Detection of a C-insertion polymorphism within the human tumor necrosis factor alpha (TNFA) gene

We have identified a C-insertion polymorphism in the 5'UTR of the first exon of the human tumor necrosis factor alpha (TNFA) gene. TNFA is a cytokine that plays an important role in the inflammatory response.     

Age-related augmentation of phosphorylase b kinase in hepatic tissue from the glycogen-storage-disease (gsd/gsd) rat.

The effects of food deprivation on body weight, liver weight, hepatic glycogen content, glycogenolytic enzymes and blood metabolites were compared in young and old phosphorylase b kinase-deficient (gsd/gsd) rats. Although the concentration of glycogen in liver from 9-week-old female gsd/gsd rats (730 mumol of glucose equivalents/g wet wt.) was increased by 7-8% during starvation, total hepatic glycogen was decreased by 12% after 24 h without food. In 12-month-old male gsd/gsd rats the concentration of liver glycogen (585 mumol of glucose equiv./g wet wt.) was decreased by 16% and total hepatic glycogen by nearly 40% after food deprivation for 24 h. Phosphorylase b kinase and phosphorylase a were present at approx. 10% of the control activities in 9-week-old gsd/gsd rats, but both enzyme activities were increased more than 3-fold in 12-month-old affected rodents. It is concluded that the age-related ability to mobilize hepatic glycogen appears to result from the augmentation of phosphorylase b kinase during maturation of the gsd/gsd rat.     

Principles and applications of luminescence spectrometry coupled to liquid chromatographic techniques

An overview is presented of the physicochemical basis of luminescence, and its application to the detection of chemicals (drugs, biomedically important compounds, environmentally active substances) in liquid chromatographic systems.     

Increases in tobacco exposure biomarkers measured in non-smokers exposed to sidestream cigarette smoke under controlled conditions

National surveys of the exposure of non-smokers to secondhand smoke based on serum cotinine analyses have consistently identified certain groups within the population including children, males and non-Hispanic Blacks as having relatively greater exposure. Although these differences in mean serum cotinine concentrations probably represent differences in exposure of individuals in their daily lives, it is also possible that metabolic or other differences in response might influence the results. To better define the nature of those findings, we have examined the response of 40 non-smokers including both men and women and African-Americans and whites to sidestream (SS) cigarette smoke generated by a smoking machine under controlled conditions. In this study, participants were exposed to aged, diluted SS smoke (ADSS) generated in an environmental chamber with a mean air nicotine concentration of 140 μg m^?3 and 8.6?ppm CO for 4?h. Salivary cotinine was measured every 30?min, and serum cotinine samples were taken prior to, and 2?h after exposure. Urinary nicotine metabolites and NNAL, a tobacco-specific nitrosamine, and 4-aminobiphenyl (4-AB) haemoglobin adducts were also measured prior to and 2?h following the exposure. Under these uniform, controlled conditions, we found a similar response to ADSS smoke exposure among all the participants. In all cases a significant increase in biomarker concentration was noted following exposure, and the short-term increases in salivary cotinine concentration were quite similar at approximately 12?pg ml^?1 min^?1 among the groups. In this small study, no significant differences by gender or race were seen in the mean increases observed in cotinine, NNAL or 4-AB adducts following 4?h of exposure. Thus, our results are most consistent with a relatively uniform response in tobacco biomarker concentrations following short-term exposure to ADSS tobacco smoke, and suggest that biomarker measurements are capable of effectively indicating increases in exposure among groups of non-smokers.     

Flow Cytometry Bioinformatics

Flow cytometry bioinformatics is the application of bioinformatics to flow cytometry data, which involves storing, retrieving, organizing, and analyzing flow cytometry data using extensive computational resources and tools. Flow cytometry bioinformatics requires extensive use of and contributes to the development of techniques from computational statistics and machine learning. Flow cytometry and related methods allow the quantification of multiple independent biomarkers on large numbers of single cells. The rapid growth in the multidimensionality and throughput of flow cytometry data, particularly in the 2000s, has led to the creation of a variety of computational analysis methods, data standards, and public databases for the sharing of results. Computational methods exist to assist in the preprocessing of flow cytometry data, identifying cell populations within it, matching those cell populations across samples, and performing diagnosis and discovery using the results of previous steps. For preprocessing, this includes compensating for spectral overlap, transforming data onto scales conducive to visualization and analysis, assessing data for quality, and normalizing data across samples and experiments. For population identification, tools are available to aid traditional manual identification of populations in two-dimensional scatter plots (gating), to use dimensionality reduction to aid gating, and to find populations automatically in higher dimensional space in a variety of ways. It is also possible to characterize data in more comprehensive ways, such as the density-guided binary space partitioning technique known as probability binning, or by combinatorial gating. Finally, diagnosis using flow cytometry data can be aided by supervised learning techniques, and discovery of new cell types of biological importance by high-throughput statistical methods, as part of pipelines incorporating all of the aforementioned methods. Open standards, data, and software are also key parts of flow cytometry bioinformatics. Data standards include the widely adopted Flow Cytometry Standard (FCS) defining how data from cytometers should be stored, but also several new standards under development by the International Society for Advancement of Cytometry (ISAC) to aid in storing more detailed information about experimental design and analytical steps. Open data is slowly growing with the opening of the CytoBank database in 2010 and FlowRepository in 2012, both of which allow users to freely distribute their data, and the latter of which has been recommended as the preferred repository for MIFlowCyt-compliant data by ISAC. Open software is most widely available in the form of a suite of Bioconductor packages, but is also available for web execution on the GenePattern platform.

This is a “Topic Page” article for PLOS Computational Biology.

     

Utilization of milk energy by suckling mink kits

A total of 36 mink dams and their litters of 3, 6 or 9 kits were used for determination of milk intake of the suckling young by means of deuterium dilution technique, and chemical composition of milk and of kit bodies. Measurements were performed during lactation weeks 1?–?4, each week with 3 dams with each litter size. Milk intake was determined over a 48?h measurement period, and by the end of this milk samples were collected and 2 kits (litters of 6 and 9) or 1 kit per litter (litters of 3) were killed for body chemical composition. Based on the results, different models were applied for calculation of the energetic efficiency of milk. Dam milk yield increased steadily from week 1 until week 3 but only slightly from week 3 to 4. The increase declined with increasing litter size, and for dams suckling 9 kits the increment from week 3 to week 4 was only 2?g. The dry matter content of milk increased significantly as lactation progressed, being reflected in crude protein increasing from 6.9% in lactation week 1 to 8.1% in week 4. Milk fat increased concomitantly from 5.6% to 8.0%. In kit bodies, crude protein content increased from 9.4% in week 1 to about 12% in weeks 3 and 4. Body fat content increased from week 1 (4.1%) to week 3 (8.4%) and then declined in week 4 (7.1%). Animals suckled in litters of 3 kits had the highest milk intake and live weight and kits suckled in litters of 9 had the lowest milk intake, live weight and daily gain. In terms of milk intake per g gain kits in litters of 6 were the most efficient, with 4.1?g milk per g body gain. The metabolizable energy requirement for maintenance (MEm) was estimated to 448 kJ/kg^0.75 and the efficiency of utilization of ME for body gain (k_g) to 0.67, the estimates being higher (MEm) or in good agreement with previous findings (k_g) in suckling mink kits.     

Smelling the Diagnosis: The Electronic Nose as Diagnostic Tool in Inflammatory Arthritis. A Case-Reference Study

Objective

To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls.

Methods

In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored.

Results

Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60–0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61–0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55–0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups.

Conclusions

Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.