bluuebunny/crossref_metadata_2025_split huggingface dataset:
Three-dimensional measurement of the course of the radial nerve at the posterior humeral shaft: An in vivo anatomical study
Authors: Park Ji-Kang , Choi Seung-Myung , Kang Sang-Woo , Kim Kook-Jong , Min Kyoung-Tae 
Published: July 2020

Purpose: Iatrogenic radial nerve injury caused by surgical exposure of the humerus is a serious complication. We aimed to describe the course of the radial nerve at the posterior humeral shaft using a three-dimensional (3D) reconstruction technique by utilizing computed tomography (CT) images of living subjects. We hypothesized that the course of the radial nerve in the posterior aspect of the humeral shaft would be reliably established using this technique and the measurements would have satisfactory intraobserver/interobserver reliabilities. Methods: This in vivo anatomical study utilized 652 upper extremity CT angiography images from 326 patients. A 3D modeling of the humerus and radial nerve was performed. We evaluated the segment of the radial nerve that lays directly on the posterior aspect of the humeral shaft and measured its proximal point, mid, and distal points. The shortest distances from the olecranon fossa to these points were defined as R1, R2, and R3, respectively. The relationships between these parameters and humeral length (HL) and transcondylar length (TL) were evaluated, and the intraobserver/interobserver reliabilities of these parameters were measured. Results: The HL was 293.6 mm, and TL was 58.64 mm on average. The R1 measured 159.2 (range 127.1–198.2) mm, R2 was 136.6 (105.7–182.5), and R3 was 112.8 (76.8–150.0) mm on average ( p < .001). The intraobserver/interobserver reliabilities ranged from 0.90 to 0.98. Conclusion: The course of the radial nerve at the posterior aspect of the humeral shaft can be reliably established using the 3D reconstruction technique, and all measurements had excellent intraobserver/interobserver reliability.
Acute sleep deprivation enhances susceptibility to the migraine substrate cortical spreading depolarization
Authors: Negro Andrea , Seidel Jessica L. , Houben Thijs , Yu Esther S. , Rosen Ike , Arreguin Andrea J. , Yalcin Nilufer , Shorser-Gentile Lea , Pearlman Lea , Sadhegian Homa , Vetrivelan Ramalingam , Chamberlin Nancy L. , Ayata Cenk , Martelletti Paolo , Moskowitz Michael A. , Eikermann-Haerter Katharina 
Published: July 2020

Abstract
Background
Migraine is a common headache disorder, with cortical spreading depolarization (CSD) considered as the underlying electrophysiological event. CSD is a slowly propagating wave of neuronal and glial depolarization. Sleep disorders are well known risk factors for migraine chronification, and changes in wake-sleep pattern such as sleep deprivation are common migraine triggers. The underlying mechanisms are unknown. As a step towards developing an animal model to study this, we test whether sleep deprivation, a modifiable migraine trigger, enhances CSD susceptibility in rodent models.

Methods
Acute sleep deprivation was achieved using the “gentle handling method”, chosen to minimize stress and avoid confounding bias. Sleep deprivation was started with onset of light (diurnal lighting conditions), and assessment of CSD was performed at the end of a 6 h or 12 h sleep deprivation period. The effect of chronic sleep deprivation on CSD was assessed 6 weeks or 12 weeks after lesioning of the hypothalamic ventrolateral preoptic nucleus. All experiments were done in a blinded fashion with respect to sleep status. During 60 min of continuous topical KCl application, we assessed the total number of CSDs, the direct current shift amplitude and duration of the first CSD, the average and cumulative duration of all CSDs, propagation speed, and electrical CSD threshold.

Results
Acute sleep deprivation of 6 h (n = 17) or 12 h (n = 11) duration significantly increased CSD frequency compared to controls (17 ± 4 and 18 ± 2, respectively, vs. 14 ± 2 CSDs/hour in controls; p = 0.003 for both), whereas other electrophysiological properties of CSD were unchanged. Acute total sleep deprivation over 12 h but not over 6 h reduced the electrical threshold of CSD compared to controls (p = 0.037 and p = 0.095, respectively). Chronic partial sleep deprivation in contrast did not affect CSD susceptibility in rats.

Conclusions
Acute but not chronic sleep deprivation enhances CSD susceptibility in rodents, possibly underlying its negative impact as a migraine trigger and exacerbating factor. Our findings underscore the importance of CSD as a therapeutic target in migraine and suggest that headache management should identify and treat associated sleep disorders.
Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning
Authors: Karakaya Mahmut , Hacisoftaoglu Recep E. 
Published: July 2020

Abstract
Background
Diabetic retinopathy (DR), the most common cause of vision loss, is caused by damage to the small blood vessels in the retina. If untreated, it may result in varying degrees of vision loss and even blindness. Since DR is a silent disease that may cause no symptoms or only mild vision problems, annual eye exams are crucial for early detection to improve chances of effective treatment where fundus cameras are used to capture retinal image. However, fundus cameras are too big and heavy to be transported easily and too costly to be purchased by every health clinic, so fundus cameras are an inconvenient tool for widespread screening. Recent technological developments have enabled to use of smartphones in designing small-sized, low-power, and affordable retinal imaging systems to perform DR screening and automated DR detection using image processing methods. In this paper, we investigate the smartphone-based portable retinal imaging systems available on the market and compare their image quality and the automatic DR detection accuracy using a deep learning framework.

Results
Based on the results, iNview retinal imaging system has the largest field of view and better image quality compared with iExaminer, D-Eye, and Peek Retina systems. The overall classification accuracy of smartphone-based systems are sorted as 61%, 62%, 69%, and 75% for iExaminer, D-Eye, Peek Retina, and iNview images, respectively. We observed that the network DR detection performance decreases as the field of view of the smartphone-based retinal systems get smaller where iNview is the largest and iExaminer is the smallest.

Conclusions
The smartphone-based retina imaging systems can be used as an alternative to the direct ophthalmoscope. However, the field of view of the smartphone-based retina imaging systems plays an important role in determining the automatic DR detection accuracy.
PDXGEM: patient-derived tumor xenograft-based gene expression model for predicting clinical response to anticancer therapy in cancer patients
Authors: Kim Youngchul , Kim Daewon , Cao Biwei , Carvajal Rodrigo , Kim Minjung 
Published: July 2020

Abstract
Background
Cancer is a highly heterogeneous disease with varying responses to anti-cancer drugs. Although several attempts have been made to predict the anti-cancer therapeutic responses, there remains a great need to develop highly accurate prediction models of response to the anti-cancer drugs for clinical applications toward a personalized medicine. Patient derived xenografts (PDXs) are preclinical cancer models in which the tissue or cells from a patient’s tumor are implanted into an immunodeficient or humanized mouse. In the present study, we develop a bioinformatics analysis pipeline to build a predictive gene expression model (GEM) for cancer patients’ drug responses based on gene expression and drug activity data from PDX models.

Results
Drug sensitivity biomarkers were identified by performing an association analysis between gene expression levels and post-treatment tumor volume changes in PDX models. We built a drug response prediction model (called PDXGEM) in a random-forest algorithm by using a subset of the drug sensitvity biomarkers with concordant co-expression patterns between the PDXs and pretreatment cancer patient tumors. We applied the PDXGEM to several cytotoxic chemotherapies as well as targeted therapy agents that are used to treat breast cancer, pancreatic cancer, colorectal cancer, or non-small cell lung cancer. Significantly accurate predictions of PDXGEM for pathological response or survival outcomes were observed in extensive independent validations on multiple cancer patient datasets obtained from retrospective observational studies and prospective clinical trials.

Conclusion
Our results demonstrated the strong potential of using molecular profiles and drug activity data of PDX tumors in developing a clinically translatable predictive cancer biomarkers for cancer patients. The PDXGEM web application is publicly available at http://pdxgem.moffitt.org.
HPG-DHunter: an ultrafast, friendly tool for DMR detection and visualization
Authors: Fernández Lisardo , Pérez Mariano , Olanda Ricardo , Orduña Juan M. , Marquez-Molins Joan 
Published: July 2020

Abstract
Background
Software tools for analyzing DNA methylation do not provide graphical results which can be easily identified, but huge text files containing the alignment of the samples and their methylation status at a resolution of base pairs. There have been proposed different tools and methods for finding Differentially Methylated Regions (DMRs) among different samples, but the execution time required by these tools is large, and the visualization of their results is far from being interactive. Additionally, these methods show more accurate results when identifying simulated DM regions that are long and have small within-group variation, but they have low concordance when used with real datasets, probably due to the different approaches they use for DMR identification. Thus, a tool which automatically detects DMRs among different samples and interactively visualizes DMRs at different scales (from a bunch to ten of millions of DNA locations) can be the key for shortening the DNA methylation analysis process in many studies.

Results
In this paper, we propose a software tool based on the wavelet transform. This mathematical tool allows the fast automatic DMR detection by simple comparison of different signals at different resolution levels. Also, it allows an interactive visualization of the DMRs found at different resolution levels. The tool is publicly available at https://grev-uv.github.io/, and it is part of a complete suite of tools which allow to carry out the complete process of DNA alignment and methylation analysis, creation of methylation maps of the whole genome, and the detection and visualization of DMRs between different samples.

Conclusions
The validation of the developed software tool shows similar concordance with other well-known and extended tools when used with real and synthetic data. The batch mode of the tool is capable of automatically detecting the existing DMRs for half (twelve) of the human chromosomes between two sets of six samples (whose.csv files after the alignment and mapping procedures have an aggregated size of 108 Gigabytes) in around three hours and a half. When compared to other well-known tools, HPG-DHunter only requires around 15% of the execution time required by other tools for detecting the DMRs.
MASS: predict the global qualities of individual protein models using random forests and novel statistical potentials
Authors: Liu Tong , Wang Zheng 
Published: July 2020

AbstractBackgroundProtein model quality assessment (QA) is an essential procedure in protein structure prediction. QA methods can predict the qualities of protein models and identify good models from decoys. Clustering-based methods need a certain number of models as input. However, if a pool of models are not available, methods that only need a single model as input are indispensable.ResultsWe developed MASS, a QA method to predict the global qualities of individual protein models using random forests and various novel energy functions. We designed six novel energy functions or statistical potentials that can capture the structural characteristics of a protein model, which can also be used in other protein-related bioinformatics research. MASS potentials demonstrated higher importance than the energy functions of RWplus, GOAP, DFIRE and Rosetta when the scores they generated are used as machine learning features. MASS outperforms almost all of the four CASP11 top-performing single-model methods for global quality assessment in terms of all of the four evaluation criteria officially used by CASP, which measure the abilities to assign relative and absolute scores, identify the best model from decoys, and distinguish between good and bad models. MASS has also achieved comparable performances with the leading QA methods in CASP12 and CASP13.ConclusionsMASS and the source code for all MASS potentials are publicly available athttp://dna.cs.miami.edu/MASS/.
MMiRNA-Viewer2, a bioinformatics tool for visualizing functional annotation for MiRNA and MRNA pairs in a network
Authors: Bai Yongsheng , Baker Steve , Exoo Kevin , Dai Xingqin , Ding Lizhong , Khattak Naureen Aslam , Li Hongtao , Liu Hannah , Liu Xiaoming 
Published: July 2020

Abstract
Background
Although there are many studies on the characteristics of miRNA-mRNA interactions using miRNA and mRNA sequencing data, the complexity of the change of the correlation coefficients and expression values of the miRNA-mRNA pairs between tumor and normal samples is still not resolved, and this hinders the potential clinical applications. There is an urgent need to develop innovative methodologies and tools that can characterize and visualize functional consequences of cancer risk gene and miRNA pairs while analyzing the tumor and normal samples simultaneously.

Results
We developed an innovative bioinformatics tool for visualizing functional annotation of miRNA-mRNA pairs in a network, known as MMiRNA-Viewer2. The tool takes mRNA and miRNA interaction pairs and visualizes mRNA and miRNA regulation network. Moreover, our MMiRNA-Viewer2 web server integrates and displays the mRNA and miRNA gene annotation information, signaling cascade pathways and direct cancer association between miRNAs and mRNAs. Functional annotation and gene regulatory information can be directly retrieved from our web server, which can help users quickly identify significant interaction sub-network and report possible disease or cancer association. The tool can identify pivotal miRNAs or mRNAs that contribute to the complexity of cancer, while engaging modern next-generation sequencing technology to analyze the tumor and normal samples concurrently. We compared our tools with other visualization tools.

Conclusion
Our MMiRNA-Viewer2 serves as a multitasking platform in which users can identify significant interaction clusters and retrieve functional and cancer-associated information for miRNA-mRNA pairs between tumor and normal samples. Our tool is applicable across a range of diseases and cancers and has advantages over existing tools.
Transcriptome analysis of activated charcoal-induced growth promotion of wheat seedlings in tissue culture
Authors: Dong Fu-shuang , lv Meng-yu , Wang Jin-ping , Shi Xue-ping , Liang Xin-xia , Liu Yong-wei , Yang Fan , Zhao He , Chai Jian-Fang , Zhou Shuo 
Published: July 2020

Abstract
Background
Activated charcoal (AC) is highly adsorbent and is often used to promote seedling growth in plant tissue culture; however, the underlying molecular mechanism remains unclear. In this study, root and leaf tissues of 10-day-old seedlings grown via immature embryo culture in the presence or absence of AC in the culture medium were subjected to global transcriptome analysis by RNA sequencing to provide insights into the effects of AC on seedling growth.

Results
In total, we identified 18,555 differentially expressed genes (DEGs). Of these, 11,182 were detected in the roots and 7373 in the leaves. In seedlings grown in the presence of AC, 9460 DEGs were upregulated and 7483 DEGs were downregulated in the presence of AC as compared to the control. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed 254 DEG-enriched pathways, 226 of which were common between roots and leaves. Further analysis of the major metabolic pathways revealed that AC stimulated the expression of nine genes in the phenylpropanoid biosynthesis pathway, including PLA, CYP73A, COMT, CYP84A, and 4CL, the protein products of which promote cell differentiation and seedling growth. Further, AC upregulated genes involved in plant hormone signaling related to stress resistance and disease resistance, including EIN3, BZR1, JAR1, JAZ, and PR1, and downregulated genes related to plant growth inhibition, including BKI1, ARR-B, DELLA, and ABF.

Conclusions
Growth medium containing AC promotes seedling growth by increasing the expression of certain genes in the phenylpropanoid biosynthesis pathway, which are related to cell differentiation and seedling growth, as well as genes involved in plant hormone signaling, which is related to resistance.
Phylogenetic analysis of the ATP-binding cassette proteins suggests a new ABC protein subfamily J in Aedes aegypti (Diptera: Culicidae)
Authors: Figueira-Mansur Janaina , Schrago Carlos G. , Salles Tiago S. , Alvarenga Evelyn S. L. , Vasconcellos Brenda M. , Melo Ana Claudia A. , Moreira Monica F. 
Published: July 2020

AbstractBackgroundWe performed an in-depth analysis of the ABC gene family inAedes aegypti(Diptera: Culicidae), which is an important vector species of arthropod-borne viral infections such as chikungunya, dengue, and Zika. Despite its importance, previous studies of the Arthropod ABC family have not focused on this species. Reports of insecticide resistance among pests and vectors indicate that some of these ATP-dependent efflux pumps are involved in compound traffic and multidrug resistance phenotypes.ResultsWe identified 53 classic complete ABC proteins annotated in theA. aegyptigenome. A phylogenetic analysis ofAedes aegyptiABC proteins was carried out to assign the novel proteins to the ABC subfamilies. We also determined 9 full-length sequences of DNA repair (MutS, RAD50) and structural maintenance of chromosome (SMC) proteins that contain the ABC signature.ConclusionsAfter inclusion of the putative ABC proteins into the evolutionary tree of the gene family, we classifiedA. aegyptiABC proteins into the established subfamilies (A to H), but the phylogenetic positioning of MutS, RAD50 and SMC proteins among ABC subfamilies—as well as the highly supported grouping of RAD50 and SMC—prompted us to name a new J subfamily ofA. aegyptiABC proteins.
How being synanthropic affects the gut bacteriome and mycobiome: comparison of two mouse species with contrasting ecologies
Authors: Bendová Barbora , Piálek Jaroslav , Ďureje Ľudovít , Schmiedová Lucie , Čížková Dagmar , Martin Jean-Francois , Kreisinger Jakub 
Published: July 2020

Abstract
Background
The vertebrate gastrointestinal tract is colonised by microbiota that have a major effect on the host’s health, physiology and phenotype. Once introduced into captivity, however, the gut microbial composition of free-living individuals can change dramatically. At present, little is known about gut microbial changes associated with adaptation to a synanthropic lifestyle in commensal species, compared with their non-commensal counterparts. Here, we compare the taxonomic composition and diversity of bacterial and fungal communities across three gut sections in synanthropic house mouse (Mus musculus) and a closely related non-synanthropic mound-building mouse (Mus spicilegus).

Results
Using Illumina sequencing of bacterial 16S rRNA amplicons, we found higher bacterial diversity in M. spicilegus and detected 11 bacterial operational taxonomic units with significantly different proportions. Notably, abundance of Oscillospira, which is typically higher in lean or outdoor pasturing animals, was more abundant in non-commensal M. spicilegus. ITS2-based barcoding revealed low diversity and high uniformity of gut fungi in both species, with the genus Kazachstania clearly dominant.

Conclusions
Though differences in gut bacteria observed in the two species can be associated with their close association with humans, changes due to a move from commensalism to captivity would appear to have caused larger shifts in microbiota.
Antimicrobial and immunomodulatory responses of photodynamic therapy in Galleria mellonella model
Authors: Huang Xiaowen , Xu Meinian , Pan Wen , Wang Menglei , Wu Xiaoyan , Dai Siqi , Li Li , Zeng Kang 
Published: July 2020

Abstract
Background
New therapeutics are urgently needed for infectious diseases, especially for the fungal infection like Fonsecaea monophora. Photodynamic therapy has been showing antimicrobial activity on some pathogens. The combination of antimicrobial medicines and photodynamic therapy (PDT) might be a practical approach. However, whether the treatment of PDT could do benefits to the host immunity remains poorly documented.

Results
In this study, Galleria mellonella larvae were employed as a model organism to evaluate the activity of PDT, and also to investigate the regulation of humoral immunity by PDT. Photosensitizer 5-aminolevulinic acid (ALA) was applied to the G. mellonella infection model. It was found that ALA-mediated PDT was non-toxic to G. mellonella, and could extend the median survival of infected larvae from 3 days to 5.5 days. We observed that larval hemocytes inhibited the growth of Candida albicans and Staphylococcus aureus, without any contribution by ALA-PDT. Furthermore, the application of ALA-PDT demonstrated the immunomodulation of larval innate immunity as increased hemocyte density counting, cell morphological transformation, and sensitivity to pathogens.

Conclusions
G. mellonella could be considered as a useful model to study the immunoregulation of PDT. This model revealed that ALA-PDT positively defense against infections through inducing humoral immune responses of larvae.
Prevalence, serotypes, and antimicrobial resistance of Salmonella isolates from patients with diarrhea in Shenzhen, China
Authors: Shen Hongwei , Chen Haochuan , Ou Yongxuan , Huang Tingting , Chen Siping , Zhou Lintao , Zhang Jinjin , Hu Qinghua , Zhou Yiwen , Ma Wen 
Published: July 2020

Abstract
Background
Salmonella is one of the main causative agents of diarrhea which results in substantial disease burden. To determine the prevalence, serotype distribution, and antimicrobial resistance profiles of clinical Salmonella isolates in Shenzhen, a 6-year surveillance study was conducted.

Results
A total of 297 (5.7%) Salmonella strains were isolated from stool samples from 5239 patients. Among the 42 serotypes identified, serotype Typhimurium was the most common one which represented 39.7% of the isolates (118), followed by serotype Enteritidis (71, 23.9%), London (12, 4.0%), 4, 5, 12: i: - (11, 3.7%), and Senftenberg (8, 2.7%). A high frequency of resistance was found in ampicillin (70.6%), piperacillin (64.5%), tetracycline (63.5%), and streptomycin (54.3%). Resistance to ampicillin and tetracycline was observed in 95.3% of S. Typhimurium isolates; and nalidixic acid in 93.1% of S. Enteritidis isolates. Resistance to 5 or more antimicrobial agents was found in 78.8% of S. Typhimurium and 69.0% of S. Enteritidis isolates. A decreased susceptibility to ciprofloxacin and levofloxacin was associated with amino acid alteration in gyrA gene. Point mutations without amino acid changes were seen in gyrB, parC, and parE genes.

Conclusions
A broad range of serotypes are responsible for Salmonellosis in Shenzhen, with Enteritidis and Typhimurium being the most common serotypes. The high level of antibiotic resistance is of public health significance and ongoing monitoring combined with rational use of antibiotics are recommended. Point mutations in gyrA gene might play an important role in the resistance to fluoroquinolones.