Product Database Research Articles

Machine learning method for cosmetic product recognition: a visual searching approach

A cosmetic product recognition system is proposed in this paper. For this recognition system, we have proposed a cosmetic product database that contains image samples of forty different cosmetic items. The purpose of this recognition system is to recognize Cosmetic products with there types, brands and retailers such that to analyze a customer experience what kind of products and brands they need. This system has various applications in such as brand recognition, product recognition and also the availability of the products to the vendors. The implementation of the proposed system is divided into three components: preprocessing, feature extraction and classification. During preprocessing we have scaled and transformed the color images into gray-scaled images to speed up the process. During feature extraction, several different feature representation schemes: transformed, structural and statistical texture analysis approaches have been employed and investigated by employing the global and local feature representation schemes. Various machine learning supervised classification methods such as Logistic Regression, Linear Support Vector Machine, Adaptive k-Nearest Neighbor, Artificial Neural Network and Decision Tree classifiers have been employed to perform the classification tasks. Apart from this, we have also performed some data analytic tasks for Brand Recognition as well as Retailer Recognition and for these experimentation, we have employed some datasets from the ‘Kaggle’ website and have obtained the performance due to the above-mentioned classifiers. Finally, the performance of the cosmetic product recognition system, Brand Recognition and Retailer Recognition have been aggregated for the customer decision process in the form of the state-of-the-art for the proposed system.

Functional group and diversity analysis of BIOFACQUIM: A Mexican natural product database.

Background: Natural product databases are important in drug discovery and other research areas. An analysis of its structural content, as well as functional group occurrence, provides a useful overview, as well as a means of comparison with related databases. BIOFACQUIM is an emerging database of natural products characterized and isolated in Mexico. Herein, we discuss the results of a first systematic functional group analysis and global diversity of an updated version of BIOFACQUIM. Methods: BIOFACQUIM was augmented through a literature search and data curation. A structural content analysis of the dataset was performed. This involved a functional group analysis with a novel algorithm to automatically identify all functional groups in a molecule and an assessment of the global diversity using consensus diversity plots. To this end, BIOFACQUIM was compared to two major and large databases: ChEMBL 25, and a herein assembled collection of natural products with 169,839 unique compounds. Results: The structural content analysis showed that 15.7% of compounds and 11.6% of scaffolds present in the current version of BIOFACQUIM have not been reported in the other large reference datasets. It also gave a diversity increase in terms of scaffolds and molecular fingerprints regarding the previous version of the dataset, as well as a higher similarity to the assembled collection of natural products than to ChEMBL 25, in terms of diversity and frequent functional groups. Conclusions: A total of 148 natural products were added to BIOFACQUIM, which meant a diversity increase in terms of scaffolds and fingerprints. Regardless of its relatively small size, there are a significant number of compounds and scaffolds that are not present in the reference datasets, showing that curated databases of natural products, such as BIOFACQUIM, can serve as a starting point to increase the biologically relevant chemical space.

Face mask designs following novel Coronavirus.

Doctors need to wear complete protective equipment when large numbers of patients flood into the emergency room. Taiwan has so far managed to prevent a large scale community outbreak, city forces wearing face masks on public transportation, and keep social distancing to stem the virus from spreading. The protective device may be contaminated and must be replaced. In the situation of limited resources, how to take care of the physiological needs of the doctor without increasing the chance of contamination during replacement is a consideration. By reducing the chance of contamination during removal and storage, the previous designs were analyzed and improved. We proposed three improved designs to reduce the contact. Design-A features a mask with a water channel that allows the user to remain hydrated without removing the cover. Design-B has a folding pattern that hides the outer surface. Design-C combines the mask with the brim of a cap which form an extended air-intake area. Through understanding the problem, related product began distribute on the market, Design-D extend the mask usages period with less contact.Significance for public healthWe demonstrated the potential for facemask contact to transmit viruses among staff and people. After an investigation of the existing product and patent database, we redesign the mask that could reduce contact transmission with a low-cost approach. Through understanding the problem, product-related improvements have already begun in the market, these designs also extend the mask usages period during daily work or a hospital visit. In this article we reviewed the process of finding problems and needs. Designers connect needs with product features through creativity. The process of exploring solutions requires a combination of domain knowledge.

Patterns of prescription medicine dispensing before and during pregnancy in New Zealand, 2005-2015.

ObjectiveTo describe prescription medicine dispensing before and during pregnancy in New Zealand, 2005–2015.MethodsMembers of the New Zealand Pregnancy Cohort were linked with their dispensing records in a national database of prescription products dispensed from community pharmacies. We identified the proportion of pregnancies during which at least one prescription medicine was dispensed, the number of different medicines used and the most commonly dispensed medicine groups both during pregnancy and in the 270 days before conception. Dispensing during pregnancy was assessed by several maternal characteristics.Results874,884 pregnancies were included. Over the study timeframe, the proportion of pregnancies exposed to a non-supplement prescription medicine increased from 38.5% to 67.2%. The mean number of different non-supplement medicines dispensed during pregnancy increased from 2.5 to 3.2. Dispensing during pregnancy was weakly associated with body mass index, smoking status and ethnicity. Pregnancy exposure was highest for Antibacterials (26.0%), Analgesics (16.7%) and Antinausea & Vertigo Agents (11.0%).ConclusionsFrom 2005–2015, both the proportion of exposed pregnancies and the number of different medicines dispensed to pregnant women in New Zealand increased.

Pepper Auction Market Development Strategy in Sleman Regency

The pepper auction market in Sleman Regency was formed in 2017. This market is becoming the main marketing line for all pepper traders in Sleman Regency because it is serving appropriate prices for the farmer. Some problems also appeared during the implementation of the pepper auction market. This study aimed to arrange an effective strategy in developing a pepper auction market in Sleman Regency. This study conducted from January to February 2020 involving 23 major traders who chosen by the census method and 6 stakeholders who chosen by purposive sampling technique. SWOT analysis was applied to arrange an effective strategy in developing the pepper auction market. The result showed that the most effective strategy used in developing the pepper auction market was the SO-Strategy, such as: improving product quantity and quality, improving the quality of services and creating good relationships with the assembly point management party and auction participants, and building an online product and price database system. The auction market management parties and some stakeholders are required to regularly monitor and assure the market system in conducting a market auction process appropriately. We also suggested to use modern technology devices to assure the auction transparency.

Characterizing Ingredients in Baked Products Sold in the U.S.

Abstract Objectives To develop a dataset of top ingredients used in baked products and to examine the scope of use of emulsifiers, leavening agents and sweeteners (nutritive and non-nutritive) in baked products. Methods We identified top-selling baked products using 2016 Information Resources Inc. market share data, and obtained ingredient lists for the top-selling products from the publicly available USDA Global Branded Food Products Database and manufacturer's websites. Individual ingredients were then parsed using a custom program in R, a statistical computing language. We performed several pre-processing steps before parsing, as ingredient lists were inconsistent and varied. For example, the additive Azodicarbonamide is listed in 9 different ways including spelling errors. We then reviewed the parsed ingredients reported more than once, to identify terms which were equivalent, such as synonyms, spelling and usage variants, common names, possible errors etc., and assigned a preferred descriptor and its technical use (eg. emulsifiers, leavening agents, sweeteners etc.). Results For the 4 baked product food categories, there are over 40,000 products available, of which ingredient lists were obtained for ∼79% of the total volume sold. These baked products use ∼6000 uniquely described ingredients (as listed on the labels). Preliminary results from grouping based on technical use shows, for example, ∼60 kinds of sweeteners were used; top nutritive sweeteners: sucrose, dextrose, high fructose corn syrup; top non-nutritive sweeteners: sucralose, stevia extract, Reb-A. Conclusions The ingredient dataset for baked products provides insight into ingredients used in commercially packaged baked products. This information can also be used to prioritize ingredients for which food composition data are needed and help in the development of computer programs and Artificial Intelligence tools. Funding Sources None.

Structural dynamic studies on identification of EGCG analogues for the inhibition of Human Papillomavirus E7

High risk human papillomaviruses are highly associated with the cervical carcinoma and the other genital tumors. Development of cervical cancer passes through the multistep process initiated from benign cyst to increasingly severe premalignant dysplastic lesions in an epithelium. Replication of this virus occurs in the fatal differentiating epithelium and involves in the activation of cellular DNA replication proteins. The oncoprotein E7 of human papillomavirus expressed in the lower epithelial layers constrains the cells into S-phase constructing an environment favorable for genome replication and cell proliferation. To date, no suitable drug molecules exist to treat HPV infection whereas anticipation of novel anti-HPV chemotherapies with distinctive mode of actions and identification of potential drugs are crucial to a greater extent. Hence, our present study focused on identification of compounds analogue to EGCG, a green tea molecule which is considered to be safe to use for mammalian systems towards treatment of cancer. A three dimensional similarity search on the small molecule library from natural product database using EGCG identified 11 potential small molecules based on their structural similarity. The docking strategies were implemented with acquired small molecules and identification of the key interactions between protein and compounds were carried out through binding free energy calculations. The conformational changes between the apoprotein and complexes were analyzed through simulation performed thrice demonstrating the dynamical and structural effects of the protein induced by the compounds signifying the domination. The analysis of the conformational stability provoked us to describe the features of the best identified small molecules through electronic structure calculations. Overall, our study provides the basis for structural insights of the identified potential identified small molecules and EGCG. Hence, the identified analogue of EGCG can be potent inhibitors against the HPV 16 E7 oncoprotein.

Well productivity in the Ponta Grossa dike Swarm, Brazil: An integrated study with magnetic data inversion and clustering analysis of model solutions

Dike swarms are mega-structures observed in different geological contexts which may affect groundwater flow systems. These structures are well recognizable from airborne magnetic, however it is difficult to obtain quantitative information about distribution and mean properties of dikes that generate the observed magnetic anomalies. This work presents a procedure to perform magnetic data inversion along profiles transecting the Ponta Grossa Dike Swarm (PGDS) and determine its mean properties with application of cluster analysis to obtained solutions. Next, the mean model solutions are correlated with a regional database of borehole productivity suggesting that more productive wells are found close to a group of shallow dikes of the PDGS in Southeastern Brazil. For the area mainly composed by sedimentary rocks, the wells situated over shallow dikes show higher values of specific capacity by a factor of 14.5 than those not close to a dike in the same domain. For the area mainly composed by granitic rocks, the productivity of wells over dikes is still higher, a factor of 4.3 higher than those with no dikes. A conceptual model is presented to explain the higher productivity of wells close to the dikes, as resulting from fracturing on host rock caused by dikes emplacement. Only a group of shallow dikes seems to be associated with more productive wells.

Study of trends and mapping of drought events in Tunisia and their impacts on agricultural production

The objective of this research is to explore spatial extent and temporal pattern of historical droughts and their impacts on agricultural production in Tunisia. This contribution was based on monthly rainfall series recorded from September 1973 to August 2016 in 16 main meteorological stations in Tunisia. The Standardized Precipitation Index (SPI), the Reconnaissance Drought Index (RDI) and the annual Potential Evapotranspiration (PET) were computed and used to characterize the gravity of climatic events and their spatial and temporal variations. A database of strategic crop productions and Agricultural Gross Domestic Product (AGDP) variation has been collected from FAO's official website.Based on SPI and RDI, strongly correlated indices (R = 0.99; p < .05), it is demonstrated that Tunisia has experienced several multi-year droughts (3 to 7 years) with different severities. During 1981, Tunisia suffered a generalized drought. However during 1996, severe to extreme humidity was observed over 70% of Tunisian territory (SPI and RDI values >1.5). Series of normal or near-normal years were recorded during 50% of the study period. Variation in cereal production showed the strongest correlation with RDI (RWheat/RDI = 0.66), followed by olive oil (ROlive.Oil/ RDI = 0.45) and citrus fruits (RCitrus/RDI = 0.43). The outputs of this research could be useful for main stakeholders to identify compromised measure (subsidies, insurance) improving management of agricultural activities to mitigate drought impacts at farm level and over production zones.

Discovery of Natural Product Compounds as Dengue Virus NS5 Methyltransferase Inhibitor Candidate through in Silico Method

Dengue is a global health problem which predominantly affected the tropical and subtropical region of Asia, Africa, and America. However, there are no available antiviral agents to treat dengue virus (DENV) infection. This study was conducted to utilize natural product compounds as an inhibitor of NS5 Methyltransferase, a viral protein which plays an essential role in the synthesis of DENV RNA. The natural product compounds were collected from the Universal Natural Product Database (UNPD), totaling 229,000 compounds. The in silico screening of the natural product compounds was performed by molecular docking simulation method, which simulates the interaction of the compounds on the active site of the NS5 methyltransferase. From the molecular docking simulation, about 51 compounds showed better affinity and interaction compared to the standard compound, S-Adenosyl-L-Homocysteine (SAH). Then, a series of pharmacological tests were performed to find the best drug candidates by employing DataWarrior and SwissADME software. Finally, three natural product compounds, namely UNPD98966, UNPD183023, and UNDP104952, were regarded as the best inhibitor against NS5 methyltransferase based on its molecular affinity and interaction. These compounds also showed potential as drug candidates due to their desirable pharmacological properties.

Metabolomics-Guided Isolation of Anti-Trypanosomal Compounds from Endophytic Fungi of the Mangrove plant Avicennia Lanata.

Endophytic fungi have been explored not just for their ecological functions but also for their secondary metabolites as a new source of these pharmacologically active natural products. Accordingly, many structurally unique and biologically active compounds have been obtained from the cultures of endophytic fungi. Fusarium sp. and Lasiodiplodia theobromae were isolated from the root and stem of the mangrove plant Avicennia lanata, respectively, collected from Terengganu, Malaysia. High-resolution mass spectrometry and NMR spectroscopy were used as metabolomics profiling tools to identify and optimize the production of bioactive secondary metabolites in both strains at different growth stages and culture media. The spectral data was processed by utilizing Mzmine 2, a quantitative expression analysis software and an in house MS-Excel macro coupled with the Dictionary of Natural Products databases for dereplication studies. The investigation for the potential bioactive metabolites from a 15-day rice culture of Fusarium sp. yielded four 1,4- naphthoquinone with naphthazarin structures (1-4). On the other hand, the endophytic fungus L. theobromae grown on the 15-day solid rice culture produced dihydroisocoumarins (5-8). All the isolated compounds (1-8) showed significant activity against Trypanosoma brucei brucei with MIC values of 0.32-12.5 µM. Preliminary cytotoxicity screening against normal prostate cells (PNT2A) was also performed. All compounds exhibited low cytotoxicity, with compounds 3 and 4 showing the lowest cytotoxicity of only 22.3% and 38.6% of the control values at 100 µg/mL, respectively. Structure elucidation of the isolated secondary metabolites was achieved using 2D-NMR and HRESI-MS as well as comparison with literature data.

Vocal tract shaping of emotional speech

Emotional speech production has been previously studied using fleshpoint tracking data in speaker-specific experiment setups. The present study introduces a real-time magnetic resonance imaging database of emotional speech production from 10 speakers and presents articulatory analysis results of speech emotional expression using the database. Midsagittal vocal tract parameters (midsagittal distances and the vocal tract length) were parameterized based on a two-dimensional grid-line system, using image segmentation software. The principal feature analysis technique was applied to the grid-line system in order to find the major movement locations. Results reveal both speaker-dependent and speaker-independent variation patterns. For example, sad speech, a low arousal emotion, tends to show smaller opening for low vowels in the front cavity than the high arousal emotions more consistently than the other regions of the vocal tract. Happiness shows significantly shorter vocal tract length than anger and sadness in most speakers. Further details of speaker-dependent and speaker-independent speech articulation variation in emotional expression and their implications are described.

Structure-based virtual screening of natural products as potential stearoyl-coenzyme a desaturase 1 (SCD1) inhibitors

Stearyl coenzyme A desaturase enzyme 1 (SCD1) is a key enzyme that catalyzes the conversion of saturated fatty acids (SFA) into monounsaturated fatty acids (MUFA) and plays a vital role in lipid metabolism of tumor cells. SCD1 is overexpressed in a variety of malignant tumors, and its related inhibitors showed significant anti-tumor activity in vitro and in vivo experiments, which is a new target for tumor therapy. The focus of this study is to identify novel SCD1 inhibitors from natural products through computer simulations. First, 176,602 compounds from natural product databases were virtually screened. By molecular dynamics (MD) simulations, the ligand-protein interactions of 5 compounds with high docking manifestation were analyzed accurately. Then, MM-GBSA and MM-PBMA methods were used to verify the results. Finally, ADMET prediction was performed for the 5 compounds. As a result, two natural products with potential inhibition towards SCD1 were identified, which had the excellent docking manifestation, binding mode within SCD1 pocket and stability during molecular dynamics simulation. This study provides a meaningful model for the development and optimization of new inhibitors and anti-tumor drugs targeting SCD1.

Coeficiente de repetibilidade para produção de frutos e seleção de matrizes de &lt;i&gt;Bertholletia excelsa&lt;/i&gt; (Bonpl.) em castanhais nativos do estado do Acre

Mais de 95% da produção brasileira de castanha-da-amazônia é oriunda da coleta extrativista sendo poucos os plantios para produção comercial. Buscando contribuir com informações básicas para o melhoramento genético da castanheira, este estudo teve por objetivos: estimar os coeficientes de repetibilidade para o número de frutos (NFP); determinar o número adequado de medições para uma eficiente seleção de matrizes; e, selecionar castanheiras promissoras em dois castanhais nativos, no Estado do Acre. O estudo foi realizado em parcelas permanentes no Filipinas (Resex Chico Mendes, Epitaciolândia-AC) e Cachoeira (PAE Chico Mendes, Xapuri-AC). O número de frutos por planta (NFP) foi avaliado em 140 castanheiras no Filipinas, no período de 2002 a 2014 (13 anos), enquanto no Cachoeira foram 175 castanheiras de 2009 a 2014 (seis anos). As análises genético-estatísticas foram feitas com base na metodologia de modelos mistos, utilizando-se o software Selegen-REML/BLUP, Modelo 63. Foram selecionadas 20 matrizes, sendo 08 no Filipinas e 12 no Cachoeira. Em ambos os castanhais, a variância fenotípica permanente (Vfp) representou a maior porcentagem da variância fenotípica individual (Vf). O coeficiente de repetibilidade foi considerado moderado para o Cachoeira e alto para o Filipinas. Considerando um coeficiente de determinação de 90%, seriam necessários sete anos de avaliação do NFP para o Cachoeira e seis anos para o Filipinas. O banco de dados existentes para a produção de frutos das castanheiras é suficiente para se realizar a seleção de matrizes com alta produção de frutos. Com base nos valores estimados espera-se que a nova população apresente uma produção média de 465,3 frutos.arv-1, indicando um ganho na produção de frutos cerca de 2,4 vezes para o Cachoeira e 4,2 para o Filipinas.

A Design of New Product Database System for Supporting Step-Compliant Total Integration Applications

Computer technology has become a very important element in an advanced manufacturing system. The good and systematic data model for the exchange of manufacturing information between different stages of development of product life cycle is paramount to ensure the product is manufactured and delivered to the market successfully. As a result, ISO 10303, an international standard, or well known as Standard for Exchange of Product Model Data (STEP) is not just for providing a neutral data format within the heterogenous CAD systems, its functionality has extended to the whole life cycle of product. STEP Part 21 is the first implementation method from EXPRESS modelling language and implemented successfully as neutral product data to integrate heterogeneous CAD platform. However, this CAD STEP Part21 text file is hardly to be applied in manufacturing processes since it consists of purely geometrical and topological data. In this research, a nonprocedural approach is presented to translate the EXPRESS language model of STEP CAD data into a new product database system model. A new nonprocedural approach of data enrichment and automated machining feature recognition is proposed and implemented on this newly developed product database system and provide a solution for the interrelated tasks of automated machining feature recognition: (1) extraction of geometrical feature from STEP CAD model data of the part (2) formation of part representation suitable for form feature identification (3) matching of form features. This paper proves the validity of this newly developed product database system by translating STEP Part21 file from a commercial CAD system to database system format, data enrichment, performing automated machining feature recognition and lastly generating STEP standard data according to AP224 for supporting STEP based process planning and manufacturing applications.

Hybrid Data Protection Framework to Enhance A2O Functionality in Production Database Virtualization

Deluge of information flows in the unprecedented scenario of smart city development trend, hence prone to issues on stability, reliability and availability. Smart data storage resources are vulnerable to provide functionality Always Available Online (A2O) due to their inherent heavy dependence on System Down Time (SDT), Redundant Systems and Software Failure (RS2F) or whole/ multiple site failures. In the absence of Production Database Management Services (PDMS), duplicate deployment of similar data on disjoint but similar architecture provides a Tightly Coupled Ultimate System (TCUS), which assures A2O mutually exclusive services. In this paper, we investigated active Data Guard (aDG) and Data Guard (DG) role management or switchover for a real time transition performed for database at standby state to cope up both planned maintenance and accidental RS2F events. We expose our results for deep integration of aDGs with ODB in-terms of Fast Sync to align synchronously at an ease of zero of wait states for disk I/O and configurability to Null Data Loss (NDL). Over a large range of remote or standby databases NDL make it certain to zero failover. The impact of aDG Fast-Start Failover in the cloud proximity make sure guaranteed NDL in synchronously and near NDL protection asynchronously. Hence, avoids unusual overhead impeding disk I/O and eventually on a primary database. We observe the key performance indicator in failover does not restart the standby database for primary role resumption, but introduce cloud proximity as a new primary database and the process is performed without any intervention of manual migration. The reliability of aDG Redo is flexible across not only standby databases but also primary sites running different operating system over diverse hardware platforms. The Redo capability enables migration with minimal downtime for any transaction in the clouds, therefore adds an inevitable functionality to big data applications.

Pharmacophore and Molecular Docking-Based Virtual Screening of B-Cell Lymphoma 2 (BCL 2) Inhibitor from Zinc Natural Database as Anti-Small Cell Lung Cancer

Cancer is a disease involving genetic factors in its pathogenesis. The increase of cell survival as a result of genetic changes, which prevent apoptosis such as Bcl2 (B-cell lymphoma-2) activation, will cause the tumor to grow. The overexpression of Bcl2 in small cell lung cancer should be inhibited. This study aims to screen natural products that can inhibit Bcl2 overexpression in lung cancer using pharmacophore- and molecular docking-based virtual screening to ZINC Natural Product database. The validation of pharmacophore-based virtual screening to the three features of the pharmacophore model (2 hydrophobic interactions and 1 hydrogen bond donor) showed that the AUC, EF, Se, Sp, ACC, and GH values were 0.57, 3.8, 0.101, 0.957, 0.936, and 0.149, respectively. On the other hand, the validation of molecular docking-based virtual screening showed that the RMSD values of Vina Wizard and AutoDock Wizard were 1.3Å and 1.9Å, respectively. The pharmacophore model virtual screening first obtained 6,615 compounds, and then the molecular docking-based virtual screening finally gained 255 compounds whose values of ΔG and Ki were lower than those of the native ligand. It was concluded that the virtual screening could yield as many as 255 potential anti-lung cancer drug candidates.&#x0D; Keywords: B-cell lymphoma 2 inhibitors, molecular docking, pharmacophore modeling, virtual screening

METHDOS OF EFFECTIVE DESIGN FOR CREATING OF PARAMETRIC 3D-MODELS OF PRODUCTS USING THE INTERNAL CAPABILITIES OF CAD-PROGRAMS

It is known that the development of a three-dimensional parametric model is a creative process, since the same 3D-model can be built in various ways. In the article the methods for effective design of parametric 3D-models with the help of internal capabilities of CAD-program without the use of programming languages (macros) is developed. Using the methods and recommendations discussed in the article on the example of Autodesk Inventor functionality will allow the engineer to design parametric three-dimensional products in CAD-programs in the most rational way, reducing the number of errors. Recommendations for effective control of 3D-model parameters during creating of Assembly parts and 2D-drawings are given. Using the functionality discussed in the article will be useful for engineers using parametric modeling methods to create typical products, optimization and analysis of structures, development of their own database of standard products that are not in the library of CAD-program components.

Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods

SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.

IDISK: the integrated DIetary Supplements Knowledge base.

To build a knowledge base of dietary supplement (DS) information, called the integrated DIetary Supplement Knowledge base (iDISK), which integrates and standardizes DS-related information from 4 existing resources. iDISK was built through an iterative process comprising 3 phases: 1) establishment of the content scope, 2) development of the data model, and 3) integration of existing resources. Four well-regarded DS resources were integrated into iDISK: The Natural Medicines Comprehensive Database, the "About Herbs" page on the Memorial Sloan Kettering Cancer Center website, the Dietary Supplement Label Database, and the Natural Health Products Database. We evaluated the iDISK build process by manually checking that the data elements associated with 50 randomly selected ingredients were correctly extracted and integrated from their respective sources. iDISK encompasses a terminology of 4208 DS ingredient concepts, which are linked via 6 relationship types to 495 drugs, 776 diseases, 985 symptoms, 605 therapeutic classes, 17 system organ classes, and 137568 DS products. iDISK also contains 7 concept attribute types and 3 relationship attribute types. Evaluation of the data extraction and integration process showed average errors of 0.3%, 2.6%, and 0.4% for concepts, relationships and attributes, respectively. We developed iDISK, a publicly available standardized DS knowledge base that can facilitate more efficient and meaningful dissemination of DS knowledge.