bluuebunny/crossref_metadata_2025_split huggingface dataset:
A prognostic risk score for development and spread of chronic pain
Authors: Tanguay-Sabourin Christophe , Fillingim Matt , Guglietti Gianluca V. , Zare Azin , Parisien Marc , Norman Jax , Sweatman Hilary , Da-ano Ronrick , Heikkala Eveliina ,   PREVENT-AD Research Group, Breitner John C. S. , Menes Julien , Poirier Judes , Tremblay-Mercier Jennifer , Perez Jordi , Karppinen Jaro , Villeneuve Sylvia , Thompson Scott J. , Martel Marc O. , Roy Mathieu , Diatchenko Luda , Vachon-Presseau Etienne 
Published: July 2023

AbstractChronic pain is a complex condition influenced by a combination of biological, psychological and social factors. Using data from the UK Biobank (n = 493,211), we showed that pain spreads from proximal to distal sites and developed a biopsychosocial model that predicted the number of coexisting pain sites. This data-driven model was used to identify a risk score that classified various chronic pain conditions (area under the curve (AUC) 0.70–0.88) and pain-related medical conditions (AUC 0.67–0.86). In longitudinal analyses, the risk score predicted the development of widespread chronic pain, the spreading of chronic pain across body sites and high-impact pain about 9 years later (AUC 0.68–0.78). Key risk factors included sleeplessness, feeling ‘fed-up’, tiredness, stressful life events and a body mass index >30. A simplified version of this score, named the risk of pain spreading, obtained similar predictive performance based on six simple questions with binarized answers. The risk of pain spreading was then validated in the Northern Finland Birth Cohort (n = 5,525) and the PREVENT-AD cohort (n = 178), obtaining comparable predictive performance. Our findings show that chronic pain conditions can be predicted from a common set of biopsychosocial factors, which can aid in tailoring research protocols, optimizing patient randomization in clinical trials and improving pain management.
Dataset of annual metal scrap circularity of titanium industry in China from 2005 to 2020
Authors: Wang Wenhao , Wu Fuzhong 
Published: July 2023

AbstractTitanium products, regarded as a strategic metal by many national governments, play important and irreplaceable roles in national defence and military applications. China has built a large-scale titanium industrial chain, and its status and development pathways will greatly affect the global market. Several researchers contributed a set of reliable statistical data to bridge the knowledge gap in evaluating the industrial layout and the entire structure of China’s titanium industry with little literature information regarding the management of metal scrap in the manufacturers of titanium products. To bridge this data gap, we present a dataset of annual metal scrap circularity to uncover China’s evolution of the titanium industry today, which contains off-grade titanium sponge, low-grade titanium scrap, and recycled high-grade titanium swarf with the relevant circularity of the titanium industry in China at the national level from 2005 to 2020.
Decoding numeracy and literacy in the human brain: insights from MEG and MVPA
Authors: Nara Sanjeev , Raza Haider , Carreiras Manuel , Molinaro Nicola 
Published: July 2023

AbstractNumbers and letters are the fundamental building blocks of our everyday social interactions. Previous studies have focused on determining the cortical pathways shaped by numeracy and literacy in the human brain, partially supporting the hypothesis of distinct perceptual neural circuits involved in the visual processing of the two categories. In this study, we aim to investigate the temporal dynamics for number and letter processing. We present magnetoencephalography (MEG) data from two experiments (N = 25 each). In the first experiment, single numbers, letters, and their respective false fonts (false numbers and false letters) were presented, whereas, in the second experiment, numbers, letters, and their respective false fonts were presented as a string of characters. We used multivariate pattern analysis techniques (time-resolved decoding and temporal generalization), testing the strong hypothesis that the neural correlates supporting letter and number processing can be logistically classified as categorically separate. Our results show a very early dissociation (~ 100 ms) between numbers, and letters when compared to false fonts. Number processing can be dissociated with similar accuracy when presented as isolated items or strings of characters, while letter processing shows dissociable classification accuracy for single items compared to strings. These findings reinforce the evidence indicating that early visual processing can be differently shaped by the experience with numbers and letters; this dissociation is stronger for strings compared to single items, thus showing that combinatorial mechanisms for numbers and letters could be categorically distinguished and influence early visual processing.
Incidence rate, risk factors, and bacterial causes of clinical mastitis on dairy farms in Hawassa City, southern Ethiopia
Authors: Abebe Rahmeto , Markos Alemayehu , Abera Mesele , Mekbib Berhanu 
Published: July 2023

AbstractMastitis is the most common disease of dairy cattle worldwide, causing economic losses due to reduced yield and poor quality of milk. It is of particular concern in Ethiopia, where effective prevention and control practices are lacking. The objective of the present prospective longitudinal study was to estimate the incidence rate of clinical mastitis (CM), identify the risk factors, isolate the bacterial agents, and determine the risk of recurrence. For this purpose, a total of 217 lactating cows were followed up every two weeks from calving to drying off or the end of the study period. Of these, 79 (36.41%) developed CM, of which 23% had recurrent infections in the same or a different quarter. The overall incidence rate of CM was 83.72 (95% CI: 63.2–98.2) cases per 100 cow-years at risk. In the multivariable Cox regression model, the risk of CM was found to be significantly higher in multiparous cows (HR = 1.96; p = 0.03), in cows with a history of mastitis (HR = 2.04; p = 0.030), in cows that had severely keratinized teat end condition (HR = 7.72; p < 0.001) and in cows kept in poorly cleaned barns (HR = 1.89; p = 0.007). The pathogenic bacteria isolated from mastitis-positive cows were Staphylococcus aureus (28.1%), E. coli (21.1%), Bacillus spp. (14%), Streptococcus spp. (14%), coagulase-negative staphylococci (12.3%), non aureus staphylococci (5.3%), Enterobacter spp. (3.5%), Klebsiella spp. (1.8%), Corynebacterium spp. (1.8%), and Proteus spp. (1.8%). The high incidence rate of CM in the present study shows that the disease spreads rapidly and can be responsible for a significant economic loss to milk producers in the study area. Therefore, raising awareness among dairy farmers, early detection and treatment of cases, post-milking teat disinfection, improvement of the hygienic status of cows and barns, use of dry cow therapy, and culling of chronic cases are recommended as viable measures to prevent and control clinical mastitis in the study area.
Formation of nuclear CPSF6/CPSF5 biomolecular condensates upon HIV-1 entry into the nucleus is important for productive infection
Authors: Luchsinger Charlotte , Lee KyeongEun , Mardones Gonzalo A. , KewalRamani Vineet N. , Diaz-Griffero Felipe 
Published: July 2023

AbstractThe early events of HIV-1 infection involve the transport of the viral core into the nucleus. This event triggers the translocation of CPSF6 from paraspeckles into nuclear speckles forming puncta-like structures. Our investigations revealed that neither HIV-1 integration nor reverse transcription is required for the formation of puncta-like structures. Moreover, HIV-1 viruses without viral genome are competent for the induction of CPSF6 puncta-like structures. In agreement with the notion that HIV-1 induced CPSF6 puncta-like structures are biomolecular condensates, we showed that osmotic stress and 1,6-hexanediol induced the disassembly of CPSF6 condensates. Interestingly, replacing the osmotic stress by isotonic media re-assemble CPSF6 condensates in the cytoplasm of the cell. To test whether CPSF6 condensates were important for infection we utilized hypertonic stress, which prevents formation of CPSF6 condensates, during infection. Remarkably, preventing the formation of CPSF6 condensates inhibits the infection of wild type HIV-1 but not of HIV-1 viruses bearing the capsid changes N74D and A77V, which do not form CPSF6 condensates during infection1,2. We also investigated whether the functional partners of CPSF6 are recruited to the condensates upon infection. Our experiments revealed that CPSF5, but not CPSF7, co-localized with CPSF6 upon HIV-1 infection. We found condensates containing CPSF6/CPSF5 in human T cells and human primary macrophages upon HIV-1 infection. Additionally, we observed that the integration cofactor LEDGF/p75 changes distribution upon HIV-1 infection and surrounds the CPSF6/CPSF5 condensates. Overall, our work demonstrated that CPSF6 and CPSF5 are forming biomolecular condensates that are important for infection of wild type HIV-1 viruses.
Development of a hydroxyflavone-labelled 4554W peptide probe for monitoring αS aggregation
Authors: Watt Kathryn J. C. , Meade Richard M. , James Tony D. , Mason Jody M. 
Published: July 2023

AbstractParkinson’s is the second most common neurodegenerative disease, with the number of individuals susceptible due to increase as a result of increasing life expectancy and a growing worldwide population. However, despite the number of individuals affected, all current treatments for PD are symptomatic—they alleviate symptoms, but do not slow disease progression. A major reason for the lack of disease-modifying treatments is that there are currently no methods to diagnose individuals during the earliest stages of the disease, nor are there any methods to monitor disease progression at a biochemical level. Herein, we have designed and evaluated a peptide-based probe to monitor αS aggregation, with a particular focus on the earliest stages of the aggregation process and the formation of oligomers. We have identified the peptide-probe K1 as being suitable for further development to be applied to number of applications including: inhibition of αS aggregation; as a probe to monitor αS aggregation, particularly at the earliest stages before Thioflavin-T is active; and a method to detect early-oligomers. With further development and in vivo validation, we anticipate this probe could be used for the early diagnosis of PD, a method to evaluate the effectiveness of potential therapeutics, and as a tool to help in the understanding of the onset and development of PD.
Association between statin therapy and mortality in patients on dialysis after atherosclerotic cardiovascular diseases
Authors: Lee Myunhee , Choi Won Jung , Lee Yunhee , Lee Kyusup , Park Mahn-Won , Myong Jun-Pyo , Kim Dae-Won 
Published: July 2023

AbstractStatin therapy is essential for secondary prevention in patients with atherosclerotic cardiovascular disease (ASCVD). However, the effects of statin therapy in patients receiving chronic dialysis remain uncertain. We aimed to evaluate the effect of statin therapy on long-term mortality in patients on dialysis after a first-time ASCVD. Patients receiving maintenance dialysis aged ≥ 18 years with a first-time ASCVD event between 2013 and 2018 were included in the Korean National Health Insurance Service database. Associations of statin use with long-term mortality were examined using Cox proportional hazards regression models adjusted for demographics and comorbidities. Among 17,242 patients on dialysis, 9611 (55.7%) were prescribed statins after a first-time ASCVD event. Among statin users, 7376 (76.7%) used moderate-intensity statins. During a mean follow-up of 32.6 ± 20.9 months, statin use was associated with a lower risk of all-cause mortality than statin nonuse after adjusting for confounding factors (hazard ratio [HR]: 0.92; 95% confidence interval [CI] 0.88–0.97; p = 0.0009). Despite a lack of evidence, more than half of patients on dialysis were prescribed statins after an ASCVD event. In patients on dialysis after ASCVD, statin therapy significantly reduced the risk of long-term all-cause mortality.
Biomarker integration for improved biodosimetry of mixed neutron + photon exposures
Authors: Shuryak Igor , Ghandhi Shanaz A. , Laiakis Evagelia C. , Garty Guy , Wu Xuefeng , Ponnaiya Brian , Kosowski Emma , Pannkuk Evan , Kaur Salan P. , Harken Andrew D. , Deoli Naresh , Fornace Albert J. , Brenner David J. , Amundson Sally A. 
Published: July 2023

AbstractThere is a persistent risk of a large-scale malicious or accidental exposure to ionizing radiation that may affect a large number of people. Exposure will consist of both a photon and neutron component, which will vary in magnitude between individuals and is likely to have profound impacts on radiation-induced diseases. To mitigate these potential disasters, there exists a need for novel biodosimetry approaches that can estimate the radiation dose absorbed by each person based on biofluid samples, and predict delayed effects. Integration of several radiation-responsive biomarker types (transcripts, metabolites, blood cell counts) by machine learning (ML) can improve biodosimetry. Here we integrated data from mice exposed to various neutron + photon mixtures, total 3 Gy dose, using multiple ML algorithms to select the strongest biomarker combinations and reconstruct radiation exposure magnitude and composition. We obtained promising results, such as receiver operating characteristic curve area of 0.904 (95% CI: 0.821, 0.969) for classifying samples exposed to ≥ 10% neutrons vs. < 10% neutrons, and R2 of 0.964 for reconstructing photon-equivalent dose (weighted by neutron relative biological effectiveness) for neutron + photon mixtures. These findings demonstrate the potential of combining various -omic biomarkers for novel biodosimetry.
The influence of seismic frequency spectrum on the instability of loess slope
Authors: Chang Chaoyu , Qiao Feng , Bo Jingshan , Peng Da , Li Qi 
Published: July 2023

AbstractThe input of seismic wave with different frequency has a significant impact on loess slope instability. On the basis of field investigation and experiments, the particle flow software PFC2D was used to explore the effect of seismic frequency spectrum on slope instability through the process of calibrating soil microscopic parameters, model establishment, seismic wave input and other processes. The results show that: 1. The low-frequency component of the input wave is the main frequency band that causes the slope instability, the slope has amplifying effect on the low-frequency input wave, and the slope has a "filtering" effect on the high-frequency input wave; 2. The instability of the slope will cause an increase in frequency components above 10 Hz; 3. The special structure of the slope is one of the main reasons for the instability of the slope. This result has theoretical and practical significance for earthquake landslide prevention and monitoring and early warning.
Exercise training improves blood pressure reactivity to stress: a systematic review and meta-analysis
Authors: Mariano Igor M. , Amaral Ana Luiza , Ribeiro Paula A. B. , Puga Guilherme Morais 
Published: July 2023

AbstractBlood pressure (BP) reactivity to stress is associated with cardiovascular events and the incidence of hypertension, therefore, tolerance to stressors is important for better management of cardiovascular risks. Exercise training is among the strategies that have been investigated as blunting the peak response to stressors, however, its efficacy is poorly explored. The aim was to explore the effects of exercise training (at least four weeks) on BP responses to stressor tasks in adults. A systematic review was performed in five electronic databases (MEDLINE, LILACS, EMBASE, SPORTDiscus, and PsycInfo). Twenty-three studies and one conference abstract was included in the qualitative analysis, totaling 1121 individuals, and k = 17 and 695 individuals in the meta-analysis. Favorable results (random-effects) for exercise training were found, with attenuated peak responses in systolic (standardized mean difference (SMD) = −0.34 [−0.56; −0.11], representing average reductions of 2.5 ± 3.6 mmHg) and null effects on diastolic BP (SMD = −0.20 [−0.54; 0.14], representing average reductions of 2.0 ± 3.5 mmHg). The analysis removing outliers’ studies improved the effects for diastolic (SMD = −0.21 [−0.38; −0.05]) but not systolic BP (SMD = −0.33 [−0.53; −0.13]). In conclusion, exercise training seems to lower stress-related BP reactivity, therefore has the potential to improve patients’ ability to better respond to stressful situations.
Migraine and white matter lesions: a mendelian randomization study
Authors: Huo Junyan , Zhang Gan , Wang Wenjing , Cao Wen , Wan Mengxia , Huang Tao , Fan Dongsheng , Fu Yu 
Published: July 2023

AbstractPrevious studies have found that migraine patients are associated with white matter lesions (WMLs), but the causal relationship between the two remains unclear. We intend to explore the bidirectional causal relationship between migraine and WMLs using a two-sample mendelian randomization (MR) method. We employed summary-level data from a recent large-scale genome-wide association study (GWAS) that characterized three white matter (WM) phenotypes: white matter hyperintensities (WMH, N = 18,381), fractional anisotropy (FA, N = 17,673), and mean diffusivity (MD, N = 17,467), as well as migraine (N = 589,356). The inverse variance-weighted (IVW) method was used as the main approach for analyzing causality. Weighted median analysis, simple median analysis, and MR-Egger regression served as complementary methods. The bidirectional MR study affords no support for causality between WMLs and migraine. In all MR methods, there was no obvious causal evidence between them. In our bidirectional MR study, we didn't reach this conclusion that WMLs can cause migraine, migraine wouldn’t increase the risk of WMLs, either.
Mathematical model combined with microdosimetric kinetic model for tumor volume calculation in stereotactic body radiation therapy
Authors: Nakano Hisashi , Shiinoki Takehiro , Tanabe Satoshi , Utsunomiya Satoru , Takizawa Takeshi , Kaidu Motoki , Nishio Teiji , Ishikawa Hiroyuki 
Published: July 2023

AbstractWe proposed a new mathematical model that combines an ordinary differential equation (ODE) and microdosimetric kinetic model (MKM) to predict the tumor-cell lethal effect of Stereotactic body radiation therapy (SBRT) applied to non-small cell lung cancer (NSCLC). The tumor growth volume was calculated by the ODE in the multi-component mathematical model (MCM) for the cell lines NSCLC A549 and NCI-H460 (H460). The prescription doses 48 Gy/4 fr and 54 Gy/3 fr were used in the SBRT, and the effect of the SBRT on tumor cells was evaluated by the MKM. We also evaluated the effects of (1) linear quadratic model (LQM) and the MKM, (2) varying the ratio of active and quiescent tumors for the total tumor volume, and (3) the length of the dose-delivery time per fractionated dose (tinter) on the initial tumor volume. We used the ratio of the tumor volume at 1 day after the end of irradiation to the tumor volume before irradiation to define the radiation effectiveness value (REV). The combination of MKM and MCM significantly reduced REV at 48 Gy/4 fr compared to the combination of LQM and MCM. The ratio of active tumors and the prolonging of tinter affected the decrease in the REV for A549 and H460 cells. We evaluated the tumor volume considering a large fractionated dose and the dose-delivery time by combining the MKM with a mathematical model of tumor growth using an ODE in lung SBRT for NSCLC A549 and H460 cells.
Removal of senescent cells reduces the viral load and attenuates pulmonary and systemic inflammation in SARS-CoV-2-infected, aged hamsters
Authors: Delval Lou , Hantute-Ghesquier Aline , Sencio Valentin , Flaman Jean Michel , Robil Cyril , Angulo Fabiola Silva , Lipskaia Larissa , Çobanoğlu Ozmen , Lacoste Anne-Sophie , Machelart Arnaud , Danneels Adeline , Corbin Mathieu , Deruyter Lucie , Heumel Séverine , Idziorek Thierry , Séron Karin , Sauve Florent , Bongiovanni Antonino , Prévot Vincent , Wolowczuk Isabelle , Belouzard Sandrine , Saliou Jean-Michel , Gosset Philippe , Bernard David , Rouillé Yves , Adnot Serge , Duterque-Coquillaud Martine , Trottein François 
Published: July 2023

AbstractOlder age is one of the strongest risk factors for severe COVID-19. In this study, we determined whether age-associated cellular senescence contributes to the severity of experimental COVID-19. Aged golden hamsters accumulate senescent cells in the lungs, and the senolytic drug ABT-263, a BCL-2 inhibitor, depletes these cells at baseline and during SARS-CoV-2 infection. Relative to young hamsters, aged hamsters had a greater viral load during the acute phase of infection and displayed higher levels of sequelae during the post-acute phase. Early treatment with ABT-263 lowered pulmonary viral load in aged (but not young) animals, an effect associated with lower expression of ACE2, the receptor for SARS-CoV-2. ABT-263 treatment also led to lower pulmonary and systemic levels of senescence-associated secretory phenotype factors and to amelioration of early and late lung disease. These data demonstrate the causative role of age-associated pre-existing senescent cells on COVID-19 severity and have clear clinical relevance.
Insulator defect detection with deep learning: A survey
Authors: Liu Yue , Liu Decheng , Huang Xinbo , Li Chenjing 
Published: July 2023

AbstractWith the improvement of smart grid, utilizing unmanned aerial vehicles (UAV) to detect the operation status of insulators has attracted widespread attention. The insulator defects can lead to serious power loss, damage the service life of power lines, and even result in power outages in serious cases. The small‐scale object, complex background, and limited‐number collected data make insulator defect still a challenging problem. Benefitted by the advances in deep learning, deep learning‐based insulator defects have achieved great progress in recent years. In the paper, the authors present a novel systematic survey of these advances, where further analysis about different processing stages methods is introduced: (i) insulator processing stage methods exploit the specific image pre‐processing algorithm for data augmentation and low‐level vision information extraction; (ii) defect detection stage model can locate and classify diagnosis fault with different task targets, like sequential task strategy and multi‐task strategy. In addition, the authors also review publicly available benchmark and datasets. The future research direction and open problem are discussed to promote the development of the community.
Anchored self‐similar 3D Gauss‐Markov mobility model for ad hoc routing scenarios
Authors: Amponis George , Lagkas Thomas , Argyriou Vasileios , Moscholios Ioannis , Zevgara Maria , Ouzounidis Savvas , Sarigiannidis Panagiotis 
Published: July 2023

AbstractGiven the observed developments of novel communication modes and the establishment of next‐generation cellular networks, mobility modelling and ad hoc routing requirements have emerged. Flying ad hoc networks are key pivots in enabling technological leaps in the domain of on‐demand communications, especially in emergency scenarios; as such, resorting to application‐ and mobility‐aware routing is a promising enabler of this emerging set of use cases. This article investigates swarm mobility modelling, and applicable routing protocols, conducting comparative analysis that leads to the introduction of the new Anchored Self‐Similar 3D Gauss‐Markov Mobility Model (ASSGM‐3D), which incorporates a novel set of spatio‐temporal statistical metrics.