Construction of diagnosis system and gene regulatory networks based on microarray analysis.

A microarray analysis generally contains expression data of thousands of genes, but most of them are irrelevant to the disease of interest, making analyzing the genes concerning specific diseases complicated. Therefore, filtering out a few essential genes as well as their regulatory networks is critical, and a disease can be easily diagnosed just depending on the expression profiles of a few critical genes. In this study, a target gene screening (TGS) system, which is a microarray-based information system that integrates F-statistics, pattern recognition matching, a two-layer K-means classifier, a Parameter Detection Genetic Algorithm (PDGA), a genetic-based gene selector (GBG selector) and the association rule, was developed to screen out a small subset of genes that can discriminate malignant stages of cancers. During the first stage, F-statistic, pattern recognition matching, and a two-layer K-means classifier were applied in the system to filter out the 20 critical genes most relevant to ovarian cancer from 9600 genes, and the PDGA was used to decide the fittest values of the parameters for these critical genes. Among the 20 critical genes, 15 are associated with cancer progression. In the second stage, we further employed a GBG selector and the association rule to screen out seven target gene sets, each with only four to six genes, and each of which can precisely identify the malignancy stage of ovarian cancer based on their expression profiles. We further deduced the gene regulatory networks of the 20 critical genes by applying the Pearson correlation coefficient to evaluate the correlationship between the expression of each gene at the same stages and at different stages. Correlationships between gene pairs were calculated, and then, three regulatory networks were deduced. Their correlationships were further confirmed by the Ingenuity pathway analysis. The prognostic significances of the genes identified via regulatory networks were examined using online tools, and most represented biomarker candidates. In summary, our proposed system provides a new strategy to identify critical genes or biomarkers, as well as their regulatory networks, from microarray data.

A bio-inspired computing model for ovarian carcinoma classification and oncogene detection.

MOTIVATION: Ovarian cancer is the fifth leading cause of cancer deaths in women in the western world for 2013. In ovarian cancer, benign tumors turn malignant, but the point of transition is difficult to predict and diagnose. The 5-year survival rate of all types of ovarian cancer is 44%, but this can be improved to 92% if the cancer is found and treated before it spreads beyond the ovary. However, only 15% of all ovarian cancers are found at this early stage. Therefore, the ability to automatically identify and diagnose ovarian cancer precisely and efficiently as the tissue changes from benign to invasive is important for clinical treatment and for increasing the cure rate. This study proposes a new ovarian carcinoma classification model using two algorithms: a novel discretization of food sources for an artificial bee colony (DfABC), and a support vector machine (SVM). For the first time in the literature, oncogene detection using this method is also investigated. RESULTS: A novel bio-inspired computing model and hybrid algorithms combining DfABC and SVM was applied to ovarian carcinoma and oncogene classification. This study used the human ovarian cDNA expression database to collect 41 patient samples and 9600 genes in each pathological stage. Feature selection methods were used to detect and extract 15 notable oncogenes. We then used the DfABC-SVM model to examine these 15 oncogenes, dividing them into eight different classifications according to their gene expressions of various pathological stages. The average accuracyof the eight classification experiments was 94.76%. This research also found some oncogenes that had not been discovered or indicated in previous scientific studies. The main contribution of this research is the proof that these newly discovered oncogenes are highly related to ovarian or other cancers. AVAILABILITY AND IMPLEMENTATION: http://mht.mis.nchu.edu.tw/moodle/course/view.php?id=7.

A Decision Tree Based Classifier to Analyze Human Ovarian Cancer cDNA Microarray Datasets.

Ovarian cancer is the deadliest gynaecological disease because of the high mortality rate and there is no any symptom in cancer early stage. It was often the terminal cancer period when patients were diagnosed with ovarian cancer and thus delays a good opportunity of treatment. The current common method for detecting ovarian cancer is blood testing for analyzing the tumor marker CA-125 of serum. However, specificity and sensitivity of CA-125 are insufficient for early detection. Therefore, it has become an urgent issue to look for an efficient method which precisely detects the tumor markers for ovarian cancer. This study aims to find the target genes of ovarian cancer by different algorithms of information science. Feature selection and decision tree were applied to analyze 9600 ovarian cancer-related genes. After screening the target genes, candidate genes will be analyzed by Ingenuity Pathway Analysis (IPA) software to create a genetic pathway model and to understand the interactive relationship in the different pathological stages of ovarian cancer. Finally, this research found 9 oncogenes associated with ovarian cancer and some genes had not been discovered in previous studies. This system will assist medical staffs in diagnosis and treatment at cancer early stage and improve the patient's survival.

Blood Smear Image Based Malaria Parasite and Infected-Erythrocyte Detection and Segmentation.

In this study, an automatic malaria parasite detector is proposed to perceive the malaria-infected erythrocytes in a blood smear image and to separate parasites from the infected erythrocytes. The detector hence can verify whether a patient is infected with malaria. It could more objectively and efficiently help a doctor in diagnosing malaria. The experimental results show that the proposed method can provide impressive performance in segmenting the malaria-infected erythrocytes and the parasites from a blood smear image taken under a microscope. This paper also presents a weighted Sobel operation to compute the image gradient. The experimental results demonstrates that the weighted Sobel operation can provide more clear-cut and thinner object contours in object segmentation.

Repurposing gestrinone for tumor suppressor through P21 reduction regulated by JNK in gynecological cancer.

Endometriosis has been shown to increase the risk of gynecological cancers. However, the effect of gestrinone, a clinical endometriosis drug, on gynecological cancers remains unclear. This study aimed to understand the effect of gestrinone on gynecological cancers. A retrospective study was conducted using the Longitudinal Health Insurance Database 2000 of the Taiwan National Health Insurance Research Database (NHIRD) to observe the risk of gynecological cancers. Medication records from the Department of Obstetrics and Gynecology, Chung Shan Medical University Hospital CSMUH and cancer records from the Taiwan Cancer Registry were collected to analyze the correlation between gestrinone use and gynecological cancers. Subsequently, human cell lines were used to investigate the effect of gestrinone on gynecological cancers. A total of 8330 endometriosis patients were enrolled, and analyses revealed that endometriosis patients had a higher risk of developing ovarian and endometrial cancer. However, the rate of cervical cancer was not statistically different (P = 0.249). Analyses of both the NHIRD and CSMUH databases revealed that gestrinone may reduce the risk of gynecological cancer. Cellular experiments verified the anticancer effects of gestrinone, which effectively and specifically inhibited the growth of HeLa cervical cancer cells, decreased P21 expression via JNK phosphorylation, and induced apoptosis. Combining the results of clinical database analysis and cell experiments, our findings prove that gestrinone has the potential to protect against cancer through regulation of the JNK-P21 axis. Repurposing the anticancer efficacy of gestrinone may be a strategy for targeted therapy in the future.

EGR-1 plays a protective role in AMPK inhibitor compound C-induced apoptosis through ROS-induced ERK activation in skin cancer cells.

Skin cancer is caused by abnormal proliferation, gene regulation and mutation of epidermis cells. Compound C is commonly used as an inhibitor of AMP-activated protein kinase (AMPK), which serves as an energy sensor in cells. Recently, compound C has been reported to induce apoptotic and autophagic death in various skin cancer cell lines via an AMPK-independent pathway. However, the signaling pathways activated in compound C-treated cancer cells remain unclear. The present oligodeoxynucleotide-based microarray screening assay showed that the mRNA expression of the zinc-finger transcription factor early growth response-1 (EGR-1), which helps regulate cell cycle progression and cell survival, was significantly upregulated in compound C-treated skin cancer cells. Compound C was demonstrated to induce EGR-1 mRNA and protein expression in a time and dose-dependent manner. Confocal imaging showed that compound C-induced EGR-1 protein expression was localized in the nucleus. Compound C was demonstrated to activate extracellular signal-regulated kinase (ERK) phosphorylation. Inhibition of this compound C-induced ERK phosphorylation downregulated the mRNA and protein expression of EGR-1. In addition, removal of compound C-induced reactive oxygen species (ROS) not only decreased ERK phosphorylation, but also inhibited compound C-induced EGR-1 expression. A functional assay showed that knock down of EGR-1 expression in cancer cells decreased the survival rate while also increasing caspase-3 activity and apoptotic marker expression after compound C treatment. However, no difference in autophagy marker light chain 3-II protein expression was observed between compound C-treated control cells and EGR-1-knockdown cells. Thus, it was concluded that that EGR-1 may antagonize compound C-induced apoptosis but not compound C-induced autophagy through the ROS-mediated ERK activation pathway.

The minor C-allele of the rs2014355 variant in ACADS gene is associated with exercise-induced increase in HDL cholesterol levels in Taiwanese adults.

ABSTRACT: We investigated the association between high-density lipoprotein cholesterol (HDL-C) and rs2014355 variant in the gene, short-chain acyl-coenzyme A dehydrogenase (ACADS) based on exercise habits.Data collected between 2008 and 2015 for individuals aged 30 to 70 years were available in the Taiwan Biobank (TWB) database. Backward stepwise linear regression was used to evaluate the associations of rs2014355 and exercise with HDL-C levels.We analyzed data of 5515 physically active and 4169 inactive biobank participants. The HDL-C concentrations were higher in the exercise compared to no exercise group (beta value, ß = 1.79856; P < .0001). We observed that the test for interaction was significant for the ACADS rs2014355 variant and exercise (P for interaction =.0412). Multivariate analyses showed significant association between TC+CC genotype and HDL-C in the exercise (ß = 1.09785; P value = .0146) compared to the no-exercise group (ß = -0.03754, P = .9154).In summary, the association between HDL-C and exercise differed significantly with respect to ACADS rs2014355 genotypes. Compared to the TT genotype, the TC+CC genotype together with exercise was associated with higher levels of HDL-C.

Leukocyte nucleus segmentation and nucleus lobe counting.

BACKGROUND: Leukocytes play an important role in the human immune system. The family of leukocytes is comprised of lymphocytes, monocytes, eosinophils, basophils, and neutrophils. Any infection or acute stress may increase or decrease the number of leukocytes. An increased percentage of neutrophils may be caused by an acute infection, while an increased percentage of lymphocytes can be caused by a chronic bacterial infection. It is important to realize an abnormal variation in the leukocytes. The five types of leukocytes can be distinguished by their cytoplasmic granules, staining properties of the granules, size of cell, the proportion of the nuclear to the cytoplasmic material, and the type of nucleolar lobes. The number of lobes increased when leukemia, chronic nephritis, liver disease, cancer, sepsis, and vitamin B12 or folate deficiency occurred. Clinical neutrophil hypersegmentation has been widely used as an indicator of B12 or folate deficiency.Biomedical technologists can currently recognize abnormal leukocytes using human eyes. However, the quality and efficiency of diagnosis may be compromised due to the limitations of the biomedical technologists' eyesight, strength, and medical knowledge. Therefore, the development of an automatic leukocyte recognition system is feasible and necessary. It is essential to extract the leukocyte region from a blood smear image in order to develop an automatic leukocyte recognition system. The number of lobes increased when leukemia, chronic nephritis, liver disease, cancer, sepsis, and vitamin B12 or folate deficiency occurred. Clinical neutrophil hypersegmentation has been widely used as an indicator of B12 or folate deficiency. RESULTS: The purpose of this paper is to contribute an automatic leukocyte nuclei image segmentation method for such recognition technology. The other goal of this paper is to develop the method of counting the number of lobes in a cell nucleus. The experimental results demonstrated impressive segmentation accuracy. CONCLUSIONS: Insensitive to the variance of images, the LNS (Leukocyte Nuclei Segmentation) method functioned well to isolate the leukocyte nuclei from a blood smear image with much better UR (Under Segmentation Rate), ER (Overall Error Rate), and RDE (Relative Distance Error). The presented LC (Lobe Counting) method is capable of splitting leukocyte nuclei into lobes. The experimental results illuminated that both methods can give expressive performances. In addition, three advanced image processing techniques were proposed as weighted Sobel operator, GDW (Gradient Direction Weight), and GBPD (Genetic-based Parameter Detector).

Interactive Effect of IGF2BP2 rs4402960 Variant, Smoking and Type 2 Diabetes.

PURPOSE: Genetic and environmental factors are related to type 2 diabetes (T2D). Genetic modifiers of T2D have not been widely determined among smoking individuals. In this population-based study, we investigated the interactive association between rs4402960 polymorphism of the insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) gene and smoking with T2D among Taiwanese adults. MATERIALS AND METHODS: We obtained genetic data collected between 2008 and 2018 for 22,039 participants (aged 30-70 years) from the Taiwan Biobank (TWB) database. These data were analyzed using the t-test, Chi-square (χ 2) test, and multiple logistic regression. RESULTS: The mean ages for participants with and without diabetes were 58.11±8.75 and 48.58±11, respectively. Compared with the rs4402960 GG genotype, the odds ratio (OR) for T2D was 1.261 among GT and 1.545 among TT genotype individuals (p<0.05). Current smokers compared to nonsmokers were associated with a higher risk of T2D (OR=1.266, p=0.0404). There was a significant interaction between the IGF2BP2 rs4402960 variant and smoking on T2D (p = 0.0497). After stratification by rs4402960 genotypes and smoking status, the OR was substantial only in current smokers with GG genotype (OR, 1.663, p = 0.0008). CONCLUSION: This population-based study indicated that the risk for T2D was stronger among current smoking rs4402960 GG individuals recruited between 2008 and 2019 in Taiwan.

Novel electrospun poly(ε-caprolactone)/type I collagen nanofiber conduits for repair of peripheral nerve injury.

Recent studies have shown the potential of artificially synthesized conduits in the repair of peripheral nerve injury. Natural biopolymers have received much attention because of their biocompatibility. To investigate the effects of novel electrospun absorbable poly(ε-caprolactone)/type I collagen nanofiber conduits (biopolymer nanofiber conduits) on the repair of peripheral nerve injury, we bridged 10-mm-long sciatic nerve defects with electrospun absorbable biopolymer nanofiber conduits, poly(ε-caprolactone) or silicone conduits in Sprague-Dawley rats. Rat neurologica1 function was weekly evaluated using sciatic function index within 8 weeks after repair. Eight weeks after repair, sciatic nerve myelin sheaths and axon morphology were observed by osmium tetroxide staining, hematoxylin-eosin staining, and transmission electron microscopy. S-100 (Schwann cell marker) and CD4 (inflammatory marker) immunoreactivities in sciatic nerve were detected by immunohistochemistry. In rats subjected to repair with electrospun absorbable biopolymer nanofiber conduits, no serious inflammatory reactions were observed in rat hind limbs, the morphology of myelin sheaths in the injured sciatic nerve was close to normal. CD4 immunoreactivity was obviously weaker in rats subjected to repair with electrospun absorbable biopolymer nanofiber conduits than in those subjected to repair with poly(ε-caprolactone) or silicone. Rats subjected to repair with electrospun absorbable biopolymer nanofiber conduits tended to have greater sciatic nerve function recovery than those receiving poly(ε-caprolactone) or silicone repair. These results suggest that electrospun absorbable poly(ε-caprolactone)/type I collagen nanofiber conduits have the potential of repairing sciatic nerve defects and exhibit good biocompatibility. All experimental procedures were approved by Institutional Animal Care and Use Committee of Taichung Veteran General Hospital, Taiwan, China (La-1031218) on October 2, 2014.

Psoralea corylifolia extract ameliorates experimental osteoporosis in ovariectomized rats.

We evaluated the protective effect of Psoralea corylifolia L. (PCL) extract on the ovariectomized (OVX) rat model. The biochemical markers of bone turnover, calcium metabolism, and calcium balance were examined. PCL extract (25 mg or 50 mg/kg body weight/day) was orally administrated to OVX rats for 3 months. PCL extract did not alter weight gain or uterus weight in OVX rats. PCL extract significantly increased serum Ca (calcium) levels (p < 0.05, vs. OVX group) as well as decreased urinary Ca excretion (p < 0.05 vs. OVX group) in OVX rats. The upregulation of serum osteocalcin level by ovariectomy was suppressed by treatment with PCL extract in rats (p < 0.05, vs. OVX group). PCL extract increased bone mineral density at 50 mg/kg body weight/day in OVX rats (p < 0.05, vs. OVX group). Our results indicate that orally administrated PCL extract can decrease urinary calcium excretion and decrease serum osteocalcin in OVX rats, resulting in positive effects on bone mineral density as well as bone formation. In conclusion, our studies showed that PCL might be a potential candidate for treatment of postmenopausal osteoporosis.

Toxicity of the 13 priority pollutant metals to Vibrio fisheri in the Microtox chronic toxicity test.

The Microtox Acute Toxicity Test has been successfully used to measure the toxicity of metals and other pollutants at high concentrations (ppm) in selected environmental samples. However, metals and other toxicants are often found in much lower concentrations (ppb) in many municipal wastewaters and receiving waters. In order to assess the toxicity of these pollutants in these samples, a more sensitive toxicity assay is needed. The Microtox chronic toxicity test has been developed to measure the sublethal effect of toxicants over multiple generations of the test species, Vibrio fisheri. In this study, the toxicity of the 13 priority pollutant metals [i.e. As, Se, Cd, Cr (III and VI), Cu, Pb, Sb, Ag, Tl, Zn, Be, Hg and Ni] to V. fisheri was evaluated using the Microtox chronic toxicity test. In this test, the inhibitory concentration (IC), lowest observable effect concentration (LOEC), and no observable effect concentration (NOEC) were obtained after 22-h of incubation at 27+/-1 degrees C, by comparing the light output of the control to that of the test sample. Among the 13 priority pollutant metals, beryllium (Be) was found to be the most toxic in the test (LOEC=0.742-1.49 microg/l) while thallium (Tl) was the least toxic (LOEC=3840-15300 microg/l). The LOECs for copper (as Cu) and lead (Pb) in reagent (ASTM Type I) water were 6.78-13.6 microg/l and 626-1251 microg/l, respectively. The toxicity of copper sulfate (as Cu) in reagent water was shown and significantly reduced with the addition of natural organic matter (fulvic acid) or EDTA to the sample. The LOEC values for the 13 priority pollutant metals in this test were comparable to or lower than those reported for commonly used aquatic toxicity tests, such as the Ceriodaphnia dubia assay.

A protozoan parasite extraction scheme for digital microscopic images.

Pathogenic protozoan parasites can cause human to get many diseases, such as, amoebiasis, typhoid fever and cholera, etc. Different protozoan parasites vary greatly in their structural and biochemical properties. Digital images are extensively applied to medical fields for doctors and pathologists to analyze pathological sections and further diagnose diseases. The aim of this paper is to develop protozoan parasite extraction techniques to segment protozoan parasites from microscopic images. The proposed scheme has precise segmentation ability even if the image is with poor quality or complex background. Experimental results show that the proposed scheme can gain 96.64% average correct rate, and about 0.04, 0.45 and 0.06 of the average error rates: misclassification error (ME), region non-uniformity (RN) and relative foreground area error (RFAE), respectively.

Cymbidium mosaic potexvirus isolate-dependent host movement systems reveal two movement control determinants and the coat protein is the dominant.

Little is known about how plant viruses of a single species exhibit different movement behavior in different host species. Two Cymbidium mosaic potexvirus (CymMV) isolates, M1 and M2, were studied. Both can infect Phalaenopsis orchids, but only M1 can systemically infect Nicotiana benthamiana plants. Protoplast inoculation and whole-mount in situ hybridization revealed that both isolates can replicate in N. benthamiana; however, M2 was restricted to the initially infected cells. Genome shuffling between M1 and M2 revealed that two control modes are involved in CymMV host dependent movement. The M1 coat protein (CP) plays a dominant role in controlling CymMV movement between cells, because all chimeric CymMV viruses containing the M1 CP systemically infected N. benthamiana plants. Without the M1 CP, one chimeric virus containing the combination of the M1 triple gene block proteins (TGBps), the M2 5' RNA (1-4333), and the M2 CP effectively moved in N. benthamiana plants. Further complementation analysis revealed that M1 TGBp1 and TGBp3 are co-required to complement the movement of the chimeric viruses in N. benthamiana. The amino acids within the CP, TGBp1 and TGBp3 which are required or important for CymMV M2 movement in N. benthamiana plants were mapped. The required amino acids within the CP map to the predicted RNA binding domain. RNA-protein binding assays revealed that M1 CP has higher RNA binding affinity than does M2 CP. Yeast two-hybrid assays to detect all possible interactions of M1 TGBps and CP, and only TGBp1 and CP self-interactions were observed.