bluuebunny/crossref_metadata_2025_split huggingface dataset:
Crackling noise microscopy
Authors: Nguyen Cam-Phu Thi , Schoenherr Peggy , Salje Ekhard K. H. , Seidel Jan 
Published: August 2023

AbstractCrackling noise is a scale-invariant phenomenon found in various driven nonlinear dynamical material systems as a response to external stimuli such as force or external fields. Jerky material movements in the form of avalanches can span many orders of magnitude in size and follow universal scaling rules described by power laws. The concept was originally studied as Barkhausen noise in magnetic materials and now is used in diverse fields from earthquake research and building materials monitoring to fundamental research involving phase transitions and neural networks. Here, we demonstrate a method for nanoscale crackling noise measurements based on AFM nanoindentation, where the AFM probe can be used to study the crackling of individual nanoscale features, a technique we call crackling noise microscopy. The method is successfully applied to investigate the crackling of individual topological defects, i.e. ferroelectric domain walls. We show that critical exponents for avalanches are altered at these nanoscale features, leading to a suppression of mixed-criticality, which is otherwise present in domains. The presented concept opens the possibility of investigating the crackling of individual nanoscale features in a wide range of material systems.
National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations
Authors: Shen Lu , Jacob Daniel J. , Gautam Ritesh , Omara Mark , Scarpelli Tia R. , Lorente Alba , Zavala-Araiza Daniel , Lu Xiao , Chen Zichong , Lin Jintai 
Published: August 2023

AbstractReducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a−1 for oil-gas and 32.7 ± 5.2 Tg a−1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a−1 or 18%.
Genome-wide association studies reveal novel loci associated with pyrethroid and organophosphate resistance in Anopheles gambiae and Anopheles coluzzii
Authors: Lucas Eric R. , Nagi Sanjay C. , Egyir-Yawson Alexander , Essandoh John , Dadzie Samuel , Chabi Joseph , Djogbénou Luc S. , Medjigbodo Adandé A. , Edi Constant V. , Kétoh Guillaume K. , Koudou Benjamin G. , Van’t Hof Arjen E. , Rippon Emily J. , Pipini Dimitra , Harding Nicholas J. , Dyer Naomi A. , Cerdeira Louise T. , Clarkson Chris S. , Kwiatkowski Dominic P. , Miles Alistair , Donnelly Martin J. , Weetman David 
Published: August 2023

AbstractResistance to insecticides in Anopheles mosquitoes threatens the effectiveness of malaria control, but the genetics of resistance are only partially understood. We performed a large scale multi-country genome-wide association study of resistance to two widely used insecticides: deltamethrin and pirimiphos-methyl, using sequencing data from An. gambiae and An. coluzzii from ten locations in West Africa. Resistance was highly multi-genic, multi-allelic and variable between populations. While the strongest and most consistent association with deltamethrin resistance came from Cyp6aa1, this was based on several independent copy number variants (CNVs) in An. coluzzii, and on a non-CNV haplotype in An. gambiae. For pirimiphos-methyl, signals included Ace1, cytochrome P450s, glutathione S-transferases and the nAChR target site of neonicotinoid insecticides. The regions around Cyp9k1 and the Tep family of immune genes showed evidence of cross-resistance to both insecticides. These locally-varying, multi-allelic patterns highlight the challenges involved in genomic monitoring of resistance, and may form the basis for improved surveillance methods.
Comparison of the relative impacts of acute consumption of an inulin-enriched diet, milk kefir or a commercial probiotic product on the human gut microbiome and metabolome
Authors: Walsh Liam H. , Walsh Aaron M. , Garcia-Perez Isabel , Crispie Fiona , Costabile Adele , Ellis Richard , Finlayson Jim , Finnegan Laura A. , Claesson Marcus J. , Holmes Elaine , Cotter Paul D. 
Published: August 2023

AbstractIt has been established that the human gut microbiota is central to health, and, consequently, there has been a growing desire to positively modulate its composition and/or function through, for example, the use of fermented foods, prebiotics or probiotics. Here, we compare the relative impact of the daily consumption of an inulin-enriched diet (n = 10), a commercial probiotic-containing fermented milk product (FMP) (n = 10), or a traditional kefir FMP (n = 9), over a 28-day period on the gut microbiome and urine metabolome of healthy human adults. None of the treatments resulted in significant changes to clinical parameters or biomarkers tested. However, shotgun metagenomic analysis revealed that kefir consumption resulted in a significant change in taxonomy, in the form of an increased abundance of the sub-dominant FMP-associated species Lactococcus raffinolactis, which further corresponded to shifts in the urine metabolome. Overall, our results indicated that daily consumption of a single portion of kefir alone resulted in detectable changes to the gut microbiota and metabolome of consumers.
Release of cognitive and multimodal MRI data including real-world tasks and hippocampal subfield segmentations
Authors: Clark Ian A. , Maguire Eleanor A. 
Published: August 2023

AbstractWe share data from N = 217 healthy adults (mean age 29 years, range 20–41; 109 females, 108 males) who underwent extensive cognitive assessment and neuroimaging to examine the neural basis of individual differences, with a particular focus on a brain structure called the hippocampus. Cognitive data were collected using a wide array of questionnaires, naturalistic tests that examined imagination, autobiographical memory recall and spatial navigation, traditional laboratory-based tests such as recalling word pairs, and comprehensive characterisation of the strategies used to perform the cognitive tests. 3 Tesla MRI data were also acquired and include multi-parameter mapping to examine tissue microstructure, diffusion-weighted MRI, T2-weighted high-resolution partial volume structural MRI scans (with the masks of hippocampal subfields manually segmented from these scans), whole brain resting state functional MRI scans and partial volume high resolution resting state functional MRI scans. This rich dataset will be of value to cognitive and clinical neuroscientists researching individual differences, real-world cognition, brain-behaviour associations, hippocampal subfields and more. All data are freely available on Dryad.
Chromosome-level genome assembly of the caenogastropod snail Rapana venosa
Authors: Song Hao , Li Zhuoqing , Yang Meijie , Shi Pu , Yu Zhenglin , Hu Zhi , Zhou Cong , Hu Pengpeng , Zhang Tao 
Published: August 2023

AbstractThe carnivorous gastropod Rapana venosa (Valenciennes, 1846) is one of the most notorious ecological invaders worldwide. Here, we present the first high-quality chromosome-scale reference R. venosa genome obtained via PacBio sequencing, Illumina paired-end sequencing, and high-throughput chromosome conformation capture scaffolding. The assembled genome has a size of 2.30 Gb, with a scaffold N50 length of 64.63 Mb, and is anchored to 35 chromosomes. It contains 29,649 protein-coding genes, 77.22% of which were functionally annotated. Given its high heterozygosity (1.41%) and large proportion of repeat sequences (57.72%), it is one of the most complex genome assemblies. This chromosome-level genome assembly of R. venosa is an important resource for understanding molluscan evolutionary adaption and provides a genetic basis for its biological invasion control.
L-lysine moderates thermal aggregation of coconut proteins induced by thermal treatment
Authors: Wang Liqiang , Zhang Youbang , Li Run , Xiang Dong 
Published: August 2023

AbstractThis work attempts to investigate the inhibitory effect of L-lysine (Lys) on the thermal aggregation of coconut protein (CP). The results showed that under neutral conditions (pH = 7), temperature reduced the solubility and enhanced the thermally induced gel formation of CP. In addition, Lys reduced the fluorescence properties, particle size and increased the turbidity of CP, which had an inhibitory effect on heat induced gels. The results indicate that Lys plays an important role in inhibiting protein thermal aggregation by interacting with CP to create steric hindrance and increase protein electrostatic repulsion.
The effect of resveratrol, curcumin and quercetin combination on immuno-suppression of tumor microenvironment for breast tumor-bearing mice
Authors: Li Chenchen , Xu Yajun , Zhang Junfeng , Zhang Yuxi , He Wen , Ju Jiale , Wu Yinghua , Wang Yanli 
Published: August 2023

AbstractResveratrol, curcumin, and quercetin are the secondary metabolites from medicinal food homology plants, that have been proven their potency in cancer treatment. However, the antitumor effect of a single component is weak. So, herein, we designed an antitumor compound named RCQ composed of resveratrol, curcumin, and quercetin. This study examined the effect on tumorigenesis and development of 4T1 breast cancer-bearing mice following administering RCQ by intragastric administration. RCQ increased the recruitment of T cells and reduced the accumulation of neutrophils and macrophages in the tumor microenvironment. Meanwhile, RCQ suppressed the development of tumor-infiltrating lymphocytes into immunosuppressive cell subpopulations, including CD4+ T cells to T helper Type 2 type (Th2), tumor-associated neutrophils (TANs) to the N2 TANs, and tumor-associated macrophages (TAMs) cells to M2 TAMs. RCQ reversed the predominance of immunosuppressive infiltrating cells in the tumor microenvironment and tipped the immune balance toward an immune activation state. In vitro the study showed that RCQ significantly increased reactive oxygen species (ROS), reduce mitochondrial membrane potentials in cancer cells, and modulate pro-apoptotic Bcl-2 family members. In conclusion, RCQ can promote the ROS apoptosis mechanism of tumor cells and alleviate immunosuppression of the tumor microenvironment to enhance the anti-tumor effect.
Altered structural hippocampal intra-networks in a general elderly Japanese population with mild cognitive impairment
Authors: Kasai Sera , Watanabe Keita , Umemura Yoshihito , Ishimoto Yuka , Sasaki Miho , Nagaya Haruka , Tatsuo Soichiro , Mikami Tatsuya , Tamada Yoshinori , Ide Satoru , Tomiyama Masahiko , Matsuzaka Masashi , Kakeda Shingo 
Published: August 2023

AbstractAlthough altered networks inside the hippocampus (hippocampal intra-networks) have been observed in dementia, the evaluation of hippocampal intra-networks using magnetic resonance imaging (MRI) is challenging. We employed conventional structural imaging and incident component analysis (ICA) to investigate the structural covariance of the hippocampal intra-networks. We aimed to assess altered hippocampal intra-networks in patients with mild cognitive impairment (MCI). A cross-sectional study of 2122 participants with 3T MRI (median age 69 years, 60.9% female) were divided into 218 patients with MCI and 1904 cognitively normal older adults (CNOA). By employing 3D T1-weighted imaging, voxels within the hippocampus were entered into the ICA analysis to extract the structural covariance intra-networks within the hippocampus. The ICA extracted 16 intra-networks from the hippocampal structural images, which were divided into two bilateral networks and 14 ipsilateral networks. Of the 16 intra-networks, two (one bilateral network and one ipsilateral networks) were significant predictors of MCI from the CNOA after adjusting for age, sex, education, disease history, and hippocampal volume/total intracranial volume ratio. In conclusion, we found that the relationship between hippocampal intra-networks and MCI was independent from the hippocampal volume. Our results suggest that altered hippocampal intra-networks may reflect a different pathology in MCI from that of brain atrophy.
Specific patterns of neural activity in the hippocampus after massed or distributed spatial training
Authors: Centofante Eleonora , Fralleoni Luca , Lupascu Carmen A. , Migliore Michele , Rinaldi Arianna , Mele Andrea 
Published: August 2023

AbstractTraining with long inter-session intervals, termed distributed training, has long been known to be superior to training with short intervals, termed massed training. In the present study we compared c-Fos expression after massed and distributed training protocols in the Morris water maze to outline possible differences in the learning-induced pattern of neural activation in the dorsal CA1 in the two training conditions. The results demonstrate that training and time lags between learning opportunities had an impact on the pattern of neuronal activity in the dorsal CA1. Mice trained with the distributed protocol showed sustained neuronal activity in the postero-distal component of the dorsal CA1. In parallel, in trained mice we found more active cells that tended to constitute spatially restricted clusters, whose degree increased with the increase in the time lags between learning trials. Moreover, activated cell assemblies demonstrated increased stability in their spatial organization after distributed as compared to massed training or control condition. Finally, using a machine learning algorithm we found that differences in the number of c-Fos positive cells and their location in the dorsal CA1 could be predictive of the training protocol used. These results suggest that the topographic organization and the spatial location of learning activated cell assemblies might be critical to promote the increased stability of the memory trace induced by distributed training.
Assessing the effectiveness of camrelizumab plus apatinib versus sorafenib for the treatment of primary liver cancer: a single-center retrospective study
Authors: Chen Dongbo , Wang Yichun , Chen Xiangxun , Kang Mei , Zhu Liyang 
Published: August 2023

AbstractAlthough the effectiveness of camrelizumab plus apatinib has been confirmed in a phase II clinical study, the efficacy of camrelizumab plus apatinib versus sorafenib for primary liver cancer (PLC) remains unverified. We retrospectively collected the data of 143 patients with PLC who received camrelizumab plus apatinib or sorafenib as the first-line treatment at The First Affiliated Hospital of Anhui Medical University from April 2018 to November 2021. Of these, 71 patients received an intravenous injection of camrelizumab 200 mg (body weight ≥ 50 kg) or 3 mg/kg (body weight < 50 kg) followed by an oral dosage of apatinib 250 mg/day every 3 weeks and 72 patients received sorafenib 400 mg orally, twice a day in 28-day cycles. The primary outcomes were overall survival and progression-free survival. The secondary outcomes were objective response rate, disease control rate, and safety. The median median progression-free survival and median overall survival with camrelizumab plus apatinib and sorafenib were 6.0 (95% confidence interval (CI) 4.2–7.8) and 3.0 months (95% CI 2.3–3.7) and 19.0 (95% CI 16.4–21.6) and 12.0 months (95% CI 8.9–15.1), respectively (death hazard ratio: 0.61, P = 0.023). Grade 3/4 treatment-related adverse events were noted in 50 (70.4%) patients in the camrelizumab plus apatinib group and 19 (26.4%) patients in the sorafenib group. Two treatment-related deaths were recorded. Clinically significant improvements were observed in overall survival and progression-free survival with camrelizumab plus apatinib versus sorafenib. Although the side effects of camrelizumab plus apatinib are relatively high, they can be controlled.
Development and validation of a sleep questionnaire, SNoRE 3.0, to evaluate sleep in companion dogs
Authors: Mondino A. , Ludwig C. , Menchaca C. , Russell K. , Simon K. E. , Griffith E. , Kis A. , Lascelles B. D. X. , Gruen M. E. , Olby N. J. 
Published: August 2023

AbstractDisturbances in the sleep–wake cycle are a debilitating, yet rather common condition not only in humans, but also in family dogs. While there is an emerging need for easy-to-use tools to document sleep alterations (in order to ultimately treat and/or prevent them), the veterinary tools which yield objective data (e.g. polysomnography, activity monitors) are both labor intensive and expensive. In this study, we developed a modified version of a previously used sleep questionnaire (SNoRE) and determined criterion validity in companion dogs against polysomnography and physical activity monitors (PAMs). Since a negative correlation between sleep time and cognitive performance in senior dogs has been demonstrated, we evaluated the correlation between the SNoRE scores and the Canine Dementia Scale (CADES, which includes a factor concerning sleep). There was a significant correlation between SNoRE 3.0 questionnaire scores and polysomnography data (latency to NREM sleep, ρ = 0.507, p < 0.001) as well as PAMs’ data (activity between 1:00 and 3:00 AM, p < 0.05). There was a moderate positive correlation between the SNoRE 3.0 scores and the CADES scores (ρ = 0.625, p < 0.001). Additionally, the questionnaire structure was validated by a confirmatory factor analysis, and it also showed an adequate test–retest reliability. In conclusion the present paper describes a valid and reliable questionnaire tool, that can be used as a cost-effective way to monitor dog sleep in clinical settings.
A comparison of the infant gut microbiome before versus after the start of the covid-19 pandemic
Authors: Querdasi Francesca R. , Vogel Sarah C. , Thomason Moriah E. , Callaghan Bridget L. , Brito Natalie H. 
Published: August 2023

AbstractThe COVID-19 pandemic and resulting public health directives led to many changes in families’ social and material environments. Prior research suggests that these changes are likely to impact composition of the gut microbiome, particularly during early childhood when the gut microbiome is developing most rapidly. Importantly, disruption to the gut microbiome during this sensitive period can have potentially long-lasting impacts on health and development. In the current study, we compare gut microbiome composition among a socioeconomically and racially diverse group of 12-month old infants living in New York City who provided stool samples before the pandemic (N = 34) to a group who provided samples during the first 9-months of the pandemic (March–December 2020; N = 20). We found that infants sampled during the pandemic had lower alpha diversity of the microbiome, lower abundance of Pasteurellaceae and Haemophilus, and significantly different beta diversity based on unweighted Unifrac distance than infants sampled before the pandemic. Exploratory analyses suggest that gut microbiome changes due to the pandemic occurred relatively quickly after the start of the pandemic and were sustained. Our results provide evidence that pandemic-related environmental disruptions had an impact on community-level taxonomic diversity of the developing gut microbiome, as well as abundance of specific members of the gut bacterial community.
Analysis of whiB7 in Mycobacterium tuberculosis reveals novel AT-hook deletion mutations
Authors: Davies-Bolorunduro Olabisi Flora , Jaemsai Bharkbhoom , Ruangchai Wuthiwat , Phumiphanjarphak Worakorn , Aiewsakun Pakorn , Palittapongarnpim Prasit 
Published: August 2023

AbstractMutations in whiB7 have been associated with both hypersusceptibility and resistance to various antibiotics in Mycobacterium tuberculosis (Mtb). Unlocking the secrets of antibiotic resistance in the bacterium, we examined mutations in the coding sequences of whiB7 of over 40,000 diverse Mtb isolates. Our results unveil the dominant c.191delG (Gly64delG) mutation, present in all members of the lineage L1.2.2 and its impact on WhiB7's conserved GVWGG-motif, causing conformational changes and deletion of the C-terminal AT-hook. Excitingly, we discovered six unique mutations associated with partial or total deletion of the AT-hook, specific to certain sublineages. Our findings suggest the selective pressures driving these mutations, underlining the potential of genomics to advance our understanding of Mtb's antibiotic resistance. As tuberculosis remains a global health threat, our study offers valuable insights into the diverse nature and functional consequences of whiB7 mutations, paving the way for the development of novel therapeutic interventions.
Two sequence- and two structure-based ML models have learned different aspects of protein biochemistry
Authors: Kulikova Anastasiya V. , Diaz Daniel J. , Chen Tianlong , Cole T. Jeffrey , Ellington Andrew D. , Wilke Claus O. 
Published: August 2023

AbstractDeep learning models are seeing increased use as methods to predict mutational effects or allowed mutations in proteins. The models commonly used for these purposes include large language models (LLMs) and 3D Convolutional Neural Networks (CNNs). These two model types have very different architectures and are commonly trained on different representations of proteins. LLMs make use of the transformer architecture and are trained purely on protein sequences whereas 3D CNNs are trained on voxelized representations of local protein structure. While comparable overall prediction accuracies have been reported for both types of models, it is not known to what extent these models make comparable specific predictions and/or generalize protein biochemistry in similar ways. Here, we perform a systematic comparison of two LLMs and two structure-based models (CNNs) and show that the different model types have distinct strengths and weaknesses. The overall prediction accuracies are largely uncorrelated between the sequence- and structure-based models. Overall, the two structure-based models are better at predicting buried aliphatic and hydrophobic residues whereas the two LLMs are better at predicting solvent-exposed polar and charged amino acids. Finally, we find that a combined model that takes the individual model predictions as input can leverage these individual model strengths and results in significantly improved overall prediction accuracy.