Arylsulfatase B Improves Locomotor Function after Mouse Spinal Cord Injury

Bacterial chondroitinase ABC (ChaseABC) has been used to remove the inhibitory chondroitin sulfate chains from chondroitin sulfate proteoglycans to improve regeneration after rodent spinal cord injury. We hypothesized that the mammalian enzyme arylsulfatase B (ARSB) would also enhance recovery after mouse spinal cord injury. Application of the mammalian enzyme would be an attractive alternative to ChaseABC because of its more robust chemical stability and reduced immunogenicity. A one-time injection of human ARSB into injured mouse spinal cord eliminated immunoreactivity for chondroitin sulfates within five days, and up to 9 weeks after injury. After a moderate spinal cord injury, we observed improvements of locomotor recovery assessed by the Basso Mouse Scale (BMS) in ARSB treated mice, compared to the buffer-treated control group, at 6 weeks after injection. After a severe spinal cord injury, mice injected with equivalent units of ARSB or ChaseABC improved similarly and both groups achieved significantly more locomotor recovery than the buffer-treated control mice. Serotonin and tyrosine hydroxylase immunoreactive axons were more extensively present in mouse spinal cords treated with ARSB and ChaseABC, and the immunoreactive axons penetrated further beyond the injury site in ARSB or ChaseABC treated mice than in control mice. These results indicate that mammalian ARSB improves functional recovery after CNS injury. The structural/molecular mechanisms underlying the observed functional improvement remain to be elucidated.     

Plasma levels of osteopontin identify patients at risk for organ damage in systemic lupus erythematosus

Introduction

Osteopontin (OPN) has been implicated as a mediator of Th17 regulation via type I interferon (IFN) receptor signaling and in macrophage activity at sites of tissue repair. This study assessed whether increased circulating plasma OPN (cOPN) precedes development of organ damage in pediatric systemic lupus erythematosus (pSLE) and compared it to circulating plasma neutrophil gelatinase-associated lipocalin (cNGAL), a predictor of increased SLE disease activity.

Methods

cOPN and cNGAL were measured in prospectively followed pSLE (n = 42) and adult SLE (aSLE; n = 23) patients and age-matched controls. Time-adjusted cumulative disease activity and disease damage were respectively assessed using adjusted-mean SLE disease activity index (SLEDAI) (AMS) and SLICC/ACR damage index (SDI).

Results

Compared to controls, elevated cOPN and cNGAL were observed in pSLE and aSLE. cNGAL preceded worsening SLEDAI by 3-6 months (P = 0.04), but was not associated with increased 6-month AMS. High baseline cOPN, which was associated with high IFNalpha activity and expression of autoantibodies to nucleic acids, positively correlated with 6-month AMS (r = 0.51 and 0.52, P = 0.001 and 0.01 in pSLE and aSLE, respectively) and was associated with SDI increase at 12 months in pSLE (P = 0.001). Risk factors for change in SDI in pSLE were cOPN (OR 7.5, 95% CI [2.9-20], P = 0.03), but not cNGAL, cumulative prednisone, disease duration, immunosuppression use, gender or ancestry using univariate and multivariate logistic regression. The area under the curve (AUC) when generating the receiver-operating characteristic (ROC) of baseline cOPN sensitivity and specificity for the indication of SLE patients with an increase of SDI over a 12 month period is 0.543 (95% CI 0.347-0.738; positive predictive value 95% and negative predictive value 38%).

Conclusion

High circulating OPN levels preceded increased cumulative disease activity and organ damage in SLE patients, especially in pSLE, and its value as a predictor of poor outcome should be further validated in large longitudinal cohorts.     

The phenotype and genotype of rheumatoid arthritis in the Democratic Republic of Congo

Introduction

Little is known about rheumatoid arthritis in the black, particularly in Congolese, populations. Our objective was to describe the phenotype and genotype of rheumatoid arthritis (RA) in Congolese.

Methods

All consecutive rheumatoid arthritis (RA) patients attending Kinshasa University Hospital in a three-year time period were included. Demographics, clinical features and tobacco consumption were noted. Disease Activity Score (DAS)-28 based on the erythrocyte sedimentation rate (ESR), Health Assessment Questionnaire (HAQ), anti-citrullinated peptide antibodies (CCP) antibodies and rheumatoid factor (RF) were determined. Radiographs were scored according to Sharp-van der Heijde. On a subset of patients and controls HLA-DRB1 typing was performed.

Results

A total of 114 females and 14 males aged 51.2 ± 14.9 were included. Mean duration of symptoms was four years. Moderate tobacco consumption was reported in a minority of patients. DAS-28 at first visit was >5.1 and HAQ ≥0.5 in all patients. X-rays showed joint erosions and/or joint space narrowing, mostly of a moderate grade in 55.8% of patients. Anti-CCP and/or RF were present in 48.6% of patients with available data (n = 72) and in 3.0% of controls (n = 67). Radiographic changes and nodules were more frequent in RF or anti-CCP positive patients. One copy of the shared epitope was found in 13 patients (35.1%) and 3 controls (12.5%). Two copies were found in one patient (2.7%) and in one control (4.2%).

Conclusion

Congolese patients with RA consult long after disease onset. Despite this delay, the majority presents without major damage and is RF, anti-CCP and SE negative. We put forward the hypothesis that besides different environmental factors there is probably also a particular genetic risk profile in Congolese patients, different from the HLA-DRB1 shared epitope.     

A novel harmony search-K means hybrid algorithm for clustering gene expression data

Recent progress in bioinformatics research has led to the accumulation of huge quantities of biological data at various data sources. The DNA microarray technology makes it possible to simultaneously analyze large number of genes across different samples. Clustering of microarray data can reveal the hidden gene expression patterns from large quantities of expression data that in turn offers tremendous possibilities in functional genomics, comparative genomics, disease diagnosis and drug development. The k- ¬means clustering algorithm is widely used for many practical applications. But the original k-¬means algorithm has several drawbacks. It is computationally expensive and generates locally optimal solutions based on the random choice of the initial centroids. Several methods have been proposed in the literature for improving the performance of the k-¬means algorithm. A meta-heuristic optimization algorithm named harmony search helps find out near-global optimal solutions by searching the entire solution space. Low clustering accuracy of the existing algorithms limits their use in many crucial applications of life sciences. In this paper we propose a novel Harmony Search-K means Hybrid (HSKH) algorithm for clustering the gene expression data. Experimental results show that the proposed algorithm produces clusters with better accuracy in comparison with the existing algorithms.