Graphical Form Research Articles

PEPerMINT: peptide abundance imputation in mass spectrometry-based proteomics using graph neural networks.

Accurate quantitative information about protein abundance is crucial for understanding a biological system and its dynamics. Protein abundance is commonly estimated using label-free, bottom-up mass spectrometry (MS) protocols. Here, proteins are digested into peptides before quantification via MS. However, missing peptide abundance values, which can make up more than 50% of all abundance values, are a common issue. They result in missing protein abundance values, which then hinder accurate and reliable downstream analyses. To impute missing abundance values, we propose PEPerMINT, a graph neural network model working directly on the peptide level that flexibly takes both peptide-to-protein relationships in a graph format as well as amino acid sequence information into account. We benchmark our method against 11 common imputation methods on 6 diverse datasets, including cell lines, tissue, and plasma samples. We observe that PEPerMINT consistently outperforms other imputation methods. Its prediction performance remains high for varying degrees of missingness, different evaluation approaches, and differential expression prediction. As an additional novel feature, PEPerMINT provides meaningful uncertainty estimates and allows for tailoring imputation to the user's needs based on the reliability of imputed values. The code is available at https://github.com/DILiS-lab/pepermint.

Rheological analysis of pressure-driven Jeffrey fluid flow between corrugated porous curved walls with slip constraints

Pressure-driven movement is a fundamental concept with numerous applications in various industries, scientific disciplines, and fields of engineering. Its proper execution is vital for promoting revolutionary innovations and providing solutions in numerous sectors. Therefore, this article scrutinizes the pressure-driven flow of a magnetized Jeffrey fluid between two curved corrugated walls. The geometry of the channel is represented mathematically in an orthogonal curvilinear coordinate system. The corrugation grooves are described by sinusoidal functions with phase differences between the corrugated curved walls. The boundary perturbation method is used to find the analytical solution for the velocity and temperature taking the corrugation amplitude as the perturbation parameter. Furthermore, the volumetric flow rate, skin friction coefficient, and local Nusselt numbers are precisely calculated numerically for a variety of parameters, with the results presented comprehensively in tabular form. The impact of dissimilar parameters, such as the curvature parameter, wave number, magnetic parameter, Darcy number, thermal radiation, heat source/sink parameter, Jeffery fluid parameter, and amplitude parameter, on the flow fields is analyzed through graphical and tabular forms and discussed in detail. The results show that the velocity profile increases due to the curvature parameter and the Jeffrey fluid parameter. However, it decreases due to the magnetic parameter. The temperature distribution rises with the thermal slip and heat source/sink parameters. Meanwhile, it declined for the radiation parameter and the curvature parameter. The model can be used to simulate blood flow in arteries with varying geometries and magnetic fields, aiding in the study of cardiovascular diseases and the design of medical devices such as stents.

Practices and Barriers in Developing and Disseminating Plain-Language Resources Reporting Medical Research Information: A Scoping Review.

The intent of plain-language resources (PLRs) reporting medical research information is to advance health literacy among the general public and enable them to participate in shared decision-making (SDM). Regulatory mandates coupled with academic and industry initiatives have given rise to an increasing volume of PLRs summarizing medical research information. However, there is significant variability in the quality, format, readability, and dissemination channels for PLRs. In this scoping review, we identify current practices, guidance, and barriers in developing and disseminating PLRs reporting medical research information to the general public including patients and caregivers. We also report on the PLR preferences of these intended audiences. A literature search of three bibliographic databases (PubMed, EMBASE, Web of Science) and three clinical trial registries (NIH, EMA, ISRCTN registry) was performed. Snowball searches within reference lists of primary articles were added. Articles with PLRs or reporting topics related to PLRs use and development available between January 2017 and June 2023 were identified. Evidence mapping and synthesis were used to make qualitative observations. Identified PLRs were quantitatively assessed, including temporal annual trends, availability by field of medicine, language, and publisher types. A total of 9116 PLRs were identified, 9041 from the databases and 75 from clinical trial registries. The final analysis included 6590 PLRs from databases and 72 from registries. Reported barriers to PLR development included ambiguity in guidance, lack of incentives, and concerns of researchers writing for the general public. Available guidance recommendations called for greater dissemination, increased readability, and varied content formats. Patients preferred visual PLRs formats (e.g., videos, comics), which were easy to access on the internet and used short jargon-free text. In some instances, older audiences and more educated readers preferred text-only PLRs. Preferences among the general public were mostly similar to those of patients. Psychology, followed by oncology, showed the highest number of PLRs, predominantly from academia-sponsored research. Text-only PLRs were most commonly available, while graphical, digital, or online formats were less available. Preferred dissemination channels included paywall-free journal websites, indexing on PubMed, third-party websites, via email to research participants, and social media. This scoping review maps current practices, recommendations, and patients' and the general public's preferences for PLR development and dissemination. The results suggest that making PLRs available to a wider audience by improving nomenclature, accessibility, and providing translations may contribute to empowerment and SDM. Minimizing variability among available guidance for PLR development may play an important role in amplifying the value and impact of these resources.

Political economy analysis of health: a scoping review protocol.

The objective of this scoping review is to identify and map the literature on concepts, definitions, frameworks, outcomes, and applications of political economic analysis of health. The political economy of health approach seeks to understand how political and economic domains interact and shape individual and population health outcomes. A political economic analysis can provide insights into health problems and inequalities; however, there needs to be more clarity on how the political economy framework is defined and the methods adopted for conducting political economy analysis concerning health. Studies focusing on the political economy analysis addressing specific health problems will be included. The study population is not limited to any sociodemographic characteristics, and there will be no restrictions on language or the source of evidence (primary studies or secondary data studies). Both qualitative and quantitative methodologies will included, but narrative and systematic reviews will be excluded, as will conference abstracts and editorials. Studies involving sector- or country-level analysis will be included. The review will follow the JBI methodology for scoping reviews. Databases to be searched include MEDLINE, Scopus, Web of Science, Cochrane CENTRAL, CINAHL, Embase, ProQuest, DynaMed, and gray literature via Google Scholar and OAIster. Two reviewers will perform study screening and data extraction using a customized data extraction form. The concepts, definitions, frameworks, outcomes, and applications of the political economy of health will be summarized and discussed. The health problems addressed using political economy analysis will be enumerated. Stakeholder engagement will guide all steps of the study. Results will be presented in tabular and graphical formats accompanied by a narrative summary. Open Science Framework https://osf.io/4qaxr/.

Innovation in Bromelain Enzyme Production from Pineapple and Honey and Its Characteristics

Bromelain enzyme is one type of protease enzyme that has the ability to hydrolyze protein peptide bonds into amino acids. Bromelain enzyme can be found in pineapple (Ananas comosus) which consists of 95% cysteine protease mixture. Bromelain is often used by athletes to treat physical injuries or minor wounds. In obtaining the bromelain enzyme found in pineapple, an isolation process is required, namely by extracting it extracellularly. The method in this study does not go through the cell breakdown process so that it is easier to separate from other impurities and does not mix with other cell materials. This study aims to develop an innovative method in the production of bromelain enzyme using pineapple and honey as raw materials and to evaluate the organoleptic properties, pH, and the presence of lactic acid bacteria. This study is a descriptive study presented in the form of graphs and images. From the research that has been done, it can be concluded that the manufacture of bromelain enzyme using pineapple and honey has succeeded in producing a product that has an organoleptic value of liking (60%), pH 3 (acid) with the number of lactic acid bacteria 2.43 cells/ml.

STAGES OF TEACHING ELEMENTS OF STATISTICS IN ELEMENTARY SCHOOL

Mathematical statistics is one of the branches of mathematics, which is dedicated to the mathematical methods of organizing, processing and using statistical data for the purpose of scientific and practical conclusions. In practice, the methods of mathematical statistics are used in cases when it is necessary to examine a large amount of data according to a certain characteristic. Mathematical statistics is of great application importance in various spheres of human activity, so the study of the elements of this branch of mathematics is more than up-to-date. In order to study the elements of statistics at school, it is necessary to develop the following abilities among students: carry out simple surveys, collect quantitative data, and present them in the form of tables, graphs and diagrams. These abilities are suitable not only for the study of mathematics, but also for the study of other academic subjects, as well as in certain life situations. One of the main ideas fixed in the standard of the subject “Mathematics” is the analysis and interpretation of data, and its sub-idea is statistics, the study of which will be carried out in all three levels of education. The article presents the stages of learning the elements of mathematical statistics in elementary school, supported by many examples. All of this creates fertile ground for continued teaching of the elements of statistics in middle and high school.

Evaluation of The Studies on Unmanned Aircraft System Safety Management Systems with Bibliometric Analysis

UAV operations and their literature are developing rapidly. Along with the increasing number of risky situations, new technologies and measures are being developed to eliminate the unsafe situations created by them. Increasing UAVs have potential to lead to unsafe situations in airspace with incident and accident background. In addition to all other studies related to UAVs, studies on safety management systems, as well as other topics related to the safety management system, need to increase. In this study, a bibliometric analysis of the studies on UAVs between the years 2003-2022 was conducted from the perspective of safety management. For this purpose, the publications found in the Dimensions database were examined. Those publications related to UAVs were filtered according to certain criteria such as year, author, country, institution, and a sample was formed with 741 publications by using bibliometric analysis method. VOSViewer application was used for bibliometric analysis and the achieved data were visualized in the form of tables, graphics and visual maps. The findings show that the vast majority of publications on keywords were published in 2021. The most cited publication was written by Colomina and Molina in 2014. Most of the publications came up from the United States of America in total where 86 studies were conducted. The most cited organization is the University of Florida. In the cluster work, the words of remote sensing, sensor, and drones appear frequently.

SSGU-CD: A combined semantic and structural information graph U-shaped network for document-level Chemical-Disease interaction extraction

Document-level interaction extraction for Chemical-Disease is aimed at inferring the interaction relations between chemical entities and disease entities across multiple sentences. Compared with sentence-level relation extraction, document-level relation extraction can capture the associations between different entities throughout the entire document, which is found to be more practical for biomedical text information. However, current biomedical extraction methods mainly concentrate on sentence-level relation extraction, making it difficult to access the rich structural information contained in documents in practical application scenarios. We put forward SSGU-CD, a combined Semantic and Structural information Graph U-shaped network for document-level Chemical-Disease interaction extraction. This framework effectively stores document semantic and structure information as graphs and can fuse the original context information of documents. Using the framework, we propose a balanced combination of cross-entropy loss function to facilitate collaborative optimization among models with the aim of enhancing the ability to extract Chemical-Disease interaction relations. We evaluated SSGU-CD on the document-level relation extraction dataset CDR and BioRED, and the results demonstrate that the framework can significantly improve the extraction performance.

Radiative flow of clay nanoparticles on the lubricity of Williamson drilling fluids across a vertical surface in a Darcy-Brinkman porous medium

Drilling fluids are essential for extracting gases and oils from rocks and soil. To increase drilling fluid efficiency, clay nanoparticles are crucial. The use of clay particles in drilling fluids increases their thermal conductivity, viscosity, and boiling point, hence giving resilience to high temperatures and controlling fluid costs. Therefore, this research examines the convection radiative flow and heat transfer incorporated in the Williamson nanofluid with a heat source/sink. The effective thermophysical properties of clay nanofluid are represented quantitatively by using Maxwell-Garnett and Brinkman's formulas. The leading PDEs with physical boundary conditions that control the flow phenomena are predetermined. These PDEs are converted into ODEs using the similarity method, and dual solutions are then found by using an effective bvp4c solver. The effects of mixed convective, permeability, Williamson constraint, heat source/sink, nanoparticle volume fraction, and radiation parameters were all thoroughly studied quantitatively and theoretically. The Nusselt number and skin friction are calculated and displayed in tabular form as well as graphical form along with the velocity and temperature profiles. Multiple solutions are observed in the shrinkable sheet as well as the buoyancy assisting flow. The findings demonstrate that the Nusselt number rises noticeably when volume concentration increases. In addition, the permeability parameter expands the boundary layer thickness in the lower solution, while the contrary behavior is observed in the upper solution.

Numerical Solution of the Cauchy Problem for the Helmholtz Equation Using Nesterov’s Accelerated Method

In this paper, the Cauchy problem for the Helmholtz equation, also known as the continuation problem, is considered. The continuation problem is reduced to a boundary inverse problem for a well-posed direct problem. A generalized solution to the direct problem is obtained and an estimate of its stability is given. The inverse problem is reduced to an optimization problem solved using the gradient method. The convergence of the Landweber method with respect to the functionals is compared with the convergence of the Nesterov method. The calculation of the gradient in discrete form, which is often used in the numerical solutions of the inverse problem, is described. The formulation of the conjugate problem in discrete form is presented. After calculating the gradient, an algorithm for solving the inverse problem using the Nesterov method is constructed. A computational experiment for the boundary inverse problem is carried out, and the results of the comparative analysis of the Landweber and Nesterov methods in a graphical form are presented.

MeDaX: A Knowledge Graph on FHIR.

In Germany, the standard format for exchange of clinical care data for research is HL7 FHIR. Graph databases (GDBs), well suited for integrating complex and heterogeneous data from diverse sources, are currently gaining traction in the medical field. They provide a versatile framework for data analysis which is generally challenging for raw FHIR-formatted data. For generation of a knowledge graph (KG) for clinical research data, we tested different extract-transform-load (ETL) approaches to convert FHIR into graph format. We designed a generalised ETL process and implemented a prototypic pipeline for automated KG creation and ontological structuring. The MeDaX-KG prototype is built from synthetic patient data and currently serves internal testing purposes. The presented approach is easy to customise to expand to other data types and formats.

ANALYSIS OF MATHEMATICAL NUMERACY SKILLS ON LINE AND ANGLE MATERIAL IN CLASS VII IN TERMS OF EXTROVERTED INTROVERTED AND AMBIVERT PERSONALITIES

This research aims to analyze the mathematical numeracy abilities of class VII students with introverted, extroverted and ambivert personalities at SMP Negeri 2 Semarang. The method used was descriptive qualitative with research subjects consisting of 34 students, one student was selected from each personality category based on a questionnaire with 70 question items. The results of the questionnaire showed AAE (introvert), LPA (extrovert), and JRA (ambivert) students as research subjects. Mathematical numeracy ability tests and interviews were carried out to test the validity of the test results through technical triangulation. Indicators of mathematical numeracy abilities include the use of mathematical numbers and symbols, analysis of information in the form of tables, graphs and charts, as well as interpretation of analysis results for decision making. The results showed that introvert and ambivert students met all indicators of numeracy ability, while extrovert students did not. Introvert students can solve problems well, extrovert students tend to be in a hurry and lack details, while ambivert students show quite good results but there are still some answers that are less detailed. This research concludes that mathematical numeracy abilities vary based on student personality.

Genotype Representation Graphs: Enabling Efficient Analysis of Biobank-Scale Data.

Computational analysis of a large number of genomes requires a data structure that can represent the dataset compactly while also enabling efficient operations on variants and samples. Current practice is to store large-scale genetic polymorphism data using tabular data structures and file formats, where rows and columns represent samples and genetic variants. However, encoding genetic data in such formats has become unsustainable. For example, the UK Biobank polymorphism data of 200,000 phased whole genomes has exceeded 350 terabytes (TB) in Variant Call Format (VCF), cumbersome and inefficient to work with. To mitigate the computational burden, we introduce the Genotype Representation Graph (GRG), an extremely compact data structure to losslessly present phased whole-genome polymorphisms. A GRG is a fully connected hierarchical graph that exploits variant-sharing across samples, leveraging ideas inspired by Ancestral Recombination Graphs. Capturing variant-sharing in a multitree structure compresses biobank-scale human data to the point where it can fit in a typical server's RAM (5-26 gigabytes (GB) per chromosome), and enables graph-traversal algorithms to trivially reuse computed values, both of which can significantly reduce computation time. We have developed a command-line tool and a library usable via both C++ and Python for constructing and processing GRG files which scales to a million whole genomes. It takes 160GB disk space to encode the information in 200,000 UK Biobank phased whole genomes as a GRG, more than 13 times smaller than the size of compressed VCF. We show that summaries of genetic variants such as allele frequency and association effect can be computed on GRG via graph traversal that runs significantly faster than all tested alternatives, including vcf.gz, PLINK BED, tree sequence, XSI, and Savvy. Furthermore, GRG is particularly suitable for doing repeated calculations and interactive data analysis. We anticipate that GRG-based algorithms will improve the scalability of various types of computation and generally lower the cost of analyzing large genomic datasets.

The impact of study habits and personal factors on the academic achievement performances of medical students

BackgroundAcademic achievement is essential for all students seeking a successful career. Studying habits and routines is crucial in achieving such an ultimate goal.ObjectivesThis study investigates the association between study habits, personal factors, and academic achievement, aiming to identify factors that distinguish academically successful medical students.MethodsA cross-sectional study was conducted at the College of Medicine, King Saud University, Riyadh, Saudi Arabia. The participants consisted of 1st through 5th-year medical students, with a sample size of 336. The research team collected study data using an electronic questionnaire containing three sections: socio-demographic data, personal characteristics, and study habits.ResultsThe study results indicated a statistically significant association between self-fulfillment as a motivation toward studying and academic achievement (p = 0.04). The results also showed a statistically significant correlation between recalling recently memorized information and academic achievement (p = 0.05). Furthermore, a statistically significant association between preferring the information to be presented in a graphical form rather than a written one and academic achievement was also found (p = 0.03). Students who were satisfied with their academic performance had 1.6 times greater chances of having a high-grade point average (OR = 1.6, p = 0.08).ConclusionThe results of this study support the available literature, indicating a correlation between study habits and high academic performance. Further multicenter studies are warranted to differentiate between high-achieving students and their peers using qualitative, semi-structured interviews. Educating the students about healthy study habits and enhancing their learning skills would also be of value.

MIPDS: a comprehensive database on the molecular interactions in protein dimer structures

Although many studies have addressed the significance of interactions in the dimeric structures of proteins, there is no dedicated database of these interactions. To this end, the Molecular Interactions in Protein Dimer Structure (MIPDS) database has been developed; it is an open-access repository containing 60 298 3D structures of dimeric proteins sourced from the Protein Data Bank. This helps researchers comprehend the types of interaction, which include those mediated by water, small molecules or ligands and direct interactions, in 3D structures at the molecular level. The database is accessible through a user-friendly interface, where users can conduct searches based on PDB accession number, interaction type and geometric parameters. It can be viewed in textual and graphical formats using the plug-in JSmol. MIPDS is updated weekly using programmed scripts to incorporate newly released dimeric structures and analyses of their interaction types. The database is intended for the scientific community working in structural biology, structural bioinformatics, drug discovery and development. MIPDS is freely accessible to users worldwide at http://dicsoft1.physics.iisc.ac.in/mipds.

Fractional order forestry resource conservation model featuring chaos control and simulations for toxin activity and human-caused fire through modified ABC operator

In this work, we proposed a nonlinear mathematical model with fractional-order differential equations employed to illustrate the impacts of depleted forestry resources with the effect of toxin activity and human-caused fire. The numerical and theoretical outcomes are based on the consideration of using a modified ABC-fractional-order depleted forestry resources dynamical system. In the theoretical aspect, we examination of solution positivity, existence, and uniqueness it makes use of Banach’s fixed point and the Leray Schauder nonlinear alternative theorem. The consecutive recursive sequences are purposefully designed to verify the existence of a solution to the depletion of forestry resources as delineated. To showcase the specificity and stability of the solution within the Hyers–Ulam framework, we employ the concepts and findings of functional analysis. Chaos control will stabilize the system following its equilibrium points by applying the regulate for linear responses technique. Using Lagrange polynomials insight of modified ABC-fractional-order, we conduct simulations and present a comparative analysis in graphical form with classical and integer derivatives. Results also demonstrate the impact of different parameters used in a model that is designed on the system, they provide more understanding and a better approach for real-life problems. Our results demonstrate the significant effects of toxic and fire activities produced by humans on forest ecosystems. More accurate management techniques are made possible by the modified ABC operator’s effectiveness in capturing the long-term effects of these disturbances. The findings highlight how crucial it is to use fractional calculus in ecological modeling to comprehend and manage the intricacies of forest preservation in the face of human pressures. To ensure the sustainable management of forest resources in the face of escalating environmental difficulties, this research offers policymakers and environmental managers a fresh paradigm for creating more robust and adaptive conservation policies.

PREVALENCE OF SELF MEDICATION AMONG MBBS STUDENTS OF SHEIKH ZAYED MEDICAL COLLEGE, RAHIM YAR KHAN

Background: The prevalence of self-medication among medical students due to the virtue of their studying medicine is a significant issue. It can lead to various challenges including inappropriate symptom management and developing resistance to certain pharmaceutical drugs. Objective: The objective of this research was to determine the frequency of selfmedication among MBBS students of Sheikh Zayed Medical College Rahim Yar Khan. Methodology: The study design for this research was Cross-sectional study. The study was conducted at Sheikh Zayed Medical College, Rahim Yar Khan. Study subjects were five batches of MBBS within the age group of 19-25 and the duration was between August 15, 2023 to September 15, 2023. A sample size of 130 students were included in the study. Before the study, consent was taken from all subjects. The questionnaire was shared via WhatsApp groups to collect information with complete anonymity. The variables included age, gender, locality and questions were: involvement in self medication practice, frequency in the past one year, reasons, source of advice, illness, complaints for medication, adverse effects, and if they had stopped it and consulted a doctor. This data was entered on SPSS and results were obtained in textural, graphical and tabular form. Results: The study showed that among 130 medical students, 107 (82.3%) had self-medicated. 65.4% did it because it was convenient. The mean age was 21.29. The most common reason was headache (63.6%) and second most prevalent reason was sore throat (59.8%). Most students (69.2%) selected the medicine based on their own experience and 58.9% did on the basis of a previous prescription. Over half of the subjects (57%) stopped using the medication once the symptoms were alleviated. Most students (72%) never had any adverse effects from self-medication. Conclusion: The prevalence of self-medication in students at Sheikh Zayed Medical College, Rahim Yar Khan is high as 82.3% of students have self-medicated. The common reasons for self-medication are headache and sore throat. Almost one-half of students stopped using the medication with alleviation of symptoms. Most students never had any adverse effects from self-medication

A Clinicopathological Study of Parotid Gland Tumours

Abstract Background: The parotid gland is the largest salivary gland. Pleomorphic adenoma (PA) is the most common tumour found in the parotid gland. Most of the parotid tumours are painless and slow-growing. Ultrasound, computed tomography and magnetic resonance imaging are modalities of diagnosis. Fine-needle aspiration cytology (FNAC) is done in some cases, and its use is controversial. Aim: This clinicopathological study mainly aims at the demographic profile of the patient and clinical implications. Investigations were done and also evaluating the efficacy of FNAC in diagnosing parotid gland tumours. Materials and Methods: We conducted a prospective, hospital-based, observational study at our institution from December 2020 to June 2022. Forty patients who satisfied the inclusion and exclusion criteria were enrolled in the study. The study was analysed using SPSS version 25 developed by IBM. The categorical variables were presented as frequency and continuous data as mean, standard deviation (SD) and range with confidence interval. Categorical variables were compared using the Chi-square test; P <0.05 is considered significant. The sensitivity, specificity positive predictive value (PPV) and diagnostic accuracy of FNAC against the gold-standard histopathological examination (HPE) were worked out. The results are shown in tabular and graphical format. Results: The incidence of swelling was higher in males than females. Swelling was the most common clinical feature of the parotid gland. The duration of the disease ranges from ½to 48 months with an SD of 8.26 and a 95% confidence interval. One patient presented with facial nerve involvement and one patient presented with lymph node involvement. Five patients gave a history of surgery done in the past, which indicates recurrence, 10 (25%) patients were smokers and 1 (3%) patient had a history of previous radiation. Amongst the population of smokers, Warthin’s tumours were the most common (50%), PA (20%), oncocytic lipoadenoma, mucoepidermoid (MEP) carcinoma and myoepithelial (MyoEP) tumours having 10% incidence. The radiological findings were evaluated showing PA in 72.5% of cases, Warthin’s in 7.5%, neoplasm in 7.5% and non-specific cyst parotitis in 2.5% each. One patient image shows features of malignancy. FNAC says that 67.5% were PA, 20% were Warthin’s cyst and non-specific cyst, MEP and inflammation, but in one patient, FNAC was inconclusive. Most of the study population underwent superficial parotidectomy (32.5%); 30% of the study group underwent superficial conservative parotidectomy, but 27.5% of patients underwent total conservative parotidectomy. About 2.5% of the study group underwent extracapsular excision and enucleation. However, 2 (5%) patients were done with simple excision only. After surgery, out of 40, 38 patients had neuropraxia which recovered on follow-up. The most common tumour was PA (67.5%), and Warthin’s (22.5%) malignant tumours like MEP and MyoEP were 5% and 2.5%, respectively. Rare benign tumours like oncocytic lipoadenoma were the finding of HPE in FNAC that was inconclusive in this case. The incidence of malignant tumours was more common in males than in females, and it was more common in the age group of 21–40 years. MEP carcinoma was the most common malignant tumour. The efficacy of FNAC was identified in terms of sensitivity, specificity, negative predictive value (NPV), PPV and diagnostic accuracy. The sensitivity for benign tumours was 91.89% and that for malignant tumours was 33.33%. The specificity was 33.33% for benign tumours and 100% for malignant tumours respectively. The PPV was 94.44% for benign and 100% for malignant tumours. NPV was 25% and 94.87%, respectively. The diagnostic accuracy was 87.5% and 95%. Conclusion: Although FNAC has some pitfalls, the high sensitivity, specificity and accuracy in diagnosing malignant lesions as evident from this study indicate that FNAC is a reliable diagnostic method when correctly performed and interpreted by an experienced cytopathologist. Not all parotid lesions are lumps are malignant. Most of the masses are benign in nature. FNAC is a simple, safe, painless and cost-effective method for easy diagnosis.

Analysis of The Structural Embeddedness of a Scientific Research Laboratory’s Supplier Network

Objective: The objective of this research is to map a scientific research laboratory’s supplier network using Ucinet software and analyze its structural network. Theoretical Reference: Supply chain management is currently becoming increasingly important in companies as a decision-making strategy. The software tool based in Social Network Analysis (SNA) Ucinet allows modeling of a supply network based on its actors. By analyzing the supplier network, it is possible to identify opportunities for improvement that may not have been seen in previous diagnoses. Method: Data were collected using a questionnaire. Ucinet software and its integrated module NetDraw were used for data analysis, which allowed the data to be visualized in graphical format, to model the network and obtain structural indicators. Results: From the analysis of the supply network, improvements for the management of the laboratory’s logistics purchasing process were suggested. Implications of the research: The management of the laboratory’s logistics purchasing process helps researchers and managers and adjust its sizing parameters to the results obtained. Originality/Value: Ability to model the supplier network and obtain structural indicators, contributing to a better clarification of the exchange relationships between the authors.

ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities.

High-throughput technologies yield a broad spectrum of multi-omics datasets, which offer unparalleled insights into complex biological systems. However, effectively analyzing this diverse array of data presents challenges, considering factors such as species diversity, data types, costs, and limitations of the available tools. Herein, we present ExpOmics, a comprehensive web platform featuring 7 applications and 4 toolkits, with 28 customizable analysis functions spanning various analyses of differential expression, co-expression, Weighted Gene Co-expression Network Analysis (WGCNA), feature selection, and functional enrichment. ExpOmics allows users to upload and explore multi-omics data without organism restrictions, supporting various expression data, including genes, mRNAs, lncRNAs, miRNAs, circRNAs, piRNAs, and proteins and is compatible with diverse gene nomenclatures and expression values. Moreover, ExpOmics enables users to analyze 22427 transcriptomic datasets of 196 cancer subtypes sourced from 63 projects of The Cancer Genome Atlas Program (TCGA) to identify cancer biomarkers. The analysis results from ExpOmics are presented in high-quality graphical formats suitable for publication and are available for free download. A case study using ExpOmics identified two potential oncogenes, SERPINE1 and SLC43A1, that may regulate colorectal cancer through distinct biological processes. In summary, ExpOmics can serves as a robust platform for global researchers to explore multi-omics data, gain biological insights, and formulate testable hypotheses. ExpOmics is available at http://www.biomedical-web.com/expomics.