Array-based Methods Research Articles

Theoretical investigation of the excitation of leaky modes for multi-layered models

Summary The dispersion analysis with array-based methods enables us to detect and analyse the multi-mode dispersive waves with weak amplitudes. Over the past years, there has been widespread extraction of higher normal modes from earthquake records and ambient noise, which have been extensively employed in near-surface and crustal investigations. Notably, the frequent reporting of leaky modes in recent observations has gained significant attention. This is because leaky modes can provide more constraints on subsurface structures. Particularly, a subset of leaky modes is found to be sensitive to P-wave velocities, which has the potential to compensate for the limitations of traditional surface wave inversion. Nevertheless, due to the lack of knowledge of the excitation and practical application of leaky modes, it is urgent to have an effective guide in selecting certain leaky modes for practical inversion combined with other imaging methods. To this end, the theoretical investigation into the excitation of leaky modes for multi-layered models is undertaken. By computing theoretical seismograms for various source mechanisms and source depths with the discrete wavenumber method and the normal-mode summation method respectively, the qualitative evaluation of the leaky-mode contributions to the synthesized seismograms is conducted. Additionally, the impact of the source depth for the same source mechanism is meticulously examined by the dispersion spectra. Furthermore, with the accurate computation of leaky modes, we categorize the leaky modes into PL and OP (organ-pipe) modes according to their distinctive properties, i.e., their attenuation and eigen-displacements, which may be used to explain very well the occurrence of certain leaky modes on the dispersion spectrum and be indicative of the reasonable choice of PL modes to put them into practical inversion for P-velocity structures.

Clinical implementation and patient-specific quality assurance solutions for real-time target tracking and dynamic delivery in Radixact synchrony.

The installation and testing of the first Radixact with Synchrony system in Colombia marked a significant milestone in Latin America's medical landscape. There was a need to devise a robust quality assurance protocol to comprehensively evaluate both dose delivery and motion tracking accuracy. However, testing experiences under clinical conditions have not been extensively reported. Additionally, there are limited recommended measuring devices for Synchrony evaluation. To validate and implement an alternative setup for dynamic-PSQA while testing Synchrony's functionality under clinical scenarios, including real-patient motion traces, and to provide guidance to new centers undergoing clinical implementation of Helical Synchrony. This approach involves using the Iba miniPhantomR with strategically placed fiducial markers for configuring Gafchromic-films and array-based setups. When paired with the CIRS Dynamic Platform, this enables an innovative dynamic setup with trackable features for Synchrony delivery testing. Assessment scenarios, including compensation (M1S1) and no-motion compensation (M1S0), were evaluated using 2D-gamma pass rate analysis with multiple clinical gamma criteria. The Synchrony-Simulation feature was used to assess pre-treatment performance and capture the patient's target motion pattern. Synchrony for common clinical cases with patient's motion-traces was validated. The results for M1S0 and M1S1 demonstrated consistency with previous studies evaluating Synchrony functionality. Analysis using different gamma criteria unveiled dosimetric differences and impacts across various motion ranges. The application of effective kV-dose subtraction for array-based methods is of upmost importance when evaluating dynamic-PSQA with stringent gamma-criteria. However, no significant kV-dose impact on EBT3-Film was detectable. Two implemented configurations for dynamic-PSQA setups were validated and successfully integrated into our clinic. We addressed both the benefits and limitations of array-based and film-based methods. The functionality and limitations of Synchrony were evaluated using the proposed setups. The potential utility of Synchrony-Simulation, along with the proposed patient-case classification table, can offer valuable support for new users during the clinical implementation of Synchrony treatments.

Nonlinear ultrasonic Lamb wave phased array imaging based on hybrid array and time-reversal of harmonic

Fatigue cracks, as one of the early performance deteriorations of plate-like structures, are critical to be detected in a timely manner to prevent further failures and disastrous accidents. But the intimate contact of crack interfaces is difficult to form a significant scattering field of traditional ultrasonic Lamb waves, resulting in the insensitivity of Lamb wave phased array-based imaging methods to crack imaging. To break through the detecting limitations of conventional Lamb wave phased array, the nonlinear Lamb wave-based phased array method is first proposed to realize fatigue crack imaging, which is achieved by a new form of phased array with hybrid elements, signal processing for harmonic enhancement and time-reversal based harmonic field focusing. The hybrid array is designed for efficient transmission and capture of fundamental wave and harmonics, and Pulse-inversion technology and continuous wavelet transform filter are used to extract and enhance second harmonic response, and the images are obtained by the time domain topological energy imaging algorithm. Finally, the imaging results of barely visible fatigue cracks and through-holes in metallic plate structures using linear and nonlinear Lamb wave-phased array are compared. The nonlinear ultrasonic Lamb wave-phased array demonstrates excellent capability of fatigue crack imaging.

P53 Abnormal (Copy Number High) Endometrioid Endometrial Carcinoma Has a Prognosis Indistinguishable From Serous Carcinoma.

Among the 4 molecular subgroups of endometrial carcinoma, the p53 abnormal (copy number high) subgroup has the worst prognosis; however, the histologic characteristics of this subgroup are not well established. Also, it is not well established whether low-grade tumors can belong to the p53 abnormal molecular subgroup and if so, what is the prognostic significance of the p53-mutated molecular subgroup in low-grade tumors. In the current study, we included 146 p53-mutated endometrial carcinomas and performed molecular subgrouping either based on a combination of immunohistochemical studies for p53 and MMR protein expression and POLE mutation testing (81 cases) or based on array-based and sequencing-based technologies (65 cases). We excluded cases that belonged to the POLE mutant or MSI molecular subgroups and only studied p53 abnormal (molecular subgroup) endometrial carcinomas (125 cases). In 71 cases, the molecular subgroup was determined by a combination of immunohistochemical studies and POLE mutation testing, and in 54 cases by array-based and sequencing-based methods. We reviewed 1 to 2 representative digital slides from each case and recorded the morphologic characteristics as well as clinical, treatment, and survival follow-up data. Overall, 47 cases were classified as endometrioid carcinoma, 55 serous carcinoma, and 23 other histotypes. Eight cases were FIGO 1, 21 were FIGO 2, and 91 were FIGO 3. A significant proportion of the cases (24.2%) were histologically classified as low-grade (FIGO 1 or 2) endometrioid carcinoma. There was no morphologic characteristic that showed prognostic implication. There was no significant difference in survival among different histotypes (P=0.60). There was no significant difference in survival among low-grade endometrioid (FIGO 1 or 2) versus high-grade (FIGO 3) tumors (P=0.98). Early-stage (stage I), low-grade tumors showed no significant survival advantage over early-stage, high-grade tumors (P=0.16) and this was more evident in FIGO 2 tumors. Although not statistically significant, the FIGO 2 tumors showed a trend toward worse survival than FIGO 3 tumors. Among the cases with available treatment data, more patients with early-stage high-grade tumors received adjuvant treatment, compared to patients with early-stage low-grade tumors, possibly explaining this trend (P=0.03). In conclusion, the findings of our study suggest that low-grade p53 abnormal endometrioid endometrial carcinomas (especially FIGO 2 tumors) have an aggressive course, with a prognosis similar to high-grade tumors. Furthermore, our study suggests that patients who had early-stage low-grade p53 abnormal disease might have been undertreated because of the "low-grade" histotype.

Investigating copy number variants in schizophrenia pedigrees using a new consensus pipeline called PECAN

Copy number variants (CNVs) have been implicated in many human diseases, including psychiatric disorders. Whole genome sequencing offers advantages in CNV calling compared to previous array-based methods. Here we present a robust and transparent CNV calling pipeline, PECAN (PEdigree Copy number vAriaNt calling), for short-read, whole genome sequencing data, comprised of a novel combination of four calling methods and structural variant genotyping. This method is scalable and can incorporate pedigree information to retain lower-confidence CNVs that would otherwise be discarded. We have robustly benchmarked PECAN using gold-standard CNV calls for two well-established evaluation samples, NA12878 and HG002, showing that PECAN performs with high precision and recall on both datasets, outperforming another pedigree-based CNV calling pipeline. As part of this work, we provide a list of high-confidence gold standard CNVs for the NA12878 reference sample, curated from multiple studies. We applied PECAN to a collection of pedigrees multiply affected with schizophrenia and identified a rare deletion that perfectly co-segregates with schizophrenia in one of the pedigrees. The CNV overlaps the gene PITRM1, which has been implicated in a complex phenotype including ataxia, developmental delay, and schizophrenia-like episodes in affected adults.

PATH-01. ACCURATE AND RAPID PAEDIATRIC BRAIN TUMOR CLASSIFICATION (PBT) BY METHYLATION PROFILING USING NOVEL NATIVE REAL TIME OXFORD NANOPORE TECHNOLOGY SEQUENCING TECHNOLOGY

Abstract BACKGROUND Pediatric brain tumors (PBTs) pose a significant challenge being the leading cause of cancer related mortality in children. The existing classification process is time-consuming and fails to capture the heterogeneity of PBTs. Urgent advancements in diagnostic and therapeutic approaches are needed. The WHO classification 5th edition for CNS tumors introduced DNA methylation analysis into the diagnostic process, especially for difficult-to-diagnose cases. However, the currently available DNA methylation array-based methods are laborious, costly, &require large amounts of DNA METHODS Nanopore methylation analysis is rapid, accurate, and inexpensive & requires minimal tissue. We applied this technology on 24 PBT samples that were classified into ten molecular subgroups. RESULTS Our results were compatible with those obtained through Heidelberg methylation analysis, standard histopathological examination, and molecular tests and were in concordance with the final neuro-pathological diagnosis. Moreover, for five prospective cases, that would have challenged standard methods, Nanopore yielded same-day results, guiding additional tests and providing a significant diagnostic advantage. In one case, a 2.2-year-old male, with a large left parieto-temporal tumor and a suprasellar lesioninitially treated elsewhere with upfront chemotherapy without biopsy, developed clinical deterioration. We resected the temporal lesion and frozen tissue diagnosis suggested low-grade glioma. However, same day Nanopore sequencing analysis indicated a high score for ‘Meningioma’. Final pathology examination 10 days later confirmed ‘‘Atypical meningioma, WHO grade 2” – an extremely rare diagnosis in this age group. Visual deterioration prompted immediate resection of the second lesion before final pathological confirmation. Thus, early Nanopore classification played a vital role in diagnosis and management. CONCLUSIONS Our preliminary results underscore the potential of Nanopore potential for accurate and rapid PBT classification from small brain biopsies, with DNA input as low as 100 nanograms. This cutting-edge technology promises to substantially reduce time to diagnosis, shaping future neurosurgical strategies for individualized PBT patient management.

A genome-wide study of gastric intramucosal neoplasia based on somatic copy number alterations, gene mutations, and mRNA expression patterns.

We performed comprehensive analyses of somatic copy number alterations (SCNAs) and gene expression profiles of gastric intramucosal neoplasia (IMN) using array-based methods in 97 intestinal-type IMNs, including 39 low-grade dysplasias (LGDs), 37 high-grade dysplasias (HGDs), and 26 intramucosal carcinomas (IMCs) with stromal invasion of the lamina propria to identify the molecular mechanism of IMN. In addition, we examined gene mutations using gene panel analyses. We used cluster analyses for exclusion of arbitrariness to identify SCNA patterns and expression profiles. IMNs were classified into two distinct subgroups (subgroups 1 and 2) based on SCNA patterns. Subgroup 1 showed a genomic stable pattern due to the low frequency of SCNAs, whereas subgroup 2 exhibited a chromosomal instability pattern due to the high frequencies of SCNAs and TP53 mutations. Interestingly, although the frequencies of LGD and HGD were significantly higher in subgroup 1 than in subgroup 2, IMC was commonly found in both types. Although the expression profiles of specific mRNAs could be used to categorise subgroups 1 and 2, no clinicopathological findings correlated with either subgroup. We examined signalling pathways specific to subgroups 1 and 2 to identify the association of each subgroup with signalling pathways based on gene ontology tree visualisation: subgroups 1 and 2 were associated with haem metabolism and chromosomal instability, respectively. These findings reveal a comprehensive genomic landscape that highlights the molecular complexity of IMNs and provide a road map to facilitate our understanding of gastric IMNs.

The Effect of Silver Nanoparticles on the Electrical Activity of PC12 Quasi-Neuronal Networks and the Comparison of Two Microelectrode Array-Based Neural Signal Analysis Methods

Our research group previously proposed the voltage thresholdmeasurement method (VTMM) based on the microelectrode array (MEA), and used VTMM to prove that PC12 cells, as a simpler cell culture, can be used as an alternative cell model to examine the effects of external factors on cytotoxicity and electrical excitability of neurons. However, there is no comparison between VTMM and the commonly used MEA neural signal analysis method, and no researchers have used the commonly used analysis method to study the spontaneous electrical signals of PC12 quasi-neuronal networks. This research aims to compare the characteristics and results of two MEA-based neural signal analysis methods. For the first time, the changes in spike frequency of the PC12 networks after exposure to various concentrations of silver nanoparticles for different durations was studied by means of MEA analysis method. It is found that due to the low intensity of spontaneous activity of PC12 networks, the commonly used analysis method is not suitable for the study of electrical activity of PC12 networks. Under the action of silver nanoparticles, the results of VTMM are consistent with those of the commonly used MEA analysis method, and VTMM has the advantages of being suitable for more kinds of neuron networks, short culture time, concise and rapid data analysis.

Improved beamforming schemes for estimation of multimode surface wave dispersion curves from seismic noise with reducing effect of the irregular array geometry and/or anisotropic source distribution

SUMMARY Dense array observation and seismic interferometry have revolutionized the imaging schemes of the earth structure. It is becoming possible to directly obtain the lateral variation of the earth's structure by applying array-based methods such as the cross-correlation beamforming (CBF) of the ambient noise to the subsets of the dense array, without tomography. CBF has been proven to extract the azimuth-averaged multimode surface wave dispersion curves. However, the resolution of the dispersion image generated by conventional CBF is low at high frequencies in the frequency–velocity (f-v) domain. Moreover, the irregular array geometry and uneven source distribution would bias the result of CBF, especially for the estimation of azimuth-dependent velocity. In this paper, two beamforming (BF) es are suggested to improve the resolution of multimode dispersion images in the f-v domain. First, the geometrical spreading of the wavefield is corrected to enhance the amplitude at high frequency (or large distance) and thereby improve the resolution of the dispersion image at high frequency. We call this scheme weighted correlation beamforming (WCBF). The azimuth-averaged velocity can be estimated with sufficient resolution using WCBF by stacking the BF output at each azimuth. We show that WCBF is the 2-D Fourier transform of the spatial wavefield from the viewpoint of the wavefield transform. Secondly, a modified beamforming scheme (MCBF) is suggested to reduce the effect of uneven source and/or irregular array geometry. The delay and summation in MCBF are performed only for plane waves incident from the stationary phase region. The azimuth-dependent velocity can therefore be estimated by MCBF with less dependence on the array geometry, as well as on the uneven source distribution. In terms of the estimation of azimuth-averaged phase velocity, we show the F-J method, another array-based method for extracting multimode surface waves from ambient noise using the Fourier–Bessel transform, is the azimuth-averaged version of WCBF. The reliability of WCBF and MCBF is verified based on the synthetic and field data using the array with different geometry. The dispersion image of multimode Rayleigh wave phase velocity at local and regional scales can be generated by WCBF or MCBF with high resolution. In particular, multimode dispersion curves at the local scale can be measured by MCBF with sufficient accuracy using quite short recordings from hours to days. This offers the possibility of a rapid assessment of the media properties.

Next-generation variant exon screening: Moving forward in routine genetic disease investigations

PurposePatients with genetic diseases often seek testing to reach a firm diagnosis. Based on clinical phenotypes, exome sequencing for small-nucleotide variations or array-based methods for copy-number variations (CNVs) are commonly offered to identify the underlying causative genetic variants. In this study, we investigated whether data from a standard ES test could be used to additionally identify pathogenic CNVs and increase diagnostic yield. MethodsProspectively, 134 patients presenting with a skin condition suspected of being genetic in origin were offered the next-generation variant exon screening (ngVES) test. Sequencing data were analyzed for both single-nucleotide variants and CNVs using established algorithms. ResultsThe positive detection rate for skin diseases using ngVES was 66% (88/134) with the most common diagnoses being neurofibromatosis type1 (n = 48) and tuberous sclerosis type2 (n = 12). The diagnostic increased yield from 58% to 66% was the result of additional detection of pathogenic CNVs. Each of the 9 CNVs were verified by independent genetic tests. ConclusionThe advances in the ngVES bioinformatics pipeline are proofs of concept, which improved identification of genetic variants associated with skin disease. Simultaneous single-nucleotide variants/INDEL and CNV detection by this approach demonstrates ngVES potential as a first-tier screen for any suspected genetic disease.

High-resolution DNA methylation screening of the major histocompatibility complex in multiple sclerosis.

The HLA-DRB1 gene in the major histocompatibility complex (MHC) region in chromosome 6p21 is the strongest genetic factor identified as influencing multiple sclerosis (MS) susceptibility. DNA methylation changes associated with MS have been consistently detected at the MHC region. However, understanding the full scope of epigenetic regulations of the MHC remains incomplete, due in part to the limited coverage of this region by standard whole genome bisulfite sequencing or array-based methods. We developed and validated an MHC capture protocol coupled with bisulfite sequencing and conducted a comprehensive analysis of the MHC methylation landscape in blood samples from 147 treatment naïve MS study participants and 129 healthy controls. We identified 132 differentially methylated region (DMRs) within MHC region associated with disease status. The DMRs overlapped with established MS risk loci. Integration of the MHC methylome with human leukocyte antigen (HLA) genetic data indicate that the methylation changes are significantly associated with HLA genotypes. Using DNA methylation quantitative trait loci (mQTL) mapping and the causal inference test (CIT), we identified 643 cis-mQTL-DMRs paired associations, including 71 DMRs possibly mediating causal relationships between 55 single nucleotide polymorphisms (SNPs) and MS risk. The results describe MS-associated methylation changes in MHC region and highlight the association between HLA genotypes and methylation changes. Results from the mQTL and CIT analyses provide evidence linking MHC region variations, methylation changes, and disease risk for MS.

Accurate long-read sequencing identified GBA1 as major risk factor in the Luxembourgish Parkinson’s study

Heterozygous variants in the glucocerebrosidase GBA1 gene are an increasingly recognized risk factor for Parkinson’s disease (PD). Due to the GBAP1 pseudogene, which shares 96% sequence homology with the GBA1 coding region, accurate variant calling by array-based or short-read sequencing methods remains a major challenge in understanding the genetic landscape of GBA1-associated PD. We analyzed 660 patients with PD, 100 patients with Parkinsonism and 808 healthy controls from the Luxembourg Parkinson’s study, sequenced using amplicon-based long-read DNA sequencing technology. We found that 12.1% (77/637) of PD patients carried GBA1 variants, with 10.5% (67/637) of them carrying known pathogenic variants (including severe, mild, risk variants). In comparison, 5% (34/675) of the healthy controls carried GBA1 variants, and among them, 4.3% (29/675) were identified as pathogenic variant carriers. We found four GBA1 variants in patients with atypical parkinsonism. Pathogenic GBA1 variants were 2.6-fold more frequently observed in PD patients compared to controls (OR = 2.6; CI = [1.6,4.1]). Three novel variants of unknown significance (VUS) were identified. Using a structure-based approach, we defined a potential risk prediction method for VUS. This study describes the full landscape of GBA1-related parkinsonism in Luxembourg, showing a high prevalence of GBA1 variants as the major genetic risk for PD. Although the long-read DNA sequencing technique used in our study may be limited in its effectiveness to detect potential structural variants, our approach provides an important advancement for highly accurate GBA1 variant calling, which is essential for providing access to emerging causative therapies for GBA1 carriers.

Copy Number Variations in Hereditary Spastic Paraplegia-Related Genes: Evaluation of an Iranian Hereditary Spastic Paraplegia Cohort and Literature Review

Introduction: In human genetic disorders, copy number variations (CNVs) are considered a considerable underlying cause. CNVs are generally detected by array-based methods but can also be discovered by read-depth analysis of whole-exome sequencing (WES) data. We performed WES-based CNV identification in a cohort of 35 Iranian families with hereditary spastic paraplegia (HSP) patients. Methods: Thirty-five patients whose routine single-nucleotide variants (SNVs) and insertion/deletion analyses from exome data were unrevealing underwent a pipeline of CNV analysis using the read-depth detection method. Subsequently, a comprehensive search about the existence of CNVs in all 84 known HSP-causing genes was carried out in all reported HSP cases, so far. Results and Discussion: CNV analysis of exome data indicated that 1 patient harbored a heterozygous deletion in exon 17 of the SPAST gene. Multiplex ligation-dependent probe amplification analysis confirmed this deletion in the proband and his affected father. Literature review demonstrated that, to date, pathogenic CNVs have been identified in 30 out of 84 HSP-causing genes (∼36%). However, CNVs in only 17 of these genes were specifically associated with the HSP phenotype. Among them, CNVs were more common in L1CAM, PLP1, SPAST, SPG7, SPG11, and REEP1 genes. The identification of the CNV in 1 of our patients suggests that WES allows the detection of both SNVs and CNVs from a single method without additional costs and execution time. However, because of intrinsic issues of WES in the detection of large rearrangements, it may not yet be exploited to replace the CNV detection methods in standard clinical practice.

Expansion spatial transcriptomics.

Capture array-based spatial transcriptomics methods have been widely used to resolve gene expression in tissues; however, their spatial resolution is limited by the density of the array. Here we present expansion spatial transcriptomics to overcome this limitation by clearing and expanding tissue prior to capturing the entire polyadenylated transcriptome with an enhanced protocol. This approach enables us to achieve higher spatial resolution while retaining high library quality, which we demonstrate using mouse brain samples.

What Happens In Utero Does Not Stay In Utero: a Review of Evidence for Prenatal Epigenetic Programming by Per- and Polyfluoroalkyl Substances (PFAS) in Infants, Children, and Adolescents.

Review human literature on the relationship between prenatal exposure to per- and polyfluoroalkyl substances (PFAS) and epigenetic modifications in infants, children, and adolescents < 18years of age. Eleven studies were identified, with study populations located in the U.S., Taiwan, Japan, and the Kingdom of Denmark. Many studies (n = 5) were cross-sectional, with PFAS exposure and epigenetic outcomes measured in the same tissue collected at delivery via cord blood or dried newborn blood spots. The other six studies were prospective, with prenatal PFAS measured on maternal blood during pregnancy and DNA methylation (DNAm) assessed in cord blood and childhood peripheral leukocytes (n = 1 study). Epigenetic marks of interest included global DNAm measures (LINE-1, Alu, and an ELISA-based method), candidate genes (IFG2, H19, and MEST), and epigenome-wide DNA methylation via array-based methods (Infinium 450K and EPIC). Two studies using array-based methods employed discovery and validation paradigms, in which a small subset of loci (n = 6 and n = 4) were replicated in the discovery population. One site (TNXB) was a hit in two independent studies. Collectively, loci associated with PFAS were in regions involved in growth and development, lipid metabolism, and nutrient metabolism. There is moderate human evidence supporting associations of prenatal PFAS exposure on DNAm at birth, with one study suggesting sustained effects into childhood. Future studies are warranted to link PFAS-associated DNAm to health outcomes, as well as to investigate the role of other epigenetic marks such as hydroxymethylation, miRNA expression, and histone modifications.

Application of six-component ambient seismic noise data for high-resolution imaging of lateral heterogeneities

SUMMARY We develop a novel approach for imaging subsurface lateral heterogeneities using six-component (6C) ambient seismic noise data, consisting of three translational components and three rotational components. We first derive the 6C cross-correlation functions (CCFs) from ambient seismic noise data for surface waves and then apply the modified frequency Bessel (MF-J) transform to the 6C CCFs for surface wave dispersion curves. The phase velocities of Rayleigh and Love waves can be directly calculated from the 6C CCFs of a single pair of stations. Traditional array-based surface wave methods derive the surface wave phase velocity based on the presumption of a horizontally layered model. When this assumption breaks down due to the presence of, for example, dipping layer or heterogeneities, the resulting phase velocity can be severely smeared. By contrast, the proposed approach is not limited by the layered model assumption because it relies on single-point measurements to calculate the localized dispersion relations of the formation right beneath a receiver. Our numerical modelling results demonstrate that this approach is applicable to heterogeneous models and can image small-scale subsurface anomalies with very high lateral resolution.

3-D Sound Source Localization With a Ternary Microphone Array Based on TDOA-ILD Algorithm

Sound source localization is essential for machine-based environmental perception when visual methods are not applicable. Current array-based localization methods often require many microphones and are heavy in computing. This article proposes an efficient algorithm for estimating the location of a single source in 3-D based on the time difference of arrival and interaural level difference (TDOA-ILD) with an array of only three microphones. The algorithm can compute the source 3-D coordinates with a closed-form analytical solution derived from geometrical modeling and identify the actual source from the cone of the confusion area through clustering methods. This article comprehensively evaluates the algorithm’s behavior for various array sizes and source locations in a wide range of signal-to-noise ratios (SNRs) with simulative models to prove that the algorithm achieves estimation errors close to its Cramer–Rao lower bound (CRLB). Experimental evaluation demonstrates the method’s localization feasibility in outdoor open environments with off-the-shelf sensing equipment. The proposed scheme is suitable for real-time 3-D sound source localization with cost-effective hardware.

Further Dimensions for Sensing in Biofluids: Distinguishing Bioorganic Analytes by the Salt-Induced Adaptation of a Cucurbit[7]uril-Based Chemosensor

Insufficient binding selectivity of chemosensors often renders biorelevant metabolites indistinguishable by the widely used indicator displacement assay. Array-based chemosensing methods are a common workaround but require additional effort for synthesizing a chemosensor library and setting up a sensing array. Moreover, it can be very challenging to tune the inherent binding preference of macrocyclic systems such as cucurbit[n]urils (CBn) by synthetic means. Using a novel cucurbit[7]uril-dye conjugate that undergoes salt-induced adaptation, we now succeeded in distinguishing 14 bioorganic analytes from each other through the facile stepwise addition of salts. The salt-specific concentration-resolved emission provides additional information about the system at a low synthetic effort. We present a data-driven approach to translate the human-visible curve differences into intuitive pairwise difference measures. Ion mobility experiments combined with density functional theory calculations gave further insights into the binding mechanism and uncovered an unprecedented ternary complex geometry for CB7. TThis work introduces the non-selectively binding, salt-adaptive cucurbit[n]uril system for sensing applications in biofluids such as urine, saliva, and blood serum.

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes.

DNA methylation analysis by sequencing is becoming increasingly popular, yielding methylomes at single-base pair and single-molecule resolution. It has tremendous potential for cell-type heterogeneity analysis using intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, systematic evaluation has not been performed yet. Here, we thoroughly benchmark six previously published methods: Bayesian epiallele detection, DXM, PRISM, csmFinder+coMethy, ClubCpG and MethylPurify, together with two array-based methods, MeDeCom and Houseman, as a comparison group. Sequencing-based deconvolution methods consist of two main steps, informative region selection and cell-type composition estimation, thus each was individually assessed. With this elaborate evaluation, we aimed to establish which method achieves the highest performance in different scenarios of synthetic bulk samples. We found that cell-type deconvolution performance is influenced by different factors depending on the number of cell types within the mixture. Finally, we propose a best-practice deconvolution strategy for sequencing data and point out limitations that need to be handled. Array-based methods—both reference-based and reference-free—generally outperformed sequencing-based methods, despite the absence of read-level information. This implies that the current sequencing-based methods still struggle with correctly identifying cell-type-specific signals and eliminating confounding methylation patterns, which needs to be handled in future studies.

Prenatal diagnosis and molecular cytogenetic characterization of an inherited microdeletion of chromosome 16p11.2.

Copy number variations (CNVs) in chromosome 16p11.2 (deletions and duplications) are not rare. 16p11.2 microdeletion is among the most commonly known genetic etiologies of autism spectrum disorder, overweightness, and related neurodevelopmental disorders. Here, we report the prenatal diagnosis and genetic counseling of a maternally inherited 16p11.2 microdeletion. In this family, the mother and fetus both have a normal phenotype and the same microdeletion. Following the use of molecular genetic techniques, including array-based methods, the number of reported cases has rapidly increased. The combination of prenatal ultrasound, karyotype analysis, chromosomal microarray analysis (CMA), and genetic counseling is helpful for the prenatal diagnosis of chromosomal microdeletions/microduplications.