In human exhaled breath, more than 3000 volatile organic compounds (VOCs) are found, which are directly or indirectly related to internal biochemical processes in the body. Electronic noses (E-noses) could play a potential role in screening/analyzing various respiratory and systemic diseases by studying breath signatures. An E-nose integrates a sensor array and an artificial neural network that responds to specific patterns of VOCs, and thus can act as a non-invasive technology for disease monitoring. The gold standard blood glucose monitoring test for diabetes diagnostics is invasive and highly uncomfortable. This contributes to the massive need for technologies which are non-invasive and can be used as an alternative to blood measurements for glucose detection. While lung cancer is one of the deadliest cancers with the highest death rate and an extremely high yearly global burden, the conventional diagnosis means, such as sputum cytology, chest radiography, or computed tomography, do not support wide-range population screening. A few standard non-invasive techniques, such as mass spectrometry and gas chromatography, are expensive, non-portable, and require skilled personnel for operation and are again not suitable for large-scale screening. Breath contains markers for both diabetes and lung cancer along with markers for several diseases and thus, a non-invasive technique such as the E-nose would greatly improve analysis procedures over existing invasive methods. This review shows the state-of-the-art technologies for VOC detection and machine learning approaches for two clinical models: diabetes and lung cancer detection.
Ectrodactyly, ectodermal dysplasia, and cleft lip/palate syndrome (EEC) syndrome is a rare genetic disorder with an incidence of around 1 in 90,000 in population. It is known with various names including split hand–split foot–ectodermal dysplasia–cleft syndrome or split hand, cleft hand, or lobster claw hand/foot. We report first case of EEC with associated heart disease (Tetralogy of Fallot) who was diagnosed as EEC on the basis of clinical features and EEC was confirmed with genetic analysis.
Thrombocytopenia absent radius (TAR) syndrome is a very rare and infrequently seen congenital disorder with an approximate frequency of 0.42/100,000 live births. It is associated with bilateral absence of radii, hypo-megakaryocytic thrombocytopenia, and presence of both thumbs. The other systems which are affected by TAR syndrome include skeletal, hematologic, and cardiac systems. Intracranial hemorrhages due to thrombocytopenia and cardiac disorders are a common association usually seen with this syndrome and are usual cause of death. We describe a 3-month-old infant who was diagnosed with TAR syndrome on the basis of clinical features (thrombocytopenia and bilateral absent radius bone and confirmed by genetic analysis). The patient was diagnosed to have Tetralogy of Fallot, for which the infant was managed with definitive repair and thrombocytopenia was managed with platelet transfusion. Infants with TAR syndrome should be assessed for other associated malformations of various systems and followed up regularly and parents should be counseled for associated expected complications in these patients. We report an infant with TAR syndrome with Tetralogy of Fallot, which has not been reported in medical literature until now and this is the first case of its type.
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