A description of externally recorded womb sounds in human subjects during gestation.
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ABSTRACT: Reducing environmental noise benefits premature infants in neonatal intensive care units (NICU), but excessive reduction may lead to sensory deprivation, compromising development. Instead of minimal noise levels, environments that mimic intrauterine soundscapes may facilitate infant development by providing a sound environment reflecting fetal life. This soundscape may support autonomic and emotional development in preterm infants. We aimed to assess the efficacy and feasibility of external non-invasive recordings in pregnant women, endeavoring to capture intra-abdominal or womb sounds during pregnancy with electronic stethoscopes and build a womb sound library to assess sound trends with gestational development. We also compared these sounds to popular commercial womb sounds marketed to new parents.Intra-abdominal sounds from 50 mothers in their second and third trimester (13 to 40 weeks) of pregnancy were recorded for 6 minutes in a quiet clinic room with 4 electronic stethoscopes, placed in the right upper and lower quadrants, and left upper and lower quadrants of the abdomen. These recording were partitioned into 2-minute intervals in three different positions: standing, sitting and lying supine. Maternal and gestational age, Body Mass Index (BMI) and time since last meal were collected during recordings. Recordings were analyzed using long-term average spectral and waveform analysis, and compared to sounds from non-pregnant abdomens and commercially-marketed womb sounds selected for their availability, popularity, and claims they mimic the intrauterine environment.Maternal sounds shared certain common characteristics, but varied with gestational age. With fetal development, the maternal abdomen filtered high (500-5,000 Hz) and mid-frequency (100-500 Hz) energy bands, but no change appeared in contributions from low-frequency signals (10-100 Hz) with gestational age. Variation appeared between mothers, suggesting a resonant chamber role for intra-abdominal space. Compared to commercially-marketed sounds, womb signals were dominated by bowel sounds, were of lower frequency, and showed more variation in intensity.High-fidelity intra-abdominal or womb sounds during pregnancy can be recorded non-invasively. Recordings vary with gestational age, and show a predominance of low frequency noise and bowel sounds which are distinct from popular commercial products. Such recordings may be utilized to determine whether sounds influence preterm infant development in the NICU.
Project description:BackgroundLittle is known of the language healthcare professionals use to describe cough sounds. We aimed to examine how they describe cough sounds and to assess whether these descriptions suggested they appreciate the basic sound qualities (as assessed by acoustic analysis) and the underlying diagnosis of the patient coughing.Methods53 health professionals from two large respiratory tertiary referral centres were recruited; 22 doctors and 31 staff from professions allied to medicine. Participants listened to 9 sequences of spontaneous cough sounds from common respiratory diseases. For each cough they selected patient gender, the most appropriate descriptors and a diagnosis. Cluster analysis was performed to assess which cough sounds attracted similar descriptions.ResultsGender was correctly identified in 93% of cases. The presence or absence of mucus was correct in 76.1% and wheeze in 39.3% of cases. However, identifying clinical diagnosis from cough was poor at 34.0%. Cluster analysis showed coughs with the same acoustics properties rather than the same diagnoses attracted the same descriptions.ConclusionThese results suggest that healthcare professionals can recognise some of the qualities of cough sounds but are poor at making diagnoses from them. It remains to be seen whether in the future cough sound acoustics will provide useful clinical information and whether their study will lead to the development of useful new outcome measures in cough monitoring.
Project description:The idea that healthy uterine cavity is sterile is challenged nowadays. It is still debatable whether the bacteria present in the uterine cavity during pregnancy are residents or invaders. To reveal microbiome composition and its characteristics in the womb of pregnant women, 41 decidual tissue samples and 64 amniotic fluid samples were taken from pregnant Chinese women. DNA extraction was followed by pyrosequencing of the hypervariable V4 region of the 16S rDNA gene to characterize womb microbiome. Both types of samples had low diversity microbiome with Enterobacteriaceae being the dominant phylotypes at family level. To characterize the nature of colonization during pregnancy, the presence of endogenous biomass was confirmed by cultivation. Surprisingly, all of the 50 amniotic fluid samples studied were culture-negative, whereas 379 out of 1,832 placenta samples were culture-positive. Our results suggested that womb contained microbiome with low diversity. Culture-based investigation of amniotic fluid and placenta samples confirmed the presence of cultivable microorganisms in the placenta but not in amniotic fluid. Thus it suggests that bacterial colonization does occur during healthy pregnancy.
Project description:ImportanceBreathing sounds during sleep are an important characteristic feature of obstructive sleep apnea (OSA) and have been regarded as a potential biomarker. Breathing sounds during sleep can be easily recorded using a microphone, which is found in most smartphone devices. Therefore, it may be easy to implement an evaluation tool for prescreening purposes.ObjectiveTo evaluate OSA prediction models using smartphone-recorded sounds and identify optimal settings with regard to noise processing and sound feature selection.Design, setting, and participantsA cross-sectional study was performed among patients who visited the sleep center of Seoul National University Bundang Hospital for snoring or sleep apnea from August 2015 to August 2019. Audio recordings during sleep were performed using a smartphone during routine, full-night, in-laboratory polysomnography. Using a random forest algorithm, binary classifications were separately conducted for 3 different threshold criteria according to an apnea hypopnea index (AHI) threshold of 5, 15, or 30 events/h. Four regression models were created according to noise reduction and feature selection from the input sound to predict actual AHI: (1) noise reduction without feature selection, (2) noise reduction with feature selection, (3) neither noise reduction nor feature selection, and (4) feature selection without noise reduction. Clinical and polysomnographic parameters that may have been associated with errors were assessed. Data were analyzed from September 2019 to September 2020.Main outcomes and measuresAccuracy of OSA prediction models.ResultsA total of 423 patients (mean [SD] age, 48.1 [12.8] years; 356 [84.1%] male) were analyzed. Data were split into training (n = 256 [60.5%]) and test data sets (n = 167 [39.5%]). Accuracies were 88.2%, 82.3%, and 81.7%, and the areas under curve were 0.90, 0.89, and 0.90 for an AHI threshold of 5, 15, and 30 events/h, respectively. In the regression analysis, using recorded sounds that had not been denoised and had only selected attributes resulted in the highest correlation coefficient (r = 0.78; 95% CI, 0.69-0.88). The AHI (β = 0.33; 95% CI, 0.24-0.42) and sleep efficiency (β = -0.20; 95% CI, -0.35 to -0.05) were found to be associated with estimation error.Conclusions and relevanceIn this cross-sectional study, recorded sleep breathing sounds using a smartphone were used to create reasonably accurate OSA prediction models. Future research should focus on real-life recordings using various smartphone devices.
Project description:PurposeDiagnosis of obstructive sleep apnea by the gold-standard of polysomnography (PSG), or by home sleep testing (HST), requires numerous physical connections to the patient which may restrict use of these tools for early screening. We hypothesized that normal and disturbed breathing may be detected by a consumer smartphone without physical connections to the patient using novel algorithms to analyze ambient sound.MethodsWe studied 91 patients undergoing clinically indicated PSG. Phase I: In a derivation cohort (n = 32), we placed an unmodified Samsung Galaxy S5 without external microphone near the bed to record ambient sounds. We analyzed 12,352 discrete breath/non-breath sounds (386/patient), from which we developed algorithms to remove noise, and detect breaths as envelopes of spectral peaks. Phase II: In a distinct validation cohort (n = 59), we tested the ability of acoustic algorithms to detect AHI < 15 vs AHI > 15 on PSG.ResultsSmartphone-recorded sound analyses detected the presence, absence, and types of breath sound. Phase I: In the derivation cohort, spectral analysis identified breaths and apneas with a c-statistic of 0.91, and loud obstruction sounds with c-statistic of 0.95 on receiver operating characteristic analyses, relative to adjudicated events. Phase II: In the validation cohort, automated acoustic analysis provided a c-statistic of 0.87 compared to whole-night PSG.ConclusionsAmbient sounds recorded from a smartphone during sleep can identify apnea and abnormal breathing verified on PSG. Future studies should determine if this approach may facilitate early screening of SDB to identify at-risk patients for definitive diagnosis and therapy.Clinical trialsNCT03288376; clinicaltrials.org.
Project description:The basic helix-loop-helix transcription factor, NEUROG3, is critical in causing endocrine commitment from a progenitor cell population in the developing pancreas. In human, NEUROG3 has been detected from 8 weeks post-conception (wpc). However, the profile of its production and when it ceases to be detected is unknown. In this study we have defined the profile of NEUROG3 detection in the developing pancreas to give insight into when NEUROG3-dependent endocrine commitment is possible in the human fetus. Immunohistochemistry allowed counting of cells with positively stained nuclei from 7 wpc through to term. mRNA was also isolated from sections of human fetal pancreas and NEUROG3 transcription analyzed by quantitative reverse transcription and polymerase chain reaction. NEUROG3 was detected as expected at 8 wpc. The number of NEUROG3-positive cells increased to peak levels between 10 wpc and 14 wpc. It declined at and after 18 wpc such that it was not detected in human fetal pancreas at 35-41 wpc. Analysis of NEUROG3 transcription corroborated this profile by demonstrating very low levels of transcript at 35-41 wpc, more than 10-fold lower than levels at 12-16 wpc. These data define the appearance, peak and subsequent disappearance of the critical transcription factor, NEUROG3, in human fetal pancreas for the first time. By inference, the window for pancreatic endocrine differentiation via NEUROG3 action opens at 8 wpc and closes between 21 and 35 wpc.
Project description:The advancement of stethoscope technology has enabled high quality recording of patient sounds. We used an electronic stethoscope to record lung sounds from healthy and unhealthy subjects. The dataset includes sounds from seven ailments (i.e., asthma, heart failure, pneumonia, bronchitis, pleural effusion, lung fibrosis, and chronic obstructive pulmonary disease (COPD)) as well as normal breathing sounds. The dataset presented in this article contains the audio recordings from the examination of the chest wall at various vantage points. The stethoscope placement on the subject was determined by the specialist physician performing the diagnosis. Each recording was replicated three times corresponding to various frequency filters that emphasize certain bodily sounds. The dataset can be used for the development of automated methods that detect pulmonary diseases from lung sounds or identify the correct type of lung sound. The same methods can also be applied to the study of heart sounds.
Project description:Radar systems allow for contactless measurements of vital signs such as heart sounds, the pulse signal, and respiration. This approach is able to tackle crucial disadvantages of state-of-the-art monitoring devices such as the need for permanent wiring and skin contact. Potential applications include the employment in a hospital environment but also in home care or passenger vehicles. This dataset consists of synchronised data which are acquired using a Six-Port-based radar system operating at 24?GHz, a digital stethoscope, an ECG, and a respiration sensor. 11 test subjects were measured in different defined scenarios and at several measurement positions such as at the carotid, the back, and several frontal positions on the thorax. Overall, around 223?minutes of data were acquired at scenarios such as breath-holding, post-exercise measurements, and while speaking. The presented dataset contains reference-labeled ECG signals and can therefore easily be used to either test algorithms for monitoring the heart rate, but also to gain insights about characteristic effects of radar-based vital sign monitoring.
Project description:As metagenomic approaches for detecting infectious agents have improved, each tissue that was once thought to be sterile has been found to harbor a variety of microorganisms. Controversy still exists over the status of amniotic fluid, which is part of an immunologically privileged zone that is required to prevent maternal immune system rejection of the fetus. Due to this privilege, the exclusion of microbes has been proposed to be mandatory, leading to the sterile womb hypothesis. Since nucleic acid yields from amniotic fluid are very low, contaminating nucleic acid found in water, reagents and the laboratory environment frequently confound attempts to address this hypothesis. Here we present metagenomic criteria for microorganism detection and a metagenomic method able to be performed with small volumes of starting material, while controlling for exogenous contamination, to circumvent these and other pitfalls. We use this method to show that human mid-gestational amniotic fluid has no detectable virome or microbiome, supporting the sterile womb hypothesis.
Project description:We performed RNA sequencing on 40,000 cells to create a high-resolution single-cell gene expression atlas of developing human cortex, providing the first single-cell characterization of previously uncharacterized cell types, including human subplate neurons, comparisons with bulk tissue, and systematic analyses of technical factors. These data permit deconvolution of regulatory networks connecting regulatory elements and transcriptional drivers to single-cell gene expression programs, significantly extending our understanding of human neurogenesis, cortical evolution, and the cellular basis of neuropsychiatric disease. We tie cell-cycle progression with early cell fate decisions during neurogenesis, demonstrating that differentiation occurs on a transcriptomic continuum; rather than only expressing a few transcription factors that drive cell fates, differentiating cells express broad, mixed cell-type transcriptomes before telophase. By mapping neuropsychiatric disease genes to cell types, we implicate dysregulation of specific cell types in ASD, ID, and epilepsy. We developed CoDEx, an online portal to facilitate data access and browsing.
Project description:BackgroundNoninvasive measurement of placental blood flow is the major technical challenge for predicting ischemic placenta (IPD). Pseudocontinuous arterial spin labeling (pCASL) MRI was recently shown to be promising, but the potential value in predicting the subsequence development of IPD is not known.PurposeTo derive global and regional placental blood flow parameters from longitudinal measurements of pCASL MRI and to assess the associations between perfusion-related parameters and IPD.Study typeProspective.PopulationEighty-four women completed two pCASL MRI scans (first; 14-18 weeks and second; 19-24 weeks) from prospectively recruited 118 subjects. A total of 69 subjects were included for the analysis, of which 15 subjects developed IPD.Field strength/sequence3T/T2 -weighted half-Fourier single-shot turbo spin-echo (HASTE) and pCASL.AssessmentFour perfusion-related parameters in the placenta were derived: placenta volume, placental blood flow (PBF), high PBF (hPBF), and relative hPBF. The longitudinal changes of the parameters and their association with IPD were tested after being normalizing to the 16th and 20th weeks of gestation.Statistical testsComparisons between two gestational ages within subjects were performed using the paired Wilcoxon tests, and comparisons between normal and IPD groups were performed using the unpaired Wilcoxon tests.ResultsThe difference between the first and second MRI scans was statistically significant for volume (156.6 cm3 vs. 269.7 cm3 , P < 0.001) and PBF (104.9 ml/100g/min vs. 111.3 ml/100g/min, P = 0.02) for normal subjects, indicating an increase in pregnancy with advancing gestation. Of the parameters tested, the difference between the normal and IPD subjects was most pronounced in hPBF (278.1 ml/100g/min vs. 180.7 ml/100g/min, P < 0.001) and relative hPBF (259.1% vs. 183.2%, P < 0.001) at 16 weeks.Data conclusionThe high perfusion-related image parameters for IPD were significantly decreased from normal pregnancy at 14-18 weeks of gestation.Level of evidence2 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;51:1247-1257.