Relationship between SDB and short-term outcome in Finnish ischemic stroke patients

Objectives Presence of sleep-disordered breathing (SDB) affects negatively recovery from stroke. The aim of this study is to evaluate the relationships between sleep-disordered breathing (SDB) and outcome measures in Finnish stroke unit cohort: mRS, need of rehabilitation and hospitalization time. Material and Methods An observational longitudinal study consisted of 95 patients referred to the Stroke Unit of Satakunta Hospital District over a period of November 2013 to March 2016. Patients were tested for SDB within 72 hr from the hospital admission because of ischemic stroke or TIA. The patients underwent polysomnography with NOX T3 wireless recorder. Results There are 37% (n = 35) non-OSA patients, 20% (n = 19) of patients have mild obstructive sleep apnea (OSA) and 39% (n = 37) have moderate/severe OSA and 4% (n = 4) have CSA. Patients with OSA have higher proportion of disability scores of mRS 3-5 (38%) compared to non-OSA (11%) and mild OSA (5%) patients on registration day (mRS0), and the same trend is seen at hospital discharge 35% versus 9% and 5%. (p = .009). Proportion of patients with OSA who needed rehabilitation is 65% (n = 19) versus non-OSA patients 17.5% (n = 4) and mild OSA patients 17.5% (n = 4;p = .039). We observed longer duration of hospitalization (5-15 days) in 29% of OSA patients compared to mild OSA patients 47% and OSA patients 54%. (p = .045). Conclusion Ischemic stroke patients with OSA have higher disability, higher need of rehabilitation, and longer hospitalization length. Prescreening tools for recognizing these stroke patients in acute phase could be valuable. That could result in earlier initiation of treatment and might prevent worse recovery from stroke

Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

BACKGROUND: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). OBJECTIVE: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. MATERIALS AND METHODS: ighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. RESULTS: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). CONCLUSION: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI

Disease progression in Plasmodium knowlesi malaria is linked to variation in invasion gene family members.

Emerging pathogens undermine initiatives to control the global health impact of infectious diseases. Zoonotic malaria is no exception. Plasmodium knowlesi, a malaria parasite of Southeast Asian macaques, has entered the human population. P. knowlesi, like Plasmodium falciparum, can reach high parasitaemia in human infections, and the World Health Organization guidelines for severe malaria list hyperparasitaemia among the measures of severe malaria in both infections. Not all patients with P. knowlesi infections develop hyperparasitaemia, and it is important to determine why. Between isolate variability in erythrocyte invasion, efficiency seems key. Here we investigate the idea that particular alleles of two P. knowlesi erythrocyte invasion genes, P. knowlesi normocyte binding protein Pknbpxa and Pknbpxb, influence parasitaemia and human disease progression. Pknbpxa and Pknbpxb reference DNA sequences were generated from five geographically and temporally distinct P. knowlesi patient isolates. Polymorphic regions of each gene (approximately 800 bp) were identified by haplotyping 147 patient isolates at each locus. Parasitaemia in the study cohort was associated with markers of disease severity including liver and renal dysfunction, haemoglobin, platelets and lactate, (r = ≥ 0.34, p =  <0.0001 for all). Seventy-five and 51 Pknbpxa and Pknbpxb haplotypes were resolved in 138 (94%) and 134 (92%) patient isolates respectively. The haplotypes formed twelve Pknbpxa and two Pknbpxb allelic groups. Patients infected with parasites with particular Pknbpxa and Pknbpxb alleles within the groups had significantly higher parasitaemia and other markers of disease severity. Our study strongly suggests that P. knowlesi invasion gene variants contribute to parasite virulence. We focused on two invasion genes, and we anticipate that additional virulent loci will be identified in pathogen genome-wide studies. The multiple sustained entries of this diverse pathogen into the human population must give cause for concern to malaria elimination strategists in the Southeast Asian region

Admission Levels of Interleukin 10 and Amyloid ß 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI).Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI.Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%.Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4).Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI.</p

The severity of Puumala hantavirus induced nephropathia epidemica can be better evaluated using plasma interleukin-6 than C-reactive protein determinations

<p>Abstract</p> <p>Background</p> <p>Nephropathia epidemica (NE) is a Scandinavian type of hemorrhagic fever with renal syndrome caused by Puumala hantavirus. The clinical course of the disease varies greatly in severity. The aim of the present study was to evaluate whether plasma C-reactive protein (CRP) and interleukin (IL)-6 levels associate with the severity of NE.</p> <p>Methods</p> <p>A prospectively collected cohort of 118 consecutive hospital-treated patients with acute serologically confirmed NE was examined. Plasma IL-6, CRP, and creatinine, as well as blood cell count and daily urinary protein excretion were measured on three consecutive days after admission. Plasma IL-6 and CRP levels higher than the median were considered high.</p> <p>Results</p> <p>We found that high IL-6 associated with most variables reflecting the severity of the disease. When compared to patients with low IL-6, patients with high IL-6 had higher maximum blood leukocyte count (11.9 <it>vs </it>9.0 × 10⁹/l, <it>P </it>= 0.001) and urinary protein excretion (2.51 <it>vs </it>1.68 g/day, <it>P </it>= 0.017), as well as a lower minimum blood platelet count (55 <it>vs </it>80 × 10⁹/l, <it>P </it>< 0.001), hematocrit (0.34 <it>vs </it>0.38, <it>P </it>= 0.001), and urinary output (1040 <it>vs </it>2180 ml/day, <it>P </it>< 0.001). They also stayed longer in hospital than patients with low IL-6 (8 <it>vs </it>6 days, <it>P </it>< 0.001). In contrast, high CRP did not associate with severe disease.</p> <p>Conclusions</p> <p>High plasma IL-6 concentrations associate with a clinically severe acute Puumala hantavirus infection, whereas high plasma CRP as such does not reflect the severity of the disease.</p

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

<p>Abstract</p> <p>Background</p> <p>The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.</p> <p>Description</p> <p>We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens <it>Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis</it>. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, <it>C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum </it>and <it>P. brasiliensis </it>thus showing high sensitivity and specificity at a threshold of 0.511. In case of <it>P. brasiliensis </it>the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.</p> <p>Conclusion</p> <p>FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.</p