Recurrent Genomic Gains in Preinvasive Lesions as a Biomarker of Risk for Lung Cancer

Lung carcinoma development is accompanied by field changes that may have diagnostic significance. We have previously shown the importance of chromosomal aneusomy in lung cancer progression. Here, we tested whether genomic gains in six specific loci, TP63 on 3q28, EGFR on 7p12, MYC on 8q24, 5p15.2, and centromeric regions for chromosomes 3 (CEP3) and 6 (CEP6), may provide further value in the prediction of lung cancer. Bronchial biopsy specimens were obtained by LIFE bronchoscopy from 70 subjects (27 with prevalent lung cancers and 43 individuals without lung cancer). Twenty six biopsies were read as moderate dysplasia, 21 as severe dysplasia and 23 as carcinoma in situ (CIS). Four-micron paraffin sections were submitted to a 4-target FISH assay (LAVysion, Abbott Molecular) and reprobed for TP63 and CEP 3 sequences. Spot counts were obtained in 30–50 nuclei per specimen for each probe. Increased gene copy number in 4 of the 6 probes was associated with increased risk of being diagnosed with lung cancer both in unadjusted analyses (odds ratio = 11, p<0.05) and adjusted for histology grade (odds ratio = 17, p<0.05). The most informative 4 probes were TP63, MYC, CEP3 and CEP6. The combination of these 4 probes offered a sensitivity of 82% for lung cancer and a specificity of 58%. These results indicate that specific cytogenetic alterations present in preinvasive lung lesions are closely associated with the diagnosis of lung cancer and may therefore have value in assessing lung cancer risk.     

Dynamics of macrozoobenthos productivity characteristics on shelves of the Far Eastern seas in the 2000s

The trophic structure of benthic communities in the Sea of Okhotsk and Bering Sea was analyzed based on the results of macrobenthic survey catches conducted in the Far Eastern seas in the 2000s. The production of trophic levels and entire communities was determined. It was shown that production of benthic communities is still at a high level and has almost not changed since the 1980s. The arrangement of the communities of some shelf areas by productivity characteristics was made.     

SERPINs shelter the endowed migrants in a hostile land

Since metastatic lesions of solid tumors are the major cause of mortality in cancer patients, understanding the molecular mechanisms of metastasis is of paramount importance. Although extensive knowledge has been accumulated regarding the early steps in metastasis—starting with the departure of cancer cells from their primary sites, to their transit through the hematogenous and/or lymphatic systems, and ending with their entrance into the parenchyma of distant organs—it is difficult if not impossible to translate such knowledge into medicine due to the challenge of identifying patients with only primary tumors but otherwise pristine organs. In other words, autopsy studies indicate that a large proportion of patients already harbor dormant, undetectable micrometastases at the time of cancer diagnosis (Hensel et al, 2013 ). Accordingly, stopping tumor cell dissemination is too late for these patients. Therefore, understanding the survival and outgrowth of micrometastases may hold greater promise to combat metastatic disease.     

Repeated pre-training sleep restriction in adolescent rats impaired spatial performance

Sleep and Biological Rhythms - Chronic sleep deprivation (SD) is an overwhelming problem in young students. Firstly, we investigated whether different levels of pre-training SD had effects on...     

Erratum to: Endogenous TGFβ1 Plays a Crucial Role in Functional Recovery After Traumatic Brain Injury Associated with Smad3 Signal in Rats

Neurochemical Research -     

Particle Pollution Estimation Based on Image Analysis

Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM_2.5 index. The results demonstrate that the image analysis method provides good prediction of PM_2.5 indexes, and different features have different significance levels in the prediction.