bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seismicity and 3-D body-wave velocity models across the Hengill geothermal area, SW Iceland
Authors: Obermann Anne , Wu Sin-Mei , Ágústsdóttir Thorbjörg , Duran Alejandro , Diehl Tobias , Sánchez-Pastor Pilar , Kristjansdóttir Sigridur , Hjörleifsdóttir Vala , Wiemer Stefan , Hersir Gylfi Páll 
Published: December 2022

We image shallow crustal structures and analyze seismicity patterns in the Hengill high-enthalpy geothermal area in SW Iceland, exploiting a temporary densification of the seismic network 2018 to 2020. Using a subset of 6,300 high-quality manually picked P- and S-phases, we compute a minimum 1-D model for the region. Our results suggest that the most consistent and accurate hypocenter locations are derived from a joint inversion of P and S arrival times for the Hengill area. We demonstrate that this minimum 1-D model in combination with SeisComP detection and location algorithms can be used to produce fully-automated yet high-quality earthquake catalogs. Our analysis established that both the induced and natural seismicity in the Hengill area occurs in several distinct, spatially constrained clusters. In production and injection areas, the depth of the clusters is at about 2 km, near the bottom of the production and injection wells. These are most likely triggered by the injection and induced by the production, respectively. Outside of these clusters, the seismicity is generally deeper, with the depth of the deepest seismicity indicating the brittle-ductile transition zone. This zone is encountered at about 4 km near the center of the Hengill volcanic area and deepens with increasing distance from its volcanic center, to about 7 km in the southernmost region. A spatial analysis of b-values shows slightly increased values in areas with numerous injection wells and slightly decreased values in production areas. Three-dimensional crustal imaging of VP, VS, VP/VSshows a SE-NW trending fast velocity that extends, at 1–3 km depth between the extinct Grensdalur volcanic center and the presently active Hengill volcanic center. The fastest velocities are found in the NW corner of the Grensdalur volcanic center coinciding with a gravity high and probably reflecting dense solidified magmatic intrusion(s). This trend coincides with traces of geothermal surface manifestations, a shallow lying low resistivity anomaly and an aero-magnetic low. All these anomalies are caused by high temperature at some point in the geological history of the area and are most likely due to migration of the crustal accretion and volcanic activity between the two volcanic centers. Below-average VP/VSratios at similar depth, coincide with the main production field. We suggest that this anomaly is caused by the extensive fluid extraction, which lowers the pore-pressure in the field and consequently increases the steam dominated zone, leading to lower Vp/Vs ratios. Most of the earthquakes are within the Vp/Vs low and at the boundary of the high and low Vp/Vs anomalies, which might indicate a region of good permeability.
Nocebo response intensity and influencing factors in the randomized clinical trials of irritable bowel syndrome: A systematic review and meta-analysis
Authors: Li Ruijie , Chen Fuping , He Xuanxuan , Feng Yuqing , Pei Qiaoqiao , Wang Dongke , Liu Xinghuang , Liu Jinsong , Hou Xiaohua , Bai Tao 
Published: December 2022

ObjectiveTo estimate the magnitude of the nocebo response and explore its influencing factors in irritable bowel syndrome (IBS).MethodsThe PubMed, Embase, and Cochrane Library databases were searched up to March 2021. We performed a random effects meta-analysis of the proportion of adverse events (AEs) in placebo-treated patients with IBS who are involved in parallel-designed, randomized, placebo-controlled trials investigating pharmacological interventions and evaluated the effect of trial characteristics on the magnitude of the nocebo response rate.ResultsA total of 6,107 studies were identified from the databases. After evaluation, 53 met the eligibility criteria and were included. The overall pooled nocebo response rate was 32% (95% CI: 26–38%). The most commonly reported AEs were headache (9%), nasopharyngitis (7%), abdominal pain (4%), and nausea (4%). The nocebo response rate was low compared with that in the treatment group applying probiotics, antispasmodics, and Traditional Chinese medicine, but high compared with that in antibiotic treatment group. The nocebo rate in patients using diaries to record AEs was lower than the average, and was higher in patients recording through checkup.DiscussionPatients with IBS have significant nocebo response intensity in clinical trials. Based on findings in this study, we recommend the researchers pay attention to the common AEs and carefully analyze the relation to the intervention.
Developing and predicting of early mortality after endovascular thrombectomy in patients with acute ischemic stroke
Authors: Chen Yimin , Zhou Sijie , Yang Shuiquan , Mofatteh Mohammad , Hu Yuqian , Wei Hongquan , Lai Yuzheng , Zeng Zhiyi , Yang Yajie , Yu Junlin , Chen Juanmei , Sun Xi , Wei Wenlong , Nguyen Thanh N. , Baizabal-Carvallo José Fidel , Liao Xuxing 
Published: December 2022

BackgroundStroke is one of the leading causes of mortality across the world. However, there is a paucity of information regarding mortality rates and associated risk factors in patients with acute ischemic stroke (AIS) undergoing endovascular thrombectomy (EVT). In this study, we aimed to clarify these issues and analyzed previous publications related to mortality in patients treated with EVT.MethodsWe analyzed the survival of 245 consecutive patients treated with mechanical thrombectomy for AIS for which mortality information was obtained. Early mortality was defined as death occurring during hospitalization after EVT or within 7 days following hospital discharge from the stroke event.ResultsEarly mortality occurred in 22.8% of cases in this cohort. Recanalization status (modified thrombolysis in cerebral infarction, mTICI) (p = 0.002), National Institute of Health Stroke Scale Score (NIHSS) score 24-h after EVT (p &lt; 0.001) and symptomatic intracerebral hemorrhage (sICH) (p &lt; 0.001) were independently associated with early mortality. Age, sex, cardiovascular risk factors, NIHSS score pre-treatment, Alberta Stroke Program Early CT Score (ASPECTS), stroke subtype, site of arterial occlusion and timing form onset to recanalization did not have an independent influence on survival. Non-survivors had a shorter hospitalization (p &lt; 0.001) but higher costs related to their hospitalization and outpatient care.ConclusionThe recanalization status, NIHSS score 24-h after EVT and sICH were predictors of early mortality in AIS patients treated with EVT.
Prefrontally modulated vagal neuroimmunomodulation is associated with telomere length
Authors: Ask Torvald F. , Sütterlin Stefan 
Published: December 2022

BackgroundAccumulated senescent cells are proposed to be one of the main drivers of age-related pathology such as dementia and cancer through disruption of tissue structure and function. We recently proposed the Neuro-Immuno-Senescence Integrative Model (NISIM), which relates prefrontally modulated vagal tone and subsequent balance between vagal and sympathetic input to the spleen to inflammatory responses leading to generation of reactive oxygen species and oxidative telomere damage.AimIn this study, we assess inflammation as a mediator in the relationship between prefrontally modulated vagal tone and leukocyte telomere length (LTL). We also assess the relationship between a recently proposed index of vagal neuroimmunomodulation (vagal tone/inflammation ratio; NIM index) and telomere length.MethodsThis study uses participant data from a large nationally representative longitudinal study since 1974 with a total of 45,000 Norwegian residents so far. A sub-sample of 131 participants from which ultrashort recordings (30 s) of vagal tone, c reactive protein, and LTL could be obtained were included in the study. Relationships were analyzed with Pearson’s correlations and hierarchical multiple linear regression using either vagal tone and CRP or the NIM index to predict telomere length.ResultsVagal tone was a significant positive predictor of telomere length but this was not mediated by c reactive protein, even after controlling for confounders. The NIM index was a significant positive predictor of telomere length, also when controlling for confounders. In a follow-up analysis simultaneously comparing telomere length between groups with high and low values of vagal tone, and between groups with high and low NIM index values, telomere length was only significantly different between NIM index groups.ConclusionThis is the first study suggesting that prefrontally modulated vagal neuroimmunomodulation is associated with telomere length thus supporting the NISIM. Results indicate that the NIM index is a more sensitive indicator of vagal neuroimmunomodulation than vagal tone and CRP in isolation.
Prognosis and immune features of pyroptosis-related RNA patterns in low-grade glioma
Authors: Liu Hanzhang , Tao Tao 
Published: December 2022

PurposeLow-grade gliomas (LGG), which are malignant primary brain tumors, are more prevalent in young adults. Pyroptosis, an inflammatory form of programmed cell death, has been shown in recent years to be directly associated with tumor growth and tumor microenvironment (TME). However, the correlation between LGG and pyroptosis remained to be explored. In this research, we explored pyroptosis-related gene expression patterns and their prognostic significance based on transcriptome profiles and clinical data in LGG.MethodsWe identified 31 pyroptosis-related genes differentially expressed at the mRNA level between the data of LGG patients from TCGA and the data of normal brain tissues from GTEx. Univariate Cox regression analysis was used to screen 16 differentially expressed genes (DEGs) based on survival data. Next, the prognostic model was established using LASSO Cox regression, which divided LGG patients into high- and low- risk subgroups and showed an independent prognostic value for overall survival (OS) combined with clinical factors in the CGGA test cohort. Pyroptosis and immune cells were correlated through the CIBERSORT R package and the TIMER database.ResultsBased on the analyses of 523 LGG and 1152 normal tissues, nine significant differential genes were identified. The AUC remained at about 0.74 when combined with the risk score and clinical factors. Enrichment analyses revealed that DEGs were mainly enriched in cytokine-cytokine receptor interactions, immune response and chemokine signaling pathways. Immune cell enrichment analysis demonstrated that scores for most immune cell types differed significantly between the high-and low-risk groups, and further infiltrating analysis showed obvious differences between these two risk subgroups.ConclusionPyroptosis-related genes play a pivotal role in LGG and are associated with tumor immunity, which may be beneficial to the prognosis and immunotherapy of LGG.
Application of machine learning techniques in real-world research to predict the risk of liver metastasis in rectal cancer
Authors: Qiu Binxu , Su Xiao hu , Qin Xinxin , Wang Quan 
Published: December 2022

BackgroundThe liver is the most common site of distant metastasis in rectal cancer, and liver metastasis dramatically affects the treatment strategy of patients. This study aimed to develop and validate a clinical prediction model based on machine learning algorithms to predict the risk of liver metastasis in patients with rectal cancer.MethodsWe integrated two rectal cancer cohorts from Surveillance, Epidemiology, and End Results (SEER) and Chinese multicenter hospitals from 2010-2017. We also built and validated liver metastasis prediction models for rectal cancer using six machine learning algorithms, including random forest (RF), light gradient boosting (LGBM), extreme gradient boosting (XGB), multilayer perceptron (MLP), logistic regression (LR), and K-nearest neighbor (KNN). The models were evaluated by combining several metrics, such as the area under the curve (AUC), accuracy score, sensitivity, specificity and F1 score. Finally, we created a network calculator using the best model.ResultsThe study cohort consisted of 19,958 patients from the SEER database and 924 patients from two hospitals in China. The AUC values of the six prediction models ranged from 0.70 to 0.95. The XGB model showed the best predictive power, with the following metrics assessed in the internal test set: AUC (0.918), accuracy (0.884), sensitivity (0.721), and specificity (0.787). The XGB model was assessed in the outer test set with the following metrics: AUC (0.926), accuracy (0.919), sensitivity (0.740), and specificity (0.765). The XGB algorithm also shows a good fit on the calibration decision curves for both the internal test set and the external validation set. Finally, we constructed an online web calculator using the XGB model to help generalize the model and to assist physicians in their decision-making better.ConclusionWe successfully developed an XGB-based machine learning model to predict liver metastasis from rectal cancer, which was also validated with a real-world dataset. Finally, we developed a web-based predictor to guide clinical diagnosis and treatment strategies better.
Feasibility and mechanism analysis of Reduning in the prevention of sepsis-induced pulmonary fibrosis
Authors: Wang Ziyi , Liu Yuxin , Chen Feng , Liao Haiyan , Wang Xuesong , Guo Zhe , Wang Zhong 
Published: December 2022

Introduction: The increasing mortality in patients with sepsis-induced pulmonary fibrosis owes to a lack of effective treatment options. This study aims to explore the possibility and possible targets of Reduning in the prevention of sepsis-related pulmonary fibrosis.Methods: The active components and targets of Reduning were searched and screened from the database and analysis platform of traditional Chinese medicine (TCM) system pharmacology. GeneCards, human genome database, DisGeNET database, and the OMIM database were checked to determine the targets associated with sepsis-induced pulmonary fibrosis. DAVID Bioinformatics Resources 6.8 was used for GO and KEGG enrichment analysis to predict its possible signaling pathways and explore its molecular mechanism. The protein–protein interaction (PPI) network was used to identify key active components and core targets. Molecular docking technology was applied to screen the complexes with stable binding of key active components and core targets. Molecular dynamics simulations were used to verify the binding stability and molecular dynamics characteristics of the complexes. The protective effect of RDN on sepsis-induced pulmonary fibrosis was verified by in vitro and in vivo experiments.Results: There were 319 shared targets between sepsis-induced pulmonary fibrosis and RDN. GO enrichment analysis showed that they mainly regulated and participated in the positive regulation of kinase activity, mitogen-activated protein kinase (MAPK) cascade, and protein phosphorylation. KEGG enrichment analysis showed that they were mainly enriched in the mitogen-activated protein kinase cascade signaling pathway, the calcium signaling pathway, the apoptosis pathway, and other signaling pathways. The results of molecular docking and molecular dynamics simulations showed that the active components, stigmasterol, beta-sitosterol, and quercetin, had good binding activities with ERBB2, and they exhibited good stability. Molecular validation experiments confirmed RDN could alleviate lung fibrosis induced by cecum ligation and puncture (CLP), in parallel with the inhibition of the ERBB2-p38 MAPK pathway in mouse alveolar macrophages (AMs).Discussion: Reduning may prevent sepsis-induced pulmonary fibrosis by regulating the ERBB2-p38 MAPK signaling pathway, which provides a possibility for the prevention of sepsis-induced pulmonary fibrosis with traditional Chinese medicine.
Interference with orco gene expression affects host recognition in Diorhabda tarsalis
Authors: Chen Hong-Hao , Dewer Youssef , Wang Yan , Tan Shu-Qian , Liu Xiao-Li , Shi Wang-Peng 
Published: December 2022

Introduction:Diorhabda tarsalis Weise is an important insect pest of the Chinese licorice Glycyrrhiza uralensis Fisch. Behavior of the beetle, including host location, oviposition site selection, self-defense, and aggregation, were regulated by plant volatiles or insect pheromones.Aim: In this study, Identification of ORs and function research on orco were carried out, these could lead to the development of understand for olfaction mechanism in D. tarsalis.Methods: ORs were identified by PacBio RS II platform to sequence the antennas of adult D. tarsalis, the function of orco was explored by dsRNA interference.Results: 29 odorant receptor candidate genes of D. tarsalis were obtained, which code for 130–479 amino acids. Phylogenetic trees of olfactory receptors were constructed with 243 ORs from eight Coleoptera species. DtarORco, DtarOR7 and DtarOR26 are specifically expressed in the antenna, and the expression levels were significantly higher than other DtarORs in antenna, there were no differential expression between male and female beetles. An odorant coreceptor gene (DtarORco) has characteristics of an odorant receptor family member, the encoded mature protein has a predicted molecular weight of 53.898 kDa, dsRNA L4440 expression vectors were constructed and successfully transformed into ribonuclease III-deficient Escherichia coli strain HT115 DE3. After interference treatment, the relative expression level of DtarORco in D. tarsalis antennae significantly decreased and electrophysiological responses to host localization odor signals significantly decreased. At the same time, beetles lost the ability to locate hosts.Discussion: The research on its mechanism of olfaction may lead to the development of new control measures that are environmentally friendly.
Assessing cognitive flexibility in humans and rhesus macaques with visual motion and neutral distractors
Authors: Yurt Pinar , Calapai Antonino , Mundry Roger , Treue Stefan 
Published: December 2022

IntroductionCognitive flexibility is the ability of an individual to make behavioral adjustments in response to internal and/or external changes. While it has been reported in a wide variety of species, established paradigms to assess cognitive flexibility vary between humans and non-human animals, making systematic comparisons difficult to interpret.MethodsWe developed a computer-based paradigm to assess cognitive flexibility in humans and non-human primates. Our paradigm (1) uses a classical reversal learning structure in combination with a set-shifting approach (4 stimuli and 3 rules) to assess flexibility at various levels; (2) it employs the use of motion as one of three possible contextual rules; (3) it comprises elements that allow a foraging-like and random interaction, i.e., instances where the animals operate the task without following a strategy, to potentially minimize frustration in favor of a more positive engagement.Results and DiscussionWe show that motion can be used as a feature dimension (in addition to commonly used shape and color) to assess cognitive flexibility. Due to the way motion is processed in the primate brain, we argue that this dimension is an ideal candidate in situations where a non-binary rule set is needed and where participants might not be able to fully grasp other visual information of the stimulus (e.g., quantity in Wisconsin Card Sorting Test). All participants in our experiment flexibly shifted to and from motion-based rules as well as color- and shape-based rules, but did so with different proficiencies. Overall, we believe that with such approach it is possible to better characterize the evolution of cognitive flexibility in primates, as well as to develop more efficient tools to diagnose and treat various executive function deficits.
Accounting for the valley of recovery during post-stroke rehabilitation training via a model-based analysis of macaque manual dexterity
Authors: Izawa Jun , Higo Noriyuki , Murata Yumi 
Published: December 2022

BackgroundTrue recovery, in which a stroke patient regains the same precise motor skills observed in prestroke conditions, is the fundamental goal of rehabilitation training. However, a transient drop in task performance during rehabilitation training after stroke, observed in human clinical outcome as well as in both macaque and squirrel monkey retrieval data, might prevent smooth transitions during recovery. This drop, i.e., recovery valley, often occurs during the transition from compensatory skill to precision skill. Here, we sought computational mechanisms behind such transitions and recovery. Analogous to motor skill learning, we considered that the motor recovery process is composed of spontaneous recovery and training-induced recovery. Specifically, we hypothesized that the interaction of these multiple skill update processes might determine profiles of the recovery valley.MethodsA computational model of motor recovery was developed based on a state-space model of motor learning that incorporates a retention factor and interaction terms for training-induced recovery and spontaneous recovery. The model was fit to previously reported macaque motor recovery data where the monkey practiced precision grip skills after a lesion in the sensorimotor area in the cortex. Multiple computational models and the effects of each parameter were examined by model comparisons based on information criteria and sensitivity analyses of each parameter.ResultBoth training-induced and spontaneous recoveries were necessary to explain the behavioral data. Since these two factors contributed following logarithmic function, the training-induced recovery were effective only after spontaneous biological recovery had developed. In the training-induced recovery component, the practice of the compensation also contributed to recovery of the precision grip skill as if there is a significant generalization effect of learning between these two skills. In addition, a retention factor was critical to explain the recovery profiles.ConclusionsWe found that spontaneous recovery, training-induced recovery, retention factors, and interaction terms are crucial to explain recovery and recovery valley profiles. This simulation-based examination of the model parameters provides suggestions for effective rehabilitation methods to prevent the recovery valley, such as plasticity-promoting medications, brain stimulation, and robotic rehabilitation technologies.