Detection Of Aberrations Research Articles

Benchmarking of Approaches for Gene Copy-Number Variation Analysis and Its Utility for Genetic Aberration Detection in High-Grade Serous Ovarian Carcinomas.

Objective: The goal of this study was to compare the results of CNV detection by three different methods using 13 paired carcinoma samples, as well as to perform a statistical analysis of the agreement. Methods: CNV was studied using NanoString nCounter v2 Cancer CN Assay (Nanostring), Illumina Infinium CoreExome microarrays (CoreExome microarrays) and digital droplet PCR (ddPCR). Results: There was a good level of agreement (PABAK score > 0.6) between the CoreExome microarrays and the ddPCR results for finding CNVs. There was a moderate level of agreement (PABAK values ≈ 0.3-0.6) between the NanoString Assay results and microarrays or ddPCR. For 83 out of 87 target genes studied (95%), the agreement between the CoreExome microarrays and NanoString nCounter was characterized by PABAK values < 0.75, except for MAGI3, PDGFRA, NKX2-1 and KDR genes (>0.75). The MET, HMGA2, KDR, C8orf4, PAX9, CDK6, and CCND2 genes had the highest agreement among all three approaches. Conclusions: Therefore, to get a better idea of how to genotype an unknown CNV spectrum in tumor or normal tissue samples that are very different molecularly, it makes sense to use at least two CNV detection methods. One of them, like ddPCR, should be able to quantitatively confirm the results of the other.

Detection of aberration in human behavior using shallow neural network over smartphone inertial sensors data

AbstractThe integration of different Mobile Edge Computing (MEC) applications has significantly enhanced the realm of security and surveillance, with Human Activity Recognition (HAR) standing out as a crucial application. The diverse sensors found in smartphones have made it convenient for monitoring applications to gather and analyze data, rendering them valuable for HAR purposes. Moreover, MEC can be employed to automate surveillance, allowing intelligent monitoring of restricted areas to identify and respond to unwanted or suspicious activities. This research develops a system using motion sensors in smartphones to identify unusual human activities. People's smartphones were employed to monitor both suspicious and regular activities. Information was collected for various actions categorized as either suspicious or regular. When a person performs a certain action, the smartphone records a series of sensory data, analyse important patterns from the basic data, and then determines what the person is doing by combining information from different sensors. To prepare the data, information from different sensors was aligned to a shared timeline. In this study, we used a sliding window approach on synchronized data to feed sequences into LSTM and CNN models. These models, which include initial layers of LSTM and CNN, automatically find important patterns in the order of human activities. We combined SVM with the features extracted by the shallow Neural Network to make a mixed model that predicts suspicious activities. Lastly, we compared LSTM, CNN, and our new shallow mixed neural network using a new real‐time dataset. The mixed model of CNN and SVM achieved an accuracy of 94.43%. Additionally, the sliding window method's effectiveness was confirmed with a 4.28% improvement in accuracy.

Development of a Framework for Establishing 'Gold Standard' Outbreak Data from Submitted SARS-CoV-2 Genome Samples.

Submitted genomic data for respiratory viruses reflect the emergence and spread of new variants. Although delays in submission limit the utility of these data for prospective surveillance, they may be useful for evaluating other surveillance sources. However, few studies have investigated the use of these data for evaluating aberration detection in surveillance systems. Our study used a Bayesian online change point detection algorithm (BOCP) to detect increases in the number of submitted genome samples as a means of establishing 'gold standard' dates of outbreak onset in multiple countries. We compared models using different data transformations and parameter values. BOCP detected change points that were not sensitive to different parameter settings. We also found data transformations were essential prior to change point detection. Our study presents a framework for using global genomic submission data to develop 'gold standard' dates about the onset of outbreaks due to new viral variants.

Algorithm for detecting abnormal electricity usage by customers based on electricity big data and deep learning

Abstract In order to optimize the effect of individuals’ aberrant power utilization detection and reinforce the recognition rate and accuracy of abnormal power consumption detection of electricity use, an aberrant power utilization identification algorithm based on electric power big data and deep learning is proposed. Taking the two-way dialogue between power users and the power company as the basic perspective, real-time monitoring and collection of power consumption dynamics of users is carried out, and the power big data collection framework is designed. The retrieval of aberrant power utilization detection indexes is completed. Based on the deep learning algorithm, the artificial neural network base operation medium is combined to quantitatively solve the aberrant power utilization indexes, completing the design of a user aberrant power utilization detection algorithm. Experimental results show that the accuracy of the designed algorithm is 0.963, the F1 value is 0.985, and the AUC value is 0.942, which can effectively identify the aberrant power utilization and has a better performance of abnormal power consumption identification and detection.

Performance analysis of free space optical communications with FOA-WFS

Adaptive optics (AO) technology can correct wavefront distortion in coherent free space optical communication (FSOC), with wavefront sensors playing a vital role in this process. However, traditional wavefront sensors are large and expensive. Therefore, we propose using the inexpensive and easy-to-deploy flat optics angle-based wavefront sensor (FOA-WFS) to measure the wavefront aberration. It aims to meet the needs of various FSOC applications. We first establish the relationship between the energy ratio and the Zernike coefficient through theoretical studies and analyze the feasibility of applying the FOA-WFS to the FSOC. We then generate experimental datasets based on the relevant principles. Through numerical simulation, we verify that it can reconstruct wavefront aberration accurately and improve system performance. Finally, we analyze the mixing efficiency and bit error rate based on the collected aberration data by the experimental platform. The results indicate that the AO system based on the FOA-WFS can efficiently improve the performance of the FSOC. This study provides a novel wavefront aberration detection method for designing the AO systems in the FSOC.

P-072 Fresh testicular sperm seems to yield more fertilization abnormalities and early pregnancy loss than frozen testicular sperm

Abstract Study question How do ICSI outcomes using fresh testicular sperm, compare to those using frozen samples cryopreserved from the previous fresh testicular sperm extraction (TESE)? Summary answer Although fresh testicular sperm led to a better fertilization and pregnancy rate,it yielded more fertilization abnormalities and miscarriages than frozen sperm for the same couples. What is known already Testicular biopsies can be performed in cases of severe male infertility to search for spermatozoa. In the current era of advanced reproductive techniques, ICSI in association with TESE may be an effective treatment for patients with azoospermia. TESE could be performed the day of oocyte pick-up, or instead, it may be accomplished previously, and in this case TESE spermatozoa are cryopreserved for the future ICSI cycles. However, when reviewing the literature, not a lot of papers tried to compare the ICSI outcomes between fresh and frozen testicular sperm in the same couples. Study design, size, duration This retrospective study included the clinical and embryological data of pairs of fresh and frozen sperm injection cycles from couples after TESE between 2010 and 2023. The first ICSI was performed with fresh spermatozoa retrieved from TESE. The subsequent ICSI cycles used frozen spermatozoa from the first TESE. Participants/materials, setting, methods All infertile couples that underwent ICSI+TESE with testicular sperm cryopreservation in the study period were identified (110 couples). Of whom, 34 couples who underwent 40 subsequent ICSI cycle using frozen spermatozoa from the previous TESE were included. ICSI cycles were divided in: Group 1:ICSI with TESE and fresh testicular sperm injection Group 2:ICSI with frozen testicular sperm injection ICSI outcomes were compared for: fertilization/fertilization abnormalities rate, embryo quality, pregnancy and miscarriages rate, and live birth rate. Main results and the role of chance The average age of men who underwent ICSI was 42 years, while that of women was 33 years. On average, the couples had their ICSI with frozen sperm within 1.7 years after the TESE. There were no significant differences in women’s clinical parameters, the type of ovarian stimulation used nor its primary outcome between the two ICSI attempts. Although the primary outcome of ICSI showed a significantly higher fertilization rate for fresh testicular sperm compared to frozen sperm (64.4% vs 44.8%; p = 0.003), there was a tendency for more fertilization abnormalities when fresh testicular sperm was used (8.3% vs 6.2%, p = 0.4). Despite a better quality of cleavage embryos in ICSI with fresh testicular sperm (43.9% vs 39.2%, p = 0.6) and a higher pregnancy rate for the same group (21.9% vs 15.9%, p = 0.52), the miscarriage rate was twice as high when compared to the miscarriage rate of ICSI with frozen testicular sperm (6.7% vs 3.4%, p = 0.8), indicating that cryopreservation of testicular sperm could play a role in selecting better sperm for micro-injection. As for the live birth rate, ICSI with frozen sperm led to not statistically inferior rates when compared with ICSI with fresh sperm in the same couples (6.7% vs 10%, p = 0.6). Limitations, reasons for caution Due to our inclusion criteria, the study population may seem to be too reduced to reach significant results. To gain more informative insights, we recommend combining results from different centers and referring to the etiology of azoospermia that led to the TESE procedure. Wider implications of the findings Genetic testing and chromosomal aberration detection on testicular spermatozoa before and after cryopreservation could be proposed to compare the proportion of defected spermatozoa in both types of samples. Trial registration number not applicable

Optical Genome Mapping for Applications in Repeat Expansion Disorders.

Short tandem repeat (STR) expansions are associated with more than 60 genetic disorders. The size and stability of these expansions correlate with the severity and age of onset of the disease. Therefore, being able to accurately detect the absolute length of STRs is important. Current diagnostic assays include laborious lab experiments, including repeat-primed PCR and Southern blotting, that still cannot precisely determine the exact length of very long repeat expansions. Optical genome mapping (OGM) is a cost-effective and easy-to-use alternative to traditional cytogenetic techniques and allows the comprehensive detection of chromosomal aberrations and structural variants >500 bp in length, including insertions, deletions, duplications, inversions, translocations, and copy number variants. Here, we provide methodological guidance for preparing samples and performing OGM as well as running the analysis pipelines and using the specific repeat expansion workflows to determine the exact repeat length of repeat expansions expanded beyond 500 bp. Together these protocols provide all details needed to analyze the length and stability of any repeat expansion with an expected repeat size difference from the expected wild-type allele of >500 bp. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Genomic ultra-high-molecular-weight DNA isolation, labeling, and staining Basic Protocol 2: Data generation and genome mapping using the Bionano Saphyr® System Basic Protocol 3: Manual De Novo Assembly workflow Basic Protocol 4: Local guided assembly workflow Basic Protocol 5: EnFocus Fragile X workflow Basic Protocol 6: Molecule distance script workflow.

Feasibility and Impact of Embedding an Extended DNA and RNA Tissue-Based Sequencing Panel for the Routine Care of Patients with Advanced Melanoma in Spain.

Targeted NGS allows a fast and efficient multi-gene analysis and the detection of key gene aberrations in melanoma. In this study, we aim to describe the genetic alterations in a series of 87 melanoma cases using the oncomine focus assay (OFA), relate these results with the clinicopathological features of the patients, and compare them with our previous study results in which we used a smaller panel, the oncomine solid tumor (OST) DNA kit. Patients diagnosed with advanced melanoma at our center from 2020 to 2022 were included and DNA and RNA were extracted for sequencing. Common mutated genes were BRAF (29%), NRAS (28%), ALK, KIT, and MAP2K1 (5% each). Co-occurring mutations were detected in 29% of the samples, including BRAF with KIT, CTNNB1, EGFR, ALK, HRAS, or MAP2K1. Amplifications and rearrangements were detected in 5% of cases. Only BRAF mutation showed a significant statistical association with sun exposure. For patients with a given genetic profile, the melanoma survival and recurrence-free survival rates were equivalent, but not for stage and LDH values. This expanded knowledge of molecular alterations has helped to more comprehensively characterize our patients and has provided relevant information for deciding the best treatment strategy.

Occupational health risk recognition, evaluation, and management of radiation workers in Gansu province, China

ObjectiveIn order to protect the health of radiation workers, scientific management of radiation workplace protection is implemented, and occupational health risks of radiation workplaces in Gansu Province, China are identified and evaluated through monitoring. MethodsThe basic situation of occupational health management of radiological workers in 1366 radiological diagnosis and treatment institutions was investigated, and 596 monitoring hospitals were selected for occupational health monitoring. Using a 2-IN∗2-in NaI (Tl) scintillation spectrometer and its supporting software, internal thyroid irradiation monitoring was performed. Fifty-one underground workers in a deep mine iron mine were selected to monitor the effect of high radon exposure. Results11 (6%) monitored hospital interventional radiology staff detected lead outside the aprons between 5 mSv and 20 mSv during a single monitoring period; In nuclear medicine, radiation monitoring in the thyroid detected 3(15%) people with doses between 5 mSv and 20msv.The chromosome aberration rate and Detection rate of posterior pole subcapsular opacification of interventional radiation group and nuclear medicine group was higher than that of conventional radiation group, and the difference between interventional radiation group and conventional medicine group was statistically significant. Abnormal detection of tumor markers in serum after sustained radon exposure accounted for 39.2% of NSE(neuron-specific enolase), 22.5% of SCC(squamous cell carcinoma associated antigen), and 5.9% of CyFRA21-1(cytokeratin 19 fragment), respectively, chest low-dose CT showed plaque and stripe shadow in 21 cases (41.2%) and nodules in 16 cases (31.4%). ConclusionIndividual dose monitoring found that radiation workers engaged in interventional radiology were exposed to higher doses and had higher occupational risks. The results of occupational health examination show that there is a certain degree of radiation injury in interventional radiology and nuclear medicine workers. Nuclear medicine radiation monitoring results show that some workplaces have radioactive contamination. The radon exposure of deep mine miners has a higher occupational risk of lung cancer caused by high radon.The analysis of chromosome aberration is an important index of occupational health monitoring of radiation workers.

RFX6 haploinsufficiency predisposes to diabetes through impaired beta cell function

Aims/hypothesisRegulatory factor X 6 (RFX6) is crucial for pancreatic endocrine development and differentiation. The RFX6 variant p.His293LeufsTer7 is significantly enriched in the Finnish population, with almost 1:250 individuals as a carrier. Importantly, the FinnGen study indicates a high predisposition for heterozygous carriers to develop type 2 and gestational diabetes. However, the precise mechanism of this predisposition remains unknown.MethodsTo understand the role of this variant in beta cell development and function, we used CRISPR technology to generate allelic series of pluripotent stem cells. We created two isogenic stem cell models: a human embryonic stem cell model; and a patient-derived stem cell model. Both were differentiated into pancreatic islet lineages (stem-cell-derived islets, SC-islets), followed by implantation in immunocompromised NOD-SCID-Gamma mice.ResultsStem cell models of the homozygous variant RFX6−/− predictably failed to generate insulin-secreting pancreatic beta cells, mirroring the phenotype observed in Mitchell–Riley syndrome. Notably, at the pancreatic endocrine stage, there was an upregulation of precursor markers NEUROG3 and SOX9, accompanied by increased apoptosis. Intriguingly, heterozygous RFX6+/− SC-islets exhibited RFX6 haploinsufficiency (54.2% reduction in protein expression), associated with reduced beta cell maturation markers, altered calcium signalling and impaired insulin secretion (62% and 54% reduction in basal and high glucose conditions, respectively). However, RFX6 haploinsufficiency did not have an impact on beta cell number or insulin content. The reduced insulin secretion persisted after in vivo implantation in mice, aligning with the increased risk of variant carriers to develop diabetes.Conclusions/interpretationOur allelic series isogenic SC-islet models represent a powerful tool to elucidate specific aetiologies of diabetes in humans, enabling the sensitive detection of aberrations in both beta cell development and function. We highlight the critical role of RFX6 in augmenting and maintaining the pancreatic progenitor pool, with an endocrine roadblock and increased cell death upon its loss. We demonstrate that RFX6 haploinsufficiency does not affect beta cell number or insulin content but does impair function, predisposing heterozygous carriers of loss-of-function variants to diabetes.Data availabilityUltra-deep bulk RNA-seq data for pancreatic differentiation stages 3, 5 and 7 of H1 RFX6 genotypes are deposited in the Gene Expression Omnibus database with accession code GSE234289. Original western blot images are deposited at Mendeley (https://data.mendeley.com/datasets/g75drr3mgw/2).Graphical

Deep tomography for the three-dimensional atmospheric turbulence wavefront aberration

Multiconjugate adaptive optics (MCAO) can overcome atmospheric anisoplanatism to achieve high-resolution imaging with a large field of view (FOV). Atmospheric tomography is the key technology for MCAO. The commonly used modal tomography approach reconstructs the three-dimensional atmospheric turbulence wavefront aberration based on the wavefront sensor (WFS) detection information from multiple guide star (GS) directions. However, the atmospheric tomography problem is severely ill-posed. The incomplete GS coverage in the FOV coupled with the WFS detection error significantly affects the reconstruction accuracy of the three-dimensional atmospheric turbulence wavefront aberration, leading to a nonuniform aberration detection precision over the whole FOV. We propose an efficient approach for achieving accurate atmospheric tomography to overcome the limitations of the traditional modal tomography approach. We employed a deep-learning-based approach to the tomographic reconstruction of the three-dimensional atmospheric turbulence wavefront aberration. We propose an atmospheric tomography residual network (AT-ResNet) that is specifically designed for this task, which can directly generate wavefronts of multiple turbulence layers based on the Shack-Hartmann (SH) WFS detection images from multiple GS directions. The AT-ResNet was trained under different turbulence intensity conditions to improve its generalization ability. We verified the performance of the proposed approach under different conditions and compared it with the traditional modal tomography approach. The well-trained AT-ResNet demonstrates a superior performance compared to the traditional modal tomography approach under different atmospheric turbulence intensities, various turbulence layer distributions, higher-order turbulence aberrations, detection noise, and reduced GSs conditions. The proposed approach effectively addresses the limitations of the modal tomography approach, leading to a notable improvement in the accuracy of atmospheric tomography. It achieves a highly uniform and high-precision wavefront reconstruction over the whole FOV. This study holds great significance for the development and application of the MCAO technology.

Phage-Displayed SH2 Domain Libraries: From Ultrasensitive Tyrosine Phosphoproteome Probes to Translational Research.

Tyrosine phosphorylation is a critical regulator of cell signaling. A large fraction of the tyrosine phosphoproteome, however, remains uncharacterized, largely due to a lack of robust and scalable methods. The Src homology 2 (SH2) domain, a structurally conserved protein domain present in many intracellular signal-transducing proteins, naturally binds phosphorylated tyrosine (pTyr) residues, providing an ideal scaffold for the development of sensitive pTyr probes. Its modest affinity, however, has greatly limited its application. Phage display is an in vitro technique used for identifying ligands for proteins and other macromolecules. Using this technique, researchers have been able to engineer SH2 domains to increase their affinity and customize their specificity. Indeed, highly diverse phage display libraries have enabled the engineering of SH2 domains as affinity-purification (AP) tools for proteomic analysis as well as probes for aberrant tyrosine signaling detection and rewiring, and represent a promising class of novel diagnostics and therapeutics. This review describes the unique structure-function characteristics of SH2 domains, highlights the fundamental contribution of phage display in the development of technologies for the dissection of the tyrosine phosphoproteome, and highlights prospective uses of SH2 domains in basic and translational research.

The Distribution of Risk Across Healthcare Providers and Reducing Misclassification

Four linear multilevel mixed-risk models were compared using model assumption tests and predictions. Models varied by the number of random intercepts from 1 to 4, producing 2-level through 5-level models of the same measure, operative time. Normality of the dependent variable and residuals, variance homoscedasticity, level-1, and level-2 exogeneity were tested using the robust test of the level-1 residuals variance by surgeon, estimates of density, skew, and the Hausman test. Measure (operative time by hospital and surgeon) aberrancy and risk classification were evaluated using traditional methods and used to assess distribution measures. The dependent variable and the level-1 residuals required transformation for linearity and variance stabilization, respectively. Normality criteria were met for both level-1 and level-2 residuals and standardized residuals. The likelihood ratio comparing the four models was significantly larger for the 5-level (1016.1; P&amp;lt;0.00005) model than the likelihood ratio for the four-level and other models. Shrinkage was greatest for the 2-level model (0.039; P&amp;lt;0.00005) and least for the 5-level model (0.028; P&amp;lt;0.00005). Level-1 variance homoscedasticity was confirmed by the robust variance test across all models (P&amp;gt;F=1). Aberrant value detection did not require the exclusion of any observations, while prediction intervals revealed low or high risk for 54.2% of surgeons for the 2-level model and 8.6% for the 5-level model. The traditional (c2 = -11.01; P=1) and instrumental variable (c2 = 21.06; P=1) Hausman tests show that the null hypothesis cannot be rejected for level-1 or level-2 exogeneity. Once level-1 and level-2 exogeneity was confirmed, and since deconfounding was a model consideration, causal inferential capacity was assumed. The likelihood ratio, residual variance, shrinkage, and predictions show that the 5-level model is preferred to the other models.

Abstract LB249: Multi-omics cancer risk assessment of Barrett’s esophagus with DNA methylation sequencing from endoscopic brush samples

Abstract Introduction: Barrett’s esophagus (BE) confers increased cancer risk. Endoscopic surveillance is recommended to distinguish non-dysplastic BE (NDBE), low grade dysplasia (LGD), high grade dysplasia (HGD), or adenocarcinoma (EAC) for endoscopic intervention. However, this paradigm is limited by sampling error, leading to missed/interval EAC. Herein, we aimed to classify these samples more accurately by performing whole genome methylation sequencing (WGMS) and utilizing multiple genomic features on endoscopic brush samples. Materials and methods: Endoscopic brush samples from patients with NDBE (n=18), HGD (18), EAC (18), and normal controls (18) were collected and underwent WGMS (discovery dataset). Sequence reads were processed through internal pipeline to extract CpG methylation and read level methylation ratio (alpha value). Copy number aberration (CNA) detection was performed using both CNVkit and ichorCNA. Differential methylated regions (DMRs) were identified through comparing EAC/HGD with NDBE and normal samples. Targeted methylation sequencing for selected DMRs and shallow WGMS were performed on EAC (41), HGD (26), LGD (23), NDBE (42), and normal controls (37) as validation. Ratio of the reads with alpha value&amp;gt;0.6 for each DMR was used for further analysis. Detected CNA segments were summarized into chromosome arm loss or gain (aneuploidy score or AS representing the number of chromosome arms gained or lost in a sample) and trimmed median absolute deviation (tMAD). Classification models were developed using the discovery set and the best performing one was applied to the validation dataset. Results: Genome-wide DNA methylation largely segregated different groups of samples as diagnosed; however, some unexpected group crossings were observed. Top 200 DMRs were identified between EAC/HGD and NDBE and normal samples. CNA changes were widespread in EAC, very common in HGD but rare in NDBE (17/18 EACs,14/18 HGDs, 5/18 NDBEs with AS&amp;gt;0). With tMAD &amp;gt; 0.015, 16/18 EACs, 8/18 HGDs but none of 18 NDBEs passed the threshold. EAC or HGD samples without detectable CNAs had very low “tumor” fraction as determined by methylation-based cell type deconvolution or ichorCNA. Similar results were found in the validation dataset. A multi-omics (AS, tMAD, estimated tumor fraction, and DMR methylation) model could predict EAC, HGD, or NDBE with 0.81 accuracy through cross validation (10X) and 0.73 in the independent dataset. This increased to 0.98 and 0.90 in separating high risk EAC/HGD from NDBE, respectively. Conclusion: Multi-omics data obtained from single WGMS allow for a comprehensive analysis of BE samples with varying dysplasia levels. Using classification modeling, these characteristics can be effectively used to accurately identify and distinguish between EAC and HGD from NDBE, suggesting their utility as adjuncts to endoscopic surveillance biopsies. Citation Format: Zhifu Sun, Caroline L. Matchett, Seth W. Slettedahl, William R. Taylor, Panwen Wang, Calise Berger, Caryn E. Anderson, Melissa A. Passe, Ramona Lansing, Collin E. Chalmers, Patrick H. Foote, Jeanette E. Eckel Passow, Doug W. Mahoney, John B. Kisiel, Prasad G. Iyer. Multi-omics cancer risk assessment of Barrett’s esophagus with DNA methylation sequencing from endoscopic brush samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB249.

Abstract 5014: Analytical validation of a complete system for detection and characterization of genomic aberrations in circulating tumor DNA

Abstract Cell-free DNA (cfDNA) fragments are readily detected at a low concentration in the human blood stream. In healthy patients cfDNA is primarily derived from apoptosis of hematopoietic cells. In cancer patients circulating DNA derived from tumor cells (ctDNA) undergoing apoptosis, shedding, and necrosis contribute to total cfDNA. Next generation sequencing (NGS) of cfDNA isolated from patient plasma can be used to fully characterize cancer driven changes in the tumor DNA including the relative contribution of cfDNA, single nucleotide variants (SNVs), small insertions and deletions (Indels), larger deletions, regions of amplified DNA, and structural rearrangements. Frontage has developed a complete lab system for analysis of circulating cfDNA including automated sample extraction, preparation and sequencing of libraries targeting exon sequences of 293 oncology-related genes, and a bioinformatic reporting system. The Frontage sample extraction process uses a post-extraction size selection step to remove high molecular weight DNA derived from lysed blood cells in the plasma sample to increase the sensitivity of detection of ctDNA. The NGS platform couples hybridization-based selection of genomic DNA fragments derived from protein-coding exons with deep sequencing to ~4,000X gross coverage on the NextSeq 2000. The bioinformatic pipeline integrates unique molecular barcode-based generation of consensus reads for each template molecule, somatic variant calling with GATK Mutect2 and FreeBayes, and removal of false positive variants by comparison to a 60 samples healthy patient data set. Analytical validation was performed for each component of the system. For verification of the sample extraction process, cfDNA was extracted in duplicate from four lots of pooled K2 EDTA plasma of healthy patients as well as individual K2 EDTA plasma of colorectal cancer (CRC) patients in four independent extraction runs. The mean yields of cfDNA from healthy samples ranged from 2.3 - 4.2 nanograms per ml plasma and all 32 of the isolated cfDNA aliquots from healthy patient plasma showed a prominent peak around 167 nt with minimal contamination from high molecular weight DNA. For validation of the NGS and bioinformatics platform a set of 8 different reference cfDNAs were processed through four independent runs of library preparation, sequencing, and analysis. For each of the validation runs, greater than 97% of 208 SNVs and Indels with expected allele frequencies (AF) between 2-3% were detected by the platform with higher levels of accuracy for variants at above 3% AF. Two or less false positive variants per run were detected out of 278,000 nucleotides of verified non-mutated sequence that overlapped with the 293 gene panel. Four known DNA amplification events were detected in each of the validation runs. Data from characterization of CRC and other clinical samples with the system will be presented. Citation Format: Ericca Stamper, Weiming Shen, Aman Pruthi, Casey Nagel, Marcin Piechota, Katarzyna Tomala, Qi Wei, David Willoughby. Analytical validation of a complete system for detection and characterization of genomic aberrations in circulating tumor DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5014.

Abstract 973: Plasma androgen receptor (AR) copy number gain at progression in patients randomized in the STAMPEDE phase 3 abiraterone acetate, prednisolone (AAP) and enzalutamide (ENZ) trial: An ancillary biomarker study

Abstract Addition of ENZ or AAP to androgen deprivation therapy (ADT) as first-line treatment for advanced prostate cancer improves survival compared to ADT alone. Genomic alterations in AR associate with resistance to ENZ/AAP when started for castration-resistant prostate cancer (CRPC). We aimed to test whether early use of AAP/ENZ altered the incidence of AR alterations at progression. Between July 2014 and March 2016, 1976 patients with metastatic or high-risk locally advanced prostate cancer were randomized to ADT or ADT+ENZ+AAP in the STAMPEDE trial (NCT00268476). Consenting patients were given the option to donate blood for the ancillary biomarker study at trial-defined progression and prior to start of the next line of treatment. We focused on patients who progressed within 4 years from the end of recruitment (early progressors), as these patients represent the greatest unmet need. We obtained plasma DNA at emergence of CRPC from 115 early progressors (ADT n=63, ADT+ENZ+AAP n=52). We performed liquid biopsy-focused, custom, high-coverage targeted enrichment sequencing (PCF-SELECT, Orlando et al, NAR Cancer 2022). We used a bespoke computational pipeline, leveraging allelic imbalance and fragmentome analysis, to detect circulating tumor DNA (ctDNA) in plasma samples and copy number changes. Of 108 samples that passed quality control, 94 were positive for tumor (ADT n=52, ADT+AAP+ENZ n=42). The detection rate and ctDNA fractions were similar between the two treatment groups [ADT: 86.7% (52/60), mean ctDNA fraction 0.18; ADT+ENZ+AAP: 87.5% (42/48), mean ctDNA fraction 0.21; p=0.34]. The proportion of plasma with detectable ctDNA and AR gain was significantly higher with ADT+AAP+ENZ vs ADT alone (15/42, 35.7% vs 8/52, 15.4%, p=0.03). We then implemented the same approach on plasma collected from patients progressing on ENZ started for metastatic CRPC in a prospective Phase 3b trial (PRESIDE, NCT02288247): we confirmed a high prevalence of AR gain in plasma samples with detectable ctDNA (47.7%, 95% CI 38.8-54.9) in the CRPC setting. Significant copy number aberrations in relevant prostate cancer-related genes/pathways (deletions of TP53, RB1, PTEN or DNA repair genes, or gain of PI3K/AKT1) were identified in 9 out of 42 evaluable samples in the ADT group and 18 out of 38 evaluable samples in the ADT+ENZ+AAP group (21.4% vs 47.4%, p=0.014). Treatment with ADT+ENZ+AAP increases detection of plasma AR gain at emergences of CRPC in early progressors compared to ADT alone. Detection of plasma AR gain increases at progression on ADT+ENZ regardless of the treatment setting. The impact of early use of ENZ/AAP on the detection of copy number aberrations, especially homozygous deletions, in other prostate cancer-related genes in plasma requires further investigation. Citation Format: Gianmarco Leone, Francesco Orlando, Suparna Thakali, Sharanpreet Lall, Daniel Wetterskog, Anna Wingate, Noel W. Clarke, Nicholas D. James, Francesca Demichelis, Gerhardt Attard. Plasma androgen receptor (AR) copy number gain at progression in patients randomized in the STAMPEDE phase 3 abiraterone acetate, prednisolone (AAP) and enzalutamide (ENZ) trial: An ancillary biomarker study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 973.

Algorithmic Approach to Determination of Epidemic Thresholds in Infectious Disease Surveillance Systems

Introduction: This review is devoted to the algorithmic approach to establishing epidemic thresholds for a wide range of diseases, including influenza and acute respiratory infections. Objective: To compare Russian and foreign approaches to the determination of epidemic thresholds within public health surveillance systems. Materials and methods: To reveal the algorithmic approach to establishing epidemic thresholds in the epidemiological surveillance system, we summarized the results of 14 foreign scientific works and two domestic method guidelines published before December 31, 2023. The literature search was conducted in the eLibrary, CyberLeninka, PubMed, and Google Scholar databases using the keywords “epidemic threshold” and “epidemic”. We compared domestic and foreign algorithms for establishing epidemic thresholds by various characteristics, including the statistical method used, determination of a numerical value of the epidemic threshold, complexity of the algorithm, and the possibility of automating calculations. Results: Here we discuss the classification and comparative characteristics of the basic algorithms for determining epidemic thresholds used in various countries of the world when carrying out epidemiological surveillance (including the syndromic one). We describe the existing methods for establishing and presenting epidemic thresholds, as well as the sequence of steps for performing the Farrington algorithms, the Early Aberration Detection System C1–C3, the Method of Moving Epidemics, the Method of Moving Percentiles, Multi-level identification of increasing activity by indicators taking into account mixed effects, as well as algorithms provided in Russian Method Guidelines MR 3.1.2.0118–17 and MR 3.1.2.0303–22. We also dwell on the problems of development, accuracy assessment and prospects for the implementation of existing and developed algorithms. Conclusions: Current algorithms for establishing epidemic thresholds in epidemiological surveillance systems around the world are diverse; they rely on different statistical methods and vary in complexity. To date, there is no convincing evidence of higher efficiency of any algorithm.

Bovine mortality: the utility of two data sources for the provision of population-level surveillance intelligence.

The use of existing data to provide surveillance intelligence is widely advocated but often presents considerable challenges. Two data sources could be used as proxies for the mortality experienced by the Scottish cattle population: deaths recorded in the mandatory register [Cattle Tracing System (CTS)] and fallen stock collections by the National Fallen Stock Company (NSFCo) with a nationwide voluntary membership. Data for the period 2011-2016 were described and compared to establish their strengths and limitations. Similarities and differences in their temporal, seasonal and spatial patterns were examined overall, at postcode area level and for different age groups. Temporal aberration detection algorithms (TADA) were fitted. Broadly, similar patterns were observed in the two datasets; however, there were some notable differences. The observed seasonal, annual and spatial patterns match expectations, given knowledge of Scottish cattle production systems. The registry data provide more comprehensive coverage of all areas of Scotland, while collections data provide a more comprehensive measure of the mortality experienced in 0-1-month-old calves. Consequently, estimates of early calf mortality and their impact on the livestock sector made using CTS, or successor registers, will be under-estimates. This may apply to other registry-based systems. Fitted TADA detected points of deviations from expected norms some of which coincided in the two datasets; one with a known external event that caused increased mortality. We have demonstrated that both data sources do have the potential to be utilized to provide measures of mortality in the Scottish cattle population that could inform surveillance activities. While neither is perfect, they are complementary. Each has strengths and weaknesses, so ideally, a system where they are analyzed and interpreted in parallel would optimize the information obtained for surveillance purposes for epidemiologists, risk managers, animal health policy-makers and the wider livestock industry sector. This study provides a foundation on which to build an operational system. Further development will require improvements in the timeliness of data availability and further investment of resources.

Prenatal diagnosis and molecular cytogenetic characterization of fetuses with central nervous system anomalies using chromosomal microarray analysis: a seven-year single-center retrospective study

Few existing reports have investigated the copy number variants (CNVs) in fetuses with central nervous system (CNS) anomalies. To gain further insights into the genotype–phenotype relationship, we conducted chromosomal microarray analysis (CMA) to reveal the pathogenic CNVs (pCNVs) that were associated with fetal CNS anomalies. We enrolled 5,460 pregnant women with different high-risk factors who had undergone CMA. Among them, 57 subjects with fetal CNS anomalies were recruited. Of the subjects with fetal CNS anomalies, 23 were given amniocentesis, which involved karyotype analysis and CMA to detect chromosomal abnormalities. The other 34 cases only underwent CMA detection using fetal abortive tissue. In this study, we identified five cases of chromosome aneuploid and nine cases of pCNVs in the fetuses, with a chromosomal aberration detection rate of 24.56% (14/57). In the 23 cases that were given both karyotype and CMA analysis, one case with trisomy 18 was detected by karyotyping. Moreover, CMA revealed a further three cases of pCNVs, including the 1p36.33p36.31, 7q11.23, and 1q21.1q21.2 microdeletions, with a 13.04% (3/23) increase in CMA yield over the karyotype analysis. Additionally, three cases of trisomy 13, one case of trisomy 21, and six cases of pCNVs were detected in the other 34 fetuses where only CMA was performed. Furthermore, a higher chromosomal aberration detection rate was observed in the extra CNS anomaly group than in the isolated CNS anomaly group (40.91% vs 14.29%). In conclude, several pathogenic CNVs were identified in the fetuses with CNS anomalies using CMA. Among the detected CNVs, ZIC2, GNB1, and NSUN5 may be the candidate genes that responsible for fetal CNS anomalies. Our findings provides an additional reference for genetic counseling regarding fetal CNS anomalies and offers further insight into the genotype–phenotype relationship.

Intracellular MicroRNA Imaging and Specific Discrimination of Prostate Cancer Circulating Tumor Cells Using Multifunctional Gold Nanoprobe-Based Thermophoretic Assay.

Circulating tumor cells (CTCs) have emerged as powerful biomarkers for diagnosis of prostate cancer. However, the effective identification and concurrently accurate imaging of CTCs for early screening of prostate cancer have been rarely explored. Herein, we reported a multifunctional gold nanoprobe-based thermophoretic assay for simultaneous specific distinguishing of prostate cancer CTCs and sensitive imaging of intracellular microRNA (miR-21), achieving the rapid and precise detection of prostate cancer. The multifunctional gold nanoprobe (GNP-DNA/Ab) was modified by two types of prostate-specific antibodies, anti-PSMA and anti-EpCAM, which could effectively recognize the targeting CTCs, and meanwhile linked double-stranded DNA for further visually imaging intracellular miR-21. Upon the specific internalization of GNP-DNA/Ab by PC-3 cells, target aberrant miR-21 could displace the signal strand to recover the fluorescence signal for sensitive detection at the single-cell level, achieving single PC-3 cell imaging benefiting from the thermophoresis-mediated signal amplification procedure. Taking advantage of the sensitive miR-21 imaging performance, GNP-DNA/Ab could be employed to discriminate the PC-3 and Jurkat cells because of the different expression levels of miR-21. Notably, PC-3 cells were efficiently recognized from white blood cells, exhibiting promising potential for the early diagnosis of prostate cancer. Furthermore, GNP-DNA/Ab possessed good biocompatibility and stability. Therefore, this work provides a great tool for aberrant miRNA-related detection and specific discrimination of CTCs, achieving the early and accurate diagnosis of prostate cancer.