bluuebunny/crossref_metadata_2025_split huggingface dataset:
Meta-analysis shows no consistent evidence for senescence in ejaculate traits across animals
Authors: Sanghvi Krish , Vega-Trejo Regina , Nakagawa Shinichi , Gascoigne Samuel J. L. , Johnson Sheri L. , Salguero-Gómez Roberto , Pizzari Tommaso , Sepil Irem 
Published: January 2024

AbstractMale reproductive traits such as ejaculate size and quality, are expected to decline with advancing age due to senescence. It is however unclear whether this expectation is upheld across taxa. We perform a meta-analysis on 379 studies, to quantify the effects of advancing male age on ejaculate traits across 157 species of non-human animals. Contrary to predictions, we find no consistent pattern of age-dependent changes in ejaculate traits. This result partly reflects methodological limitations, such as studies sampling a low proportion of adult lifespan, or the inability of meta-analytical approaches to document non-linear ageing trajectories of ejaculate traits; which could potentially lead to an underestimation of senescence. Yet, we find taxon-specific differences in patterns of ejaculate senescence. For instance, older males produce less motile and slower sperm in ray-finned fishes, but larger ejaculates in insects, compared to younger males. Notably, lab rodents show senescence in most ejaculate traits measured. Our study challenges the notion of universal reproductive senescence, highlighting the need for controlled methodologies and a more nuanced understanding of reproductive senescence, cognisant of taxon-specific biology, experimental design, selection pressures, and life-history.
How solute atoms control aqueous corrosion of Al-alloys
Authors: Zhao Huan , Yin Yue , Wu Yuxiang , Zhang Siyuan , Mingers Andrea M. , Ponge Dirk , Gault Baptiste , Rohwerder Michael , Raabe Dierk 
Published: January 2024

AbstractAluminum alloys play an important role in circular metallurgy due to their good recyclability and 95% energy gain when made from scrap. Their low density and high strength translate linearly to lower greenhouse gas emissions in transportation, and their excellent corrosion resistance enhances product longevity. The durability of Al alloys stems from the dense barrier oxide film strongly bonded to the surface, preventing further degradation. However, despite decades of research, the individual elemental reactions and their influence on the nanoscale characteristics of the oxide film during corrosion in multicomponent Al alloys remain unresolved questions. Here, we build up a direct correlation between the near-atomistic picture of the corrosion oxide film and the solute reactivity in the aqueous corrosion of a high-strength Al-Zn-Mg-Cu alloy. We reveal the formation of nanocrystalline Al oxide and highlight the solute partitioning between the oxide and the matrix and segregation to the internal interface. The sharp decrease in partitioning content of Mg in the peak-aged alloy emphasizes the impact of heat treatment on the oxide stability and corrosion kinetics. Through H isotopic labelling with deuterium, we provide direct evidence that the oxide acts as a trap for this element, pointing at the essential role of the Al oxide might act as a kinetic barrier in preventing H embrittlement. Our findings advance the mechanistic understanding of further improving the stability of Al oxide, guiding the design of corrosion-resistant alloys for potential applications.
Host- plasmid network structure in wastewater is linked to antimicrobial resistance genes
Authors: Risely Alice , Newbury Arthur , Stalder Thibault , Simmons Benno I. , Top Eva M. , Buckling Angus , Sanders Dirk 
Published: January 2024

AbstractAs mobile genetic elements, plasmids are central for our understanding of antimicrobial resistance spread in microbial communities. Plasmids can have varying fitness effects on their host bacteria, which will markedly impact their role as antimicrobial resistance vectors. Using a plasmid population model, we first show that beneficial plasmids interact with a higher number of hosts than costly plasmids when embedded in a community with multiple hosts and plasmids. We then analyse the network of a natural host-plasmid wastewater community from a Hi-C metagenomics dataset. As predicted by the model, we find that antimicrobial resistance encoding plasmids, which are likely to have positive fitness effects on their hosts in wastewater, interact with more bacterial taxa than non-antimicrobial resistance plasmids and are disproportionally important for connecting the entire network compared to non- antimicrobial resistance plasmids. This highlights the role of antimicrobials in restructuring host-plasmid networks by increasing the benefits of antimicrobial resistance carrying plasmids, which can have consequences for the spread of antimicrobial resistance genes through microbial networks. Furthermore, that antimicrobial resistance encoding plasmids are associated with a broader range of hosts implies that they will be more robust to turnover of bacterial strains.
Connectivity-guided intermittent theta burst versus repetitive transcranial magnetic stimulation for treatment-resistant depression: a randomized controlled trial
Authors: Morriss Richard , Briley Paul M. , Webster Lucy , Abdelghani Mohamed , Barber Shaun , Bates Peter , Brookes Cassandra , Hall Beth , Ingram Luke , Kurkar Micheal , Lankappa Sudheer , Liddle Peter F. , McAllister-Williams R. Hamish , O’Neil-Kerr Alexander , Pszczolkowski Stefan , Suazo Di Paola Ana , Walters Yvette , Auer Dorothee P. 
Published: January 2024

AbstractDisruption in reciprocal connectivity between the right anterior insula and the left dorsolateral prefrontal cortex is associated with depression and may be a target for neuromodulation. In a five-center, parallel, double-blind, randomized controlled trial we personalized resting-state functional magnetic resonance imaging neuronavigated connectivity-guided intermittent theta burst stimulation (cgiTBS) at a site based on effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. We tested its efficacy in reducing the primary outcome depression symptoms measured by the GRID Hamilton Depression Rating Scale 17-item over 8, 16 and 26 weeks, compared with structural magnetic resonance imaging (MRI) neuronavigated repetitive transcranial magnetic stimulation (rTMS) delivered at the standard stimulation site (F3) in patients with ‘treatment-resistant depression’. Participants were randomly assigned to 20 sessions over 4–6 weeks of either cgiTBS (n = 128) or rTMS (n = 127) with resting-state functional MRI at baseline and 16 weeks. Persistent decreases in depressive symptoms were seen over 26 weeks, with no differences between arms on the primary outcome GRID Hamilton Depression Rating Scale 17-item score (intention-to-treat adjusted mean, −0.31, 95% confidence interval (CI) −1.87, 1.24, P = 0.689). Two serious adverse events were possibly related to TMS (mania and psychosis). MRI-neuronavigated cgiTBS and rTMS were equally effective in patients with treatment-resistant depression over 26 weeks (trial registration no. ISRCTN19674644).
RailFOD23: A dataset for foreign object detection on railroad transmission lines
Authors: Chen Zhichao , Yang Jie , Feng Zhicheng , Zhu Hao 
Published: January 2024

AbstractArtificial intelligence models play a crucial role in monitoring and maintaining railroad infrastructure by analyzing image data of foreign objects on power transmission lines. However, the availability of publicly accessible datasets for railroad foreign objects is limited, and the rarity of anomalies in railroad image data, combined with restricted data sharing, poses challenges for training effective foreign object detection models. In this paper, the aim is to present a new dataset of foreign objects on railroad transmission lines, and evaluating the overall performance of mainstream detection models in this context. Taking a unique approach and leveraging large-scale models such as ChatGPT (Chat Generative Pre-trained Transformer) and text-to-image generation models, we synthesize a series of foreign object data. The dataset includes 14,615 images with 40,541 annotated objects, covering four common foreign objects on railroad power transmission lines. Through empirical research on this dataset, we validate the performance of various baseline models in foreign object detection, providing valuable insights for the monitoring and maintenance of railroad facilities.
Pollutant accumulation and microbial community evolution in rain gardens with different drainage types at field scale
Authors: Zhang Zhaoxin , Zhang Yang , Li Jiake , Sun Yingying , Liu Zhe 
Published: January 2024

AbstractRain gardens play a key role in urban non-point source pollution control. The drainage type affects the infiltration processes of runoff pollutants. The soil properties and microbial community structures were studied to reveal the stability of the ecosystem in rain gardens with different drainage types under long-term operation. The results showed that the soil water content and total organic carbon in the drained rain gardens were always higher than that of the infiltrated ones. With the increase in running time, the contents of heavy metals in rain gardens showed significant accumulation phenomena, especially the contents of Zn and Pb in drained rain gardens were higher than that in infiltrated ones. The accumulation of pollutants resulted in lower microbial diversity in drained rain gardens than in infiltrated rain gardens, but the microbial community structures were the same in all rain gardens. The effects of drainage type on microbial community evolution were not significant, only the accumulation of heavy metals led to changes in the abundance of dominant microorganisms. There were differences in the soil environment of rain gardens with different drainage types. The long-term operation of rain gardens led to fluctuations in the soil ecosystem, while the internal micro-ecosystems of the drained rain gardens were in unstable states.
Public health-focused use of COVID-19 rapid antigen and PCR tests
Authors: Woodbridge Yonatan , Goldberg Yair , Amit Sharon , Kopelman Naama M. , Mandel Micha , Huppert Amit 
Published: January 2024

AbstractDuring the Covid-19 pandemic, accurate PCR tests were augmented by the cheap, rapid, and logistically convenient, yet less sensitive antigen tests. In Israel, a testing policy shift was implemented due to limited availability of PCR tests during the Omicron surge. Thus, both PCR and antigen tests were used, as this was the only alternative for mass testing and surveillance at the time. Yet, evidence-based surveillance requires a robust understanding of the expected consequences of changing the testing policy. Using 41,065 paired tests performed by trained staff between January and April 2022 in Israel, we estimate how the sensitivity of antigen tests changes as a function of Ct value and other key covariates. The results reveal a logarithmic relationship between antigen detection probability and viral load, as quantified by Ct-values of the PCR tests. Further analysis shows a statistically significant association with an odds ratio of approximately 0.76 with each unit of Ct-value. The analysis suggests that in spite of their compromised sensitivity, antigen tests are a natural solution for routine use, while PCR tests should be considered in situations where a false negative result could have serious consequences. These findings are the foundations of policies that will utilize the strengths of the different tests, and achieve enhanced hybrid surveillance.
Golgi-targeting viscosity probe for the diagnosis of Alzheimer’s disease
Authors: Wu Wenjing , Zhao Lingyu , Zhang Yuanyuan , Wei Jinchao , Han Juanjuan , Zhang Yangyang , Zhao Zhenwen 
Published: January 2024

AbstractEarly diagnosis and intervention of Alzheimer’s disease (AD) are particularly important to delay the pathological progression. Although fluorescent probes have been widely employed for investigating and diagnosing AD, their biological applications are significantly restricted due to the low penetration ability of the blood–brain barrier (BBB) in vivo. In this study, we reported the first Golgi-targeted two-photon (TP) fluorescent probe, DCM-DH, for detecting viscosity in the Golgi apparatus. The probe was rationally designed to exhibit superior analytical performance including high sensitivity, specific Golgi-targeting, efficient BBB penetration ability, and deep tissue penetration (247 μm) in the brains of AD model mice. Using the probe, we demonstrated that the fluorescence intensity in the human liver cancer cell (HepG2 cells) was higher than that of human normal liver cell (LO2 cells), and the brain viscosity of AD model mice increased significantly. We anticipate that this competent tool could be easily extended to other AD biomarkers for fundamental research on this detrimental disease.
Prenatal tobacco smoke exposure and risk for cognitive delays in infants born very premature
Authors: Mahabee-Gittens E. Melinda , Harun Nusrat , Glover Meredith , Folger Alonzo T. , Parikh Nehal A. ,   Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS) Investigators, Altaye Mekibib , Arnsperger Anita , Beiersdorfer Traci , Bridgewater Kaley , Cahill Tanya , Cecil Kim , Dietrich Kent , Distler Christen , Dudley Juanita , Georg Brianne , Grisby Cathy , Haas Lacey , He Lili , Holland Scott K. , Illapani V. S. Priyanka , Kirker Kristin , Kline‐Fath Beth M. , Li Hailong , Lanier Matt , Merhar Stephanie L. , Muthig Greg , Poindexter Brenda B. , Russell David , Tepe Kari , Tamm Leanne , Thompson Julia , Wang Hui , Wang Jinghua , Williams Brynne , Wineland Kelsey , Wuertz Sandra , Wuest Donna , Yuan Weihong 
Published: January 2024

AbstractPrenatal tobacco smoke exposure (TSE) and prematurity are independent risk factors for abnormal neurodevelopment. The objectives were to compare differences in Bayley-III cognitive, language, and motor scores at 2 years corrected age (CA) in 395 infants born very preterm (≤ 32 weeks gestation) with and without prenatal TSE. We performed multivariable linear regression analyses to examine associations between prenatal TSE and neurodevelopmental outcomes and a mediation analysis to estimate direct effects of prenatal TSE on outcomes and indirect effects through preterm birth. In total, 50 (12.6%) infants had prenatal TSE. Infants with prenatal TSE had lower mean [95% CI] Cognitive score (82.8 [78.6, 87.1]) vs. nonexposed infants (91.7 [90.1, 93.4]). In children with and without prenatal TSE, there were significant differences in mean [95% CI] Language scores (81.7 [76.0, 87.4] vs. 92.4 [90.2, 94.6], respectively) and mean [95% CI] Motor scores (86.5 [82.2, 90.7] vs. 93.4 [91.8, 95.0], respectively); scores remained significant after controlling for confounders. Preterm birth indirectly mediated 9.0% of the total effect of prenatal TSE on Cognitive score (P = NS). However, 91% of the remaining total effect was significant and attributable to TSE’s direct harmful effects on cognitive development (β = − 5.17 [95% CI − 9.97, − 0.38]). The significant association is largely due to TSE’s direct effect on cognitive development and not primarily due to TSE’s indirect effect on preterm birth.
Ion-retention properties of graphene oxide/zinc oxide nanocomposite membranes at various pH and temperature conditions
Authors: Hassanpour Amir , Gauthier Marc A. , Sun Shuhui 
Published: January 2024

AbstractLaminar graphene oxide (GO) is a promising candidate material for next-generation highly water-permeable membranes. Despite extensive research, there is little information known concerning GO's ion-sieving properties at high acidic/basic pH and temperatures. In this study, the ion-blockage properties of the pristine GO and GO/zinc oxide (ZnO) nanocomposite membranes were tested using a non-pressure-driven filtration setup over a wide range of pH and temperatures. The ZnO nanoparticles within the composite membranes were synthesized via the room-temperature oxidation of zinc acetate and zinc acrylate precursors and were uniformly distributed across the composite membrane. It is observed that partially replacing the zinc acetate precursor with zinc acrylate improves the blockage performance of the composite membranes under extreme basic conditions by 42%. Moreover, photocatalytically-reduced composite membranes blocked copper sulfate ions 28% more than as-prepared composite membranes. Further, it was discovered that the composition of the membrane plays a vital role in its ion blockage performance at higher temperatures.
GPU-accelerated lung CT segmentation based on level sets and texture analysis
Authors: Reska Daniel , Kretowski Marek 
Published: January 2024

AbstractThis paper presents a novel semi-automatic method for lung segmentation in thoracic CT datasets. The fully three-dimensional algorithm is based on a level set representation of an active surface and integrates texture features to improve its robustness. The method’s performance is enhanced by the graphics processing unit (GPU) acceleration. The segmentation process starts with a manual initialisation of 2D contours on a few representative slices of the analysed volume. Next, the starting regions for the active surface are generated according to the probability maps of texture features. The active surface is then evolved to give the final segmentation result. The recent implementation employs features based on grey-level co-occurrence matrices and Gabor filters. The algorithm was evaluated on real medical imaging data from the LCTCS 2017 challenge. The results were also compared with the outcomes of other segmentation methods. The proposed approach provided high segmentation accuracy while offering very competitive performance.
A hybrid cloud load balancing and host utilization prediction method using deep learning and optimization techniques
Authors: Simaiya Sarita , Lilhore Umesh Kumar , Sharma Yogesh Kumar , Rao K. B. V. Brahma , Maheswara Rao V. V. R. , Baliyan Anupam , Bijalwan Anchit , Alroobaea Roobaea 
Published: January 2024

AbstractVirtual machine (VM) integration methods have effectively proven an optimized load balancing in cloud data centers. The main challenge with VM integration methods is the trade-off among cost effectiveness, quality of service, performance, optimal resource utilization and compliance with service level agreement violations. Deep Learning methods are widely used in existing research on cloud load balancing. However, there is still a problem with acquiring noisy multilayered fluctuations in workload due to the limited resource-level provisioning. The long short-term memory (LSTM) model plays a vital role in the prediction of server load and workload provisioning. This research presents a hybrid model using deep learning with Particle Swarm Intelligence and Genetic Algorithm (“DPSO-GA”) for dynamic workload provisioning in cloud computing. The proposed model works in two phases. The first phase utilizes a hybrid PSO-GA approach to address the prediction challenge by combining the benefits of these two methods in fine-tuning the Hyperparameters. In the second phase, CNN-LSTM is utilized. Before using the CNN-LSTM approach to forecast the consumption of resources, a hybrid approach, PSO-GA, is used for training it. In the proposed framework, a one-dimensional CNN and LSTM are used to forecast the cloud resource utilization at various subsequent time steps. The LSTM module simulates temporal information that predicts the upcoming VM workload, while a CNN module extracts complicated distinguishing features gathered from VM workload statistics. The proposed model simultaneously integrates the resource utilization in a multi-resource utilization, which helps overcome the load balancing and over-provisioning issues. Comprehensive simulations are carried out utilizing the Google cluster traces benchmarks dataset to verify the efficiency of the proposed DPSO-GA technique in enhancing the distribution of resources and load balancing for the cloud. The proposed model achieves outstanding results in terms of better precision, accuracy and load allocation.
Chemical basis of microbiome preference in the nematode C. elegans
Authors: Chai Victor Z. , Farajzadeh Tiam , Meng Yufei , Lo Sokhna B. , Asaed Tymmaa A. , Taylor Charles J. , Glater Elizabeth E. 
Published: January 2024

AbstractAnimals are exposed to many microbes in their environment, some of which have been shown to colonize various tissues including the intestine. The composition of the intestinal microbiota affects many aspects of the host’s physiology and health. Despite this, very little is known about whether host behavior contributes to the colonization. We approach this question in the nematode C. elegans, which feeds on bacteria and also harbors an intestinal microbiome. We examined the behavior of C. elegans towards CeMbio, a simplified microbiome consisting of twelve strains that represent the bacteria found in the animal’s natural environment. We observed that C. elegans raised on E. coli shows a strong preference for three members of CeMbio (Lelliottia amnigena JUb66, Enterobacter hormaechei CEent1, and Pantoea nemavictus BIGb0393) compared to E. coli. Previously, these three bacterial strains have been shown to support faster C. elegans development time than E. coli OP50 and are low colonizers compared to eight other members of CeMbio. We then used gas chromatography coupled to mass spectrometry to identify that these three bacteria release isoamyl alcohol, a previously described C. elegans chemoattractant. We suggest that C. elegans seeks bacteria that release isoamyl alcohol and support faster growth.
A genome-wide association study of social trust in 33,882 Danish blood donors
Authors: Sequeros Celia Burgos , Hansen Thomas Folkmann , Westergaard David , Louloudis Ioannis , Kalamajski Sebastian , Röder Timo , Rohde Palle Duun , Schwinn Michael , Clemmensen Line Harder , Didriksen Maria , Nyegaard Mette , Hjalgrim Henrik , Nielsen Kaspar René , Bruun Mie Topholm , Ostrowski Sisse Rye , Erikstrup Christian , Mikkelsen Susan , Sørensen Erik ,   DBDS Genomic Consortium, Banasik Karina , Bay Jakob , Boldsen Jens Kjærgaard , Brodersen Thorsten , Brunak Søren , Burgdorf Kristoffer , Chalmer Mona Ameri , Didriksen Maria , Dinh Khoa Manh , Dowsett Joseph , Erikstrup Christian , Feenstra Bjarke , Geller Frank , Gudbjartsson Daniel , Hansen Thomas Folkmann , Hindhede Lotte , Hjalgrim Henrik , Jacobsen Rikke Louise , Jemec Gregor , Jensen Bitten Aagaard , Kaspersen Katrine , Kjerulff Bertram Dalskov , Kogelman Lisette , Larsen Margit Anita Hørup , Louloudis Ioannis , Lundgaard Agnete , Mikkelsen Susan , Mikkelsen Christina , Nissen Ioanna , Nyegaard Mette , Ostrowski Sisse Rye , Pedersen Ole Birger Vestager , Pil Henriksen Alexander , Rohde Palle Duun , Rostgaard Klaus , Schwinn Michael , Stefansson Kari , Stefánsson Hreinn , Sørensen Erik , Thorsteinsdóttir Unnur , Thørner Lise Wegner , Topholm Bruun Mie , Ullum Henrik , Werge Thomas , Westergaard David , Pedersen Ole Birger Vestager , Brunak Søren , Banasik Karina , Giordano Giuseppe Nicola 
Published: January 2024

AbstractSocial trust is a heritable trait that has been linked with physical health and longevity. In this study, we performed genome-wide association studies of self-reported social trust in n = 33,882 Danish blood donors. We observed genome-wide and local evidence of genetic similarity with other brain-related phenotypes and estimated the single nucleotide polymorphism-based heritability of trust to be 6% (95% confidence interval = (2.1, 9.9)). In our discovery cohort (n = 25,819), we identified one significantly associated locus (lead variant: rs12776883) in an intronic enhancer region ofPLPP4, a gene highly expressed in brain, kidneys, and testes. However, we could not replicate the signal in an independent set of donors who were phenotyped a year later (n = 8063). In the subsequent meta-analysis, we found a second significantly associated variant (rs71543507) in an intergenic enhancer region. Overall, our work confirms that social trust is heritable, and provides an initial look into the genetic factors that influence it.