Modern Medical Laboratory Journal
Volume:6 Issue: 1, Winter-Spring 2023

Breast cancer is a prevalent form of endocrine cancer that affects women globally, and its incidence and mortality rates are predicted to rise significantly in the coming years. As a result, breast cancer continues to pose a significant health issue and is a top priority for biomedical research.

We used bioinformatics and reverse pharmacology techniques to identify herbal medicines that could be effective in treating breast cancer. To do this, we analyzed 121 genes from a dataset (GSE 42568) containing both cancer and normal samples. Through this analysis, we identified differentially expressed genes (DEGs) and then used the protein-protein interaction (PPI) network to identify 19 hub genes. To pinpoint hub genes, the widely-used bioinformatics tool, Search Tool for Retrieving Reciprocal Genes (STRING), was utilized. To conduct a more detailed analysis, subnetworks were identified using the MCODE algorithm.

The hub genes identified in our reaserch are involved in various functions, including positive regulation of cold-induced thermogenesis, patched binding, and the PPAR signaling pathway, as revealed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. We understood that the herbs Ginkgo biloba seeds, Polygoni Cuspidati Rhizoma Et Radix, Smilacis Glabrae Rhixoma, Capsici Fructus, Cyathulae Radix, Puerariae Flos, and Ardisiae Japonicae Herba can target hub genes such as PPARG, CCNB1, CAV1, CDH1, ADIPOQ, LEP, IGF1, LPL, DGAT2, ACSL1, and PCK1. Using nine identified ingredients, these herbs were identified as key in targeting hub genes.

Ulcerative colitis (UC) is a chronic inflammatory disease that affects the colon and rectum. There is a constant need for improvements to be made in the current medical therapy since UC is extremely burdensome and kills many individuals. There are significant proportion of patients who experience adverse effects with current therapies. Consequently, new alternatives for the treatment of UC are constantly being sought. Probiotics are living microorganisms that are meant to improve one's health whether taken orally or topically. Gut microbiota balance, gut barrier function, and host immune responses all benefit from probiotic microorganisms. Probiotic supplementation is therefore becoming an increasingly popular treatment approach for treating UC and reducing chronic inflammation while also enhancing patients' quality of life. In order to assess the clinical effectiveness of probiotics, we examined the databases of PubMed, Web of Science, Embase, Science Direct, and Google Scholar. Probiotics are equally beneficial as conventional medication therapy in treating UC, according to several studies. Here, we've outlined the key findings of research that employed probiotics either alone or in conjunction with traditional UC treatment on individuals with UC.

Bee products, such as honey, propolis, royal jelly, bee pollen, bee bread, bee venom, and bee wax, have been used for centuries in traditional medicine for their various health benefits. In recent years, bee products have attained popularity in the cosmetics industry due to their potential benefits for the skin and hair. Bee products can be used in several cosmetics, including creams, serums, masks, shampoos, and hair conditioners. They can be used as ingredients in formulations or as independent products. This narrative review is designed to describe the current uses of bee products in skin and hair care.

The identification of Alzheimer's disease (AD) has become crucial in recent years due to the global increase in life expectancy. If mild cognitive impairment (MCI) occurs, it can progress to Alzheimer's disease and dementia because it permanently impairs the patient's mental ability. Many researchers have given this condition their undivided focus since, if caught early enough, it can be treated and its progression halted. Psychological examinations and biochemical tests are frequently used to diagnose the illness. The analysis of magnetic resonance imaging (MRI) scans, which are used to examine changes in the structure of the human brain, is one of the suggested methods for detecting Alzheimer's disease. The SPM (Statistical Parametric Mapping) toolbox is used in this study to preprocess brain MRI images before segmenting the brain's gray matter (GM) and feeding it into the convolutional neural network (CNN) algorithm. The ADNI (Alzheimer's Disease Neuroimaging Initiative) dataset is used in this paper. Based on the test's results, we could accurately distinguish the three groups of normal control (NC), Alzheimer's disease, and moderate cognitive impairment.

This study uses deep learning algorithms and CT (Computed Tomography) scans to diagnose COVID-19. First, we introduce a novel method to reduce noise in CT images by combining wavelet transformation with fuzzy logic. Then, using the suggested combined global and local threshold technique, we segmented lung pictures. Lung areas from CT scans can be successfully segregated in this manner. Features and categorization will be extracted in the following stage. While an SVM (Support Vector Machine) is used for classification, AlexNet extracts features. Three categories of data are categorized with a 99.8% accuracy: COVID-19, Viral Pneumonia, and Normal. The proposed strategy outperforms earlier approaches in terms of classification performance.

Dental pulp stem cells(DPSCs) are a class of stem cells which originate from dental pulp tissue and possess multiple stem cell characteristics including high clonogenicity, differentiation capacity and immunomodulatory effects.  DPSCs can be used in different stem cell-based therapy to treat a variety of diseases, such as autoimmune, orthopedic, and neurological diseases.Recent studies showed that DPSCs combined with biomaterials provides an effective approach to craniofacial bone regeneration and reconstruction of bone defects. Scaffolds improve cell attachment, proliferation, differentiation, and migration. In the present study we discuss different combination of biomaterials with DPSCs.