Artificial Intelligence (AI) and Nuclear Features from the Fine Needle Aspirated (FNA) Tissue Samples to Recognize Breast Cancer.

Breast cancer is one of the paramount causes of new cancer cases worldwide annually. It is a malignant neoplasm that develops in the breast cells. The early screening of this disease is essential to prevent its metastasis. A mammogram X-ray image is the most common screening tool practiced currently when this disease is suspected; all the breast lesions identified are not malignant. The invasive fine needle aspiration (FNA) of a breast mass sample is the secondary screening tool to clinically examine cancerous lesions. The visual image analysis of the stained aspirated sample imposes a challenge for the cytologist to identify the malignant cells accurately. The formulation of an artificial intelligence-based objective technique on top of the introspective assessment is essential to avoid misdiagnosis. This paper addresses several artificial intelligence (AI)-based techniques to diagnose breast cancer from the nuclear features of FNA samples. The Wisconsin Breast Cancer dataset (WBCD) from the UCI machine learning repository is applied for this investigation. Significant statistical parameters are measured to evaluate the performance of the proposed techniques. The best detection accuracy of 98.10% is achieved with a two-layer feed-forward neural network (FFNN). Finally, the developed algorithm's performance is compared with some state-of-the-art works in the literature.

Bioactive properties and gut microbiota modulation by date seed polysaccharides extracted using ultrasound-assisted deep eutectic solvent.

Polysaccharides are abundant macromolecules. The study extracted date seed polysaccharides (UPS) using ultrasound-assisted deep eutectic solvent extraction to valorize date seeds. UPS were subjected to comprehensive characterization and evaluation of their bioactivity, prebiotic properties, and their potential to modulate the gut microbiome. Characterization revealed UPS's heteropolysaccharide composition with galactose, mannose, fructose, glucose, and galacturonic acid respectively in 66.1, 13.3, 9.9, 5.4, and 5.1%. UPS showed a concentration-dependent increase of radical scavenging and antioxidant activities, evidenced by FRAP, TAC, and RP assays. They also displayed antimicrobial efficacy against E. coli O157:H7, S. typhimurium, S. aureus, and L. monocytogenes. Rheological analysis showed UPS's elastic-dominant nature with thixotropic tendencies. UPS inhibited α-glycosidase, α-amylase, and ACE up to 86%, and reduced Caco-2 and MCF-7 cell viability by 70% and 46%, respectively. UPS favored beneficial gut microbiota growth, releasing significant SCFAs during fecal fermentation.

Date fruit melanin is primarily based on (-)-epicatechin proanthocyanidin oligomers.

Plant-based melanin seems to be abundant, but it did not receive scientific attention despite its importance in plant biology and medicinal applications, e.g. photoprotection, radical scavenging, antimicrobial properties, etc. Date fruit melanin (DM) has complex, graphene-like, polymeric structure that needs characterization to understand its molecular properties and potential applications. This study provides the first investigation of the possible molecular composition of DM. High performance size-exclusion chromatography (HPSEC) suggested that DM contains oligomeric structures (569-3236 Da) and transmission electron microscopy (TEM) showed agglomeration of these structures in granules of low total porosity (10-1000 Å). Nuclear magnetic resonance (NMR) spectroscopy provided evidence for the presence of oligomeric proanthocyanidins and electron paramagnetic resonance (EPR) spectroscopy revealed a g-factor in the range 2.0034-2.005. Density functional theory (DFT) calculations suggested that the EPR signals can be associated with oligomeric proanthocyanidin structures having 4 and above molecular units of (-)-epicatechin. The discovery of edible melanin in date fruits and its characterization are expected to open a new area of research on its significance to nutritional and sensory characteristics of plant-based foods.

Exopolysaccharides from Enterococcus faecium and Streptococcus thermophilus: Bioactivities, gut microbiome effects, and fermented milk rheology.

Exopolysaccharides (EPSs) are carbohydrate polymers that can be produced from probiotic bacteria. This study characterized the EPSs from Enterococcus faecium (EPS-LB13) and Streptococcus thermophilus (EPS-MLB10) and evaluated their biological and technological potential. The EPSs had high molecular weight and different monosaccharide compositions. The EPSs exhibited various biological activities at 250 mg/L, such as scavenging free radicals (10 % to 88.8 %), enhancing antioxidant capacity (714 to 2848 µg/mL), inhibiting pathogens (53 % to 74 %), and suppressing enzymes and cancer cells (2 % to 83 %), etc. The EPSs supported the growth of beneficial gut bacteria from Proteobacteria, Bacteroidetes, Firmicutes, and Acinetobacter in fecal fermentation with total Short-chain fatty acids production from 5548 to 6023 PPM. Moreover, the EPSs reduced the gelation time of fermented skimmed bovine milk by more than half. These results suggest that the EPSs from LB13 and MLB10 have promising applications in the dairy and pharmaceutical industries.

Effect of whey protein isolate addition on set-type camel milk yogurt: Rheological properties and biological activities of the bioaccessible fraction.

The manufacture of camel milk (CM) yogurt has been associated with several challenges, such as the weak structure and watery texture, thereby decreasing its acceptability. Therefore, this study aimed to investigate the effect of whey protein isolate (WPI) addition on the health-promoting benefits, texture profile, and rheological properties of CM yogurt after 1 and 15 d of storage. Yogurt was prepared from CM supplemented with 0, 3, and 5% of WPI and compared with bovine milk yogurt. The results show that the water holding capacity was affected by WPI addition representing 31.3%, 56.8%, 64.7%, and 45.1% for yogurt from CM containing 0, 3 or 5% WPI, and bovine milk yogurt, respectively, after 15 d. The addition of WPI increased yogurt hardness, adhesiveness, and decreased the resilience. CM yogurt without WPI showed lower apparent viscosity, storage modulus, and loss modulus values compared with other samples. The supplementation of CM with WPI improved the rheological properties of the obtained yogurt. Furthermore, the antioxidant activities of yogurt before and after in vitro digestion varied among yogurt treatments, which significantly increased after digestion except the superoxide anion scavenging and lipid oxidation inhibition. After in vitro digestion at d 1, the superoxide anion scavenging of the 4 yogurt treatments respectively decreased from 83.7%, 83.0%, 79.1%, and 87.4% to 36.7%, 38.3%, 44.6%, and 41.3%. The inhibition of α-amylase and α-glucosidase, angiotensin-converting enzyme inhibition, cholesterol removal, and degree of hydrolysis exhibited different values before and after in vitro digestion.

An Update on Genetic Predisposition for Prostate Cancer: Perspectives and Prospects.

Prostate cancer (PC) is a heterogeneous disease that kills a significant number of people all over the world. It is the most common cancer in men, especially in the western world, and causes morbidity and mortality. There are several important risk factors known for PC like age, ethnicity, and inherited genetic variants which contribute significantly. The current research studies are endeavoring to identify genetic markers for PC and to understand underlying molecular mechanisms, so that new diagnostic and screening tests based on genetics can be developed for PC. The present review discusses candidate genes such as HOXB13, BRCA1, BRCA2, ATM, MMR gene, RAD51C, CHECK2, etc., and family-based linkage studies which defined the location of loci on chromosomal regions like 1q24-25, 1q42-43, Xq27-28, 1p36, 20q13, 17q21. Furthermore, the major part of the review focuses on important PC susceptible loci (8q24, 10q11, 17q12, 17q24, and 19q13, etc.) and risk variants identified by population-based genome-wide association studies (GWAS).

Simultaneous quantification of losartan potassium and its active metabolite, EXP3174, in rabbit plasma by validated HPLC-PDA.

Herein, we report a novel, accurate and cost-effective validated analytical method for the quantification of losartan potassium and its active metabolite, EXP 3174, in rabbit plasma by reversed-phase high-performance liquid chromatography. Valsartan was used as an internal standard. The method was validated as per International Conference on Harmonization guidelines. The analytes were extracted in rabbit plasma using liquid-liquid extraction technique and analyzed at 247 nm after separation through a reverse-phase C18 column. The isocratic mobile phase used is a mixture of acetonitrile, water and glacial acetic acid in the ratio of 60:40:1 v/v/v maintained at pH 3.4. All calibration curves showed a good linear relationship (r > 0.995) within the test range. Precision was evaluated by intra- and interday tests with RSDs <1.91% and accuracy showed validated recoveries of 86.20-101.11%. Based on our results, the developed method features good quantification parameters and can serve as an effective quality control method for the standardization of drugs.

Physicochemical, rheological, and bioactive properties of exopolysaccharide produced by a potential probiotic Enterococcus faecalis 84B.

Exopolysaccharides (EPS) have attracted a great interest due to their potential health-promoting properties and industrial applications. This study aimed to investigate the physicochemical, rheological, and biological properties of an EPS produced by a potential probiotic strain Enterococcus faecalis 84B. The results show that the extracted EPS, designated EPS-84B, had an average molecular weight of 604.8 kDa, particles size diameter of 322.0 nm, and mainly composed of arabinose and glucose with a molar ratio of 1:2. Furthermore, EPS-84B exhibited a shear-thinning behavior and had a high melting point. The rheological properties of EPS-84B were strongly influenced by the type of salt than by the pH value. EPS-84B displayed ideal viscoelastic properties, with both viscous and storage moduli increasing with frequency. The antioxidant activity of EPS-84B at a concentration of 5 mg/mL was 81.1 % against DPPH and 35.2 % against ABTS. At 5 mg/mL, the antitumor activity of EPS-84B against Caco-2 and MCF-7 cell lines was 74.6 and 38.6 %, respectively. In addition, the antidiabetic activity of EPS-84B towards α-amylase and α-glucosidase was 89.6 and 90.0 %, respectively at 100 µg/mL. The inhibition of foodborne pathogens by EPS-84B was up to 32.6 %. Overall, EPS-84B has promising properties that could be utilized in food and pharmaceutical industries.

Bioactive properties and untargeted metabolomics analysis of bioaccessible fractions of non-fermented and fermented date fruit pomace by novel yeast isolates.

In this study, attempts were made to utilize date by-product (date fruit pomace; DFP). This study aimed to investigate the health-promoting benefits of the fermented and non-fermented DFP before in vitro digestion and after (bioaccessible fraction). Untargeted metabolomic analyses for bioaccessible fractions were performed by UPLC-QTOF. DPPH percentages were 89.7%-90.3%, 90.1%-91.3%, and 90.8%-91.3% in the control, I. orientalis, and P. kudriazevii samples, respectively, before digestion; α-glucosidase inhibition before digestion was 1.9%-24.4%, 16.3%-30.0%, and 21.3%-31.3%, respectively; antimicrobial activities were 6.1%-13.3%, 13.7%-25.7%, and 20.6%-28.0% against E. coli O157:H7 and 2.2%-11.9%, 7.2%-20.7%, and 11.9%-29.2% against L. monocytogenes, respectively. The DPPH scavenging percentages were ∼63% lower in the bioaccessible fraction. The differentially regulated metabolites classes were benzene and derivatives, amino acids, peptides and analogs, organic acids, and phenols. This study revealed that the fermented DFP exhibited higher health properties than control.

A study of using cough sounds and deep neural networks for the early detection of Covid-19.

The current clinical diagnosis of COVID-19 requires person-to-person contact, needs variable time to produce results, and is expensive. It is even inaccessible to the general population in some developing countries due to insufficient healthcare facilities. Hence, a low-cost, quick, and easily accessible solution for COVID-19 diagnosis is vital. This paper presents a study that involves developing an algorithm for automated and noninvasive diagnosis of COVID-19 using cough sound samples and a deep neural network. The cough sounds provide essential information about the behavior of glottis under different respiratory pathological conditions. Hence, the characteristics of cough sounds can identify respiratory diseases like COVID-19. The proposed algorithm consists of three main steps (a) extraction of acoustic features from the cough sound samples, (b) formation of a feature vector, and (c) classification of the cough sound samples using a deep neural network. The output from the proposed system provides a COVID-19 likelihood diagnosis. In this work, we consider three acoustic feature vectors, namely (a) time-domain, (b) frequency-domain, and (c) mixed-domain (i.e., a combination of features in both time-domain and frequency-domain). The performance of the proposed algorithm is evaluated using cough sound samples collected from healthy and COVID-19 patients. The results show that the proposed algorithm automatically detects COVID-19 cough sound samples with an overall accuracy of 89.2%, 97.5%, and 93.8% using time-domain, frequency-domain, and mixed-domain feature vectors, respectively. The proposed algorithm, coupled with its high accuracy, demonstrates that it can be used for quick identification or early screening of COVID-19. We also compare our results with that of some state-of-the-art works.

Chest X-Ray Images to Differentiate COVID-19 from Pneumonia with Artificial Intelligence Techniques.

This paper presents an automated and noninvasive technique to discriminate COVID-19 patients from pneumonia patients using chest X-ray images and artificial intelligence. The reverse transcription-polymerase chain reaction (RT-PCR) test is commonly administered to detect COVID-19. However, the RT-PCR test necessitates person-to-person contact to administer, requires variable time to produce results, and is expensive. Moreover, this test is still unreachable to the significant global population. The chest X-ray images can play an important role here as the X-ray machines are commonly available at any healthcare facility. However, the chest X-ray images of COVID-19 and viral pneumonia patients are very similar and often lead to misdiagnosis subjectively. This investigation has employed two algorithms to solve this problem objectively. One algorithm uses lower-dimension encoded features extracted from the X-ray images and applies them to the machine learning algorithms for final classification. The other algorithm relies on the inbuilt feature extractor network to extract features from the X-ray images and classifies them with a pretrained deep neural network VGG16. The simulation results show that the proposed two algorithms can extricate COVID-19 patients from pneumonia with the best accuracy of 100% and 98.1%, employing VGG16 and the machine learning algorithm, respectively. The performances of these two algorithms have also been collated with those of other existing state-of-the-art methods.

Novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) and Other Coronaviruses: A Genome-wide Comparative Annotation and Analysis.

Novel strain of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) causes mild to severe respiratory illness. The early symptoms may be fever, dry cough, sour throat, and difficulty in breathing which may lead to death in severe cases. Compared to previous outbreaks like SARS-CoV and Middle East Respiratory Syndrome (MERS), SARS-CoV2 disease (COVID-19) outbreak has been much distressing due to its high rate of infection but low infection fatality rate (IFR) with 1.4% around the world. World Health Organization (WHO) has declared (COVID-19) a pandemic on March 11, 2020. In the month of January 2020, the whole genome of SARS-CoV2 was sequenced which made work easy for researchers to develop diagnostic kits and to carry out drug repurposing to effectively alleviate the pandemic situation in the world. Now, it is important to understand why this virus has high rate of infectivity or is there any factor involved at the genome level which actually facilitates this virus infection globally? In this study, we have extensively analyzed the whole genomes of different coronaviruses infecting humans and animals in different geographical locations around the world. The main aim of the study is to identify the similarity and the mutational adaptation of the coronaviruses from different host and geographical locations to the SARS-CoV2 and provide a better strategy to understand the mutational rate for specific target-based drug designing. This study is focused to every annotation in a comparative manner which includes SNPs, repeat analysis with the different categorization of the short-sequence repeats and long-sequence repeats, different UTR's, transcriptional factors, and the predicted matured peptides with the specific length and positions on the genomes. The extensive analysis on SNPs revealed that Wuhan SARS-CoV2 and Indian SARS-CoV2 are having only eight SNPs. Collectively, phylogenetic analysis, repeat analysis, and the polymorphism revealed the genomic conserveness within the SARS-CoV2 and few other coronaviruses with very less mutational chances and the huge distance and mutations from the few other species.

Erratum: Molecular docking and pharmacokinetic evaluation of natural compounds as targeted inhibitors against Crz1 protein in Rhizoctonia solani.

[This corrects the article on p. 227 in vol. 15, PMID: 31285645.].

Nanotechnology-based approaches in the fight against SARS-CoV-2.

The COVID-19 pandemic caused by highly-infectious virus namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in infection of millions of individuals and deaths across the world. The need of an hour is to find the innovative solution for diagnosis, prevention, and cure of the COVID-19 disease. Nanotechnology is emerging as one of the important tool for the same. In the present review we discuss the applications of nanotechnology-based approaches that are being implemented to speed up the development of diagnostic kits for SARS-CoV-2, development of personal protective equipments, and development of therapeutics of COVID-19 especially the vaccine development.

Receptor-based targeting of engineered nanocarrier against solid tumors: Recent progress and challenges ahead.

Background In past few decades, the research on engineered nanocarriers (NCs) has gained significant attention in cancer therapy due to selective delivery of drug molecules on the diseased cells thereby preventing unwanted uptake into healthy cells to cause toxicity. Scope of review The applicability of enhanced permeability and retention (EPR) effect for the delivery of nanomedicines in cancer therapy has gained limited success due to poor accessibility of the drugs to the target cells where non-specific payload delivery to the off target region lack substantial reward over the conventional therapeutic systems. Major conclusions In spite of the fact, nanomedicines fabricated from the biocompatible nanocarriers have reduced targeting potential for meaningful clinical benefits. However, over expression of receptors on the tumor cells provides opportunity to design functional nanomedicine to bind substantially and deliver therapeutics to the cells or tissues of interest by alleviating the bio-toxicity and unwanted effects. This critique will give insight into the over expressed receptor in various tumor and targeting potential of functional nanomedicine as new therapeutic avenues for effective treatment. General significance This review shortly shed light on EPR-based drug targeting using nanomedicinal strategies, their limitation, and advances in therapeutic targeting to the tumor cells.

Nanomedicinal strategies as efficient therapeutic interventions for delivery of cancer vaccines.

The applications of gene therapy-based treatment of cancers were started almost two decades back as a boon over the chemotherapeutic treatment strategies. Gene therapy helps in correcting the genetic sequences for treatment of cancers, thus also acts like a vaccine to induce the cellular and humoral immunity. However, the cancer vaccines typically suffer from a series of biopharmaceutical challenges due to poor solubility, low systemic availability and lack of targeting ability. Owing to these challenges, the physicians and pharmaceutical scientists have explored the applications of nanocarriers as quite promising systems for effective treatment against the tumors. A series of nanotherapeutic systems are available to date for diverse drug therapy applications. Systematic understanding on the preparation, evaluation and application of nanomedicines as a carrier system for delivering the cancer vaccines is highly important. The present review article provides an in-depth understanding on the challenges associated with cancer vaccine delivery and current opportunities with diverse nanomedicinal carriers being available for treatment of cancers.

From sequence analysis of DPP-4 to molecular docking based searching of its inhibitors.

Literature data suggests that Dipeptidyl peptidase-4 (DPP-4) is a potential target for type 2 Diabetes Mellitus. Therefore, it is of interest to identify new DPP-4 inhibitors using molecular docking analysis. We document compounds such as STOCK1N-98884, STOCK1N-98881, and STOCK1N-98866 with optimal binding features with DPP-4 from the ligand database at https://www.ibscreen.com/ for further consideration.

3D printing for drug delivery and biomedical applications.

Pharmaceutical product development is continuously witnessing innovations for the design of new delivery systems to improve the therapeutic efficacy of drugs. 3D-printing technology has been used to design customized personalized medication to provide maximal therapeutic benefits for patients. I addition, 3D printing has also been used to manufacture drug delivery systems and biomedical devices to establish a paradigm shift in the healthcare industry. In this review, we provide an update on current progress, technological gaps, and regulatory considerations in 3D-printing technology.