NATCON 2022 Panel discussion: "TB vaccination - Going Forward"

Vaccination is important tuberculosis (TB) preventive strategy that is essential to achieve the goals of the End TB strategy. The BCG vaccination at birth offers protection against TB in young children but not in adolescents and adults. New TB vaccines are the need of the hour. The TB vaccine development pipeline in the past years is encouraging with newer TB vaccines in clinical trials in humans. The focus of the newer TB vaccine is the prevention of infection, disease, and recurrence of TB disease. Therapeutic vaccines focus on better treatment outcomes and prevention of TB recurrence. BCG revaccination is of current interest. Novel, safe, and efficient TB vaccines that prevent TB infection and disease if introduced in 2025 could drastically reduce the rate of TB incidence. However, the development of an effective vaccine for TB is challenging. Engagement of stakeholders, mobilizing funding, and advocacy could accelerate the newer TB vaccine development process.

A deep learning approach based hardware solution to categorise garbage in environment

Garbage detection and disposal have become one of the major hassles in urban planning. Due to population influx in urban areas, the rate of garbage generation has increased exponentially along with garbage diversity. In this paper, we propose a hardware solution for garbage segregation at the base level based on deep learning architecture. The proposed deep-learning-based hardware solution SmartBin can segregate the garbage into biodegradable and non-biodegradable using Image classification through a Convolutional Neural Network System Architecture using a Real-time embedded system. Garbage detection via image classification aims for quick and efficient categorization of garbage present in the bin. However, this is an arduous task as garbage can be of any dimension, object, color, texture, unlike object detection of a particular entity where images of objects of that entity do share some similar characteristics and traits. The objective of this work is to compare the performance of various pre-trained Convolution Neural Network namely AlexNet, ResNet, VGG-16, and InceptionNet for garbage classification and test their working along with hardware components (PiCam, raspberry pi, infrared sensors, etc.) used for garbage detection in the bin. The InceptionNet Neural Network showed the best performance measure for the proposed model with an accuracy of 98.15% and a loss of 0.10 for the training set while it was 96.23% and 0.13 for the validation set.

Relative quantification of BCL2 mRNA for diagnostic usage needs stable uncontrolled genes as reference

Dysregulation of BCL2 is a pathophysiology observed in haematological malignancies. For implementation of available treatment-options it is preferred to know the relative quantification of BCL2 mRNA with appropriate reference genes. For the choice of reference genes-(i) Reference Genes were selected by assessing variation of >60,000 genes from 4 RNA-seq datasets of haematological malignancies followed by filtering based on their GO biological process annotations and proximity of their chromosomal locations to known disease translocations. Selected genes were experimentally validated across various haematological malignancy samples followed by stability comparison using geNorm, NormFinder, BestKeeper and RefFinder. (ii) 43 commonly used Reference Genes were obtained from literature through extensive systematic review. Levels of BCL2 mRNA was assessed by qPCR normalized either by novel reference genes from this study or GAPDH, the most cited reference gene in literature and compared. The analysis showed PTCD2, PPP1R3B and FBXW9 to be the most unregulated genes across lymph-nodes, bone marrow and PBMC samples unlike the Reference Genes used in literature. BCL2 mRNA level shows a consistent higher expression in haematological malignancy patients when normalized by these novel Reference Genes as opposed to GAPDH, the most cited Reference Gene. These reference genes should also be applicable in qPCR platforms using Taqman probes and other model systems including cell lines and rodent models. Absence of sample from healthy-normal individual in diagnostic cases call for careful selection of Reference Genes for relative quantification of a biomarker by qPCR.BCL2 can be used as molecular diagnostics only if normalized with a set of reference genes with stable yet low levels of expression across different types of haematological malignancies.

Bilateral superficial brachial artery

Variations of the upper limb arterial system are well documented. Accurate knowledge of the normal and variant arterial anatomy of the axillary artery is important for clinical procedures and vascular radiology. In this article, a rare bilateral variation of superficial brachial artery is being reported. The axillary artery on both sides divided in its third part into a superficial brachial artery passing superficial to the lateral root of median nerve and brachial artery proper. The former terminated in the cubital fossa by dividing into ulnar and radial arteries while the later descended deep to the medial root of median nerve and gave anterior and posterior circumflex humeral branches of axillary artery and profunda brachii of brachial artery. Then it terminated by giving twigs to muscles of arm. Earlier superficial brachial artery is reported with a prevalence rate varying from 0.2-25 % but a bilateral variation is extremely rare. Further its ontogeny and clinical implications are discussed in detail.

Adenyl cyclase activity in Duchenne dystrophic muscle

Adenyl cyclase activity in normal and Duchenne dystrophic muscle was assayed using a radiochemical method. In dystrophic muscle, the enzyme activity is reduced. The reduced enzyme activity and its adverse effects on energy metabolism in dystrophic patients are discussed.