bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonmonotone invasion landscape by noise-aware control of metastasis activator levels
Authors: Wan Yiming , Cohen Joseph , Szenk Mariola , Farquhar Kevin S. , Coraci Damiano , Krzysztoń Rafał , Azukas Joshua , Van Nest Nicholas , Smashnov Alex , Chern Yi-Jye , De Martino Daniela , Nguyen Long Chi , Bien Harold , Bravo-Cordero Jose Javier , Chan Chia-Hsin , Rosner Marsha Rich , Balázsi Gábor 
Published: May 2023

AbstractA major pharmacological assumption is that lowering disease-promoting protein levels is generally beneficial. For example, inhibiting metastasis activator BACH1 is proposed to decrease cancer metastases. Testing such assumptions requires approaches to measure disease phenotypes while precisely adjusting disease-promoting protein levels. Here we developed a two-step strategy to integrate protein-level tuning, noise-aware synthetic gene circuits into a well-defined human genomic safe harbor locus. Unexpectedly, engineered MDA-MB-231 metastatic human breast cancer cells become more, then less and then more invasive as we tune BACH1 levels up, irrespective of the native BACH1. BACH1 expression shifts in invading cells, and expression of BACH1ʼs transcriptional targets confirm BACH1ʼs nonmonotone phenotypic and regulatory effects. Thus, chemical inhibition of BACH1 could have unwanted effects on invasion. Additionally, BACH1ʼs expression variability aids invasion at high BACH1 expression. Overall, precisely engineered, noise-aware protein-level control is necessary and important to unravel disease effects of genes to improve clinical drug efficacy.
Surveying the global landscape of post-transcriptional regulators
Authors: Reynaud Kendra , McGeachy Anna M. , Noble David , Meacham Zuriah A. , Ingolia Nicholas T. 
Published: May 2023

AbstractNumerous proteins regulate gene expression by modulating mRNA translation and decay. To uncover the full scope of these post-transcriptional regulators, we conducted an unbiased survey that quantifies regulatory activity across the budding yeast proteome and delineates the protein domains responsible for these effects. Our approach couples a tethered function assay with quantitative single-cell fluorescence measurements to analyze ~50,000 protein fragments and determine their effects on a tethered mRNA. We characterize hundreds of strong regulators, which are enriched for canonical and unconventional mRNA-binding proteins. Regulatory activity typically maps outside the RNA-binding domains themselves, highlighting a modular architecture that separates mRNA targeting from post-transcriptional regulation. Activity often aligns with intrinsically disordered regions that can interact with other proteins, even in core mRNA translation and degradation factors. Our results thus reveal networks of interacting proteins that control mRNA fate and illuminate the molecular basis for post-transcriptional gene regulation.
Analysis-ready optical underwater images of Manganese-nodule covered seafloor of the Clarion-Clipperton Zone
Authors: Mbani Benson , Greinert Jens 
Published: May 2023

AbstractWe provide a sequence of analysis-ready optical underwater images from the Clarion-Clipperton Zone (CCZ) of the Pacific Ocean. The images were originally recorded using a towed camera sledge that photographed a seabed covered with polymetallic manganese-nodules, at an average water depth of 4,250 meters. The original degradation in visual quality and inconsistent scale among individual raw images due to different altitude implies that they are not scientifically comparable in their original form. Here, we present analysis-ready images that have already been pre-processed to account for this degradation. We also provide accompanying metadata for each image, which includes their geographic coordinates, depth of the seafloor, absolute scale (cm/pixel), and seafloor habitat class obtained from a previous study. The provided images are thus directly usable by the marine scientific community e.g., to train machine learning models for seafloor substrate classification and megafauna detection.
COVID-19 vaccination, risk-compensatory behaviours, and contacts in the UK
Authors: Buckell John , Jones Joel , Matthews Philippa C. , Diamond Sir Ian , Rourke Emma , Studley Ruth , Cook Duncan , Walker Ann Sarah , Pouwels Koen B. ,   the COVID-19 Infection Survey Team, Thomas Tina , Ayoubkhani Daniel , Black Russell , Felton Antonio , Crees Megan , Jones Joel , Lloyd Lina , Sutherland Esther , Pritchard Emma , Vihta Karina-Doris , Doherty George , Kavanagh James , Chau Kevin K. , Hatch Stephanie B. , Ebner Daniel , Ferreira Lucas Martins , Christott Thomas , Dejnirattisai Wanwisa , Mongkolsapaya Juthathip , Cameron Sarah , Tamblin-Hopper Phoebe , Wolna Magda , Brown Rachael , Cornall Richard , Screaton Gavin , Cox Stuart , Paddon Kevin , James Tim , House Thomas , Robotham Julie , Birrell Paul , Jordan Helena , Sheppard Tim , Athey Graham , Moody Dan , Curry Leigh , Brereton Pamela , Jarvis Ian , Godsmark Anna , Morris George , Mallick Bobby , Eeles Phil , Hay Jodie , VanSteenhouse Harper , Lee Jessica , White Sean , Evans Tim , Bloemberg Lisa , Allison Katie , Pandya Anouska , Davis Sophie , Conway David I. , MacLeod Margaret , Cunningham Chris , Lythgoe Katrina , Bonsall David , Golubchik Tanya , Fryer Helen 
Published: May 2023

AbstractThe physiological effects of vaccination against SARS-CoV-2 (COVID-19) are well documented, yet the behavioural effects not well known. Risk compensation suggests that gains in personal safety, as a result of vaccination, are offset by increases in risky behaviour, such as socialising, commuting and working outside the home. This is potentially important because transmission of SARS-CoV-2 is driven by contacts, which could be amplified by vaccine-related risk compensation. Here, we show that behaviours were overall unrelated to personal vaccination, but—adjusting for variation in mitigation policies—were responsive to the level of vaccination in the wider population: individuals in the UK were risk compensating when rates of vaccination were rising. This effect was observed across four nations of the UK, each of which varied policies autonomously.
Simple and efficient differentiation of human iPSCs into contractible skeletal muscles for muscular disease modeling
Authors: Rashid Muhammad Irfanur , Ito Takuji , Miya Fuyuki , Shimojo Daisuke , Arimoto Kanae , Onodera Kazunari , Okada Rina , Nagashima Takunori , Yamamoto Kazuki , Khatun Zohora , Shimul Rayhanul Islam , Niwa Jun-ichi , Katsuno Masahisa , Sobue Gen , Okano Hideyuki , Sakurai Hidetoshi , Shimizu Kazunori , Doyu Manabu , Okada Yohei 
Published: May 2023

AbstractPathophysiological analysis and drug discovery targeting human diseases require disease models that suitably recapitulate patient pathology. Disease-specific human induced pluripotent stem cells (hiPSCs) differentiated into affected cell types can potentially recapitulate disease pathology more accurately than existing disease models. Such successful modeling of muscular diseases requires efficient differentiation of hiPSCs into skeletal muscles. hiPSCs transduced with doxycycline-inducible MYOD1 (MYOD1-hiPSCs) have been widely used; however, they require time- and labor-consuming clonal selection, and clonal variations must be overcome. Moreover, their functionality should be carefully examined. Here, we demonstrated that bulk MYOD1-hiPSCs established with puromycin selection rather than G418 selection showed rapid and highly efficient differentiation. Interestingly, bulk MYOD1-hiPSCs exhibited average differentiation properties of clonally established MYOD1-hiPSCs, suggesting that it is possible to minimize clonal variations. Moreover, disease-specific hiPSCs of spinal bulbar muscular atrophy (SBMA) could be efficiently differentiated via this method into skeletal muscle that showed disease phenotypes, suggesting the applicability of this method for disease analysis. Finally, three-dimensional muscle tissues were fabricated from bulk MYOD1-hiPSCs, which exhibited contractile force upon electrical stimulation, indicating their functionality. Thus, our bulk differentiation requires less time and labor than existing methods, efficiently generates contractible skeletal muscles, and may facilitate the generation of muscular disease models.
Deciphering of seed Health of common food grains (wheat, rice) of North Eastern UP and Gurgaon Haryana, India
Authors: Kumar Narendra , Khurana S. M. Paul , Pandey Vashist N. 
Published: May 2023

AbstractThe stored random samples of food seeds of wheat and rice (60 samples) were purchased from places of Eastern UP and Gurgaon district Haryana. Its moisture contents were estimated. The Mycological investigations of wheat seeds revealed presence of a total number of 16 fungal species viz.,Alternaria alternata,Aspergillus candidus,Aspergillus flavus,A. niger,A. ochraceous,A. phoenicis,A. tamari,A. terreus,A. sydowi,Fusarium moniliforme,F. oxysporum F. solani,P. glabrum,Rhizopus nigricans,Trichoderma virideandTrichothecium roseum.While mycological analysis of rice seeds showed presence of 15 fungal species viz.,Alternaria padwickii,A. oryzae,Curvularia lunata,Fusarium moniliforme,Aspergillus clavatus,A. flavus,A. niger,Cladosporiumsp.,Nigrospora oryzae,Alternaria tenuissima,Chaetomium globosum,F. solani,Microascus cirrosus,Helminthosporium oryzae,Pyricularia grisea. It also projected variation in presence of fungal species in blotter and agar plate method of analysis. In wheat Blotter method of analysis showed 16 fungal species while agar plate depicted 13 fungal species. In rice Agar plate method depicted presence of 15 fungal species while blotter method shows presence of 12 fungal species. The insect analysis revealed that wheat samples were infected withTribolium castaneum. While rice seeds sample showed presence of insectSitophilus oryzae. The investigations revealed thatAspergillus flavus,A. niger,Sitophilus oryzaeandTribolium castaneumcaused reduction in seed weight loss, seed germination, carbohydrate and protein contents of common food grains (wheat, rice). It also revealed that randomly selected A. flavus isolate 1 of wheat showed higher potential of aflatoxin B1production (1392.940 μg/l) while rice isolate 2 showed 1231.117 μg/l production.
Assessing thermal imagery integration into object detection methods on air-based collection platforms
Authors: Gallagher James E. , Oughton Edward J. 
Published: May 2023

AbstractObject detection models commonly focus on utilizing the visible spectrum via Red–Green–Blue (RGB) imagery. Due to various limitations with this approach in low visibility settings, there is growing interest in fusing RGB with thermal Long Wave Infrared (LWIR) (7.5–13.5 µm) images to increase object detection performance. However, we still lack baseline performance metrics evaluating RGB, LWIR and RGB-LWIR fused object detection machine learning models, especially from air-based platforms. This study undertakes such an evaluation, finding that a blended RGB-LWIR model generally exhibits superior performance compared to independent RGB or LWIR approaches. For example, an RGB-LWIR blend only performs 1–5% behind the RGB approach in predictive power across various altitudes and periods of clear visibility. Yet, RGB fusion with a thermal signature overlay provides edge redundancy and edge emphasis, both which are vital in supporting edge detection machine learning algorithms (especially in low visibility environments). This approach has the ability to improve object detection performance for a range of use cases in industrial, consumer, government, and military applications. This research greatly contributes to the study of multispectral object detection by quantifying key factors affecting model performance from drone platforms (including distance, time-of-day and sensor type). Finally, this research additionally contributes a novel open labeled training dataset of 6300 images for RGB, LWIR, and RGB-LWIR fused imagery, collected from air-based platforms, enabling further multispectral machine-driven object detection research.
Clinical analysis of secondary glaucoma in Central China
Authors: Liu Qian , Liu Changgeng , Cheng Wenjun , Feng Xiaomei , Li Haijun , Yang Xiaoyuan , Dong Yangzeng 
Published: May 2023

AbstractTo describe the epidemiology, clinical and social characteristics, management, and outcomes of patients with secondary glaucoma in Central China, a total of 1,129 cases (1,158 eyes) among 710 males (62.89%) and 419 females (37.11%) were analyzed. The mean age was 53.75 ± 17.11 years. The New Rural Cooperative Medical System (NCMS) played the most important role in reimbursement (60.32%) for secondary glaucoma-related medical expenses. The predominant occupation was “farmer” (53.41%). Neovascularization and trauma were the leading causes of secondary glaucoma. Cases of trauma-induced glaucoma decreased substantially during the coronavirus disease 2019 (COVID-19) pandemic. An education level of senior high school or above was uncommon. Ahmed glaucoma valve implantation was the most commonly performed surgery. At the final follow-up, the overall intraocular pressure (IOP) in patients with vascular disease- and trauma-related secondary glaucoma was 19.53 ± 10.20 mmHg, 20.26 ± 11.75 mmHg, and 16.90 ± 6.72 mmHg, while the mean visual acuity (VA) was 0.33 ± 0.32, 0.34 ± 0.36, and 0.43 ± 0.36. In 814 (70.29%) eyes, the VA was < 0.01. Effective preventive measures for at-risk populations, increased NCMS coverage and the promotion of higher education are necessary. These findings will help ophthalmologists detect secondary glaucoma early and manage it in a timely manner.
Learning without forgetting by leveraging transfer learning for detecting COVID-19 infection from CT images
Authors: Subramanian Malliga , Sathishkumar Veerappampalayam Easwaramoorthy , Cho Jaehyuk , Shanmugavadivel Kogilavani 
Published: May 2023

AbstractCOVID-19, a global pandemic, has killed thousands in the last three years. Pathogenic laboratory testing is the gold standard but has a high false-negative rate, making alternate diagnostic procedures necessary to fight against it. Computer Tomography (CT) scans help diagnose and monitor COVID-19, especially in severe cases. But, visual inspection of CT images takes time and effort. In this study, we employ Convolution Neural Network (CNN) to detect coronavirus infection from CT images. The proposed study utilized transfer learning on the three pre-trained deep CNN models, namely VGG-16, ResNet, and wide ResNet, to diagnose and detect COVID-19 infection from the CT images. However, when the pre-trained models are retrained, the model suffers the generalization capability to categorize the data in the original datasets. The novel aspect of this work is the integration of deep CNN architectures with Learning without Forgetting (LwF) to enhance the model’s generalization capabilities on both trained and new data samples. The LwF makes the network use its learning capabilities in training on the new dataset while preserving the original competencies. The deep CNN models with the LwF model are evaluated on original images and CT scans of individuals infected with Delta-variant of the SARS-CoV-2 virus. The experimental results show that of the three fine-tuned CNN models with the LwF method, the wide ResNet model’s performance is superior and effective in classifying original and delta-variant datasets with an accuracy of 93.08% and 92.32%, respectively.
Rab27a-mediated extracellular vesicle secretion contributes to osteogenesis in periodontal ligament-bone niche communication
Authors: Lu Yun , Zhao Liru , Mao Jiaqi , Liu Wen , Ma Wensheng , Zhao Bingjiao 
Published: May 2023

AbstractPeriodontitis, an infectious and common disease worldwide, leads to the destruction of the periodontal ligament-alveolar bone complex. Within the bone metabolic niche, communication between periodontal ligament stem cells (PDLSCs) and bone marrow mesenchymal stem cells (BMMSCs) has been considered a major contributor to osteogenesis. PDLSC-derived extracellular vesicles (P-EVs) have shown great potential for bone regeneration. However, the secretion and uptake mechanisms of P-EVs remain elusive. Herein, the biogenesis of extracellular vesicles (EVs) from PDLSCs was observed using scanning and transmission electron microscopy. PDLSCs were transduced with Ras-associated protein 27a (Rab27a) siRNA (PDLSCsiRab27a) to inhibit EV secretion. The effect of P-EVs on BMMSCs was evaluated using a non-contact transwell co-culture system. We observed that Rab27a knockdown decreased EV secretion, and PDLSCsiRab27a remarkably attenuated co-culture-enhanced osteogenesis of BMMSCs. Isolated PDLSC-derived EVs enhanced osteogenic differentiation of BMMSCs in vitro and induced bone regeneration in a calvarial defect model in vivo. PDLSC-derived EVs were rapidly endocytosed by BMMSCs via the lipid raft/cholesterol endocytosis pathway and triggered the phosphorylation of extracellular signal-regulated kinase 1/2. In conclusion, PDLSCs contribute to the osteogenesis of BMMSCs through Rab27a-mediated EV secretion, thereby providing a potential cell-free approach for bone regeneration.
Time-series analysis of satellite imagery for detecting vegetation cover changes in Indonesia
Authors: Furusawa Takuro , Koera Takuya , Siburian Rikson , Wicaksono Agung , Matsudaira Kazunari , Ishioka Yoshinori 
Published: May 2023

AbstractIndonesia has one of the world’s largest tropical forests; thus, its deforestation and environmental degradation are a global concern. This study is the first to perform comprehensive big data analyses with coherent vegetation criteria to measure the vegetation change at a high temporal resolution (every 16-day period) for 20 years and the high administrative resolution (regency or city) all over Indonesia. The normalized difference vegetation index (NDVI) of the Moderate Resolution Imaging Spectroradiometer is analyzed through state space modeling. The findings reveal that the NDVI increases in almost all regencies, except in urban areas. A high correlation between the NDVI change and the time is observed in Sumatra, Papua, and Kalimantan. The gain of the NDVI values is obvious in the Central and Eastern Java Island. Human activities, such as the expansion of agriculture and forestry and forest conservation policies, are the key factors for the observed pattern.
Compensatory mechanisms of reduced interhemispheric EEG connectivity during sleep in patients with apnea
Authors: Zhuravlev Maksim , Agaltsov Mikhail , Kiselev Anton , Simonyan Margarita , Novikov Mikhail , Selskii Anton , Ukolov Rodion , Drapkina Oksana , Orlova Anna , Penzel Thomas , Runnova Anastasiya 
Published: May 2023

AbstractWe performed a mathematical analysis of functional connectivity in electroencephalography (EEG) of patients with obstructive sleep apnea (OSA) (N = 10; age: 52.8 ± 13 years; median age: 49 years; male/female ratio: 7/3), compared with a group of apparently healthy participants (N = 15; age: 51.5 ± 29.5 years; median age: 42 years; male/female ratio: 8/7), based on the calculation of wavelet bicoherence from nighttime polysomnograms. Having observed the previously known phenomenon of interhemispheric synchronization deterioration, we demonstrated a compensatory increase in intrahemispheric connectivity, as well as a slight increase in the connectivity of the central and occipital areas for high-frequency EEG activity. Significant changes in functional connectivity were extremely stable in groups of apparently healthy participants and OSA patients, maintaining the overall pattern when comparing different recording nights and various sleep stages. The maximum variability of the connectivity was observed at fast oscillatory processes during REM sleep. The possibility of observing some changes in functional connectivity of brain activity in OSA patients in a state of passive wakefulness opens up prospects for further research. Developing the methods of hypnogram evaluation that are independent of functional connectivity may be useful for implementing a medical decision support system.
Simultaneous selection of multiple important single nucleotide polymorphisms in familial genome wide association studies data
Authors: Majumdar Subhabrata , Basu Saonli , McGue Matt , Chatterjee Snigdhansu 
Published: May 2023

AbstractWe propose a resampling-based fast variable selection technique for detecting relevant single nucleotide polymorphisms (SNP) in a multi-marker mixed effect model. Due to computational complexity, current practice primarily involves testing the effect of one SNP at a time, commonly termed as ‘single SNP association analysis’. Joint modeling of genetic variants within a gene or pathway may have better power to detect associated genetic variants, especially the ones with weak effects. In this paper, we propose a computationally efficient model selection approach—based on the e-values framework—for single SNP detection in families while utilizing information on multiple SNPs simultaneously. To overcome computational bottleneck of traditional model selection methods, our method trains one single model, and utilizes a fast and scalable bootstrap procedure. We illustrate through numerical studies that our proposed method is more effective in detecting SNPs associated with a trait than either single-marker analysis using family data or model selection methods that ignore the familial dependency structure. Further, we perform gene-level analysis in Minnesota Center for Twin and Family Research (MCTFR) dataset using our method to detect several SNPs using this that have been implicated to be associated with alcohol consumption.
Cough sound-based estimation of vital capacity via cough peak flow using artificial neural network analysis
Authors: Umayahara Yasutaka , Soh Zu , Furui Akira , Sekikawa Kiyokazu , Imura Takeshi , Otsuka Akira , Tsuji Toshio 
Published: May 2023

AbstractThis study presents a novel approach for estimating vital capacity using cough sounds and proposes a neural network-based model that utilizes the reference vital capacity computed using the lambda-mu-sigma method, a conventional approach, and the cough peak flow computed based on the cough sound pressure level as inputs. Additionally, a simplified cough sound input model is developed, with the cough sound pressure level used directly as the input instead of the computed cough peak flow. A total of 56 samples of cough sounds and vital capacities were collected from 31 young and 25 elderly participants. Model performance was evaluated using squared errors, and statistical tests including the Friedman and Holm tests were conducted to compare the squared errors of the different models. The proposed model achieved a significantly smaller squared error (0.052 L2,p < 0.001) than the other models. Subsequently, the proposed model and the cough sound-based estimation model were used to detect whether a participant’s vital capacity was lower than the typical lower limit. The proposed model demonstrated a significantly higher area under the receiver operating characteristic curve (0.831,p < 0.001) than the other models. These results highlight the effectiveness of the proposed model for screening decreased vital capacity.