Case Report: Cerebral Revascularization in a Child With Mucopolysaccharidosis Type I

Mucopolysaccharidosis (MPS) type I is a rare lysosomal storage disorder caused by an accumulation of glycosaminoglycans (GAGs) resulting in multisystem disease. Neurological morbidity includes hydrocephalus, spinal cord compression, and cognitive decline. While many neurological symptoms have been described, stroke is not a widely-recognized manifestation of MPS I. Accordingly, patients with MPS I are not routinely evaluated for stroke, and there are no guidelines for managing stroke in patients with this disease. We report the case of a child diagnosed with MPS I who presented with overt stroke and repeated neurological symptoms with imaging findings for severe ventriculomegaly, infarction, and bilateral terminal carotid artery stenosis. Direct intracranial pressure evaluation proved negative for hydrocephalus. The patient was subsequently treated with cerebral revascularization and at a 3-year follow-up, the patient reported no further neurological events or new ischemia on cerebral imaging. Cerebral arteriopathy in patients with MPS I may be associated with GAG accumulation within the cerebrovascular system and may predispose patients to recurrent strokes. However, further studies are required to elucidate the etiology of cerebrovascular arteriopathy in the setting of MPS I. Although the natural history of steno-occlusive arteriopathy in patients with MPS I remains unclear, our findings suggest that cerebral revascularization is a safe treatment option that may mitigate the risk of future strokes and should be strongly considered within the overall management guidelines for patients with MPS I

Machine Learning Techniques in Indoor Environmental Quality Assessment

This chapter provides a comprehensive exploration of the evolving role of machine learning in Indoor Environmental Quality (IEQ) assessment. As urban living spaces become increasingly enclosed, the importance of maintaining optimal IEQ for human health and well-being has surged. Traditional methods for IEQ assessment, while effective, often fail to provide real-time monitoring and control. This gap is increasingly being addressed by the integration of machine learning techniques, allowing for enhanced predictive modeling, real-time optimization, and robust anomaly detection. The chapter delves into a comparative analysis of various machine learning techniques including supervised, unsupervised, and reinforcement learning, demonstrating their unique benefits in IEQ assessment. Practical implementations of these techniques in residential, commercial, and specialized environments are further illustrated through detailed case studies. The chapter also addresses the existing challenges in implementing machine learning for IEQ assessment and provides an outlook on future trends and potential research directions. The comprehensive review offered in this chapter encourages continued innovation and research in leveraging machine learning. for more efficient and effective IEQ assessment

Machine Learning-Based Approach to Wind Turbine Wake Prediction under Yawed Conditions

As wind energy continues to be a crucial part of sustainable power generation, the need for precise and efficient modeling of wind turbines, especially under yawed conditions, becomes increasingly significant. Addressing this, the current study introduces a machine learning-based symbolic regression approach for elucidating wake dynamics. Utilizing WindSE’s actuator line method (ALM) and Large Eddy Simulation (LES), we model an NREL 5-MW wind turbine under yaw conditions ranging from no yaw to 40 degrees. Leveraging a hold-out validation strategy, the model achieves robust hyper-parameter optimization, resulting in high predictive accuracy. While the model demonstrates remarkable precision in predicting wake deflection and velocity deficit at both the wake center and hub height, it shows a slight deviation at low downstream distances, which is less critical to our focus on large wind farm design. Nonetheless, our approach sets the stage for advancements in academic research and practical applications in the wind energy sector by providing an accurate and computationally efficient tool for wind farm optimization. This study establishes a new standard, filling a significant gap in the literature on the application of machine learning-based wake models for wind turbine yaw wake prediction

Predicting symptomatic cerebral vasospasm after aneurysmal subarachnoid hemorrhage with an artificial neural network in a pediatric population

PURPOSE: Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomatic cerebral vasospasm (SCV) in adults presenting after aneurysmal subarachnoid hemorrhage (aSAH). Although SCV is unusual in children with aSAH, the clinical consequences are severe. Consequently, reliable tools to predict patients at greatest risk for SCV may have significant value. We applied ANN modeling to a consecutive cohort of pediatric aSAH cases to assess its ability to predict SCV. METHODS: A retrospective chart review was conducted to identify patients \u3c 21 years of age who presented with spontaneously ruptured, non-traumatic, non-mycotic, non-flow-related intracranial arterial aneurysms to our institution between January 2002 and January 2015. Demographics, clinical, radiographic, and outcome data were analyzed using an adapted ANN model using learned value nodes from the adult aneurysmal SAH dataset previously reported. The strength of the ANN prediction was measured between - 1 and 1 with - 1 representing no likelihood of SCV and 1 representing high likelihood of SCV. RESULTS: Sixteen patients met study inclusion criteria. The median age for aSAH patients was 15 years. Ten underwent surgical clipping and 6 underwent endovascular coiling for definitive treatment. One patient experienced SCV and 15 did not. The ANN applied here was able to accurately predict all 16 outcomes. The mean strength of prediction for those who did not exhibit SCV was - 0.86. The strength for the one patient who did exhibit SCV was 0.93. CONCLUSIONS: Adult-derived aneurysmal SAH value nodes can be applied to a simple AAN model to accurately predict SCV in children presenting with aSAH. Further work is needed to determine if ANN models can prospectively predict SCV in the pediatric aSAH population in toto; adapted to include mycotic, traumatic, and flow-related origins as well

Hydrocephalus associated with childhood nonaccidental head trauma

OBJECTIVE The incidence of posttraumatic ventriculomegaly (PTV) and shunt-dependent hydrocephalus after nonaccidental head trauma (NAHT) is unknown. In the present study, the authors assessed the timing of PTV development, the relationship between PTV and decompressive craniectomy (DC), and whether PTV necessitated placement of a permanent shunt. Also, NAHT/PTV cases were categorized into a temporal profile of delay in admission and evaluated for association with outcomes at discharge. METHODS The authors retrospectively reviewed the cases of patients diagnosed with NAHT throughout a 10-year period. Cases in which sequential CT scans had been obtained (n = 28) were evaluated for Evans\u27 index to determine the earliest time ventricular dilation was observed. Discharge outcomes were assessed using the King\u27s Outcome Scale for Childhood Head Injury score. RESULTS Thirty-nine percent (11 of 28) of the patients developed PTV. A low admission Glasgow Coma Scale (GCS) score predicted early PTV presentation (within \u3c 3 days) versus a high GCS score (\u3e 1 week). A majority of PTV/NAHT patients presented with a subdural hematoma (both convexity and interhemispheric) and ischemic stroke, but subarachnoid hemorrhage was significantly associated with PTV/NAHT (p = 0.011). Of 6 patients undergoing a DC for intractable intracranial pressure, 4 (67%) developed PTV (p = 0.0366). These patients tended to present with lower GCS scores and develop ventriculomegaly early. Only 2 patients developed hydrocephalus requiring shunt placement. CONCLUSIONS PTV presents early after NAHT, particularly after a DC has been performed. However, the authors found that only a few PTV/NAHT patients developed shunt-dependent hydrocephalus

Hydrocephalus associated with childhood nonaccidental head trauma.

OBJECTIVE The incidence of posttraumatic ventriculomegaly (PTV) and shunt-dependent hydrocephalus after nonaccidental head trauma (NAHT) is unknown. In the present study, the authors assessed the timing of PTV development, the relationship between PTV and decompressive craniectomy (DC), and whether PTV necessitated placement of a permanent shunt. Also, NAHT/PTV cases were categorized into a temporal profile of delay in admission and evaluated for association with outcomes at discharge. METHODS The authors retrospectively reviewed the cases of patients diagnosed with NAHT throughout a 10-year period. Cases in which sequential CT scans had been obtained (n = 28) were evaluated for Evans\u27 index to determine the earliest time ventricular dilation was observed. Discharge outcomes were assessed using the King\u27s Outcome Scale for Childhood Head Injury score. RESULTS Thirty-nine percent (11 of 28) of the patients developed PTV. A low admission Glasgow Coma Scale (GCS) score predicted early PTV presentation (within \u3c 3 days) versus a high GCS score (\u3e 1 week). A majority of PTV/NAHT patients presented with a subdural hematoma (both convexity and interhemispheric) and ischemic stroke, but subarachnoid hemorrhage was significantly associated with PTV/NAHT (p = 0.011). Of 6 patients undergoing a DC for intractable intracranial pressure, 4 (67%) developed PTV (p = 0.0366). These patients tended to present with lower GCS scores and develop ventriculomegaly early. Only 2 patients developed hydrocephalus requiring shunt placement. CONCLUSIONS PTV presents early after NAHT, particularly after a DC has been performed. However, the authors found that only a few PTV/NAHT patients developed shunt-dependent hydrocephalus

Functional Neuroanatomy of Secondary Self-Injurious Behavior

BACKGROUND: Secondary self-injurious behavior (SSIB) is underreported and predominantly not associated with suicide. In both adults and children, SSIB can cause intractable self-harm and is associated with a variety of clinical disorders, particularly those involving dysfunctional motor control. METHODS: We performed a literature review evaluating the clinical efficacy of deep-brain stimulation (DBS) as modulating SSIB observations and review current progress in preclinical SSIB animal studies. RESULTS: Neuromodulation is an effective therapeutic option for several movement disorders. Interestingly, this approach is emerging as a potentially effective treatment for movement disorder-associated SSIB (secondary); however, it is important to understand the neuroanatomy, clinical appraisal, and outcome data when considering surgical therapy for SSIB. CONCLUSION: The current review examines the literature encompassing animal models and human case studies while identifying existing hypotheses from cytoarchitectonic-based targeting to neurotransmitter-based pathways. This review also highlights the need for awareness of an underrecognized pathology that may be amenable to DBS

Delay in Arrival to Care in Perpetrator-Identified Nonaccidental Head Trauma: Observations and Outcomes.

BACKGROUND: Children who sustained nonaccidental head trauma (NAHT) are at severe risk for mortality within the first 24 hours after presentation. OBJECTIVE: Extent of delay in seeking medical attention may be related to patient outcome. METHODS: A 10-year, single-institution, retrospective review of 48 cases treated at a large tertiary Children\u27s Hospital reported to the New York State Central Registrar by the child protection team was conducted. The perpetrator was identified in 28 cases on the basis of confession or conviction. The medical and legal records allowed for identification of time of injury and the interval between injury and arrival to the hospital; this information was categorized as follows:(without delay); 6-12 hours (moderate delay); and \u3e12 hours (severe delay). The King\u27s Outcome Scale for Childhood Head Injury (KOSCHI) score was recorded for each case. RESULTS: All children were 3 years of age or younger (2.1-34 months) and predominantly male (68%; 19/28). On arrival, 61% of patients (17/28) presented with moderate or severe delay. A low arrival Glasgow Coma Scale (GCS) score (P \u3c 0.0001) and extracranial injuries (P \u3c 0.0061) correlated with worse clinical patient outcomes. Patients with an arrival GCS score CONCLUSION: Patients presenting to medical care 6-12 hours after NAHT (moderate delay) appeared to have worse outcomes than those presenting earlier or later