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Triazines are six-membered privileged scaffolds that have been explored in drug discovery programs owing to their stability in biological media and robust reactivity. Their unique chemical properties have led to the exploration of the triazine-containing molecules for multifaceted disorders like Alzheimer's disease (AD). The pathology of AD involves the interplay of multiple biochemical events such as amyloid beta-aggregation, formation of reactive oxygen species, cholinergic degradation, and metal ion dysregulation. The growing incidence of AD, coupled with the limited availability of efficacious medicines, necessitates the identification of newer therapeutic approaches. Privileged scaffolds like triazines with the potential for multiple biological effects offer excellent alternatives to the treatment of multifactorial AD. The present review describes numerous triazine-containing molecules capable of modulating single as well as multiple pathological factors involved in AD. The analysis of structural features of these molecules can provide useful insights for developing newer therapies.

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Deep learning models in healthcare may fail to generalize on data from unseen corpora. Additionally, no quantitative metric exists to tell how existing models will perform on new data. Previous studies demonstrated that NLP models of medical notes generalize variably between institutions, but ignored other levels of healthcare organization. We measured SciBERT diagnosis sentiment classifier generalizability between medical specialties using EHR sentences from MIMIC-III. Models trained on one specialty performed better on internal test sets than mixed or external test sets (mean AUCs 0.92, 0.87, and 0.83, respectively; p = 0.016). When models are trained on more specialties, they have better test performances (p < 1e-4). Model performance on new corpora is directly correlated to the similarity between train and test sentence content (p < 1e-4). Future studies should assess additional axes of generalization to ensure deep learning models fulfil their intended purpose across institutions, specialties, and practices.

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Alzheimer's disease (AD) is a progressive neurodegenerative disorder primarily caused by accumulation of amyloid-beta (Aß) peptide extracellularly and neurofibrillary tangles intracellularly. Recently, it has been shown that oxidative stress and mitochondrial dysregulation play an important role in pathology of AD. Therefore, modulating various targets such as Aß aggregation, neuro-inflammation, and oxidative stress, genetic factors such as Apolipoprotein E gene (ApoE) are some of the ways to manage AD. Studying the natural products which can act as multifunctional agents could be key toward discovering new therapeutics. Ferulic acid (FA) represents one such natural product, which has exhibited great potential in this regard. Found in the plant cell walls, FA is an antioxidant, free radical scavenger with anti-inflammatory activity. Taking this into consideration, over the years, various derivatives have been reported as anti-AD molecules based on structure of FA. The present review explores the role of FA and its derivatives as therapeutic agents in AD.

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With the increasing number of cases of latent and drug resistant tuberculosis, there is an urgent need to develop new, potent molecules capable of combating this deadly disease. Molecules containing oxadiazoles are one such class that could be considered to fulfil this need. Oxadiazole regioisomers have been explored in drug discovery programs for their ability to act as effective linkers and also as pharmacophoric features. Oxadiazoles can act as bioisosteric replacements for the hydrazide moiety which can be found in first line anti-TB drugs, and some have been also reported to interact with newer anti-TB targets. In this context, the present review describes the potential of oxadiazoles as antituberculosis agents.

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We report design of a series of 2,4-diamino triazines as Mycobacterium tuberculosis (Mtb) dihydrofolate reductase inhibitors. The synthesized compounds were evaluated against Mtb (H37Rv and Dormant stage H37Ra), their cytotoxicity was assessed (HepG2 and A549 cell lines), and selectivity toward Mtb was evaluated by testing against other bacterial strains. Some derivatives showed promising activity along with low cytotoxicity. The most potent compound in the whole cell assay (MIC 0.325 µM against H37Rv) showed selectivity in the enzyme assay and exhibited synergy with second line anti-TB agent p-amino salicylic acid. This study therefore provides promising molecules for further development as antituberculosis DHFR inhibitors.

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With the view of exploring phytochemicals as Mycobacterium tuberculosis (Mtb) dihydrofolate reductase inhibitors, known plant polyphenols from various classes were subjected to detailed docking studies. From this in-silico screening, seven polyphenols were selected and tested against Mtb H37 Rv in whole cell assays. The phytochemicals exhibited potential activity ranging from 3 to 183 µm. These molecules were then tested against the pathogenic and human enzymes in a high-throughput microtitre assay. Epigallocatechin gallate showed the best activity and selectivity. The in-silico analysis was in agreement with the assay results. Of these 7 polyphenols, 5 exhibiting minimum inhibitory concentration values of ≤15 µm were tested for synergistic activity with first line drug Ethambutol and second line folate inhibitor para-amino salicylic acid. Epigallocatechin gallate, Magnolol and Bakuchiol exhibited moderate synergistic association by lowering the minimum inhibitory concentration of these drugs. These simple phytochemicals could hence be considered as leads for further studies, or for preparation of semi-synthetic derivatives to be used in combination therapy, for increased anti-tuberculosis activity after validation in-vivo.

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