Investigating brain-gut microbiota dynamics and inflammatory processes in an autistic-like rat model using MRI biomarkers during childhood and adolescence.

Autism spectrum disorder (ASD) is characterized by social interaction deficits and repetitive behaviors. Recent research has linked that gut dysbiosis may contribute to ASD-like behaviors. However, the exact developmental time point at which gut microbiota alterations affect brain function and behavior in patients with ASD remains unclear. We hypothesized that ASD-related brain microstructural changes and gut dysbiosis induce metabolic dysregulation and proinflammatory responses, which collectively contribute to the social behavioral deficits observed in early childhood. We used an autistic-like rat model that was generated via prenatal valproic acid exposure. We analyzed brain microstructural changes using diffusion tensor imaging (DTI) and examined microbiota, blood, and fecal samples for inflammation biomarkers. The ASD model rats exhibited significant brain microstructural changes in the anterior cingulate cortex, hippocampus, striatum, and thalamus; reduced microbiota diversity (Prevotellaceae and Peptostreptococcaceae); and altered metabolic signatures. The shift in microbiota diversity and density observed at postnatal day (PND) 35, which is a critical developmental period, underscored the importance of early ASD interventions. We identified a unique metabolic signature in the ASD model, with elevated formate and reduced acetate and butyrate levels, indicating a dysregulation in short-chain fatty acid (SCFA) metabolism. Furthermore, increased astrocytic and microglial activation and elevated proinflammatory cytokines-interleukin-1 beta (IL-1ß), interleukin-6 (IL-6), interferon-gamma (IFN-γ), and tumor necrosis factor-alpha (TNF-α)-were observed, indicating immune dysregulation. This study provided insights into the complex interplay between the brain and the gut, and indicated DTI metrics as potential imaging-based biomarkers in ASD, thus emphasizing the need for early childhood interventions.

Utilizing diffusion tensor imaging as an image biomarker in exploring the therapeutic efficacy of forniceal deep brain stimulation in a mice model of Alzheimer's disease.

Objective.With prolonged life expectancy, the incidence of memory deficits, especially in Alzheimer's disease (AD), has increased. Although multiple treatments have been evaluated, no promising treatment has been found to date. Deep brain stimulation (DBS) of the fornix area was explored as a possible treatment because the fornix is intimately connected to memory-related areas that are vulnerable in AD; however, a proper imaging biomarker for assessing the therapeutic efficiency of forniceal DBS in AD has not been established.Approach.This study assessed the efficacy and safety of DBS by estimating the optimal intersection volume between the volume of tissue activated and the fornix. Utilizing a gold-electroplating process, the microelectrode's surface area on the neural probe was increased, enhancing charge transfer performance within potential water window limits. Bilateral fornix implantation was conducted in triple-transgenic AD mice (3 × Tg-AD) and wild-type mice (strain: B6129SF1/J), with forniceal DBS administered exclusively to 3 × Tg-AD mice in the DBS-on group. Behavioral tasks, diffusion tensor imaging (DTI), and immunohistochemistry (IHC) were performed in all mice to assess the therapeutic efficacy of forniceal DBS.Main results.The results illustrated that memory deficits and increased anxiety-like behavior in 3 × Tg-AD mice were rescued by forniceal DBS. Furthermore, forniceal DBS positively altered DTI indices, such as increasing fractional anisotropy (FA) and decreasing mean diffusivity (MD), together with reducing microglial cell and astrocyte counts, suggesting a potential causal relationship between revised FA/MD and reduced cell counts in the anterior cingulate cortex, hippocampus, fornix, amygdala, and entorhinal cortex of 3 × Tg-AD mice following forniceal DBS.Significance.The efficacy of forniceal DBS in AD can be indicated by alterations in DTI-based biomarkers reflecting the decreased activation of glial cells, suggesting reduced neural inflammation as evidenced by improvements in memory and anxiety-like behavior.

Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.

BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction. NEW METHOD: This study introduces a 3D convolutional neural network (3D-CNN) model to decode finger movements using ECoG data. The model employs adaptive, explainable AI (xAI) techniques to interpret the physiological relevance of brain signals. ECoG signals from epilepsy patients during awake craniotomy were processed to extract power spectral density across multiple frequency bands. These data formed a 3D matrix used to train the 3D-CNN to predict finger trajectories. RESULTS: The 3D-CNN model showed significant accuracy in predicting finger movements, with root-mean-square error (RMSE) values of 0.26-0.38 for single finger movements and 0.20-0.24 for combined movements. Explainable AI techniques, Grad-CAM and SHAP, identified the high gamma (HG) band as crucial for movement prediction, showing specific cortical regions involved in different finger movements. These findings highlighted the physiological significance of the HG band in motor control. COMPARISON WITH EXISTING METHODS: The 3D-CNN model outperformed traditional machine learning approaches by effectively capturing spatial and temporal patterns in ECoG data. The use of xAI techniques provided clearer insights into the model's decision-making process, unlike the "black box" nature of standard deep learning models. CONCLUSIONS: The proposed 3D-CNN model, combined with xAI methods, enhances the decoding accuracy of finger movements from ECoG data. This approach offers a more efficient and interpretable solution for brain-computer interface (BCI) applications, emphasizing the HG band's role in motor control.

Cigarette smoke-induced dysbiosis: comparative analysis of lung and intestinal microbiomes in COPD mice and patients.

BACKGROUND: The impact of cigarette smoke (CS) on lung diseases and the role of microbiome dysbiosis in chronic obstructive pulmonary disease (COPD) have been previously reported; however, the relationships remain unclear. METHODS: Our research examined the effects of 20-week cigarette smoke (CS) exposure on the lung and intestinal microbiomes in C57BL/6JNarl mice, alongside a comparison with COPD patients' intestinal microbiome data from a public dataset. RESULTS: The study found that CS exposure significantly decreased forced vital capacity (FVC), thickened airway walls, and induced emphysema. Increased lung damage was observed along with higher lung keratinocyte chemoattractant (KC) levels by CS exposure. Lung microbiome analysis revealed a rise in Actinobacteriota, while intestinal microbiome showed significant diversity changes, indicating dysbiosis. Principal coordinate analysis highlighted distinct intestinal microbiome compositions between control and CS-exposed groups. In the intestinal microbiome, notable decreases in Patescibacteria, Campilobacterota, Defferibacterota, Actinobacteriota, and Desulfobacterota were observed. We also identified correlations between lung function and dysbiosis in both lung and intestinal microbiomes. Lung interleukins, interferon-É£, KC, and 8-isoprostane levels were linked to lung microbiome dysbiosis. Notably, dysbiosis patterns in CS-exposed mice were similar to those in COPD patients, particularly of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 4 patients. This suggests a systemic impact of CS exposure. CONCLUSION: In summary, CS exposure induces significant dysbiosis in lung and intestinal microbiomes, correlating with lung function decline and injury. These results align with changes in COPD patients, underscoring the important role of microbiome in smoke-related lung diseases.

Impact of miscarriage and termination of pregnancy on subsequent pregnancies: A longitudinal study of maternal and paternal depression, anxiety and eudaimonia.

BACKGROUND: Although miscarriage and termination of pregnancy affect maternal mental illnesses on subsequent pregnancies, their effects on the positive mental health (e.g., eudaimonia) of both first-time and multi-time parents have received minimal attention, especially for fathers. This longitudinal study examines the effects of experiences of miscarriage and termination on parental well-being in subsequent pregnancies from prenatal to postpartum years, while simultaneously considering parity. METHODS: Pregnant women and their partners were recruited during early prenatal visits in Taiwan from 2011 to 2022 and were followed up from mid-pregnancy to 1 year postpartum. Six waves of self-reported assessments were employed. RESULTS: Of 1813 women, 11.3 % and 14.7 % had experiences of miscarriage and termination, respectively. Compared with the group without experiences of miscarriage or termination, experiences of miscarriage were associated with increased risks of paternal depression (adjusted odds ratio = 1.6, 95 % confidence interval [CI] = 1.13-2.27), higher levels of anxiety (adjusted ß = 1.83, 95 % CI = 0.21-3.46), and lower eudaimonia scores (adjusted ß = -1.09, 95 % CI = -1.99 to -0.19) from the prenatal to postpartum years, particularly among multiparous individuals. Additionally, experiences of termination were associated with increased risks of depression in their partner. LIMITATIONS: The experiences of miscarriage and TOP were self-reported and limited in acquiring more detailed information through questioning. CONCLUSIONS: These findings highlight the decreased well-being of men whose partners have undergone termination of pregnancy or experienced miscarriage, and stress the importance of interventions aimed at preventing adverse consequences among these individuals.

Amelioration of the brain structural connectivity is accompanied with changes of gut microbiota in a tuberous sclerosis complex mouse model.

Tuberous sclerosis complex (TSC) is a genetic disease that causes benign tumors and dysfunctions in many organs, including the brain. Aside from the brain malformations, many individuals with TSC exhibit neuropsychiatric symptoms. Among these symptoms, autism spectrum disorder (ASD) is one of the most common co-morbidities, affecting up to 60% of the population. Past neuroimaging studies strongly suggested that the impairments in brain connectivity contribute to ASD, whether or not TSC-related. Specifically, the tract-based diffusion tensor imaging (DTI) analysis provides information on the fiber integrity and has been used to study the neuropathological changes in the white matter of TSC patients with ASD symptoms. In our previous study, curcumin, a diet-derived mTOR inhibitor has been shown to effectively mitigate learning and memory deficits and anxiety-like behavior in Tsc2+/- mice via inhibiting astroglial proliferation. Recently, gut microbiota, which is greatly influenced by the diet, has been considered to play an important role in regulating several components of the central nervous system, including glial functions. In this study, we showed that the abnormal social behavior in the Tsc2+/- mice can be ameliorated by the dietary curcumin treatment. Second, using tract-based DTI analysis, we found that the Tsc2+/- mice exhibited altered fractional anisotropy, axial and radial diffusivities of axonal bundles connecting the prefrontal cortex, nucleus accumbens, hypothalamus, and amygdala, indicating a decreased brain network. Third, the dietary curcumin treatment improved the DTI metrics, in accordance with changes in the gut microbiota composition. At the bacterial phylum level, we showed that the abundances of Actinobacteria, Verrucomicrobia, and Tenericutes were significantly correlated with the DTI metrics FA, AD, and RD, respectively. Finally, we revealed that the expression of myelin-associated proteins, myelin bassic protein (MBP) and proteolipid protein (PLP) was increased after the treatment. Overall, we showed a strong correlation between structural connectivity alterations and social behavioral deficits, as well as the diet-dependent changes in gut microbiota composition.

Assessment of sources and health risks of heavy metals in metropolitan household dust among preschool children: The LEAPP-HIT study.

The most common construction material used in Taiwan is concrete, potentially contaminated by geologic heavy metals (HMs). Younger children spend much time indoors, increasing HM exposure risks from household dust owing to their behaviors. We evaluated arsenic (As), cadmium (Cd), and lead (Pb) concentrations in fingernails among 280 preschoolers between 2017 and 2023. We also analyzed HM concentrations, including As, Cd, Pb, chromium (Cr), nickel (Ni), copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn), in 90 household dust and 50 road dust samples from a residential area where children lived between 2019 and 2021 to deepen the understanding of sources and health risks of exposure to HMs from household dust. The average As, Cd, and Pb concentrations in fingernails were 0.12 ± 0.06, 0.05 ± 0.05, and 0.95 ± 0.77 µg/g, respectively. Soil parent materials, indoor construction activities, vehicle emissions, and mixed indoor combustion were the pollution sources of HMs in household dust. Higher Cr and Pb levels in household dust may pose non-carcinogenic risks to preschoolers. Addressing indoor construction and soil parent materials sources is vital for children's health. The finding of the present survey can be used for indoor environmental management to reduce the risks of HM exposure and avoid potential adverse health effects for younger children.

Associations Between Brain-Gut Axis and Psychological Distress in Fibromyalgia: A Microbiota and Magnetic Resonance Imaging Study.

An altered brain-gut axis is suspected to be one of the pathomechanisms in fibromyalgia (FM). This cross-sectional study investigated the associations among altered microbiota, psychological distress, and brain functional connectivity (FC) in FM. We recruited 25 FM patients and 25 healthy people in the present study. Psychological distress was measured using standardized questionnaires. Microbiota analysis was performed on the participants' stools. Functional magnetic resonance imaging data were acquired, and seed-based resting-state FC (rs-FC) analysis was conducted with the salience network nodes as seeds. Linear regression and mediation analyses evaluated microbiota, symptoms, and rs-FCs associations. We found altered microbiota diversity in FM, of which Phascolarctobacterium and Lachnoclostridium taxa increased the most and Faecalibacterium taxon decreased the most compared to controls. The Phascolarctobacterium abundance significantly predicted Beck depression inventory (BDI-II) scores in FM (ß = 6.83; P = .033). Rs-FCs from salience network nodes were reduced in FM, of which rs-FCs from the right lateral rostral prefrontal cortex (RPFC) to the lateral occipital cortex, superior division right (RPFC-sLOC) could be predicted by BDI-II scores in patients (ß = -.0064; P = .0054). In addition, the BDI-II score was a mediator in the association between Phascolarctobacterium abundance and rs-FCs of RPFC-sLOC (ab = -.06; 95% CI: -.16 to -9.10-3). In conclusion, microbial dysbiosis might be associated with altered neural networks mediated by psychological distress in FM, emphasizing the critical role of the brain-gut axis in FM's non-pain symptoms and supporting further analysis of mechanism-targeted therapies to reduce FM symptoms. PERSPECTIVE: Our study suggests microbial dysbiosis might be associated with psychological distress and the altered salience network, supporting the role of brain-gut axis dysfunction in fibromyalgia pathomechanisms. Further targeting therapies for microbial dysbiosis should be investigated to manage fibromyalgia patients in the future.

Associations between parental and postnatal metal mixture exposure and developmental delays in a Taiwanese longitudinal birth cohort of preschool children.

Studies have evaluated the impact of environmental exposure to neurotoxic metals on developmental delays (DDs). However, comprehensive understanding regarding the associations between parental and postnatal exposure to metal mixtures and the occurrence of DDs in offspring is limited. In this study, we assessed the relationships between parental and postnatal exposure to three metals (arsenic [As], cadmium [Cd], and lead [Pb], levels of which were measured in toenails) and suspected DDs (SDDs) in preschool children within a Taiwanese longitudinal birth cohort. In total between 2017 and 2021, 154 pairs of parents and their children under the age of 6 years were recruited, and 462 toenail samples and 154 completed questionnaires were collected. Metal concentrations in toenails were quantified using inductively coupled plasma-mass spectrometry after acid digestion of the toenails. We applied multivariable logistic regression and Bayesian kernel machine regression to evaluate the overall effect and to identify key components of the metal mixture that were associated with the SDD risk. Higher concentrations of As, Cd, and Pb were found in the toenails of the parents of children with SDDs compared with the toenails of the parents of children without SDDs. Our examination of the combined effects of exposure to the metal mixture revealed that As concentration in the father's toenail and Cd concentration in the mother's toenail were positively correlated with the risk of SDDs in their offspring. Notably, the effect of exposure to the metal mixture on the risk of SDDs was stronger in boys than in girls. Our findings suggest that parents taking measures to minimize their exposure to metals might enhance their children's developmental outcomes.

Nucleus accumbens deep brain stimulation improves depressive-like behaviors through BDNF-mediated alterations in brain functional connectivity of dopaminergic pathway.

Major depressive disorder (MDD), a common psychiatric condition, adversely affects patients' moods and quality of life. Despite the development of various treatments, many patients with MDD remain vulnerable and inadequately controlled. Since anhedonia is a feature of depression and there is evidence of leading to metabolic disorder, deep brain stimulation (DBS) to the nucleus accumbens (NAc) might be promising in modulating the dopaminergic pathway. To determine whether NAc-DBS alters glucose metabolism via mitochondrial alteration and neurogenesis and whether these changes increase neural plasticity that improves behavioral functions in a chronic social defeat stress (CSDS) mouse model. The Lab-designed MR-compatible neural probes were implanted in the bilateral NAc of C57BL/6 mice with and without CSDS, followed by DBS or sham stimulation. All animals underwent open-field and sucrose preference testing, and brain resting-state functional MRI analysis. Meanwhile, we checked the placement of neural probes in each mouse by T2 images. By confirming the placement location, mice with incorrect probe placement (the negative control group) showed no significant therapeutic effects in behavioral performance and functional connectivity (FC) after receiving electrical stimulation and were excluded from further analysis. Western blotting, seahorse metabolic analysis, and electron microscopy were further applied for the investigation of NAc-DBS. We found NAc-DBS restored emotional deficits in CSDS-subjected mice. Concurrent with behavioral amelioration, the CSDS DBS-on group exhibited enhanced FC in the dopaminergic pathway with increased expression of BDNF- and NeuN-positive cells increased dopamine D1 receptor, dopamine D2 receptors, and TH in the medial prefrontal cortex, NAc, ventral hippocampus, ventral tegmental area, and amygdala. Increased pAMPK/total AMPK and PGC-1α levels, functions of oxidative phosphorylation, and mitochondrial biogenesis were also observed after NAc-DBS treatment. Our findings demonstrate that NAc-DBS can promote BDNF expression, which alters FC and metabolic profile in the dopaminergic pathway, suggesting a potential strategy for ameliorating emotional processes in individuals with MDD.

Assessing traffic-related air pollution-induced fiber-specific white matter degradation associated with motor performance declines in aged rats.

Fine particulate matter (PM2.5) is thought to exacerbate Parkinson's disease (PD) in the elderly, and early detection of PD progression may prevent further irreversible damage. Therefore, we used diffusion tensor imaging (DTI) for probing microstructural changes after late-life chronic traffic-related PM2.5 exposure. Herein, 1.5-year-old Fischer 344 rats were exposed to clean air (control), high-efficiency particulate air (HEPA)-filtered ambient air (HEPA group), and ambient traffic-related PM2.5 (PM2.5 group, 9.933 ± 1.021 µg/m3) for 3 months. Rotarod test, DTI tractographic analysis, and immunohistochemistry were performed in the end of study period. Aged rats exposed to PM2.5 exhibited motor impairment with decreased fractional anisotropy and tyrosine hydroxylase expression in olfactory and nigrostriatal circuits, indicating disrupted white matter integrity and dopaminergic (DA) neuronal loss. Additionally, increased radial diffusivity and lower expression of myelin basic protein in PM2.5 group suggested ageing progression of demyelination exacerbated by PM2.5 exposure. Significant production of tumor necrosis factor-α was also observed after PM2.5 exposure, revealing potential inflammation of injury to multiple fiber tracts of DA pathways. Microstructural changes demonstrated potential links between PM2.5-induced inflammatory white matter demyelination and behavioral performance, with indication of pre-manifestation of DTI-based biomarkers for early detection of PD progression in the elderly.

Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task.

Complete reaching movements involve target sensing, motor planning, and arm movement execution, and this process requires the integration and communication of various brain regions. Previously, reaching movements have been decoded successfully from the motor cortex (M1) and applied to prosthetic control. However, most studies attempted to decode neural activities from a single brain region, resulting in reduced decoding accuracy during visually guided reaching motions. To enhance the decoding accuracy of visually guided forelimb reaching movements, we propose a parallel computing neural network using both M1 and medial agranular cortex (AGm) neural activities of rats to predict forelimb-reaching movements. The proposed network decodes M1 neural activities into the primary components of the forelimb movement and decodes AGm neural activities into internal feedforward information to calibrate the forelimb movement in a goal-reaching movement. We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration. We also show that the M1 and AGm neural activities contribute to controlling forelimb movement during goal-reaching movements, and we report an increase in the power of the local field potential (LFP) in beta and gamma bands over AGm in response to a change in the target distance, which may involve sensorimotor transformation and communication between the visual cortex and AGm when preparing for an upcoming reaching movement. The proposed parallel computing neural network with the internal feedback model improves prediction accuracy for goal-reaching movements.

Effects of indoor air quality and home environmental characteristics on allergic diseases among preschool children in the Greater Taipei Area.

Indoor air quality and home environmental characteristics are potential factors associated with the onset and exacerbation of allergic diseases. Our study examined the effects of these factors on allergic diseases (i.e., asthma, allergic rhinitis, allergic conjunctivitis, and atopic dermatitis) among preschool children. We recruited a total of 120 preschool children from an ongoing birth cohort study in the Greater Taipei Area. A comprehensive environmental evaluation was conducted at each participant's residence and included measurements of indoor and outdoor air pollutants, fungal spores, endotoxins, and house dust mite allergens. A structured questionnaire was used to collect information on the allergic diseases and home environments of participants. Land-use characteristics and points of interest in the surrounding area of each home were analyzed. Other covariates were obtained from the cohort data. Multiple logistic regressions were used to examine the relationships between allergic diseases and covariates. We observed that all mean indoor air pollutant levels were below Taiwan's indoor air quality standards. After adjustment for covariates, the total number of fungal spores and the ozone, Der f 1, and endotoxin levels were significantly associated with increased risks of allergic diseases. Biological contaminants more significantly affected allergic diseases than other pollutants. Moreover, home environmental characteristics (e.g., living near power facilities and gas stations) were associated with an increased risk of allergic diseases. Regular and proper home sanitation is recommended to prevent the accumulation of indoor pollutants, especially biological contaminants. Living away from potential sources of pollution is also crucial for protecting the health of children.

Effects of mobile device use on emotional and behavioral problems in the CBCL among preschoolers: Do shared reading and maternal depression matter?

INTRODUCTION: Although mobile devices are used ubiquitously, studies on their detrimental effects on preschoolers are limited. Furthermore, no study has considered shared reading and mobile device usage simultaneously. Therefore, this study examined the effects of mobile devices and shared reading on preschoolers' development along with the effects of maternal depression on this association. MATERIALS AND METHODS: Mothers of 202 children aged 2-5 years were recruited in Taiwan. Maternal self-reported questionnaires on mobile device usage, shared reading, and child's emotional and behavioral development were collected. Multiple linear regression models were used for analyses. RESULTS: Mothers' higher usage time on mobile devices and an education level of college or less were significantly associated with the child's exceeding recommended use of mobile devices. Particularly among depressed mothers, preschoolers' exceeding recommended use of mobile devices was associated with more sleep (ß = 9.87, 95% confidence interval [CI] = 1.34, 18.40) and attention (ß = 7.20, 95% CI = 1.50, 12.91) problems, whereas shared reading was associated with less somatic complaints (ß = -16.19, 95% CI = -32.22, -0.15) and withdrawn (ß = -21.50, 95% CI = -40.52, -2.47), compared with their respective counterparts. CONCLUSION: Our study suggested the beneficial effects of shared reading. Moreover, we highlighted the adverse effects of preschoolers' exceeding recommended use of mobile device on sleep and attention problems, especially for children of mothers with depression.

Data on lung and intestinal microbiome after air pollution exposure in ageing rats.

Air pollution has been linked to respiratory diseases, and urban air pollution can be attributed to a number of emission sources. The emitted particles and gases are the primary components of air pollution that enter the lungs during respiration. Particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5) can deposit deep into the respiratory tract via inhalation and has been proposed as a causative agent for adverse respiratory health. In addition, the lung contains a diverse microbial community (microbiome) that maintains normal homeostasis and is significantly altered in a variety of pulmonary disorders. Air pollution, specifically PM2.5, has previously been shown to significantly alter the composition of the lower airway microbiome, which has been linked to decreased lung function in chronic obstructive pulmonary disease (COPD) patients. Surprisingly, the intestinal microbiome has also been implicated in the modulation of pulmonary inflammatory diseases. Therefore, dysbiosis of the lung and intestinal microbiomes pose significant negative effects on human health. This dataset describes the microbial community profiles of the lungs and intestines of ageing rats exposed to ambient unconcentrated traffic-related air pollution for three months. The whole-body exposure system was equipped with and without high efficiency particulate air (HEPA) filtration (gaseous vs. PM2.5 pollution). The data can provide valuable information on lung and intestinal microbiome changes, including that which was only found after traffic-related air pollution exposure.

Adverse effects of inadequate sleep duration patterns during pregnancy on toddlers suspected developmental delay: A longitudinal study.

BACKGROUND: Although studies have reported the effects of inadequate sleep on maternal health, few have examined the relationships of maternal sleep patterns with fetal health and early childhood development. This study investigated maternal sleep duration patterns from early pregnancy to 3-years postpartum and their effects on birth outcomes and child development. METHODS: This study recruited pregnant women and their partners during prenatal visits at five selected hospitals in the Taipei area; follow-up lasted from July 2011 to April 2021. A total of 1178 parents completed self-reported assessments from early pregnancy until childbirth and 544 completed eight assessments up to 3-years postpartum. Generalized estimated equation models were used for analyses. RESULTS: Group-based trajectory modeling was used to identify four trajectories of sleep duration patterns. Although maternal sleep duration was not associated with birth outcomes, maternal "short decreasing" and "stably short" sleep patterns were associated with a higher risk of suspected overall developmental delay and language developmental delay, respectively. Furthermore, an "extremely long decreasing" pattern was associated with a higher risk of suspected overall developmental delay, [adjusted odds ratio (aOR) = 2.97, 95% confidence interval (CI):1.39-6.36)], gross motor delay, (aOR = 3.14, 95% CI: 1.42-6.99) and language developmental delay (aOR = 4.59, 95% CI:1.62-13.00). The results were significant for the children of multiparous women. CONCLUSIONS: We identified a U-shaped distribution of risk between offspring developmental delay and maternal prenatal sleep duration, with the highest risk levels on both ends of the maternal prenatal sleep duration pattern. Interventions for maternal sleep are relatively straightforward to implement and should thus be a key part of standard prenatal care.

Upper-Arm Photoplethysmographic Sensor with One-Time Calibration for Long-Term Blood Pressure Monitoring.

Wearable cuffless photoplethysmographic blood pressure monitors have garnered widespread attention in recent years; however, the long-term performance values of these devices are questionable. Most cuffless blood pressure monitors require initial baseline calibration and regular recalibrations with a cuffed blood pressure monitor to ensure accurate blood pressure estimation, and their estimation accuracy may vary over time if left uncalibrated. Therefore, this study assessed the accuracy and long-term performance of an upper-arm, cuffless photoplethysmographic blood pressure monitor according to the ISO 81060-2 standard. This device was based on a nonlinear machine-learning model architecture with a fine-tuning optimized method. The blood pressure measurement protocol followed a validation procedure according to the standard, with an additional four weekly blood pressure measurements over a 1-month period, to assess the long-term performance values of the upper-arm, cuffless photoplethysmographic blood pressure monitor. The results showed that the photoplethysmographic signals obtained from the upper arm had better qualities when compared with those measured from the wrist. When compared with the cuffed blood pressure monitor, the means ± standard deviations of the difference in BP at week 1 (baseline) were -1.36 ± 7.24 and -2.11 ± 5.71 mmHg for systolic and diastolic blood pressure, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg and met the second criterion of a systolic blood pressure ≤ 6.89 mmHg and a diastolic blood pressure ≤ 6.84 mmHg. The differences in the uncalibrated blood pressure values between the test and reference blood pressure monitors measured from week 2 to week 5 remained stable and met both criteria 1 and 2 of the ISO 81060-2 standard. The upper-arm, cuffless photoplethysmographic blood pressure monitor in this study generated high-quality photoplethysmographic signals with satisfactory accuracy at both initial calibration and 1-month follow-ups. This device could be a convenient and practical tool to continuously measure blood pressure over long periods of time.

Experimental Verification for Numerical Simulation of Thalamic Stimulation-Evoked Calcium-Sensitive Fluorescence and Electrophysiology with Self-Assembled Multifunctional Optrode.

Owing to its capacity to eliminate a long-standing methodological limitation, fiber photometry can assist research gaining novel insight into neural systems. Fiber photometry can reveal artifact-free neural activity under deep brain stimulation (DBS). Although evoking neural potential with DBS is an effective method for mediating neural activity and neural function, the relationship between DBS-evoked neural Ca2+ change and DBS-evoked neural electrophysiology remains unknown. Therefore, in this study, a self-assembled optrode was demonstrated as a DBS stimulator and an optical biosensor capable of concurrently recording Ca2+ fluorescence and electrophysiological signals. Before the in vivo experiment, the volume of tissue activated (VTA) was estimated, and the simulated Ca2+ signals were presented using Monte Carlo (MC) simulation to approach the realistic in vivo environment. When VTA and the simulated Ca2+ signals were combined, the distribution of simulated Ca2+ fluorescence signals matched the VTA region. In addition, the in vivo experiment revealed a correlation between the local field potential (LFP) and the Ca2+ fluorescence signal in the evoked region, revealing the relationship between electrophysiology and the performance of neural Ca2+ concentration behavior. Concurrent with the VTA volume, simulated Ca2+ intensity, and the in vivo experiment, these data suggested that the behavior of neural electrophysiology was consistent with the phenomenon of Ca2+ influx to neurons.

Proof of Concept for Sustainable Manufacturing of Neural Electrode Array for In Vivo Recording.

Increasing requirements for neural implantation are helping to expand our understanding of nervous systems and generate new developmental approaches. It is thanks to advanced semiconductor technologies that we can achieve the high-density complementary metal-oxide-semiconductor electrode array for the improvement of the quantity and quality of neural recordings. Although the microfabricated neural implantable device holds much promise in the biosensing field, there are some significant technological challenges. The most advanced neural implantable device relies on complex semiconductor manufacturing processes, which are required for the use of expensive masks and specific clean room facilities. In addition, these processes based on a conventional photolithography technique are suitable for mass production, which is not applicable for custom-made manufacturing in response to individual experimental requirements. The microfabricated complexity of the implantable neural device is increasing, as is the associated energy consumption, and corresponding emissions of carbon dioxide and other greenhouse gases, resulting in environmental deterioration. Herein, we developed a fabless fabricated process for a neural electrode array that was simple, fast, sustainable, and customizable. An effective strategy to produce conductive patterns as the redistribution layers (RDLs) includes implementing microelectrodes, traces, and bonding pads onto the polyimide (PI) substrate by laser micromachining techniques combined with the drop coating of the silver glue to stack the laser grooving lines. The process of electroplating platinum on the RDLs was performed to increase corresponding conductivity. Sequentially, Parylene C was deposited onto the PI substrate to form the insulation layer for the protection of inner RDLs. Following the deposition of Parylene C, the via holes over microelectrodes and the corresponding probe shape of the neural electrode array was also etched by laser micromachining. To increase the neural recording capability, three-dimensional microelectrodes with a high surface area were formed by electroplating gold. Our eco-electrode array showed reliable electrical characteristics of impedance under harsh cyclic bending conditions of over 90 degrees. For in vivo application, our flexible neural electrode array demonstrated more stable and higher neural recording quality and better biocompatibility as well during the 2-week implantation compared with those of the silicon-based neural electrode array. In this study, our proposed eco-manufacturing process for fabricating the neural electrode array reduced 63 times of carbon emissions compared to the traditional semiconductor manufacturing process and provided freedom in the customized design of the implantable electronic devices as well.