bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-dimensional flat Landau levels in an inhomogeneous acoustic crystal
Authors: Cheng Zheyu , Guan Yi-Jun , Xue Haoran , Ge Yong , Jia Ding , Long Yang , Yuan Shou-Qi , Sun Hong-Xiang , Chong Yidong , Zhang Baile 
Published: March 2024

AbstractWhen electrons moving in two dimensions (2D) are subjected to a strong uniform magnetic field, they form flat bands called Landau levels (LLs). LLs can also arise from pseudomagnetic fields (PMFs) induced by lattice distortions. In three-dimensional (3D) systems, there has been no experimental demonstration of LLs as a type of flat band thus far. Here, we report the experimental realization of a flat 3D LL in an acoustic crystal. Starting from a lattice whose bandstructure exhibits a nodal ring, we design an inhomogeneous distortion corresponding to a specific pseudomagnetic vector potential (PVP). This distortion causes the nodal ring states to break up into LLs, including a zeroth LL that is flat along all three directions. These findings suggest the possibility of using nodal ring materials to generate 3D flat bands, allowing access to strong interactions and other attractive physical regimes in 3D.
Quantifying how single dose Ad26.COV2.S vaccine efficacy depends on Spike sequence features
Authors: Magaret Craig A. , Li Li , deCamp Allan C. , Rolland Morgane , Juraska Michal , Williamson Brian D. , Ludwig James , Molitor Cindy , Benkeser David , Luedtke Alex , Simpkins Brian , Heng Fei , Sun Yanqing , Carpp Lindsay N. , Bai Hongjun , Dearlove Bethany L. , Giorgi Elena E. , Jongeneelen Mandy , Brandenburg Boerries , McCallum Matthew , Bowen John E. , Veesler David , Sadoff Jerald , Gray Glenda E. , Roels Sanne , Vandebosch An , Stieh Daniel J. , Le Gars Mathieu , Vingerhoets Johan , Grinsztejn Beatriz , Goepfert Paul A. , de Sousa Leonardo Paiva , Silva Mayara Secco Torres , Casapia Martin , Losso Marcelo H. , Little Susan J. , Gaur Aditya , Bekker Linda-Gail , Garrett Nigel , Truyers Carla , Van Dromme Ilse , Swann Edith , Marovich Mary A. , Follmann Dean , Neuzil Kathleen M. , Corey Lawrence , Greninger Alexander L. , Roychoudhury Pavitra , Hyrien Ollivier , Gilbert Peter B. 
Published: March 2024

AbstractIn the ENSEMBLE randomized, placebo-controlled phase 3 trial (NCT04505722), estimated single-dose Ad26.COV2.S vaccine efficacy (VE) was 56% against moderate to severe–critical COVID-19. SARS-CoV-2 Spike sequences were determined from 484 vaccine and 1,067 placebo recipients who acquired COVID-19. In this set of prespecified analyses, we show that in Latin America, VE was significantly lower against Lambda vs. Reference and against Lambda vs. non-Lambda [family-wise error rate (FWER) p < 0.05]. VE differed by residue match vs. mismatch to the vaccine-insert at 16 amino acid positions (4 FWER p < 0.05; 12 q-value ≤ 0.20); significantly decreased with physicochemical-weighted Hamming distance to the vaccine-strain sequence for Spike, receptor-binding domain, N-terminal domain, and S1 (FWER p < 0.001); differed (FWER ≤ 0.05) by distance to the vaccine strain measured by 9 antibody-epitope escape scores and 4 NTD neutralization-impacting features; and decreased (p = 0.011) with neutralization resistance level to vaccinee sera. VE against severe–critical COVID-19 was stable across most sequence features but lower against the most distant viruses.
YTHDF2 governs muscle size through a targeted modulation of proteostasis
Authors: Gilbert Christopher J. , Rabolli Charles P. , Golubeva Volha A. , Sattler Kristina M. , Wang Meifang , Ketabforoush Arsh , Arnold W. David , Lepper Christoph , Accornero Federica 
Published: March 2024

AbstractThe regulation of proteostasis is fundamental for maintenance of muscle mass and function. Activation of the TGF-β pathway drives wasting and premature aging by favoring the proteasomal degradation of structural muscle proteins. Yet, how this critical post-translational mechanism is kept in check to preserve muscle health remains unclear. Here, we reveal the molecular link between the post-transcriptional regulation of m6A-modified mRNA and the modulation of SMAD-dependent TGF-β signaling. We show that the m6A-binding protein YTHDF2 is essential to determining postnatal muscle size. Indeed, muscle-specific genetic deletion of YTHDF2 impairs skeletal muscle growth and abrogates the response to hypertrophic stimuli. We report that YTHDF2 controls the mRNA stability of the ubiquitin ligase ASB2 with consequences on anti-growth gene program activation through SMAD3. Our study identifies a post-transcriptional to post-translational mechanism for the coordination of gene expression in muscle.
Lipoarabinomannan mediates localized cell wall integrity during division in mycobacteria
Authors: Sparks Ian L. , Kado Takehiro , Prithviraj Malavika , Nijjer Japinder , Yan Jing , Morita Yasu S. 
Published: March 2024

AbstractThe growth and division of mycobacteria, which include clinically relevant pathogens, deviate from that of canonical bacterial models. Despite their Gram-positive ancestry, mycobacteria synthesize and elongate a diderm envelope asymmetrically from the poles, with the old pole elongating more robustly than the new pole. The phosphatidylinositol-anchored lipoglycans lipomannan (LM) and lipoarabinomannan (LAM) are cell envelope components critical for host-pathogen interactions, but their physiological functions in mycobacteria remained elusive. In this work, using biosynthetic mutants of these lipoglycans, we examine their roles in maintaining cell envelope integrity in Mycobacterium smegmatis and Mycobacterium tuberculosis. We find that mutants defective in producing mature LAM fail to maintain rod cell shape specifically at the new pole and para-septal regions whereas a mutant that produces a larger LAM becomes multi-septated. Therefore, LAM plays critical and distinct roles at subcellular locations associated with division in mycobacteria, including maintenance of local cell wall integrity and septal placement.
A framework for tracing timber following the Ukraine invasion
Authors: Mortier Thomas , Truszkowski Jakub , Norman Marigold , Boner Markus , Buliga Bogdan , Chater Caspar , Jennings Henry , Saunders Jade , Sibley Rosie , Antonelli Alexandre , Waegeman Willem , Deklerck Victor 
Published: March 2024

AbstractScientific testing including stable isotope ratio analysis (SIRA) and trace element analysis (TEA) is critical for establishing plant origin, tackling deforestation and enforcing economic sanctions. Yet methods combining SIRA and TEA into robust models for origin verification and determination are lacking. Here we report a (1) large Eastern European timber reference database (Betula, Fagus, Pinus, Quercus) tailored to sanctioned products following the Ukraine invasion; (2) statistical test to verify samples against a claimed origin; (3) probabilistic model of SIRA, TEA and genus distribution data, using Gaussian processes, to determine timber harvest location. Our verification method rejects 40–60% of simulated false claims, depending on the spatial scale of the claim, and maintains a low probability of rejecting correct origin claims. Our determination method predicts harvest location within 180 to 230 km of true location. Our results showcase the power of combining data types with probabilistic modelling to identify and scrutinize timber harvest location claims.
Demographic, health, physical activity, and workplace factors are associated with lower healthy working life expectancy and life expectancy at age 50
Authors: Lynch Marty , Bucknall Milica , Jagger Carol , Kingston Andrew , Wilkie Ross 
Published: March 2024

AbstractAlthough retirement ages are rising in the United Kingdom and other countries, the average number of years people in England can expect to spend both healthy and work from age 50 (Healthy Working Life Expectancy; HWLE) is less than the number of years to the State Pension age. This study aimed to estimate HWLE with the presence and absence of selected health, socio-demographic, physical activity, and workplace factors relevant to stakeholders focusing on improving work participation. Data from 11,540 adults in the English Longitudinal Study of Ageing were analysed using a continuous time 3-state multi-state model. Age-adjusted hazard rate ratios (aHRR) were estimated for transitions between health and work states associated with individual and combinations of health, socio-demographic, and workplace factors. HWLE from age 50 was 3.3 years fewer on average for people with pain interference (6.54 years with 95% confidence interval [6.07, 7.01]) compared to those without (9.79 [9.50, 10.08]). Osteoarthritis and mental health problems were associated with 2.2 and 2.9 fewer healthy working years respectively (HWLE for people without osteoarthritis: 9.50 years [9.22, 9.79]; HWLE with osteoarthritis: 7.29 years [6.20, 8.39]; HWLE without mental health problems: 9.76 years [9.48, 10.05]; HWLE with mental health problems: 6.87 years [1.58, 12.15]). Obesity and physical inactivity were associated with 0.9 and 2.0 fewer healthy working years respectively (HWLE without obesity: 9.31 years [9.01, 9.62]; HWLE with obesity: 8.44 years [8.02, 8.86]; HWLE without physical inactivity: 9.62 years [9.32, 9.91]; HWLE with physical inactivity: 7.67 years [7.23, 8.12]). Workers without autonomy at work or with inadequate support at work were expected to lose 1.8 and 1.7 years respectively in work with good health from age 50 (HWLE for workers with autonomy: 9.50 years [9.20, 9.79]; HWLE for workers lacking autonomy: 7.67 years [7.22, 8.12]; HWLE for workers with support: 9.52 years [9.22, 9.82]; HWLE for workers with inadequate support: 7.86 years [7.22, 8.12]). This study identified demographic, health, physical activity, and workplace factors associated with lower HWLE and life expectancy at age 50. Identifying the extent of the impact on healthy working life highlights these factors as targets and the potential to mitigate against premature work exit is encouraging to policy-makers seeking to extend working life as well as people with musculoskeletal and mental health conditions and their employers. The HWLE gaps suggest that interventions are needed to promote the health, wellbeing and work outcomes of subpopulations with long-term health conditions.
Population genetics of the critically endangered three-striped turtle, Batagur dhongoka, from the Ganga river system using mitochondrial DNA and microsatellite analysis
Authors: Kumar Ajit , Panda Ashish Kumar , Usmani Aftab Alam , Yadav Prabhaker , Panwar Anshu , Badola Ruchi , Hussain Syed Ainul , Gupta Sandeep Kumar 
Published: March 2024

AbstractThe three-striped roofed (Batagur dhongoka) is a semi-aquatic turtle that belongs to family Geoemydidae. Due to anthropogenic pressure, it has been facing an intense decline of over 80% in its distribution range in the past 50 years. It is considered as 'Critically Endangered' so effective conservation strategies are needed to protect the species by determining their genetic diversity and population genetic structure. This study investigates the genetic diversity, population structure and demographic pattern of B. dhongoka from two Turtle Rescue and Rehabilitation Centre established near Ganga river using mitochondrial cytochrome b (Cyt b: 1140 bp) ; control region (CR: 451 bp) and ten nuclear microsatellite loci. mtDNA results show low levels of nucleotide diversity (π = 0.0022) in B. dhongoka haplotypes and provide evidence for a low substitution rate. The demographic pattern estimated by the Bayesian skyline plot (BSP) analysis indicates historical stability followed by growth in the effective population size, with a recent reduction in population size from ~ 2 thousand years ago. The microsatellite findings show a moderate level of observed heterozygosity (Ho: 0.49). Bayesian-based clustering analysis revealed weak genetic structures in B. dhongoka and presence of admixed assignations suggesting close genetic relationships. These findings shed light on B. dhongoka's genetic status and underline the necessity of comprehensive rehabilitation and relocation programs and conservation and management techniques to ensure the species' long-term survival. In order to ensure the effective protection and conservation of B. dhongoka, the Government of India has taken a proactive measure by incorporating it into Schedule I of the Wildlife (Protection) Act, 1972, as amended in 2022.
Comprehensive study reveals phenotypic heterogeneity in Klebsiella pneumoniae species complex isolates
Authors: Rodríguez-Medina Nadia , Rodríguez-Santiago Jonathan , Alvarado-Delgado Alejandro , Sagal-Prado Alan , Silva-Sánchez Jesús , De la Cruz Miguel A. , Ares Miguel Angel , Sánchez-Arias Margarita , Morfín-Otero Rayo , Hernández-Castro Rigoberto , Cornejo-Juárez Patricia , Jiménez-Villanueva Emmanuel , Sánchez-Francia Domingo , Garza-Ramos Ulises 
Published: March 2024

AbstractHere, we conducted a comprehensive analysis of 356 Klebsiella pneumoniae species complex (KpSC) isolates that were classified as classical (cl), presumptive hypervirulent (p-hv) and hypermucoviscous-like (hmv-like). Overall, K. pneumoniae (82.3%), K. variicola (2.5%) and K. quasipneumoniae (2.5%) were identified. These isolates comprised 321 cl-KpSC, 7 p-hv-KpSC and 18 hmv-like-KpSC. A large proportion of cl-KpSC isolates were extended-spectrum-β-lactamases (ESBLs)-producers (64.4%) and 3.4% of isolates were colistin-resistant carrying carbapenemase and ESBL genes. All p-hv-KpSC showed an antibiotic susceptible phenotype and hmv-like isolates were found to be ESBL-producers (8/18). Assays for capsule production and capsule-dependent virulence phenotypes and whole-genome sequencing (WGS) were performed in a subset of isolates. Capsule amount differed in all p-hv strains and hmv-like produced higher capsule amounts than cl strains; these variations had important implications in phagocytosis and virulence. Murine sepsis model showed that most cl strains were nonlethal and the hmv-like caused 100% mortality with 3 × 108 CFUs. Unexpectedly, 3/7 (42.9%) of p-hv strains required 108 CFUs to cause 100% mortality (atypical hypervirulent), and 4/7 (57.1%) strains were considered truly hypervirulent (hv). Genomic analyses confirmed the diverse population, including isolates belonging to hv clonal groups (CG) CG23, CG86, CG380 and CG25 (this corresponded to the ST3999 a novel hv clone) and MDR clones such as CG258 and CG147 (ST392) among others. We noted that the hmv-like and hv-ST3999 isolates showed a close phylogenetic relationship with cl-MDR K. pneumoniae. The information collected here is important to understand the evolution of clinically important phenotypes such as hypervirulent and ESBL-producing-hypermucoviscous-like amongst the KpSC in Mexican healthcare settings. Likewise, this study shows that mgrB inactivation is the main mechanism of colistin resistance in K. pneumoniae isolates from Mexico.
Global multi-hazard risk assessment in a changing climate
Authors: Stalhandske Zélie , Steinmann Carmen B. , Meiler Simona , Sauer Inga J. , Vogt Thomas , Bresch David N. , Kropf Chahan M. 
Published: March 2024

AbstractNatural hazards pose significant risks to people and assets in many regions of the world. Quantifying associated risks is crucial for many applications such as adaptation option appraisal and insurance pricing. However, traditional risk assessment approaches have focused on the impacts of single hazards, ignoring the effects of multi-hazard risks and potentially leading to underestimations or overestimations of risks. In this work, we present a framework for modelling multi-hazard risks globally in a consistent way, considering hazards, exposures, vulnerabilities, and assumptions on recovery. We illustrate the approach using river floods and tropical cyclones impacting people and physical assets on a global scale in a changing climate. To ensure physical consistency, we combine single hazard models that were driven by the same climate model realizations. Our results show that incorporating common physical drivers and recovery considerably alters the multi-hazard risk. We finally demonstrate how our framework can accommodate more than two hazards and integrate diverse assumptions about recovery processes based on a national case study. This framework is implemented in the open-source climate risk assessment platform CLIMADA and can be applied to various hazards and exposures, providing a more comprehensive approach to risk management than conventional methods.
AMENet is a monocular depth estimation network designed for automatic stereoscopic display
Authors: Wu Tianzhao , Xia Zhongyi , Zhou Man , Kong Ling Bing , Chen Zengyuan 
Published: March 2024

AbstractMonocular depth estimation has a wide range of applications in the field of autostereoscopic displays, while accuracy and robustness in complex scenes are still a challenge. In this paper, we propose a depth estimation network for autostereoscopic displays, which aims at improving the accuracy of monocular depth estimation by fusing Vision Transformer (ViT) and Convolutional Neural Network (CNN). Our approach feeds the input image as a sequence of visual features into the ViT module and utilizes its global perception capability to extract high-level semantic features of the image. The relationship between the losses is quantified by adding a weight correction module to improve robustness of the model. Experimental evaluation results on several public datasets show that AMENet exhibits higher accuracy and robustness than existing methods in different scenarios and complex conditions. In addition, a detailed experimental analysis was conducted to verify the effectiveness and stability of our method. The accuracy improvement on the KITTI dataset compared to the baseline method is 4.4%. In summary, AMENet is a promising depth estimation method with sufficient high robustness and accuracy for monocular depth estimation tasks.
Generalizable disease detection using model ensemble on chest X-ray images
Authors: Abad Maider , Casas-Roma Jordi , Prados Ferran 
Published: March 2024

AbstractIn the realm of healthcare, the demand for swift and precise diagnostic tools has been steadily increasing. This study delves into a comprehensive performance analysis of three pre-trained convolutional neural network (CNN) architectures: ResNet50, DenseNet121, and Inception-ResNet-v2. To ensure the broad applicability of our approach, we curated a large-scale dataset comprising a diverse collection of chest X-ray images, that included both positive and negative cases of COVID-19. The models’ performance was evaluated using separate datasets for internal validation (from the same source as the training images) and external validation (from different sources). Our examination uncovered a significant drop in network efficacy, registering a 10.66% reduction for ResNet50, a 36.33% decline for DenseNet121, and a 19.55% decrease for Inception-ResNet-v2 in terms of accuracy. Best results were obtained with DenseNet121 achieving the highest accuracy at 96.71% in internal validation and Inception-ResNet-v2 attaining 76.70% accuracy in external validation. Furthermore, we introduced a model ensemble approach aimed at improving network performance when making inferences on images from diverse sources beyond their training data. The proposed method uses uncertainty-based weighting by calculating the entropy in order to assign appropriate weights to the outputs of each network. Our results showcase the effectiveness of the ensemble method in enhancing accuracy up to 97.38% for internal validation and 81.18% for external validation, while maintaining a balanced ability to detect both positive and negative cases.
HSPA9 reduction exacerbates symptoms and cell death in DSS-Induced inflammatory colitis
Authors: Jang Soyoung , Jang Soyeon , Ko Jiwon , Bae Ji-Eun , Hyung Hyejin , Park Ji Yeong , Lim Su-Geun , Park Sijun , Park Song , Yi Junkoo , Kim Seonggon , Kim Myoung Ok , Cho Dong-Hyung , Ryoo Zae Young 
Published: March 2024

AbstractInflammatory bowel disease (IBD) is a chronic inflammatory condition that is influenced by various factors, including environmental factors, immune responses, and genetic elements. Among the factors that influence IBD progression, macrophages play a significant role in generating inflammatory mediators, and an increase in the number of activated macrophages contributes to cellular damage, thereby exacerbating the overall inflammatory conditions. HSPA9, a member of the heat shock protein 70 family, plays a crucial role in regulating mitochondrial processes and responding to oxidative stress. HSPA9 deficiency disrupts mitochondrial dynamics, increasing mitochondrial fission and the production of reactive oxygen species. Based on the known functions of HSPA9, we considered the possibility that HSPA9 reduction may contribute to the exacerbation of colitis and investigated its relevance. In a dextran sodium sulfate-induced colitis mouse model, the downregulated HSPA9 exacerbates colitis symptoms, including increased immune cell infiltration, elevated proinflammatory cytokines, decreased tight junctions, and altered macrophage polarization. Moreover, along with the increased mitochondrial fission, we found that the reduction in HSPA9 significantly affected the superoxide dismutase 1 levels and contributed to cellular death. These findings enhance our understanding of the intricate mechanisms underlying colitis and contribute to the development of novel therapeutic approaches for this challenging condition.
Prediction of neovascular age-related macular degeneration recurrence using optical coherence tomography images with a deep neural network
Authors: Jung Juho , Han Jinyoung , Han Jeong Mo , Ko Junseo , Yoon Jeewoo , Hwang Joon Seo , Park Ji In , Hwang Gyudeok , Jung Jae Ho , Hwang Daniel Duck-Jin 
Published: March 2024

AbstractNeovascular age-related macular degeneration (nAMD) can result in blindness if left untreated, and patients often require repeated anti-vascular endothelial growth factor injections. Although, the treat-and-extend method is becoming popular to reduce vision loss attributed to recurrence, it may pose a risk of overtreatment. This study aimed to develop a deep learning model based on DenseNet201 to predict nAMD recurrence within 3 months after confirming dry-up 1 month following three loading injections in treatment-naïve patients. A dataset of 1076 spectral domain optical coherence tomography (OCT) images from 269 patients diagnosed with nAMD was used. The performance of the model was compared with that of 6 ophthalmologists, using 100 randomly selected samples. The DenseNet201-based model achieved 53.0% accuracy in predicting nAMD recurrence using a single pre-injection image and 60.2% accuracy after viewing all the images immediately after the 1st, 2nd, and 3rd injections. The model outperformed experienced ophthalmologists, with an average accuracy of 52.17% using a single pre-injection image and 53.3% after examining four images before and after three loading injections. In conclusion, the artificial intelligence model demonstrated a promising ability to predict nAMD recurrence using OCT images and outperformed experienced ophthalmologists. These findings suggest that deep learning models can assist in nAMD recurrence prediction, thus improving patient outcomes and optimizing treatment strategies.