Human milk is optimal for infant nutrition. However, many mothers cease breastfeeding because of low milk supply (LMS). It is difficult to identify mothers at risk for LMS because its biologic ...underpinnings are not fully understood. Previously, we demonstrated that milk micro-ribonucleic acids (miRNAs) may be related to LMS. Transforming growth factor beta (TGFbeta) also plays an important role in mammary involution and may contribute to LMS. We performed a longitudinal cohort study of 139 breastfeeding mothers to test the hypothesis that milk levels of TGFbeta would identify mothers with LMS. We explored whether TGFbeta impacts the expression of LMS-related miRNAs in cultured human mammary epithelial cells (HMECs). LMS was defined by maternal report of inadequate milk production, and confirmed by age of formula introduction and infant weight trajectory. Levels of TGF-beta1 and TGF-beta2 were measured one month after delivery. There was a significant relationship between levels of TGF-beta1 and LMS (X.sup.2 = 8.92, p = 0.003) on logistic regression analysis, while controlling for lactation stage (X.sup.2 = 1.28, p = 0.25), maternal pre-pregnancy body mass index (X.sup.2 = 0.038, p = 0.84), and previous breastfeeding experience (X.sup.2 = 7.43, p = 0.006). The model accounted for 16.8% of variance in the data (p = 0.005) and correctly predicted LMS for 84.6% of mothers (22/26; AUC = 0.72). Interactions between TGF-beta1 and miR-22-3p displayed significant effect on LMS status (Z = 2.67, p = 0.008). Further, incubation of HMECs with TGF-beta1 significantly reduced mammary cell number (t = -4.23, p = 0.003) and increased levels of miR-22-3p (t = 3.861, p = 0.008). Interactions between TGF-beta1 and miR-22-3p may impact mammary function and milk levels of TGF-beta1 could have clinical utility for identifying mothers with LMS. Such information could be used to provide early, targeted lactation support.
Some children and young people (CYP) with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) experience persistent symptoms, commonly called “long COVID.” It remains unclear whether ...symptoms of SARS-CoV-2 persist longer than those of other respiratory viruses, particularly in young children. This cross-sectional study involved 372 CYP (0-15 years) tested for SARS-CoV-2. Character and duration of symptoms (cough, runny nose, sore throat, rash, diarrhea, vomiting, sore muscles, fatigue, fever, loss of smell) were compared between CYP with a positive test (n = 100) and those with a negative test (n = 272), while controlling for medical/demographic covariates. The average duration of symptoms for CYP with a positive SARS-CoV-2 test (8.5 ± 10 days) did not differ from that of CYP with a negative test (7.2 ± 5 days, P = .71, d = 0.046). A positive SARS-CoV-2 test did not increase the risk (36/372, 10%) of symptoms persisting for ≥3 weeks (odds ratio = 0.96, 95% confidence interval = 0.45-2.0). These results suggest CYP with non-SARS-CoV-2 infections experience a similar duration of symptoms as peers with SARS-CoV-2 infection.
There is growing public concern surrounding traumatic brain injury (TBI). TBI can cause significant morbidity, and the long-term sequelae are poorly understood. TBI diagnosis and management rely on ...patient-reported symptoms and subjective clinical assessment. There are no biologic tools to detect mild TBI or to track brain recovery. Emerging evidence suggests that microRNAs (miRNAs) may provide information about the injured brain. These tiny epigenetic molecules are expressed throughout the body. However, they are particularly important in neurons, can cross the blood-brain barrier, and are securely transported from cell to cell, where they regulate gene expression. miRNA levels may identify patients with TBI and predict symptom duration. This review synthesizes miRNA findings from 14 human studies. We distill more than 291 miRNAs to 17 biomarker candidates that overlap across multiple studies and multiple biofluids. The goal of this review is to establish a collective understanding of miRNA biology in TBI and identify clinical priorities for future investigations of this promising biomarker.
The microbiome plays a vital role in human health and disease. Interaction between human hosts and the microbiome occurs through a number of mechanisms, including transcriptomic regulation by ...microRNA (miRNA). In animal models, circadian variations in miRNA and microbiome elements have been described, but patterns of co-expression and potential diurnal interaction in humans have not. We investigated daily oscillations in salivary miRNA and microbial RNA to explore relationships between these components of the gut-brain-axis and their implications in human health. Nine subjects provided 120 saliva samples at designated times, on repeated days. Samples were divided into three sets for exploration and cross-validation. Identification and quantification of host miRNA and microbial RNA was performed using next generation sequencing. Three stages of statistical analyses were used to identify circadian oscillators: 1) a two-way analysis of variance in the first two sample sets identified host miRNAs and microbial RNAs whose abundance varied with collection time (but not day); 2) multivariate modeling identified subsets of these miRNAs and microbial RNAs strongly-associated with collection time, and evaluated their predictive ability in an independent hold-out sample set; 3) regulation of circadian miRNAs and microbial RNAs was explored in data from autistic children with disordered sleep (n = 77), relative to autistic peers with typical sleep (n = 63). Eleven miRNAs and 11 microbial RNAs demonstrated consistent diurnal oscillation across sample sets and accurately predicted collection time in the hold-out set. Associations among five circadian miRNAs and four circadian microbial RNAs were observed. We termed the 11 miRNAs CircaMiRs. These CircaMiRs had 1,127 predicted gene targets, with enrichment for both circadian gene targets and metabolic signaling processes. Four CircaMiRs had "altered" expression patterns among children with disordered sleep. Thus, novel and correlated circadian oscillations in human miRNA and microbial RNA exist and may have distinct implications in human health and disease.
Traumatic brain injury (TBI) is a major cause of death and disability worldwide, with mild TBI (mTBI) accounting for 85% of cases. mTBI is also implicated in serious long-term sequelae including ...second impact syndrome and chronic traumatic encephalopathy. mTBI often goes undiagnosed due to delayed symptom onset and limited sensitivity of conventional assessment measures compared with severe TBI. Current efforts seek to identify accurate and reliable non-invasive biomarkers associated with functional measures relevant to long-term outcomes. Here we evaluated the utility of serum and salivary microRNAs (miRNAs) to serve as sensitive and specific peripheral biomarkers of possible mTBI. Our primary objectives were to establish the relationship between peripheral measures of miRNA, objective quantification of head impacts, and sensitive indices of balance and cognitive function in healthy young adult athletes. A secondary objective was to compare the sensitivity of miRNA versus commonly used blood-based protein biomarkers. 50 amateur mixed martial arts (MMA) fighters participated. 216 saliva and serum samples were collected at multiple time points, both pre- and post-fight. Levels of 10 serum proteins were compared in a subset of the fighters (n = 24). Levels of miRNAs were obtained by next generation sequencing. Functional outcomes were evaluated using a computerized assessment system that measured cognitive performance, body sway, and combined cognitive performance and body sway during dual task completion. Data were analyzed using multivariate logistic regression for predictive classification, analysis of variance, correlation analysis and principal component analysis. We identified a subset of salivary and serum miRNAs that showed robust utility at predicting TBI likelihood and demonstrated quantitative associations with head impacts as well as cognitive and balance measures. In contrast, serum proteins demonstrated far less utility. We also found that the timing of the responses varies in saliva and serum, which is a critical observation for biomarker studies to consider.
Analyzing medical data to find abnormalities is a time-consuming and costly task, particularly for rare abnormalities, requiring tremendous efforts from medical experts. Therefore, artificial ...intelligence has become a popular tool for the automatic processing of medical data, acting as a supportive tool for doctors. However, the machine learning models used to build these tools are highly dependent on the data used to train them. Large amounts of data can be difficult to obtain in medicine due to privacy reasons, expensive and time-consuming annotations, and a general lack of data samples for infrequent lesions. In this study, we present a novel synthetic data generation pipeline, called SinGAN-Seg, to produce synthetic medical images with corresponding masks using a single training image. Our method is different from the traditional generative adversarial networks (GANs) because our model needs only a single image and the corresponding ground truth to train. We also show that the synthetic data generation pipeline can be used to produce alternative artificial segmentation datasets with corresponding ground truth masks when real datasets are not allowed to share. The pipeline is evaluated using qualitative and quantitative comparisons between real data and synthetic data to show that the style transfer technique used in our pipeline significantly improves the quality of the generated data and our method is better than other state-of-the-art GANs to prepare synthetic images when the size of training datasets are limited. By training UNet++ using both real data and the synthetic data generated from the SinGAN-Seg pipeline, we show that the models trained on synthetic data have very close performances to those trained on real data when both datasets have a considerable amount of training data. In contrast, we show that synthetic data generated from the SinGAN-Seg pipeline improves the performance of segmentation models when training datasets do not have a considerable amount of data. All experiments were performed using an open dataset and the code is publicly available on GitHub.
Prompt recognition of neurodevelopmental delay is critical for optimizing developmental trajectories. Currently, this is achieved with caregiver questionnaires whose sensitivity and specificity can ...be limited by socioeconomic and cultural factors. This prospective study of 121 term infants tested the hypothesis that microRNA measurement could aid early recognition of infants at risk for neurodevelopmental delay. Levels of four salivary microRNAs implicated in childhood autism (miR-125a-5p, miR-148a-5p, miR-151a-3p, miR-28-3p) were measured at 6 months of age, and compared between infants who displayed risk for neurodevelopmental delay at 18 months (
= 20) and peers with typical development (
= 101), based on clinical evaluation aided by the Survey of Wellbeing in Young Children (SWYC). Accuracy of microRNAs for predicting neurodevelopmental concerns at 18 months was compared to the clinical standard (9-month SWYC). Infants with neurodevelopmental concerns at 18 months displayed higher levels of miR-125a-5p (d = 0.30,
= 0.018, adj
= 0.049), miR-151a-3p (d = 0.30,
= 0.017, adj
= 0.048), and miR-28-3p (d = 0.31,
= 0.014, adj
= 0.048). Levels of miR-151a-3p were associated with an 18-month SWYC score (R = -0.19,
= 0.021) and probability of neurodevelopmental delay at 18 months (OR = 1.91, 95% CI, 1.14-3.19). Salivary levels of miR-151a-3p enhanced predictive accuracy for future neurodevelopmental delay (
= 0.010, X
= 6.71, AUC = 0.71) compared to the 9-month SWYC score alone (OR = 0.56, 95% CI, 0.20-1.58, AUC = 0.567). This pilot study provides evidence that miR-151a-3p may aid the identification of infants at risk for neurodevelopmental delay. External validation of these findings is necessary.
Objective: To assess discrepancies between child and parent symptom reports following concussion.
Methods: Prospective cohort study involving 61 patients, age 7-21 years, diagnosed with a concussion ...within the previous 14 days. Children/parents completed the Child SCAT-3 symptom inventory at enrollment and 4 weeks post-injury. A within-subjects t-test was used to compare differences in child/parent response for each of 20 individual symptoms, 4 symptom domains, and total symptom severity. Pearson correlations were used to measure agreement between child/parent responses. A repeated measures analysis of variance assessed the effect of time on child/parent symptom discrepancy.
Results: At enrollment, children reported higher symptom severity for 'distracted easily' (adj. p = .015) and 'confused' (adj. p = .015). There was moderate-to-high (r > 0.3) agreement between children and parents for more individual symptoms at enrollment (18/20) than at 4 weeks post-injury (14/20). Age had no effect (p > .05) on the discrepancy between child/parent reports.
Conclusions: Although there was moderate-to-strong agreement between child/parent reports of concussion symptoms, discrepancies in individual cognitive symptom reports exist, in both children and adolescents. Therefore, collection of parent scales may provide useful information when tracking cognitive symptoms in adolescent patients, who may under-report or under-recognize cognitive deficits.
Human milk is thought to reduce infant atopy risk. The biologic mechanism for this protective effect is not fully understood.
We tested the hypothesis that infant consumption of 4 microRNAs ...(miR-146b-5p, miR-148b-3p, miR-21–5p, and miR-375–3p) in human milk would be associated with reduced atopy risk.
The Breast Milk Influence of the Microtranscriptome Profile on Atopy in Children over Time (IMPACT) study involved a cohort of mother-infant dyads who planned to breastfeed beyond 4 mo. Infant consumption of the 4 human milk microRNAs (miRNAs) in the first 6 mo was calculated as the product of milk miRNA concentration and the number of human milk feeds, across 3 lactation stages: early milk (0–4 wk), transitional milk (4–16 wk), and mature milk (16–24 wk). The primary outcome was infant atopy in the first year, defined as atopic dermatitis (AD), food allergies, or wheezing. The final analysis included 432 human milk samples and 7824 wk of longitudinal health data from 163 dyads.
Seventy-three infants developed atopy. Forty-one were diagnosed with AD (25%), 33 developed food allergy (20%), and 10 had wheezing (6%). Eleven developed >1 condition (7%). Infants who did not develop atopy consumed higher concentrations of miR-375–3p (d = 0.18, P = 0.022, adj P = 0.044) and miR-148b-3p (d = 0.23, P = 0.007, adj P = 0.028). The consumption of miR-375–3p (X2 = 5.7, P = 0.017, OR: 0.92, 95% CI: 0.86, 0.99) was associated with reduced atopy risk. Concentrations of miR-375–3p increased throughout lactation (r = 0.46, F = 132.3, P = 8.4 × 10−34) and were inversely associated with maternal body mass (r = –0.11, t = –2.1, P = 0.032).
This study provides evidence that infant consumption of miR-375–3p may reduce atopy risk.
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