Urinary Volatomic Expression Pattern: Paving the Way for Identification of Potential Candidate Biosignatures for Lung Cancer

The urinary volatomic profiling of Indian cohorts composed of 28 lung cancer (LC) pa tients and 27 healthy subjects (control group, CTRL) was established using headspace solid phase microextraction technique combined with gas chromatography mass spectrometry methodology as a powerful approach to identify urinary volatile organic metabolites (uVOMs) to discriminate among LC patients from CTRL. Overall, 147 VOMs of several chemistries were identified in the intervention groups—including naphthalene derivatives, phenols, and organosulphurs—augmented in the LC group. In contrast, benzene and terpenic derivatives were found to be more prevalent in the CTRL group. The volatomic data obtained were processed using advanced statistical analysis, namely partial least square discriminative analysis (PLS-DA), support vector machine (SVM), random forest (RF), and multilayer perceptron (MLP) methods. This resulted in the identification of nine uVOMs with a higher potential to discriminate LC patients from CTRL subjects. These were furan, o-cymene, furfural, linalool oxide, viridiflorene, 2-bromo-phenol, tricyclazole, 4-methyl-phenol, and 1-(4-hydroxy-3,5-di-tert-butylphenyl)-2-methyl-3-morpholinopropan-1-one. The metabolic pathway analysis of the data obtained identified several altered biochemical pathways in LC mainly affecting glycolysis/gluconeogenesis, pyruvate metabolism, and fatty acid biosynthesis. Moreover, acetate and octanoic, decanoic, and dodecanoic fatty acids were identified as the key metabolites responsible for such deregulation. Furthermore, studies involving larger cohorts of LC patients would allow us to consolidate the data obtained and challenge the potential of the uVOMs as candidate biomarkers for LC.info:eu-repo/semantics/publishedVersio

Identification of a biomarker panel for improvement of prostate cancer diagnosis by volatile metabolic profiling of urine

Background: The lack of sensitive and specific biomarkers for the early detection of prostate cancer (PCa) is a major hurdle to improve patient management. Methods: A metabolomics approach based on GC-MS was used to investigate the performance of volatile organic compounds (VOCs) in general and, more specifically, volatile carbonyl compounds (VCCs) present in urine as potential markers for PCa detection. Results: Results showed that PCa patients (n = 40) can be differentiated from cancer-free subjects (n = 42) based on their urinary volatile profile in both VOCs and VCCs models, unveiling significant differences in the levels of several metabolites. The models constructed were further validated using an external validation set (n = 18 PCa and n = 18 controls) to evaluate sensitivity, specificity and accuracy of the urinary volatile profile to discriminate PCa from controls. The VOCs model disclosed 78% sensitivity, 94% specificity and 86% accuracy, whereas the VCCs model achieved the same sensitivity, a specificity of 100% and an accuracy of 89%. Our findings unveil a panel of 6 volatile compounds significantly altered in PCa patients' urine samples that was able to identify PCa, with a sensitivity of 89%, specificity of 83%, and accuracy of 86%. Conclusions: It is disclosed a biomarker panel with potential to be used as a non-invasive diagnostic tool for PCa.info:eu-repo/semantics/publishedVersio

Comprehensive Review of the Effects of Vibrations on Wind Turbine During Energy Generation Operation, Its Structural Challenges and Way Forward

The effects of vibration cannot be overemphasized when it comes to generating energy via wind turbine. Vibration is one of the major challenges faced by the wind turbine, due to the complexity of the structure and the area of installation. This research work focuses on a compressive review of the effects of vibration occurrence on wind turbine during energy generation operations and its economical challenges’. Therefore, this research paper has reviewed various aspects of vibration effects in horizontal wind turbine such as the blades region, tower structure, nacelles compartment, and condition monitoring along with fault diagnosis models. The result from this study has shown that, there are needs to develop and implement a good reliability model, fatigue assessment process, and a well-developed monitoring model for wind turbine during operation. When these things are properly put in place, it will help to reduce unwanted vibration occurrence, eliminate unexpected failure of the wind turbine in operations, and hence sustainable energy generation from wind turbine

<smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="country-region"><smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="place"> Isolation, cloning and molecular characterization of polygalacturonase I (<i style="">pga</i>I) gene from <i style="">Aspergillus niger</i> isolate from mango </smarttagtype></smarttagtype>

153-159 Isolation, cloning and molecular characterization of polygalacturonase (pga1) gene from the mango isolate of Aspergillus niger has been reported. The full length amplicon consisted of 1101 bp. The entire cDNA gene with the predicted protein of 367 amino acids had an estimated mol wt of 38.28 kDa with pI 4.40. When the nucleic acid sequence was compared with other Aspergillus spp., pga1 sequence showed the highest sequence similarity with A. niger and A. fumigatus. Comparison of the amino acid sequences revealed the presence of high degree of homology among the polygalacturonases (PGs) from different fungi. Bioinformatics analysis suggests that nucleic acid sequence of the isolated pgaI gene shares 98% homology with the pgaI gene of A. niger. </smarttagtype