Artificial intelligence methods for the diagnosis of breast cancer by image processing: a review

Farahnaz Sadoughi,1 Zahra Kazemy,1 Farahnaz Hamedan,1 Leila Owji,1 Meysam Rahmanikatigari,2 Tahere Talebi Azadboni1 1Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran; 2Social Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran Abstract: Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide; thus, its early diagnosis has a significant impact on reducing mortality. However, it is often difficult to diagnose breast abnormalities. Different tools such as mammography, ultrasound, and thermography have been developed to screen breast cancer. In this way, the computer helps radiologists identify chest abnormalities more efficiently using image processing and artificial intelligence (AI) tools. This article examined various methods of AI using image processing to diagnose breast cancer. It was a review study through library and Internet searches. By searching the databases such as Medical Literature Analysis and Retrieval System Online (MEDLINE) via PubMed, Springer, IEEE, ScienceDirect, and Gray Literature (including Google Scholar, articles published in conferences, government technical reports, and other materials not controlled by scientific publishers) and searching for breast cancer keywords, AI and medical image processing techniques were extracted. The results were provided in tables to demonstrate different techniques and their results over recent years. In this study, 18,651 articles were extracted from 2007 to 2017. Among them, those that used similar techniques and reported similar results were excluded and 40 articles were finally examined. Since each of the articles used image processing, a list of features related to the image used in each article was also provided. The results showed that support vector machines had the highest accuracy percentage for different types of images (ultrasound =95.85%, mammography =93.069%, thermography =100%). Computerized diagnosis of breast cancer has greatly contributed to the development of medicine, is constantly being used by radiologists, and is clear in ethical and medical fields with regard to its effects. Computer-assisted methods increase diagnosis accuracy by reducing false positives. Keywords: breast cancer, breast cancer screening techniques, artificial intelligence techniques, medical image processin

The Effect of Bright Light on Physiological Circadian Rhythms and Subjective Alertness of Shift Work Nurses in Iran

In this study, the effects of bright light (BL) on the rhythms in body temperature, plasma melatonin, plasma cortisol and subjective alertness, in 34 shift work nurses at a university hospital were assessed. They were exposed to very BL (4 500 lx) during 2 breaks (21:15–22:00 and 3:15–4:00) or dim light (300 lx). The subjects were studied under 24 h of realistic conditions during which their plasma cortisol and melatonin were measured at 3-h intervals; their body temperature was also measured during and after night shift work. Subjective alertness was evaluated with the Karolinska sleepiness scale. Administration of BL significantly suppressed night-time melatonin levels. A one-way ANOVA revealed that BL tended to increase cortisol levels and body temperature and significantly improved alertness. These results demonstrate that photic stimulation in a hospital setting can have a powerful influence on the adjustment of the circadian system

Advanced biocomposites of poly(glycerol sebacate) and β-tricalcium phosphate by in situ microwave synthesis for bioapplication

Biodegradable poly(glycerol sebacate) [PGS] has gained substantial attention in the soft tissue engineering field over the past few years, but its application is limited because its fast degradation rate causes an acidic environment which can adversely affect cell viability and eventually tissue growth. β-tricalcium phosphate (β-TCP) is an ideal biocompatible candidate to mitigate these drawbacks of PGS. This work for the first time rationalizes a biocomposite composed of PGS and β-TCP prepared by a fast and well-controlled microwave approach. As expected, the presence of β-TCP particles (i) improves the degree of cross-linking of PGS, thus decreasing the sol content by ca. 66%, (ii) enhances its hydrophilicity with much lower contact angle, (iii) reduces the degradation rate by a factor of two and (iv) increases the swelling effect of the biocomposite by ca. 10%. Furthermore both PGS/β-TCP150 and PGS/β-TCP180 biocomposites demonstrate significant difference in cell viability form the single PGS materials, which is more than 65% higher in cell growth in one day proliferation, demonstrating an advanced biomaterial embodying both advantages of PGS polymer and β-TCP bioceramics

Down-Regulation of SIRT1 Expression by mir-23b Contributes to Lipid Accumulation in HepG2 Cells

Non-alcoholic fatty liver disease is one of the main causes of chronic liver disease and therefore is currently considered a major public health problem. Sirtuin 1 (SIRT1) is an NAD-dependent deacetylase enzyme that contributes in the regulation of metabolic processes and protects against lipid accumulation in hepatocytes. Its expression is potentially regulated by microRNAs which attach to the 3� untranslated region (3�-UTR) of their target mRNA. HepG2 cells were incubated by glucose to induce lipid accumulation and were subsequently transfected with mir-23b mimic and inhibitor. Real-time PCR was used for measuring the expression of mir-23b and SIRT1 mRNA. Cell survival assay and intracellular triglyceride measurement were performed using colorimetric methods. Determination of SIRT1 protein level and activity were done by western blot and fluorometric analysis, respectively. The interaction of miR-23b with 3�-UTR of SIRT1 mRNA was confirmed by dual luciferase. miR-23b mimic inhibited gene and protein expression of SIRT1, while the inhibitor of miR-23b significantly elevated the expression levels of SIRT1 mRNA and protein. The results showed that the 3�-UTR of SIRT1 mRNA is a direct target for miR-23b. The intracellular triglyceride level was increased following the inhibition of SIRT1 in transfected HepG2 cell by miR-23b mimic. Cell viability was decreased in response to miR-23b upregulation compared to control cells. miR-23b reduces the expression and activity of SIRT1 and therefore may be a causative factor in the enhancement of lipid accumulation in HepG2 cells. © 2019, Springer Science+Business Media, LLC, part of Springer Nature

Bacteria-Derived Protein Aggregates Contribute to the Disruption of Host Proteostasis

Neurodegenerative protein conformational diseases are characterized by the misfolding and aggregation of metastable proteins encoded within the host genome. The host is also home to thousands of proteins encoded within exogenous genomes harbored by bacteria, fungi, and viruses. Yet, their contributions to host protein-folding homeostasis, or proteostasis, remain elusive. Recent studies, including our previous work, suggest that bacterial products contribute to the toxic aggregation of endogenous host proteins. We refer to these products as bacteria-derived protein aggregates (BDPAs). Furthermore, antibiotics were recently associated with an increased risk for neurodegenerative diseases, including Parkinson’s disease and amyotrophic lateral sclerosis—possibly by virtue of altering the composition of the human gut microbiota. Other studies have shown a negative correlation between disease progression and antibiotic administration, supporting their protective effect against neurodegenerative diseases. These contradicting studies emphasize the complexity of the human gut microbiota, the gut–brain axis, and the effect of antibiotics. Here, we further our understanding of bacteria’s effect on host protein folding using the model Caenorhabditis elegans. We employed genetic and chemical methods to demonstrate that the proteotoxic effect of bacteria on host protein folding correlates with the presence of BDPAs. Furthermore, the abundance and proteotoxicity of BDPAs are influenced by gentamicin, an aminoglycoside antibiotic that induces protein misfolding, and by butyrate, a short-chain fatty acid that we previously found to affect host protein aggregation and the associated toxicity. Collectively, these results increase our understanding of host–bacteria interactions in the context of protein conformational diseases