Pediatric spondylodiscitis (PSD) is a rare disease with a major impact on mobility and functional status. Data concerning demographic and microbiological characteristics, clinical course, treatment, and outcome are scarce. Therefore, the aim of this study was to present clinical experiences of a third-level hospital (2009-2019) in PSD and compare these with adult spondylodiscitis (ASD). Of a total of 10 PSD patients, most of the infants presented with unspecific pain such as hip pain or a limping, misleading an adequate diagnosis of spine origin. Eight patients could be treated conservatively whereas surgery was performed in two cases with one case of tuberculous PSD (tPSD). The causative agent was detected in three of the patients. The diagnosis of PSD is often difficult since clinical symptoms are unspecific and causative pathogens often remain undetected. Nevertheless, empirical anti-infective therapy also seems to be effective. Based on recent studies, clinicians should be encouraged to keep the duration of anti-infective therapy in children short. Since comorbidities are not presented in PSD it is unclear which children suffer from PSD; thus, studies are necessary to identify predisposing factors for PSD. In our study, PSD differs from ASD in diagnostic and especially in therapeutic aspects. Therefore, specific guidelines for PSD would be desirable.
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http://dx.doi.org/10.3390/children9081103 | DOI Listing |
Alzheimers Dement
December 2024
Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, U.S.A., Philadelphia, PA, USA.
Background: The vicious cycle between depression and dementia increases the risk of Alzheimer's Disease (AD) pathogenesis and pathology. This study investigates therapeutic effectiveness versus side effects and the underlying mechanisms of intranasal dantrolene nanoparticles (IDNs) to treat depression behavior and memory loss in 5XFAD mice.
Method: 5XFAD and wild-type B6SJLF1/J mice were treated with IDNs (IDN, 5 mg/kg) in Ryanodex formulation for a duration of 12 weeks.
Alzheimers Dement
December 2024
Department of Anesthesiology and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, U.S.A., Philadelphia, PA, USA.
Background: This study investigates the therapeutic versus side effects of intranasal lithium chloride (LiCl) in Ryanodex formulation vehicle (RFV) to inhibit inflammation and pyroptosis and to ameliorate on cognitive dysfunction and depressive behavior in 5XFAD mice.
Method: 5XFAD and wild type (WT) B6SJLF1/J mice were treated with intranasal or oral LiCl (3 mM/kg) dissolved in RFV starting at 2 or 9 months old and the continuous treatment lasted for 12 weeks. Behavior was examined for depression, cognition, olfaction, and motor function at the ages of 5 or 12 months.
Background: Alzheimer's disease is the most dreaded multifactorial neurological illness for which there is currently no known treatment. Although the exact cause of AD is still unknown, several factors related to lifestyle, genetics, and environment are known to have a significant role in the disease's development. Alzheimer's disease is characterized by neuronal loss, neurofibrillary tangles, and senile plaques.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Department of Bionano Technology, Gachon University, Seongnam, Korea, Republic of (South).
Background: Electroencephalography (EEG) is a non-intrusive technique that provides comprehensive insights into the electrical activities of the brain's cerebral cortex. The brain signals obtained from EEGs can be used as a neuropsychological biomarker to detect different stages of Alzheimer's disease (AD) through quantitative EEG (qEEG) analysis. This paper investigates the difference in the abnormalities of resting state EEG (rEEG) signals between eyes-open (EOR) and eyes-closed (ECR) in AD by analyzing 19- scalp electrode EEG signals and making a comparison with healthy controls (HC).
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
Department of Biomedical Engineering, College of Health Science, Yonsei University, Wonju, Republic of Korea.
Unlabelled: This study aims to create a fatigue recognition system that utilizes electroencephalogram (EEG) signals to assess a driver's physiological and mental state, with the goal of minimizing the risk of road accidents by detecting driver fatigue regardless of physical cues or vehicle attributes. A fatigue state recognition system was developed using transfer learning applied to partial ensemble averaged EEG power spectral density (PSD). The study utilized layer-wise relevance propagation (LRP) analysis to identify critical cortical regions and frequency bands for effective fatigue discrimination.
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