bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short-Term Tropical Cyclone Intensity Forecasting from Satellite Imagery Based on the Deviation Angle Variance Technique
Authors: Hu Liang , Ritchie Elizabeth A. , Tyo J. Scott 
Published: December 2019

Abstract
The deviation angle variance (DAV) is a parameter that characterizes the level of organization of a cloud cluster compared with a perfectly axisymmetric tropical cyclone (TC) using satellite infrared (IR) imagery, and can be used to estimate the intensity of the TC. In this study, the DAV technique is further used to analyze the relationship between satellite imagery and TC future intensity over the North Atlantic basin. The results show that the DAV of the TC changes ahead of the TC intensity change, and this can be used to predict short-term TC intensity. The DAV-IR 24-h forecast is close to the National Hurricane Center (NHC) 24-h forecast, and the bias is lower than NHC and other methods during weakening periods. Furthermore, an improved TC intensity forecast is obtained by incorporating all four satellite bands. Using SST and TC latitude as the other two predictors in a linear regression model, the RMSE and MAE of the DAV 24-h forecast are 13.7 and 10.9 kt (1 kt ≈ 0.51 m s−1), respectively, and the skill space of the DAV is about 5.5% relative to the Statistical Hurricane Intensity Forecast model with inland decay (Decay-SHIFOR) during TC weakening periods. Considering the DAV is an independent intensity technique, it could potentially add value as a member of the suite of operational intensity forecast techniques, especially during TC weakening periods.
Evaluation of chemiluminescent immunoassay quantitative detection for pro-gastrin-releasing peptide (ProGRP) in serum and plasma
Authors: Cheng Yizhuang , He Jing , Zhang Liping , Chen Xiufa , Ou Saiying 
Published: December 2019

Objective To evaluate a newly developed Hybiome ProGRP chemiluminescent assay. Methods Analytical sensitivity, precision, recovery, and equivalency of serum and plasma, serum stability, and complement interference of the Hybiome ProGRP assay were evaluated. Serum specimens from 318 individuals including 38 small cell lung cancer (SCLC), 65 non-small cell lung cancer (NSCLC), 53 benign lung diseases, and 162 healthy controls were assessed using the Hybiome ProGRP assay and Roche Elecsys ProGRP assay, and the results were compared. Results The Hybiome ProGRP assay showed good analytical sensitivity, precision, and accuracy, and it showed equivalence between serum and plasma and serum stability. The methodological comparison results showed good correlation between the Hybiome and Roche assays (slope, 0.9889; intercept, 1.28). Both the Hybiome and Roche assays showed good ability to distinguish between SCLC and NSCLC. Based on 95% specificity in the NSCLC cohort, a clinical differentiation cut-off for separating SCLC from NSCLC patients was 114 pg/mL for the Hybiome assay and 117 pg/mL for the Roche assay; the AUC was 0.9166 and the sensitivity was 71.05% for Hybiome and 0.9045 and 76.32% for Roche, respectively. Conclusion The Hybiome ProGRP chemiluminescent assay shows good analytical performance and good correlation with the Roche Elecsys ProGRP assay.
Contribution of intraganglionic CGRP to migraine-like responses in male and female rats
Authors: Araya Erika Ivanna , Turnes Joelle de Melo , Barroso Amanda Ribeiro , Chichorro Juliana Geremias 
Published: December 2019

Objective To evaluate whether intraganglionic calcitonin gene-related peptide induced differential migraine-like responses in male and female rats. Methods Calcitonin gene-related peptide was injected in the trigeminal ganglion of male and female rats followed by assessment of periorbital mechanical allodynia with von Frey hairs. The influence of systemic treatment with sumatriptan or intraganglionic treatment with minocycline and propentofylline was determined on the calcitonin gene-related peptide-induced mechanical allodynia in male and female rats. One additional group was exposed to an aversive light 24 h after calcitonin gene-related peptide priming, followed by evaluation of periorbital mechanical threshold, and another group was tested in the elevated-plus maze. Results Intraganglionar calcitonin gene-related peptide-induced periorbital mechanical allodynia in female (0.5 to 6 h) and male rats (0.5 to 4 h). Systemic sumatriptan briefly attenuated the mechanical allodynia, but intraganglionar minocycline or propentofylline injection was effective only in male rats. Calcitonin gene-related peptide induced photic sensitivity in female and male rats (lasting 4 h and 1 h, respectively), as well as anxiety-like behavior. Conclusions Intraganglionar calcitonin gene-related peptide may play a major role in migraine-like responses, including periorbital mechanical allodynia, light sensitivity and anxiety like-behavior. Female rats are likely to be more susceptible to calcitonin gene-related peptide effects and a better understanding of the sexual dimorphism in calcitonin gene-related peptide signaling may help to improve migraine therapy.
Designing and evaluating dose-escalation studies made easy: The MoDEsT web app
Authors: Pallmann Philip , Wan Fang , Mander Adrian P , Wheeler Graham M , Yap Christina , Clive Sally , Hampson Lisa V , Jaki Thomas 
Published: December 2019

Background/aims: Dose-escalation studies are essential in the early stages of developing novel treatments, when the aim is to find a safe dose for administration in humans. Despite their great importance, many dose-escalation studies use study designs based on heuristic algorithms with well-documented drawbacks. Bayesian decision procedures provide a design alternative that is conceptually simple and methodologically sound, but very rarely used in practice, at least in part due to their perceived statistical complexity. There are currently very few easily accessible software implementations that would facilitate their application. Methods: We have created MoDEsT, a free and easy-to-use web application for designing and conducting single-agent dose-escalation studies with a binary toxicity endpoint, where the objective is to estimate the maximum tolerated dose. MoDEsT uses a well-established Bayesian decision procedure based on logistic regression. The software has a user-friendly point-and-click interface, makes changes visible in real time, and automatically generates a range of graphs, tables, and reports. It is aimed at clinicians as well as statisticians with limited expertise in model-based dose-escalation designs, and does not require any statistical programming skills to evaluate the operating characteristics of, or implement, the Bayesian dose-escalation design. Results: MoDEsT comes in two parts: a ‘Design’ module to explore design options and simulate their operating characteristics, and a ‘Conduct’ module to guide the dose-finding process throughout the study. We illustrate the practical use of both modules with data from a real phase I study in terminal cancer. Conclusion: Enabling both methodologists and clinicians to understand and apply model-based study designs with ease is a key factor towards their routine use in early-phase studies. We hope that MoDEsT will enable incorporation of Bayesian decision procedures for dose escalation at the earliest stage of clinical trial design, thus increasing their use in early-phase trials.
The Utility of Computed Tomography and Intrathecal Fluorescein in the Management of Cerebrospinal Fluid Leak
Authors: Flynn John P. , Pavelonis Anna , Ledbetter Luke , Bhalla Vidur , Alvi Sameer A. , Chiu Alexander G. , Villwock Jennifer 
Published: December 2019

Background Intrathecal fluorescein (IF) has become a common tool for localization of cerebrospinal fluid (CSF) leak, but despite frequent use, IF lacks Food and Drug Administration approval. The diagnostic ability of high-resolution computed tomography (HRCT) has increased over several decades. Subspecialized rhinology training within otolaryngology has, similarly, allowed for dedicated skull base surgeons to become more adept at CSF leak localization. Objectives To evaluate the utility of HRCT and IF in CSF leak localization. To identify certain patient populations in which IF has added utility. To analyze the ability of fellowship-trained neuroradiologist and rhinologist to localize CSF leak sites. Methods Data were collected from a single, tertiary care academic institution. Patients admitted for CSF leak between 2003 and 2016 were included. Diagnostic yield of preoperative imaging and IF for identification of leak site was analyzed. Fellowship-trained neuroradiologist and rhinologist performed retrospective review of CT imaging and identified CSF leak sites. Results One hundred and two patients underwent CSF leak repair. Skull base defects were preoperatively localized to exact sinus on imaging report in 67% of patients. Preoperative imaging stratified by CT slice thickness of 0.625 mm identified leak site in 88.9% of cases. Blinded retrospective review by a neuroradiologist and rhinologist was able to localize the CSF leak to the correct or adjacent sinus in >80% of cases. IF was useful for intraoperative localization in 73% of cases. When preoperative imaging failed at leak site localization, IF was able to correctly identify leak site in 75% of cases. Conclusions The diagnostic yield of IF and CT imaging was equivalent, with each modality localizing leak site approximately two-thirds of the time. CT imaging with 0.625 mm slice thickness proved more efficacious in identification of skull base defects. IF demonstrated increased utility in instances where preoperative imaging has failed at leak site identification.
“We Really Help, Taking Care of Each Other”: Older Homeless Adults as Caregivers
Authors: Rosenwohl-Mack Sarah , Kushel Margot , Ramsey Claire , Handley Margaret , Knight Kelly R. 
Published: December 2019

Objectives: Many older homeless adults maintain contact with family. We conducted a qualitative study examining the role of family caregiving for older homeless adults. Method: We conducted semi-structured qualitative interviews with a sample of 46 homeless participants who reported spending at least one night with a housed family member in the prior 6 months. Results: A total of 13 of 46 older adult participants provided caregiving. Themes included (a) the death of the care recipient led to the participant’s homelessness; (b) feeling a duty to act as caregivers; (c) providing care in exchange for housing; (d) caregivers’ ability to stay was tenuous; (e) providing care conflicted with the caregiver’s needs; and (f) resentment when family was ungrateful. Discussion: In a sample of older homeless adults in contact with family, many provided caregiving for housed family. For some, caregiving precipitated homelessness; for others, caregiving provided temporary respite from homelessness, and for others, caregiving continued during homelessness.
Connexin-43 is a promising target for pulmonary hypertension due to hypoxaemic lung disease
Authors: Bouvard Claire , Genet Nafiisha , Phan Carole , Rode Baptiste , Thuillet Raphaël , Tu Ly , Robillard Paul , Campagnac Marilyne , Soleti Raffaella , Dumas De La Roque Eric , Delcambre Frédéric , Cronier Laurent , Parpaite Thibaud , Maurat Elise , Berger Patrick , Savineau Jean-Pierre , Marthan Roger , Guignabert Christophe , Freund-Michel Véronique , Guibert Christelle 
Published: December 2019

The mechanisms underlying pulmonary hypertension (PH) are complex and multifactorial, and involve different cell types that are interconnected through gap junctional channels. Although connexin (Cx)-43 is the most abundant gap junction protein in the heart and lungs, and critically governs intercellular signalling communication, its contribution to PH remains unknown. The focus of the present study is thus to evaluate Cx43 as a potential new target in PH.Expressions of Cx37, Cx40 and Cx43 were studied in lung specimens from patients with idiopathic pulmonary arterial hypertension (IPAH) or PH associated with chronic hypoxaemic lung diseases (chronic hypoxia-induced pulmonary hypertension (CH-PH)). Heterozygous Cx43 knockdown CD1 (Cx43+/−) and wild-type littermate (Cx43+/+) mice at 12 weeks of age were randomly divided into two groups, one of which was maintained in room air and the other exposed to hypoxia (10% oxygen) for 3 weeks. We evaluated pulmonary haemodynamics, remodelling processes in cardiac tissues and pulmonary arteries (PAs), lung inflammation and PA vasoreactivity.Cx43 levels were increased in PAs from CH-PH patients and decreased in PAs from IPAH patients; however, no difference in Cx37 or Cx40 levels was noted. Upon hypoxia treatment, the Cx43+/−mice were partially protected against CH-PH when compared to Cx43+/+mice, with reduced pulmonary arterial muscularisation and inflammatory infiltration. Interestingly, the adaptive changes in cardiac remodelling in Cx43+/−mice were not affected. PA contraction due to endothelin-1 (ET-1) was increased in Cx43+/−mice under normoxic and hypoxic conditions.Taken together, these results indicate that targeting Cx43 may have beneficial therapeutic effects in PH without affecting compensatory cardiac hypertrophy.
The effect of HIV-associated tuberculosis, tuberculosis-IRIS and prednisone on lung function
Authors: Stek Cari , Allwood Brian , Du Bruyn Elsa , Buyze Jozefien , Schutz Charlotte , Thienemann Friedrich , Lombard Adele , Wilkinson Robert J. , Meintjes Graeme , Lynen Lutgarde 
Published: December 2019

Residual pulmonary impairment is common after treatment for tuberculosis (TB). Lung function data in patients with HIV-associated TB are scarce, especially in the context of paradoxical TB-associated immune reconstitution inflammatory syndrome (TB-IRIS) and prophylactic prednisone. We aimed to determine the prevalence of lung function abnormalities in patients with HIV-associated TB and CD4 counts ≤100 cells·μL−1and assess the effect of prophylactic prednisone and the development of paradoxical TB-IRIS on pulmonary impairment.We performed spirometry, 6-min walk test (6MWT) and chest radiography at baseline (week 0) and at weeks 4, 12 and 28 in participants of the PredART trial, which evaluated a 28-day course of prednisone to prevent TB-IRIS in patients with HIV-associated TB commencing antiretroviral therapy.153 participants underwent spirometry and/or 6MWT at one or more time points. Abnormal spirometry measurements were present in 66% of participants at week 0 and 50% at week 28; low forced vital capacity was the commonest abnormality. Chest radiographs showed little or no abnormalities in the majority of participants. Prednisone use resulted in a 42 m greater 6-min walk distance and a 4.9% higher percentage of predicted forced expiratory volume in 1 s at week 4; these differences were no longer significantly different from week 12 onwards. TB-IRIS did not significantly impair lung function outcome.Residual pulmonary impairment is common in HIV-associated TB. In patients with low CD4 counts, neither prophylactic prednisone as used in our study nor the development of TB-IRIS significantly affected week-28 pulmonary outcome.
The International Conference on Intelligent Biology and Medicine (ICIBM) 2019: bioinformatics methods and applications for human diseases
Authors: Zhao Zhongming , Dai Yulin , Zhang Chi , Mathé Ewy , Wei Lai , Wang Kai 
Published: December 2019

AbstractBetween June 9–11, 2019, the International Conference on Intelligent Biology and Medicine (ICIBM 2019) was held in Columbus, Ohio, USA. The conference included 12 scientific sessions, five tutorials or workshops, one poster session, four keynote talks and four eminent scholar talks that covered a wide range of topics in bioinformatics, medical informatics, systems biology and intelligent computing. Here, we describe 13 high quality research articles selected for publishing in BMC Bioinformatics.
Challenges in proteogenomics: a comparison of analysis methods with the case study of the DREAM proteogenomics sub-challenge
Authors: Eicher Tara , Patt Andrew , Kautto Esko , Machiraju Raghu , Mathé Ewy , Zhang Yan 
Published: December 2019

Abstract
Background
Proteomic measurements, which closely reflect phenotypes, provide insights into gene expression regulations and mechanisms underlying altered phenotypes. Further, integration of data on proteome and transcriptome levels can validate gene signatures associated with a phenotype. However, proteomic data is not as abundant as genomic data, and it is thus beneficial to use genomic features to predict protein abundances when matching proteomic samples or measurements within samples are lacking.

Results
We evaluate and compare four data-driven models for prediction of proteomic data from mRNA measured in breast and ovarian cancers using the 2017 DREAM Proteogenomics Challenge data. Our results show that Bayesian network, random forests, LASSO, and fuzzy logic approaches can predict protein abundance levels with median ground truth-predicted correlation values between 0.2 and 0.5. However, the most accurately predicted proteins differ considerably between approaches.

Conclusions
In addition to benchmarking aforementioned machine learning approaches for predicting protein levels from transcript levels, we discuss challenges and potential solutions in state-of-the-art proteogenomic analyses.
A novel graph theoretical approach for modeling microbiomes and inferring microbial ecological relationships
Authors: Kim Suyeon , Thapa Ishwor , Zhang Ling , Ali Hesham 
Published: December 2019

Abstract
Background
Microbiomes play vital roles in shaping environments and stabilize them based on their compositions and inter-species relationships among its species. Variations in microbial properties have been reported to have significant impact on their host environment. For example, variants in gut microbiomes have been reported to be associated with several chronic conditions, such as inflammatory disease and irritable bowel syndrome. However, how microbial bacteria contribute to pathogenesis still remains unclear and major research questions in this domain remain unanswered.

Methods
We propose a split graph model to represent the composition and interactions of a given microbiome. We used metagenomes from Korean populations in this study. The dataset consists of three different types of samples, viz. mucosal tissue and stool from Crohn’s disease patients and stool from healthy individuals. We use the split graph model to analyze the impact of microbial compositions on various host phenotypes. Utilizing the graph model, we have developed a pipeline that integrates genomic information and pathway analysis to characterize both critical informative components of inter-bacterial correlations and associations between bacterial taxa and various metabolic pathways.

Results
The obtained results highlight the importance of the microbial communities and their inter-relationships and show how these microbial structures are correlated with Crohn’s disease. We show that there are significant positive associations between detected taxonomic biomarkers as well as multiple functional modules in the split graph of mucosal tissue samples from CD patients. Bacteria Moraxellaceae and Pseudomonadaceae were detected as taxonomic biomarkers in CD groups. Higher abundance of these bacteria have been reported in previous study and several metabolic pathways associated with these bacteria were characterized in CD samples.

Conclusions
The proposed pipeline provides a new way to approach the analysis of complex microbiomes. The results obtained from this study show great potential in unraveling mechansims in complex biological systems to understand how various components in such complex environments are associated with critical biological functions.
Identification of lung cancer gene markers through kernel maximum mean discrepancy and information entropy
Authors: Zhao Zhixun , Peng Hui , Zhang Xiaocai , Zheng Yi , Chen Fang , Fang Liang , Li Jinyan 
Published: December 2019

AbstractBackgroundThe early diagnosis of lung cancer has been a critical problem in clinical practice for a long time and identifying differentially expressed gene as disease marker is a promising solution. However, the most existing gene differential expression analysis (DEA) methods have two main drawbacks: First, these methods are based on fixed statistical hypotheses and not always effective; Second, these methods can not identify a certain expression level boundary when there is no obvious expression level gap between control and experiment groups.MethodsThis paper proposed a novel approach to identify marker genes and gene expression level boundary for lung cancer. By calculating a kernel maximum mean discrepancy, our method can evaluate the expression differences between normal, normal adjacent to tumor (NAT) and tumor samples. For the potential marker genes, the expression level boundaries among different groups are defined with the information entropy method.ResultsCompared with two conventional methods t-test and fold change, the top average ranked genes selected by our method can achieve better performance under all metrics in the 10-fold cross-validation. Then GO and KEGG enrichment analysis are conducted to explore the biological function of the top 100 ranked genes. At last, we choose the top 10 average ranked genes as lung cancer markers and their expression boundaries are calculated and reported.ConclusionThe proposed approach is effective to identify gene markers for lung cancer diagnosis. It is not only more accurate than conventional DEA methods but also provides a reliable method to identify the gene expression level boundaries.
Finding prognostic gene pairs for cancer from patient-specific gene networks
Authors: Park Byungkyu , Lee Wook , Park Inhee , Han Kyungsook 
Published: December 2019

Abstract
Background
Molecular characterization of individual cancer patients is important because cancer is a complex and heterogeneous disease with many possible genetic and environmental causes. Many studies have been conducted to identify diagnostic or prognostic gene signatures for cancer from gene expression profiles. However, some gene signatures may fail to serve as diagnostic or prognostic biomarkers and gene signatures may not be found in gene expression profiles.

Methods
In this study, we developed a general method for constructing patient-specific gene correlation networks and for identifying prognostic gene pairs from the networks. A patient-specific gene correlation network was constructed by comparing a reference gene correlation network from normal samples to a network perturbed by a single patient sample. The main difference of our method from previous ones includes (1) it is focused on finding prognostic gene pairs rather than prognostic genes and (2) it can identify prognostic gene pairs from gene expression profiles even when no significant prognostic genes exist.

Results
Evaluation of our method with extensive data sets of three cancer types (breast invasive carcinoma, colon adenocarcinoma, and lung adenocarcinoma) showed that our approach is general and that gene pairs can serve as more reliable prognostic signatures for cancer than genes.

Conclusions
Our study revealed that prognosis of individual cancer patients is associated with the existence of prognostic gene pairs in the patient-specific network and the size of a subnetwork of the prognostic gene pairs in the patient-specific network. Although preliminary, our approach will be useful for finding gene pairs to predict survival time of patients and to tailor treatments to individual characteristics. The program for dynamically constructing patient-specific gene networks and for finding prognostic gene pairs is available at http://bclab.inha.ac.kr/pancancer.