. The production of these antibacterial molecules reflects the relentless competition Streptomyces engage in with other bacteria, including other Streptomyces species1,2. Here we show that in addition to small-molecule antibiotics, Streptomyces produce and secrete antibacterial protein complexes that feature a large, degenerate repeat-containing polymorphic toxin protein. A cryo-electron microscopy structure of these particles reveals an extended stalk topped by a ringed crown comprising the toxin repeats scaffolding five lectin-tipped spokes, which led us to name them umbrella particles. Streptomyces coelicolor encodes three umbrella particles with distinct toxin and lectin composition. Notably, supernatant containing these toxins specifically and potently inhibits the growth of select Streptomyces species from among a diverse collection of bacteria screened. For one target, Streptomyces griseus, inhibition relies on a single toxin and that intoxication manifests as rapid cessation of vegetative hyphal growth. Our data show that Streptomyces umbrella particles mediate competition among vegetative mycelia of related species, a function distinct from small-molecule antibiotics, which are produced at the onset of reproductive growth and act broadly3,4. Sequence analyses suggest that this role of umbrella particles extends beyond Streptomyces, as we identified umbrella loci in nearly 1,000 species across Actinobacteria.
Integrative common and rare variant analyses provide insights into the genetic architecture of liver cirrhosis
Authors: Ghouse Jonas , Sveinbjörnsson Gardar , Vujkovic Marijana , Seidelin Anne-Sofie , Gellert-Kristensen Helene , Ahlberg Gustav , Tragante Vinicius , Rand Søren A. , Brancale Joseph , Vilarinho Silvia , Lundegaard Pia Rengtved , Sørensen Erik , Erikstrup Christian , Bruun Mie Topholm , Jensen Bitten Aagaard , Brunak Søren , Banasik Karina , Ullum Henrik ,   DBDS Genomic Consortium, Verweij Niek , Lotta Luca , Baras Aris ,   Regeneron Genetics Center, Lotta Luca A. , Mirshahi Tooraj , Carey David J. ,   Geisinger-Regeneron DiscovEHR Collaboration,   VA Million Veteran Program, Kaplan David E. , Lynch Julie , Morgan Timothy , Schwantes-An Tae-Hwi , Dochtermann Daniel R. , Pyarajan Saiju , Tsao Philip S. ,   Estonian Biobank Research Team, Laisk Triin , Mägi Reedik , Kozlitina Julia , Tybjærg-Hansen Anne , Jones David , Knowlton Kirk U. , Nadauld Lincoln , Ferkingstad Egil , Björnsson Einar S. , Ulfarsson Magnus O. , Sturluson Árni , Sulem Patrick , Pedersen Ole B. , Ostrowski Sisse R. , Gudbjartsson Daniel F. , Stefansson Kari , Olesen Morten Salling , Chang Kyong-Mi , Holm Hilma , Bundgaard Henning , Stender Stefan 
Published: April 2024

AbstractWe report a multi-ancestry genome-wide association study on liver cirrhosis and its associated endophenotypes, alanine aminotransferase (ALT) and γ-glutamyl transferase. Using data from 12 cohorts, including 18,265 cases with cirrhosis, 1,782,047 controls, up to 1 million individuals with liver function tests and a validation cohort of 21,689 cases and 617,729 controls, we identify and validate 14 risk associations for cirrhosis. Many variants are located near genes involved in hepatic lipid metabolism. One of these, PNPLA3 p.Ile148Met, interacts with alcohol intake, obesity and diabetes on the risk of cirrhosis and hepatocellular carcinoma (HCC). We develop a polygenic risk score that associates with the progression from cirrhosis to HCC. By focusing on prioritized genes from common variant analyses, we find that rare coding variants in GPAM associate with lower ALT, supporting GPAM as a potential target for therapeutic inhibition. In conclusion, this study provides insights into the genetic underpinnings of cirrhosis.
Efficacy of a new refractive multifocal contact lens for presbyopia
Authors: Kim Do Young , Ahn Hyunmin , Lee Sukyung , Jun Ikhyun , Seo Kyoung Yul , Kim Sang Yeop , Kim Tae-Im 
Published: April 2024

AbstractThis prospective single-arm study aimed to evaluate the clinical efficacy and safety of a refractive multifocal contact lens for the correction of presbyopia in 22 patients. The participants underwent clinical examinations before and 1 week after wearing a refractive multifocal contact lens (OptaCon ZOOM). The primary endpoints were the corrected distance visual acuity (CDVA) and distance-corrected near visual acuity (DCNVA). Defocus curve, contrast sensitivity, and ocular surface disease index (OSDI) were analyzed. A slit-lamp examination was performed for safety analysis. Contact lens comfort and patient satisfaction were assessed using a questionnaire. No significant difference in CDVA was observed before and 1 week after refractive multifocal contact lens use (p = 0.127), whereas DCNVA was significantly improved after 1 week (p < 0.001). The contrast sensitivity was not significantly affected at any spatial frequency under mesopic or photopic conditions. OSDI was significantly increased (p = 0.023). The patient-reported satisfaction scores were 96.2, 91.9, and 85.0 out of 100 at far, intermediate, and near distances, respectively. No significant adverse events were observed. Refractive multifocal contact lenses improved near vision while maintaining distance vision in presbyopic patients, without compromising contrast sensitivity. The study results suggest that OptaCon ZOOM can be considered safe and effective for the correction of presbyopia.
Application of evolutionary algorithms to design economic flat slab buildings based on the intended function
Authors: Rady Mohammed 
Published: April 2024

AbstractNumerous studies revealed optimization techniques' applicability in minimizing the costs of reinforced concrete buildings. However, the existing literature has narrowly focused on optimizing buildings with a single function, such as residential or office buildings, hindering the generalization of the results. This paper aims to bridge the gap between optimization and structural engineering by obtaining the minimum-cost design of flat slab buildings with different intended functions. In this context, the optimal designs of 120 alternatives were obtained, considering various spans (4–8 m), live loads (2–10 kPa), and concrete compressive strength (25–40 MPa). The optimization was executed using the evolutionary algorithm provided in Microsoft Excel’s Solver tool. The optimization model permits the utilization of drop panels to resist punching stresses developed from the slab-column interaction. The objective function is the cost of materials and labor involved in constructing floors and columns. The decision variables are the floor dimensions and column configurations in dimensions and reinforcement. The structural constraints were applied per the Egyptian design code (ECP203-2020). Eventually, guidelines were developed to help the designers choose the economic floor system and quantities of materials based on the building's intended function.
Glyphosate-induced changes in the expression of galanin and GALR1, GALR2 and GALR3 receptors in the porcine small intestine wall
Authors: Palus Katarzyna , Chmielewska-Krzesińska Małgorzata , Jana Barbara , Całka Jarosław 
Published: April 2024

AbstractGlyphosate is the active ingredient of glyphosate-based herbicides and the most commonly used pesticide in the world. The goal of the present study was to verify whether low doses of glyphosate (equivalent to the environmental exposure) evoke changes in galanin expression in intramural neurons in the small intestine in pigs and to quantitatively determine changes in the level of galanin receptor encoding mRNA (GALR1, GALR2, GALR3) in the small intestine wall. The experiment was conducted on 15 sexually immature gilts divided into three study groups: control (C)—animals receiving empty gelatin capsules; experimental 1 (G1)—animals receiving a low dose of glyphosate (0.05 mg/kg b.w./day); experimental 2 (G2)—animals receiving a higher dose of glyphosate (0.5 mg/kg b.w./day) orally in gelatine capsules for 28 days. Glyphosate ingestion led to an increase in the number of GAL-like immunoreactive intramural neurons in the porcine small intestine. The results of RT-PCR showed a significant increase in the expression of mRNA, which encodes the GAL-receptors in the ileum, a decreased expression in the duodenum and no significant changes in the jejunum. Additionally, intoxication with glyphosate increased the expression of SOD2-encoding mRNA in the duodenum and decreased it in the jejunum and ileum, but it did not affect SOD1 expression. The results suggest that it may be a consequence of the cytotoxic and/or neurotoxic properties of glyphosate and/or its ability to induce oxidative stress.
Randomized feature selection based semi-supervised latent Dirichlet allocation for microbiome analysis
Authors: Pais Namitha , Ravishanker Nalini , Rajasekaran Sanguthevar , Weinstock George , Tran Dong-Binh 
Published: April 2024

AbstractHealth and disease are fundamentally influenced by microbial communities and their genes (the microbiome). An in-depth analysis of microbiome structure that enables the classification of individuals based on their health can be crucial in enhancing diagnostics and treatment strategies to improve the overall well-being of an individual. In this paper, we present a novel semi-supervised methodology known as Randomized Feature Selection based Latent Dirichlet Allocation (RFSLDA) to study the impact of the gut microbiome on a subject’s health status. Since the data in our study consists of fuzzy health labels, which are self-reported, traditional supervised learning approaches may not be suitable. As a first step, based on the similarity between documents in text analysis and gut-microbiome data, we employ Latent Dirichlet Allocation (LDA), a topic modeling approach which uses microbiome counts as features to group subjects into relatively homogeneous clusters, without invoking any knowledge of observed health status (labels) of subjects. We then leverage information from the observed health status of subjects to associate these clusters with the most similar health status making it a semi-supervised approach. Finally, a feature selection technique is incorporated into the model to improve the overall classification performance. The proposed method provides a semi-supervised topic modelling approach that can help handle the high dimensionality of the microbiome data in association studies. Our experiments reveal that our semi-supervised classification algorithm is effective and efficient in terms of high classification accuracy compared to popular supervised learning approaches like SVM and multinomial logistic model. The RFSLDA framework is attractive because it (i) enhances clustering accuracy by identifying key bacteria types as indicators of health status, (ii) identifies key bacteria types within each group based on estimates of the proportion of bacteria types within the groups, and (iii) computes a measure of within-group similarity to identify highly similar subjects in terms of their health status.
Multi-scale attention network (MSAN) for track circuits fault diagnosis
Authors: Tao Weijie , Li Xiaowei , Liu Jianlei , Li Zheng 
Published: April 2024

AbstractAs one of the three major outdoor components of the railroad signal system, the track circuit plays an important role in ensuring the safety and efficiency of train operation. Therefore, when a fault occurs, the cause of the fault needs to be found quickly and accurately and dealt with in a timely manner to avoid affecting the efficiency of train operation and the occurrence of safety accidents. This article proposes a fault diagnosis method based on multi-scale attention network, which uses Gramian Angular Field (GAF) to transform one-dimensional time series into two-dimensional images, making full use of the advantages of convolutional networks in processing image data. A new feature fusion training structure is designed to effectively train the model, fully extract features at different scales, and fusing spatial feature information through spatial attention mechanisms. Finally, experiments are conducted using real track circuit fault datasets, and the accuracy of fault diagnosis reaches 99.36%, and our model demonstrates better performance compared to classical and state-of-the-art models. And the ablation experiments verified that each module in the designed model plays a key role.
Genetic barriers more than environmental associations explain Serratia marcescens population structure
Authors: Sterzi Lodovico , Nodari Riccardo , Di Marco Federico , Ferrando Maria Laura , Saluzzo Francesca , Spitaleri Andrea , Allahverdi Hamed , Papaleo Stella , Panelli Simona , Rimoldi Sara Giordana , Batisti Biffignandi Gherard , Corbella Marta , Cavallero Annalisa , Prati Paola , Farina Claudio , Cirillo Daniela Maria , Zuccotti Gianvincenzo , Bandi Claudio , Comandatore Francesco 
Published: April 2024

AbstractBacterial species often comprise well-separated lineages, likely emerged and maintained by genetic isolation and/or ecological divergence. How these two evolutionary actors interact in the shaping of bacterial population structure is currently not fully understood. In this study, we investigate the genetic and ecological drivers underlying the evolution of Serratia marcescens, an opportunistic pathogen with high genomic flexibility and able to colonise diverse environments. Comparative genomic analyses reveal a population structure composed of five deeply-demarcated genetic clusters with open pan-genome but limited inter-cluster gene flow, partially explained by Restriction-Modification (R-M) systems incompatibility. Furthermore, a large-scale research on hundred-thousands metagenomic datasets reveals only a partial habitat separation of the clusters. Globally, two clusters only show a separate gene composition coherent with ecological adaptations. These results suggest that genetic isolation has preceded ecological adaptations in the shaping of the species diversity, an evolutionary scenario coherent with the Evolutionary Extended Synthesis.
Synthetic Lagrangian turbulence by generative diffusion models
Authors: Li T. , Biferale L. , Bonaccorso F. , Scarpolini M. A. , Buzzicotti M. 
Published: April 2024

AbstractLagrangian turbulence lies at the core of numerous applied and fundamental problems related to the physics of dispersion and mixing in engineering, biofluids, the atmosphere, oceans and astrophysics. Despite exceptional theoretical, numerical and experimental efforts conducted over the past 30 years, no existing models are capable of faithfully reproducing statistical and topological properties exhibited by particle trajectories in turbulence. We propose a machine learning approach, based on a state-of-the-art diffusion model, to generate single-particle trajectories in three-dimensional turbulence at high Reynolds numbers, thereby bypassing the need for direct numerical simulations or experiments to obtain reliable Lagrangian data. Our model demonstrates the ability to reproduce most statistical benchmarks across time scales, including the fat-tail distribution for velocity increments, the anomalous power law and the increased intermittency around the dissipative scale. Slight deviations are observed below the dissipative scale, particularly in the acceleration and flatness statistics. Surprisingly, the model exhibits strong generalizability for extreme events, producing events of higher intensity and rarity that still match the realistic statistics. This paves the way for producing synthetic high-quality datasets for pretraining various downstream applications of Lagrangian turbulence.
The buzz about honey-based biosurveys
Authors: Vuong Paton , Griffiths Anna Poppy , Barbour Elizabeth , Kaur Parwinder 
Published: April 2024

AbstractApproximately 1.8 million metric tonnes of honey are produced globally every year. The key source behind this output, the honey bee (Apis mellifera), works tirelessly to create the delicious condiment that is consumed worldwide. The honey that finds its way into jars on store shelves contains a myriad of information about its biogeographical origins, such as the bees that produced it, the botanical constituents, and traces of other organisms or pathogens that have come in contact with the product or its producer. With the ongoing threat of honey bee decline and overall global biodiversity loss, access to ecological information has become an key factor in preventing the loss of species. This review delves into the various molecular techniques developed to characterize the collective DNA harnessed within honey samples, and how it can be used to elucidate the ecological interactions between honey bees and the environment. We also explore how these DNA-based methods can be used for large-scale biogeographical studies through the environmental DNA collected by foraging honey bees. Further development of these techniques can assist in the conservation of biodiversity by detecting ecosystem perturbations, with the potential to be expanded towards other critical flying pollinators.