Plasma irisin and its associations with oxidative stress in athletes suffering from overtraining syndrome.

Irisin is a novel exercise-induced myokine that may be involved in regulating energy metabolism. We determined whether overtraining syndrome (OTS) and its biochemical markers are associated with plasma irisin levels in athletes. Seven severely overtrained athletes (OA) and 10 healthy control athletes (CA) were recruited and examined at the time of diagnosis (baseline) and after 6- and 12-months follow-up. Training volume and intensity were initially restricted but progressively increased in OA as OTS symptoms alleviated; CA continued their normal training routine. A maximal cycle ergometer test was performed with irisin analyzed before and after the test. Before the exercise test, irisin levels tended to be lower in OA than in CA at baseline (154.5 ± 28.5 vs. 171.7 ± 58.7 ng/mL). In both groups, at rest irisin levels changed only marginally during follow-up and were not affected by maximal exercise, nor were they associated with physical performance or body fat percentage. Irisin concentration at rest correlated positively with an oxidative stress marker, malondialdehyde (MDA) and negatively with an antioxidant protection marker, oxygen radical absorbance capacity (ORAC) in response to the exercise test in OA at baseline. Our findings help to clarify the possible contribution of irisin and its association with oxidative stress in the pathophysiology of OTS.

Associations of I148M variant in PNPLA3 gene with plasma ALT levels during 2-year follow-up in normal weight and overweight children: the PANIC Study.

OBJECTIVES: PNPLA3 I148M polymorphism (rs738409) has been strongly associated with liver fat content and plasma alanine aminotransferase (ALT) levels in obese adults and children, but little is known about these relationships in normal weight individuals. We studied the associations and interactions of overweight and the PNPLA3 I148M polymorphism with plasma ALT levels during 2-year follow-up in children. METHODS: Subjects were a population sample of 481 Caucasian children aged 6-8 years examined at baseline and 419 children re-examined after 2-year follow-up. Altogether, 58 (12%) of 481 children at baseline and 71 (17%) of 419 children after 2-year follow-up were overweight. We assessed plasma ALT levels and other cardiometabolic risk factors and genotyped the PNPLA3 I148M polymorphism. RESULTS: Being overweight and carrying PNPLA3 148M allele were associated with increased ALT levels at baseline (P = 0.002; P = 0.033) and after 2-year follow-up (P < 0.001; P = 0.001). Being overweight (P < 0.001) and carrying PNPLA3 148M allele (P = 0.001) were also associated with increase in ALT levels during 2-year follow-up. PNPLA3 148M allele carriers had increased ALT levels at baseline (P = 0.024 for interaction) and after 2-year follow-up (P = 0.002 for interaction) as well as a larger increase in ALT levels during 2-year follow-up (P = 0.002 for interaction) if they were overweight but not if they were normal weight. Further adjustment for clinical puberty, dietary factors, physical activity or sedentary behaviour had little or no effect on these associations. CONCLUSION: PNPLA3 148M allele carriers had higher plasma ALT levels and larger increase in ALT levels during follow-up than non-carriers only among overweight children.

NADINE: new approaches to detecting breast cancer by sequential µm-wavelength imaging with the aid of novel frequency analysis techniques.

The study focuses on 12 breasts of six breast cancer patients sequential µm-wavelength imaging, taken by two different 3-5 µm wavelength area indium antimony (InSb) photovoltaic cameras. The aim of the study was to compare the functionality of area and pixel-based frequency analyses. Comparisons between these frequency analysis methods were made according to their relevancy to mammographic findings. Another objective of the study was to find reliable imaging conditions by specifying the border conditions for the patient stabilizing imaging bed and managing the imaging situation. According to the results, the match of pixel based frequency analysis to the mammography findings is better than using area frequency analysis. The results also indicate that when the optical axis of the camera in relation to the surface of the breast to be imaged grows to more than 40°, the emissivity changes dramatically and at that point reliable results will not be obtained. Consequently the analysis of the imagined breast requires more images to be fused into one analysis image to cover the whole breast.

A dynamic infrared imaging-based diagnostic process for breast cancer.

BACKGROUND: Dynamic infrared (IR) imaging is an emerging functional imaging modality for the detection of breast cancer without evidence of optimal imaging and diagnostic application. PURPOSE: To evaluate dynamic IR imaging in breast cancer diagnostics by comparing a stepwise diagnostic scheme to digital mammography and postoperative histopathology. MATERIAL AND METHODS: Dynamic IR imaging of breasts was undertaken preoperatively with a long-wave quantum well (QWIP) and two mid-wave photovoltaic (PV) IR cameras in 10 cases (age 34-80 years) with breast cancer size 6-45 mm on mammography. Image stabilization, two-phase frequency analysis, and two image-processing algorithms were applied. RESULTS: Combining image processing with frequency analysis proved advantageous in detecting breast cancer. The IR imaging process recognized the cancer area independently of tissue density, cancer size, and cancer appearance on mammography. Compared to histopathology, all cancers yielded abnormal analysis results, including one case of ductal carcinoma in situ. Evidence of lymphatic invasion in postoperative histopathology, imaging with PV camera, and image processing with the Wiener filtering combination correlated with highest confidence between normal and cancer tissue measured by the calculated superiority value. CONCLUSION: Dynamic IR imaging with image-processing-guided frequency analysis is a promising modality for breast cancer detection and may not have the tissue-dependent limitations of mammography. Our results encourage further work on medical IR imaging and comparison to established breast-imaging modalities.

Dynamic infrared imaging in identification of breast cancer tissue with combined image processing and frequency analysis.

Five combinations of image-processing algorithms were applied to dynamic infrared (IR) images of six breast cancer patients preoperatively to establish optimal enhancement of cancer tissue before frequency analysis. mid-wave photovoltaic (PV) IR cameras with 320x254 and 640x512 pixels were used. The signal-to-noise ratio and the specificity for breast cancer were evaluated with the image-processing combinations from the image series of each patient. Before image processing and frequency analysis the effect of patient movement was minimized with a stabilization program developed and tested in the study by stabilizing image slices using surface markers set as measurement points on the skin of the imaged breast. A mathematical equation for superiority value was developed for comparison of the key ratios of the image-processing combinations. The ability of each combination to locate the mammography finding of breast cancer in each patient was compared. Our results show that data collected with a 640x512-pixel mid-wave PV camera applying image-processing methods optimizing signal-to-noise ratio, morphological image processing and linear image restoration before frequency analysis possess the greatest superiority value, showing the cancer area most clearly also in the match centre of the mammography estimation.

Imaging of breast cancer with mid- and long-wave infrared camera.

In this novel study the breasts of 15 women with palpable breast cancer were preoperatively imaged with three technically different infrared (IR) cameras - micro bolometer (MB), quantum well (QWIP) and photo voltaic (PV) - to compare their ability to differentiate breast cancer from normal tissue. The IR images were processed, the data for frequency analysis were collected from dynamic IR images by pixel-based analysis and from each image selectively windowed regional analysis was carried out, based on angiogenesis and nitric oxide production of cancer tissue causing vasomotor and cardiogenic frequency differences compared to normal tissue. Our results show that the GaAs QWIP camera and the InSb PV camera demonstrate the frequency difference between normal and cancerous breast tissue; the PV camera more clearly. With selected image processing operations more detailed frequency analyses could be applied to the suspicious area. The MB camera was not suitable for tissue differentiation, as the difference between noise and effective signal was unsatisfactory.