bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian joint quantile autoregression
Authors: Castillo-Mateo Jorge , Gelfand Alan E. , Asín Jesús , Cebrián Ana C. , Abaurrea Jesús 
Published: November 2023

AbstractQuantile regression continues to increase in usage, providing a useful alternative to customary mean regression. Primary implementation takes the form of so-called multiple quantile regression, creating a separate regression for each quantile of interest. However, recently, advances have been made in joint quantile regression, supplying a quantile function which avoids crossing of the regression across quantiles. Here, we turn to quantile autoregression (QAR), offering a fully Bayesian version. We extend the initial quantile regression work of Koenker and Xiao (J Am Stat Assoc 101(475):980–990, 2006. https://doi.org/10.1198/016214506000000672) in the spirit of Tokdar and Kadane (Bayesian Anal 7(1):51–72, 2012. https://doi.org/10.1214/12-BA702). We offer a directly interpretable parametric model specification for QAR. Further, we offer a pth-order QAR(p) version, a multivariate QAR(1) version, and a spatial QAR(1) version. We illustrate with simulation as well as a temperature dataset collected in Aragón, Spain.
The quest for multifunctional and dedicated PET instrumentation with irregular geometries
Authors: Sanaat Amirhossein , Amini Mehdi , Arabi Hossein , Zaidi Habib 
Published: November 2023

AbstractWe focus on reviewing state-of-the-art developments of dedicated PET scanners with irregular geometries and the potential of different aspects of multifunctional PET imaging. First, we discuss advances in non-conventional PET detector geometries. Then, we present innovative designs of organ-specific dedicated PET scanners for breast, brain, prostate, and cardiac imaging. We will also review challenges and possible artifacts by image reconstruction algorithms for PET scanners with irregular geometries, such as non-cylindrical and partial angular coverage geometries and how they can be addressed. Then, we attempt to address some open issues about cost/benefits analysis of dedicated PET scanners, how far are the theoretical conceptual designs from the market/clinic, and strategies to reduce fabrication cost without compromising performance.
CRISPR-broad: combined design of multi-targeting gRNAs and broad, multiplex target finding
Authors: Veluchamy Alaguraj , Teles Kaian , Fischle Wolfgang 
Published: November 2023

AbstractIn CRISPR-Cas and related nuclease-mediated genome editing, target recognition is based on guide RNAs (gRNAs) that are complementary to selected DNA regions. While single site targeting is fundamental for localized genome editing, targeting to expanded and multiple chromosome elements is desirable for various biological applications such as genome mapping and epigenome editing that make use of different fusion proteins with enzymatically dead Cas9. The current gRNA design tools are not suitable for this task, as these are optimized for defining single gRNAs for unique loci. Here, we introduce CRISPR-broad, a standalone, open-source application that defines gRNAs with multiple but specific targets in large continuous or spread regions of the genome, as defined by the user. This ability to identify multi-targeting gRNAs and corresponding multiple targetable regions in genomes is based on a novel aggregate gRNA scoring derived from on-target windows and off-target sites. Applying the new tool to the genomes of two model species, C. elegans and H. sapiens, we verified its efficiency in determining multi-targeting gRNAs and ranking potential target regions optimized for broad targeting. Further, we demonstrated the general usability of CRISPR-broad by cellular mapping of a large human genome element using dCas9 fused to green fluorescent protein.
Knee osteoarthritis with a high grade of Kellgren–Lawrence score is associated with a worse frailty status, KNHANES 2010–2013
Authors: Joo Sang Hyun , Song Jin Woo , Shin Kichul , Kim Min Jung , Lee Joongyub , Song Yeong Wook 
Published: November 2023

AbstractFrailty as a syndrome of physical decline in late life is associated with adverse health outcomes. Knee osteoarthritis (KOA) could contribute to frailty conditions. The objective of this study was to evaluate the impact of KOA on frailty risk in a Korean National Health and Nutrition Examination Survey (KNHANES) cohort. In this study (N, total = 11,910, age; 64.10 years old [63.94–64.27; mean 95% CI], sex (female, %); 6,752 (56.69)), KOA patients were defined as those with knee joint pain and grade 2 Kellgren–Lawrence (K–L) or more on plain radiographic images who were 40 years old or older in Korean population data of KNHANES. The frailty index was calculated using 46 items related to co-morbidities and laboratory parameters. The impact of KOA on frailty risk was evaluated with logistic regression analyses. The prevalence of KOA patients was 35.6% [95% CI 34.7–36.46]. In polytomous logistic regression, the relative risk ratio (RRR) of KOA was significantly increased in the pre-frail group (2.76, 95% CI 2.30–3.31) and the frail group (7.28, 95% CI 5.90–8.98). RRR of frailty was significantly increased in patients with K–L grade 3 (1.36, 95% CI 1.13–1.63) and K-L grade 4 (2.19, 95% CI 1.72–2.79). Older age, higher BMI, smoking status, alcohol intake, low-income status, higher WBC count, higher platelet count, higher serum creatinine level and low estimated GFR were significantly associated with increased frailty risk. High hemoglobin and regular walking habits were associated with decreased frailty risk in KOA patients. In this large observation population- based survey cohort, KOA is linked to an increased risk of frailty syndrome. We found a significant connection between KOA and frailty syndrome. These results show that we need to think about the overall health of people with KOA and give them special care to prevent frailty syndrome.
Cement pavement void detection algorithm based on GPR signal and continuous wavelet transform method
Authors: Yu Qiuqin , Li Youxin , Luo Tingyi , Zhang Jun , Tao Liang , Zhu Xin , Zhang Yun , Luo Liufen , Xu Xinxin 
Published: November 2023

AbstractThe dimension of the void area in pavement is crucial to its structural safety. However, there is no effective method to measure its geometric parameters. To address this issue, a void size extraction algorithm based on the continuous wavelet transform (CWT) method was proposed using ground-penetrating radar (GPR) signal. Firstly, the finite-difference time-domain (FDTD) method was used to investigate the GPR response of void areas with different shapes, sizes, and depths. Next, the GPR signal was processed using the CWT method, and a 3D image based on the CWT result was used to visualize the void area. Based on the differences between the void and normal pavement in the time and frequency domains, the signal with maximum energy from the CWT time–frequency result was extracted and combined to reconstruct the new B-scan image, where void areas have energy concentration phenomenon. Based on this, width and depth of void detection algorithm was proposed to recognize the void area. Finally, the detection algorithm was verified both in numerical model and physical lab model. The results indicated that the CWT time–frequency energy spectrum can be used to enhance the void feature, and the 3D CWT image can clearly visualize the void area with a highlighted energy area. After fully testing and validating in numerical and lab models, our proposed method achieved high accuracy in void width and depth detection, providing a precise method for estimating void dimension in pavement. This method can guide DOT departments to carry out pre-maintenance, thereby ensuring pavement safety.
Assessment of the therapeutic potential of lutein and beta-carotene nanodispersions in a rat model of fibromyalgia
Authors: Elkholy Nourhan S. , Mohammed Haitham S. , Shafaa Medhat W. 
Published: November 2023

AbstractFibromyalgia (FM) is a chronic disorder characterized by widespread musculoskeletal pain, fatigue, and cognitive impairment. Despite the availability of various treatment options, FM remains a challenging condition to manage. In the present study, we investigated the efficacy of formulated nanodispersions of lutein and beta-carotene in treating FM-related symptoms induced by reserpine in female Wistar rats. Several techniques have been implemented to assess this efficacy at various levels, including biochemical, bioelectrical, and behavioral. Namely, oxidative stress markers, monoamine levels, electrocorticography, pain threshold test, and open field test were conducted on control, FM-induced, and FM-treated groups of animals. Our results provided compelling evidence for the efficacy of carotenoid nanodispersions in treating FM-related symptoms. Specifically, we found that the dual action of the nanodispersion, as both antioxidant and antidepressant, accounted for their beneficial effects in treating FM. With further investigation, nano-carotenoids and particularly nano-lutein could potentially become an effective alternative treatment for patients with FM who do not respond to current treatment options.
ACD‐YOLO: Improved YOLOv5‐based method for steel surface defects detection
Authors: Fan Jiacheng , Wang Min , Li Baolei , Liu Mingxue , shen Dingcai 
Published: November 2023

AbstractSince the quality of steel is of paramount importance in modern production, the defects detection of steel surface is significantly crucial. In this field, two‐stage detection algorithms have encountered issues about low detection speed, while one‐stage detection algorithms have room for improvement in detection accuracy. How to trade‐off between accuracy and speed of detection to better meet the demands of industrial production remains a challenge. To address this problem, this paper proposes a You Only Look Once version 5 (YOLOv5)‐based improved method ACD‐YOLO. ACD‐YOLO model incorporates anchors optimization, context augmentation module, and efficient convolution operators. In anchor optimization, the boundaries of anchors are optimized using an improved genetic algorithm. Moreover, to improve detection accuracy, a context augmentation module is incorporated into both the head and the backbone end of the network. Additionally, efficient convolution operators are adopted to address the increase of computation complexity caused by the context augmentation module. Experimental results show that ACD‐YOLO achieves mean average precision of 79.3%, with frames per second of 72. Compared to reference methods, ACD‐YOLO achieves the best balance between accuracy and speed of detection, and is more suitable for practice industrial production.
The spatial and temporal variability and influence factor analysis of soil erosion in a grass farming area: a case study in central China
Authors: Xue Zijing , Liu Xiaohuang , Sawut Mamat , Liu Jiufen , Zhao Xiaofeng , Xing Liyuan , Wang Ran , Luo Xinping , Wang Chao , Zhao Honghui , Wang Ying 
Published: November 2023

Context Analysing soil erosion has important research significance for the protection of the ecological environment and the prevention and control measures of soil erosion. Methods This paper aims to discuss the soil erosion degree in the warm temperate grass farming subregion of the southern Shanxi and Guanzhong Basin, China, based on Universal Soil Loss Model, RUSLE. Aims The soil erosion modulus from 1998 to 2020 of the study area was calculated and divided into five periods: 2000, 2005, 2010, 2015, and 2020. Key results We highlight two key findings: (1) the average soil erosion modulus changed from 498.86 t km−2 a−1 in 2000 to 316.94 t km−2 a−1 in 2020, and the proportion of soil area with an unchanged erosion degree is above 85%; (2) the average annual erosion area is the largest when rainfall is greater than 550 mm and less than 620 mm. From 2000 to 2020, the area of cultivated land decreased by 3497.47 km2, and the area of grassland increased by 1364.96 km2. The degree of erosion of grassland is the most severe, with soil erosion is most intense when the Normalised Vegetation Index (NDVI) is greater than 0.55 and less than 0.75. Conclusions The results show that the soil erosion in this area is slight on the whole and its degree has been decreasing. Implications The analysis in this paper can elucidate the seriousness of the soil erosion problem so that the government can strengthen the key management of soil and water conservation and achieve the purpose of reducing soil erosion.
Herbgenomics meets Papaveraceae: a promising -omics perspective on medicinal plant research
Authors: Kielich Natalia , Mazur Oliwia , Musidlak Oskar , Gracz-Bernaciak Joanna , Nawrot Robert 
Published: November 2023

Abstract
Herbal medicines were widely used in ancient and modern societies as remedies for human ailments. Notably, the Papaveraceae family includes well-known species, such as Papaver somniferum and Chelidonium majus, which possess medicinal properties due to their latex content. Latex-bearing plants are a rich source of diverse bioactive compounds, with applications ranging from narcotics to analgesics and relaxants. With the advent of high-throughput technologies and advancements in sequencing tools, an opportunity exists to bridge the knowledge gap between the genetic information of herbs and the regulatory networks underlying their medicinal activities. This emerging discipline, known as herbgenomics, combines genomic information with other -omics studies to unravel the genetic foundations, including essential gene functions and secondary metabolite biosynthesis pathways. Furthermore, exploring the genomes of various medicinal plants enables the utilization of modern genetic manipulation techniques, such as Clustered Regularly-Interspaced Short Palindromic Repeats (CRISPR/Cas9) or RNA interference. This technological revolution has facilitated systematic studies of model herbs, targeted breeding of medicinal plants, the establishment of gene banks and the adoption of synthetic biology approaches. In this article, we provide a comprehensive overview of the recent advances in genomic, transcriptomic, proteomic and metabolomic research on species within the Papaveraceae family. Additionally, it briefly explores the potential applications and key opportunities offered by the -omics perspective in the pharmaceutical industry and the agrobiotechnology field.
SynAI: an AI-driven cancer drugs synergism prediction platform
Authors: Yan Kuan , Jia Runjun , Guo Sheng 
Published: November 2023

Abstract

Summary
The SynAI solution is a flexible AI-driven drug synergism prediction solution aiming to discover potential therapeutic value of compounds in early stage. Rather than providing a finite choice of drug combination or cell lines, SynAI is capable of predicting potential drug synergism/antagonism using in silico compound SMILE (Simplified Molecular Input Line Entry System) sequences. The AI core of SynAI platform has been trained against cell lines and compound pairs listed by NCI (National Cancer Institute)-Almanac and DurgCombDB datasets. In total, the training data consists of over 1 200 000 in vitro synergism tests on 150 cancer cell lines of different organ origins. Each cell line is tested against over 6000 pairs of FDA (Food and Drug Administration) approved compound combinations. Given one or both candidate compound in SMILE sequence, SynAI is able to predict the potential Bliss score of the combined compound test with the designated cell line without the needs of compound synthetization or structural analysis; thus can significantly reduce the candidate screening costs during the compound development. SynAI platform demonstrates a comparable performance to existing methods but offers more flexibilities for data input.

Availability and implementation
The evaluation version of SynAI is freely accessible online at https://synai.crownbio.com.
Getting it right: Teaching undergraduate biology to undermine racial essentialism
Authors: Guevara Elaine , Gopalan Shyamalika , Massey Dashiell J , Adegboyega Mayowa , Zhou Wen , Solis Alma , Anaya Alisha D , Churchill Steven E , Feldblum Joseph , Lawler Richard R 
Published: November 2023

Abstract
How we teach human genetics matters for social equity. The biology curriculum appears to be a crucial locus of intervention for either reinforcing or undermining students’ racial essentialist views. The Mendelian genetic models dominating textbooks, particularly in combination with racially inflected language sometimes used when teaching about monogenic disorders, can increase middle and high school students’ racial essentialism and opposition to policies to increase equity. These findings are of particular concern given the increasing spread of racist misinformation online and the misappropriation of human genomics research by white supremacists, who take advantage of low levels of genetics literacy in the general public. Encouragingly, however, teaching updated information about the geographical distribution of human genetic variation and the complex, multifactorial basis of most human traits, reduces students’ endorsement of racial essentialism. The genetics curriculum is therefore a key tool in combating misinformation and scientific racism. Here, we describe a framework and example teaching materials for teaching students key concepts in genetics, human evolutionary history, and human phenotypic variation at the undergraduate level. This framework can be flexibly applied in biology and anthropology classes and adjusted based on time availability. Our goal is to provide undergraduate-level instructors with varying levels of expertise with a set of evidence-informed tools for teaching human genetics to combat scientific racism, including an evolving set of instructional resources, as well as learning goals and pedagogical approaches. Resources can be found at https://noto.li/YIlhZ5. Additionally, we hope to generate conversation about integrating modern genetics into the undergraduate curriculum, in light of recent findings about the risks and opportunities associated with teaching genetics.
Evaluating dynamic and predictive discrimination for recurrent event models: use of a time-dependent C-index
Authors: Wang Jian , Jiang Xinyang , Ning Jing 
Published: November 2023

Summary
Interest in analyzing recurrent event data has increased over the past few decades. One essential aspect of a risk prediction model for recurrent event data is to accurately distinguish individuals with different risks of developing a recurrent event. Although the concordance index (C-index) effectively evaluates the overall discriminative ability of a regression model for recurrent event data, a local measure is also desirable to capture dynamic performance of the regression model over time. Therefore, in this study, we propose a time-dependent C-index measure for inferring the model’s discriminative ability locally. We formulated the C-index as a function of time using a flexible parametric model and constructed a concordance-based likelihood for estimation and inference. We adapted a perturbation-resampling procedure for variance estimation. Extensive simulations were conducted to investigate the proposed time-dependent C-index’s finite-sample performance and estimation procedure. We applied the time-dependent C-index to three regression models of a study of re-hospitalization in patients with colorectal cancer to evaluate the models’ discriminative capability.
Dorsal subthalamic nucleus targeting in deep brain stimulation: microelectrode recording versus 7-Tesla connectivity
Authors: Kremer Naomi I , Roberts Mark J , Potters Wouter V , Dilai José , Mathiopoulou Varvara , Rijks Niels , Drost Gea , van Laar Teus , van Dijk J Marc C , Beudel Martijn , de Bie Rob M A , van den Munckhof Pepijn , Janssen Marcus L F , Schuurman P Richard , Bot Maarten 
Published: November 2023

Abstract
Connectivity-derived 7-Tesla MRI segmentation and intraoperative microelectrode recording can both assist subthalamic nucleus targeting for deep brain stimulation in Parkinson’s disease. It remains unclear whether deep brain stimulation electrodes placed in the 7-Tesla MRI segmented subdivision with predominant projections to cortical motor areas (hyperdirect pathway) achieve superior motor improvement and whether microelectrode recording can accurately distinguish the motor subdivision. In 25 patients with Parkinson’s disease, deep brain stimulation electrodes were evaluated for being inside or outside the predominantly motor-connected subthalamic nucleus (motor-connected subthalamic nucleus or non-motor-connected subthalamic nucleus, respectively) based on 7-Tesla MRI connectivity segmentation. Hemi-body motor improvement (Movement Disorder Society Unified Parkinson’s Disease Rating Scale, Part III) and microelectrode recording characteristics of multi- and single-unit activities were compared between groups. Deep brain stimulation electrodes placed in the motor-connected subthalamic nucleus resulted in higher hemi-body motor improvement, compared with electrodes placed in the non-motor-connected subthalamic nucleus (80% versus 52%, P &lt; 0.0001). Multi-unit activity was found slightly higher in the motor-connected subthalamic nucleus versus the non-motor-connected subthalamic nucleus (P &lt; 0.001, receiver operating characteristic 0.63); single-unit activity did not differ between groups. Deep brain stimulation in the connectivity-derived 7-Tesla MRI subthalamic nucleus motor segment produced a superior clinical outcome; however, microelectrode recording did not accurately distinguish this subdivision within the subthalamic nucleus.
Combination therapy with moderate-intensity atorvastatin and ezetimibe vs. high-intensity atorvastatin monotherapy in patients treated with percutaneous coronary intervention in practice: assessing RACING generalizability
Authors: Lee Seung-Jun , Joo Jae Hong , Park Sohee , Kim Choongki , Choi Dong-Woo , Lee Yong-Joon , Hong Sung-Jin , Ahn Chul-Min , Kim Jung-Sun , Kim Byeong-Keuk , Ko Young-Guk , Choi Donghoon , Jang Yangsoo , Nam Chung-Mo , Hong Myeong-Ki 
Published: November 2023

Abstract

Aims
Using rosuvastatin, the RACING (randomized comparison of efficacy and safety of lipid-lowering with statin monotherapy versus statin/ezetimibe combination for high-risk cardiovascular diseases) trial showed the beneficial effects of combining moderate-intensity statin with ezetimibe compared with high-intensity statin monotherapy in patients with atherosclerotic cardiovascular disease. This study investigated whether the beneficial effects of combination lipid-lowering therapy extend to patients treated with atorvastatin, not rosuvastatin, in daily clinical practice.

Methods and results
Using stabilized inverse probability of treatment weighting, a total of 31 993 patients who were prescribed atorvastatin after drug-eluting stent (DES) implantation were identified from a nationwide cohort database: 6215 patients with atorvastatin 20 mg plus ezetimibe 10 mg (combination lipid-lowering therapy) and 25 778 patients with atorvastatin 40–80 mg monotherapy. The primary endpoint was the 3-year composite of cardiovascular death, myocardial infarction, coronary artery revascularization, hospitalization for heart failure treatment, or non-fatal stroke in accordance with the RACING trial design. Combination lipid-lowering therapy was associated with a lower incidence of the primary endpoint (12.9% vs. 15.1% in high-intensity atorvastatin monotherapy; hazard ratio [HR] 0.81, 95% confidence interval [CI] 0.74–0.88, P &lt; 0.001). Compared with high-intensity atorvastatin monotherapy, combination lipid-lowering therapy was also significantly associated with lower rates of statin discontinuation (10.0% vs. 8.4%, HR 0.81, 95% CI 0.73–0.90, P &lt; 0.001) and new-onset diabetes requiring medication (8.8% vs. 7.0%, HR 0.80, 95% CI 0.70–0.92, P = 0.002).

Conclusion
In clinical practice, a combined lipid-lowering approach utilizing ezetimibe and moderate-intensity atorvastatin was correlated with favourable clinical outcomes, drug compliance, and a reduced incidence of new-onset diabetes requiring medications in patients treated with DES implantation.
Trial registration: ClinicalTrial.gov (NCT04715594).