Array Data Research Articles

South Atlantic meridional overturning circulation and its respective heat and freshwater transports from sustained observations near 34.5°S

The Atlantic Meridional Overturning Circulation (AMOC) drives northward Meridional Heat Transport (MHT) and affects climate and weather patterns, regional sea levels, and ecosystems. This study uses a methodology recently applied in 22.5°S to estimate the strength and structure of the AMOC, MHT and freshwater (FWT) transports at 34.5°S since 2005. For this, temperature and salinity profiles from sustained observations were used in conjunction with satellite and reanalysis data under two mapping methodologies: (i) an optimized mapping and (ii) a two-layer feed-forward neural network approach. There is strong agreement between both methods for AMOC, MHT and FWT estimates, thus showing the mapping methodologies are robust. In addition, the AMOC variability estimate is significantly correlated with the monthly SAMBA array data (correlation of 0.41). The mean AMOC transport of 17.0 ± 1.6 Sv, a MHT of 0.6 ± 0.1 PW, and a FWT of -0.02 ± 0.01 Sv are estimated between January 2005 and May 2023 at 34.5°S. The MHT and FWT are analyzed in terms of their horizontal (Hhor and Fhor) and overturning contributions (Hov and Fov), and vertical structures. The MHT is dominated by the overturning contribution (correlation of 0.92), while the FWT is controlled by the overturning contribution driven by the wind via Ekman transport at seasonal timescale, and by horizontal contribution at longer timescales. Both horizontal heat (Hhor) and freshwater (Fhor) components are mostly confined to the upper 500 m, with the geostrophic Fov and Fhor offsetting each other between 50 m and 500 m, and the Ekman Fov in the upper 50 m determining the negative FWT. Finally, the estimated mean Fov of -0.15 Sv agrees with previous estimates that the AMOC exports freshwater in the South Atlantic, and suggests that the AMOC is unstable. Although a long-term trend in the Fov was not detected in the past 20 years, there is a salinification trend (0.05 ± 0.01 PSU/decade) in the upper 300 m near 34.5°S since 2005.

Multi-Modal Dataset of Human Activities of Daily Living with Ambient Audio, Vibration, and Environmental Data

The detection of human activities is an important step in automated systems to understand the context of given situations. It can be useful for applications like healthcare monitoring, smart homes, and energy management systems for buildings. To achieve this, a sufficient data basis is required. The presented dataset contains labeled recordings of 25 different activities of daily living performed individually by 14 participants. The data were captured by five multisensors in supervised sessions in which a participant repeated each activity several times. Flawed recordings were removed, and the different data types were synchronized to provide multi-modal data for each activity instance. Apart from this, the data are presented in raw form, and no further filtering was performed. The dataset comprises ambient audio and vibration, as well as infrared array data, light color and environmental measurements. Overall, 8615 activity instances are included, each captured by the five multisensor devices. These multi-modal and multi-channel data allow various machine learning approaches to the recognition of human activities, for example, federated learning and sensor fusion.

Polygenic Selection and Environmental Influence on Adult Body Height: Genetic and Living Standard Contributions Across Diverse Populations.

We analyzed whole-genome sequencing (WGS) data from 51 populations and combined WGS and array data from 89 populations. Multiple types of polygenic scores (PGS) were employed, derived from multi-ancestry, between-family genome-wide association study (GWAS; MIX-Height), European-ancestry, between-family GWAS (EUR-Height), and European-ancestry siblings GWAS (SIB-Height). Our findings demonstrate that both genetic and environmental factors significantly influence adult body height between populations. Models that included both genetic and environmental predictors best explained population differences in adult body height, with the MIX-Height PGS and environmental factors (Human Development Index [HDI] + per capita caloric intake) achieving an R2 of .83. Our findings shed light on Deaton's 'African paradox', which noted the relatively tall stature of African populations despite poor nutrition and childhood health. Contrary to Deaton's hypotheses, we demonstrate that both genetic differences and environmental factors significantly influence body height in countries with high infant mortality rates. This suggests that the observed tall stature in African populations can be attributed, in part, to a high genetic predisposition for body height. Furthermore, tests of divergent selection based on the QST (i.e., standardized measure of the genetic differentiation of a quantitative trait among populations) and FST (neutral marker loci) measures exceeded neutral expectations, reaching statistical significance (p < .01) with the MIX-Height PGS but not with the SIB-Height PGS. This result indicates potential selective pressures on body height-related genetic variants across populations.

Detection of infrasound sources using three-years array data in 2019-2021 deployed at the Lützow-Holm Bay region, Antarctica

Time-space variations of infrasound source locations for three years, 2019-2021, were studied byusing a combination of two local arrays in the Lützow-Holm Bay region (LHB), Antarctica. The local arrays deployed at two coastal outcrops clearly detected temporal variations in signal frequency content as well as propagating directions during the three years. A large number of infrasound sources were detected with many located to the north and north-west directions from the arrays. These events were generated within the Southern Indian Ocean and the northern part of LHB with frequency-content of a few seconds; these “microbaroms” are believed to originate from oceanic swells. From austral summer to fall additional infrasound sources are determined to be located to the north-east. These sources might be related to the effects of katabatic winds across the continental coastal area. Furthermore, several impulsive infrasound events during the winter had higher predominant frequencies of a few Hz, higher than the microbaroms. On the basis of a comparison of source locations with sea-ice and glacier distribution form MODIS satellite images, these high-frequency sporadic sources may be cryo-seismic signals associated with cryosphere dynamics near the local arrays. These results suggest that infrasound waves can be used to monitor surface environments in the coastal area of Antarctica.

Genome-wide DNA methylation analysis reveals a unique methylation pattern for pleural mesothelioma compared to healthy pleura and other lung diseases

BackgroundPleural mesothelioma (PM) is a rare and aggressive cancer type, typically diagnosed at advanced stages. Distinguishing PM from other lung diseases is often challenging. There is an urgent need for biomarkers that can enable early detection. Interest in the field of epigenetics has increased, particularly in the context of tumour development and biomarker discovery. This study aims to identify specific changes in DNA methylation from healthy pleural tissue to PM and to compare these methylation patterns with those found in other lung diseases.ResultsEPIC methylation array data (850 K) were generated for 11 PM and 29 healthy pleura in-house collected samples. This is the first time such a large dataset of healthy pleura samples has been generated. Additional EPIC methylation array data (850 K) for pleural mesothelioma and other lung-related diseases were downloaded from public databases. We conducted pairwise differential methylation analyses across all tissue types, which facilitated the identification of significantly differentially methylated CpG sites. Extensive differential methylation between PM and healthy pleura was observed, identifying 81,968 differentially methylated CpG sites across all genomic regions. Among these, five CpG sites located within four genes (MIR21, RNF39, SPEN and C1orf101) exhibited the most significant and pronounced methylation differences between PM and healthy pleura. Moreover, our analysis delineated distinct methylation patterns specific to PM subtypes. Finally, the methylation profiles of PM were distinctly different from those of other lung cancers, enabling accurate differentiation.ConclusionsDNA methylation analyses provide a robust method for distinguishing PM from healthy pleural tissues, and specific methylation patterns exist within PM subtypes. These methylation differences underscore their importance in understanding disease progression and may serve as viable biomarkers or therapeutic targets. Moreover, differential methylation patterns between PM and other lung cancers highlights its diagnostic potential. These findings necessitate further translational studies to explore their clinical applications.

CMB constraints on natural inflation with gauge field production

The natural inflation model with a periodic cosine potential is ruled out by recent Planck 2018 data for the decay constant f ≲ 5.5 M Pl. If the Planck data is combined with the BICEP Keck array and BAO data, the model is excluded (at 2-σ) for all values of f. In this context, we revisit the model when the pseudoscalar inflation ϕ is coupled with a gauge field via a coupling of the form α/fϕ FF̃, where F(F̃) denotes the gauge field (dual) strength tensor, and α is the coupling constant. The back-reactions associated with the gauge field production during the later stages of inflation extend the duration of inflation. We numerically evaluate the dynamics of the fields while neglecting the effects due to the perturbations in the inflaton field. It allows us to determine the scalar and tensor power spectra leading to the calculations of observables at the Cosmic Microwave Background (CMB) scales. We find that the natural inflation model survives the test of the latest data only for a certain range of the coupling constant α. Our analysis shows that the latest constraints coming from the scalar spectral index are more stringent than the ones arising from the non-gaussianities and the running of the scalar spectrum. This leads to lower and upper bounds on ξ *, the parameter that controls the growth of the gauge field.

SAUNAS. II. Discovery of Cross-shaped X-Ray Emission and a Rotating Circumnuclear Disk in the Supermassive S0 Galaxy NGC 5084

Combining Chandra, Atacama Large Millimeter/submillimeter Array, EVLA, and Hubble Space Telescope archival data and newly acquired data from the Apache Point Observatory/Dual Imaging Spectrograph, we detect a double-lobed 17 kpc X-ray emission with plumes oriented approximately perpendicular and parallel to the galactic plane of the massive lenticular galaxy NGC 5084 at 0.3–2.0 keV. We detect a highly inclined ( i=71.2−1.7+1.8◦ ), molecular circumnuclear disk ( D=304−11+10 pc) in the core of the galaxy rotating (V rot(2−1)CO=242.7−6.4+9.6 km s−1) in a direction perpendicular to that of the galactic disk, implying a total mass of log10MBHM⊙=7.66−0.15+0.21 for NGC 5084's supermassive black hole. Archival EVLA radio observations at 6 and 20 cm reveal two symmetric radio lobes aligned with the galactic plane, extending to a distance of R¯=4.6±0.6kpc from the core, oriented with the polar axis of the circumnuclear disk. The spectral energy distribution lacks strong emission lines in the optical range. Three formation scenarios are considered to explain these multiwavelength archival observations: (1) active galactic nuclei (AGN) reorientation caused by accretion of surrounding material, (2) AGN-driven hot gas outflow directed along the galactic minor axis, or (3) a starburst/supernovae driven outflow at the core of the galaxy. This discovery is enabled by new imaging analysis tools including the Selective Amplification of Ultra Noisy Astronomical Signal, demonstrating the abundance of information still to be exploited in the vast and growing astronomical archives.

Graphyne-supported manganese single-atom nanozyme sensor array for bisphenol identification

Bisphenols, as common industrial raw materials, are widely used in food packaging such as plastics. However, their migration and residue may affect the hormone secretion of the human body and then lead to health problems. Therefore, a low-cost, rapid and simple detection method that can simultaneously detect multiple bisphenols is very necessary. In this work, two types of manganese single-atom nanozymes with excellent peroxidase-like activity were synthesized with graphyne as a support. A high-throughput colorimetric sensor array was constructed using three types of nanozymes (Mn-GY, Mn-GY-2N, GY-2N) to distinguish various bisphenols. Due to the absorption of bisphenol molecules on the surface of nanozymes, the activity of nanozymes decreases differently, when different bisphenols are added to the catalytic system. The results proved that the prepared sensor had good linear relationships at both low and high concentrations for determination of five bisphenols. The LODs of BPA, BPS, BPF, BPAF, and Diphenolic Acid were 0.443, 0.280, 0.277, 0.424, and 0.326 μM respectively. Compared with traditional sensors, the sensor array can simultaneously detect multiple analytes with high throughput, showing great advantage in dealing with complex samples. Combined with machine learning algorithms, five bisphenols can be successfully identified by the obtained array data. The sensor array also demonstrated excellent performance in the detection of both mixed samples and real samples. This high-throughput colorimetric sensor array achieves accurate and sensitive detection of bisphenol substances, providing new means and ideas for enhancing food safety. At the same time, the simple and rapid identification of structurally similar compounds demonstrates its potential for more precise analysis, providing possibilities for future development.

Estimation of S-wave velocity structures of Tainan area, Taiwan, using array records of microtremors

In this study, the shallow S-wave velocity structures beneath the Tainan area, Taiwan are investigated using microtremor array measurements at 18 sites. An F-K spectrum method was used to calculate the dispersion curves for these sites, and surface-wave inversion was used to estimate the S-wave velocity structures beneath the Tainan area. The results indicated that, at frequencies between 0.2 and 1.1 Hz, propagation is concentrated between the northwest and south quadrants, corresponding to the coast of the Taiwan Strait. CHM, a hard central site on the Tainan tableland, was found to have higher phase velocities than the soft sites do, such as site SIM, on the Anping Plain, particularly at frequencies of 0.3–5.0 Hz. Given that the tertiary basement exhibits an S-wave velocity of 1500 m/s, the depth of the Quaternary alluvium in the Tainan area ranges from 400 m at site CHM to 1350 m at site FUP on the Anping Plain. In addition, the depth of the alluvium gradually increases radially from the central CHM site (on the Tainan tableland) to the surrounding areas. These results are consistent with the geolpogy of the Tainan area. Because our shallow S-wave velocity structures are comparable to those proposed in three other studies, our inversion results are concluded to be reasonable and valid. According to the horizontal/vertical (H/V) ratios of our microtremor array data from 18 sites, the predominant frequencies range from 1.0 to 3.8 Hz. Compared with the eastern part (i.e., Dawan lowland), the central part (i.e., Tainan tableland) has higher predominant frequencies.

Prognostic signature detects homologous recombination deficient in glioblastoma.

Glioblastoma (GBM) is a frequent malignant tumor in neurosurgery characterized by a high degree of heterogeneity and genetic instability. DNA double-strand breaks generated by homologous recombination deficiency (HRD) are a well-known contributor to genomic instability, which can encourage tumor development. It is unknown, however, whether the molecular characteristics linked with HRD have a predictive role in GBM. The study aims to assess the extent of genomic instability in GBM using HRD score and investigate the prognostic significance of HRD-related molecular features in GBM. The discovery cohort comprised 567 GBM patients from The Cancer Genome Atlas (TCGA) database. We established HRD scores using the single nucleotide polymorphism (SNP) array data and analyzed transcriptomic data from patients with different HRD scores to identify biomarkers associated with HRD. A prognostic model was built by using HRD-related differentially expressed genes (DEGs) and validated in a distinct cohort from the Chinese Glioma Genome Atlas (CGGA) database. Based on the SNP array data, the gene expression profile data, and the clinical characteristics of GBM patients, we found that patients with a high HRD score had a better prognosis than those with a low HRD score. The DNA damage repair (DDR) signaling pathways were notably enriched in the HRD-positive subgroup. The prognostic model was developed by including HRD-related DEGs that could evaluate the clinical prognosis of patients more efficiently than the HRD score. In addition, patients with a low-risk score had a considerably augmented signature of γδT cells. Finally, through univariate and multivariate Cox regression analyses, it was demonstrated that the prognostic model was superior to other prognostic markers. In conclusion, our research has not only demonstrated that a high HRD score is a valid prognostic biomarker in GBM patients but also built a stable prognosis model [odds ratio (OR) 0.18, 95% confidence interval (CI): 0.11-0.23, P<0.001] that is more accurate than conventional prognostic markers such as O6-methylguanine-DNA methyltransferase (MGMT) methylation (OR 0.55, 95% CI: 0.33-0.91, P=0.02).

Transposable element 5mC methylation state of blood cells predicts age and disease.

Transposable elements (TEs) are DNA sequences that expand selfishly in the genome, possibly causing severe cellular damage. While normally silenced, TEs have been shown to activate during aging. DNA 5-methylcytosine (5mC) is one of the main epigenetic modifications by which TEs are silenced and has been used to train highly accurate age predictors. Yet, one common criticism of such predictors is that they lack interpretability. In this study, we investigate the changes in TE 5mC methylation that occur during aging in human blood using published methylation array data. We find that evolutionarily young long interspersed nuclear elements 1 (L1s), the only known TEs capable of autonomous transposition in humans, undergo the fastest loss of 5mC methylation, suggesting an active mechanism of de-repression. The same young L1s also showed preferential gain in chromatin accessibility but not expression. The long terminal repeat retrotransposons THE1A and THE1C also showed very rapid 5mC loss. We then show that accurate age predictors can be trained on both 5mC methylation of individual TE copies and average methylation of TE families genome wide. Lastly, we show that while old L1s gradually lose 5mC during the entire lifespan, demethylation of young L1s only happens late in life and is associated with cancer.

Lightning and radar measures of mixed phase updraft variability in tracked storms during the TRACER field campaign in Houston, Texas

Abstract Properties of 7488 thunderstorms are summarized for June-September 2022 during the TRACER field campaign Houston, Texas using polarimetric weather radar and VHF 3D lightning mapping array data. Automated tracking of storms linked each instrument’s measurements to a data-defined, time-evolving storm footprint. Within each storm, the depth and magnitude of episodic columns of radar differential reflectivity and specific differential phase quantified the prevalence of updrafts that activated mixed-phase precipitation pathways. Lightning measurements further distinguished the degree of rimed precipitation formation: the fraction of tracks with lightning varied from day to day, and cells with lightning had stronger polarimetric columns. Track-level correlation of lightning flash rate with radar polarimetric measures had substantial spread, showing that lightning provides an additional signal of mixed-phase precipitation processes that can complement future studies of thermodynamic and aerosol controls on cloud microphysics in the Houston region.

CNV-Finder: Streamlining Copy Number Variation Discovery.

Copy Number Variations (CNVs) play pivotal roles in the etiology of complex diseases and are variable across diverse populations. Understanding the association between CNVs and disease susceptibility is of significant importance in disease genetics research and often requires analysis of large sample sizes. One of the most cost-effective and scalable methods for detecting CNVs is based on normalized signal intensity values, such as Log R Ratio (LRR) and B Allele Frequency (BAF), from Illumina genotyping arrays. In this study, we present CNV-Finder, a novel pipeline integrating deep learning techniques on array data, specifically a Long Short-Term Memory (LSTM) network, to expedite the large-scale identification of CNVs within predefined genomic regions. This facilitates the efficient prioritization of samples for subsequent, costly analyses such as short-read and long-read whole genome sequencing. We focus on five genes-Parkin (PRKN), Leucine Rich Repeat And Ig Domain Containing 2 (LINGO2), Microtubule Associated Protein Tau (MAPT), alpha-Synuclein (SNCA), and Amyloid Beta Precursor Protein (APP)-which may be relevant to neurological diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), or related disorders such as essential tremor (ET). By training our models on expert-annotated samples and validating them across diverse cohorts, including those from the Global Parkinson's Genetics Program (GP2) and additional dementia-specific databases, we demonstrate the efficacy of CNV-Finder in accurately detecting deletions and duplications. Our pipeline outputs app-compatible files for visualization within CNV-Finder's interactive web application. This interface enables researchers to review predictions and filter displayed samples by model prediction values, LRR range, and variant count in order to explore or confirm results. Our pipeline integrates this human feedback to enhance model performance and reduce false positive rates. Through a series of comprehensive analyses and validations using both short-read and long-read sequencing data, we demonstrate the robustness and adaptability of CNV-Finder in identifying CNVs with regions of varied sparsity, noise, and size. Our findings highlight the significance of contextual understanding and human expertise in enhancing the precision of CNV identification, particularly in complex genomic regions like 17q21.31. The CNV-Finder pipeline is a scalable, publicly available resource for the scientific community, available on GitHub (https://github.com/GP2code/CNV-Finder; DOI 10.5281/zenodo.14182563). CNV-Finder not only expedites accurate candidate identification but also significantly reduces the manual workload for researchers, enabling future targeted validation and downstream analyses in regions or phenotypes of interest.

Age-Dependent DNA Methylation Variability on the X-Chromosome in Male and Female Twins.

We aimed to explore the age-dependent epigenetic variability on the X-chromosome with consideration of X-chromosome inactivation by applying a sex-stratified regression analysis to DNA methylation array data on X-linked CpGs in aging identical twins. We found 13 X-linked CpGs showing age-related significant increase in variability in males (FDR < 0.05) but none in females. In females, we found a significantly higher proportion of CpGs showing increased variability with age among nominally significant (p < 0.05) CpGs under inactivation, but not among CpGs escaping inactivation. Survival analysis showed a slight trend of correlation by directional change in the variable CpGs with mortality in males. Compared with females, the male X-chromosome can be more vulnerable to epigenetic instability during aging.

B3AM: A beamforming toolbox for three-component ambient seismic noise analysis

We introduce the MATLAB toolbox B3AM for beamforming of three-component ambient noise array data. We explain the theory behind three-component beamforming and polarisation analysis in particular, provide an overview of the workflow, and discuss the output using a worked example. The strength of the presented code package is the analysis of multiple beam response maps from multiple time windows. Hence, it provides statistical information about the ambient noise wavefield recorded over a period of time, such as the ratio of surface to body waves, average dispersion velocities, or dominant propagation direction. It can be used to validate assumptions made about the ambient noise wavefield in a particular location, helping to interpret results from other techniques, such as the analysis of horizontal-to-vertical spectral ratios or ambient noise interferometry, and enabling more precise monitoring of specific wavefield components. While designed initially with seismic networks in mind, B3AM is applicable over a wide range of frequencies and array sizes and can thus be adapted also for laboratory settings or civil engineering applications.

Real-Time Detection, Bearing Estimation, and Whale Species Vocalization Classification From Passive Underwater Acoustic Array Data

Real-Time Detection, Bearing Estimation, and Whale Species Vocalization Classification From Passive Underwater Acoustic Array Data

Meningiomas: Sex-Specific Differences and Prognostic Implications of a Chromosome X Loss.

Meningiomas are the most common primary intracranial tumours in adults. Several studies proposed new stratification systems with a more accurate risk prediction than the WHO grading, e.g. based on methylation and copy number variations (CNVs). Yet, common shortcomings in these analyses are either a lack of stratification by sex of patients or excluding the gonososmes from CNV assessment. Within this study, DNA methylation array data from 7,424 meningioma samples as well as targeted sequencing, clinical annotations and morphology subtyping of 796 samples were examined for differences between females and males regarding mutations, methylation classes, copy number variations and histology. Meningiomas from females accounted for about 53 % of the malignant tumours and present a loss of one X chromosome in 57 % of these malignant cases. In the group of benign tumours, females comprised about 75 % of the patients. Therein, a loss of one X chromosome was detected in only about 10 % of the cases but was associated with a significantly worse progression free survival. Although genomic instability is a common feature of malignant meningiomas, particularly loss of the X chromosome in tumours of female patients in otherwise histologically and molecularly low-risk tumours confers higher risk. Hence, the gonosomal copy number status can be leveraged for increased diagnostic accuracy.

Genome-wide copy number variation association study in anorexia nervosa.

This study represents the first large-scale investigation of rare (<1% population frequency) copy number variants (CNVs) in anorexia nervosa (AN). Large, rare CNVs are reported to be causally associated with anthropometric traits, neurodevelopmental disorders, and schizophrenia, yet their role in the genetic basis of AN is unclear. Using genome-wide association study (GWAS) array data from the Anorexia Nervosa Genetics Initiative (ANGI), which included 7414 AN case and 5044 controls, we investigated the association of 67 well-established syndromic CNVs and 178 pleiotropic disease-risk dosage-sensitive CNVs with AN. To identify novel CNV regions (CNVRs) that increase the risk of AN, we conducted genome-wide association studies with a focus on rare CNV-breakpoints (CNV-GWAS). We found no net enrichment of rare CNVs, either deletions or duplications, in AN, and none of the well-established syndromic or pleiotropic CNVs had a significant association with AN status. However, the CNV-GWAS found 21 nominally associated CNVRs that contribute to AN risk, covering protein-coding genes implicated in synaptic function, metabolic/mitochondrial factors, and lipid characteristics, like the CD36 (7q21.11) gene, which transports long-chain fatty acids into cells. CNVRs intersecting genes previously related to neurodevelopmental traits include deletions of NRXN1 intron 5 (2p16.3), IMMP2L (7q31.1), and PTPRD (9p23). Overall, given that our study is well powered to detect the CNV burden level reported for schizophrenia, we can conclude that rare CNVs have a limited role in the etiology of AN, as reported for bipolar disorder. Our nominal associations for the 21 discovered CNVRs are consistent with AN being a metabo-psychiatric trait, as demonstrated by the common genetic architecture of AN, and we provide association results to allow for replication in future research.

Abstract 4120375: Penetrance and Phenotype Conversion Rate of Genetic Hypertrophic Cardiomyopathy in an Academic Biobank

Introduction: Hypertrophic cardiomyopathy (HCM) is an autosomal dominant condition with incomplete penetrance and variable expressivity. Given the increasing prevalence of sequencing and current guidelines on secondary finding disclosure, HCM P/LP alleles are increasingly being returned to patients who undergo genetic testing for other reasons. Whether individuals carrying P/LP HCM variants discovered in a genome-first context have progressive endophenotypes indicative of HCM remains poorly understood. Methods: To evaluate the penetrance and phenotype conversion rate of adults with P/LP HCM variants, we leveraged the Massachusetts General Brigham Biobank (MGBB), which consists of 36,417 participants with genotyping array and clinical data. Primary images of the earliest and latest TTE studies were reviewed for measurements of the posterior wall (PW), interventricular septum (IVS), and left ventricular morphology. Phenotype-positive (P+) status was defined by a PW or IVS thickness of at least 13 mm. Results: P/LP HCM variants were identified in 42 (0.1%) individuals with mean (SD) age 50.0 (16.6) years and 21 (50%) female sex. The most common HCM variants were in MYBPC3 (44%) and MYH7 (40%), followed by TNNI3(7%), MYL3 (7%), and TNNT2 (2%). Among the 42 genotype-positive (G+) individuals in MGBB, 17 (40%) had pre-existing HCM diagnoses prior to genomic return of results (gRoR). In contrast, 25 (60%) G+ individuals lacked a prior HCM diagnosis, among whom gRoR prompted TTE studies in 13 patients, revealing evidence of HCM in 9 individuals. Among the 42 G+ patients, 25 (58%) patients had completed at least two TTE studies, with a median [IQR] of 6 [3-9] TTE studies per patient, across a span of 10 [7-15] years follow-up. At the time of first TTE, 16 (64%) patients were P+ while 9 (36%) were P-. No G+, P- individuals converted to P+ over 10 years follow-up, nor was there any significant change in IVS or PW thickness. In contrast, individuals who were P+ at the initial TTE exhibited thickening PW (25% increase, CI 97.5% of 6 to 44) and IVS (26% increase, CI 97.5% of 4 to 49) over 8 years follow-up. Conclusion: In a genome-first approach, we identified 42 individuals in the MGBB with a P/LP HCM variant, among whom 60% lacked a prior clinical diagnosis of HCM. Targeted phenotyping revealed that nearly half of this newly identified group were P+. Over a median of 10 years follow-up, we observed a 0% phenotype conversion rate among G+, P- adult carriers of HCM variants.

Sulfur-bearing molecules in a sample of early star-forming cores

The sulfur content in dense molecular regions is highly depleted in comparison to diffuse clouds. The reason for this phenomenon is unclear, and it is therefore necessary to carry out observational studies of sulfur-bearing species toward dense regions, mainly in early evolution stages. In this context, the analysis of sulfur-bearing molecules in a large sample of dense starless molecular cores is of great importance to help us uncover the early sulfur chemistry in these regions. From the Atacama Large Millimeter Array (ALMA) data archive, we selected a project in Band 7 (275--373 GHz), which contains the emission of several sulfur-bearing species. The observations were performed toward a sample of 37 dense cores that are embedded in the most massive infrared-quiet molecular clumps from the ATLASGAL survey. The lines of 34SO, SO$_ $, NS, SO, SO$^ $, and H$_ $CS were analyzed, and the column densities of each molecular species were obtained. Based on the continuum emission and two CH$_ $OH lines, the 37 cores were characterized in density and temperature, and the corresponding H$_ $ column densities were derived. The abundances of these sulfur-bearing species were derived and studied. We find that the abundances of the analyzed sulfur-bearing species increase with increasing gas temperature. Based on the correlation between abundances and temperature, we suggest that the chemistry involved in the formation of each of the analyzed molecules may similarly depend on T$_ k $ in the range 20 to 100 K. Additionally, we find that the comparisons among abundances are highly correlated in general. Taking into account that this correlation decreases in more evolved sources, we suggest that the sulfur-bearing species we analyzed have a similar chemical origin. Our observational results show that the X(SO$_ $)/X(SO) ratio can be used as a chemical clock of molecular cores. Based on the line widths of the molecular lines, we point out that molecules with an oxygen content (34SO, SO$_ $, SO, and SO$^ $) may be associated with warmer and more turbulent gas than the other molecules. H$_ $CS and NS are associated with more quiescent gas, probably in the external envelopes of the cores, which trace similar physical and chemical conditions. We complement recent similar works done toward more evolved sources with a large sample of sources, but also provide quantitative information about abundances that might be useful in chemical models for explaining the sulfur chemistry in the interstellar medium.