GAN-Based Approaches for Generating Structured Data in the Medical Domain

Modern machine and deep learning methods require large datasets to achieve reliable and robust results. This requirement is often difficult to meet in the medical field, due to data sharing limitations imposed by privacy regulations or the presence of a small number of patients (e.g., rare diseases). To address this data scarcity and to improve the situation, novel generative models such as Generative Adversarial Networks (GANs) have been widely used to generate synthetic data that mimic real data by representing features that reflect health-related information without reference to real patients. In this paper, we consider several GAN models to generate synthetic data used for training binary (malignant/benign) classifiers, and compare their performances in terms of classification accuracy with cases where only real data are considered. We aim to investigate how synthetic data can improve classification accuracy, especially when a small amount of data is available. To this end, we have developed and implemented an evaluation framework where binary classifiers are trained on extended datasets containing both real and synthetic data. The results show improved accuracy for classifiers trained with generated data from more advanced GAN models, even when limited amounts of original data are available

KARTIRANJE LISKUNASTE ŽELJEZNE RUDE I IZRADA PRIMJENJIVIH INDUSTRIJSKIH STANDARDA

The purpose of this study is to determine the appropriate method for micaceous iron ore processing and production per-industrial application standards. After identifying the characteristics of the samples (with XRF, XRD, mineralogical analyzes), gravity and magnetic separation tests were carried out. Quartz and hematite are the main minerals of micaceous hematite ores. Silica grade as the major impurity varies from 10% to 68%. The total iron content of the samples also varies from 15% to 62%. A jig and shaking table did not provide a good result in micaceous hematite beneficiation to achieve the standard of its specific applications. Gravity concentration by the spiral in the size range of -200 and -300 μm has led to the production of iron concentrates with a grade of 62.34% and 64.84%, respectively. The recovery values for the two experiments are 13.50% and 12.60%, respectively. Therefore, the spiral did not provide a good result in the micaceous iron ore beneficiation. High-intensity magnetic separation (1.2 T) has resulted in a product with a grade and recovery of 65.98% and 88.35%, respectively. The experimental design utilizing the Taguchi method considering the increasing of grade or recovery priority indicated that for micaceous iron beneficiation with a priority of recovery increasing, the feeder frequency, roll speed, and adjustable gate angle should be at 6.5 Hz, 95 rpm, and 20°, respectively. However, for micaceous iron beneficiation with a priority of grade increasing, the feeder frequency, roll speed, and adjustable gate angle should be at 2.5 Hz, 135 rpm, and 60°, respectively.Svrha je ovoga istraživanja odrediti prikladnu metodu za oplemenjivanje liskunaste željezne rude te izrada standarda primjenjivih u industriji. Nakon utvrđivanja karakteristika uzoraka (s XRF, XRD, mineraloškim analizama) provedena su ispitivanja gravitacijskom i magnetskom separacijom. Kvarc i hematit glavni su minerali liskunastih hematitnih ruda. Udio silicija kao glavne nečistoće varira od 10 % do 68 %. Ukupni sadržaj željeza u uzorcima također varira od 15 % do 62 %. Plakalica i koncentracijski stol nisu dali dobre rezultate u obogaćivanju liskunastoga hematita za postizanje standar-da njegove specifične primjene. No, gravitacijska koncentracija spiralom veličine zrna -200 i -300 μm rezultirala je kvali-tetom koncentrata željeza od 62,34 odnosno 64,84 %. Vrijednosti iskorištenja bile su 13,50 odnosno 12,60 %. Stoga ni spirala nije dala dobar rezultat u obogaćivanju liskunaste željezne rude. Visokointenzivna magnetska separacija (1,2 T) rezultirala je kvalitetom koncentrata od 65,98 % i iskorištenjem od 88,35 %. Eksperimentalni dizajn prema Taguchiju s obzirom na povećanje kvalitete ili iskorištenja pokazao je da za povećanje iskorištenja frekvencija dodavača, brzina bub-nja i kut separacijskoga noža trebaju biti na 6,5 Hz, 95 o/min i 20°. Međutim, za obogaćivanje liskunaste željezne rude s prioritetom povećanja kvalitete koncentrata frekvencija dodavača, brzina bubnja i kut separacijskoga noža trebaju biti 2,5 Hz, 135 o/min, odnosno 60°

TP53 Mutations and HBX Status Analysis in Hepatocellular Carcinomas from Iran: Evidence for Lack of Association between HBV Genotype D and TP53 R249S Mutations

High incidence of HCC is mostly due to the combination of two major risk factors, chronic infection with hepatitis B (HBV) and/or C (HCV) viruses and exposure to the mycotoxin aflatoxin B1, which induces a particular mutation at codon 249 in TP53 (R249S). Eight genotypes of HBV are diversely found in high and low incidence areas. Regardless of documented strong associations between TP53 R249S mutation and HBV genotypes B, C, A or E, there is no report of such association for genotype D despite of the presence of aflatoxin in areas with high prevalence of HBV genotype D. In Iran, 3% of the population is chronically infected with HBV, predominantly genotype D. Twenty-one histologically confirmed HCC cases from Iran were analyzed for TP53 R249S and HBV double mutations 1762T/1764A, hallmarks of more pathogenic forms of HBV. We did not detect any of these mutations. In addition, we report the only case identified so far carrying both R249S mutation and chronic HBV genotype D, a patient from The Gambia in West Africa. This paper suggests that association between HBV genotype D and aflatoxin-induced TP53 mutation is uncommon, explaining the relatively lower incidence of HCC in areas where genotype D is highly prevalent

A Monte Carlo study for optimizing the detector of SPECT imaging using a XCAT human phantom

BACKGROUND: Acquiring a high quality image has assigned an important concern for obtaining accurate diagnosis in nuclear medicine. Detector is a critical component of Single Photon Emission Computed Tomography (SPECT) imaging system for giving accurate information from exact pattern of radionuclide distribution in the target organ. The images are strongly affected by the attenuation, scattering, and response of the detector. The conventional detector is mainly made from sodium iodide activated by thallium [NaI(Tl)] in nuclear medicine imaging. The aim of the study. This study has planned to introduce a suitable for an optimized SPECT imaging. SIMIND Monte Carlo program was utilized for simulating a SPECT imaging system with a NaI(Tl) detector, and a low-energy high-resolution (LEHR) collimator. MATERIAL AND METHODS: The Planar and SPECT scans of a 99mTc point source and also an extended Cardiac-Torso (XCAT) computerized phantom with the experiment and simulated systems were prepared. After verification and validation of the simulated system, the similar scans of the phantoms were compared from the point of view of image quality for 7 scintillator crystals including: NaI(Tl), BGO, YAG:Ce, YAP:Ce, LuAG:Ce, LaBr3 and CZT. The parameters of energy and spatial resolution, and sensitivity of the systems were compared. Images were analyzed quantitatively by SSIM algorithm with Zhou Wang and Rouse/Hemami methods, and also qualitatively by two nuclear medicine specialists. RESULTS: Energy resolutions of the mentioned crystals obtained were: 9.864, 9.8545, 10.229, 10.221, 10.230, 10.131and10.223 percentage for 99mTc photopeak 140 Kev, respectively. Finally, SSIM indexes for the related phantom images were calculated to 0.794, 0.738, 0.735, 0.607, 0.760 and 0.811 compared to the NaI(Tl) acquired images, respectively. Medical diagnosis of the SPECT images of the phantom showed that the system with BGO crystal potentially provides a better detectability for hot and cold lesions in the liver of XCAT phantom. CONCLUSIONS: The results showed that BGO crystal has a high sensitivity and resolution, and also provides a better lesion detectability from the point of view of image quality on XCAT phantom

Investigation of the Potential Presence of Porphyromonas gingivalis in Esophageal Squamous Cell Carcinoma (ESCC) Paraffin Embedded Tissue Samples

Background and Aim: Esophageal cancer is the eighth most common cancer and the sixth leading cause of cancer death worldwide Evidence suggests that there is a link between bacterial infection and malignancy. There are few studies on the prevalence of Porphyromonas gingivalis in esophageal squamous cell carcinoma (ESCC), so this study aimed to investigate the possible presence of this bacterium in ESCC tissue samples.Materials and Methods: In this study, 34 esophageal squamous cell carcinoma samples were collected to evaluate the potential presence of Porphyromonas gingivalis. After extracting the DNA, the polymerase chain reaction (PCR) technique was used to detect the presence of the bacterium molecularly.Results: The age range of the study population was 26 to 90 years, with a mean age of 63 years. Most tissue samples come from stage I cancer (73.5%). Based on the molecular analysis, no P. gingivalis was detected in any biopsy specimensConclusion: P. gingivalis infection and ESCC were not correlated based on the current in this study. Likely, the use of fresh samples, more accurate diagnostic methods, geographic differences, and larger sample sizes all contribute to the differences in results between related research, which can be clarified through large-scale studies

Geoelectrical characterization of a landslide surface for investigating hazard potency, a case study in the Tehran- North freeway, Iran

Landslide, as a geohazard issue, causes enormous threats to human lives and properties. In order to characterize the subsurface prone to the landslide which is occurred in the Tehran-North freeway, Iran, a comprehensive study focused on geological field observations, and a geoelectrical survey as a cost-effective and fast, non-invasive geophysical measurement was conducted in the area. As a result of road construction, problems in this region have increased. The Vertical Electrical Sounding (VES) investigation in the landslide area has been carried out by the Schlumberger array for data acquisition, implementing eight survey profiles varying in length between 60 and 130 m. Based on the electrical resistivity models through a smoothness-constrained least-square inversion methodology, the landslide structure (i.e., depth of the mobilized material and potential sliding surface) is better defined. The inferred lithological units, accompanied by stratigraphical data from a borehole and geological investigations for the prone landslide region, consisted of a discontinuous slip surface, having a wide range of resistivity, observed to be characterized by tuff with silt. Electrical resistivity values above 150 Ωm indicate a basement of weathered marlstone and sand. Values between 15 and 150 Ωm illustrate a shale-content layer with outcrops in the area that is the reason for movement. The sliding surface is at a depth of about 12 m. The method used in this study is a good candidate to investigate the risk of landslides in this region and can be applied to other landslide areas where borehole exploration is inefficient and expensive due to local complications

Antibiotic Resistance and RAPD-PCR Genotyping of Pseudomonas aeruginosa Clinical Strains Isolated from Intensive Care Unit Patients

Background: Pseudomonas aeruginosa is one the most important nosocomial pathogens, especially in immunocompromised patients. Identifying the source of contamination in health centers plays an important role in the control of hospital infections. The aim of this study was to determine antibiotic susceptibility and genetic patterns of P. aeruginosa isolated from patients hospitalized in intensive care unit of Masih Daneshvari Hospital, Tehran, Iran. Materials and Methods: Antibiotic susceptibility of the isolates was examined through 10 antibiotics recommended by Clinical and Laboratory Standards Institute (CLSI, 2018) guidelines using the Kirby-Bauer disc diffusion method. Random amplified polymorphic DNA (RAPD) analysis with the short primer of 272 was used to evaluate genetic relationship among the isolates and the results were analyzed by Gelcompar II software. Results: Of the antibiotics used, the most sensitive was found in colistin (96.4%) and the highest resistance rates were observed in cefotaxime (94.6%), chloramphenicol (83.9%) and imipenem (71.4%). DNA fingerprinting was able to identify 12 genetic patterns by RAPD-PCR technique. Conclusion: Antibiotic resistance in isolates of P. aeruginosa is rising and there is possibility of occurring outbreaks in the medical centers. Different sources of strains show their constant exchange via intra- and extra-hospital transmission routes. Thus, according to the data of this study, there is a serious need to control sources of infections by physicians and staff when they are working in several sectors to control and prevent the transmission of the bacterium

Machine Learning Made Easy (MLme): A Comprehensive Toolkit for Machine Learning-Driven Data Analysis.

BACKGROUND Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills. Furthermore, users are required to engage in the comprehensive configuration of their ML pipeline to obtain optimal performance. RESULTS To address these challenges, we have developed a novel tool called Machine Learning Made Easy (MLme) that streamlines the use of ML in research, specifically focusing on classification problems at present. By integrating four essential functionalities, namely Data Exploration, AutoML, CustomML, and Visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. To demonstrate the applicability of MLme, we conducted rigorous testing on six distinct datasets, each presenting unique characteristics and challenges. Our results consistently showed promising performance across different datasets, reaffirming the versatility and effectiveness of the tool. Additionally, by utilizing MLme's feature selection functionality, we successfully identified significant markers for CD8+ naive (BACH2), CD16+ (CD16), and CD14+ (VCAN) cell populations. CONCLUSION MLme serves as a valuable resource for leveraging machine learning (ML) to facilitate insightful data analysis and enhance research outcomes, while alleviating concerns related to complex coding scripts. The source code and a detailed tutorial for MLme are available at https://github.com/FunctionalUrology/MLme

Techno-Economic and Exergetic Analysis and Optimization of Integrated MED- RO Desalination System in the Genaveh Combined Cycle Power Plant

Hybrid power and desalinated water generation systems with two Multi-Effect Distillation (MED) technologies and Reverse Osmosis (RO) are investigated for a combined-cycle power plant in this study. The generated steam enters MED from the low-pressure section of the Heat Recovery Steam Generator (HRSG) in the hybrid system. Seawater is divided into two sections after entering the MED condenser – one part is fed into MED and its process. The other is rejected after cooling in the condenser and turns back to the sea. A reverse osmotic desalination system is implemented in this study. In the present combined cycles, steam generated in the Low Pressure (LP) section enters the steam turbine. To reduce the generated power and increase desalinated water in MED and RO, exergy analysis and cycle optimization are required. The system is simulated and verified based on the available data on the model power plant. The results showed that by selecting 43 optimization parameters and applying constraints like acidification temperature, the integrated cycle's exergy efficiency could be raised by 50%. Under this condition, the water price is calculated to be 1.16 $/m3. Under hybrid conditions of the design power and freshwater cogeneration system, the present design's efficiency without optimization and its final cost is 48.8$/m3

SpheroScan: A User-Friendly Deep Learning Tool for Spheroid Image Analysis.

BACKGROUND In recent years, three-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional two-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays. RESULTS To address these issues, we have developed a fully automated, web-based tool called SpheroScan, which uses the deep learning framework called Mask Regions with Convolutional Neural Networks (R-CNN) for image detection and segmentation. To develop a deep learning model that could be applied to spheroid images from a range of experimental conditions, we trained the model using spheroid images captured using IncuCyte Live-Cell Analysis System and a conventional microscope. Performance evaluation of the trained model using validation and test datasets shows promising results. CONCLUSION SpheroScan allows for easy analysis of large numbers of images and provides interactive visualization features for a more in-depth understanding of the data. Our tool represents a significant advancement in the analysis of spheroid images and will facilitate the widespread adoption of 3D spheroid models in scientific research. The source code and a detailed tutorial for SpheroScan are available at https://github.com/FunctionalUrology/SpheroScan