Background. Colorectal carcinoma is the third cause of cancer deaths in the world. For diagnosis, invasive methods like colonoscopy and sigmoidoscopy are used, and noninvasive screening tests are not very accurate. We decided to study the potential of 1HNMR spectroscopy with metabolomics and chemometrics as a preliminary noninvasive test. We obtained a distinguishing pattern of metabolites and metabolic pathways between colon cancer patient and normal. Methods. Sera were obtained from confirmed colon cancer patients and the same number of healthy controls. Samples were sent for 1HNMR spectroscopy and analysis was carried out Chenomex and MATLAB software. Metabolites were identified using Human Metabolic Data Base (HDMB) and the main metabolic cycles were identified using Metaboanalyst software. Results. 15 metabolites were identified such as pyridoxine, orotidine, and taurocholic acid. Main metabolic cycles involved were the bile acid biosynthesis, vitamin B6 metabolism, methane metabolism, and glutathione metabolism. Discussion. The main detected metabolic cycles were also reported earlier in different cancers. Our observations corroborated earlier studies that suggest the importance of lowering serum LCA/DCA and increasing vitamin B6 intake to help prevent colon cancer. This work can be looked upon as a preliminary step in using 1HNMR analysis as a screening test before invasive procedures.

Intravenous laser blood irradiation (ILBI) is widely applied in the treatment of different pathologies including diabetes mellitus. The aim of this study is to evaluate the effects of ILBI on the metabolites of blood in diabetic type 2 patients using metabolomics. We compared blood samples of nine diabetic type 2 patients, using metabolomics, before and after ILBI with blue light laser. The results showed significant decrease in glucose, glucose 6 phosphate, dehydroascorbic acid, R-3-hydroxybutyric acid, L-histidine, and L-alanine and significant increase in L-arginine level in blood and blood sugar in the patients have reduced significantly (p < 0.05). This study clearly demonstrated a significant positive effect of ILBI on metabolites of blood in diabetic type 2 patients. These findings support the therapeutic potential of ILBI in diabetic patients.

Cancer is currently a major international health problem. The development of resistance to chemotherapy has resulted in the search for herbal drugs. Ginger is a medicinal plant with several clinical applications. Metabolomics is a simultaneous detection of all the metabolites by use of 1HNMR or mass spectroscopy and interpretation by modeling software. The purpose of this study was to detect the altered metabolites of Raji cells in the presence of ginger extract in vitro. Cells were cultured in the presence and absence of methanolic ginger extract in RPMI medium. IC50 determined by MTT and lipophilic and hydrophilic extracts were prepared from control and treated groups which were analyzed by 1HNMR. The IC50 was 1000 μg/mL. Modeling of spectra was carried out on the two groups using OSC-PLS with MATLAB software and the main metabolites detected. Further analysis was carried out using MetaboAnalyst database. The main metabolic pathways affected by the ginger extract were detected. Ginger extract was seen to effect the protein biosynthesis, amino acid, and carbohydrate metabolism and had a strong cytotoxic effect on Raji cells in vitro.

Vaccines require a period of at least three months for clinical trials, hence a method that can identify elicitation of immune response a few days after the first dose is a necessity. Evolutionary variable selections are modeling approaches for proper manipulation of available data which were used to set up an animal model for classification of time dependent 1HNMR metabolomic profiles and pattern recognition of fluctuations of metabolites in two groups of male rabbits. One group of rabbits was immunized with human red blood cells and the other used as control. Blood was obtained every 48 h from each rabbit for a period of six weeks and the serum monitored for antibodies and metabolites by 1HNMR spectra. Evaluation of data was carried out using orthogonal signal correction followed by principal component analysis and partial least square. A neural network was also set up to predict immunization profiles. A distinct separation in patterns of significant metabolites was obtained between the two groups, just a few days after the first and the second dose. These metabolites were used as targets of neural networks where each sample was used as test, validation and training and their quantitative influence predicted by regression. This model could be used for prediction of immunization in rabbits a few days after the first dose with 96% accuracy. Similar animals and human vaccine trials would assist greatly in reaching early conclusions in advance of the usual two month immunization schedule; resulting in an appreciable saving of cost and time.

The initial success of any adopted anti-infective strategy to malaria is followed by a descent due to the emergence of resistance to it. The search for new drugs and drug targets is a consistent demand in this disease. Eosin B, a common laboratory dye, is reported to have good antiparasitic properties in vitro. It was studied for its antiparasitic effect in vivo on chloroquine-sensitive Plasmodium berghei murine malaria. Eosin B was administered in 2 different doses by either the oral or parenteral route, once or twice daily to mice infected with Plasmodium berghei. Both the doses of eosin B 400 mg/kg and 800 mg/kg gave better results than the controls which were 40 mg/kg chloroquine and 100 mg/kg of arteether with P < 0.005 significance. Percentage suppressive activity by Peter's test of eosin B was better, though at a higher dose than both the controls. Survival rate of mice receiving the higher dose of eosin B was longer than that of the controls. When administered twice daily, the mice were fully cured after 4 days. Eosin B seems to be a promising drug exhibiting good antimalarial effects in the murine model of the disease.