Innovative Fusion of Probiotics and Mouth Fresheners: Investigating Unaltered Growth, Microscopic Analysis, and Mucoadhesive Strength.

Since ancient times, mouth fresheners in many different forms have been used throughout the world. Traditional knowledge describes the health benefits of mouth fresheners, and contemporary science is now investigating their benefits. Claims have been made that mouth fresheners not only improve digestion but also promote oral health. Similar, but in a more profound sense, probiotics offer astounding advantages in treating many disorders. In certain cases, probiotics also offer prophylactic effects. Numerous benefits for dental health are being studied for B. coagulans (MB-BCM9) and B. subtilis (MB-BSM12). In this current study, a probiotic and a mouth freshener were combined to ameliorate the impacts of both. The oral residence of probiotics was enhanced by employing mucoadhesive polymers. Numerous compositions were developed and evaluated for the unaltered growth of probiotics, along with other evaluations like microscopy, in vitro mucoadhesive strength, and stability studies. Xanthan gum and hydroxypropyl methylcellulose were used in the development of mucoadhesive probiotic powder by employing the lyophilization technique. More than five hours of residence time were observed in the in vitro study with goat oral mucosa. The enumeration study validated the label claims of MB-BCM9 and MB-BSM12. It also concluded that none of the components of the formulation had a detrimental effect on probiotics. In essence, the present work discloses the novel and stable formulation of a probiotic-based mouth freshener.

DE-INTERACT: A machine-learning-based predictive tool for the drug-excipient interaction study during product development-Validation through paracetamol and vanillin as a case study.

The compatibility of drugs with excipients plays a crucial role in the prospective stability of pharmaceutical formulations. Apart from real-time stability studies, conventional analytical tools like DSC, FTIR, NMR, and chromatography help identify the possibilities of drug-excipient interactions. Machine learning can assist in developing a predictive tool for drug-excipient incompatibility. In the present work, PubChem Fingerprint is employed as the descriptor of compounds that thoroughly represents the drug's and excipient's chemistry. The 881-bit binary fingerprints of each drug and excipient make 1762 inputs, and one categorical output makes an instance in the dataset. A dataset of more than 3500 instances of drugs and excipients is carefully selected from peer-reviewed research papers. Rigorous training of the Artificial Neural Network (ANN) model was performed with maximum validation accuracy, minimum validation loss, and maximum validation precision as the checkpoints. The machine learning model (DE-Interact) was trained, achieving training and validation accuracies of 0.9930 and 0.9161, respectively. The performance of the DE-Interact model was evaluated by confirming three incompatible predictions by conventional analytical tools. Paracetamol with vanillin, paracetamol with methylparaben, and brinzolamide with polyethyleneglycol are these instances which are predicted as incompatible by the DE-Interact. DSC, FTIR, HPTLC, and HPLC analysis confirm the prediction. The present work offers a reliable DE-Interact tool for quick referencing while selecting excipients in formulation design.

Draft Genome Sequence of Weizmannia coagulans MB BCM9, a Stable Spore-Forming Probiotic.

Weizmannia coagulans MB BCM9 (MTCC 25157) is a safe probiotic strain. Here, we announce a fully assembled draft genome sequence consisting of 3,450,803 bp, with 139 contigs. A total of 3,377 protein-coding genes, 15 rRNAs, 80 tRNAs, 5 noncoding RNAs (ncRNAs), and 107 pseudogenes were identified from this assembly.

Probiotic Formulations: A Patent Landscaping Using the Text Mining Approach.

The outstanding research outcomes and registrations of myriads of probiotic strains have flooded the health market with various innovative probiotic-based products and their patents. The study of patented formulations of probiotics can give an overall insight into its existing application. A landscaping review of patents for probiotic-based preparations is presented in the current work. The patent search was performed over commercially available patent databased and analysis tool-PatSeer Pro®. Search strings containing words "Formulation" and "Composition" resulted in more than 3700 patents. Landscaping review of 400 + patents from the last 20 years (2000-2020) was performed using the Text-Mining approach. Text-Mining helped to identify 19 technological clusters which represent these patents. These clusters include the patents of probiotic preparations on animal feed, human food, cosmetics, antimicrobial, antidiabetic, arthritis, etc. A review of this massive number of patents unveiled many exciting preparations. Probiotic-based innovative products for depression, diabetes, Parkinson's, tumor, acne, and animal husbandry are reviewed comprehensively. The present work also unravels a few new-flanged products like probiotic layered condoms, products for acute alcoholism, and traditional Chinese medicine with probiotics. The patent landscape of probiotic-based preparations has presented a whole scenario of probiotic-based preparations. It has also revealed many unexplored areas where innovation can be excelled.

Review and Analysis of Massively Registered Clinical Trials of COVID-19 using the Text Mining Approach.

OBJECTIVE: Immediately after the outbreak of nCoV, many clinical trials are registered for COVID-19. The numbers of registrations are now raising inordinately. It is challenging to understand which research areas are explored in this massive pool of clinical studies. If such information can be compiled, then it is easy to explore new research studies for possible contributions in COVID-19 research. METHODS: In the present work, a text-mining technique of artificial intelligence is utilized to map the research domains explored through the clinical trials of COVID-19. With the help of the open-- source and graphical user interface-based tool, 3007 clinical trials are analyzed here. The dataset is acquired from the international clinical trial registry platform of WHO. With the help of hierarchical cluster analysis, the clinical trials were grouped according to their common research studies. These clusters are analyzed manually using their word clouds for understanding the scientific area of a particular cluster. The scientific fields of clinical studies are comprehensively reviewed and discussed based on this analysis. RESULTS: More than three-thousand clinical trials are grouped in 212 clusters by hierarchical cluster analysis. Manual intervention of these clusters using their individual word-cloud helped to identify various scientific areas which are explored in COVID19 related clinical studies. CONCLUSION: The text-mining is an easy and fastest way to explore many registered clinical trials. In our study, thirteen major clusters or research areas were identified in which the majority of clinical trials were registered. Many other uncategorized clinical studies were also identified as "miscellaneous studies". The clinical trials within the individual cluster were studied, and their research purposes are compiled comprehensively in the present work.

Author Correction: Whole exome sequencing reveals rare variants linked to congenital pouch colon.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Whole exome sequencing reveals rare variants linked to congenital pouch colon.

We demonstrate the application of whole exome sequencing to discover the rare variants for congenital pouch colon, acronymed CPC. For 18 affected individuals in a total of 64 samples, we sequenced coding regions to a mean coverage of 100×. A sufficient depth of ca. 94% of targeted exomes was achieved. Filtering against the public SNP/variant repositories, we identified a host of candidate genes, EPB41L4A and CTC1 associated with colon, neural/brain muscles and Dyskeratosis Congenita maladies. Furthermore, the stop gain mutations in the form of JAG1,OR5AR1,SLC22A24,PEX16,TSPAN32,TAF1B,MAP2K3 and SLC25A19 appears to be localized to Chromosomes 2, 11, 17 and 20 in addition to the three stop lost mutants across three genes, viz. OAS2, GBA3 and PKD1L2 affecting the colon tissue. While our results have paved way for transcendence of monogenic traits in identifying the genes underlying rare genetic disorders, it will provide helpful clues for further investigating genetic factors associated with anorectal anomalies, particularly CPC.

De novo Transcriptome Sequencing to Dissect Candidate Genes Associated with Pearl Millet-Downy Mildew (Sclerospora graminicola Sacc.) Interaction.

Understanding the plant-pathogen interactions is of utmost importance to design strategies for minimizing the economic deficits caused by pathogens in crops. With an aim to identify genes underlying resistance to downy mildew, a major disease responsible for productivity loss in pearl millet, transcriptome analysis was performed in downy mildew resistant and susceptible genotypes upon infection and control on 454 Roche NGS platform. A total of ~685 Mb data was obtained with 1 575 290 raw reads. The raw reads were pre-processed into high-quality (HQ) reads making to ~82% with an average of 427 bases. The assembly was optimized using four assemblers viz. Newbler, MIRA, CLC and Trinity, out of which MIRA with a total of 14.10 Mb and 90118 transcripts proved to be the best for assembling reads. Differential expression analysis depicted 1396 and 936 and 1000 and 1591 transcripts up and down regulated in resistant inoculated/resistant control and susceptible inoculated/susceptible control respectively with a common of 3644 transcripts. The pathways for secondary metabolism, specifically the phenylpropanoid pathway was up-regulated in resistant genotype. Transcripts up-regulated as a part of defense response included classes of R genes, PR proteins, HR induced proteins and plant hormonal signaling transduction proteins. The transcripts for skp1 protein, purothionin, V type proton ATPase were found to have the highest expression in resistant genotype. Ten transcripts, selected on the basis of their involvement in defense mechanism were validated with qRT-PCR and showed positive co-relation with transcriptome data. Transcriptome analysis evoked potentials of hypersensitive response and systemic acquired resistance as possible mechanism operating in defense mechanism in pearl millet against downy mildew infection.