Comparison of quantitative REM without atonia parameters in isolated REM sleep behavior disorder and early untreated Parkinson's disease.

OBJECTIVES: To analyze REM sleep without atonia (RWA) metrics in patients with isolated REM sleep behavior disorder (iRBD), Parkinson's disease (PD) and healthy subjects and compare them in terms of degree of presumed brainstem damage. METHODS: Forty-nine iRBD patients, 62 PD patients and 38 healthy controls were included into the analysis. Detailed polysomnographic and clinical data including motor, olfactory, autonomic, and cognitive assessment were obtained in all participants and subsequently compared within groups without RBD (i.e., healthy controls, PD-RBD-) and with RBD (i.e., iRBD, PD-RBD+). SINBAR criteria were used to score RWA. RESULTS: Twenty-one PD patients (33.8 %) had RBD. When comparing PD-RBD-patients and controls, RWA tonic (p = 0.001) and RWA mixed (p = 0.03) were higher in PD-RBD-group. PD-RBD-patients had worse olfactory function than controls (p < 0.001); no significant difference in autonomic or cognitive function was registered. There were no significant differences in RWA parameters when comparing iRBD and PD-RBD + groups. iRBD patients had better olfactory function than PD-RBD+ (p = 0.006); no significant difference in autonomic or cognitive function was registered. PD-RBD + had worse autonomic (p = 0.006) and olfactory (p = 0.001) but not motor and cognitive function compared to PD-RBD-. CONCLUSIONS: Untreated de-novo PD patients without RBD have increased RWA metrics compared to healthy subjects indicating subclinical degeneration of brainstem nuclei responsible for RWA. iRBD patients do not differ in RWA metrics from untreated de-novo PD patients with premotor RBD suggesting a similar level of brainstem degeneration caudal to substantia nigra in both groups. Groups with RBD are associated with autonomic dysfunction.

Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration

ABSTRACT BACKGROUND: Infections, mostly those associated with colonization of wound by different pathogenic microorganisms, are one of the most serious health complications during a medical treatment. Therefore, this study is focused on the isolation, characterization, and identification of microorganisms prevalent in superficial wounds of patients (n = 50) presenting with bacterial infection. METHODS: After successful cultivation, bacteria were processed and analyzed. Initially the identification of the strains was performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on comparison of protein profiles (2-30 kDa) with database. Subsequently, bacterial strains from infected wounds were identified by both matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and sequencing of 16S rRNA gene 108. RESULTS: The most prevalent species was Staphylococcus aureus (70%), and out of those 11% turned out to be methicillin-resistant (mecA positive). Identified strains were compared with patients' diagnoses using the method of artificial neuronal network to assess the association between severity of infection and wound microbiome species composition. Artificial neuronal network was subsequently used to predict patients' prognosis (n = 9) with 85% success. CONCLUSIONS: In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.