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This article discusses a case report of a neonate with severe left heart failure after neonatal myocardial infarction. The patient underwent various treatments, including thrombolysis, inotropic therapy, and prostaglandin E1, to stabilize their condition. A hybrid treatment involving stenting of the arterial duct and bilateral pulmonary banding was performed as a bridge to recovery or transplantation. Eventually, the patient received a successful heart transplant after a waiting time of ten months. The case highlights the importance of adjusting therapeutic strategies to maintain sufficient cardiac output and the need to avoid extracorporeal circulation in neonatal heart failure to reduce morbidity and mortality. [Extracted from the article]

Microgrids (MGs) have become a reliable power source for supplying energy to rural areas in a secure, consistent, and low-carbon emission manner. Power quality disturbance (PQD) is a common issue that reduces the MGs networks' reliability and restricts its usage on a small scale. The performance, reliability and lifetime of the various power devices can be affected due to the problem of PQD in the network. Researchers have proposed numerous PQD monitoring techniques based on artificial intelligence. However, they are limited to low margins and accuracy. So, this paper suggests a novel hyperparameter-tuned or optimized deep learning model with an attention-based feature learning mechanism for PQD prediction. The critical stages of the proposed work, such as data collection, feature extraction, and PQD prediction, are as follows. The PQD signals are first produced using the IEEE 1159 standard. Following that, the original time-domain features are directly recovered from the dataset, and the frequency-domain features using discrete wavelet transform (DWT). The extracted features were fed into visual geometry group 16 with multi-head attention and optimal hyperparameter-based bidirectional long short-term memory (V16MHA-OHBM) to perform spatial and temporal feature extraction. These extracted features are concatenated and given to the fully connected layer to forecast the PQD. The results showed that the suggested approach surpasses the prior state-of-the-art algorithms when trained and tested using 16 different types of synthetic noise PQD data produced using mathematical models in line with IEEE 1159. [ABSTRACT FROM AUTHOR]

Air pollution is one of the major concerns considering detriments to human health. This type of pollution leads to several health problems for humans, such as asthma, heart issues, skin diseases, bronchitis, lung cancer, and throat and eye infections. Air pollution also poses serious issues to the planet. Pollution from the vehicle industry is the cause of greenhouse effect and CO2 emissions. Thus, real-time monitoring of air pollution in these areas will help local authorities to analyze the current situation of the city and take necessary actions. The monitoring process has become efficient and dynamic with the advancement of the Internet of things and wireless sensor networks. Localization is the main issue in WSNs; if the sensor node location is unknown, then coverage and power and routing are not optimal. This study concentrates on localization-based air pollution prediction systems for real-time monitoring of smart cities. These systems comprise two phases considering the prediction as heavy or light traffic area using the Gaussian support vector machine algorithm based on the air pollutants, such as PM2.5 particulate matter, PM10, nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and sulfur dioxide (SO2). The sensor nodes are localized on the basis of the predicted area using the meta-heuristic algorithms called fast correlation-based elephant herding optimization. The dataset is divided into training and testing parts based on 10 cross-validations. The evaluation on predicting the air pollutant for localization is performed with the training dataset. Mean error prediction in localizing nodes is 9.83 which is lesser than existing solutions and accuracy is 95%. [ABSTRACT FROM AUTHOR]

Objective: To examine the relationship between perioperative brain injury and neurodevelopment during early childhood in patients with severe congenital heart disease (CHD)., Study Design: One hundred and seventy children with CHD and born at term who required cardiopulmonary bypass surgery in the first 6 weeks after birth were recruited from 3 European centers and underwent preoperative and postoperative brain MRIs. Uniform description of imaging findings was performed and an overall brain injury score was created, based on the sum of the worst preoperative or postoperative brain injury subscores. Motor and cognitive outcomes were assessed with the Bayley Scales of Infant and Toddler Development Third Edition at 12 to 30 months of age. The relationship between brain injury score and clinical outcome was assessed using multiple linear regression analysis, adjusting for CHD severity, length of hospital stay (LOS), socioeconomic status (SES), and age at follow-up., Results: Neither the overall brain injury score nor any of the brain injury subscores correlated with motor or cognitive outcome. The number of preoperative white matter lesions was significantly associated with gross motor outcome after correction for multiple testing (P = .013, β = -0.50). SES was independently associated with cognitive outcome (P < .001, β = 0.26), and LOS with motor outcome (P < .001, β = -0.35)., Conclusion: Preoperative white matter lesions appear to be the most predictive MRI marker for adverse early childhood gross motor outcome in this large European cohort of infants with severe CHD. LOS as a marker of disease severity, and SES influence outcome and future intervention trials need to address these risk factors., Competing Interests: Declaration of Competing Interest Financial relationships/disclosures/grants: This research was funded by a Consolidator Grant of the European Society of Paediatric Research (ESPR). WKZ: This research was funded by the Hartekind Foundation and Vrienden van het Wilhelmina Kinderziekenhuis Foundation. CRUCIAL-TRIAL by ZonMw. KCL: This research was funded by the Medical Research Council UK (MR/L011530/1 and MR/V002465/1), the British Heart Foundation (FS/15/55/31649), and Action Medical Research (GN2630) and was supported by the Wellcome Engineering and Physical Sciences Research Council Centre for Medical Engineering at Kings College London (WT 203148/Z/16/Z). UCZ: This research was funded by the Mäxi-Foundation Switzerland, the Anna Müller Grocholski Foundation Switzerland and the EMDO Foundation Switzerland. The sponsors were not involved in the study design, the collection, analysis, and interpretation of data, the writing of the report; and the decision to submit the paper for publication., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: Children with univentricular congenital heart disease undergoing staged surgical palliation are at risk for impaired neurodevelopmental (ND) outcome. Little is known about the long-term effects on brain growth until school age., Methods: In a prospective two-centre study, consecutive patients undergoing stage I (Hybrid or Norwood) to stage III (Fontan procedure) were evaluated by 2 serial cerebral magnetic resonance imaging examinations, somatic growth and ND testing before Fontan procedure at 2 years of age (Bayley-III) and after Fontan at 6-8 years of age (Wechsler Intelligence Scale for Children-third edition). Magnetic resonance imaging findings were compared with 8 healthy controls. Medical and sociodemographic characteristics were documented and related to cerebral and ND findings., Results: We examined 33 children (16 female) at a mean age of 2.3 (0.35) and 6.8 (± 0.7) years. The mean Bayley-III cognitive scales were 99.1 (9.9), language scales 98.4 (11.9) and motor scales 98.5 (13.8) at the first examination. Follow-up at school age showed a mean total IQ of 86.7 (13.6). The rate of structural brain lesions increased from 39% at 2 years to 58% at school age. Bayley-III language scale (P = 0.021) and mean Wechsler Intelligence Scale for Children-third edition (P = 0.019) were lower in children with pathological MR findings. Total brain volume (P < 0.001), total grey matter volume (P = 0.002), deep grey matter volume (P = 0.001) and white matter volume (P < 0.001) were smaller in patients compared to age- and gender-matched healthy controls., Conclusions: Smaller brain volumes and structural brain lesions in complex congenital heart defect patients at school age are associated with impaired ND outcome. For the evaluation of predictive surgical or clinical factors, larger multicentre studies are needed., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.)

Background: Brain injury and neurodevelopmental impairment remain a concern in children with complex congenital heart disease (CHD). A practice guideline on neuromonitoring, neuroimaging, and neurodevelopmental follow-up in CHD patients undergoing cardiopulmonary bypass surgery is lacking. The aim of this survey was to systematically evaluate the current practice in centers across Europe., Methods: An online-based structured survey was sent to pediatric cardiac surgical centers across Europe between April 2019 and June 2020. Results were summarized by descriptive statistics., Results: Valid responses were received by 25 European centers, of which 23 completed the questionnaire to the last page. Near-infrared spectroscopy was the most commonly used neuromonitoring modality used in 64, 80, and 72% preoperatively, intraoperatively, and postoperatively, respectively. Neuroimaging was most commonly performed by means of cranial ultrasound in 96 and 84% preoperatively and postoperatively, respectively. Magnetic resonance imaging was obtained in 72 and 44% preoperatively and postoperatively, respectively, but was predominantly reserved for clinically symptomatic patients (preoperatively 67%, postoperatively 64%). Neurodevelopmental follow-up was implemented in 40% of centers and planned in 24%., Conclusions: Heterogeneity in perioperative neuromonitoring and neuroimaging practice in CHD in centers across Europe is large. The need for neurodevelopmental follow-up has been recognized. A clear practice guideline is urgently needed., Impact: There is large heterogeneity in neuromonitoring, neuroimaging, and neurodevelopmental follow-up practices among European centers caring for neonates with complex congenital heart disease. This study provides a systematic evaluation of the current neuromonitoring, neuroimaging, and neurodevelopmental follow-up practice in Europe. The results of this survey may serve as the basis for developing a clear practice guideline that could help to early detect and prevent neurological and neurodevelopmental sequelae in neonates with complex congenital heart disease., (© 2022. The Author(s).)

Background: Infants with congenital heart disease are at risk of brain injury and impaired neurodevelopment. The aim was to investigate risk factors for perioperative brain lesions in infants with congenital heart disease., Methods: Infants with transposition of the great arteries, single ventricle physiology, and left ventricular outflow tract and/or aortic arch obstruction undergoing cardiac surgery <6 weeks after birth from 3 European cohorts (Utrecht, Zurich, and London) were combined. Brain lesions were scored on preoperative (transposition of the great arteries N=104; single ventricle physiology N=35; and left ventricular outflow tract and/or aortic arch obstruction N=41) and postoperative (transposition of the great arteries N=88; single ventricle physiology N=28; and left ventricular outflow tract and/or aortic arch obstruction N=30) magnetic resonance imaging for risk factor analysis of arterial ischemic stroke, cerebral sinus venous thrombosis, and white matter injury., Results: Preoperatively, induced vaginal delivery (odds ratio [OR], 2.23 [95% CI, 1.06-4.70]) was associated with white matter injury and balloon atrial septostomy increased the risk of white matter injury (OR, 2.51 [95% CI, 1.23-5.20]) and arterial ischemic stroke (OR, 4.49 [95% CI, 1.20-21.49]). Postoperatively, younger postnatal age at surgery (OR, 1.18 [95% CI, 1.05-1.33]) and selective cerebral perfusion, particularly at ≤20 °C (OR, 13.46 [95% CI, 3.58-67.10]), were associated with new arterial ischemic stroke. Single ventricle physiology was associated with new white matter injury (OR, 2.88 [95% CI, 1.20-6.95]) and transposition of the great arteries with new cerebral sinus venous thrombosis (OR, 13.47 [95% CI, 2.28-95.66]). Delayed sternal closure (OR, 3.47 [95% CI, 1.08-13.06]) and lower intraoperative temperatures (OR, 1.22 [95% CI, 1.07-1.36]) also increased the risk of new cerebral sinus venous thrombosis., Conclusions: Delivery planning and surgery timing may be modifiable risk factors that allow personalized treatment to minimize the risk of perioperative brain injury in severe congenital heart disease. Further research is needed to optimize cerebral perfusion techniques for neonatal surgery and to confirm the relationship between cerebral sinus venous thrombosis and perioperative risk factors.