Notes

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Glioma is one of the primary tumors of the central nervous system that occurs in the spinal cord or brain and the origin of the tumor is from glial cell cells. The most common site of glioma tumors is the brain. Glioma accounts for 30% of all central nervous system tumors and 80% of malignant brain tumors. Alpha-thalassemia/mental retardation syndrome X-linked (ATRX) mutations are frequently distinguished in gliomas. Current research is an attempt to assess ATRX immunoexpression in different types of gliomas diagnosed, in Erbil-Iraq, and to evaluate its association with patient's age, gender, tumor location, grade and type. From January 2015 to January 2017, we reviewed and analyzed 97 cases of glioma. Immunohistochemical staining, for ATRX, was performed using an automated immunostainer technique. According to the WHO grading system for brain tumors, 16 (16.5%) cases were grade I gliomas, 27 (27.8%) were grade II, 10 (10.3%) were anaplastic gliomas (grade III), and 44 (45.3%) cases were glioblastomas WHO (grade IV). Positive ATRX immunoexpression was demonstrated in 27 (27.8%) cases. The highest rates of ATRX expression (55.6%) were among 30-39 years' age group, supratentorial (34.2%), and among grade II and III tumors (40.7% and 30% respectively). A significant association was observed between ATRX expression and patient's age, tumor location, tumor type and grade (p-values 0.010, 0.004, 0.004, and 0.037 respectively). No significant association was found between ATRX expression and patient's gender (p-value 0.097). It was found that ATRX is frequently expressed in grade II and III astrocytomas and was significantly related to the patient's age, tumor location, type and grade, so it can be used as a good diagnostic and prognostic indicator for glioma.Benign prostatic hyperplasia (BPH) is a common multifactorial inflammatory disease of older men, defined by increased growth of prostate epithelial and stromal cells. Elevation serum levels of Interleukin-8 (IL-8), oxidative stress and inflammatory markers represent predictive surrogate markers of the disease progression in smoker BPH patients. A total of 86 BPH patients and 54 control subjects were admitted to the urology unit, Rizgary Teaching Hospital in Erbil City, Iraq between January and June 2020. Sera levels of prostate-specific antigen(PSA), IL-8, malondialdehyde (MDA), high sensitive C-reactive protein (hs-CRP), testosterone and some biomarkers concentrations were measured in the patients according to instructions of manufacturers. Patients and controls were categorized into groups according to smoking status (smokers and non-smokers). The sera levels of PSA, IL-8 and inflammatory markers like oxidative stress(MDA), hs-CRP and testosterone in every smoker subgroup (BPH patients and control) increased compared to the same non-smoker subgroups and significantly increased compared with non-smoker control (p<0.05). PSA demonstrated a significant positive correlation with the following terms, IL-8, MDA, hs-CRP, testosterone and low-density lipid (LDL)(p<0.05) and, insignificant negative correlation with high-density lipoprotein(HDL), (p>0.05). The current study demonstrated mounting evidence to support the role of smoking in the pathophysiology of BPH through elevation levels of inflammatory and oxidative stress biomarkers in sera of BPH patients.The purpose of this study was to evaluate the prophylactic effects of quercetin (QUE) against oxidative damages and histological changes induced by 1, 2, 3, 4-tetrachlorodibenzo-p-dioxin (TCDD) in rat heart. For this purpose, 20 adult male Wistar rats were divided into four groups as fellow control group, TCDD group (10µg/kg BW/day by gavage daily for 60 consecutive days), QUE group (30 mg/kg BW/day) and TCDD + QUEgroup. The oxidative biomarkers of heart tissue and the levels of cTnI and lipid profile in serum were measured. Our results showed that the cTnI serum level and the heart lipid peroxidation significantly increased and the heart level of antioxidant profile significantly decreased in the TCDD group compared to control and QUEgroups. While pretreatment with QUEcould significantly improved these factors in serum and heart tissue in animals that consumed TCDD. It can be concluded that QUEat doses of 30 mg/kg/day could alleviate heart oxidative damage and histological changes induced by TCDD.Bifidobacterium selectively colonizes the infants' intestinal tract, and the relevant coliform bacteria in adults are particularly beneficial because of their enhanced capability to prevent pathogens of gastro intestine by direct antimicrobial action and relieve infection, which led to their intensification, the antibacterial activities of titanium nanoparticles producing by some bacteria, makes them attractive as a new agent against pathogenic bacteria. In our present study, we used a probiotic bacteria Bifidobacterium bifidum which was isolated from the commercial market capsule to produce TiO2 nanoparticles and study the biologically characterized nanoparticle using various techniques like Scanning Electron Microscopic (SEM), atomic force microscopy (AFM), and study its antimicrobial activity against a bacteria isolated from the stool of patients suffering from acute diarrhea. check details The results showed that the morphological characteristics of nanoparticles were found to have a spherical shape and mean size of 81 nm by AFM while scanning electron microscope viewed as an oval shape with anatase form synthesized by B. bifidum. TiO2-NP synthesized by B. bifidum had an inhibitory effect against P. aeruginosa, A. baumanii, K. pneumonia at a concentration 16 mg/ml and 32 mg/ml towards E. coli and S. typhi, the minimum inhibitory concentration (MIC) against pathogenic bacteria isolated from acute diarrhea included Pseudomonas aeruginosa, Acinetobacter baumanii, Klebsiella pneumonia, E.coli and salmonella typhi was utilized to determine the antibacterial impact of the synthesized TIO2 nanoparticles. Our biologically synthesized titanium nanoparticles were effective against all the tested pathogenic bacteria at various degrees and had a probable role in significantly greater antimicrobial efficacy against all isolates under study. This trial may have considerable significance for the prevention of antibiotic resistance associated diarrhea in hospitals.In view of the shortcomings of the current abnormal data detection system of the protein gene library, such as low detection rate and high error detection rate, the abnormal data detection system of the protein gene library based on data mining technology is designed. The protein gene enters the firewall module of the system, and enters the immune module when it does not match the firewall rules; the memory detector in the immune module presents the protein gene, if the memory detector does not match the protein gene, the mature detector presents the protein gene, if the mature detector does not match the protein gene, it is determined as the normal protein gene data package, if it matches, it is considered that The abnormal data of protein gene was processed by the collaborative stimulation module, and the control module controlled by C8051F060 chip to detect the abnormal data of protein gene library. The immune module generates new protein gene sequences through an immature detector, simulates the immune mechanism of protein gene through a mature detector module, and simulates the secondary response in the abnormal data detection system of protein gene library through memory detector. The system introduces data mining technology into the detection and uses a two-level dynamic optimization algorithm to calculate the ASG similarity value of protein gene secondary structure arrangement. According to this value, the abnormal data detection of the protein gene library is realized by randomly generating protein genes, negative selection, clone selection and copying memory cells through gene expression. The experimental results show that the system can quickly detect abnormal data of the protein gene library, ensure the detection efficiency, and the detection accuracy reaches 97.1%. The system can reduce the error rate of normal protein gene detection as an abnormal protein gene.At present, bioinformatics research focuses on the development from the accumulation of biological data to the integration and processing of biological data. This paper designs a bio gene information collection system based on data mining technology. In the system, the information of gene web analysis database, data mining model database and gene chip database is transferred to gene algorithm tool library, which can extract, transform and load the biological gene information, transfer the collected and processed biological gene information to gene general chip and web database analysis logic, and pass it to gene expression spectrum chip/data mining module through API function GUI, through the data mining module GUI feedback to the system users. The system hardware stores the biochip information in the virtual chip set model through the gene expression spectrum data analysis model uses the gene expression similarity analysis model to analyze the expression similarity of the biological gene information, and stores the information in the gene chip database; through the multi-layer structure model, constructs the web genome biochip including the application layer, the data processing layer and the representation layer. The information analysis module analyzes the biological gene information and stores the information in the gene web analysis database. The system software adopts the method of automatic collection of biological gene data based on the web to realize the collection of biological gene information, and gives the main implementation technology of the system. The experimental results show that the system can effectively collect biological gene information, and has high accuracy and anti-noise performance.Hemoglobin (Hb) is a protein and its functional form has a tetrameric structure. This structure is the result of a combination of four sub-units called globin and indicates the dynamic interaction between them. Each subunit has a ring-shaped organic molecule called a heme that contains an iron atom; Heme is a group that mediates the reversible binding of oxygen by hemoglobin. This research was performed to observe the image of Hb by an atomic force microscope (AFM) and measure the physical function of athletes. For this purpose, based on the principle of AFM imaging, the hemoglobin crosslinking method was used to measure the morphology and size of cross-linked Hb, glutaraldehyde and Hb diameter were detected to prepare cross-linked Hb samples with different molar ratio, the activity of peroxidase was detected by Trinder reaction. The AFM was used to detect the influence of physiological environment changes such as pH, temperature, oxygen partial pressure and osmotic pressure on the absorption spectrum of Hb intration of HbO2) decreased, the osmotic pressure increased, the RBC dehydrated, the volume decreased, and the concentration of Hb increased. Conclusion It is more accurate and comprehensive to use AFM to observe athletes' hemoglobin.Proteins, as the largest macromolecules in the body, are among the most important components of the body and play very vital and important roles. These substances are made up of a series of amino acid chains that, depending on the type of protein, the number of these amino acids can reach several thousand. Proteins function differently depending on the type and location of their presence, including enzymatic activity to catalyze the process, identify microbes and cancer cells, transport substances such as respiratory gases, and signalize. In the biochemical experiment, the problem of optimizing the detection of protein molecular defects, because of the randomness of the information, parameters, selection and setting, limits the detection accuracy of protein molecular defects. Based on the characteristics of fast learning speed and a robust network of neural network algorithm, a protein molecular defect detection method based on a neural network algorithm was proposed. Firstly, the protein secondary structure was predicted by the method of protein secondary structure prediction based on the generalized regression neural network to obtain the protein structural features; secondly, the protein defective molecular sequence classification model based on the neural network was used to classify the protein defective molecular sequence to achieve the protein molecular defect detection.
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