Online Repository Research Articles

The Creation of High-Resolution Brain Cross-sections for 3D Printing and Virtual Reality Applications.

Technologies such as 3D printing and virtual/augmented reality have great potential for improving the teaching of highly spatial topics such as neuroanatomy. We created a set of 3D printed and virtual brain cross-sections using a high-resolution MRI dataset. These resources have been made freely available via online repositories. We also report a pilot study of the use of both the physical and virtual specimens in the classroom. Students completed a lab exercise where they used either the 3D printed or virtual brain sections to order a set of axial slices from dorsal to ventral. They then labeled the different structures that they found useful in determining the slices' positions. We measured the students' ability to localize 2D brain cross-sections before and after the lab exercise. Overall, we saw pre- to post-test increases in accuracy on a brain cross-sections task compared to a lecture-based neuroanatomy instruction.

Abstract PO-019: General social media use amongst young adult cancer patients and caregivers

Abstract Purpose: Our purpose was to describe the social media platforms and experiences of adolescent and young adult (AYA) cancer patients and caregivers. We aimed to identify the general social media use of this group in order to determine the information seeking and sharing behaviors within the AYA cancer experience. Methods: From March 2021 to July 2021, we recruited participants through online repositories (e.g., ResearchMatch), and posted flyers on social media and at a large adolescent and young adult (AYA) conference. Eligible participants included 1) cancer patients who were between the ages of 18-39 and were diagnosed within this age range, use social media weekly, and speaks English and 2) informal cancer caregivers between the ages of 18-39, use social media weekly, and speaks English. Semi-structured interviews were conducted with participants over the telephone. We summarized sociodemographic and cancer factors, then categorized qualitative and quantitative data about general social media usage into platform use, differences between platform experiences, and information found. Results: There were 50 participants who completed an online screening form regarding social media platform usage, 17 of whom completed the study (36.0% participation rate). Of the 17 participants, Facebook (88.2%), Instagram (82.3%), and Twitter (76.5%) were the most common social media platforms used. Participants described that when using social media during cancer their preferred platforms were Facebook and Instagram, respectively, because of their ease of use and accessibility. This allowed a large population of cancer patients to be active on these platforms. Facebook was used most frequently for finding support through “groups”, from which participants could seek advice, anecdotes, or support from other cancer patients. On Instagram, participants most often interacted with cancer information through cancer specific pages like “Stupid Cancer” or “The Cancer Patient”. These pages target the adolescent-young adult age group. Participants felt as if the aspect of humor, the sharing of survival stories, research findings and opportunities, and fellow cancer survivors within the comments or through direct messages helped support them. The anecdotes/stories that were shared on social media often detailed a patient's treatment regimen, survivorship, and daily life, which helped patients and caregivers analyze their own cancer experiences and routines. Conclusions: Adolescents and young adults are diagnosed at a developmentally unique time in life, where they may seek support and comfort through social media platforms. By studying the types of platforms used, the reasons for using social media, and patterns of social media use this work provides a foundation for targeting AYA cancer patients and caregivers for social media interventions. Citation Format: Keely K. Smith, Ashley Green, Jennifer Traslavina Jimenez, Terry Badger, Echo L. Warner. General social media use amongst young adult cancer patients and caregivers [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-019.

Risk factors of pediatric acute lymphoblastic leukemia: A review

Background: Pediatric cancers are one of the most common diseases growing worldwide and are categorized into acute lymphocytic leukemia, acute myelogenous leukemia, chronic lymphocytic leukemia, and chronic myelogenous leukemia, and the most common form of childhood leukemia is ALL. Aim: In this review, we tried to grasp different risk elements of ALL and the complexity of ALL. Method: Concerning the data collection, different keywords were used for the data retrieval from the different online repositories were utilized which include PubMed, Medline, Web of Science, etc. Result: It was plethora of risk factors was found to increases the risk of ALL in pediatrics which includes paternal alcoholic consumption, smoking habits, and maternal & paternal age, are important contributors to the risk of ALL in the child. Different changes at chromosomal level and also at gene level were found to be an important contributor for determining the susceptibility of ALL in pediatrics. Also, different inherited syndromes were found comorbid with the risk of ALL in children, with predisposing recessive mutation inherited from parents to offspring. Discussion & Conclusion: It is concluded that ALL is a very complex disorder where genetic alteration is the prime factor for determining the risk of diseases and concerning the ALL in pediatrics, maternal and paternal life style factors are import for lowering the threshold of susceptibility of diseases. Therefore, it is important to prevent or limit the exposure to various environmental risk attributes and thus help in lowering the diseases susceptibility.

Using Open-Source Bioinformatics and Visualization Tools to Explore the Structure and Function of SARS-CoV-2 Spike Protein

The relationship between protein structure and function is a foundational concept in undergraduate biochemistry. We find this theme is best presented with assignments that encourage exploration and analysis. Here, we share a series of four assignments that use open-source, online molecular visualization and bioinformatics tools to examine the interaction between the SARS-CoV-2 spike protein and the ACE2 receptor. The interaction between these two proteins initiates SARS-CoV-2 infection of human host cells and is the cause of COVID-19. In assignment I, students identify sequences with homology to the SARS-CoV-2 spike protein and use them to build a primary sequence alignment. Students make connections to a linked primary research article as an example of how scientists use molecular and phylogenetic analysis to explore the origins of a novel virus. Assignments II through IV teach students to use an online molecular visualization tool for analysis of secondary, tertiary, and quaternary structure. Emphasis is placed on identification of noncovalent interactions that stabilize the SARS-CoV-2 spike protein and mediate its interaction with ACE2. We assigned this project to upper-level undergraduate biochemistry students at a public university and liberal arts college. Students in our courses completed the project as individual homework assignments. However, we can easily envision implementation of this project during multiple in-class sessions or in a biochemistry laboratory using in-person or remote learning. We share this project as a resource for instructors who aim to teach protein structure and function using inquiry-based molecular visualization activities. <em>Primary image:</em>&nbsp;Exploration of SARS-CoV-2 spike protein: student generated data from assignments I - IV. Includes examples of figures submitted by students, including a sequence alignment and representations of 3D protein structure generated using UCSF Chimera.&nbsp;The primary image includes student generated data and a cartoon from Pixabay, an online repository of copyright free art.&nbsp;

Prevalence of episiotomy practice and factors associated with it in Ethiopia, systematic review and meta-analysis.

An episiotomy is one of the most commonly performed obstetrics surgeries indicated in emergencies during the second stage of labor like fetal distress, dystocia, and tight perineum. As a result, this systematic review and meta-analysis aimed to assess the prevalence of episiotomy practice and associated factors in Ethiopia. Ten cross-sectional studies with a total population of 3718 were included in this study. The search was done using online databases like PubMed, HINARI, Web of Science, other gray, and online repositories of Universities. All the included papers were extracted and appraised using the standard extraction sheet format of JOANNA Briggs Institute. The Cochran Q-test and I2 statistics test were used to test the heterogeneity of studies. To detect the publication bias of the included studies, a funnel plot and Egger’s test were used. The pooled prevalence of episiotomy practice and the odds ratio with a 95% confidence interval were presented using forest plots. The overall pooled prevalence of episiotomy practice was 45.11% (95% CI; 37.04–53.18; I2 = 96.3%). Prolonged second stage of labor (OR: 4.79, 95% CI: 3.03, 7.57), face presentation (OR: 4.26, 95% CI: 1.21, 15.07), birth weight > 4000 g (OR: 6.71, 95% CI: 3.14–14.33), instrumental delivery (OR: 4.26, 95% CI 2.95, 6.14), and primiparity (OR: 3.70, 95% CI: 1.90, 7.2) were factors associated with episiotomy practice. The overall prevalence of episiotomy practice was higher in Ethiopia compared to studies conducted in other countries. The prolonged second stage of labor, face presentation, birth weight > 4000 g, instrumental delivery, and primiparity of women were the factors associated with episiotomy practice. Therefore, efforts should be made to prevent routine episiotomy practice through creating awareness, adjusting national guidelines, affecting the World Health Organization episiotomy policy, and monitoring the activities of the health care facilities in executing the protocols.

Mapping the selection, availability, price and affordability of essential medicines for mental health conditions at a global level.

To provide a cross-country analysis of selection, availability, prices and affordability of essential medicines for mental health conditions, aiming to identify areas for improvement. We used the World Health Organization (WHO) online repository of national essential medicines lists (EMLs) to extract information on the inclusion of essential psychotropic medicines within each country's EML. Data on psychotropic medicine availability, price and affordability were obtained from the Health Action International global database. Additional information on country availability, prices and affordability of essential medicines for mental disorders was identified by searching, up to January 2021, PubMed/Medline, CINAHIL, Scopus and the WHO Regional Databases. We summarised and compared the indicators across lowest-price generic and originator brand medicines in the public and private sectors, and by country income groups. A total of 112 national EMLs were analysed, and data on psychotropic medicine availability, price and affordability were obtained from 87 surveys. While some WHO essential psychotropic medicines, such as chlorpromazine, haloperidol, amitriptyline, carbamazepine and diazepam, were selected by most national lists, irrespective of the country income level, other essential medicines, such as risperidone or clozapine, were included by most national lists in high-income countries, but only by a minority of lists in low-income countries. Up to 40% of low-income countries did not include medicines that have been in the WHO list for decades, such as long-acting fluphenazine, lithium carbonate and clomipramine. The availability of generic and originator psychotropic medicines in the public sector was below 50% for all medicines, with low-income countries showing rates lower than the overall average. Analysis of price data revealed that procurement prices were lower than patient prices in the public sector, and medicines in the private sector were associated with the highest prices. In low-income countries, the average patient price for amitriptyline and fluoxetine was three times the international unit reference price, while the average patient price for diazepam was ten times the international unit reference price. Affordability was higher in the public than the private sector, and in high-income than low-income countries. Access to medicines for mental health conditions is an ongoing challenge for health systems worldwide, and no countries can claim to be fully aligned with the general principle of providing full access to essential psychotropic medicines. Low availability and high costs are major barriers to the use of and adherence to essential psychotropic medicines, particularly in low-and middle-income countries.

A Security Testbed for Networked DES Control Systems

In this paper we present an implementation scheme for a networked control system where the coordination between devices is done by supervisory control theory. The system is intended to be used as a testbed for DES security-related techniques. We provide some examples of attacks whose effect can be evaluated using the proposed setup. The hardware and software are based on low-cost devices and can be modified to suit different control systems. The details of the implementation are available on a free online repository.

Корпус стандартов цифровой доступности: современный этап развития применительно к электронному обучению

The article deals with issues of standardization of e-learning digital accessibility. It aims to analyze the content of the current digital accessibility standards and to assess the possibility of their use to ensure the accessibility of e-learning and its components. International and Russian federal standards that are directly or indirectly related to the digital accessibility of e-learning were studied. The search for documents was carried out in October 2021 – February 2022 on the official websites of standardization bodies by thematic headings and keywords in the title or abstract of the document. A sample of 92 current standards was obtained, including: international (global) – 57 (62%); international (European) – 23 (25%); international (Commonwealth of Independent States) – 2 (3%); Russian federal – 10 (11%). Using the content analysis method, the standards were systematized according to the following parameters: publication date; publication language; full text access features; geographical coverage; digital accessibility standardized parameters; digital accessibility beneficiary groups. The corresponding data set was published in the Mendeley Data online repository. The obtained data were studied using descriptive statistics in Microsoft Excel. As a result of the study, five categories of digital accessibility standards were identified (by areas of application in elearning): digital content accessibility standards (39; 42%), software accessibility standards (26; 28%), Internet communications accessibility standards (10; 11%), standards for ensuring individual needs and preferences (20; 22%), standards for the development and interpretation of digital accessibility standards (15; 16%). Some standards (13; 14%) cover more than one category. It has been determined that the beneficiaries of applying the most digital accessibility standards are all e-learning users who may be in conditions that make learning difficult. The analysis has identified two key groups of standards that can be used as a basis for the implementation of universally accessible elearning – standards based on the WCAG and AccessForAll concepts. WCAG regulates the requirements for the development of accessible digital content, and AccessForAll methods for meeting the user’s personal needs and preferences. It was determined that both concepts together can form a unified system in which WCAG is a mandatory component, and AccessForAll is an optional one. The need to develop new combined standards for e-learning digital accessibility, taking into account the best standardization practices, has been identified.

The Aston Forensic Linguistic Databank (FoLD)

The Aston Forensic Linguistic Databank (FoLD) is a permanent,controlled access online repository for forensic linguistic data. We broadlyunderstand forensic linguistics as any academic research with a potential toimprove the delivery of justice through the analysis of language. FoLD thuscomprises a wide range of datasets with relevance to forensic linguistics andlanguage and law, including commercial extortion letters, investigative interviewsin police and other contexts, legal documents, forum posts from far-right onlinegroups, and comment threads from political blogs. This paper outlines how FoLDworks and its potential impact on the general discipline of forensic linguistics.

Systems Biology-Derived Genetic Signatures of Mastitis in Dairy Cattle: A New Avenue for Drug Repurposing.

Simple SummaryTherapeutic success of bovine mastitis depends mainly on accurately diagnosing the type of pathogen involved. Despite the development prospects for bovine mastitis diagnosis, including new biomarker discovery to target specific pathogens with high sensitivity and specificity, treatment studies have shown controversial results, and the most efficient, safe, and economical treatments for mastitis are still topics of scientific debate. The goal of this research is the integration of different levels of systems biology data to predict candidate drugs for the control and management of E. coli mastitis. We propose that the novel drugs could be used by pharmaceutical scientists or veterinarians to find commercially efficacious medicines.Mastitis, a disease with high incidence worldwide, is the most prevalent and costly disease in the dairy industry. Gram-negative bacteria such as Escherichia coli (E. coli) are assumed to be among the leading agents causing acute severe infection with clinical signs. E. Coli, environmental mastitis pathogens, are the primary etiological agents of bovine mastitis in well-managed dairy farms. Response to E. Coli infection has a complex pattern affected by genetic and environmental parameters. On the other hand, the efficacy of antibiotics and/or anti-inflammatory treatment in E. coli mastitis is still a topic of scientific debate, and studies on the treatment of clinical cases show conflicting results. Unraveling the bio-signature of mastitis in dairy cattle can open new avenues for drug repurposing. In the current research, a novel, semi-supervised heterogeneous label propagation algorithm named Heter-LP, which applies both local and global network features for data integration, was used to potentially identify novel therapeutic avenues for the treatment of E. coli mastitis. Online data repositories relevant to known diseases, drugs, and gene targets, along with other specialized biological information for E. coli mastitis, including critical genes with robust bio-signatures, drugs, and related disorders, were used as input data for analysis with the Heter-LP algorithm. Our research identified novel drugs such as Glibenclamide, Ipratropium, Salbutamol, and Carbidopa as possible therapeutics that could be used against E. coli mastitis. Predicted relationships can be used by pharmaceutical scientists or veterinarians to find commercially efficacious medicines or a combination of two or more active compounds to treat this infectious disease.

A remote laboratory course on experimental human physiology using wearable technology.

To help educators deliver their physiology laboratory courses remotely, we developed an inexpensive, customizable hardware kit along with freely available teaching resources. We based the course design on four principles that should allow students to conduct insightful experiments on different physiological systems. First, the experimental setup should not be constrained to laboratory environments. Second, students should be able to take this course without prior coding and electronics experience. Third, the hardware kit should be relatively inexpensive, and all other resources should be freely available. Fourth, all resources should be customizable for educators. The hardware kit consists of commercially available electronic components, with a microcontroller as its hub (Arduino friendly). All measurement systems can be assembled without soldering. The hardware kit is cost-effective (approximately the cost of a textbook) and can be customized depending upon instructional needs. All software is freely available, and we share all necessary codes in open-access online repositories for simple use and customizability. All lab manuals and additional video tutorials are also freely available online and customizable. In our particular course, we have weekly asynchronous physiology lectures and one synchronous laboratory session, where students can get help with their equipment. In this article, we only focus on the novel and open-source laboratory part of the course. The laboratory includes four units [data acquisition, ECG, electromyography (EMG), activity classification] and one final project. It is our intent that these resources will allow other educators to rapidly implement their own remote physiology laboratories or to extend our work into other pedagogical applications of wearable technology.

The Azurin Coding Gene: Origin and Phylogenetic Distribution.

Azurin is a bacterial-derived cupredoxin, which is mainly involved in electron transport reactions. Interest in azurin protein has risen in recent years due to its anticancer activity and its possible applications in anticancer therapies. Nevertheless, the attention of the scientific community only focused on the azurin protein found in Pseudomonas aeruginosa (Proteobacteria, Gammaproteobacteria). In this work, we performed the first comprehensive screening of all the bacterial genomes available in online repositories to assess azurin distribution in the three domains of life. The Azurin coding gene was not detected in the domains Archaea and Eucarya, whereas it was detected in phyla other than Proteobacteria, such as Bacteroidetes, Verrucomicrobia and Chloroflexi, and a phylogenetic analysis of the retrieved sequences was performed. Observed patchy distribution and phylogenetic data suggest that once it appeared in the bacterial domain, the azurin coding gene was lost in several bacterial phyla and/or anciently horizontally transferred between different phyla, even though a vertical inheritance appeared to be the major force driving the transmission of this gene. Interestingly, a shared conserved domain has been found among azurin members of all the investigated phyla. This domain is already known in P. aeruginosa as p28 domain and its importance for azurin anticancer activity has been widely explored. These findings may open a new and intriguing perspective in deciphering the azurin anticancer mechanisms and to develop new tools for treating cancer diseases.

Systematic Analysis of Artificial Intelligence-Based Platforms for Identifying Governance and Access Control

Artificial intelligence (AI) has become omnipotent with its variety of applications and advantages. Considering the other side of the coin, the eruption of technology has created situations that need more caution about the safety and security of data and systems at all levels. Thus, to hedge against the growing threats of cybersecurity, the need for a robust AI platform supported by machine learning and other supportive technologies is well recognized by organizations. AI is a much sought-after topic, and there is extolling literature available in repositories. Hence, a systematic arrangement of the literature that can help identify the right AI platform that can provide identity governance and access control is the need of the hour. Having this background, the present study is commissioned a Systematic Literature Review (SLR) to accomplish the necessity. Literature related to AI and Identity and Access Management (IAM) is collected from renowned peer-reviewed digital libraries for systematic analysis and assessment purposes using the systematic review guidelines. Thus, the final list of articles relevant to the framed research questions related to the study topic is fetched and is reviewed thoroughly. For the proposed systematic research work, the literature reported during the period ranging from 2016 to 2021 (a portion of 2021 is included) is analyzed and a total of 43 papers were depicted more relevant to the selected research domain. These articles were accumulated from ProQuest, Scopus, Taylor &amp; Franics, Science Direct, and Wiley online repositories. The article's contribution can supplement the AI-based IAM information and steer the entities of diverse sectors concerning seamless implementation. Appropriate suggestions are proposed to encourage research work in the required fields.

GeneExpressionFromGEO: An R Package to Facilitate Data Reading from Gene Expression Omnibus (GEO).

Gene expression profiling is a useful way to measure the activity of genes in molecular biology and, because of its effectiveness, researchers have released thousands of gene expression datasets publicly in online databases and repositories, such as Gene Expression Omnibus (GEO). To read and analyze gene expression data, the computational biology community has developed several tools and platforms, including Bioconductor, an R open-source platform of software packages that can be used to analyze these data. Despite the usefulness of Bioconductor and of its packages, it is still difficult to read gene expression data from GEO, and to assign gene symbols to the probesets of datasets. To alleviate this problem, we introduce here a new R software package, geneExpressionFromGEO, which provides to the users the possibility to easily download gene expression data from GEO and to easily associate gene symbols to probesets. In this short chapter, we describe the assets of our software package, and we report an example of its usage. We believe that geneExpressionFromGEO can be very useful for the R community of bioinformaticians working on gene expression data.

Assessment of YouTube as an educational tool in teaching thyroidectomy and parathyroidectomy.

YouTube has become the preferred resource for trainees to learn and prepare for surgical cases. This study evaluated the educational quality of YouTube videos detailing thyroidectomy and parathyroidectomy. YouTube was systematically searched using 11 terms related to thyroidectomy and parathyroidectomy. Four independent clinical reviewers assessed the videos using Laparoscopic Surgery Video Educational Guidelines as well as modified Laparoscopic Surgery Video Educational Guidelines subgroup tools. Sixty-five videos were identified and evaluated. Overall Laparoscopic Surgery Video Educational Guidelines score was 8.58 ± 3.85 (mean subgroup score, 5.67 ± 2.40). Twenty-eight of 65, 25 of 65 and 12 of 65 videos were deemed medium, low and high quality, respectively. Inter-rater reliability was good for both attending surgeons and residents. Presence of audio or visual commentary had a positive correlation with total Laparoscopic Surgery Video Educational Guidelines scores (R2=0.38). Videos produced by otolaryngologists and US-based physicians scored higher on total scores compared to non-otolaryngology and non-US based physicians. Some YouTube videos on thyroidectomy and parathyroidectomy exhibit high educational value. Future efforts should increase the number of high-quality YouTube videos containing both audio and visual commentary or create an online repository of videos for medical students and residents to augment their surgical training.

Development of 3D MRI-Based Anatomically Realistic Models of Breast Tissues and Tumours for Microwave Imaging Diagnosis.

Breast cancer diagnosis using radar-based medical MicroWave Imaging (MWI) has been studied in recent years. Realistic numerical and physical models of the breast are needed for simulation and experimental testing of MWI prototypes. We aim to provide the scientific community with an online repository of multiple accurate realistic breast tissue models derived from Magnetic Resonance Imaging (MRI), including benign and malignant tumours. Such models are suitable for 3D printing, leveraging experimental MWI testing. We propose a pre-processing pipeline, which includes image registration, bias field correction, data normalisation, background subtraction, and median filtering. We segmented the fat tissue with the region growing algorithm in fat-weighted Dixon images. Skin, fibroglandular tissue, and the chest wall boundary were segmented from water-weighted Dixon images. Then, we applied a 3D region growing and Hoshen-Kopelman algorithms for tumour segmentation. The developed semi-automatic segmentation procedure is suitable to segment tissues with a varying level of heterogeneity regarding voxel intensity. Two accurate breast models with benign and malignant tumours, with dielectric properties at 3, 6, and 9 GHz frequencies have been made available to the research community. These are suitable for microwave diagnosis, i.e., imaging and classification, and can be easily adapted to other imaging modalities.

Advancing Pediatrics During Turbulent Times.

Advancing Pediatrics During Turbulent Times.

Characterizing the Observation Bias in Gravitational-wave Detections and Finding Structured Population Properties

Abstract The observed distributions of the source properties from gravitational-wave (GW) detections are biased due to the selection effects and detection criteria in the detections, analogous to the Malmquist bias. In this work, this observation bias is investigated through its fundamental statistical and physical origins. An efficient semi-analytical formulation for its estimation is derived, which is as accurate as the standard method of numerical simulations, with only a millionth of the computational cost. Then, the estimated bias is used for unmodeled inferences on the binary black hole population. These inferences show additional structures, specifically two peaks in the joint mass distribution around binary masses ∼10 M ⊙ and ∼30 M ⊙. Example ready-to-use scripts and some produced data sets for this method are shared in an online repository.

Economic perspectives on the future of academic publishing: Introduction to the special issue

Economic perspectives on the future of academic publishing: Introduction to the special issue

RNA-Seq Data Analysis Pipeline for Plants: Transcriptome Assembly, Alignment, and Differential Expression Analysis.

In this chapter, we describe methods for analyzing RNA-Seq data, presented as a flow along a pipeline beginning with raw data from a sequencer and ending with an output of differentially expressed genes and their functional characterization. The first section covers de novo transcriptome assembly for organisms lacking reference genomes or for those interested in probing against the background of organism-specific transcriptomes assembled from RNA-Seq data. Section 2 covers both gene- and transcript-level quantifications, leading to the third and final section on differential expression analysis between two or more conditions. The pipeline starts with raw sequence reads, followed by quality assessment and preprocessing of the input data to ensure a robust estimate of the transcripts and their differential regulation. The preprocessed data can be inputted into the de novo transcriptome flow to assemble transcripts, functionally annotated using tools such as InterProScan or Blast2Go and then forwarded to differential expression analysis flow, or directly inputted into the differential expression analysis flow if a reference genome is available. An online repository containing sample data has also been made available, as well as custom Python scripts to modify the output of the programs within the pipeline for various downstream analyses.