Search results for: international ovarian tumor analysis classification

Authors: Zulkiflee Abd Latif, Sitinor Atikah Nordin, Alawi Sulaiman

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Different tree species possess different and various benefits. Arenga Pinnata tree species own several potential uses that is valuable for the economy and the country. Mapping vegetation using remote sensing technique involves various process, techniques and consideration. Using satellite imagery, this method enables the access of inaccessible area and with the availability of near infra-red band; it is useful in vegetation analysis, especially in identifying tree species. Pixel-based and object-based classification technique is used as a method in this study. Pixel-based classification technique used in this study divided into unsupervised and supervised classification. Object based classification technique becomes more popular another alternative method in classification process. Using spectral, texture, color and other information, to classify the target make object-based classification is a promising technique for classification. Classification of Arenga Pinnata trees is overlaid with elevation, slope and aspect, soil and river data and several other data to give information regarding the tree character and living environment. This paper will present the utilization of remote sensing technique in order to map Arenga Pinnata tree species

Keywords: Arenga Pinnata, pixel-based classification, object-based classification, remote sensing

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Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

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In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

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Authors: Vanda Božić, Željko Nikač

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The wars and armed conflicts have often resulted in violations of international humanitarian law, and often commit the most serious international crimes such as war crimes, crimes against humanity, aggression and genocide. However, only in the XX century the rule was articulated idea of establishing a body of international criminal justice in order to prosecute these crimes and their perpetrators. The first steps in this field have been made by establishing the International military tribunals for war crimes at Nuremberg and Tokyo, and the formation of ad hoc tribunals for the former Yugoslavia and Rwanda. In the end, The International Criminal Court was established in Rome in 1998 with the aim of justice and in order to give satisfaction the victims of crimes and their families. The aim of the paper was to provide a historical and comparative analysis of the institutions of international criminal justice based on which these institutions de lege lata fulfilled the goals of individual criminal responsibility and justice. Furthermore, the authors suggest de lege ferenda that the Permanent International Criminal Tribunal, in addition to the prospective case, also takes over the current ICTY and ICTR cases.

Keywords: international crimes, international criminal justice, prosecution of crimes, ad hoc tribunal, the international criminal court

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Authors: Tahraoui Boualem

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Researching the historical framework of international crime means examining the historical facts that have contributed to uncovering this serious crime affecting international interests, and the law by which the study of the subject of international crime is determined is international criminal law, which is a branch of public international law. In this context, the historical study of international crime means recognizing the existence of an international community governed by international law, which makes us acknowledge that ancient societies lacked such stable and recurring international relations. Therefore, an attempt to monitor international crime in those ancient societies is only to demonstrate a historical fact that those societies have known some features of this crime, and have contributed in one way or another to the development of international criminal law without defining its concept or legal nature. The international community has affirmed the principle of establishing peace, achieving security, and respecting human rights. As a basis for friendly relations between the people of the international community and in case of prejudice, such as the aggressors breaching the obligations imposed on them, whether in time of peace or war.

Keywords: historical framework, of international crime, peace or war., international law

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Authors: Ouafae Baida, Najma Hamzaoui, Maha Akbib, Abdelfettah Sedqui, Abdelouahid Lyhyaoui

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Numerous scientific works present various methods to analyze the data for several domains, specially the comparison of classifications. In our recent work, we presented a new approach to help the user choose the best classification method from the results obtained by every method, by basing itself on the distances between the trees of classification. The result of our approach was in the form of a dendrogram contains methods as a succession of connections. This approach is much needed in phylogeny analysis. This discipline is intended to analyze the sequences of biological macro molecules for information on the evolutionary history of living beings, including their relationship. The product of phylogeny analysis is a phylogenetic tree. In this paper, we recommend the use of a new method of construction the phylogenetic tree based on comparison of different classifications obtained by different molecular genes.

Keywords: hierarchical classification, classification methods, structure of tree, genes, phylogenetic analysis

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Salina Yahya Saddik

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The present study is designed to demonstrate the Ovarian Surface Epithelial cells (OSE) Estrogen Receptor α (ERα) and Progesterone Receptor (PR) during pregnancy and estrous cycle in rat. Moreover, determination of the levels of plasma progesterone, estradiol, FSH and LH were also made. The levels of plasma progesterone, estradiol, FSH and LH concentrations were determined on days 7 (n=5), 14 (n=5), and 21(n=5) of pregnancy in three groups of rats and during the estrous cycle (n=5) using ELISA kit. Immunohistochemical method for PR and ERα expression was also made on the ovary. During pregnancy, FSH and LH remained low except at term when LH levels began to increase from 16 ng/ml to 47 ng/ml. Progesterone levels significantly exceeded estradiol values in all pregnant rats with a peak value of 202 ng/ml on day 14. Elevated progesterone levels were associated negatively with LH and estradiol levels during pregnancy. The levels of estradiol surged significantly on day 21. Immunohistochemistry of the ovary showed low levels of OSE cells staining positive for ERα expression. ERα positive cells were absent on day 7 and 14 of pregnancy, only day 21 recorded a very low percentage of immunostaining (0.5%) within the nuclei of OSE cells. On the contrary, immunostaining of PR was not observed within the nuclei of OSE cells in all groups of study. In conclusions, these results may suggest that progesterone effect during pregnancy seems to be overriding the positive effect of estrogens on OSE cells. High progesterone levels may have a direct negative effect on gonadotropin production and thereby it might inhibit events leading to both follicular development and OSE proliferation. Understanding the factors affecting OSE proliferation may help elucidating the mechanism(s) of assisted diseases such as ovarian cancer.

Keywords: ovarian surface, pregnancy, gonadotropins, steroids

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Authors: Marcela Capcarova, Adriana Kolesarova, Marina Medvedova, Peter Petruska, Alexander V. Sirotkin

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The aim of this study was to determine the activity of superoxide dismutase (SOD), glutathione peroxidase (GPx), total antioxidant status (TAS) and accumulation of Hsp70 in porcine ovarian granulosa cells after deoxynivalenol (DON) and zearalenone (ZEA) exposure in vitro. Porcine ovarian granulosa cells were incubated with DON/ZEA administrations as follows: group A (10/10 ng/mL), group B (100/100 ng/mL), group C (1000/1000 ng/mL), and the control group without any additions for 24h. In this study mycotoxins developed stress reaction of porcine ovarian granulosa cells and increased accumulation of Hsp70 what resulted in increasing activities of SOD and GPx in groups with lower doses of mycotoxins. High dose of DON and ZEA had opposite effect on GPx activity than the lower doses. Slight increase in TAS of porcine granulosa cells was observed after mycotoxins exposure. These results contribute towards the understanding of cellular stress and its response.

Keywords: deoxynivalenol, zearalenone, antioxidants, Hsp70, granulosa cells

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

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Authors: Hala M. El-hanbuli, Mohammed F. Darweesh

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The incidence rates of any tumor vary hugely with geographical location. Basal Cell Carcinoma (BCC) is one of the most common skin cancer that has many histopathologic subtypes. Objective: The aim was to study the histopathological features of BCC cases that were received in the Pathology Department, Kasr El-Aini hospital, Cairo University, Egypt during the period from Jan 2004 to Dec 2013 and to evaluate the clinical characters through the patient data available in the request sheets. Methods: Slides and data of BCC cases were collected from the archives of the pathology department, Kasr El-Aini hospital. Revision of all available slides and histological classification of BCC according to WHO (2006) was done. Results: A total number of 310 cases of BCC representing about 65% from the total number of malignant skin tumors examined during the 10-years duration in the department. The age ranged from 8 to 84 years, the mean age was (55.7 ± 15.5). Most of the patients (85%) were above the age of 40 years. There was a slight male predominance (55%). Ulcerated BCC was the most common gross picture (60%), followed by nodular lesion (30%) and finally the ulcerated nodule (10%). Most of the lesions situated in the high-risk sites (77%) where the nose was the most common site (35%) followed by the periocular area (22%), then periauricular (15%) and finally perioral (5%). No lesion was reported outside the head. The tumor size was less than 2 centimeters in 65% of cases, and from 2-5 centimeters in the lesions' greatest dimension in the rest of cases. Histopathological reclassification revealed that the nodular BCC was the most common (68%) followed by the pigmented nodular (18.75%). The histologic high-risk groups represented (7.5%) about half of them (3.75%) being basosquamous carcinoma. The total incidence for multiple BCC and 2nd primary was 12%. Recurrent BCC represented 8%. All of the recurrent lesions of BCC belonged to the histologic high-risk group. Conclusion: Basal Cell Carcinoma is the most common skin cancer in the 10-year survey. Histopathological diagnosis and classification of BCC cases are essential for the determination of the tumor type and its biological behavior.

Keywords: basal cell carcinoma, high risk, histopathological features, statistical analysis

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Authors: Waleed Aly Sayed Ahmed, Eman Kishk, Tahani Shams

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Aim: To study the effects of co-administration of phosphodiesterase-5 inhibitor (PDE-5) and sodium selenite against the damage induced by ovarian ischemia-reperfusion in rats. Materials and Methods: A total of forty-two sexually mature, virgin, female rats were divided randomly into six groups of seven each: sham group (C), ischemia group (I), ischemia/reperfusion group (I/R), ischemia/reperfusion plus 1.4mg/kg sildenafil (I/R+S) group, ischemia/reperfusion plus 0.2mg/kg selenium (I/R+Se) group and ischemia/reperfusion plus combination of sildenafil and selenium (I/R+S+Se) group. In ischemia group (I), rats were exposed to ischemia for 3 hours (h). In ischemia/reperfusion group (I/R), rats were exposed to ischemia for 3 h followed by 6 h of reperfusion. Treated groups received 1.4mg/kg sildenafil or 0.2 mg/kg selenium or both 30 min before reperfusion. Both ovaries were surgically removed carefully. One ovary was examined for histopathological changes and the other was subject to biochemical analysis including malondialdehyde (MDA), catalase (CAT) and glutathione peroxidase (GPx). Results: Assessment of ovarian tissue damage using a scoring system showed marked vascular congestion, interstitial edema, leukocyte infiltration, hemorrhage, and follicular degeneration in ischemia and ischemia/reperfusion groups. Tissue damage score for I, IR and all treated groups were significantly higher than those of the sham group (p<0.001), while tissue damage score decreased significantly in I/R+S and I/R+Se groups compared to I/R group (p<0.05), and notably, the difference was highly significant in I/R+S+Se group (p<0.001). There was significant increase in MDA levels and reduction in activities of CAT and GPx in I/R group compared to the sham group (p < 0.05). In I/R+S and I/R+Se groups, MDA was significantly decreased compared to the I/R group (p<0.05) and the difference was highly significant with co-administration of sildenafil and selenium (p<0.001). CAT and GPx were higher in all treated groups compared to I/R group (p<0.05). Conclusion: The co-administration of sildenafil citrate and selenium are highly protective against damage induced by ovarian ischemia/reperfusion in rats.

Keywords: phosphodiesterase-5 inhibitor, sildenafil, antioxidant, selenium, ovarian ischemia

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Authors: Najam Aziz, Nasru Minallah, Ahmad Junaid, Kashaf Gul

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Landcover classification using automated classification techniques, while employing remotely sensed multi-spectral imagery, is one of the promising areas of research. Different land conditions at different time are captured through satellite and monitored by applying different classification algorithms in specific environment. In this paper, a SPOT-5 image provided by SUPARCO has been studied and classified in Environment for Visual Interpretation (ENVI), a tool widely used in remote sensing. Then, Artificial Neural Network (ANN) classification technique is used to detect the land cover changes in Abbottabad district. Obtained results are compared with a pixel based Distance classifier. The results show that ANN gives the better overall accuracy of 99.20% and Kappa coefficient value of 0.98 over the Mahalanobis Distance Classifier.

Keywords: landcover classification, artificial neural network, remote sensing, SPOT 5

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Authors: Minzi Mao, Jianjun Ren, Yu Zhao

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Objectives: The absence of a uniform staging scheme for temporal bone carcinoma (TBC) seriously impedes the improvement of its management strategies. Therefore, this research was aimed to investigate the prognostic values of two currently applying staging schemes, namely, the modified Pittsburgh staging system (MPB) and Stell’s T classification (Stell-T) in patients with TBC. Methods: Areal-world single-institution retrospectivereview of patientsdiagnosed with TBC between2008 and 2019 was performed. Baseline characteristics were extracted, and patients were retrospectively staged by both the MPB and Stell-T classifications. Cox regression analyseswereconductedtocomparetheoverall survival (OS). Results: A total of 69 consecutive TBC patients were included in thisstudy. Univariate analysis showed that both Stell-T and T- classifications of the modified Pittsburgh staging system (MPB-T) were significant prognostic factors for all TBC patients as well as temporal bone squamous cell carcinoma (TBSCC, n=50) patients (P < 0.05). However, only Stell-T was confirmed to be an independent prognostic factor in TBSCC patients (P = 0.004). Conclusions: Tumor extensions, quantified by both Stell-T and MPB-T classifications, are significant prognostic factors for TBC patients, especially for TBSCC patients. However, only the Stell-T classification is an independent prognostic factor for TBSCC patients.

Keywords: modified pittsburgh staging system, overall survival, prognostic factor, stell’s T- classification, temporal bone carcinoma

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Authors: Leda Maria Costa Pereira, Maria Denise Lopes, Nucharin Songsasen

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Mammalian ovaries contain thousands of follicles that eventually degenerate or die after culture in vitro. Caspase-3 is a key enzyme that regulating cell death. Our objective was to examine the influence of anti-apoptotic drug Z-VAD-FMK (pan-caspase inhibitor) on in vitro viability of dog follicles within the ovarian cortex. Ovaries were obtained from prepubertal (age, 2.5–6 months) and adult (age, 8 months to 2 years) bitches and ovarian cortical fragments were recovered. The cortices were then incubated on 1.5% (w/v) agarose gel blocks within a 24-wells culture plate (three cortical pieces/well) containing Minimum Essential Medium Eagle - Alpha Modification (Alpha MEM) supplemented with 4.2 µg/ml insulin, 3.8 µg/ml transferrin, 5 ng/ml selenium, 2 mM L-glutamine, 100 µg/mL of penicillin G sodium, 100 µg/mL of streptomycin sulfate, 0.05 mM ascorbic acid, 10 ng/mL of FSH and 0.1% (w/v) polyvinyl alcohol in humidified atmosphere of 5% CO2 and 5% O2. The cortices were divided in six treatment groups: 1) 10 ng/mL EGF (EGF V0); 2) 10 ng/mL of EGF plus 1 mM Z-VAD-FMK (EGF V1); 3) 10 ng/mL of EGF and 10 mM Z-VAD-FMK (EGF V10); 4) 1 mM Z-VAD-FMK; 5) 10 mM Z-VAD-FMK and (6) no EGF and Z-VAD-FMK supplementation. Ovarian follicles within the tissues were processed for histology and assessed for follicle density, viability (based on morphology) and diameter immediately after collection (Control) or after 3 or 7 days of in vitro incubation. Comparison among fresh and culture treatment group was performed using ANOVA test. There were no differences (P > 0.05) in follicle density and viability among different culture treatments. However, there were differences in this parameter between culture days. Specifically, culturing tissue for 7 days resulted in significant reduction in follicle viability and density, regardless of treatments. We found a difference in size between culture days when these follicles were cultured using 10 mM Z-VAD-FMK or 10 ng/mL EGF (EGF V0). In sum, the finding demonstrated that Z-VAD-FMK at the dosage used in the present study does not provide the protective effect to ovarian tissue during in vitro culture. Future studies should explore different Z-VAD-FMK dosages or other anti-apoptotic agent, such as surviving in protecting ovarian follicles against cell death.

Keywords: anti apoptotic drug, bitches, follicles, Z-VAD-FMK

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Authors: Versha Sharma

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Juvenile hormone analogue, fenoxycarb and ecdysterone, when applied at varying concentrations in the adult females of Dysdercus similis, in situ histochemical observations of treated ovarian and adipose tissues during the first gonotrophic cycle elicited drastic histomorphological changes in both tissues. The action and effect of both JHa and ecdysterone on ovarian development, vitellogenesis, the activity of follicular epithelium, chorion formation all were monitored in detail. SDS-PAGE electrophoretic analysis showed drastic downregulation on the protein profile of differently treated tissue samples. After exogenous JHa supply, resorption of the developing oocytes was also often noticed. Gradational decline and disappearance of different protein bands in treated both ovarian and adipose tissues noticed could be due to the depletion of specific metabolites essential for oocyte development and maturation. Natural products support both crop production and the environment that being effective in pest control, less toxic to non-target organisms and at the same time biodegradable. Hence, these could be utilized as an attractive alternative to the synthetic chemical insecticides for at least cotton bug pest management. Increasing IGR dosages is found to elicit both qualitative and quantitative depletion of protein metabolites and drastic histochemical changes in the gonads of the treated forms brought forth the production of a large number of immature mal-formed oocytes. Findings in greater detail could be discussed.

Keywords: juvenile hormone, ecdysone, P. picta, Dysdercus similis

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Authors: Hwang Kwon

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Objective: To assess the efficacy of embryo transfer (ET) of accumulated vitrified embryos and compare pregnancy outcomes between ET of thawed embryos following accumulation of vitrified embryos (frozen ET) and ET of fresh and thawed frozen embryos following accumulation of vitrified embryos (fresh ET + frozen ET). Study design: Patients were poor ovarian responders defined according to the Bologna criteria as well as a subgroup of women whose previous IVF-ET cycle through controlled ovarian stimulation (COS) yielded one or no embryos. Sixty-four frozen ETs were performed following accumulation of vitrified embryos (ACCE )(ACCE Frozen) and 51 fresh + frozen ETs were performed following accumulation of vitrified embryos (ACCE Fresh + Frozen). Positive βhCG rate, clinical pregnancy rate, ongoing pregnancy rate, and good quality embryos (%, ±SD) were compared between two groups. Results: There were more good quality embryos in the ACCE Fresh + Frozen group than in the ACCE Frozen group: 60±34.7 versus 42.9±28.9, respectively (p=0.03). Positive βhCG rate [18/64(28.2%) vs. 13/51(25.5%); p=0.75] and clinical pregnancy rate [12/64 (18.8%) vs. 11/51 (10.9%); p=0.71] were comparable between the two groups. Conclusion: Accumulation of vitrified embryos is an effective method in patients with poor ovarian response who fulfill the Bologna criteria. Pregnancy outcomes were comparable between the two groups.

Keywords: accumulation of embryos, frozen embryo transfer, poor responder, Bologna criteria

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Authors: Yusha'u Shu'aibu Baraya, Kah Keng Wong, Nik Soriani Yaacob

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Strobilanthes crispus (S. crispus), is a Malaysian herb locally known as ‘Pecah kaca’ or ‘Jin batu’ which have demonstrated potent anticancer effects in both in vitro and in vivo models. In particular, S. crispus subfraction (SCS) significantly reduced tumor growth in N-methyl-N-Nitrosourea-induced breast cancer rat model. However, there is paucity of information on the effects of SCS in breast cancer metastasis. Thus, in this study, the antimetastatic effects of SCS (100 mg/kg) was investigated following 30 days of treatment in 4T1-induced mammary tumor (n = 5) model. The response to treatment was assessed based on the outcome of the tumour growth, body weight and hematological parameters. The results demonstrated that tumor bearing mice treated with SCS (TM-S) had significant (p<0.05) reduction in the mean tumor number and tumor volume as well as tumor weight compared to the tumor bearing mice (TM), i.e. tumor untreated group. Also, there was no secondary tumor formation or tumor-associated lesions in the major organs of TM-S compared to the TM group. Similarly, comparable body weights were observed among the TM-S, normal (uninduced) mice treated with SCS and normal (untreated/control) mice (NM) groups compared to the TM group (p<0.05). Furthermore, SCS administration does not cause significant changes in the hematological parameters as compared to the NM group, which indicates no sign of anemia and toxicity related effects. In conclusion, SCS significantly inhibited the overall tumor growth and metastasis in 4T1-induced breast cancer mouse model suggesting its promising potentials as therapeutic agent for breast cancer treatment.

Keywords: 4T1-cells, breast cancer, metastasis, Strobilanthes crispus

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Authors: Mostafa Sefidgar, Kaamran Raahemifar, Hossein Bazmara, Madjid Soltani

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The computational methods provide condition for investigation related to the process of drug delivery, such as convection and diffusion of drug in extracellular matrices, and drug extravasation from microvascular. The information of this process clarifies the mechanisms of drug delivery from the injection site to absorption by a solid tumor. In this study, an advanced numerical method is used to solve fluid flow and solute transport equations simultaneously to show how capillary network structure induced by tumor affects drug delivery. The effect of heterogeneous capillary network induced by tumor on interstitial fluid flow and drug delivery is investigated by this multi scale method. The sprouting angiogenesis model is used for generating capillary network induced by tumor. Fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. The Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. Finally, convection-diffusion-reaction equation is used to simulate drug delivery. The dynamic approach which changes the capillary network structure based on signals sent by hemodynamic and metabolic stimuli is used in this study for more realistic assumption. The study indicates that drug delivery to solid tumors depends on the tumor induced capillary network structure. The dynamic approach generates the irregular capillary network around the tumor and predicts a higher interstitial pressure in the tumor region. This elevated interstitial pressure with irregular capillary network leads to a heterogeneous distribution of drug in the tumor region similar to in vivo observations. The investigation indicates that the drug transport properties have a significant role against the physiological barrier of drug delivery to a solid tumor.

Keywords: solid tumor, physiological barriers to drug delivery, angiogenesis, microvascular network, solute transport

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Authors: R. L. Ujjwal, Abhishek Jain

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In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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Authors: Hamidreza Khodaei, Behnaz Mahdavi, Leila Karshenas

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Nitric oxide (NO) is a small fast acting neurotransmitter, which is synthesized From L-arginine by nitric oxide synthase. Studies show that NO affects a wide range of reproductive functions. Steroidal hormones synthesis, LH surge during ovulation, follicular growth and ovulation are all affected by NO. Therefore, the objective of this study was to evaluate the relationship between NO and estradiol (E2) production in ovarian follicles and cysts in bovines. Two experiment groups were formed and serum and follicular fluid levels Of NO and estradiol (E2) was measured. In the first group, follicular fluids were obtained from 30 slaughtered cows. Follicles were divided into three groups according to follicular diameter: Small follicles, <5 mm, medium-sized follicles, 5 to 10 mm, and large follicles, >10 mm. 30 follicles were randomly selected within each group. Blood samples were obtained via jugular vein. NO concentrations in blood and ovarian follicular fluids were measured by Griess reaction method and radio-immunoassay respectively. In the second group: 12 cows in follicular phase and with cystic follicles were selected and a cystic follicle was obtained from each. NO and E2 levels were measured as done for the first experiment group. The data were analyzed by SAS software using ANOVA and Duncan’s test. NO concentrations of follicular fluids from large follicles were significantly higher than those of the medium and small-sized ones. There were significant differences in the concentrations of nitrite and nitrate (Stable metabolites of NO) between large and cystic follicles, with extremely low NO and high E2 levels in cystic follicles (p<0.01).The results suggest that paracrine effects of NO may play an important role in the control of ovarian follicle growth and development of cystic follicles in bovines. It seems that NO dictates its effects through inhibition of ovarian steroidal synthesis.

Keywords: nitric oxide, estradiol, cystic follicle, cow, oogenesis, oocyte maturation, follicular fluid

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Fabio Fabris, Alex A. Freitas

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Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: algorithm recommendation, meta-learning, bioinformatics, hierarchical classification

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Yiannis G. Smirlis

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The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

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Authors: Eashwar V. Somasundaram, Raoul R. Wadhwa, Jacob G. Scott

Abstract:

The use of radiomics in measuring geometric properties of tumor images such as size, surface area, and volume has been invaluable in assessing cancer diagnosis, treatment, and prognosis. In addition to analyzing geometric properties, radiomics would benefit from measuring topological properties using persistent homology. Intuitively, features uncovered by persistent homology may correlate to tumor structural features. One example is necrotic cavities (corresponding to 2D topological features), which are markers of very aggressive tumors. We develop a data pipeline in R that clusters tumors images based on persistent homology is used to identify meaningful clinical distinctions between tumors and possibly new relationships not captured by established clinical categorizations. A preliminary analysis was performed on 16 Magnetic Resonance Imaging (MRI) breast tissue segments downloaded from the 'Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis' (I-SPY TRIAL or ISPY1) collection in The Cancer Imaging Archive. Each segment represents a patient’s breast tumor prior to treatment. The ISPY1 dataset also provided the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status data. A persistent homology matrix up to 2-dimensional features was calculated for each of the MRI segmentation. Wasserstein distances were then calculated between all pairwise tumor image persistent homology matrices to create a distance matrix for each feature dimension. Since Wasserstein distances were calculated for 0, 1, and 2-dimensional features, three hierarchal clusters were constructed. The adjusted Rand Index was used to see how well the clusters corresponded to the ER/PR/HER2 status of the tumors. Triple-negative cancers (negative status for all three receptors) significantly clustered together in the 2-dimensional features dendrogram (Adjusted Rand Index of .35, p = .031). It is known that having a triple-negative breast tumor is associated with aggressive tumor growth and poor prognosis when compared to non-triple negative breast tumors. The aggressive tumor growth associated with triple-negative tumors may have a unique structure in an MRI segmentation, which persistent homology is able to identify. This preliminary analysis shows promising results in the use of persistent homology on tumor imaging to assess the severity of breast tumors. The next step is to apply this pipeline to other tumor segment images from The Cancer Imaging Archive at different sites such as the lung, kidney, and brain. In addition, whether other clinical parameters, such as overall survival, tumor stage, and tumor genotype data are captured well in persistent homology clusters will be assessed. If analyzing tumor MRI segments using persistent homology consistently identifies clinical relationships, this could enable clinicians to use persistent homology data as a noninvasive way to inform clinical decision making in oncology.

Keywords: cancer biology, oncology, persistent homology, radiomics, topological data analysis, tumor imaging

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Authors: Hanan Alshaher, Jinsheng Xu

Abstract:

Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Sona Babu Rathinam, Lavanya Dharmendran, Therraddi Mutthu

Abstract:

Objectives: The purpose of this paper is to provides an overview of the neuroendocrine tumors that arise in the oral cavity. Material and Methods: An overview of the relevant papers on neuroendocrine tumors of the oral cavity by various authors was studied and summarized. Results: On the basis of the relevant studies, this paper provides an overview of the classification and histological differentiation of the neuroendocrine tumors that arise in the oral cavity. Conclusions: The basis of classification of neuroendocrine tumors is largely determined by their histologic differentiation. Though they reveal biologic heterogeneity, there should be an awareness of the occurrence of such lesions in the oral cavity to enable them to be detected and treated early.

Keywords: malignant peripheral nerve sheath tumor, olfactory neuroblastoma, paraganglioma, schwannoma

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Authors: Noraziah Nordin, Najihah Mohd Hashim, Nazia Abdul Majid, Mashitoh Abdul Rahman, Hamed Karimian, Hapipah Mohd Ali

Abstract:

Enicosanthellum pulchrum belongs to family Annonaceae is also known as family of 'mempisang' in Malaysia. Liriodenine was isolated by prep-HPLC method. This method was first technique used for the isolation of this compound. The structure of the liriodenine was elucidated by 1D and 2D spectroscopy techniques. Liriodenine was tested on ovarian cancer cells line (CAOV-3) for MTT, AO/PI and cytotoxicity 3 assays. The MTT assay was performed to determine the cytotoxicity effect of lirodenine on CAOV-3 cells. The morphological changes on CAOV-3 cells were observed by AO/PI assay for the early and late stage of apoptosis, as well as necrosis. Meanwhile, the measurement of cell loss, nuclear morphology, DNA content, cell membrane permeability, mitochondrial membrane potential changes and cytochrome c release from mitochondria were detected through cytotoxicity 3 assay. The IC50 results showed liriodenine inhibits the growth of CAOV-3 cells after 24 h of treatment at 10.25 ± 1.06 µg/mL. After 48 and 72 h of treatments, the IC50 values were decreased to 7.65 ± 0:07 and 6.35 ± 1.62 µg/mL, respectively. The morphology changes can be seen on CAOV-3 with a production of cell membrane blebbing, cromatin condensation and apoptotic bodies with increasing time of treatment from 24 to 72 h. Evaluation of cytotoxicity 3 on CAOV-3 cells after treated with liriodenine, resulting loss of mitochondrial membrane potential and release of cytochrome c from mitochondria. The results demonstrated the capability of liriodenine as a promising anticancer agent, particularly on human ovarian cancer.

Keywords: Enicosanthellum pulchrum, ovarian cancer, apoptosis, cytotoxicity

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