Effects of disulfiram on the metabolome of MRSA

Disulfiram, known as Antabuse®, is an oral drug for the treatment of alcohol dependence. Previous studies have indicated that disulfiram (DSF) exhibits antibacterial effects, particularly against Gram-positive bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA). Our study delves into the antibacterial mechanism of DSF in MRSA through High-Pressure Liquid Chromatography (HPLC) metabolomics, investigating the underlying mechanism of DSF effects on thiamine and amino acid metabolism. Thiamine pyrophosphate (TPP) plays a crucial role as a cofactor for critical enzymes such as transketolase, pyruvate dehydrogenase, and 2-oxoglutarate dehydrogenase. These enzymes are integral to the carbohydrate metabolism process within bacterial cells. TPP also contributes to coenzyme A (CoA) biosynthesis, identified as a prospective drug target for DSF in MRSA. Recent research highlighted DSF\u27s role in lowering intracellular CoA levels in MRSA, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways helped to uncover enriched genes related to the biosynthesis of TPP. Our transcriptome data further illuminated different amino acid metabolism shifts within DSF-treated MRSA. In-depth HPLC investigations utilized various methods to gauge TPP and amino acid levels in DSF-treated MRSA. These HPLC results effectively validated our hypothesis, confirming DSF\u27s influence on increasing cellular levels of TPP and amino acids like glutamate, glutamine, arginine, glycine, β-alanine, and lysine. Notably, our study also revealed diminished cellular levels of aspartate, valine, phenylalanine, and threonine. Our comprehensive study offers further insight on why DSF treatment alters TPP and select amino acid levels. These findings add to our understanding of DSF\u27s antibacterial mechanism in MRSA

Registration Management System for an Online Learning

As there are so many changes occurring in the current education system. If we see the last 2 years, most of the student community faced a lot of issues in attending classes. To overcome all those issues, all the educational organizations transformed their current manual teaching-learning system into an online learning system. Sudden transformation to an E-Learning system is creating issues like managing the students, schedules, communication, and other information. Keeping all this in mind, we want to manage all the student and teacher data with the help of automating the current manual system. To learn the courses online, educational institutes need to automate physical services. For doing this, a registration management system needs to be implemented. This registration system will be managing the data of students, teachers, course details, etc. For doing such operations the application will be categorizing the users into 3 types of students, teacher, and admin. The main objective of this application is to manage the student\u27s and teachers’ data. Students who want to learn need to register with the application and then they need to sign up. This will add security to the application and the student will be identified with the help of a username and password. All the personal information of students and teachers will be maintained, they will be given additional features like adding the details, updating the data, deleting the data, searching for the data, etc. Existing applications will not suit the requirements of our system, that is the reason a new application needs to be developed. As per the requirements of the application, the estimated project completion date is 12th December 2022

Influence of climate change on pavement design and materials in Canada

Anthropogenic climate change is having and will continue to have adverse effects on Canadian weather. Trends over the last 50 years elevate the rapid increase in number of the extreme event, the variations in temperature and precipitation, etc. The severe climatic variations in Canada are in line with global climate changes occurring due to increased greenhouse gas concentrations in the atmosphere. Under the current CO₂ emission scenarios, scientists predict that climate trends will further intensify in the near future. It is well known that asphalt pavements are highly sensitive to climate factors. Hence, reviewing both pavement design and materials while accounting climate change is a vital step that can help decelerate pavement deterioration. This study aims to quantify the impact of climate change on pavement performance, including revising pavement design and materials. To achieve this, the temperature and precipitation data were extracted from ten statistically downscaled climate change models, which were gathered from the pacific Canada Climate database. Also, the pavement materials, traffic, and structural data were collected from the Long-term Pavement Performance (LTPP) database. All these data were used in the Pavement Mechanistic-Empirical (ME) software to determine the pavement performance for both baseline and future climate. Various adaptation strategies such as upgrading asphalt binder grade, increasing the thickness of asphalt concrete layer, increasing the base layer thickness, and using stabilized base layers were analyzed to mitigate the climate change impact and to extend the service life of the pavement. All of these adaptation strategies are based on climate change data and its effect on pavement performance. It is also evident that selecting a climate-appropriate asphalt binder is essential in ensuring the longevity of pavement surfaces. As the selection methodology depends on the pavement's temperature, several models can predict pavement temperatures based on recorded ambient air temperatures and other related factors. A commonality between the most predominant pavement temperature models is the geographical limitations to their application. As a result, widely used models such as the Long-Term Pavement Performance (LTPP) and Strategic Highway Research Program (SHRP) do not return accurate values for more Northern temperatures such as those observed in Canada. Thus, a new pavement temperature model was developed for Canadian climatic conditions to determine the appropriate asphalt binder grade for future climate. In addition, Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA) were also carried out for all the alternatives to determine the CO₂ contributions to Canadian environment and changes in life cycle cost of Canadian pavement surfaces

GSUFC

GSUFC will be a web application to provide online membership to users and to enroll in different fitness classes. The application will handle the data with a real time database. The web application provides different types of memberships and the user can select a specific membership and get registered for the Fitness Center. The Fitness Center offers different classes and the cost of each class for the user depends on the membership purchased by user. User can view the classes in different sessions and can search for any particular class in a session. The user can view their registered classes and they can also renew his/her membership. The administrator for the application provides the information for the user. Administrator has the ability to add or edit existing classes, sessions, memberships

On Approximability of Steiner Tree in ℓp\ell_p-metrics

In the Continuous Steiner Tree problem (CST), we are given as input a set of points (called terminals) in a metric space and ask for the minimum-cost tree connecting them. Additional points (called Steiner points) from the metric space can be introduced as nodes in the solution. In the Discrete Steiner Tree problem (DST), we are given in addition to the terminals, a set of facilities, and any solution tree connecting the terminals can only contain the Steiner points from this set of facilities. Trevisan [SICOMP'00] showed that CST and DST are APX-hard when the input lies in the $\ell_1$-metric (and Hamming metric). Chleb\'ik and Chleb\'ikov\'a [TCS'08] showed that DST is NP-hard to approximate to factor of $96/95\approx 1.01$ in the graph metric (and consequently $\ell_\infty$-metric). Prior to this work, it was unclear if CST and DST are APX-hard in essentially every other popular metric! In this work, we prove that DST is APX-hard in every $\ell_p$-metric. We also prove that CST is APX-hard in the $\ell_{\infty}$-metric. Finally, we relate CST and DST, showing a general reduction from CST to DST in $\ell_p$-metrics. As an immediate consequence, this yields a $1.39$-approximation polynomial time algorithm for CST in $\ell_p$-metrics.Comment: Abstract shortened due to arxiv's requirement

ARTIFICIAL NEURAL NETWORKS: FUNCTIONINGANDAPPLICATIONS IN PHARMACEUTICAL INDUSTRY

Artificial Neural Network (ANN) technology is a group of computer designed algorithms for simulating neurological processing to process information and produce outcomes like the thinking process of humans in learning, decision making and solving problems. The uniqueness of ANN is its ability to deliver desirable results even with the help of incomplete or historical data results without a need for structured experimental design by modeling and pattern recognition. It imbibes data through repetition with suitable learning models, similarly to humans, without actual programming. It leverages its ability by processing elements connected with the user given inputs which transfers as a function and provides as output. Moreover, the present output by ANN is a combinational effect of data collected from previous inputs and the current responsiveness of the system. Technically, ANN is associated with highly monitored network along with a back propagation learning standard. Due to its exceptional predictability, the current uses of ANN can be applied to many more disciplines in the area of science which requires multivariate data analysis. In the pharmaceutical process, this flexible tool is used to simulate various non-linear relationships. It also finds its application in the enhancement of pre-formulation parameters for predicting physicochemical properties of drug substances. It also finds its applications in pharmaceutical research, medicinal chemistry, QSAR study, pharmaceutical instrumental engineering. Its multi-objective concurrent optimization is adopted in the drug discovery process, protein structure, rational data analysis also

Online Library Project

The main objective of this project is to provide the hand free access to the library portal through web interface. This project of “ONLINE LIBRARY” gives us the complete information about the library. We can enter the record of new books and retrieve the details of books available in the library. We can issue the books to the students and maintain their records and can also check how many books are issued and stock available in the library. In this project we can maintain the late fine of students who returns the issued books after the due date. Throughout the project the focus has been on making the students to grab the books of which they are in need with an exact details of the versions and editions of their respected volumes in an easy and intelligible manner. The project is very useful for those who want to know about online Library System

Clustering Categorical Data: Soft Rounding k-modes

Over the last three decades, researchers have intensively explored various clustering tools for categorical data analysis. Despite the proposal of various clustering algorithms, the classical k-modes algorithm remains a popular choice for unsupervised learning of categorical data. Surprisingly, our first insight is that in a natural generative block model, the k-modes algorithm performs poorly for a large range of parameters. We remedy this issue by proposing a soft rounding variant of the k-modes algorithm (SoftModes) and theoretically prove that our variant addresses the drawbacks of the k-modes algorithm in the generative model. Finally, we empirically verify that SoftModes performs well on both synthetic and real-world datasets