bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel nutritional parameters-based nomogram for predicting severe neutropenia after CAPEOX/XELOX or SOX adjuvant chemotherapy in gastric cancer patients
Authors: Gao Chun , Zhu Li , Zhang Yu Jie , Tong Yi Xin , Zhang Sheng 
Published: October 2022

Abstract
PurposeThe aim of this study is to develop and internal validate a novel and specific predictive model for severe neutropenia during adjuvant chemotherapy cycles among patients with gastric cancer.
Methods We included 391 gastric cancer patients underwent curative laparoscopic D2 gastrectomy and divided them into development cohort and validation cohorts. The study endpoint was grade 3/4 neutropenia. Multivariate logistic regression was performed to analyze the independent risk factor of severe neutropenia. Predictive nomogram was constructed based on the multivariate model using R. We applied area under ROC curve (AUC) and decision curve analysis (DCA) to evaluate the performance of the model.
Results 318 patients and 73 patients were divided into development and validation cohorts, treated with 1518 and 356 chemotherapy cycles respectively. The multivariable analysis revealed 4 predictive factors for severe neutropenia: Age, prealbumin level, prognostic nutritional index (PNI) and neutropenia in previous cycles. The constructed nomogram displayed a good predictive value, with AUCs as 0.825 (95%CI, 0.789-0.860) and 0.810 (95%CI, 0.783-0.835) in development and validation cohorts.
ConclusionsWe developed and internally validate a novel and specific risk prediction model for severe neutropenia among gastric cancer patients during adjuvant chemotherapy. This model is user-friendly and can guide clinical decision for personalized treatment plan. Further external validation should be necessary.
Hippocampal Subregions Volume and Texture for the Diagnosis of Mild Cognitive Impairment
Authors: Chu Tongpeng , Liu Yajun , Zhang Zhongsheng , Zhang Gang , Dong Fanghui , Dong Jianli , Lin Shujuan 
Published: October 2022

Abstract
Purpose
The aim of this study was to examine the diagnostic efficacy of hippocampal subregions volume and texture in differentiating amnestic mild cognitive impairment (MCI) from normal aging changes.
Materials and Methods
Ninety MCI subjects and eighty-eight well-matched healthy controls (HCs) were selected from the Open Access Series of Imaging Studies Database. Twelve hippocampal subregions volume and texture features were extracted using Freesurfer and MaZda based on T1 weighted magnetic resonance images. Then, two-sample t-test and Least Absolute Shrinkage and Selection Operator (LASSO) regression were developed to select a subset of the original features. Finally, a support vector machine (SVM) was used to perform the classification task and the area under the curve (AUC), sensitivity, specificity, and accuracy were calculated to evaluate the diagnostic efficacy of the model.
Results
The volume features with high discriminative power were mainly located in the bilateral CA1, and bilateral CA4, while texture feature were gray-level non-uniformity, run length non-uniformity and fraction. Our model based on hippocampal subregions volume and texture features achieved better classification performance with an area under the curve (AUC) of 0.90.
Conclusions
Based on hippocampal subregions volume and texture can be used to diagnose MCI. Moreover, we found that the features that contributed most to the model were mainly textural features, followed by volume. These results may guide future studies using structural scans to classify patients with MCI.
CHIP mediates CAD ubiquitination and degradation to suppress the proliferation and colony formation of glioblastoma cells
Authors: Li Guanya , Xiao Kai , Li Yinan , Gao Jianfang , He Shanping , Li Tingting 
Published: October 2022

Abstract
Cancer cells are characterized as the uncontrolled proliferation, which demands high levels of nucleotides that are the building blocks for DNA replication. CAD is a trifunctional enzyme that initiates the de novo pyrimidine synthesis, which is normally enhanced in cancer cells to preserve the pyrimidine pool for cell division. Glioma, representing the majority of brain cancers, is highly addicted to nucleotides like pyrimidine to sustain the abnormal growth and proliferation of cells. CAD is previously reported to by dysregulated in glioma, but the underlying mechanism remains unclear. Here, we showed that the expression of CAD was upregulated in glioma, which was positively correlated with tumor grade and the survival of glioma patients. Knockdown of CAD robustly inhibited the cell proliferation and colony formation of glioblastoma (GBM) cells, indicating the essential role of CAD in the pathogenesis of GBM. Mechanistically, we firstly identified that CAD was modified by the K29-linked polyubiquitination, and subsequently subjected to degradation. CHIP interacted and ubiquitinated CAD, which accounted for the anti-proliferative role of CHIP in GBM. Specifically, the ectopic expression of CAD dramatically enhanced the colony formation of GBM cells, which was subsequently abolished by CHIP overexpression. To sustain the expression of CAD, CHIP is significantly downregulated, which is correlated with the poor prognosis and survival of GBM patients. Notably, low level of CHIP and high level of CAD predict the short overall survival of GBM patients. These results illustrated the essential role of CAD in glioma and reveal novel therapeutic targets for CAD-positive and CHIP-negative cancer.
Autoimmune cerebellar ataxia associated with anti-glutamate receptor δ2 antibodies: a rare but treatable entity
Authors: Khatib Laura , Do Le-Duy , Benaiteau Marie , Villagrán-García Macarena , Meyer Pierre , Haidar Lydia Abou , Demeret Sophie , Honnorat Jérôme 
Published: October 2022

Abstract
We reported two novel cases of autoimmune cerebellar ataxia (ACA) associated with anti-glutamate receptor δ2 antibodies (Gluδ2-Abs). This first case was confirmed by indirect immunofluorescence and cell-based assays: a 29-year-old woman presenting, after 5 days of headache and vomiting, a pancerebellar syndrome, a downbeat nystagmus, a decreased visual acuity, and a lymphocytic pleocytosis in the cerebrospinal fluid (CSF) without any abnormality detected using cerebral magnetic resonance imaging (MRI). Clinical improvement was obtained progressively after second-line immunotherapy, full recovery was achieved after a 4-year follow-up. Thereafter, we retrospectively tested Gluδ2-Abs in 350 patients with a suspicion of autoimmune encephalitis without characterized autoantibody. We identified a second case, a 12-year-old boy developing, 10 days after a respiratory infection, a static cerebellar syndrome with lymphocytosis in the CSF and right cerebellum hyperintensity in MRI. Five days of corticosteroid treatment allowed a quick clinical improvement. No tumor was identified in both cases whereas laboratory analyzes revealed autoimmune stigma. The present cases suggested that ACA associated with Gluδ2-Abs is an extremely rare but treatable disease. Therefore, testing for Gluδ2-Abs might be considered in the setting of suspected ACA and no initial antibody identification. The visual deficits and ocular motility abnormalities observed in the first reported case might be part of the clinical spectrum of Gluδ2-Abs ACA. Young age, infectious prodromes, lymphocytic pleocytosis, and autoimmune background usually appear together with this syndrome and should lead to the prompt initiation of immunotherapy.
BFAST_CSP_KAZE computing model for effective image registration
Authors: Zhang Sheng , Shen Jie , Zheng Shengnan , Tang Jingjing 
Published: October 2022

Abstract
The incompatible problem between velocity and accuracy has been restricting the application and the development of image registration, in order to resolve this problem, we propose the BFAST_CSP_KAZE computing model. This model consists of four stages. First, the registration images are preprocessed by the average and the perceptual Hashing algorithms. Second, the additive operator splitting algorithm is used to construct the nonlinear multi-scale space and utilize the FAST algorithm to extract the image features. Third, a new method to generate the image features descriptor sequences is presented based on the optimized KAZE algorithm, meanwhile, reduce the dimension of the image features descriptor sequences by the compressed sensing principle. Finally, adopt the fusion matching method based on the FLANN and the KNN algorithms to match, and the RANSAC algorithm further match. This paper utilizes two groups of the experiments to verify this model, the experiment results show that this model has obvious advantage in terms of velocity and accuracy compared with the state-of-the-art image registration methods, and also achieves the compatible between velocity and accuracy in the case of the higher matching score. This model provides an effective solution for the application of image registration, and also has great significance for the development of image registration.
Vulnerability reduction in post-conflict areas through a Nexus approach to sustainable food production systems: a case study in Colombia
Authors: Guzman-Molina Jairo , Caucci Serena , Al-Qubati Abdulhakeem Amer Abdulhafed , Schellens Marie 
Published: October 2022

Abstract

To increase the resilience of agroecosystems, and allow for sustainable economic reactivation, it is vital that the introduction of sustainable measures - particularly in agriculture – is advanced via an integrated management approach such as the Resource Nexus. An essential aspect of this approach is to optimise the efficiency of ecosystems and resources in conjunction with environmentally friendly economic growth. Colombia has experienced the impact of armed conflict over many years, while geographic regions have been shaped by environmental conflicts; resulting in vulnerable areas suffering from land and population inequalities that also translate into wicked planning for resilient food systems. This paper addresses a double challenge: the improvement of natural resources management and reducing the population's vulnerability in line with the principles of inclusion and gender equity. The paper developed a methodology to identify those productive regions that require improved management at the landscape level, which could benefit under the main framework of the water-energy-food Nexus. It also provides evidence of the value of the science-policy interface to ensure increased social equity, economic growth, and the conservation of resources. A geographic information system approach has been utilised to spatially evaluate the effects of land-use change, ecosystem services provision, and the impacts of climate change at the municipality scale of productive agricultural regions. The objectives of this research were to: (i) evaluate the impact of climate change and anthropogenic activities on natural resources, (ii) assess productive landscape fragmentation due to the overuse of resources, and (iii) consider ecosystem services planning as an operational methodology for municipality ecosystem-based management. The study results show a decrease in the natural Andean Forest, coupled with an increase in agricultural fields over the past 35 years, and a decrease in freshwater availability in the last decade. The expansion trend of the agricultural frontier into the protected areas is also highlighted.
Landscape homogenization correlates with decreasing butterfly diversity
Authors: Habel Jan Christian , Schmitt Thomas , Ulrich Werner , Gros Patrick , Salcher Bernhard , Teucher Mike 
Published: October 2022

AbstractAgricultural intensification leads to a strong homogenization of landscapes. Plots have become larger, boundaries of fields straight, and land plots have been cultivated more intensively. Field copses, ruderal areas and hedgerows were removed. As a result, most of these small-scale habitats located at the edges of fields have disappeared. Thus, many potential habitats of plant and animal species have been destroyed, and the permeability of the landscape decreased during the past decades. Landscape homogenization consequently impacts biodiversity and reduces species richness and abundance of many taxa. In this study, we surveyed changes of land cover and landscape configuration on a field-by-field basis, based on historical (1953) and recent (2018) aerial and satellite images. We further compiled data of butterfly diversity for the same time periods and region. Our data show significant decrease of field copses over the past decades. The landscape structure changed towards rather homogenous fields with straight boundaries among single land plots. The expected number of species per sample unit of an assumed species decreased significantly. Particularly butterflies relying on oligotrophic and xerothermic grasslands decreased, as well as sedentary specialist species. In contrast, the proportion of ubiquitous and mobile generalist species increased. This underlines the general trend of faunal homogenization and the loss of specialized and sedentary species, in the wake of landscape homogenization.
Conditional Hitting Time and Mean Residual life in Semi-Markov Models
Authors: Khorshidian K , Fathizadeh M 
Published: October 2022

Abstract
The mean residual life (MRL) in the repairable systems will have been introduced and a formula for its calculating presented based on the conditional distribution of the excess life for semi-Markov processes (SMPs). Moreover, the first hitting time to some specified state given the past history of the SMP has been presented besides calculating its expected value. By the best of our knowledge, it seems that there does not exist any specific research related to the issue of the MRL function in the area of repairable systems with semi-Markov structure. Nevertheless, there are a large amount of studies related to the various aspects of reliability systems, where almost all of them employ the MRL function and emphasis on the significant importance and applications of it. So, these studies and applications motivated us to examine the MRL function for repairable systems. As an application, a two unit cold standby system with a repairman has been considered as a semi-Markov model and the associated MRL has been studied in details.
Duodenal microbiota and weight-loss following sleeve gastrectomy and Roux-en-Y gastric bypass – a pilot study
Authors: Stefura Tomasz , Rusinek Jakub , Zając Maciej , Zapała Barbara , Gosiewski Tomasz , Sroka-Oleks Agnieszka , Salamon Dominika , Pędziwiatr Michał , Major Piotr 
Published: October 2022

Abstract
Background
Bariatric surgery is the most effective method of morbid obesity treatment. Microbiota has many functions in human body and many of them are still unknown. The aim of this study was to establish if the composition of duodenal microbiota influence success rate of bariatric surgery.
Methods
It was a prospective cohort study. The data concerning demographics and comorbidities was collected perioperatively. The duodenal biopsies were collected prior to surgery with the gastroscope. Then DNA analysis was conducted. The data connected to the operation outcomes was gathered after 6 and 12 months after surgery.
Results
The group of 32 patients was included. Two groups (successful – group 1 and unsuccessful – group 0) based on percentage excess weight loss after 6 months were created. The Total Actual Abundance was higher in group 0. In group 0 there was a significantly higher amount of Roseburia and Arthrobacter (p = 0.024, p = 0.027, respectively). Genus LDA effect size analysis showed Prevotella, Megasphaera and Pseudorhodobacter in group 1 to be significant. Whereas Roseburia and Arthrobacter were significant in group 0.
Conclusions
Duodenal microbiota composition may be a prognostic factor for the success of the bariatric surgery but further research on the larger group is needed.
Tsunami genesis of strike-slip earthquakes revealed in the 2018 Indonesian Palu event
Authors: Song Y. Tony , Chen Kejie , Prasetya Gegar 
Published: October 2022

Abstract
The devastating tsunami after the 2018 Indonesian Sulawesi-Palu strike-slip earthquake was a surprise because strike-slip faulting is a known phenomenon of primarily lateral movement of land, while tsunamis are believed to be caused by vertical movement of seafloor. Here we show that the horizontal displacement of seafloor slopes, instead of the vertical movement or land-sliding, was the primary cause of the tsunami. We reconstructed the earthquake from seismographs and satellite data, and used the earthquake-induced momentum to replicate the tsunami. We found that the strike-slip faulting could generate multiple tsunami sources by pushing waters laterally. Sources from the deeper slopes caused the deadly long-wave tsunami hit the Palu city, while sources outside the Palu bay resulted in the “early arrival” tsunami at Mamuju, explained observations that could not be reconciled previously. Our findings suggest a new approach of using lateral movement of faulting to detect tsunamis for early warning.
Dynamic analysis of the rotor system with elastic ring squeeze film damper considering oil film temperature
Authors: Luo Zhong , Sun Kai , Ge Xiangdong , Zhou Guangze , Cui Zewen 
Published: October 2022

Abstract
Elastic ring squeeze film damper (ERSFD) is widely used for vibration and noise control of industrial rotating machinery. However, the oil film temperature has an impact on the ERSFD rotor system under large unbalanced force and speed, which is not considered in the existing ERSFD rotor system research. In this paper, by coupling energy equation with Reynolds equation and viscosity-temperature equation, an ERSFD model considering oil film temperature is established to investigate the oil film force and temperature distribution. Based on this model, an ERSFD combined support rotor considering oil film temperature is modeled by coupling the dynamic equations of the combined support rotor with the ERSFD reaction force. Then, the influence of oil film temperature on the amplitude frequency response curve and the sudden unbalance response curve of the ERSFD rotor is analyzed. The results reveal that lower temperature decreases the vibration amplitude and shortens the transient process. Finally, the established model and some simulation results are validated by the ERSFD rotor test platform.
An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering
Authors: Hu Nan , Wu Yike , Qi Guilin , Min Dehai , Chen Jiaoyan , Pan Jeff Z. , Ali Zafar 
Published: October 2022

Abstract
Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensus of the NLP community to adopt PLMs as the backbone for downstream tasks. In recent works on knowledge graph question answering (KGQA), BERT or its variants have become necessary in their KGQA models.However, there is still a lack of comprehensive research and comparison of the performance of different PLMs in KGQA. To this end, we summarize two basic KGQA frameworks based on PLMs without additional neural network modules to compare the performance of nine PLMs in terms of accuracy and efficiency. In addition, we present three benchmarks for larger-scale KGs based on the popular SimpleQuestions benchmark to investigate the scalability of PLMs. We carefully analyze the results of all PLMs-based KGQA basic frameworks on these benchmarks and find that knowledge distillation techniques and knowledge enhancement methods in PLMs are promising for KGQA. We have released the code and benchmarks to promote the use of PLMs on KGQA.
A generalized GPR application potential zonation in the karst catchment of SW China
Authors: Gao Qiangshan , Hussain Yawar , Cao Le , Cheng Dandan 
Published: October 2022

Abstract
The epikarst together with its soil stocks (subcutaneous structure), resulted from the dissolution and weathering of soft rocks, are crucial to the fact that they may contribute to the canopy growth and can significantly influence the ecological restoration and organic carbon sequestration. For the delineation of these ecological significant karst features, ground penetrating radar (GPR) seemed to be a promising technique because of its noninvasive, cost-prohibited and lesser labor-intensive operations. However, the landscape heterogeneity, connection between surface morphology and underground environments and high vegetative endemism making karst as a complicated environment for any geophysical application. Same is the case with the GPR applicability in SW Chinese catchment as it is affected by numerous features such as epikarst slope, peak-cluster depression, tree trunks and roots, precipitation and moisture contents as well as proximity to high voltage power lines. Considering these factors, the present study analyzes the GPR data acquired at the sites representing each of these aforementioned features. The analysis includes calculation of GPR attributes as average energy, coherence and total energy together with the forward calculations wherever required. Tilt signals from surrounding hills mix with the tilt signals from subsurface inclined interfaces in a GPR image. The information of soil-rock distribution above epikarst in the slope is difficult to obtain completely for GPR. The interpretation of epikarst bottom boundary faces two possibilities considering the affects of moisture. The affects of tree trunks and roots and strong electromagnetic fields of high voltages lines make the GPR data interpretation about subsurface soil-rock structure high difficult. The soil moisture greater than ~ 30% makes GPR inapplicability. These site-specific findings are used for the generalized GPR application potential zonation in the typical SW Chinese catchment (the central Guizhou plateau). The findings of the present study may prove as a reconnaissance and an application paradigm for the future GPR utilities in complex karst characterization especially, in SW China as well as the areas having similar karstic conditions.
Highly sensitive RI sensor based on a D-shaped modulated single-mode-graded-index multimode-single- mode fiber structure
Authors: XIANG ZIHANG , RUI ZEJU , ZENG FEI , WANG SHENGJIA , LU CHUPENG , WANG YIFEI , SUN CUITING , JIN XIREN , LI SONG , GENG TAO 
Published: October 2022

Abstract
A novel refractive-index (RI) sensor based on a D-shaped modulated single-mode-graded-index multimode-single-mode fiber (DM-SGIMS) structure is presented and investigated in detail. A CO2 laser was used to process the SGIMS structure, which produced a strong evanescent field. The structural parameters were determined via simulations, and the experimental results were consistent with those of the theoretical analysis. The transmission spectra and RI sensitivity of the fabricated sensors with different lengths were compared via experiments, the results of which indicated that the maximum RI sensitivity was 811.00 nm/RIU in the range 1.333–1.419. Therefore, the proposed DM-SGIMS structure can provide high-precision measurement capabilities and can be applied in the field of biochemistry.