bluuebunny/crossref_metadata_2025_split huggingface dataset:
The serological response to SARS corona virus-2 is characterized by frequent incomplete maturation of functional affinity (avidity)
Authors: Bauer Georg , Struck Friedhelm , Schreiner Patrick , Staschik Eva , Soutschek Erwin , Motz Manfred 
Published: November 2020

Abstract
The humoral immune systems controls viral infections through recognition of critical viral target structures, selective proliferation stimulation of IgM-presenting B cells, class switch to IgG-generating B cells and subsequent affinity maturation of IgG. Affinity maturation is achieved through proliferation, hypermutation and clonal selection of IgG-generating B cells (1-4). The establishment of high affinity IgG is essential for sustained protective antiviral effects (5-10).
While analyzing the maturation of functional affinity (avidity) of IgG towards SARS CoV-2 nucleoprotein, surface protein and its receptor-binding domain, we realized that avidity maturation was frequently not completed after infection. This finding gives insight into the biological strategy of SARS CoV-2 and is important for serodiagnosis. Incomplete avidity maturation might explain the observed decline of the humoral response (11-14), allow for secondary SARS CoV-2 infections and prevent the establishment of herd immunity. Therefore, future immunization strategies should achieve the goal to induce neutralizing IgG of high avidity.
Chronicle of the Causes of Famine in the World during 1840–2019 and their Risks
Authors: Funahashi Soma , Okaneya Misato , Oki Taikan 
Published: November 2020

Abstract
Famine still exists in this world, hindering the achievement of sustainable development goal 2: zero hunger. The history and mechanism of famine have been broadly studied; however, few studies have focused on quantitative and long-term analysis of the general characteristics of famine. This study aims to analyze the factors influencing famine and estimate its risk. We developed a famine database and estimated the probability of the occurrence of famine through logistic regression with physical and social factors. Herein, we identified a few factors that are strongly related to the occurrence of famine and found that soil water and gross domestic product per capita are the most influential. By extrapolating the logistic regression to a future scenario, we revealed that although the number of countries with high famine risk would decrease, some countries in sub-Saharan Africa would remain at high famine risk for a while.
Charge localized atomic Moδ+ site boosting hydrogen evolution in alkaline solution
Authors: Cao Maoqi , Liu Kang , Song Yao , Ma Chao , Lin Yiyang , Li Huangjingwei , Fu Junwei , Li HongMei , Chen Zhiyan , Zheng Xu-Sheng , Hu Junhua , Xie Haipeng , Lu YR , Chan Ting-Shan , Liu Min 
Published: November 2020

Abstract
Electrochemical water splitting has drawn tremendous interest for the scalable and sustainable conversion of renewable electricity to clear hydrogen fuel and chemicals. However, the sluggishly kinetics of water dissociation step in alkaline solutions restrict severely the application of hydrogen evolution reaction (HER). Here, we designed and prepared cobalt layers with nitrogen modified atomically dispersed Mo sites (N-Mo/Co SAA) to boost the activity of HER. Density functional theory (DFT) calculations demonstrated that the N can induce the asymmetry charge localization of Moδ+ to facilitate the water dissociation. The energy barriers of water dissociation reduced from 0.48 to 0.35 eV by the charge localized Moδ+ site. High resolution transmission electron microscope (HRTEM) and synchrotron X-ray absorption spectroscopy (XAS) measurements confirmed the structure of N modified atomically dispersed Moδ+. Ambient pressure X-ray photoelectron spectroscopy (AP-XPS) measurements assessed the atomically dispersed Moδ+ site is the active site for water dissociation. Thus, the obtained N-Mo/Co catalyst exhibits record activity with 12 mV overpotential to achieve the current density of 10 mA cm− 2 and Tafel slope of 31 mV dec− 1 in alkaline media, which are superior to 32 mV overpotential for 10 mA cm− 2 and 38 mV dec− 1 Tafel slope on best commercial 20 wt% Pt/C sample in the same condition. This design strategy provided a new pathway to boost the activity of single atom alloy (SAA) by regulating the charge localization of the active site precisely at the atomic-level.
Health improvement framework for planning actionable treatment process using surrogate Bayesian model
Authors: Nakamura Kazuki , Kojima Ryosuke , Uchino Eiichiro , Murashita Koichi , Itoh Ken , Nakaji Shigeyuki , Okuno Yasushi 
Published: November 2020

Abstract
Clinical decision making regarding treatments based on personal characteristics leads to effective health improvements. Machine learning (ML) has been the primary concern of diagnosis support according to comprehensive patient information. However, the remaining prominent issue is the development of objective treatment processes in clinical situations. This study proposes a novel framework to plan treatment processes in a data-driven manner. A key point of the framework is the evaluation of the "actionability" for personal health improvements by using a surrogate Bayesian model in addition to a high-performance nonlinear ML model. We first evaluated the framework from the viewpoint of its methodology using a synthetic dataset. Subsequently, the framework was applied to an actual health checkup dataset comprising data from 3,132 participants, to improve systolic blood pressure values at the individual level. We confirmed that the computed treatment processes are actionable and consistent with clinical knowledge for lowering blood pressure. These results demonstrate that our framework could contribute toward decision making in the medical field, providing clinicians with deeper insights.
Clinical, Surgical Characteristics and Long-Term Outcomes of Lumbar Hernia.
Authors: Shen Chaoyong , Zhang Guixiang , Zhang Sen , Yin Yuan , Zhang Bo , Song Yinghan , Lei Wenzhang 
Published: November 2020

Abstract
Background/AimLumbar hernia is extremely rare which resulting from a defect in the abdominal wall. Due to its rarity, there is no established optimal treatment available for lumbar hernia yet. Thus, we here investigated the clinical, surgical characteristics and outcomes of lumbar hernia by collecting 28 such patients in our hospital. MethodsPatients diagnosed with lumbar hernia from our institution between April 2011 and August 2020 were retrospectively collected in this study. Demographics, clinical characteristics and surgical information were recorded. ResultsA consecutive series of 28 patients with lumbar hernia were retrospectively collected, including 13 males (46.4%) and 15 females (53.6%). The ages of the patients ranged from 5 to 79 years (median: 55 years), with a mean age of 55.6±14.9 years. A total of 7 cases had a history of previous lumbar trauma or surgery. There were 11 (39.3%), 15 (53.6%) and 2 (7.1%) cases had right, left and bilateral lumbar hernia, respectively. Superior and inferior lumbar hernia were found in 25 (89.3%) and 3 (10.7%) patients. General anesthesia was applied in 16 cases (group A), whereas 12 patients received local anesthesia (group B). Patients in the group B had a shorter hospital stay than that of the group A (3.5±1.3 days vs. 7.1±3.2 days, p=0.001), as well as total hospitalization expenses between the two groups (8309.3±1467.1 CNY vs. 19117.3±8116.1 CNY, p<0.001). ConclusionsLumbar hernia is a relatively rare entity, and inferior lumbar hernia is rarer. It is feasible to repair lumbar hernia under local anesthesia, and it may be more suitable than general anesthesia in some selected cases.
Genomic Alterations Characterization in Colorectal Cancer Identifies a Prognostic and Metastasis Biomarker: FAM83A|IDO1
Authors: Liu Zaoqu , Zhang Yuyuan , Dang Qin , Wu Kunpeng , Jiao Dechao , Li Zhen , Sun Zhenqiang , han xinwei 
Published: November 2020

Abstract
Background: Genomic alterations constitute crucial elements of colorectal cancer (CRC). Accumulating evidences have elucidated their clinical significance in predicting outcomes and therapeutic efficacy. However, a comprehensive understanding of CRC genomic alterations from a global perspective is lacking. Methods: A total of 2778 patients in 15 public datasets were enrolled. Tissues and clinical information of 30 patients were also collected. Consensus clustering was performed for samples classification based on mutation signatures.Results: We identified two distinct mutation signature clusters (MSC) featured by massive mutations and dominant somatic copy number alterations (SCNA) respectively. MSC-1 was associated with defective DNA mismatch repair, exhibiting more frequent mutations such as ATM, BRAF, and SMAD4. The mutational co-occurrences of BRAF-HMCN and DNAH17-MDN1 as well as the methylation silence event of MLH-1 were only found in MSC-1. MSC-2 was linked to the carcinogenic process of age and tobacco chewing habit, exhibiting dominant SCNA such as MYC (8q24.21) and PTEN (10q23.31) deletion as well as CCND3 (6p21.1) and ERBB2 (17q12) amplification. MSC-1 displayed higher immunogenicity and immune infiltration. MSC-2 had better prognosis and significant stromal activation. Based on the two subtypes, we identified and validated the expression relationship of FAM83A and IDO1 as a robust biomarker for prognosis and distant metastasis of CRC in 15 independent cohorts and qRT-PCR assay. Conclusions: We identified two subtypes with heterogeneous molecular alterations and functional status, which might advance precise treatment and clinical management in CRC. A robust biomarker for predicting prognosis and distant metastasis of CRC was identified and validated.
Novel Uses of Three-Parameter Logistic Models and First-Derivative Models for the Coronavirus Disease (COVID-19) Epidemic in the United States, in Three Distinct Scenarios
Authors: Samuel Bishoy T. 
Published: November 2020

Abstract
Background:Forecasting the current coronavirus disease (COVID-19) epidemic in the United States necessitates novel mathematical models for accurate predictions. This paper examines novel uses of three-parameter logistic models and first-derivative models through three distinct scenarios that have not been examined in the literature as of July 14, 2020.Methods:Using publicly available data, statistical software was used to conduct a non-linear least-squares estimate to generate a three-parameter logistic model, with a subsequently generated first-derivative model. In the first scenario a logistic model was used to examine the natural log of COVID-19 cases as the dependent variable (versus day number), on July 11 and May 1. Independent t-test analyses were used to test comparative coefficient differences across models. In the second scenario, a first-derivative model was derived from a base three-parameter logistic model for April 27, examining time to peak mortality and decrease in case fatality rate. In the third scenario, a first-derivative model of mortality through July 11 as the dependent variable, versus confirmed cases, was generated to look at case fatality rate relative to increasing cases.Results:All models generated were statistically significant with R2 > 99%. The logistic models in the first scenario best predicted time to growth deceleration in the natural log of cases in the U.S. (slowing of exponential growth), estimated at March 11, 2020. For the May 1 data, independent t-test analyses of comparative coefficients across models were useful to track improvements from implemented public health measures. The first-derivative model in the second scenario on April 27, when the epidemic was more controlled, showed peak mortality around April 12-13, with a case fatality rate of < 1,000 deaths and trending down. The first-derivative model in the third scenario estimated a near-zero case fatality rate to occur at 4 million confirmed cases. It has not been affected by fluctuations in mortality from June 29 through July 11.Conclusion:Three-parameter logistic models and first-derivative models have utility in predicting time to growth deceleration, and case fatality rates relative to cases. They can objectively assess improvements of implemented epidemiologic measures and have applicable public health safety implications.
Design and Psychometric Evaluation of Mothers' Perception of Postpartum Care in Comprehensive Health Centers
Authors: Vizeshfar Fatemeh , Ahmadinezhad Maryam , Pakniat Azadeh 
Published: November 2020

Abstract
Background: In order to properly evaluate postpartum services in comprehensive health centers, encouraging women to use these services and presence of a reliable and valid tool, is necessary to design and assess mothers' perceptions of postpartum care.Aim: Designed to evaluate the psychometric dimensions of Iranian version of Mothers' Perception of Postpartum Health care Questionnaire at Comprehensive Health Centers. Methods: This is a cross-sectional study. The verbatim translation was used to translate the questionnaire from English to Persian. Face, content, and structural validity as well as reliability of the questionnaire were evaluated. Findings: The results showed that the face, content, and structure validity as well as reliability of this questionnaire to be appropriate. The calculated Cronbach's alpha coefficient for the whole questionnaire was 0.668. Interclass correlation coefficient was 0.688, which confirmed divergent validity.Conclusion: Mothers' Perception of Postpartum Health care Questionnaire at Comprehensive Health Centers is a valid and reliable questionnaire to measure mothers’ perceptions of these vital services.
Typhoon Eye Effect Vs. Ripple Effect: The Role of Family Size on the Mental Health Under the Covid-19 Pandemic in Pakistan
Authors: Lateef Tooba , Chen Jiyao , Tahir Muhammad , Lateef Teba Abdul , Chen Bryan , Li Jizhen , Zhang Stephen X 
Published: November 2020

Abstract
Background: The recent outbreak of COVID-19 impacts the mental health of people worldwide. The mental conditions and the associated predictors of adults in Pakistan, the fifth most populous country in the world, during the COVID-19 remains understudied. We aim to investigate distress, anxiety and overall mental health and their associated predictors among Pakistani adults in this pandemic. We specifically examine the mental health issues based on the distance to the epicenter, a predictor that has revealed opposing evidence in other countries based on the theories of typhoon eye effect and ripple effect. The samples consist of 601 adults who were surveyed online about 2.5 months into the outbreak across Pakistan with varying distance to the epicenter of COVID-19 of Karachi in Pakistan. Results: The results showed that 9.2% and 19.0% of the participants surpassed the cut-off of distress and anxiety disorders, respectively. Overall, the distance to the epicenter positively predicted the mental health of adults in Pakistan, and family size negatively moderated this effect. The distance to the epicenter negatively predicted distress and anxiety disorders for adults in large families, which are quite common in Pakistan. Conclusion: The evidence of the study interestingly finds the prediction of the mental health of people by their distance to the epicenter depends on the family. The evidence of this study can help to provide the initial indicator for mental health care providers to screen vulnerable groups in Pakistan, a populous country that continues to struggle to cope with the COVID-19 pandemic.
Early Gastric Cancer Lymph Node Metastasis Model and Prognostic Survival Prediction Model in Western Population
Authors: Tian Huakai , Zhang Zuo , Liu Zitao , Hu Cegui , Liu Jiang , Xu Tian , Zong Zhen 
Published: November 2020

Abstract
Objective This study analyzed the characteristics of early gastric cancer lymph node metastasis and survival prognosis after surgical resection in western population, and established a predictive model.MethodsPatients with stage T1a and T1b gastric cancer from 2010 to 2015 were screened from the surveillance, epidemiology and final outcome databases. Patients with multiple in situ tumors, distant metastases, and incomplete data were excluded. The risk factors for lymph node metastasis in early gastric cancer were analyzed by binary logistic regression and the chi-square test. Multivariate Cox analysis and the Kaplan-Meier test were used to evaluate the prognostic factors and survival rates of patients with early gastric cancer after surgical resection. The prediction model of lymph node metastasis and survival rate of early gastric cancer was established and verified by R software.ResultsIn 2294 patients, the lymph node metastasis rate was 14.5% (333/2294). Binary logistic multivariate regression analysis showed that tumor size (>2cm), tumor grade (III/IV), and stage T1b were risk factors for lymph node metastasis of early gastric cancer. Area under the curve (AUC) is 0.782.A predictive model was developed based on risk factors, and the model C index was 0.771, indicating that the model has good predictive ability. In addition, survival analysis of 2294 patients showed that the 5-year OS and CSS (75.4% and 88.7%) in patients without EGC were significantly higher than those with lymph node metastasis (64.3% and 72.8%) (P<0.05). Multivariate COX analysis showed that age, sex, race, tumor size, submucosal invasion and lymph node metastasis were independent factors influencing the prognosis of early gastric cancer. A cancer-specific survival (CSS) prediction model was constructed based on prognostic risk factors. The 3-year area under the CSS curve (AUC) was 0.706, and the 5-year area under the CSS curve (AUC) was 0.710. The prediction model is more consistent with the actual situation.ConclusionsWe established a reliable prediction model for lymph node metastasis of early gastric cancer and a prognostic model for early gastric cancer, which provided a good basis for clinical treatment decision.
Informational Cost and Networks Navigability
Authors: Estrada Ernesto 
Published: November 2020

Abstract
Understanding how information navigates through nodes of a complex network has become an increasingly pressing problem across scientific disciplines. Several approaches have been proposed on the basis of shortest paths or diffusive navigation. However, no existing approaches have tackled the challenges of efficient communication in networks without full knowledge of their global topology under external noise. Here, we develop a first principles approach to determine the informational cost of navigating a network under different levels of external noise. We discover the existence of a trade-off between the ways in which networks route information through shortest paths, their entropies and stability, which define three classes of real-world networks. This approach reveals that environmental pressure has shaped the ways in which information is transferred in bacterial metabolic networks and allowed us to determine the levels of noise at which a protein-protein interaction network seems to work in normal conditions in a cell.
Auto Classification of Biomass through Characterization of their Pyrolysis Behaviors by using Thermogravimetric Analysis with Support Vector Machine Algorithm: Case Study for Tobacco
Authors: Yin Chao , Deng Xiaohua , Yu Zhiqiang , Chen Ruting , Zhong Hongxiang , Liu Zechun , Cai Guohua , Zheng Quanxing , Liu Xiucai , Zhong Jiawei , Ma Pengfei , He Wei , Lin Kai , Li Qiaoling , Wu Anan 
Published: November 2020

Abstract
Background: During the biomass-to-bio-oil conversion process, many researches focus on the study of the association between the biomass and the bio-products by using near infrared spectra (NIR) and chemical analysis method. However, the characterization of biomass pyrolysis behaviors by using thermogravimetric analysis (TGA) with support vector machine (SVM) algorithm has not been reported. In this study, tobacco was chosen as the object for biomass, because the cigarette smoke (including water, tar and gases) released by tobacco pyrolysis reactions decide the sensory quality, which is similar to the use of biomass as a renewable resource through the pyrolysis process. Results: Support vector machine (SVM) has been employed to automatically classify the planting area and growing position of tobacco leaves by using thermogravimetric analysis data as the information source for the first time. 88 single-grade tobacco samples belonging to 4 grades and 8 categories were split into the training, validation and blind testing set. Our model showed excellent performances in both the training and validation set as well as in the blind test, with accuracy over 91.67%. Throughout the whole dataset of 88 samples, our model not only provides precise results on the planting area of tobacco leave, but also accurately distinguishes the major grades among the upper, lower and middle positions. Error only occurs in the classification of subgrades of the middle position. Conclusions: Our results not only validated the feasibility of using thermogravimetric analysis with SVM algorithm as an objective and rapid method for automatic classification of tobacco planting area and growing position, but also showed this new analysis method would be a promising way to exploring bio-oil quality prior to biomass pyrolysis production.
Atypical Meningioma in the Medulla Oblongata Parenchyma
Authors: Xu Qiushi , Pan Ziang , Hou Meidan , Peng Fang 
Published: November 2020

Abstract
Background: Glioma is the most common tumor occurring in the brainstem. A primary intraparenchymal meningioma located in the brainstem without dura attachment is rare. Meanwhile, atypical meningiomas that occur in the medulla oblongata parenchyma, and without dura coverage, are extremely rare. In this study, we report the first case of atypical meningioma in the medulla oblongata parenchyma and review the existing literature.Case presentation: A 38-year-old female was admitted at our hospital with a 2-week history of progressive neck and occipital pain. Magnetic resonance imaging revealed a presence of a 1.5x0.9cm mass lesion, located in the left side of the medulla oblongata, which was hypointense on T1-weighted and hyperintense on T2-weighted images, and with inhomogeneous enhancement following gadolinium-diethylenet-riamine pentaacetic acid (Gd-DTPA) administration. The initial preoperative diagnosis was glioma or angioblastoma. The patient underwent a total surgical resection of the left medulla oblongata tumor and the histopathological examination indicated that the lesion was an atypical meningioma. The patient returned to normal life after surgery.Conclusions: Although glioma is the most common tumor occurring in the brainstem parenchyma, the possibility of meningioma cannot be ruled out in this area.