Vaccine Development for Respiratory Syncytial Virus

The respiratory syncytial virus (RSV) is a human pathogen that causes a lower respiratory infection in infants and healthy adults. The first incidence of RSV was recorded in the 1960s. The greatest success against viruses has always been by increasing immunity through vaccination like in smallpox, measles, influenza, polio. Though RSV spread its roots almost six decades ago, the creation of a vaccine against RSV is still an ongoing challenge. The structural proteins of RSV, mainly F and G, play an essential role in pathogenicity. Structural instability of the F protein is responsible for making the vaccine discovery an uncertain outcome. This review focuses on the details of the vaccine strategies that have been explored so far. It includes an emphasis on the initial formalin-inactivated vaccine, structure-based vaccine, monoclonal antibodies like Palivizumab with a concise portrayal of nanoparticle, chimeric vaccines, and maternal derived immunization. The structure-based vaccine is one of the most reliable strategies to explicate further research. Focusing on the epitopes that monoclonal antibodies can act upon will result in dependable vaccine outcomes

Studies On 3/7 Caspase Activity And Apoptosis Induction By Diarylheptaniods Isolated From Garuga Pinnata Roxb

This study aims to evaluate the stimulation of caspase 3/7, 8 and 9 activity and induction of apoptosis by the diarylheptanoids isolated from Garuga pinnata (G. pinnata) RoxB. Garuganin 1, 3, 4 and 5 which were previously reported for their isolation have tested for their anticancer potencies by different caspase activation and apoptosis induction in MCF-7 and HCT-15 cell lines. However, based on the MTT assay results (Previously reported) Garuganin 3 and 5 were selected for this study.  from the stem bark of G. pinnata. The activation of caspases 3/7, 8, and 9 is a conformational process of cancer cell death. Such activation of caspases by different concentrations (05, 10, 15, 2

Early diagnosis, a step towards reducing mortality in placenta accreta spectrum: a case series

The worldwide incidence of placenta accrete spectrum (PAS) is increasing day by day, mostly due to the increasing trends in caesarean section (CS) rates. PAS is accountable for high maternal morbidity and mortality as it is associated with extensive haemorrhage, which often requires hysterectomy, multiple blood and blood product transfusions, ureteric and bladder injuries and prolonged ICU stay. The aim of this case series is to highlight the importance of early diagnosis and high degree of suspicion of PAS for a planned management in decreasing maternal morbidity and mortality. Antenatal patients who were associated with PAS and managed in obstetrics and gynaecology department, Kalinga institute of medical sciences, Bhubaneswar during the time period of 2 years were critically reviewed and are being presented as case series. High degree of suspicion, pre operative radiological diagnosis, well preparedness and multidisciplinary approach help us in reducing the maternal mortality and morbidity significantly. Conservative management of PAS can preserve future fertility but should only be done in hospitals with 24 hour emergency care and enough expertise as it carries high chances of maternal complications

A hybrid quantum-classical fusion neural network to improve protein-ligand binding affinity predictions for drug discovery

The field of drug discovery hinges on the accurate prediction of binding affinity between prospective drug molecules and target proteins, especially when such proteins directly influence disease progression. However, estimating binding affinity demands significant financial and computational resources. While state-of-the-art methodologies employ classical machine learning (ML) techniques, emerging hybrid quantum machine learning (QML) models have shown promise for enhanced performance, owing to their inherent parallelism and capacity to manage exponential increases in data dimensionality. Despite these advances, existing models encounter issues related to convergence stability and prediction accuracy. This paper introduces a novel hybrid quantum-classical deep learning model tailored for binding affinity prediction in drug discovery. Specifically, the proposed model synergistically integrates 3D and spatial graph convolutional neural networks within an optimized quantum architecture. Simulation results demonstrate a 6% improvement in prediction accuracy relative to existing classical models, as well as a significantly more stable convergence performance compared to previous classical approaches.Comment: 5 pages, 3 figure

Discovery of a high-temperature antiferromagnetic state and transport signatures of exchange interactions in a Bi2Se3/EuSe heterostructure

Spatial confinement of electronic topological surface states (TSS) in topological insulators poses a formidable challenge because TSS are protected by time-reversal symmetry. In previous works formation of a gap in the electronic spectrum of TSS has been successfully demonstrated in topological insulator/magnetic material heterostructures, where ferromagnetic exchange interactions locally lifts the time-reversal symmetry. Here we report an experimental evidence of exchange interaction between a topological insulator Bi2Se3 and a magnetic insulator EuSe. Spin-polarized neutron reflectometry reveals a reduction of the in-plane magnetic susceptibility within a 2 nm interfacial layer of EuSe, and the combination of SQUID magnetometry and Hall measurements points to the formation of an antiferromagnetic layer with at least five-fold enhancement of N\'eel's temperature. Abrupt resistance changes in high magnetic fields indicate interfacial exchange coupling that affects transport in a TSS. High temperature local control of TSS with zero net magnetization unlocks new opportunities for the design of electronic, spintronic and quantum computation devices, ranging from quantization of Hall conductance in zero fields to spatial localization of non-Abelian excitations in superconducting topological qubits

Cognitive neuroscience of delusions in aging

Assessments and clinical understanding of late-onset delusions in the elderly are inconsistent and often incomplete. In this review, we consider the prevalence, neurobehavioral features, and neuroanatomic correlations of delusions in elderly persons – those with documented cognitive decline and those with no evidence of cognitive decline. Both groups exhibit a common phenotype: delusions are either of persecution or of misidentification. Late-onset delusions show a nearly complete absence of the grandiose, mystical, or erotomanic content typical of early onset psychoses. Absent also from both elderly populations are formal thought disorders, thought insertions, and delusions of external control. Neuroimaging and behavioral studies suggest a frontotemporal localization of delusions in the elderly, with right hemispheric lateralization in delusional misidentification and left lateralization in delusions of persecution. We propose that delusions in the elderly reflect a common neuroanatomic and functional phenotype, and we discuss applications of our proposal to diagnosis and treatment