No abstract

Management of patient with Lupus Nephritis (LN) continues to remain a challenge for the treating physicians because of considerable morbidity and even mortality. The search of biomarkers in serum and urine is a focus of researchers to unravel new targets for therapy. In the present study, the utility of NMR-based serum metabolomics has been evaluated for the first time in discriminating LN patients from non-nephritis lupus patients (SLE) and further to get new insights into the underlying disease processes for better clinical management. Metabolic profiling of sera obtained from 22 SLE patients, 40 LN patients and 30 healthy controls (HC) were performed using high resolution 1D 1H-CPMG and diffusion edited NMR spectra to identify the potential molecular biomarkers. Using multivariate analysis, we could distinguish SLE and LN patients from HC and LN from SLE patients. Compared to SLE patients, the LN patients had increased serum levels of lipid metabolites (including LDL/VLDL lipoproteins), creatinine and decreased levels of acetate. Our results revealed that metabolic markers especially lipids and acetate derived from NMR spectroscopy has high sensitivity and specificity to distinguish LN among SLE patients and has the potential to be a useful adjunctive tool in diagnosis and clinical management of LN.

No abstract

Takayasu arteritis (TA) is a debilitating, systemic disease that involves the aorta and large arteries in a chronic inflammatory process that leads to vessel stenosis. Initially, the disease remains clinically silent (or remains undetected) until the patients present with vascular occlusion. Therefore, new methods for appropriate and timely diagnosis of TA cases are needed to start proper therapy on time and also to monitor the patient's response to the given treatment. In this context, NMR-based serum metabolomic profiling has been explored in this proof-of-principle study for the first time to determine characteristic metabolites that could be potentially helpful for diagnosis and prognosis of TA. Serum metabolic profiling of TA patients (n = 29) and healthy controls (n = 30) was performed using 1D (1)H NMR spectroscopy, and possible biomarker metabolites were identified. Using projection to least-squares discriminant analysis, we could distinguish TA patients from healthy controls. Compared to healthy controls, TA patients had (a) increased serum levels of choline metabolites, LDL cholesterol, N-acetyl glycoproteins (NAGs), and glucose and (b) decreased serum levels of lactate, lipids, HDL cholesterol, and glucogenic amino acids. The results of this study are preliminary and need to be confirmed in a prospective study.

Proanthocyanidin is commonly used for inhibiting urinary tract infection (UTI) of sensitive strains of Escherichia coli. The aim of this study was to investigate the effect of proanthocyanidin on adherence of uropathogenic multi-drug resistant E. coli to uroepithelial cells, which has not yet been investigated so far. Extracts of the purified proanthocyanidin were prepared from dried cranberry juice. Purity and structural assignment of proanthocyanidin was assessed using high performance liquid chromatography and 13 C nuclear magnetic resonance spectroscopy, respectively. Subsequently, its affect on multi-drug resistant bacteria as well as quantification of anti-adherence bioactivity on human vaginal and bladder epithelial cells was appraised. Inhibition of adherence to an extent of about 70% with multi-drug resistant E. coli strains was observed on uroepithelial cell. The anti-adherence bioactivity of the proanthocyanidin was detected at concentrations of 10-50 lg/ml with significant bacteriuria. Probable proanthocyanidin through A-type linkages either combines to P-fimbriae of bacterial cells or modifies the structural entity of P-fimbriae and inhibits bacterial adherence to uroepithelial cells. The proanthocyanidin exhibited anti-adherence property with multi-drug resistant strains of uropathogenic P-fimbriated E. coli with in vitro study. Hence proanthocyanidin may be considered as an inhibitory agent for multi-drug resistant strains of E. coli adherence to uroepithelial cells.

No abstract

A method of choosing the correction factor based on Bloch equation for the quantitative estimation of metabolite from 1 H NMR spectra recorded with reduced recycle delay is prescribed. The procedure reduces the experimental time without substantially compromising the accuracy of quantitative estimation. It is based on choosing the correction factors, which depend on T 1 and T 2 of the metabolite and recycle delay used for recording the spectra. It is validated by studying a mixture of amino acids with known concentration of constituents and human serum sample and it provides accuracy of quantitative estimation to 95-96%.

To address the shortcomings of urine culture for the rapid identification of urinary tract infection (UTI), we applied (1)H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate method for fast screening of microorganisms. Study includes 682 urine samples from suspected UTI patients, 50 healthy volunteers, and commercially available standard strains of gram negative bacilli (GNB) (Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumonia, Enterobacter, Acinetobacter, Proteus mirabilis, Citrobacter frundii) and gram positive cocci (GPC) (Enterococcus faecalis, Streptococcus group B, Staphylococcus saprophyticus). Acetate, lactate, ethanol, succinate, creatinine, trimethylamine (TMA), citrate, trimethylamin-N-oxide, glycine, urea, and hippurate were measured by (1)H NMR spectroscopy. All urine specimens were evaluated with culture method. Multivariate discriminant function analysis (DFA) reveals that acetate, lactate, succinate, and formate were able to differentiate, with high accuracy (99.5%), healthy controls from UTI patients. This statistical analysis was also able to classify GNB to GPC infected urine samples with high accuracy (96%). This technique appears to be a promising, rapid, and noninvasive approach to probing GNB and GPC infected urine specimens with its distinguishing metabolic profile. The determination of infection will be very important for rapidly and efficiently measuring the efficacy of a tailored treatment, leading to prompt and appropriate care of UTI patients.