Search results for: brain tumor classification

Authors: Dost Muhammad Halepoto, Laila AL-Ayadhi

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Neurodevelopmental disorders such as autism can cause lifelong disability. Genetic and environmental factors are believed to contribute to the development of autism spectrum disorder (ASD), but relatively few studies have considered potential environmental risks. Several industrial chemicals and other environmental exposures are recognized causes of neurodevelopmental disorders and subclinical brain dysfunction. The toxic effects of such chemicals in the developing human brain are not known. This review highlights the role of environmental risk factors including drugs, toxic chemicals, heavy metals, pesticides, vaccines, and other suspected neurotoxicants including persistent organic pollutants for ASD. It also provides information about the environmental toxins to yield new insights into factors that affect autism risk as well as an opportunity to investigate the relation between autism and environmental exposure.

Keywords: Autism Spectrum Disorder, ASD, environmental factors, neurodevelopmental disorder

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Authors: Hushyar Azari

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Aim and background: Deep brain stimulation (DBS) is regarded as an important therapeutic choice for Parkinson's disease (PD). The two most common targets for DBS are the subthalamic nucleus (STN) and globus pallidus (GPi). This review was conducted to compare the clinical effectiveness of these two targets. Methods: A systematic literature search in electronic databases: Embase, Cochrane Library and PubMed were restricted to English language publications 2010 to 2021. Specified MeSH terms were searched in all databases. Studies which evaluated the Unified Parkinson's Disease Rating Scale (UPDRS) III were selected by meeting the following criteria: (1) compared both GPi and STN DBS; (2) had at least three months follow-up period; (3)at least five participants in each group; (4)conducted after 2010. Study quality assessment was performed using the Modified Jadad Scale. Results: 3577 potentially relevant articles were identified, of these, 3569 were excluded based on title and abstract, duplicate and unsuitable article removal. Eight articles satisfied the inclusion criteria and were scrutinized (458 PD patients). According to Modified Jadad Scale, the majority of included studies had low evidence quality which was a limitation of this review. 5 studies reported no statistically significant between-group difference for improvements in UPDRS ш scores. At the same time, there were some results in terms of pain, action tremor, rigidity, and urinary symptoms, which indicated that STN DBS might be a better choice. Regarding the adverse effects, GPi was superior. Conclusion: It is clear that other larger randomized clinical trials with longer follow-up periods and control groups are needed to decide which target is more efficient for deep brain stimulation in Parkinson’s disease and imposes fewer adverse effects on the patients. Meanwhile, STN seems more reasonable according to the results of this systematic review.

Keywords: brain stimulation, globus pallidus, Parkinson's disease, subthalamic nucleus

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Authors: Miceska Simona, Škof Erik, Frković Grazio Snježana, Jeričević Anja, Smrkolj Špela, Cvjetićanin Branko, Novaković Srdjan, Grčar Kuzmanov Biljana, Kloboves-Prevodnik Veronika

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Objectives: High-grade serous ovarian cancer (HGSOC) is characterized by the dissemination of the tumor cells (TC) in the peritoneal cavity forming malignant ascites at the time of diagnosis or recurrence. Still, cytology itself has been underutilized as a modality for the diagnosis of HGSOC from ascites, and histological examination from the tumor tissue is yet the only validated method used. The objective of this study was to evaluate the reliability of cytology in the diagnosis of HGSOC in relation to the histopathological examination. Methods: The study included 42 patients with histologically confirmed HGSOC, accompanied by malignant ascites. To confirm the malignancy of the TC in the ascites and to define their immunophenotype, immunohistochemical reaction (IHC) of the following antigens: Calretinin, MOC, WT1, PAX8, p53, p16 & Ki-67 was evaluated on ascites cytospins and tissue blocks. For complete cytological determination of HGSOC, BRCA 1/2 gene mutation was determined from ascites, tissue block, and blood. BRCA1/2 mutation from blood was performed to define the type of mutation, somatic vs germline. Results: Among 42 patients, the immunophenotype of HGSOC from ascites was confirmed in 36 cases (86%). For more profound analysis, the patients were divided in 3 groups regarding the number of TC present in the ascites: patients with less than 10% TC, 10% TC, and more than 10% TC. From all included patients, in the group with less than 10% TC, there were 10 cases, and only 5 of them(50%) showed HGSOC phenotype; 12 cases had equally 10% of TC, and 11 cases (92%) showed HGSOC phenotype; 20 cases had more than 10% TC and all of them (100%) confirmed the HGSOC immunophenotype from ascites. Only 33 patients were eligible for further BRCA1/2 analysis. Eleven BRCA1/2 mutations were detected from thetissue block: 6 germline and 5 somatic. In 2 cases with less than 10% TC, BRCA1/2 mutation was not detected; 4 cases had 10% TC, and 2 of them (50%) confirmed the mutation; 4 cases had more than 10% TC, and all showed 100% reliability with the tumor tissue. Conclusions: Cytology is a highly reliable method for determining the immunophenotype of HGSOC and BRCA1/2 mutation if more than 10% of tumor cells are present in the ascites. This may present an additional non-invasive clinical approach for fast and effective diagnose in the future, especially in inoperable conditions or relapses.

Keywords: cytology, ascites, high-grade serous ovarian cancer, immunophenotype, BRCA1/2

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Authors: Jiping Cai, Ningzhi Wangyang, Jun Shao

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Traumatic brain injury (TBI) is one of the major causes of morbidity and mortality that leads to structural and functional damage in several parts of the brain, such as cranial nerves, optic nerve tract or other circuitry involved in vision and occipital lobe, depending on its location and severity. As a result, the function associated with vision processing and perception are significantly affected and cause blurred vision, double vision, decreased peripheral vision and blindness. Here two cases complaining of monocular vision loss (actually temporal hemianopia) due to traumatic chiasmal syndrome after frontal head injury were reported, and were compared the findings with individual case reports published in the literature. Reported cases of traumatic chiasmal syndrome appear to share some common features, such as injury to the frontal bone and fracture of the anterior skull base. The degree of bitemporal hemianopia and visual loss acuity have a variable presentation and was not necessarily related to the severity of the craniocerebral trauma. Chiasmal injury may occur even in the absence bony chip impingement. Isolated bitemporal hemianopia is rare and clinical improvement usually may not occur. Mechanisms of damage to the optic chiasm after trauma include direct tearing, contusion haemorrhage and contusion necrosis, and secondary mechanisms such as cell death, inflammation, edema, neurogenesis impairment and axonal damage associated with TBI. Beside visual field test, MRI evaluation of optic pathways seems to the strong objective evidence to demonstrate the impairment of the integrity of visual systems following TBI. Therefore, traumatic chiasmal syndrome should be considered as a differential diagnosis by both neurosurgeons and ophthalmologists in patients presenting with visual impairment, especially bitemporal hemianopia after head injury causing frontal and anterior skull base fracture.

Keywords: bitemporal hemianopia, brain injury, optic chiasma, traumatic chiasmal syndrome.

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Authors: Yu-Mei Hsueh, Cheng-Shiuan Tsai, Chao-Yuan Huang

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Prostate Cancer (PC) is a malignant tumor originated in prostate and is a second common male’s cancer in the world. Incidence of PC in Asia countries, have still been rising over the past few decades. As an antioxidant, selenium can slow down prostate cancer tumor progression, but the association between plasma selenium levels and risk of aggressive prostate cancer may be modified by different genotype of selenoprotein. The aim of this study is to determine the relationship between plasma selenium, polymorphism of selenoprotein, urinaty total arsenic, and prostate cancer. Two hundred ninety five pathologically-confirmed cases of PC and 295 cancer-free controls were individually matched to case subjects by age (± 5 years) were recruited from Department of Urology of National Taiwan University Hospital, Taipei Municipal Wan Fang Hospital and Taipei Medical University Hospital. Personal interview and biospeciment of urine and blood collection from participants were conducted by well-trained interviewers after participants’ informed consent was obtained. Plasma selenium was measured by an inductively coupled plasma mass. Urinary arsenic concentration was detected using high-performance liquid chromatography-linked hydride generator and atomic absorption spectrometry. The polymorphism of SEPP1rs3797310 and SEP15 rs5859 were determined using polymerase chain reaction-restriction fragment length polymorphism method. The higher plasma selenium was the lower OR of PC with a dose-response relationship. Prostate cancer patients with high plasma selenium had low tumor stage and grade. Participants carried SEPP1rs3797310 CT+TT genotype compared to those with CC genotype had a lower OR of PC in crude model; then this relationship was disappeared after confounder was adjusted. Prostate cancer patients with high urinary total arsenic concentration had high tumor stage and grade. Urinary total arsenic concentration was significantly positively related with plasma selenium and prostate specific antigen concentration. Participants with lower plasma selenium concentration and higher urinary total arsenic concentration compared to those with higher plasma selenium concentration and lower urinary total arsenic concentration had a higher OR of PC with a dose-response relationship.

Keywords: prostate cancer, plasma selenium concentration, urinary arsenic concentration, prostate specific antigen

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Authors: Ronak Khosravi, Mahmood Abbasi Layegh, Siamak Haghipour, Avin Esmaili

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In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function.

Keywords: coefficient features, relevance vector machines, spectral features, support vector machines, temporal features

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Authors: B. S. Premalatha, Kausalya Sahani

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Background: Glomus jugulare tumors arise within the jugular foramen and are commonly seen in females particularly on the left side. Surgical excision of the tumor may cause lower cranial nerve deficits. Cranial nerve involvement produces hoarseness of voice, slurred speech, and dysphagia along with other physical symptoms, thereby affecting the quality of life of individuals. Though oncological clearance is mainly emphasized on while treating these individuals, little importance is given to their communication, voice and swallowing problems, which play a crucial part in daily functioning. Objective: To examine the functions of voice, speech and swallowing outcomes of the subjects, following excision of glomus jugulare tumor. Methods: Two female subjects aged 56 and 62 years had come with a complaint of change in voice, inability to swallow and reduced clarity of speech following surgery for left glomus jugulare tumor were participants of the study. Their surgical information revealed multiple cranial nerve palsies involving the left facial, left superior and recurrent branches of the vagus nerve, left pharyngeal, left soft palate, left hypoglossal and vestibular nerves. Functional outcomes of voice, speech and swallowing were evaluated by perceptual and objective assessment procedures. Assessment included the examination of oral structures and functions, dysarthria by Frenchey dysarthria assessment, cranial nerve functions and swallowing functions. MDVP and Dr. Speech software were used to evaluate acoustic parameters of voice and quality of voice respectively. Results: The study revealed that both the subjects, subsequent to excision of glomus jugulare tumor, showed a varied picture of affected oral structure and functions, articulation, voice and swallowing functions. The cranial nerve assessment showed impairment of the vagus, hypoglossal, facial and glossopharyngeal nerves. Voice examination indicated vocal cord paralysis associated with breathy quality of voice, weak voluntary cough, reduced pitch and loudness range, and poor respiratory support. Perturbation parameters as jitter, shimmer were affected along with s/z ratio indicative of voice fold pathology. Reduced MPD(Maximum Phonation Duration) of vowels indicated that disturbed coordination between respiratory and laryngeal systems. Hypernasality was found to be a prominent feature which reduced speech intelligibility. Imprecise articulation was seen in both the subjects as the hypoglossal nerve was affected following surgery. Injury to vagus, hypoglossal, gloss pharyngeal and facial nerves disturbed the function of swallowing. All the phases of swallow were affected. Aspiration was observed before and during the swallow, confirming the oropharyngeal dysphagia. All the subsystems were affected as per Frenchey Dysarthria Assessment signifying the diagnosis of flaccid dysarthria. Conclusion: There is an observable communication and swallowing difficulty seen following excision of glomus jugulare tumor. Even with complete resection, extensive rehabilitation may be necessary due to significant lower cranial nerve dysfunction. The finding of the present study stresses the need for involvement of as speech and swallowing therapist for pre-operative counseling and assessment of functional outcomes.

Keywords: functional outcome, glomus jugulare tumor excision, multiple cranial nerve impairment, speech and swallowing

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Authors: Mohammed Mustapha Alhaji, Sadiku Salawu

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A clay soil which classified under A-7-6 soil according to AASHTO soil classification system and CH according to the unified soil classification system was stabilized using A-3 soil (AASHTO soil classification system). The clay soil was replaced with 0%, 10%, 20% to 100% A-3 soil, compacted at both the BSL and BSH compaction energy level and using unconfined compressive strength as evaluation criteria. The MDD of the compactions at both the BSL and BSH compaction energy levels showed increase in MDD from 0% A-3 soil replacement to 40% A-3 soil replacement after which the values reduced to 100% A-3 soil replacement. The trend of the OMC with varied A-3 soil replacement is similar to that of MDD but in a reversed order. The OMC reduced from 0% A-3 soil replacement to 40% A-3 soil replacement after which the values increased to 100% A-3 soil replacement. This trend was attributed to the observed reduction in the void ratio from 0% A-3 soil replacement to 40% A-3 soil replacement after which the void ratio increased to 100% A-3 soil replacement. The maximum UCS for clay at varied A-3 soil replacement increased from 272 and 770kN/m2 for BSL and BSH compaction energy level at 0% A-3 soil replacement to 295 and 795kN/m2 for BSL and BSH compaction energy level respectively at 10% A-3 soil replacement after which the values reduced to 22 and 60kN/m2 for BSL and BSH compaction energy level respectively at 70% A-3 soil replacement. Beyond 70% A-3 soil replacement, the mixture cannot be moulded for UCS test.

Keywords: A-3 soil, clay minerals, pozzolanic action, stabilization

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Authors: Anne Giles

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Humans naturally wish they could forget traumatic experiences. To help prevent future harm, however, the human brain has evolved to retain data about experiences of threat, alarm, or violation. When given compassionate support and assistance with thinking helpfully and realistically about traumatic events, most people can adjust to experiencing hardships, albeit with residual sad, unfortunate memories. Persistent, recurrent, intrusive memories, difficulty sleeping, emotion dysregulation, and avoidance of reminders, however, may be symptoms of Post-traumatic Stress Disorder (PTSD). Brain scans show that PTSD affects brain functioning. We currently have no physical means of restoring the system of brain structures and functions involved with PTSD. Medications may ease some symptoms but not others. However, forms of "talk therapy" with cognitive components have been found by researchers to reduce, even resolve, a broad spectrum of trauma symptoms. Many cultures have taboos against talking about hardships. Individuals may present themselves to mental health care professionals with severe, disabling trauma symptoms but, because of cultural norms, be unable to speak about them. In China, for example, relationship expectations may include the belief, "Bad things happening in the family should stay in the family (jiāchǒu bùkě wàiyán 家丑不可外扬)." The concept of "family (jiā 家)" may include partnerships, close and extended families, communities, companies, and the nation itself. In contrast to many trauma therapies, Cognitive Processing Therapy (CPT) for Post-traumatic Stress Disorder asks its participants to focus not on "what" happened but on "why" they think the trauma(s) occurred. The question "why" activates and exercises cognitive functioning. Brain scans of individuals with PTSD reveal executive functioning portions of the brain inadequately active, with emotion centers overly active. CPT conceptualizes PTSD as a network of cognitive distortions that keep an individual "stuck" in this under-functioning and over-functioning dynamic. Through asking participants forms of the question "why," plus offering a protocol for examining answers and relinquishing unhelpful beliefs, CPT assists individuals in consciously reactivating the cognitive, executive functions of their brains, thus restoring normal functioning and reducing distressing trauma symptoms. The culturally sensitive components of CPT that allow people to "talk about it without talking about it" may offer the possibility for worldwide relief from symptoms of trauma.

Keywords: cognitive processing therapy (CPT), cultural norms, post-traumatic stress disorder (PTSD), trauma recovery

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Authors: Alexander N. Savostyanov, Tatyana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Yulia V. Kovas

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The present study compared spectral-power indexes and cortical topography of brain activity in a sample characterized by different levels of trait and mathematical anxiety. 52 healthy Russian-speakers (age 17-32; 30 males) participated in the study. Participants solved an error recognition task under 3 conditions: A lexical condition (simple sentences in Russian), and two numerical conditions (simple arithmetic and complicated algebraic problems). Trait and mathematical anxiety were measured using self-repot questionnaires. EEG activity was recorded simultaneously during task execution. Event-related spectral perturbations (ERSP) were used to analyze spectral-power changes in brain activity. Additionally, sLORETA was applied in order to localize the sources of brain activity. When exploring EEG activity recorded after tasks onset during lexical conditions, sLORETA revealed increased activation in frontal and left temporal cortical areas, mainly in the alpha/beta frequency ranges. When examining the EEG activity recorded after task onset during arithmetic and algebraic conditions, additional activation in delta/theta band in the right parietal cortex was observed. The ERSP plots reveled alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three (lexical, arithmetic and algebraic) conditions. The level of trait anxiety was positively correlated with the amplitude of alpha/beta desynchronization. The level of mathematical anxiety was negatively correlated with the amplitude of theta synchronization and of alpha/beta desynchronization. Overall, trait anxiety was related with an increase in brain activation during task execution, whereas mathematical anxiety was associated with increased inhibitory-related activity. We gratefully acknowledge the support from the №11.G34.31.0043 grant from the Government of the Russian Federation.

Keywords: anxiety, EEG, lexical and numerical error-recognition tasks, alpha/beta desynchronization

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Authors: Chimey Lhamo, Ngawang Tsering

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Traditional Tibetan medicine, known as Sowa Rigpa (Science of healing), originated more than 2500 years ago with an insightful background, and it has been growing significant attention in many Asian countries like China, India, Bhutan, and Nepal. Particularly, the Indian government has targeted Traditional Tibetan medicine as its major Indian medical system, including Ayurveda. Although Traditional Tibetan medicine has been growing interest and has a long history, it is not easily recognized worldwide because it exists only in the Tibetan language and it is neither accessible nor understood by patent examiners at the international patent office, data about Traditional Tibetan medicine is not yet broadly exist in the Internet. There has also been the exploitation of traditional Tibetan medicine increasing. The Traditional Knowledge Digital Library is a database aiming to prevent the patenting and misappropriation of India’s traditional medicine knowledge by using India’s Traditional knowledge Digital Library on Sowa Rigpa in order to prevent its exploitation at international patent with the help of information technology tools and an innovative classification systems-traditional knowledge resource classification (TKRC). As of date, more than 3000 Sowa Rigpa formulations have been transcribed into a Traditional Knowledge Digital Library database. In this paper, we are presenting India's Traditional Knowledge Digital Library for Traditional Tibetan medicine, and this database system helps to preserve and prevent the exploitation of Sowa Rigpa. Gradually it will be approved and accepted globally.

Keywords: traditional Tibetan medicine, India's traditional knowledge digital library, traditional knowledge resources classification, international patent classification

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Authors: Shu-Pin Huang, Pai-Chi Teng, Hao-Han Chang, Chia-Hsin Liu, Yung-Lun Lin, Shu-Chi Wang, Hsin-Chih Yeh, Chih-Pin Chuu, Jiun-Hung Geng, Li-Hsin Chang, Wei-Chung Cheng, Chia-Yang Li

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The emergence of immune checkpoint inhibitors (ICIs) targeting proteins like PD-1 and PD-L1 has changed the treatment paradigm of bladder cancer. However, not all patients benefit from ICIs, with some experiencing early death. There's a significant need for biomarkers associated with the PD-1 pathway in bladder cancer. Current biomarkers focus on tumor PD-L1 expression, but a more comprehensive understanding of PD-1-related biology is needed. Our study has developed a seven-gene risk score panel, employing a comprehensive bioinformatics strategy, which could serve as a potential prognostic and predictive biomarker for bladder cancer. This panel incorporates the FYN, GRAP2, TRIB3, MAP3K8, AKT3, CD274, and CD80 genes. Additionally, we examined the relationship between this panel and immune cell function, utilizing validated tools such as ESTIMATE, TIDE, and CIBERSORT. Our seven-genes panel has been found to be significantly associated with bladder cancer survival in two independent cohorts. The panel was also significantly correlated with tumor infiltration lymphocytes, immune scores, and tumor purity. These factors have been previously reported to have clinical implications on ICIs. The findings suggest the potential of a PD-1 pathway-based transcriptomic panel as a prognostic and predictive biomarker in bladder cancer, which could help optimize treatment strategies and improve patient outcomes.

Keywords: bladder cancer, programmed cell death protein 1, prognostic biomarker, immune checkpoint inhibitors, predictive biomarker

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Authors: Zahow Muoftah

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Traditional manual visual grading of fruits has been one of the agricultural industry’s major challenges due to its laborious nature as well as inconsistency in the inspection and classification process. The main requirements for computer vision and visual processing are some effective techniques for identifying defects and estimating defect areas. Automated defect detection using computer vision and machine learning has emerged as a promising area of research with a high and direct impact on the visual inspection domain. Grading, sorting, and disease detection are important factors in determining the quality of fruits after harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have used computer vision to evaluate the quality level of fruits during post-harvest. Many studies have been conducted to identify diseases and pests that affect the fruits of agricultural crops. However, most previous studies concentrated solely on the diagnosis of a lesion or disease. This study focused on a comprehensive study to identify pests and diseases of apple and banana fruits using detection and classification defects on Banana and Apples by Computer Vision. As a result, the current article includes research from these domains as well. Finally, various pattern recognition techniques for detecting apple and banana defects are discussed.

Keywords: computer vision, banana, apple, detection, classification

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Reza Ehsani, Hawa Ze Jaffar, Ishak Aris

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Ripeness estimation of oil palm fresh fruit is important processes that affect the profitableness and salability of oil palm fruits. The adulthood or ripeness of the oil palm fruits influences the quality of oil palm. Conventional procedure includes physical grading of Fresh Fruit Bunches (FFB) maturity by calculating the number of loose fruits per bunch. This physical classification of oil palm FFB is costly, time consuming and the results may have human error. Hence, many researchers try to develop the methods for ascertaining the maturity of oil palm fruits and thereby, deviously the oil content of distinct palm fruits without the need for exhausting oil extraction and analysis. This research investigates the potential of infrared images (Thermal Images) as a predictor to classify the oil palm FFB ripeness. A total of 270 oil palm fresh fruit bunches from most common cultivar of oil palm bunches Nigresens according to three maturity categories: under ripe, ripe and over ripe were collected. Each sample was scanned by the thermal imaging cameras FLIR E60 and FLIR T440. The average temperature of each bunches were calculated by using image processing in FLIR Tools and FLIR ThermaCAM researcher pro 2.10 environment software. The results show that temperature content decreased from immature to over mature oil palm FFBs. An overall analysis-of-variance (ANOVA) test was proved that this predictor gave significant difference between underripe, ripe and overripe maturity categories. This shows that the temperature as predictors can be good indicators to classify oil palm FFB. Classification analysis was performed by using the temperature of the FFB as predictors through Linear Discriminant Analysis (LDA), Mahalanobis Discriminant Analysis (MDA), Artificial Neural Network (ANN) and K- Nearest Neighbor (KNN) methods. The highest overall classification accuracy was 88.2% by using Artificial Neural Network. This research proves that thermal imaging and neural network method can be used as predictors of oil palm maturity classification.

Keywords: artificial neural network, maturity classification, oil palm FFB, thermal imaging

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Authors: Smruti Mahapatra, Dipankar Biswas, Richard Um, Michael Meggyesy, Riccardo Serra, Noah Gorelick, Steven Marra, Amir Manbachi, Mark G. Luciano

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Intracranial pressure (ICP) is profoundly regulated by the effects of cardiac pulsation and the volume of the incoming blood. Furthermore, these effects on ICP are incremented by the presence of a rigid skull that does not allow for changes in total volume during the cardiac cycle. These factors play a pivotal role in cerebrospinal fluid (CSF) dynamics and distribution, with consequences that are not well understood to this date and that may have a deep effect on the Central Nervous System (CNS) functioning. We designed this study with two specific aims: (a) To study how pulsatility influences local CSF flow, and (b) To study how modulating intracranial pressure affects drug distribution throughout the SAS globally. In order to achieve these aims, we built an elaborate in-vitro model of the SAS closely mimicking the dimensions and flow rates of physiological systems. To modulate intracranial pressure, we used an intracranially implanted, cardiac-gated, volume-oscillating balloon (CADENCE device). Commercially available dye was used to visualize changes in CSF flow. We first implemented two control cases, seeing how the tracer behaves in the presence of pulsations from the brain phantom and the balloon individually. After establishing the controls, we tested 2 cases, having the brain and the balloon pulsate together in sync and out of sync. We then analyzed the distribution area using image processing software. The in-sync case produced a significant increase, 5x times, in the tracer distribution area relative to the out-of-sync case. Assuming that the tracer fluid would mimic blood flow movement, a drug introduced in the SAS with such a system in place would enhance drug distribution and increase the bioavailability of therapeutic drugs to a wider spectrum of brain tissue.

Keywords: blood-brain barrier, cardiac-gated, cerebrospinal fluid, drug delivery, neurosurgery

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Authors: Jie Huo, Jonathan Wu

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Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Milan N. A. Van Der Kuil, Anne M. A. Visser-Meily, Andrea W. M. Evers, Ineke J. M. Van Der Ham

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Navigation ability is essential for autonomy and mobility in daily life. In patients with acquired brain injury, navigation impairment is frequently impaired; however, in this study, we tested the effectiveness of a serious gaming training protocol as a tool for cognitive rehabilitation to reduce navigation impairment. In total, 38 patients with acquired brain injury and subjective navigation complaints completed the experiment, with a partially blind, randomized control trial design. An objective navigation test was used to construct a strengths and weaknesses profile for each patient. Subsequently, patients received personalized compensation training that matched their strengths and weaknesses by addressing an egocentric or allocentric strategy or a strategy aimed at minimizing the use of landmarks. Participants in the experimental condition received psychoeducation and a home-based rehabilitation game with a series of exercises (e.g., map reading, place finding, and turn memorization). The exercises were developed to stimulate the adoption of more beneficial strategies, according to the compensatory approach. Self-reported navigation ability (wayfinding questionnaire), participation level, and objective navigation performance were measured before and after 1 and 4 weeks after completing the six-week training program. Results indicate that the experimental group significantly improved in subjective navigation ability both 1 and 4 weeks after completion of the training, in comparison to the score before training and the scores of the control group. Similarly, goal attainment showed a significant increase after the first and fourth week after training. Objective navigation performance was not affected by the training. This navigation training protocol provides an effective solution to address navigation impairment after acquired brain injury, with clear improvements in subjective performance and goal attainment of the participants. The outcomes of the training should be re-examined after implementation in a clinical setting.

Keywords: spatial navigation, cognitive rehabilitation, serious gaming, acquired brain injury

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Authors: Sankarprasad Bhuniya, Sukhendu Maiti, Eun-Joong Kim, Hyunseung Lee, Jonathan L. Sessler, Kwan Soo Hong, Jong Seung Kim

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A new theranostic strategy is described. It is based on the use of an “all in one” prodrug, namely the biotinylated piperazine-rhodol conjugate 4a. This conjugate, which incorporates the anticancer drug SN-38, undergoes self-immolative cleavage when exposed to biological thiols. This leads to the tumor-targeted release of the active SN-38 payload along with fluorophore 1a. This release is made selective as the result of the biotin functionality. Fluorophore 1a is 32-fold more fluorescent than prodrug 4a. It permits the delivery and release of the SN-38 payload to be monitored easily in vitro and in vivo, as inferred from cell studies and ex vivo analyses of mice xenografts derived HeLa cells, respectively. Prodrug 4a also displays anticancer activity in the HeLa cell murine xenograft tumor model. On the basis of these findings we suggest that the present strategy, which combines within a single agent the key functions of targeting, release, imaging, and treatment, may have a role to play in cancer diagnosis and therapy.

Keywords: theranostic, prodrug, cancer therapy, fluorescence

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Lal Hussain, Wajid Aziz, Sajjad Ahmed Nadeem, Saeed Arif Shah, Abdul Majid

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Brain electrical activity as reflected in Electroencephalography (EEG) have been analyzed and diagnosed using various techniques. Among them, complexity measure, nonlinearity, disorder, and unpredictability play vital role due to the nonlinear interconnection between functional and anatomical subsystem emerged in brain in healthy state and during various diseases. There are many social and economical issues of alcoholic abuse as memory weakness, decision making, impairments, and concentrations etc. Alcoholism not only defect the brains but also associated with emotional, behavior, and cognitive impairments damaging the white and gray brain matters. A recently developed signal analysis method i.e. Multiscale Permutation Entropy (MPE) is proposed to estimate the complexity of long-range temporal correlation time series EEG of Alcoholic and Control subjects acquired from University of California Machine Learning repository and results are compared with MSE. Using MPE, coarsed grained series is first generated and the PE is computed for each coarsed grained time series against the electrodes O1, O2, C3, C4, F2, F3, F4, F7, F8, Fp1, Fp2, P3, P4, T7, and T8. The results computed against each electrode using MPE gives higher significant values as compared to MSE as well as mean rank differences accordingly. Likewise, ROC and Area under the ROC also gives higher separation against each electrode using MPE in comparison to MSE.

Keywords: electroencephalogram (EEG), multiscale permutation entropy (MPE), multiscale sample entropy (MSE), permutation entropy (PE), mann whitney test (MMT), receiver operator curve (ROC), complexity measure

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Authors: Joanna Marie A. Paulino-Morente, Vaneza Valentina L. Penolio, Grace Sabado

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Ovarian cancer is extremely hard to diagnose in its early stages, and those afflicted at the time of diagnosis are typically asymptomatic and in the late stages of the disease, with metastasis to other organs. Ovarian cancers often occur sporadically, with only 5% associated with hereditary mutations. Mutations in the BRCA1 and BRCA2 tumor suppressor genes have been found to be responsible for the majority of hereditary ovarian cancers. One type of ovarian tumor is Malignant Mixed Mullerian Tumor (MMMT), which is a very rare and aggressive type, accounting for only 1% of all ovarian cancers. Reported is a case of a 43-year-old G3P3 (3003), who came into our institution due to a 2-month history of difficulty of breathing. Family history reveals that her eldest and younger sisters both died of ovarian malignancy, with her younger sister having a histopathology report of endometrioid ovarian carcinoma, left ovary stage IIIb. She still has 2 asymptomatic sisters. Physical examination pointed to pleural effusion of right lung, and presence of bilateral ovarian new growth, which had a Sassone score of 13. Admitting Diagnosis was G3P3 (3003), Ovarian New Growth, bilateral, Malignant; Pleural effusion secondary to malignancy. BRCA was requested to establish a hereditary mutation; however, the patient had no funds. Once the patient was stabilized, TAHBSO with surgical staging was performed. Intraoperatively, the pelvic cavity was occupied by firm, irregularly shaped ovaries, with a colorectal metastasis. Microscopic sections from both ovaries and the colorectal metastasis had pleomorphic tumor cells lined by cuboidal to columnar epithelium exhibiting glandular complexity, displaying nuclear atypia and increased nuclear-cytoplasmic ratio, which are infiltrating the stroma, consistent with the features of Malignant Mixed Mullerian Tumor, since MMMT is composed histologically of malignant epithelial and sarcomatous elements. In conclusion, discussed is the clinic-pathological feature of a patient with primary ovarian Malignant Mixed Mullerian Tumor, a rare malignancy comprising only 1% of all ovarian neoplasms. Also, by understanding the hereditary ovarian cancer syndromes and its relation to this patient, it cannot be overemphasized that a comprehensive family history is really fundamental for early diagnosis. The familial association of the disease, given that the patient has two sisters who were diagnosed with an advanced stage of ovarian cancer and succumbed to the disease at a much earlier age than what is reported in the general population, points to a possible hereditary syndrome which occurs in only 5% of ovarian neoplasms. In a low-resource setting, being in a third world country, the following will be recommended for monitoring and/or screening women who are at high risk for developing ovarian cancer, such as the remaining sisters of the patient: 1) Physical examination focusing on the breast, abdomen, and rectal area every 6 months. 2) Transvaginal sonography every 6 months. 3) Mammography annually. 4) CA125 for postmenopausal women. 5) Genetic testing for BRCA1 and BRCA2 will be reserved for those who are financially capable.

Keywords: BRCA, hereditary breast-ovarian cancer syndrome, malignant mixed mullerian tumor, ovarian cancer

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper introduces an original method of parametric optimization of the structure for multimodal decision-level fusion scheme which combines the results of the partial solution of the classification task obtained from assembly of the mono-modal classifiers. As a result, a multimodal fusion classifier which has the minimum value of the total error rate has been obtained.

Keywords: classification accuracy, fusion solution, total error rate, multimodal fusion classifier

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Authors: Hammad T. Janjuhah, Josep Sanjuan, Mohamed K. Salah

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Biological and chemical activities in carbonates are responsible for the complexity of the pore system. Primary porosity is generally of natural origin while secondary porosity is subject to chemical reactivity through diagenetic processes. To understand the integrated part of hydrocarbon exploration, it is necessary to understand the carbonate pore system. However, the current porosity classification scheme is limited to adequately predict the petrophysical properties of different reservoirs having various origins and depositional environments. Rock classification provides a descriptive method for explaining the lithofacies but makes no significant contribution to the application of porosity and permeability (poro-perm) correlation. The Central Luconia carbonate system (Malaysia) represents a good example of pore complexity (in terms of nature and origin) mainly related to diagenetic processes which have altered the original reservoir. For quantitative analysis, 32 high-resolution images of each thin section were taken using transmitted light microscopy. The quantification of grains, matrix, cement, and macroporosity (pore types) was achieved using a petrographic analysis of thin sections and FESEM images. The point counting technique was used to estimate the amount of macroporosity from thin section, which was then subtracted from the total porosity to derive the microporosity. The quantitative observation of thin sections revealed that the mouldic porosity (macroporosity) is the dominant porosity type present, whereas the microporosity seems to correspond to a sum of 40 to 50% of the total porosity. It has been proven that these Miocene carbonates contain a significant amount of microporosity, which significantly complicates the estimation and production of hydrocarbons. Neglecting its impact can increase uncertainty about estimating hydrocarbon reserves. Due to the diversity of geological parameters, the application of existing porosity classifications does not allow a better understanding of the poro-perm relationship. However, the classification can be improved by including the pore types and pore structures where they can be divided into macro- and microporosity. Such studies of microporosity identification/classification represent now a major concern in limestone reservoirs around the world.

Keywords: overview of porosity classification, reservoir characterization, microporosity, carbonate reservoir

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Authors: Adesuyi Ayodeji Steve, Zahn Munch

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This study investigates the use of MODIS NDVI to identify agricultural land cover change areas on an annual time step (2007 - 2012) and characterize the trend in the study area. An ISODATA classification was performed on the MODIS imagery to select only the agricultural class producing 3 class groups namely: agriculture, agriculture/semi-natural, and semi-natural. NDVI signatures were created for the time series to identify areas dominated by cereals and vineyards with the aid of ancillary, pictometry and field sample data. The NDVI signature curve and training samples aided in creating a decision tree model in WEKA 3.6.9. From the training samples two classification models were built in WEKA using decision tree classifier (J48) algorithm; Model 1 included ISODATA classification and Model 2 without, both having accuracies of 90.7% and 88.3% respectively. The two models were used to classify the whole study area, thus producing two land cover maps with Model 1 and 2 having classification accuracies of 77% and 80% respectively. Model 2 was used to create change detection maps for all the other years. Subtle changes and areas of consistency (unchanged) were observed in the agricultural classes and crop practices over the years as predicted by the land cover classification. 41% of the catchment comprises of cereals with 35% possibly following a crop rotation system. Vineyard largely remained constant over the years, with some conversion to vineyard (1%) from other land cover classes. Some of the changes might be as a result of misclassification and crop rotation system.

Keywords: change detection, land cover, modis, NDVI

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Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

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Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

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Authors: Mai M. Farid, Ximeng Yang, Tomoharu Kuboyama, Yuna Inada, Chihiro Tohda

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Intro: Trigonella foenum-graecum (Fenugreek), from Fabaceae family is a well-known plant traditionally used as food and medicine. Many pharmacological effects of Trigonella foenum- graecum seeds extract (TF extract) were evaluated such as anti-diabetic, anti-tumor and anti-dementia effects using in vivo models. Regarding the anti-dementia effects of TF extract, diabetic rats, aluminum chloride-induced amnesia rats and scopolamine-injected mice were used previously for evaluation, which are not well established as Alzheimer’s disease models. In addition, those previous studies, active constituents in TF extract for memory function were not identified. Method: This study aimed to clarify the effect of TF extract on Alzheimer’s disease model, 5XFAD mouse that overexpresses mutated APP and PS1 genes and determine the major active constituent in the brain after oral intake of TF extract. Results: Trigonelline was detected in the cerebral cortex of 5XFAD mice after 24 hours of oral administration of TF extract by LC-MS/MS. Oral administration of TF extract for 17 days improved object location memory in 5XFAD mice. Conclusion: These results suggest that TF extract and its active constituents could be an expected therapeutic candidate for Alzheimer’s disease.

Keywords: Alzheimer's disease, LC-MS/MS, memory recovery, Trigonella foenum-graecum Seeds, 5XFAD mice

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Authors: Ismail Elkhrachy

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Determination of land use changing is an important component of regional planning for applications ranging from urban fringe change detection to monitoring change detection of land use. This data are very useful for natural resources management.On the other hand, the technologies and methods of change detection also have evolved dramatically during past 20 years. So it has been well recognized that the change detection had become the best methods for researching dynamic change of land use by multi-temporal remotely-sensed data. The objective of this paper is to assess, evaluate and monitor land use change surrounding the area of Najran city, Kingdom of Saudi Arabia (KSA) using Landsat images (June 23, 2009) and ETM+ image(June. 21, 2014). The post-classification change detection technique was applied. At last,two-time subset images of Najran city are compared on a pixel-by-pixel basis using the post-classification comparison method and the from-to change matrix is produced, the land use change information obtained.Three classes were obtained, urban, bare land and agricultural land from unsupervised classification method by using Erdas Imagine and ArcGIS software. Accuracy assessment of classification has been performed before calculating change detection for study area. The obtained accuracy is between 61% to 87% percent for all the classes. Change detection analysis shows that rapid growth in urban area has been increased by 73.2%, the agricultural area has been decreased by 10.5 % and barren area reduced by 7% between 2009 and 2014. The quantitative study indicated that the area of urban class has unchanged by 58.2 km〗^2, gained 70.3 〖km〗^2 and lost 16 〖km〗^2. For bare land class 586.4〖km〗^2 has unchanged, 53.2〖km〗^2 has gained and 101.5〖km〗^2 has lost. While agriculture area class, 20.2〖km〗^2 has unchanged, 31.2〖km〗^2 has gained and 37.2〖km〗^2 has lost.

Keywords: land use, remote sensing, change detection, satellite images, image classification

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Authors: Atefeh Saljooghi Khoshkar, Jafar Hassanpour

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One of the main problems of the design stage relating to many tunneling projects is the lack of an appropriate standard for the provision of engineering geological data in a predefined format. In particular, this is more reflected in highway and railroad tunnel projects in which there is a number of tunnels and different professional teams involved. In this regard, comprehensive software needs to be designed using the accepted methods in order to help engineering geologists to prepare standard reports, which contain sufficient input data for the design stage. Regarding this necessity, applied software has been designed using macro capabilities and Visual Basic programming language (VBA) through Microsoft Excel. In this software, all of the engineering geological input data, which are required for designing different parts of tunnels, such as discontinuities properties, rock mass strength parameters, rock mass classification systems, boreability classification, the penetration rate, and so forth, can be calculated and reported in a standard format.

Keywords: engineering geology, rock mass classification, rock mechanic, tunnel

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