Numerical Simulation for a Multidimensional Fourth-Order Nonlinear Fractional Subdiffusion Model with Time Delay

The purpose of this paper is to develop a numerical scheme for the two-dimensional fourth-order fractional subdiffusion equation with variable coefficients and delay. Using the L2 − 1σ approximation of the time Caputo derivative, a finite difference method with second-order accuracy in the temporal direction is achieved. The novelty of this paper is to introduce a numerical scheme for the problem under consideration with variable coefficients, nonlinear source term, and delay time constant. The numerical results show that the global convergence orders for spatial and time dimensions are approximately fourth order in space and second-order in time. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Acknowledgments: M.A.Z. wishes to acknowledge the support of Nazarbayev University Program 091019CRP2120 and the partial support of the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant “Dynamical Analysis and Synchronization of Complex Neural Networks with Its Applications”). M.A.Z. wishes also to acknowledge the financial support of the National Research Centre of Egypt (NRC)

An ethnomedicinal survey of traditionally used medicinal plants from Charkhi Dadri district, Haryana: an attempt towards documentation and preservation of ethnic knowledge

Medicinal plants have remained an integral source of therapeutics for primary healthcare since antiquity. The information pertaining to usage of plants is either inherited from elders or acquired through trials or the experience of others but is not documented frequently. South Haryana is one such rich storehouse of ethnomedicinal knowledge. Hence, ethnomedicinally important plants from Charkhi Dadri district of Haryana state were documented in the present study. The data was collected through field surveys and in-depth interviews organized in the fields during the years 2018-19. Factor of informant consensus was also calculated. A total of 90 ethnomedicinal plants were identified, belonging to 41 families and 79 genera. Majority of plants were herbs (47.7%), followed by trees (30%). Leguminosae (10%) represented the maximum number of plants, followed by Solanaceae (6.6% each) and Amaranthaceae, Lamiaceae and Poaceae (5.5% each). A total of 64 ailments were reported to be treated traditionally by ethnomedicinal plants in the area. The most commonly treated diseases were menorrhagia, skin boils, typhoid, diabetes, piles and diarrhoea. It was observed that the majority of plants were used freshly to extract juice, followed by powder and decoction and rarely as tea or oil forms. The present study provides comprehensive ethnomedicinal data including vernacular and botanical names, names of the family, mode of preparation, administration and dosage of plant drugs and diseases treated. It was concluded that this region still possesses numerous useful ethnomedicinal knowledge and may contribute to further herbal drug development programs

An ethnomedicinal survey of traditionally used medicinal plants from Charkhi Dadri district, Haryana: an attempt towards documentation and preservation of ethnic knowledge

436-450Medicinal plants have remained an integral source of therapeutics for primary healthcare since antiquity. The information pertaining to usage of plants is either inherited from elders or acquired through trials or the experience of others but is not documented frequently. South Haryana is one such rich storehouse of ethnomedicinal knowledge. Hence, ethnomedicinally important plants from Charkhi Dadri district of Haryana state were documented in the present study. The data was collected through field surveys and in-depth interviews organized in the fields during the years 2018-19. Factor of informant consensus was also calculated. A total of 90 ethnomedicinal plants were identified, belonging to 41 families and 79 genera. Majority of plants were herbs (47.7%), followed by trees (30%). Leguminosae (10%) represented the maximum number of plants, followed by Solanaceae (6.6% each) and Amaranthaceae, Lamiaceae and Poaceae (5.5% each). A total of 64 ailments were reported to be treated traditionally by ethnomedicinal plants in the area. The most commonly treated diseases were menorrhagia, skin boils, typhoid, diabetes, piles and diarrhoea. It was observed that the majority of plants were used freshly to extract juice, followed by powder and decoction and rarely as tea or oil forms. The present study provides comprehensive ethnomedicinal data including vernacular and botanical names, names of the family, mode of preparation, administration and dosage of plant drugs and diseases treated. It was concluded that this region still possesses numerous useful ethnomedicinal knowledge and may contribute to further herbal drug development programs

Contralateral asymmetry for breast cancer detection : A CADx approach

Early detection is fundamental for the effective treatment of breast cancer and the screening mammography is the most common tool used by the medical community to detect early breast cancer development. Screening mammograms include images of both breasts using two standard views, and the contralateral asymmetry per view is a key feature in detecting breast cancer. we propose a methodology to incorporate said asymmetry information into a computer-aided diagnosis system that can accurately discern between healthy subjects and subjects at risk of having breast cancer. Furthermore, we generate features that measure not only a view-wise asymmetry, but a subject-wise one. Briefly, the methodology co-registers the left and right mammograms, extracts image characteristics, fuses them into subjectwise features, and classifies subjects. In this study, 152 subjects from two independent databases, one with analog- and one with digital mammograms, were used to validate the methodology. Areas under the receiver operating characteristic curve of 0.738 and 0.767, and diagnostic odds ratios of 23.10 and 9.00 were achieved, respectively. In addition, the proposed method has the potential to rank subjects by their probability of having breas

COLOMBOS: Access Port for Cross-Platform Bacterial Expression Compendia

Background: Microarrays are the main technology for large-scale transcriptional gene expression profiling, but the large bodies of data available in public databases are not useful due to the large heterogeneity. There are several initiatives that attempt to bundle these data into expression compendia, but such resources for bacterial organisms are scarce and limited to integration of experiments from the same platform or to indirect integration of per experiment analysis results. Methodology/Principal Findings: We have constructed comprehensive organism-specific cross-platform expression compendia for three bacterial model organisms (Escherichia coli, Bacillus subtilis, and Salmonella enterica serovar Typhimurium) together with an access portal, dubbed COLOMBOS, that not only provides easy access to the compendia, but also includes a suite of tools for exploring, analyzing, and visualizing the data within these compendia. It is freely available at http://bioi.biw.kuleuven.be/colombos. The compendia are unique in directly combining expression information from different microarray platforms and experiments, and we illustrate the potential benefits of this direct integration with a case study: extending the known regulon of the Fur transcription factor of E. coli. The compendia also incorporate extensive annotations for both genes and experimental conditions; these heterogeneous data are functionally integrated in the COLOMBOS analysis tools to interactively browse and query the compendia not only for specific genes or experiments, but also metabolic pathways, transcriptional regulation mechanisms, experimental conditions, biological processes, etc. Conclusions/Significance: We have created cross-platform expression compendia for several bacterial organisms and developed a complementary access port COLOMBOS, that also serves as a convenient expression analysis tool to extract useful biological information. This work is relevant to a large community of microbiologists by facilitating the use of publicly available microarray experiments to support their research

CyclinPred: A SVM-Based Method for Predicting Cyclin Protein Sequences

Functional annotation of protein sequences with low similarity to well characterized protein sequences is a major challenge of computational biology in the post genomic era. The cyclin protein family is once such important family of proteins which consists of sequences with low sequence similarity making discovery of novel cyclins and establishing orthologous relationships amongst the cyclins, a difficult task. The currently identified cyclin motifs and cyclin associated domains do not represent all of the identified and characterized cyclin sequences. We describe a Support Vector Machine (SVM) based classifier, CyclinPred, which can predict cyclin sequences with high efficiency. The SVM classifier was trained with features of selected cyclin and non cyclin protein sequences. The training features of the protein sequences include amino acid composition, dipeptide composition, secondary structure composition and PSI-BLAST generated Position Specific Scoring Matrix (PSSM) profiles. Results obtained from Leave-One-Out cross validation or jackknife test, self consistency and holdout tests prove that the SVM classifier trained with features of PSSM profile was more accurate than the classifiers based on either of the other features alone or hybrids of these features. A cyclin prediction server- CyclinPred has been setup based on SVM model trained with PSSM profiles. CyclinPred prediction results prove that the method may be used as a cyclin prediction tool, complementing conventional cyclin prediction methods

Metallation and mismetallation of iron and manganese proteins in vitro and in vivo: the class I ribonucleotide reductases as a case study

How cells ensure correct metallation of a given protein and whether a degree of promiscuity in metal binding has evolved are largely unanswered questions. In a classic case, iron- and manganese-dependent superoxide dismutases (SODs) catalyze the disproportionation of superoxide using highly similar protein scaffolds and nearly identical active sites. However, most of these enzymes are active with only one metal, although both metals can bind in vitro and in vivo. Iron(II) and manganese(II) bind weakly to most proteins and possess similar coordination preferences. Their distinct redox properties suggest that they are unlikely to be interchangeable in biological systems except when they function in Lewis acid catalytic roles, yet recent work suggests this is not always the case. This review summarizes the diversity of ways in which iron and manganese are substituted in similar or identical protein frameworks. As models, we discuss (1) enzymes, such as epimerases, thought to use Fe[superscript II] as a Lewis acid under normal growth conditions but which switch to Mn[superscript II] under oxidative stress; (2) extradiol dioxygenases, which have been found to use both Fe[superscript II] and Mn[superscript II], the redox role of which in catalysis remains to be elucidated; (3) SODs, which use redox chemistry and are generally metal-specific; and (4) the class I ribonucleotide reductases (RNRs), which have evolved unique biosynthetic pathways to control metallation. The primary focus is the class Ib RNRs, which can catalyze formation of a stable radical on a tyrosine residue in their β2 subunits using either a di-iron or a recently characterized dimanganese cofactor. The physiological roles of enzymes that can switch between iron and manganese cofactors are discussed, as are insights obtained from the studies of many groups regarding iron and manganese homeostasis and the divergent and convergent strategies organisms use for control of protein metallation. We propose that, in many of the systems discussed, “discrimination” between metals is not performed by the protein itself, but it is instead determined by the environment in which the protein is expressed.National Institutes of Health (U.S.) (Grant GM81393

Effect of Silicon dioxide coating of acrylic resin surfaces on Candida albicans adhesion.

Acrylic resin has been used in the manufacture of prostheses, however, in the oral cavity, this material starts to retain microorganisms capable of causing gingival inflammation due its porosities. The aim of this study was to evaluate the influence of the use of silicon dioxide as a coating layer applied onto acrylic resin, on the adhesion of Candida albicans (Ca). After the incubation period in Sabouraud Dextrose Broth, a total of 1 ml of the Ca suspension was added to plate wells, each well containing a specimen of acrylic resin. The adhesion ability of Ca on acrylic resin was determined by counting colonies. Three groups (n = 6) of acrylic resin were assessed: with polishing (RP); without polishing (RW); with polishing and coating layer of silicon dioxide (RPC). Ca deposited on the surface of the acrylic resin was also observed using Scanning Electron Microscopy (SEM). Statistical assessment by Kruskal-Wallis and Student-Newman-Keuls Method were done (α = 2%). There was significant difference among the groups. The RPC group showed the lowest growth, with an average of 5.59 Log CFU/cm 2 ; there was a statistically significant difference in relation to group RW, which presented a growth of 6.07 Log CFU/cm 2 and to group RP with 5.91 Log CFU/cm 2 (p < 000.1). SEM images demonstrated that in the RP and RPC group, the surface of the resin had greater regularity, and smaller number of microorganisms. The application of silicon dioxide coating on acrylic resin appears to be a promising alternative, and its use can help in reducing the adhesion of Ca in prostheses