bluuebunny/crossref_metadata_2025 huggingface dataset:
Brain White Matter: A Substrate for Resilience and a Substance for Subcortical Small Vessel Disease
Authors: Sorond Farzaneh A. , Gorelick Philip B.
Published: August 2019

Age-related brain white matter disease is a form of small vessel disease (SVD) that may be associated with lacunar and other small subcortical infarcts, cerebral microbleeds, and perivascular spaces. This common form of cerebrovascular disease may manifest clinically as cognitive impairment of varying degrees and difficulty with mobility. Whereas some persons show cognitive decline and mobility failure when there are brain white matter hyperintensities (WMH) and acute stroke, others recover, and not everyone with brain white matter disease is disabled. Thus, repair or compensation of brain white matter may be possible, and furthermore, certain vascular risks, such as raised blood pressure, are targets for prevention of white matter disease or are administered to reduce the burden of such disease. Vascular risk modification may be useful, but alone may not be sufficient to prevent white matter disease progression. In this chapter, we specifically focus on WMH of vascular origin and explore white matter development, plasticity, and enduring processes of myelination across the health span in the context of experimental and human data, and compare and contrast resilient brain white matter propensity to a diseased white matter state. We conclude with thoughts on novel ways one might study white matter resilience, and predict future healthy cognitive and functional outcomes.
EMT and Stemness—Key Players in Pancreatic Cancer Stem Cells
Authors: Rodriguez-Aznar Eva , Wiesmüller Lisa , Sainz Bruno , Hermann Patrick C.
Published: August 2019

Metastasis and tumor progression are the major cause of death in patients suffering from pancreatic ductal adenocarcinoma. Tumor growth and especially dissemination are typically associated with activation of an epithelial-to-mesenchymal transition (EMT) program. This phenotypic transition from an epithelial to a mesenchymal state promotes migration and survival both during development and in cancer progression. When re-activated in pathological contexts such as cancer, this type of developmental process confers additional stemness properties to specific subsets of cells. Cancer stem cells (CSCs) are a subpopulation of cancer cells with stem-like features that are responsible for the propagation of the tumor as well as therapy resistance and cancer relapse, but also for circulating tumor cell release and metastasis. In support of this concept, EMT transcription factors generate cells with stem cell properties and mediate chemoresistance. However, their role in pancreatic ductal adenocarcinoma metastasis remains controversial. As such, a better characterization of CSC populations will be crucial in future development of therapies targeting these cells. In this review, we will discuss the latest updates on the mechanisms common to pancreas development and CSC-mediated tumor progression.
Inclusion of Platinum Agents in Neoadjuvant Chemotherapy Regimens for Triple-Negative Breast Cancer Patients: Development of GRADE (Grades of Recommendation, Assessment, Development and Evaluation) Recommendation by the Italian Association of Medical Oncology (AIOM)
Authors: Dieci Maria Vittoria , Del Mastro Lucia , Cinquini Michela , Montemurro Filippo , Biganzoli Laura , Cortesi Laura , Zambelli Alberto , Criscitiello Carmen , Levaggi Alessia , Conte Benedetta , Calabrese Massimo , Fiorentino Alba , Marchiò Caterina , Tinterri Corrado , Fittipaldo Veronica Andrea , Pappagallo Giovanni , Gori Stefania
Published: August 2019

In the absence of identified therapeutic targets, chemotherapy is the main systemic treatment option for triple-negative breast cancer (TNBC). The achievement of a pathological complete response (pCR) after neoadjuvant chemotherapy leads to good outcome, whereas patients not achieving a pCR are at high risk of relapse. Various trials have evaluated the inclusion of platinum in neoadjuvant chemotherapy regimens for TNBC, leading to non-univocal results. The panel of the Italian Association of Medical Oncology (AIOM) Guidelines on Breast Cancer developed a clinical recommendation on the addition of platinum to anthracycline/taxane-based neoadjuvant chemotherapy for TNBC by using the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) methodology and the Evidence to Decision framework (EtD). Five studies were eligible. The panel identified the following outcomes of benefit: pCR (critical), disease/event-free survival (DFS/EFS, critical), and overall survival (OS, critical). The panel identified febrile neutropenia (critical), serious adverse events (critical), anemia grade 3–4 (important), thrombocytopenia grade 3–4 (important) as outcomes of harms. The probability of pCR was higher in the platinum-based chemotherapy group versus control group (RR = 1.45, 95%CI 1.28–1.64); however, no impact on long-term outcome was observed. Neoadjuvant treatment regimens containing platinum resulted in a non-significant increase in the risk of febrile neutropenia and in a significant increase in the risk serious adverse events, G3–G4 anemia and G3–G4 thrombocytopenia: 11.3% versus 0.8%, RR = 15.66 (95%CI 6.38–38.44). The panel judged uncertain/favorable the benefit/harms balance. The panel’s final recommendation was conditional in favor of the inclusion of platinum in anthracycline/taxane-based neoadjuvant regimens for TNBC.
Catalytic Processes for The Valorization of Biomass Derived Molecules
Authors: Espro Claudia , Mauriello Francesco
Published: August 2019

Industrial chemistry is changing its fossil distinctiveness into a new green identity by using renewable resources [...]
Gel-Type and Macroporous Cross-Linked Copolymers Functionalized with Acid Groups for the Hydrolysis of Wheat Straw Pretreated with an Ionic Liquid
Authors: Lavarda Giulia , Morales-delaRosa Silvia , Centomo Paolo , Campos-Martin Jose M. , Zecca Marco , Fierro Jose L. G.
Published: August 2019

Several sulfonated cross-linked copolymers functionalized with hydroxyl and carboxylic groups have been synthesized. The amount of the cross-linking monomer was tailored (from 4% up to 40%) to tune the resulting micro- and nano-morphologies, and two types of catalysts, namely, gel-type and macroreticular catalysts, were obtained. These copolymers were employed in the catalytic hydrolysis of wheat straw pretreated in 1-ethyl-3-methylimidazolium acetate to obtain sugars. Remarkably, the presence of additional oxygenated groups enhances the catalytic performances of the polymers by favoring the adsorption of β-(1,4)-glucans and makes these materials significantly more active than an acidic resin bearing only sulfonic groups (i.e., Amberlyst 70). In addition, the structure of the catalyst (gel-type or macroreticular) appears to be a determining factor in the catalytic process. The gel-type structure provides higher glucose concentrations because the morphology in the swollen state is more favorable in terms of the accessibility of the catalytic centers. The observed catalytic behavior suggests that the substrate diffuses within the swollen polymer matrix and indirectly confirms that the pretreatment based on dissolution/precipitation in ionic liquids yields a substantial enhancement of the conversion of lignocellulosic biomass to glucose in the presence of heterogeneous catalysts.
Mitochondria and Female Germline Stem Cells—A Mitochondrial DNA Perspective
Authors: St. John Justin C.
Published: August 2019

Mitochondria and mitochondrial DNA have important roles to play in development. In primordial germ cells, they progress from small numbers to populate the maturing oocyte with high numbers to support post-fertilization events. These processes take place under the control of significant changes in DNA methylation and other epigenetic modifiers, as well as changes to the DNA methylation status of the nuclear-encoded mitochondrial DNA replication factors. Consequently, the differentiating germ cell requires significant synchrony between the two genomes in order to ensure that they are fit for purpose. In this review, I examine these processes in the context of female germline stem cells that are isolated from the ovary and those derived from embryonic stem cells and reprogrammed somatic cells. Although our knowledge is limited in this respect, I provide predictions based on other cellular systems of what is expected and provide insight into how these cells could be used in clinical medicine.
Roles of JAK2 in Aging, Inflammation, Hematopoiesis and Malignant Transformation
Authors: Perner Florian , Perner Caroline , Ernst Thomas , Heidel Florian H.
Published: August 2019

Clonal alterations in hematopoietic cells occur during aging and are often associated with the establishment of a subclinical inflammatory environment. Several age-related conditions and diseases may be initiated or promoted by these alterations. JAK2 mutations are among the most frequently mutated genes in blood cells during aging. The most common mutation within the JAK2 gene is JAK2-V617F that leads to constitutive activation of the kinase and thereby aberrant engagement of downstream signaling pathways. JAK2 mutations can act as central drivers of myeloproliferative neoplasia, a pre-leukemic and age-related malignancy. Likewise, hyperactive JAK-signaling is a hallmark of immune diseases and critically influences inflammation, coagulation and thrombosis. In this review we aim to summarize the current knowledge on JAK2 in clonal hematopoiesis during aging, the role of JAK-signaling in inflammation and lymphocyte biology and JAK2 function in age-related diseases and malignant transformation.
The Effects of Adipocytes on the Regulation of Breast Cancer in the Tumor Microenvironment: An Update
Authors: Chu Dinh-Toi , Nguyen Thi Phuong Thuy , Tien Nguyen Le Bao , Tran Dang-Khoa , Nguyen Tran-Thuy , Thanh Vo Van , Luu Quang Thuy , Minh Le Bui , Pham Van Huy , Ngoc Vo Truong Nhu , Kushekhar Kushi , Chu-Dinh Thien
Published: August 2019

Obesity is a global pandemic and it is well evident that obesity is associated with the development of many disorders including many cancer types. Breast cancer is one of that associated with a high mortality rate. Adipocytes, a major cellular component in adipose tissue, are dysfunctional during obesity and also known to promote breast cancer development both in vitro and in vivo. Dysfunctional adipocytes can release metabolic substrates, adipokines, and cytokines, which promote proliferation, progression, invasion, and migration of breast cancer cells. The secretion of adipocytes can alter gene expression profile, induce inflammation and hypoxia, as well as inhibit apoptosis. It is known that excessive free fatty acids, cholesterol, triglycerides, hormones, leptin, interleukins, and chemokines upregulate breast cancer development. Interestingly, adiponectin is the only adipokine that has anti-tumor properties. Moreover, adipocytes are also related to chemotherapeutic resistance, resulting in the poorer outcome of treatment and advanced stages in breast cancer. Evaluation of the adipocyte secretion levels in the circulation can be useful for prognosis and evaluation of the effectiveness of cancer therapy in the patients. Therefore, understanding about functions of adipocytes as well as obesity in breast cancer may reveal novel targets that support the development of new anti-tumor therapy. In this systemic review, we summarize and update the effects of secreted factors by adipocytes on the regulation of breast cancer in the tumor microenvironment.
A Model of Perception of Privacy, Trust, and Self-Disclosure on Online Social Networks
Authors: Nemec Zlatolas Lili , Welzer Tatjana , Hölbl Marko , Heričko Marjan , Kamišalić Aida
Published: August 2019

Online Social Networks are used widely, raising new issues in terms of privacy, trust, and self-disclosure. For a better understanding of these issues for Facebook users, a model was built that includes privacy value, privacy risk, trust, privacy control, privacy concerns, and self-disclosure. A total of 602 respondents participated in an online survey, and structural equation modeling was used to evaluate the model. The findings indicate significant relationships between the constructs in this study. The model from our study contributes new knowledge to privacy issues, trust and self-disclosure on Online Social Networks for other researchers or developers of online social networks.
A New Technique Based on Voronoi Tessellation to Assess the Space-Dependence of Categorical Variables
Authors: Zufiria Pedro J. , Hernández-Medina Miguel Á.
Published: August 2019

Based on a sample of geolocated elements, each of them labeled with a (not necessarily ordered) categorical feature, several indexes for assessing the relationship between the geolocation variables (latitude and longitude) and the categorical variable are evaluated. Among these indexes, a new one based on a Voronoi tessellation presents several advantages since it does not require a variable transformation or a previous discretization; in addition, simulations show that this index is considerably robust when compared with the previously known ones. Finally, the use of the presented indexes is also illustrated by analyzing the geolocation of communities in some communication networks derived from Call Detail Records.
Maximum Entropy Analysis of Flow Networks: Theoretical Foundation and Applications
Authors: Niven Robert K. , Abel Markus , Schlegel Michael , Waldrip Steven H.
Published: August 2019

The concept of a “flow network”—a set of nodes and links which carries one or more flows—unites many different disciplines, including pipe flow, fluid flow, electrical, chemical reaction, ecological, epidemiological, neurological, communications, transportation, financial, economic and human social networks. This Feature Paper presents a generalized maximum entropy framework to infer the state of a flow network, including its flow rates and other properties, in probabilistic form. In this method, the network uncertainty is represented by a joint probability function over its unknowns, subject to all that is known. This gives a relative entropy function which is maximized, subject to the constraints, to determine the most probable or most representative state of the network. The constraints can include “observable” constraints on various parameters, “physical” constraints such as conservation laws and frictional properties, and “graphical” constraints arising from uncertainty in the network structure itself. Since the method is probabilistic, it enables the prediction of network properties when there is insufficient information to obtain a deterministic solution. The derived framework can incorporate nonlinear constraints or nonlinear interdependencies between variables, at the cost of requiring numerical solution. The theoretical foundations of the method are first presented, followed by its application to a variety of flow networks.
Power, Efficiency and Fluctuations in a Quantum Point Contact as Steady-State Thermoelectric Heat Engine
Authors: Kheradsoud Sara , Dashti Nastaran , Misiorny Maciej , Potts Patrick , Splettstoesser Janine , Samuelsson Peter
Published: August 2019

The trade-off between large power output, high efficiency and small fluctuations in the operation of heat engines has recently received interest in the context of thermodynamic uncertainty relations (TURs). Here we provide a concrete illustration of this trade-off by theoretically investigating the operation of a quantum point contact (QPC) with an energy-dependent transmission function as a steady-state thermoelectric heat engine. As a starting point, we review and extend previous analysis of the power production and efficiency. Thereafter the power fluctuations and the bound jointly imposed on the power, efficiency, and fluctuations by the TURs are analyzed as additional performance quantifiers. We allow for arbitrary smoothness of the transmission probability of the QPC, which exhibits a close to step-like dependence in energy, and consider both the linear and the non-linear regime of operation. It is found that for a broad range of parameters, the power production reaches nearly its theoretical maximum value, with efficiencies more than half of the Carnot efficiency and at the same time with rather small fluctuations. Moreover, we show that by demanding a non-zero power production, in the linear regime a stronger TUR can be formulated in terms of the thermoelectric figure of merit. Interestingly, this bound holds also in a wide parameter regime beyond linear response for our QPC device.
The Rényi Entropies Operate in Positive Semifields
Authors: Valverde-Albacete Francisco J. , Peláez-Moreno Carmen
Published: August 2019

We set out to demonstrate that the Rényi entropies are better thought of as operating in a type of non-linear semiring called a positive semifield. We show how the Rényi’s postulates lead to Pap’s g-calculus where the functions carrying out the domain transformation are Rényi’s information function and its inverse. In its turn, Pap’s g-calculus under Rényi’s information function transforms the set of positive reals into a family of semirings where “standard” product has been transformed into sum and “standard” sum into a power-emphasized sum. Consequently, the transformed product has an inverse whence the structure is actually that of a positive semifield. Instances of this construction lead to idempotent analysis and tropical algebra as well as to less exotic structures. We conjecture that this is one of the reasons why tropical algebra procedures, like the Viterbi algorithm of dynamic programming, morphological processing, or neural networks are so successful in computational intelligence applications. But also, why there seem to exist so many computational intelligence procedures to deal with “information” at large.
Optimal Multi-Step-Ahead Prediction of ARCH/GARCH Models and NoVaS Transformation
Authors: Chen Jie , Politis Dimitris N.
Published: August 2019

This paper gives a computer-intensive approach to multi-step-ahead prediction of volatility in financial returns series under an ARCH/GARCH model and also under a model-free setting, namely employing the NoVaS transformation. Our model-based approach only assumes i . i . d innovations without requiring knowledge/assumption of the error distribution and is computationally straightforward. The model-free approach is formally quite similar, albeit a GARCH model is not assumed. We conducted a number of simulations to show that the proposed approach works well for both point prediction (under L 1 and/or L 2 measures) and prediction intervals that were constructed using bootstrapping. The performance of GARCH models and the model-free approach for multi-step ahead prediction was also compared under different data generating processes.
Stochastic Dynamic Analysis of an Offshore Wind Turbine Structure by the Path Integration Method
Authors: Zhao Yue , Lian Jijian , Lian Chong , Dong Xiaofeng , Wang Haijun , Liu Chunxi , Jiang Qi , Wang Pengwen
Published: August 2019

Stochastic dynamic analysis of an offshore wind turbine (OWT) structure plays an important role in the structural safety evaluation and reliability assessment of the structure. In this paper, the OWT structure is simplified as a linear single-degree-of-freedom (SDOF) system and the corresponding joint probability density function (PDF) of the dynamic response is calculated by the implementation of the path integration (PI) method. Filtered Gaussian white noise, which is obtained from the utilization of a second-order filter, is considered as horizontal wind excitation and used to excite the SDOF system. Thus, the SDOF model and the second-order linear filter model constitute a four-dimensional dynamic system. Further, a detailed three-dimensional finite element model is applied to obtain the natural frequency of the OWT and the efficient PI method, which is modified based on the fast Fourier transform (FFT) convolution method, is also utilized to reduce the execution time to obtain the PDF of the response. Two important parameters of wind conditions, i.e., horizontal mean wind speed and turbulence standard deviation, are investigated to highlight the influences on the PDF of the dynamic response and the reliability of the OWT.
Analysis of Influencing Factors and Trend Forecast of Carbon Emission from Energy Consumption in China Based on Expanded STIRPAT Model
Authors: Li Zhen , Li Yanbin , Shao Shuangshuang
Published: August 2019

With the convening of the annual global climate conference, the issue of global climate change has gradually become the focus of attention of the international community. As the largest carbon emitter in the world, China is facing a serious situation of carbon emission reduction. This paper uses the IPCC (The Intergovernmental Panel on Climate Change) method to calculate the carbon emissions of energy consumption in China from 1996 to 2016, and uses it as a dependent variable to analyze the influencing factors. In this paper, five factors, total population, per capita GDP (Gross Domestic Product), urbanization level, primary energy consumption structure, technology level, and industrial structure are selected as the influencing factors of carbon emissions. Based on the expanded STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) model, the influencing degree of different factors on carbon emissions of energy consumption is analyzed. The results show that the order of impact on carbon emissions from high to low is total population, per capita GDP, technology level, industrial structure, primary energy consumption structure, and urbanization level. On the basis of the above research, the carbon emissions of China′s energy consumption in the future are predicted under eight different scenarios. The results show that, when the population and economy keep a low growth rate, while improving the technology level can effectively control carbon emissions from energy consumption, China′s carbon emissions from energy consumption will reach 302.82 million tons in 2020.
Performance Evaluation of Energy Transition Based on the Technique for Order Preference by a Similar to Ideal Solution and Support Vector Machine Optimized by an Improved Artificial Bee Colony Algorithm
Authors: Li Zhen , Li Yun , Li Yanbin
Published: August 2019

Energy transition is an important factor when dealing with climate change and energy crisis under resource constraints. The performance evaluation of it is significant for improving and promoting the process of energy transition. This paper explores the application of the support vector machine improved by the artificial bee colony algorithm (IABC-SVM) method in the energy transition performance evaluation process. It provides an intelligent evaluation tool for the evaluation of the regional energy transition performance. Firstly, the evaluation indicator system of energy transition is constructed from five dimensions: energy supply, demand, efficiency, institution, and environment. Then, the technique for order preference by a similar to ideal solution improved by a combination weighting (CW-TOPSIS) method and IABC-SVM are constructed. After that, according to the evaluation values of 30 provinces in China calculated by CW-TOPSIS, 10-fold cross validation is used to compare the errors of support vector machine (SVM), support vector machine optimized by the artificial bee colony algorithm (ABC-SVM), and IABC-SVM, which proves the effectiveness and accuracy of IABC-SVM in evaluating the performance of energy transition. Finally, the IABC-SVM is used to evaluate the energy transition performance of 30 provinces in 2016. Through a comparative analysis, the relevant suggestions of energy transition are put forward.
Proof-of-Concept of Spent Mushrooms Compost Torrefaction—Studying the Process Kinetics and the Influence of Temperature and Duration on the Calorific Value of the Produced Biocoal
Authors: Syguła Ewa , Koziel Jacek , Białowiec Andrzej
Published: August 2019

Poland, being the 3rd largest and growing producer of mushrooms in the world, generates almost 25% of the total European production. The generation rate of waste mushroom spent compost (MSC) amounts to 5 kg per 1 kg of mushrooms produced. We proposed the MSC treatment via torrefaction for the production of solid fuel—biocoal. In this research, we examined the MSC torrefaction kinetics using thermogravimetric analyses (TGA) and we tested the influence of torrefaction temperature within the range from 200 to 300 °C and treatment time lasting from 20 to 60 min on the resulting biocoal’s (fuel) properties. The estimated value of the torrefaction activation energy of MSC was 22.3 kJ mol−1. The highest calorific value = 17.9 MJ kg−1 d.m. was found for 280 °C (60 min torrefaction time). A significant (p < 0.05) influence of torrefaction temperature on HHV increase within the same group of torrefaction duration, i.e., 20, 40, or 60 min, was observed. The torrefaction duration significantly (p < 0.05) increased the HHV for 220 °C and decreased HHV for 300 °C. The highest mass yield (98.5%) was found for 220 °C (60 min), while the highest energy yield was found for 280 °C (60 min). In addition, estimations of the biocoal recirculation rate to maintain the heat self-sufficiency of MSC torrefaction were made. The net quantity of biocoal (torrefied MSC; 65.3% moisture content) and the 280 °C (60 min) torrefaction variant was used. The initial mass and energy balance showed that MSC torrefaction might be feasible and self-sufficient for heat when ~43.6% of produced biocoal is recirculated to supply the heat for torrefaction. Thus, we have shown a concept for an alternative utilization of abundant biowaste (MSC). This research provides a basis for alternative use of an abundant biowaste and can help charting improved, sustainable mushroom production.
Effects of Mechanical Site Preparation on Microsite Availability and Growth of Planted Black Spruce in Canadian Paludified Forests
Authors: Henneb Mohammed , Valeria Osvaldo , Thiffault Nelson , Fenton Nicole J. , Bergeron Yves
Published: August 2019

Low productivity caused by paludification in some parts of the closed black spruce (Picea mariana (Mill.) B.S.P) dominated boreal forest threatens the provision of ecosystem services, including wood fiber production. The accumulation, over time, of organic matter in paludified soils leads to an anaerobic environment that reduces microbial activity, decelerates decomposition of organic matter, and generates nutrient-poor microsites for regeneration. Consequently, it results in significant impacts on site productivity. Considering its ability to disturb the soil, mechanical site preparation (MSP) is viewed as a potential treatment that can help restore productivity of paludified sites following harvesting. We conducted a field experiment to verify if (1) the availability of microsites conducive to reforestation varies with MSP, microtopography (slope and aspect) and initial OLT conditions; (2) the growth of planted seedlings depends on the intensity of mechanical disturbance of the organic layer, type of microsite, planting density, presence of Ericaceae, and the planting position and depth; (3) there are direct and indirect causal relationships between microsites availability after MSP, OLT, microtopography, planting quality and seedlings growth; and (4) if mechanical site preparation and microsite type exposed affect the Ericaceae cover after planting. Our results confirmed that MSP is effective in establishing conditions that permit a productive regeneration cohort on these paludified sites. To ensure successful establishment of plantations on these sites, it is necessary, however, to distinguish between those that are slightly or moderately paludified from those that are highly paludified, as treatment effectiveness of different MSP types depends on organic layer thickness. Our results also show that preference should be given to some microsite types as clay and mixed-substrate microsites for planting to ensure sufficient availability of water and nutrients for seedlings.
Genomic Regions Associated with IgE Levels against Culicoides spp. Antigens in Three Horse Breeds
Authors: François Liesbeth , Hoskens Hanne , Velie Brandon D. , Stinckens Anneleen , Tinel Susanne , Lamberigts Chris , Peeters Liesbet , Savelkoul Huub F. J. , Tijhaar Edwin , Lindgren Gabriella , Janssens Steven , Ducro Bart J. , Buys Nadine , Schurink Anouk
Published: August 2019

Insect bite hypersensitivity (IBH), which is a cutaneous allergic reaction to antigens from Culicoides spp., is the most prevalent skin disorder in horses. Misdiagnosis is possible, as IBH is usually diagnosed based on clinical signs. Our study is the first to employ IgE levels against several recombinant Culicoides spp. allergens as an objective, independent, and quantitative phenotype to improve the power to detect genetic variants that underlie IBH. Genotypes of 200 Shetland ponies, 127 Icelandic horses, and 223 Belgian Warmblood horses were analyzed while using a mixed model approach. No single-nucleotide polymorphism (SNP) passed the Bonferroni corrected significance threshold, but several regions were identified within and across breeds, which confirmed previously identified regions of interest and, in addition, identifying new regions of interest. Allergen-specific IgE levels are a continuous and objective phenotype that allow for more powerful analyses when compared to a case-control set-up, as more significant associations were obtained. However, the use of a higher density array seems necessary to fully employ the use of IgE levels as a phenotype. While these results still require validation in a large independent dataset, the use of allergen-specific IgE levels showed value as an objective and continuous phenotype that can deepen our understanding of the biology underlying IBH.
Citizenship’s Insular Cases, from Ancient Greece and Rome to Puerto Rico
Authors: Peralta Dan-el Padilla
Published: August 2019

Engaging equally with ancient Greco-Roman and contemporary Euro-American paradigms of citizenship, this essay argues that experiences of civic integration are structured around figurations of island and archipelago. In elaboration of this claim, I offer a transhistorical account of how institutions and imaginaries of citizenship take shape around an “insular scheme” whose defining characteristic is displacement. Shuttling from Homer and Livy to Imbolo Mbue and Danez Smith, I rely on the work of postcolonial literary critics and political theorists to map those repetitive deferrals of civic status to which immigrants and refugees in particular are uniquely subject.
A Quantitative Approach to Evaluate Changes in Hydrologic Conditions of Headwater Streams: A Case Study of Restoration and Recovery Following Longwall Mine Subsidence
Authors: Silvis Joshua M. , Benson Brian C. , Shema Michael L. , Haibach Mark R.
Published: August 2019

Mine subsidence can induce streambed ruptures that pirate surface water from a stream. Current understanding of the effects of longwall mining on streams lacks rigorous analytical approaches to detect hydrologic effects and does not consider the efficacy of streambed restoration techniques to address flow disruption. CONSOL Pennsylvania Coal Company, LLC (CPCC) collected and analyzed pre-mining, post-mining, and post-restoration stream discharge and flow duration data from 51.9 km of streams overlying its Bailey Mine to define pre-mining flow variability, detect post-mining changes, and evaluate post-intervention flow recovery. The primary intervention method for restoring stream flow was bedrock permeation grouting. Pre-mine and post-mine baseflow data were compared using both parametric and non-parametric hypothesis testing, which yielded similar results. An environmental flow assessment method for headwater streams using probabilistic risk assessment and correlation analysis of change threshold criteria was developed to differentiate hydrologic change as induced by mine subsidence or explained by natural variability. The method is objective, pragmatic, and statistically delimited.
Factors Associated with Marital Satisfaction and Quality of Life in Family Caregivers of Patients with Mental Disorders
Authors: Nogueira Douglas José , Minamisava Ruth , Teles Sheila Araujo , Souza Sandra Maria Brunini de , Cordeiro Jacqueline Andréia Bernardes Leão , Cirqueira Denise Soares de , Brasil Virginia Visconde , Souza Ana Lúcia Rezende , Caetano Karlla Antonieta Amorim , Oliveira Lizete Malagoni de Almeida Cavalcante , Lago Diane Maria Scherer Kuhn , Barbosa Maria Alves
Published: August 2019

(1) Background: The aim of this research was to analyze factors associated with quality of life (QoL) and marital satisfaction in married family caregivers of patients with mental disorders. (2) Methods: A cross-sectional study was conducted in all community mental health services in Goiania municipality, Brazil, in 2016–2017. Married family caregivers of patients with severe and persistent mental disorders were recruited and their QoL and marital satisfaction was assessed by using the World Health Organization Quality of Life Instrument Abbreviated version (WHOQOL-BREF) and Marital Satisfaction Scale. Multiple linear regressions were performed to identify factors associated with QoL and marital satisfaction. (3) Results: For 163 family caregivers, the psychological and environmental QoL domains presented the best and the worst scores, respectively. Factors independently associated with better QoL for caregivers were male caregiver, the younger age of a caregiver, >8 years of schooling, ≥5 years as a caregiver who performed physical activities, caregiver without chronic disease, and no patient’s crisis in the last 30 days. Factors independently associated with marital satisfaction of the caregiver were male caregiver, caregiver with >8 years of schooling, caregiver who received support by relatives to care for the patient, caregiver who performed physical activities, no patient’s crisis in the last 30 days, and patient hospitalization in the last six months; (4) Conclusions: The main predictor for marital satisfaction was support by relatives, and for QoL it was no patient’s crisis in the last 30 days.
The Association of Peer Smoking Behavior and Social Support with Quit Success in Employees Who Participated in a Smoking Cessation Intervention at the Workplace
Authors: van den Brand Floor A. , Nagtzaam Puck , Nagelhout Gera E. , Winkens Bjorn , van Schayck Constant P.
Published: August 2019

The current study investigated whether quit success among employees who participated in a smoking cessation intervention at the workplace was associated with social support from, and the smoking behavior of, people in their environment. Tobacco-smoking employees (n = 604) from 61 companies participated in a workplace group smoking cessation program. Participants completed questionnaires assessing social support from, and the smoking behavior of, people in their social environment. They were also tested for biochemically validated continuous abstinence directly after finishing the training and after 12 months. The data were analyzed using mixed-effects logistic regression analyses. Social support from colleagues was positively associated with 12-month quit success (odds ratio (OR) = 1.85, 95% confidence interval (CI) = 1.14–3.00, p = 0.013). Support from a partner was positively associated with short-term quit success (OR = 2.01, 95% CI = 1.23–3.30, p = 0.006). Having a higher proportion of smokers in the social environment was negatively associated with long-term abstinence (OR = 0.81, 95% CI = 0.71–0.92, p = 0.002). Compared to having a non-smoking partner, long-term quit success was negatively associated with having no partner (OR = 0.48, 95% CI = 0.26–0.88, p < 0.019), with having a partner who smokes (OR = 0.40, 95% CI = 0.24–0.66, p < 0.001), and with having a partner who used to smoke (OR = 0.47, 95% CI = 0.26–0.86, p = 0.014). In conclusion, people in a smoker’s social environment, particularly colleagues, were strongly associated with quit success. The workplace may, therefore, be a favorable setting for smoking cessation interventions.
Evaluation of Occupational Exposure to Perchlorethylene in a Group of Italian Dry Cleaners Using Noninvasive Exposure Indices
Authors: Modenese Alberto , Gioia Tiziana Concetta , Chiesi Andrea , Abbacchini Carlotta , Borsari Lucia , Ferrari Davide , De Pasquale Fabrizio , Di Rico Renato , Ricci Raffaella , Sala Antonella , Gianaroli Ennio , Predieri Guerrino , Verri Sara , Gobba Fabriziomaria
Published: August 2019

Recent data suggest a general trend in decreased occupational exposure to perchlorethylene (PCE) in the dry-cleaning sector. The aims of this study were to confirm this trend to lower exposure levels in a group of Italian dry cleaners and to evaluate the current occupational PCE exposure in these works using noninvasive biological indices. Environmental exposure was assessed by personal sampling in 60 operators working in 21 dry cleaning shops in North Italy. PCE in the exhaled alveolar air (PCEalv), urinary concentration of PCE and of trichloroacetic acid (TCA) (PCEu and TCAu respectively), were measured as biological exposure indices. Median PCE environmental concentration in the whole sample was 10.6 mg/m3 (i.e., less than the 25% of the levels measured in the same area in a previous study). All values were less than 10% of the occupational limits. PCEu measured in samples collected at the end of the work shift resulted the biological markers having the strongest correlation with environmental PCE (r = 0.81). PCEalv also resulted in a high correlation (r = 0.66), while a lower correlation was found for TCAu measured at the end shift (r = 0.32). According to our results, PCEu can be proposed as a valid, noninvasive, and easily reliable exposure index to evaluate PCE exposure at the low levels currently observed in dry cleaners, therefore representing a promising alternative to invasive blood sample collections needed to determine PCE blood concentration.
Unmethylated Insulin as an Adjunctive Marker of Beta Cell Death and Progression to Type 1 Diabetes in Participants at Risk for Diabetes
Authors: Simmons Kimber , Fouts Alexandra , Pyle Laura , Clark Pamela , Dong Fran , Yu Liping , Usmani-Brown Sahar , Gottlieb Peter , Herold Kevan , Steck Andrea ,   The Type 1 Diabetes TrialNet Study Group
Published: August 2019

Islet autoantibody (iAb)-positive individuals have a high risk of progression to type 1 diabetes (T1D), although the rate of progression is highly variable and factors involved in the rate of progression are largely unknown. The ratio of unmethylated/methylated insulin DNA levels (unmethylated INS ratio) has been shown to be higher in participants at high risk of T1D compared to healthy controls. We aimed to evaluate whether an unmethylated INS ratio may be a useful biomarker of beta cell death and rate of progression to T1D. In TrialNet participants who were followed in the Pathway to Prevention Study and progressed to diabetes (n = 57, median age of onset 15.3 years), we measured unmethylated INS ratio and autoantibodies by electrochemiluminescence (ECL) assays (ECL-IAA, ECL-GADA, and ECL-IA2) and radioimmunoassays (RIA) (mIAA, GADA, IA2A, and ZnT8A) longitudinally for 24 months prior to diagnosis. Linear models were used to test the association between unmethylated INS ratio and the age at T1D diagnosis and unmethylated INS ratio and iAb over time. Close to diabetes onset, the unmethylated INS ratio was associated with mIAA (p = 0.003), ECL-IAA (p = 0.002), and IA2A (p = 0.01) levels, but not with GADA, ECL-GADA, ECL-IA2, or ZnT8A levels. No significant associations were found at baseline (24 months prior to T1D diagnosis). Only mIAA levels were significantly associated with an unmethylated INS ratio over time, with a 0.24 change in the ratio for each 0.1 change in mIAA z-score (p = 0.02). Adjusting for a baseline unmethylated INS ratio, an increased rate of change in unmethylated INS ratio from baseline to diabetes onset was associated with a five-year decrease in age at T1D diagnosis (p = 0.04).
All-Atom Molecular Dynamics Simulations of Dimeric Lung Surfactant Protein B in Lipid Multilayers
Authors: Robichaud Nicholas A. S. , Khatami Mohammad Hassan , Saika-Voivod Ivan , Booth Valerie
Published: August 2019

Although lung surfactant protein B (SP-B) is an essential protein that plays a crucial role in breathing, the details of its structure and mechanism are not well understood. SP-B forms covalent homodimers, and in this work we use all-atom molecular dynamics simulations to study dimeric SP-B’s structure and its behavior in promoting lipid structural transitions. Four initial system configurations were constructed based on current knowledge of SP-B’s structure and mechanism, and the protein maintained a helicity consistent with experiment in all systems. Several SP-B-induced lipid reorganization behaviors were observed, and regions of the protein particularly important for these activities included SP-B’s “central loop” and “hinge” regions. SP-B dimers with one subunit initially positioned in each of two adjacent bilayers appeared to promote close contact between two bilayers. When both subunits were initially positioned in the same bilayer, SP-B induced the formation of a defect in the bilayer, with water penetrating into the centre of the bilayer. Similarly, dimeric SP-B showed a propensity to interact with preformed interpores in the bilayer. SP-B dimers also promoted bilayer thinning and creasing. This work fleshes out the atomistic details of the dimeric SP-B structures and SP-B/lipid interactions that underlie SP-B’s essential functions.
The Role of Mesenchymal Stem Cells in Radiation-Induced Lung Fibrosis
Authors: Zanoni Michele , Cortesi Michela , Zamagni Alice , Tesei Anna
Published: August 2019

Radiation therapy is one of the most important treatment modalities for thoracic tumors. Despite significant advances in radiation techniques, radiation-induced lung injury (RILI) still occurs in up to 30% of patients undergoing thoracic radiotherapy, and therefore remains the main dose-limiting obstacle. RILI is a potentially lethal clinical complication of radiotherapy that has 2 main stages: an acute stage defined as radiation pneumonitis, and a late stage defined as radiation-induced lung fibrosis. Patients who develop lung fibrosis have a reduced quality of life with progressive and irreversible organ malfunction. Currently, the most effective intervention for the treatment of lung fibrosis is lung transplantation, but the lack of available lungs and transplantation-related complications severely limits the success of this procedure. Over the last few decades, advances have been reported in the use of mesenchymal stem cells (MSCs) for lung tissue repair and regeneration. MSCs not only replace damaged lung epithelial cells but also promote tissue repair through the secretion of anti-inflammatory and anti-fibrotic factors. Here, we present an overview of MSC-based therapy for radiation-induced lung fibrosis, focusing in particular on the molecular mechanisms involved and describing the most recent preclinical and clinical studies carried out in the field.
Change Point Detection for Diversely Distributed Stochastic Processes Using a Probabilistic Method
Authors: Khan Muhammad Rizwan , Sarkar Biswajit
Published: August 2019

Unpredicted deviations in time series data are called change points. These unexpected changes indicate transitions between states. Change point detection is a valuable technique in modeling to estimate unanticipated property changes underlying time series data. It can be applied in different areas like climate change detection, human activity analysis, medical condition monitoring and speech and image analyses. Supervised and unsupervised techniques are equally used to identify changes in time series. Even though change point detection algorithms have improved considerably in recent years, several undefended challenges exist. Previous work on change point detection was limited to specific areas; therefore, more studies are required to investigate appropriate change point detection techniques applicable to any data distribution to assess the numerical productivity of any stochastic process. This research is primarily focused on the formulation of an innovative methodology for change point detection of diversely distributed stochastic processes using a probabilistic method with variable data structures. Bayesian inference and a likelihood ratio test are used to detect a change point at an unknown time (k). The likelihood of k is determined and used in the likelihood ratio test. Parameter change must be evaluated by critically analyzing the parameters expectations before and after a change point. Real-time data of particulate matter concentrations at different locations were used for numerical verification, due to diverse features, that is, environment, population densities and transportation vehicle densities. Therefore, this study provides an understanding of how well this recommended model could perform for different data structures.
The Impact of the Covariance Matrix Sampling on the Angle of Arrival Estimation Accuracy
Authors: Al-Sadoon Mohammed A. G. , Abd-Alhameed Raed A. , McEwan Neil J.
Published: August 2019

Several works show that the linear Angle of Arrival (AoA) methods such as Projection Matrix (PM) have low computational complexity compared to the subspace methods. Although the PM method is classified as a subspace method, it does not need decomposition of the measured matrix. This work investigates the effect of the sampled columns within the covariance matrix on the projection matrix construction. To the authors’ knowledge, this investigation has not been addressed in the literature. Unlike the subspace methods such as Multiple Signal Classification (MUSIC), Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Minimum Norm, Propagator, etc., which have to use a specific number of columns, we demonstrate this aspect is not applicable in the PM method. To this end, the projection matrix is formed based on a various number of sampled columns to estimate the arrival angles. A theoretical analysis is accomplished to illustrate the relationship between the number of the sampled columns and the degrees of freedom (DOFs). The analysis shows that with the same aperture size, the DOFs can be increased by increasing only the number of sampled columns in the projection matrix calculation step. An intensive Monte Carlo simulation for different scenarios is presented to validate the theoretical claims. The estimation accuracy of the PM method, based on the proposed selected sampling methodology outperforms all the other techniques with less complexity compared to the Capon and MUSIC methods. The estimation accuracy is evaluated in terms of Root Mean Square Error (RMSE) and the Probability of Successful Detection (PSD). The results are presented and discussed.