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Reliability of information in YouTube™ videos on types of root resorption and related stimulating factors.

Root resorption occurs for various reasons and can also be seen as a treatment complication in orthodontics. This study aimed to assess the reliability and quality of YouTube™ videos on root resorption and to assess whether the videos referred to orthodontic treatment and other stimulation factors. YouTube was searched using the keyword 'root resorption', which is the most searched term on Google Trends. The first 200 videos identified using the default filter 'sort by relevance' were used. Information such as the source, type, duration, and number of likes were recorded. Videos were analyzed using a 23-point content scale related to root resorption and divided into groups (poor, moderate, and excellent) based on the Global Quality Score. A total of 95 videos were included in the study. Most were uploaded by dentists or dental clinics (n = 64, 67.4%). The mean number of days since upload was 1536 ± 1254, and the mean duration was 5 ± 4 min. The videos had a mean of 80 ± 515 likes and 7043 ± 35,382 views, and a mean viewing rate of 1131.71 ± 8736.83. The most discussed topic was radiographic signs of root resorption. While the highest content score for the videos was 21, the average score was only 4. The mean GQS was 2 ± 1. Grouping videos by GQS showed that 55 (57.9%) were poor, 38 (40%) were moderate, and 2 (2.1%) were excellent. There was a significant relationship between videos that mentioned orthodontics (n = 62; 65.3%) and higher GQS (p = .036), and a significant difference was between GQS groups for total content levels (p < .001). YouTube videos related to root resorption lack sufficient information and clarity, and their quality needs to be improved. Oral health professionals should strive to produce higher-quality videos.

Development, testing and validation of a targeted NGS-panel for the detection of actionable mutations in lung cancer (NSCLC) using anchored multiplex PCR technology in a multicentric setting.

Lung cancer is a paradigm for a genetically driven tumor. A variety of drugs were developed targeting specific biomarkers requiring testing for tumor genetic alterations in relevant biomarkers. Different next-generation sequencing technologies are available for library generation: 1) anchored multiplex-, 2) amplicon based- and 3) hybrid capture-based-PCR. Anchored multiplex PCR-based sequencing was investigated for routine molecular testing within the national Network Genomic Medicine Lung Cancer (nNGM). Four centers applied the anchored multiplex ArcherDX-Variantplex nNGMv2 panel to re-analyze samples pre-tested during routine diagnostics. Data analyses were performed by each center and compiled centrally according to study design. Pre-defined standards were utilized, and panel sensitivity was determined by dilution experiments. nNGMv2 panel sequencing was successful in 98.9% of the samples (N = 90). With default filter settings, all but two potential MET exon 14 skipping variants were identified at similar allele frequencies. Both MET variants were found with an adapted calling filter. Three additional variants (KEAP1, STK11, TP53) were called that were not identified in pre-testing analyses. Only total DNA amount but not a qPCR-based DNA quality score correlated with average coverage. Analysis was successful with a DNA input as low as 6.25ng. Anchored multiplex PCR-based sequencing (nNGMv2) and a sophisticated user-friendly Archer-Analysis pipeline is a robust and specific technology to detect tumor genetic mutations for precision medicine of lung cancer patients.

Analyzing biomimetic dentistry YouTube videos' quality and content

Aim: This study evaluated the quality and content of YouTube videos about biomimetic dentistry. Methodology: A keyword search for "biomimetic dentistry" was conducted on YouTube. It used only publicly available Internet data from searching YouTube with the default filter “Biomimetic Dentistry” on April 3, 2023. Of the 200 examined videos, only 91 fit the inclusion criteria; those 91 videos underwent a content quality evaluation. The videos' viewing rates were determined after their demographic characteristics were assessed. The information quality index (VIQI) and the Global Quality Scale (GQS) were used to evaluate the video quality. For the statistical analysis, the Shapiro–Wilk, Kruskal–Wallis, Mann–Whitney U, Chi-square, and Fisher's exact tests were used. Results: Most of the videos (n = 59) were labeled "low content," and healthcare practitioners uploaded the majority (91.2%) of them to YouTube. The most discussed subject was advantages and disadvantages (87.9%), followed by the definition of biomimetic dentistry (76.9%). The high-content video group's GQS and VIQI scores were significantly higher than low-content group. There was a statistically significant positive correlation between the VIQI and GQS (p &lt; 0.05) (p = 0,001) and a positive correlation between the overall content, total VIQI, and total GQS scores. Conclusion: The material in YouTube videos about biomimetic dentistry is insufficient for use as a patient information tool. Biomimetic dentistry-related YouTube videos' quality and content were typically poor. Health practitioners should be aware of the content of video-sharing platforms and take responsibility for enriching video content. How to cite this article: Erdem Hepşenoğlu Y, Değirmencioğlu D, Topbaş C. Analyzing biomimetic dentistry YouTube videos' quality and content. Int Dent Res 2023;13(S1):44-49. https://doi.org/10.5577/idr.2023.vol13.s1.7 Linguistic Revision: The English in this manuscript has been checked by at least two professional editors, both native speakers of English.

Comparative Analysis of ActiGraph Step Counting Methods in Adults: A Systematic Literature Review and Meta-Analysis.

The primary aim of this study was to compare steps/day across ActiGraph models, wear locations, and filtering methods. A secondary aim was to compare ActiGraph steps/day to those estimated by the ankle-worn StepWatch. We conducted a systematic literature review to identify studies of adults published before May 12, 2022, that compared free-living steps/day of ActiGraph step-counting methods and studies that compared ActiGraph to StepWatch. Random effects meta-analysis compared ActiGraph models, wear locations, filter mechanisms, and ActiGraph to StepWatch steps/day. A sensitivity analysis of wear location by younger and older age was included. Twelve studies, with 46 comparisons, were identified. When worn on the hip, the AM-7164 recorded 123% of the GT series steps (no low-frequency extension (no LFE) or default filter). However, the AM-7164 recorded 72% of the GT series steps when the LFE was enabled. Independent of the filter used (i.e., LFE, no LFE), ActiGraph GT series monitors captured more steps on the wrist than on the hip, especially among older adults. Enabling the LFE on the GT series monitors consistently recorded more steps, regardless of wear location. When using the default filter (no LFE), ActiGraph recorded fewer steps than StepWatch (ActiGraph on hip 73% and ActiGraph on wrist 97% of StepWatch steps). When LFE was enabled, ActiGraph recorded more steps than StepWatch (ActiGraph on the hip 132% and ActiGraph on the wrist 178% of StepWatch steps). The choice of ActiGraph model, wear location, and filter all impacted steps/day in adults. These can markedly alter the steps recorded compared to a criterion method (StepWatch). This review provides critical insights for comparing studies using different ActiGraph step-counting methods.

Influence of the Frequency-to-Place Function on Recognition with Place-Based Cochlear Implant Maps.

Comparison of acute speech recognition for cochlear implant (CI) alone and electric-acoustic stimulation (EAS) users listening with default maps or place-based maps using either a spiral ganglion (SG) or a new Synchrotron Radiation-Artificial Intelligence (SR-AI) frequency-to-place function. Thirteen adult CI-alone or EAS users completed a task of speech recognition at initial device activation with maps that differed in the electric filter frequency assignments. The three map conditions were: (1) maps with the default filter settings (default map), (2) place-based maps with filters aligned to cochlear SG tonotopicity using the SG function (SG place-based map), and (3) place-based maps with filters aligned to cochlear Organ of Corti (OC) tonotopicity using the SR-AI function (SR-AI place-based map). Speech recognition was evaluated using a vowel recognition task. Performance was scored as the percent correct for formant 1 recognition due to the rationale that the maps would deviate the most in the estimated cochlear place frequency for low frequencies. On average, participants had better performance with the OC SR-AI place-based map as compared to the SG place-based map and the default map. A larger performance benefit was observed for EAS users than for CI-alone users. These pilot data suggest that EAS and CI-alone users may experience better performance with a patient-centered mapping approach that accounts for the variability in cochlear morphology (OC SR-AI frequency-to-place function) in the individualization of the electric filter frequencies (place-based mapping procedure). 3 Laryngoscope, 133:3540-3547, 2023.

Abstract 876: Sequencing a new broadly-consented tumor/normal cell line for a Genome in a Bottle Benchmark

Abstract Here, we describe analyses towards the first tumor/normal benchmark from the Genome in a Bottle (GIAB) consortium using new cell lines from a broadly-consented pancreatic ductal adenocarcinoma patient. This effort builds on the widely-used germline variant benchmarks for seven normal DNA reference materials. GIAB benchmarks are designed to reliably identify false positive and false negative variant calls, and are formed by combining multiple sequencing technologies and variant callers. To combine technologies and variant callers, we first understand their strengths and weaknesses for different variant types and repetitive regions. In this initial work on the new tumor/normal cell line, we have analyzed sequencing from HiC for copy number and structural variant analysis and 100to150x PCR-free Illumina WGS from normal and tumor cells for small variants. Preliminary HiC results identified substantial aneuploidy common in pancreatic tumors, with ~15 large inversions and translocations and 16 chromosomes with extensive loss of heterozygosity due to missing &amp;gt;30% of one copy. The tumor contains the common G12V mutation in KRAS, and interestingly the ~2Mbp region containing this mutation is likely triplicated. About 300 (76% of) SNVs and 10,000 (69% of) small indels agree between mutect2 and strelka2 with default filtering. After excluding difficult regions, 95% of SNVs and 94% of small indels agree, with remaining disagreements caused by systematic sequencing errors, alignment errors, low frequency, and proximity to germline variants. Examining discordant SNVs indifficult regions, most are erroneous somatic variants inregions with loss of heterozygosity that also have mapping errors due to segmental duplications, sequences missing from GRCh38, and/or tandem repeats. After excluding difficult regions, we also found that somatic SNVs fell in 4 primary classes: ~5100 in most cells in diploid regions, ~2100 in most cells in haploid regions, ~760 in only some cells in diploid regions, and ~450 in only some cells in haploid regions. GIAB plans to perform PacBioHiFi and ultra long ONT sequencing to generate phased assemblies for the normal and tumor, and is forming an open working group to develop the first authoritative benchmarks from publicly available, broadly-consented tumor-normal cell lines. Citation Format: Gail Rosen, Justin Wagner, Andrew Liss, Justin Zook. Sequencing a new broadly-consented tumor/normal cell line for a Genome in a Bottle Benchmark [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 876.

YouTube as a source of information on Helicobacter pylori: Content and quality analysis.

Helicobacter pylori infection is the most common cause of infectious diseases worldwide, and management is a current and vital problem for physicians and patients. One of the online platforms that people use most to access health information is YouTube. Therefore, this study aimed to evaluate the quality and reliability of H. pylori information videos on YouTube. The "Helicobacter pylori" keyword was searched with default filters on YouTube. Two hundred videos were evaluated. The source of videos was categorized as academic institutions, professional organizations, physicians, healthcare professionals other than physicians, health information websites, and independent users. The target audience of the videos was classified as patients and healthcare professionals. The Global Quality Scale (GQS), JAMA, and modified DISCERN video scores were obtained by taking the average of the scores given by the two authors. Seventy-four videos were analyzed, and the median duration was 9.25 (range: 1.14-121)min. The target audience of 43 (58.1%) videos was healthcare professionals, and 31 (41.9%) videos were for patients. There was no correlation between likes, dislikes, views, and the quality-usefulness of the videos. Video characteristics such as duration, likes, number of views, and time since video upload day were not associated with the source. The JAMA and DISCERN scores were significantly higher in academic institutions than in other sources. Health information websites had a significantly higher GQS score than other video sources (p=.01). In comparison, there was no significant difference between the target audience (patients and healthcare professionals) in terms of JAMA, modified DISCERN, and GQS scores. YouTube has numerous videos for healthcare information nowadays. Although the quality and reliability of YouTube videos on H. pylori are average according to common scoring systems, we recommend videos produced by academic institutions and health information websites to inform patients.

Semantic segmentation using GSAUNet

Gabor filters well support computer vision tasks due to its steerable properties, that are useful for handling image transformation such as image rotation and image scaling. In this paper, the Gabor-based UNet (GSAUNet) model is proposed where the Gabor filters replace the few default filters in the UNet. Besides, it has adopted a squeeze-and-excitation module to increase channel interdependencies and attention mechanism to focus on an important part of the network. The performance of GSAUNet is assessed on the CamVid and Cityscape datasets that attain improvement for the semantic segmentation tasks.

Aerosol Management in Dentistry During the COVID-19 on YouTube

Aim: The novel coronavirus continues to spread around the world despite all efforts. Dental professionals and staff are exposed to high infection risks and have the potential to spread these infections. Web-based portals are widely used in dentistry for obtaining information. YouTube is one of the most popular web platforms provides a wide variety of information, however, concerns are raised regarding the quality of the videos. The purpose of this study is to analyze the content of YouTube videos on aerosol management in dentistry during the COVID-19 pandemic.&#x0D; Materials and Methods: YouTube search was performed using the terms “dental aerosol management and COVID-19”, “dental aerosol control and COVID-19” and “dental aerosol reduction and COVID-19” with the default filter set to ‘‘sort by relevance’’. The first 100 videos for each term were viewed and analyzed by 2 independent research. The Global Quality Scale (GQS) and the video information and quality index (VIQI) INDEX were performed to evaluate video quality. Viewers’ interactions and Viewing Rate index were chosen to evaluate the video popularity and also other parameters (number of views, duration, time since upload, and likes and dislikes, country of origin, source of upload) were evaluated. &#x0D; Results: After the exclusion criteria 57 videos were evaluated. 11 of the 57 videos had excellent quality and flow. It was observed that as the duration increased, the quality of the videos in both evaluation indexes (VIQI-GQS) were increased. There was no significant difference in terms of loading sources for VIQI and GQS index.&#x0D; Discussion and Conclusions: Besides high-quality videos on aerosol management, there were some low-quality videos that may cause spread of misleading information. Healthcare professionals should play a more active role in the educational videos about infection prevention and aerosol management during pandemic on YouTube.

MycoVarP: Mycobacterium Variant and Drug Resistance Prediction Pipeline for Whole-Genome Sequence Data Analysis.

Whole-genome sequencing (WGS) provides a comprehensive tool to analyze the bacterial genomes for genotype–phenotype correlations, diversity of single-nucleotide variant (SNV), and their evolution and transmission. Several online pipelines and standalone tools are available for WGS analysis of Mycobacterium tuberculosis (Mtb) complex (MTBC). While they facilitate the processing of WGS data with minimal user expertise, they are either too general, providing little insights into bacterium-specific issues such as gene variations, INDEL/synonymous/PE-PPE (IDP family), and drug resistance from sample data, or are limited to specific objectives, such as drug resistance. It is understood that drug resistance and lineage-specific issues require an elaborate prioritization of identified variants to choose the best target for subsequent therapeutic intervention. Mycobacterium variant pipeline (MycoVarP) addresses these specific issues with a flexible battery of user-defined and default filters. It provides an end-to-end solution for WGS analysis of Mtb variants from the raw reads and performs two quality checks, viz, before trimming and after alignments of reads to the reference genome. MycoVarP maps the annotated variants to the drug-susceptible (DS) database and removes the false-positive variants, provides lineage identification, and predicts potential drug resistance. We have re-analyzed the WGS data reported by Advani et al. (2019) using MycoVarP and identified some additional variants not reported so far. We conclude that MycoVarP will help in identifying nonsynonymous, true-positive, drug resistance–associated variants more effectively and comprehensively, including those within the IDP of the PE-PPE/PGRS family, than possible from the currently available pipelines.

Trainable segmentation for transmission electron microscope images of inorganic nanoparticles.

We present a trainable segmentation method implemented within the python package ParticleSpy. The method takes user labelled pixels, which are used to train a classifier and segment images of inorganic nanoparticles from transmission electron microscope images. This implementation is based on the trainable Waikato Environment for Knowledge Analysis (WEKA) segmentation, but is written in python, allowing a large degree of flexibility and meaning it can be easily expanded using other python packages. We find that trainable segmentation offers better accuracy than global or local thresholding methods and requires as few as 100 user-labelled pixels to produce an accurate segmentation. Trainable segmentation presents a balance of accuracy and training time between global/local thresholding and neural networks, when used on transmission electron microscope images of nanoparticles. We also quantitatively investigate the effectiveness of the components of trainable segmentation, its filter kernels and classifiers, in order to demonstrate the use cases for the different filter kernels in ParticleSpy and the most accurate classifiers for different data types. A set of filter kernels is identified that are effective in distinguishing particles from background but that retain dissimilar features. In terms of classifiers, we find that different classifiers perform optimally for different image contrast; specifically, a random forest classifier performs best for high-contrast ADF images, but that QDA and Gaussian Naïve Bayes classifiers perform better for low-contrast TEM images.

Memory Efficient Hardware Architecture for 5/3 Lifting-Based 2-D Forward Discrete Wavelet Transform

Novel memory efficient hardware architecture for 5/3 lifting-based two-dimensional (2-D) forward discrete wavelet transform (DWT) is presented in this paper. The proposed novel architecture requires total memory of size less than 4N in case of J levels of decomposition for an N×N image, which is the lowest size of required total memory compared with the best of the existing state-of-the-art solutions. This novel architecture is able to process multiple levels of decomposition simultaneously by using only one one-dimensional (1-D) 5/3 lifting-based horizontal filter and one 1-D 5/3 lifting-based vertical filter. Since 5/3 DWT filter is the default filter for reversible transformation in JPEG 2000 standard, the proposed hardware architecture is quite suitable for the implementation in a JPEG 2000 coder.

Reliability of information on YouTube™ regarding pediatric dental trauma.

Traumatic dental injuries are a common health problem in children. The aim of this study was to evaluate the quality of the video contents on YouTube™ regarding traumatic dental injuries in children taking into account the information of IADT, and to analyze whether it is useful for patients and dentists. A search was performed on YouTube™ using the search term "trauma in pediatric dentistry" with the default filter set to "sort by relevance". Based on this search, 127 videos were included. Demographic data such as the source, type, duration, upload date, number of likes and dislikes, interaction index, and viewing rate of the videos were recorded. Using a 23-point scale for video content analysis, they were classified into groups as low, moderate, and high content. A total of 127 videos were analyzed. Most of the videos were uploaded by healthcare professionals (n=90; 70.8%). The average length of the videos was 16.4min (range: 0.6-122.9min; median: 7.8). The average number of views of each video was 3702.9 views (range: 4-87 103). The average interaction index (views/day) was 2.4 views (range: 0.00-19.5). The average viewing rate was 522.3 (range: 1.8-6381.2). The average number of "likes" was 45.0 (range: 0-619) and the average number of "dislikes" was 2.1 (range: 0-81). The mean number of days since the uploading of the video was 772.8days (range: 23-3805). Most of the videos (94.4%, n=120) were educational videos and 27 (21.2%), 40 (31.4%), and 60 (47.2%) were classified as high-content, moderate-content, and low-content groups, respectively. YouTube™ videos can be a useful resource for dental trauma in children. However, there is a need to improve the quality of YouTube™ videos uploaded by oral health professionals.

Validity of Hip and Ankle Worn Actigraph Accelerometers for Measuring Steps as a Function of Gait Speed during Steady State Walking and Continuous Turning.

This study aimed to investigate the accuracy and reliability of hip and ankle worn Actigraph GT3X+ (AG) accelerometers to measure steps as a function of gait speed. Additionally, the effect of the low frequency extension filter (LFEF) on the step accuracy was determined. Thirty healthy individuals walked straight and walked with continuous turns in different gait speeds. Number of steps were recorded with a hip and ankle worn AG, and with a Stepwatch (SW) activity monitor positioned around the right ankle, which was used as a reference for step count. The percentage agreement, interclass correlation coefficients and Bland–Altmann plots were determined between the AG and the reference SW across gait speeds for the two walking conditions. The ankle worn AG with the default filter was the most sensitive for step detection at >0.6 m/s, whilst accurate step detection for gait speeds < 0.6 m/s were only observed when applying the LFEF. The hip worn AG with the default filter showed poor accuracy (12–78%) at gait speeds < 1.0 m/s whereas the accuracy increased to >87% for gait speeds < 1.0 m/s when applying the LFEF. Ankle worn AG was the most sensitive to measure steps at a vast range of gait speeds. Our results suggest that sensor placement and filter settings need to be taken into account to provide accurate estimates of step counts.

Improved Variant Detection in Clinical Myeloid NGS Testing by Supplementing a Commercial Myeloid NGS Assay with Custom or Extended Data Filtering and Accessory Fragment Analysis.

Commercial myeloid next-generation sequencing (NGS) panels may facilitate uniform generation of raw data between laboratories. However, different strategies for data filtering and variant annotation may contribute to differences in variant detection and reporting. Here, we present how custom data filtering or the use of Oncomine extended data filtering improve detection of clinically relevant mutations with the Oncomine Myeloid Research Assay. The study included all patient samples (n = 264) analyzed during the first-year, single-site, clinical use of the Ion Torrent Oncomine Myeloid Research Assay. In data analysis, the default analysis filter was supplemented with our own data filtering algorithm in order to detect additional clinically relevant mutations. In addition, we developed a sensitive supplementary test for the ASXL1 c.1934dupG p.Gly646fs mutation by fragment analysis. Using our custom filter chain, we found 96 different reportable variants that were not detected by the default filter chain. Twenty-six of these were classified as variants of strong or potential clinical significance (tier I/tier II variants), and the custom filtering discovered otherwise undetected tier I/tier II variants in 25 of 132 patients with clinically relevant mutations (19%). The remaining 70 variants not detected by the default filter chain were classified as variants of unknown significance. Among these were several unique variants with possible pathogenic potential judged by bioinformatic predictions. The recently launched Oncomine 5.14 extended filter algorithm detects most but not all of the tier I/tier II variants that were not detected by the default filter. The supplementary fragment analysis for the ASXL1 c.1934dupG p.Gly646fs confidently detected a variant allele frequency of down to 4.8% (SD 0.83%). The assay also detected the ASXL1 c.1900_1922del23 mutation. Detection of clinically relevant variants with the Oncomine Myeloid Research NGS assay can be significantly improved by supplementing the default filter chain with custom data filtering or the recently launched Oncomine 5.14 extended filter algorithm. Our accessory fragment analysis facilitates easy testing for frequent ASXL1 mutations that are poorly or not covered by the NGS assay.

Finding a suitable library size to call variants in RNA-Seq

BackgroundRNA sequencing allows the study of both gene expression changes and transcribed mutations, providing a highly effective way to gain insight into cancer biology. When planning the sequencing of a large cohort of samples, library size is a fundamental factor affecting both the overall cost and the quality of the results. Here we specifically address how overall library size influences the detection of somatic mutations in RNA-seq data in two acute myeloid leukaemia datasets.Results We simulated shallower sequencing depths by downsampling 45 acute myeloid leukaemia samples (100 bp PE) that are part of the Leucegene project, which were originally sequenced at high depth. We compared the sensitivity of six methods of recovering validated mutations on the same samples. The methods compared are a combination of three popular callers (MuTect, VarScan, and VarDict) and two filtering strategies. We observed an incremental loss in sensitivity when simulating libraries of 80M, 50M, 40M, 30M and 20M fragments, with the largest loss detected with less than 30M fragments (below 90%, average loss of 7%). The sensitivity in recovering insertions and deletions varied markedly between callers, with VarDict showing the highest sensitivity (60%). Single nucleotide variant sensitivity is relatively consistent across methods, apart from MuTect, whose default filters need adjustment when using RNA-Seq. We also analysed 136 RNA-Seq samples from the TCGA-LAML cohort (50 bp PE) and assessed the change in sensitivity between the initial libraries (average 59M fragments) and after downsampling to 40M fragments. When considering single nucleotide variants in recurrently mutated myeloid genes we found a comparable performance, with a 6% average loss in sensitivity using 40M fragments.ConclusionsBetween 30M and 40M 100 bp PE reads are needed to recover 90–95% of the initial variants on recurrently mutated myeloid genes. To extend this result to another cancer type, an exploration of the characteristics of its mutations and gene expression patterns is suggested.

Abstract 3623: Differences in the frequency of CRC-associated pathogen variants in colorectal adenomas and cancers from the Hungarian population

Abstract Background: Colorectal cancer (CRC) has high incidence in Eastern-Europe, especially in Hungary. In addition to environmental factors, the genetic and epigenetic background of this phenomenon still remains unknown. Aims: We aimed to perform whole exome sequencing along the colorectal adenoma-carcinoma sequence on tissue samples in order to identify characteristic germline and somatic variants. Materials &amp; methods: Genomic DNA was isolated from 111 colonic tissue samples including 20 adenomas (AD) with matched normal adjacent tissue (NAT) pairs, 18 CRC with matched NAT pairs, 3 normal (N) young donors, 1 CRC and 1 AD and from 2 colorectal cancer cell lines (HT29, SW480), furthermore, 20 buffy coat (from 10 healthy, 5 adenoma and CRC patients). Exome enrichment was done with the Nextera DNA Exome Kit and sequencing was performed with the NextSeq 500/550 High Output v2 kit using the NextSeq 500 Instrument. Raw data analysis and demultiplexing was completed on BaseSpace Sequence Hub. Germline and somatic variants were determined by Genome Analysis Toolkit (GATK) and MuTect2 algorithms by using the default filter settings and were confirmed by ddPCR. Results: The total number of detected variants increased along the adenoma-carcinoma sequence and NAT samples showed higher number of variants compared to healthy tissues. On the basis of the somatic variant analysis, certain genes with the most frequent CRC-associated pathogenic mutations could be detected in relatively higher [e.g. APC (89% of AD samples, 74% of CRC samples)], with relatively lower [e.g. KRAS (47% of ADs, 33% CRC), TP53 (26% of ADs, 14% of CRCs), or with average frequencies [PIK3CA (4.8% of AD samples, 11% of CRC samples), NRAS (5% of ADs, 4.7% of CRCs)]. One adenoma sample (4.7%) exerted BRAF mutation. On the basis of the COSMIC database, the expected variant profile of the CRC cell lines could be confirmed (HT-29: BRAF, TP53; SW480: KRAS, TP53). Among the germline variants, MTHFR C677T (rs1801133) were detected in 4 N (40% CT) 8 AD (37% CT, 5% TT) 9 CRC samples (37% CT, 11% TT), and MTHFR A1298C (rs1801131) were detected in 7 N (50% AC, 20% CC) 12 AD (47% AC, 16% CC) and 10 CRC samples (42% AC, 11% CC) representing a relatively higher frequency in the Hungarian population compared to the European and worldwide statistics. Conclusion: Identification of CRC-associated pathogen variant patterns in the Hungarian population revealed a higher tumor mutation burden already in pre-malignant colorectal adenoma samples, as well as in CRC. Alterations in the frequencies of CRC-associated somatic variants compared to the European averages might contribute to the high CRC incidence observed in the Hungarian population. The germline variants of MTHFR gene were observed with a relatively higher frequency in our cohort having an effect on the DNA methylation regulation system that might be a link between the genetic and epigenetic alterations of the CRC development. Citation Format: Alexandra Kalmar, Orsolya Galamb, Barnabas Wichmann, Barbara B Bartak, Zsofia B Nagy, Sara Zsigrai, Krisztina Szigeti, Orsolya Pipek, Anna Medgyes-Horváth, Istvan Csabai, Zsolt Tulassay, Peter Igaz, Bela Molnar. Differences in the frequency of CRC-associated pathogen variants in colorectal adenomas and cancers from the Hungarian population [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3623.

Default filtration for datum cylinders: a proposal

Abstract New default filters are proposed for datum cylinders subject to the ISO GPS family of standards. The filters are based on new geometric concepts: the intersection structured hull for outer cylinders and the union structured hull for inner cylinders. The hulls are mathematically defined, and their properties are illustrated graphically and analytically. The resulting filters’ behavior is compared to the closing ball filter, showing improved effectiveness in representing part assembly in the presence of a variety of form errors, surface interruptions, and voids.

2876 YouTube Videos on Irritable Bowel Disease: A Qualitative Analysis of Views and Content

INTRODUCTION: IBS is a functional disorder of the GI tract. It accounts for 25-50% of all referrals to gastroenterologists in the US, ranking it as the second highest cause of work absenteeism. Patients tend to use the internet, and particularly social media sites, to learn more about their medical condition. YouTube being one of the largest search engines, has grown its popularity as a go-to health-related source of information. This study aims to evaluate the quality of material available for IBS patients. METHODS: Youtube.com main page was queried for the search term “Irritable Bowel Disease”. The resulting videos were evaluated for content, duration, source, and audience interaction: number of views, likes, and dislikes. Content was classified as useful, misleading or patient’s views/experience. Useful videos were further analyzed for content using the published DISCERN instrument with 16 questions each consists of 5-point scale for assessing the quality of health information. RESULTS: The search phrase “Irritable Bowel Disease” recaptured thousands of videos sorted by default filter of “relevance.” The top 20 videos were analyzed as these are the videos that patients were likely to view by visitor statistics. On average, videos had 5:41 minutes duration, 184892 views, 1471 likes, and 81 dislikes. 50% of videos were from health care professionals, 30% from health care organizations, 10% from individuals/patients, 5% clips from TV shows, and 5% non-professional educational groups. 60% of the videos were classified as useful. Wheres 25% were misleading, 10% were irrelevant, and 5% were patient experience. Useful videos scored an average of 2.8 out of 5 on the DISCERN scale indicating fair quality. 66% of the useful videos were from health care professionals with average DISCERN score of 2.6 out of 5. 33% were from health care organizations with an average score of 3.3 out of 5. CONCLUSION: Despite YouTube being the fastest growing shared videos website, it lacks qualitative videos about a very common disease such IBS. As one of the largest online references for many patients, healthcare organizations can utilize this platform to correct misconceptions about the disease. Although the majority of the top 20 videos were created by healthcare professionals, it is advisable to improve their content quality and given the prevalence of misleading videos, patients should exercise extra caution towards these information and verify it directly from a healthcare provider.

Comparing Filtering Techniques for Removing Vegetation from UAV-Based Photogrammetric Point Clouds

Digital Elevation Models (DEMs) are 3D representations of the Earth’s surface and have numerous applications in geomorphology, hydrology and ecology. Structure-from-Motion (SfM) photogrammetry using photographs obtained by unmanned aerial vehicles (UAVs) have been increasingly used for obtaining high resolution DEMs. These DEMs are interpolated from point clouds representing entire landscapes, including points of terrain, vegetation and infrastructure. Up to date, there has not been any study clearly comparing different algorithms for filtering of vegetation. The objective in this study was, therefore, to assess the performance of various vegetation filter algorithms for SfM-obtained point clouds. The comparison was done for a Mediterranean area in Murcia, Spain with heterogeneous vegetation cover. The filter methods that were compared were: color-based filtering using an excessive greenness vegetation index (VI), Triangulated Irregular Networks (TIN) densification from LAStools, the standard method in Agisoft Photoscan (PS), iterative surface lowering (ISL), and a combination of iterative surface lowering and the VI method (ISL_VI). Results showed that for bare areas there was little to no difference between the filtering methods, which is to be expected because there is little to no vegetation present to filter. For areas with shrubs and trees, the ISL_VI and TIN method performed best. These results show that different filtering techniques have various degrees of success in different use cases. A default filter in commercial software such as Photoscan may not always be the best way to remove unwanted vegetation from a point cloud, but instead alternative methods such as a TIN densification algorithm should be used to obtain a vegetation-less Digital Terrain Model (DTM).