Search results for: brain tumor segmentation

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

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The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

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Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Nick Weir, Robert Stevens, Alan Hargreaves, Martin McGinnity, Chris Tinsley

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Hydrophobic materials have previously demonstrated the ability to elevate cell-cell interactions and promote the formation of neural networks whilst aligned nanofibers demonstrate the ability to induce extensive neurite outgrowth in an aligned manner. Hydrophobic materials typically elicit an immune response upon implantation and thus materials used for implantation are typically hydrophilic. Poly-L-lactic acid (PLLA) is a hydrophobic, non-immunogenic, FDA approved material that can be electrospun to form aligned nanofibers. Primary rat cortical neurons cultured for 10 days on aligned PLLA nanofibers formed 3D cell clusters, approximately 800 microns in diameter. Neurites that extended from these clusters were highly aligned due to the alignment of the nanofibers they were cultured upon and fasciculation was also evident. Plasma treatment of the PLLA nanofibers prior to seeding of cells significantly reduced the hydrophobicity and abolished the cluster formation and neurite fasciculation, whilst reducing the extent and directionality of neurite outgrowth; it is proposed that hydrophobicity induces the changes to cellular behaviors. Aligned PLLA nanofibers induced the formation of a structure that mimics the grey-white matter compartmentalization that is observed in vivo and thus represents a step forward in generating organoids or biomaterial-based implants. Upon implantation into the brain, the biomaterial architectures described here may provide a useful platform for both brain repair and brain remodeling initiatives.

Keywords: hydrophobicity, nanofibers, neurite fasciculation, neurite outgrowth, PLLA

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Authors: Naouel Zoghlami

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Spoken-word recognition involves the simultaneous activation of potential word candidates which compete with each other for final correct recognition. In continuous speech, the activation-competition process gets more complicated due to speech reductions existing at word boundaries. Lexical processing is more difficult in L2 than in L1 because L2 listeners often lack phonetic, lexico-semantic, syntactic, and prosodic knowledge in the target language. In this study, we investigate the on-line lexical segmentation hypotheses that French listeners of L2 English form and then revise as subsequent perceptual evidence is revealed. Our purpose is to shed further light on the processes of L2 spoken-word recognition in context and better understand L2 listening difficulties through a comparison of skilled and unskilled reactions at the point where their working hypothesis is rejected. We use a variant of the gating experiment in which subjects transcribe an English sentence presented in increments of progressively greater duration. The spoken sentence was “And this amazing athlete has just broken another world record”, chosen mainly because it included common reductions and phonetic features in English, such as elision and assimilation. Our preliminary results show that there is an important difference in the manner in which proficient and less-proficient L2 listeners handle connected speech. Less-proficient listeners delay recognition of words as they wait for lexical and syntactic evidence to appear in the gates. Further statistical results are currently being undertaken.

Keywords: gating paradigm, spoken word recognition, online lexical segmentation, L2 listening

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Authors: Ahmed Atwa, Ashraf Hafez, Mohamed Abdelhameed, Adel Nabeeh, Mohamed Dawaba, Tamer Helmy

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Introduction and Objective: Tumour staging and grading do not usually reflect the future behavior of Wilms' tumor (WT) regarding mortality. Therefore, in this study, P53, Ki67 and cyclin A immunohistochemistry were used in a trial to predict WT cancer-specific survival (CSS). Methods: In this nonconcurrent cohort study, patients' archived data, including age at presentation, gender, history, clinical examination and radiological investigations, were retrieved then the patients were reviewed at the outpatient clinic of a tertiary care center by history-taking, clinical examination and radiological investigations to detect the oncological outcome. Cases that received preoperative chemotherapy or died due to causes other than WT were excluded. Formalin-fixed, paraffin-embedded specimens obtained from the previously preserved blocks at the pathology laboratory were taken on positively charged slides for IHC with p53, Ki67 and cyclin A. All specimens were examined by an experienced histopathologist devoted to the urological practice and blinded to the patient's clinical findings. P53 and cyclin A staining were scored as 0 (no nuclear staining),1 (<10% nuclear staining), 2 (10-50% nuclear staining) and 3 (>50% nuclear staining). Ki67 proliferation index (PI) was graded as low, borderline and high. Results: Of the 75 cases, 40 (53.3%) were males and 35 (46.7%) were females, and the median age was 36 months (2-216). With a mean follow-up of 78.6±31 months, cancer-specific mortality (CSM) occurred in 15 (20%) and 11 (14.7%) patients, respectively. Kaplan-Meier curve was used for survival analysis, and groups were compared using the Log-rank test. Multivariate logistic regression and Cox regression were not used because only one variable (cyclin A) had shown statistical significance (P=.02), whereas the other significant factor (residual tumor) had few cases. Conclusions: Cyclin A IHC should be considered as a marker for the prediction of WT CSS. Prospective studies with a larger sample size are needed.

Keywords: wilms’ tumour, nephroblastoma, urology, survival

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Authors: Luis Enrique Bautista-Hinojosa, Luis A. Herrera, Cristian Arriaga-Canon

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Text should be written in the third person. Please avoid using "I" “my” or the pronoun "one". It is best to say "It is believed..." rather than "I believe..." or "One believes...".

Keywords: transcriptomics, co-expression, cancer, biomarkers

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Authors: Mohamed Hafid, Marcel Lacroix

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This study aimed at developing an inverse heat transfer approach for predicting the time-varying freezing front and the temperature distribution of tumors during cryosurgery. Using a temperature probe pressed against the layer of tumor, the inverse approach is able to predict simultaneously the metabolic heat generation and the blood perfusion rate of the tumor. Once these parameters are predicted, the temperature-field and time-varying freezing fronts are determined with the direct model. The direct model rests on one-dimensional Pennes bioheat equation. The phase change problem is handled with the enthalpy method. The Levenberg-Marquardt Method (LMM) combined to the Broyden Method (BM) is used to solve the inverse model. The effect (a) of the thermal properties of the diseased tissues; (b) of the initial guesses for the unknown thermal properties; (c) of the data capture frequency; and (d) of the noise on the recorded temperatures is examined. It is shown that the proposed inverse approach remains accurate for all the cases investigated.

Keywords: cryosurgery, inverse heat transfer, Levenberg-Marquardt method, thermal properties, Pennes model, enthalpy method

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Authors: Nurkhairul Bariyah Baharun, Afzan Adam, Reena Rahayu Md Zin

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Tumor microenvironment (TME) in breast cancer is mainly composed of cancer cells, immune cells, and stromal cells. The interaction between cancer cells and their microenvironment plays an important role in tumor development, progression, and treatment response. The TME in breast cancer includes tumor-infiltrating lymphocytes (TILs) that are implicated in killing tumor cells. TILs can be found in tumor stroma (sTILs) and within the tumor (iTILs). TILs in triple negative breast cancer (TNBC) have been demonstrated to have prognostic and potentially predictive value. The international Immune-Oncology Biomarker Working Group (TIL-WG) had developed a guideline focus on the assessment of sTILs using hematoxylin and eosin (H&E)-stained slides. According to the guideline, the pathologists use “eye balling” method on the H&E stained- slide for sTILs assessment. This method has low precision, poor interobserver reproducibility, and is time-consuming for a comprehensive evaluation, besides only counted sTILs in their assessment. The TIL-WG has therefore recommended that any algorithm for computational assessment of TILs utilizing the guidelines provided to overcome the limitations of manual assessment, thus providing highly accurate and reliable TILs detection and classification for reproducible and quantitative measurement. This study is carried out to develop a TNBC digital whole slide image (WSI) dataset from H&E-stained slides and IHC (CD4+ and CD8+) stained slides. TNBC cases were retrieved from the database of the Department of Pathology, Hospital Canselor Tuanku Muhriz (HCTM). TNBC cases diagnosed between the year 2010 and 2021 with no history of other cancer and available block tissue were included in the study (n=58). Tissue blocks were sectioned approximately 4 µm for H&E and IHC stain. The H&E staining was performed according to a well-established protocol. Indirect IHC stain was also performed on the tissue sections using protocol from Diagnostic BioSystems PolyVue™ Plus Kit, USA. The slides were stained with rabbit monoclonal, CD8 antibody (SP16) and Rabbit monoclonal, CD4 antibody (EP204). The selected and quality-checked slides were then scanned using a high-resolution whole slide scanner (Pannoramic DESK II DW- slide scanner) to digitalize the tissue image with a pixel resolution of 20x magnification. A manual TILs (sTILs and iTILs) assessment was then carried out by the appointed pathologist (2 pathologists) for manual TILs scoring from the digital WSIs following the guideline developed by TIL-WG 2014, and the result displayed as the percentage of sTILs and iTILs per mm² stromal and tumour area on the tissue. Following this, we aimed to develop an automated digital image scoring framework that incorporates key elements of manual guidelines (including both sTILs and iTILs) using manually annotated data for robust and objective quantification of TILs in TNBC. From the study, we have developed a digital dataset of TNBC H&E and IHC (CD4+ and CD8+) stained slides. We hope that an automated based scoring method can provide quantitative and interpretable TILs scoring, which correlates with the manual pathologist-derived sTILs and iTILs scoring and thus has potential prognostic implications.

Keywords: automated quantification, digital pathology, triple negative breast cancer, tumour infiltrating lymphocytes

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Authors: Jonathan Gong

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deep learning, image processing, machine learning

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Authors: Mahdi Asghari Ozma

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Background and Objective:Maclurapomifera (Rafin.) Schneider, known as osage orange, is a north american native plant which has multiple applications in herbal medicine. The extract of this plant has many therapeutic effects, including antimicrobial, anti-tumor, anti-inflammation, etc., that discussed in this study. Materials and Methods: For this study, the keywords "Maclurapomifera", "osage orange, ""herbal medicine ", and "plant extract" in the databases PubMed and Google Scholar between 2002 and 2021 were searched, and 20 articles were chosen, studied and analyzed. Results: Due to the increased resistance of microbes to antibiotics, the need for antimicrobial plants is increasing. Maclurapomifera is one of the plants with antimicrobial properties that can affect all microbes, especially Gram-negative bacteria, and fungi. This plant also has anti-tumor, anti-inflammatory, anti-oxidant, anti-aging, antiviral, anti-fungal, anti-ulcerogenic, anti-diabetic, and anti-nociceptive effects, which can be used as a substance with many amazing therapeutic applications. Conclusion: These results suggest that the extract of Maclurapomifera can be used in clinical medicine as a remedial agent, which can be substituted for chemical drugs or help them in the treatment of diseases.

Keywords: maclura pomifera, osage orange, herbal medicine, plant extract

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Authors: Yi Li, Yinan Zheng, Ya Ke, Yungwing Ho

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Motor learning is a process that frequently happens among humans and rodents, which is defined as the changes in the capability to perform a skill that is conformed to have a relatively permanent improvement through practice or experience. There are many ways to learn a behavior, among which is observational learning. Observational learning is the process of learning by watching the behaviors of others, for example, a child imitating parents, learning a new sport by watching the training videos or solving puzzles by watching the solutions. Many research explores observational learning in humans and primates. However, the neuronal mechanism of which, especially observational motor learning, was uncertain. It’s well accepted that mirror neurons are essential in the observational learning process. These neurons fire when the primate performs a goal-directed action and sees someone else demonstrating the same action, which suggests they have high firing activity both completing and watching the behavior. The mirror neurons are assumed to mediate imitation or play a critical and fundamental role in action understanding. They are distributed in many brain areas of primates, i.e., posterior parietal cortex (PPC), premotor cortex (M2), and primary motor cortex (M1) of the macaque brain. However, few researchers report the existence of mirror neurons in rodents. To verify the existence of mirror neurons and the possible role in motor learning in rodents, we performed customised string-pulling behavior combined with multiple behavior analysis methods, photometry, electrophysiology recording, c-fos staining and optogenetics in healthy mice. After five days of training, the demonstrator (demo) mice showed a significantly quicker response and shorter time to reach the string; fast, steady and accurate performance to pull down the string; and more precisely grasping the beads. During three days of observation, the mice showed more facial motions when the demo mice performed behaviors. On the first training day, the observer reduced the number of trials to find and pull the string. However, the time to find beads and pull down string were unchanged in the successful attempts on the first day and other training days, which indicated successful action understanding but failed motor learning through observation in mice. After observation, the post-hoc staining revealed that the c-fos expression was increased in the cognitive-related brain areas (medial prefrontal cortex) and motor cortices (M1, M2). In conclusion, this project indicated that the observation led to a better understanding of behaviors and activated the cognitive and motor-related brain areas, which suggested the possible existence of mirror neurons in these brain areas.

Keywords: observation, motor learning, string-pulling behavior, prefrontal cortex, motor cortex, cognitive

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Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

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The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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Authors: Amar Ranjan, Julieana Durai, Pranay Tanwar

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Background &Introduction: Ovarian cancer is one of the most common malignant tumor in the female. 70% of the cases of ovarian cancer are diagnosed at an advanced stage. The five-year survival rate associated with ovarian cancer is less than 30%. The early diagnosis of ovarian cancer becomes a key factor in improving the survival rate of patients. Presently, CAl25 (carbohydrate antigen125) is used for the diagnosis and therapeutic monitoring of ovarian cancer, but its sensitivity and specificity is not ideal. The introduction of HE4, human epididymis protein 4 has attracted much attention. HE4 has a sensitivity and specificity of 72.9% and 95% for differentiating between benign and malignant adnexal masses, which is better than CA125 detection.  Methods: Serum HE4 and CA -125 were estimated using the chemiluminescence method. Our cases were 40 epithelial ovarian cancer, 9 benign ovarian tumor, 29 benign gynaecological diseases and 13 healthy individuals. This group include healthy woman those who have undergoing family planning and menopause-related medical consultations and they are negative for ovarian mass. Optimal cut off values for HE4 and CA125 were 55.89pmol/L and 40.25U/L respectively (determined by statistical analysis). Results: The level of HE4 was raised in all ovarian cancer patients (n=40) whereas CA125 levels were normal in 6/40 ovarian cancer patients, which were the cases of OC confirmed by histopathology. There is a significant decrease in the level of HE4 with comparison to CA125 in benign ovarian tumor cases. Both the levels of HE4 and CA125 were raised in the nonovarian cancer group, which includes cancer of endometrium and cervix. In the healthy group, HE4 was normal in all patients except in one case of the rudimentary horn, and the reason for this raised HE4 level is due to the incomplete development of uterus whereas CA125 was raised in 3 cases. Conclusions: Findings showed that the serum level of HE4 is an important indicator in the diagnosis of ovarian cancer, and it also distinguishes between benign and malignant pelvic masses. However, a combination of HE4 and CA125 panel will be extremely valuable in improving the diagnostic efficiency of ovarian cancer. These findings of our study need to be validated in the larger cohort of patients.

Keywords: human epididymis protein 4, ovarian cancer, diagnosis, benign lesions

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Authors: Palak V. Patel, Jessica Pixley, Steven R. Feldman

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Introduction: Basal cell carcinoma (BCC) is the most common skin cancer worldwide and requires substantial resources to treat. When choosing between indicated therapies, providers consider their associated adverse effects, efficacy, cosmesis, and function preservation. The patient’s tumor burden, infiltrative risk, and risk of tumor recurrence are also considered. Treatment cost is often left out of these discussions. This can lead to financial toxicity, which describes the harm and quality of life reductions inflicted by high care costs. Methods: We studied the guidelines set forth by the American Academy of Dermatology for the treatment of BCC. A PubMed literature search was conducted to identify the costs of each recommended therapy. We discuss costs alongside treatment efficacy and side-effect profile. Results: Surgical treatment for BCC can be cost-effective if the appropriate treatment is selected for the presenting tumor. Curettage and electrodesiccation can be used in low-grade, low-recurrence tumors in aesthetically unimportant areas. The benefits of cost-conscious care are not likely to be outweighed by the risks of poor cosmesis or tumor return ($471 BCC of the cheek). When tumor burden is limited, MMS offers better cure rates and lower recurrence rates than surgical excision, and with comparable costs (MMS $1263; SE $949). Surgical excision with permanent sections may be indicated when tumor burden is more extensive or if molecular testing is necessary. The utility of surgical excision with frozen sections, which costs substantially more than MMS without comparable outcomes, is less clear (SE with frozen sections $2334-$3085). Less data exists on non-surgical treatments for BCC. These techniques cost less, but recurrence-risk is high. Side-effects of nonsurgical treatment are limited to local skin reactions, and cosmesis is good. Cryotherapy, 5-FU, and MAL-PDT are all more affordable than surgery, but high recurrence rates increase risk of secondary financial and psychosocial burden (recurrence rates 21-39%; cost $100-270). Radiation therapy offers better clearance rates than other nonsurgical treatments but is associated with similar recurrence rates and a significantly larger financial burden ($2591-$3460 BCC of the cheek). Treatments for advanced or metastatic BCC are extremely costly, but few patients require their use, and the societal cost burden remains low. Vismodegib and sonidegib have good response rates but substantial side effects, and therapy should be combined with multidisciplinary care and palliative measures. Expert-review has found sonidegib to be the less expensive and more efficacious option (vismodegib $128,358; sonidegib $122,579). Platinum therapy, while not FDA-approved, is also effective but expensive (~91,435). Immunotherapy offers a new line of treatment in patients intolerant of hedgehog inhibitors ($683,061). Conclusion: Dermatologists working within resource-compressed practices and with resource-limited patients must prudently manage the healthcare dollar. Surgical therapies for BCC offer the lowest risk of recurrence at the most reasonable cost. Non-surgical therapies are more affordable, but high recurrence rates increase the risk of secondary financial and psychosocial burdens. Treatments for advanced BCC are incredibly costly, but the low incidence means the overall cost to the system is low.

Keywords: nonmelanoma skin cancer, basal cell skin cancer, squamous cell skin cancer, cost of care

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Authors: Yihenew Simegniew Birhan, Hsieh Chih Tsai

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The recent advancements in synthetic chemistry and nanotechnology fostered the development of different nanocarriers for enhanced intracellular delivery of pharmaceutical agents to tumor cells. Polymeric micelles (PMs), characterized by small size, appreciable drug loading capacity (DLC), better accumulation in tumor tissue via enhanced permeability and retention (EPR) effect, and the ability to avoid detection and subsequent clearance by the mononuclear phagocyte (MNP) system, are convenient to improve the poor solubility, slow absorption and non-selective biodistribution of payloads embedded in their hydrophobic cores and hence, enhance the therapeutic efficacy of chemotherapeutic agents. Recently, redox-responsive polymeric micelles have gained significant attention for the delivery and controlled release of anticancer drugs in tumor cells. In this study, we synthesized redox-responsive diselenide bond containing amphiphilic polymer, Bi(mPEG-PLGA)-Se₂ from mPEG-PLGA, and 3,3'-diselanediyldipropanoic acid (DSeDPA) using DCC/DMAP as coupling agents. The successful synthesis of the copolymers was verified by different spectroscopic techniques. Above the critical micelle concentration, the amphiphilic copolymer, Bi(mPEG-PLGA)-Se₂, self-assembled into stable micelles. The DLS data indicated that the hydrodynamic diameter of the micelles (123.9 ± 0.85 nm) was suitable for extravasation into the tumor cells through the EPR effect. The drug loading content (DLC) and encapsulation efficiency (EE) of DOX-loaded micelles were found to be 6.61 wt% and 54.9%, respectively. The DOX-loaded micelles showed initial burst release accompanied by sustained release trend where 73.94% and 69.54% of encapsulated DOX was released upon treatment with 6mM GSH and 0.1% H₂O₂, respectively. The biocompatible nature of Bi(mPEG-PLGA)-Se₂ copolymer was confirmed by the cell viability study. In addition, the DOX-loaded micelles exhibited significant inhibition against HeLa cells (44.46%), at a maximum dose of 7.5 µg/mL. The fluorescent microscope images of HeLa cells treated with 3 µg/mL (equivalent DOX concentration) revealed efficient internalization and accumulation of DOX-loaded Bi(mPEG-PLGA)-Se₂ micelles in the cytosol of cancer cells. In conclusion, the intelligent, biocompatible, and the redox stimuli-responsive behavior of Bi(mPEG-PLGA)-Se₂ copolymer marked the potential applications of diselenide-linked mPEG-PLGA micelles for the delivery and on-demand release of chemotherapeutic agents in cancer cells.

Keywords: anticancer drug delivery, diselenide bond, polymeric micelles, redox-responsive

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Authors: Riaan Kleyn

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Mass wine production companies across the globe are provided with grapes from winegrowers that predominantly utilize mechanical harvesting machines to harvest wine grapes. Mechanical harvesting accelerates the rate at which grapes are harvested, allowing grapes to be delivered faster to meet the demands of wine cellars. The disadvantage of the mechanical harvesting method is the inclusion of material-other-than-grapes (MOG) in the harvested wine grape loads arriving at the cellar which degrades the quality of wine that can be produced. Currently, wine cellars do not have a method to determine the amount of MOG present within wine grape loads. This paper seeks to find an optimal computer vision method capable of detecting the amount of MOG within a wine grape load. A MOG detection method will encourage winegrowers to deliver MOG-free wine grape loads to avoid penalties which will indirectly enhance the quality of the wine to be produced. Traditional image segmentation methods were compared to deep learning segmentation methods based on images of wine grape loads that were captured at a wine cellar. The Mask R-CNN model with a ResNet-50 convolutional neural network backbone emerged as the optimal method for this study to determine the amount of MOG in an image of a wine grape load. Furthermore, a statistical analysis was conducted to determine how the MOG on the surface of a grape load relates to the mass of MOG within the corresponding grape load.

Keywords: computer vision, wine grapes, machine learning, machine harvested grapes

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Anthony S. Machi, Joseph Minardi

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We present a case report of left atrial myxoma diagnosed by bedside transesophageal (TEE) ultrasound. Left atrial myxoma is the most common benign cardiac tumor and can obstruct blood flow and cause valvular insufficiency. Common symptoms consist of dyspnea, pulmonary edema and other features of left heart failure in addition to thrombus release in the form of tumor fragments. The availability of bedside ultrasound equipment is essential for the quick diagnosis and treatment of various emergency conditions including cardiac neoplasms. A 48-year-old Caucasian female with a four-year history of an untreated renal mass and anemia presented to the ED with two months of sharp, intermittent, bilateral flank pain radiating into the abdomen. She also reported intermittent vomiting and constipation along with generalized body aches, night sweats, and 100-pound weight loss over last year. She had a CT in 2013 showing a 3 cm left renal mass and a second CT in April 2016 showing a 3.8 cm left renal mass along with a past medical history of diverticulosis, chronic bronchitis, dyspnea on exertion, uncontrolled hypertension, and hyperlipidemia. Her maternal family history is positive for breast cancer, hypertension, and Type II Diabetes. Her paternal family history is positive for stroke. She was a current everyday smoker with an 11 pack/year history. Alcohol and drug use were denied. Physical exam was notable for a Grade II/IV systolic murmur at the right upper sternal border, dyspnea on exertion without angina, and a tender left lower quadrant. Her vitals and labs were notable for a blood pressure of 144/96, heart rate of 96 beats per minute, pulse oximetry of 96%, hemoglobin of 7.6 g/dL, hypokalemia, hypochloremia, and multiple other abnormalities. Physicians ordered a CT to evaluate her flank pain which revealed a 7.2 x 8.9 x 10.5 cm mixed cystic/solid mass in the lower pole of the left kidney and a filling defect in the left atrium. Bedside TEE was ordered to follow up on the filling defect. TEE reported an ejection fraction of 60-65% and visualized a mobile 6 x 3 cm mass in the left atrium attached to the interatrial septum extending into the mitral valve. Cardiothoracic Surgery and Urology were consulted and confirmed a diagnosis of left atrial myxoma and clear cell renal cell carcinoma. The patient returned a week later due to worsening nausea and vomiting and underwent emergent nephrectomy, lymph node dissection, and colostomy due to a necrotic colon. Her condition declined over the next four months due to lung and brain metastases, infections, and other complications until she passed away.

Keywords: bedside ultrasound, echocardiography, emergency medicine, left atrial myxoma

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Authors: Ali A. Bazzi, Ameer Hamza, Riley O’Hara, Kimberly Kado, Karen H. Hagglund, Lamia Fathallah, Robert T. Morris

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Introduction: Endometrial Cancer is a common gynecologic malignancy primarily treated with complete surgical staging, which may include complete pelvic and para-aortic lymphadenectomy. The role of lymphadenectomy is controversial, especially the intraoperative indications for the procedure. Three factors are important in decision to proceed with lymphadenectomy: Myometrial invasion, maximum tumor dimension, and histology. Many institutions incorporate these criteria in varying degrees in the decision to proceed with lymphadenectomy. This investigation assesses the use of intraoperatively measured MTD with and without pre-operative histologic grade. Methods: This study compared retrospectively EEC patients with intraoperatively measured MTD ≤2 cm to those with MTD >2 cm from January 1, 2002 to August 31, 2017. This assessment compared those with MTD ≤ 2cm with endometrial biopsy (EB) grade 1-2 to patients with MTD > 2cm with EB grade 3. Lymph node metastasis (LNM), recurrence, and survival were compared in these groups. Results: This study reviewed 222 patient cases. In tumors > 2 cm, LNM occurred in 20% cases while in tumors ≤ 2 cm, LNM was found in 6% cases (p=0.04). Recurrence and mean survival based on last follow up visit in these two groups were not statistically different (p=0.78 and 0.36 respectively). Data demonstrated a trend that when combined with preoperative EB International Federation of Gynecology and Obstetrics (FIGO) grade, a higher proportion of patients with EB FIGO Grade 3 and MTD > 2 cm had LNM compared to those with EB FIGO Grade 1-2 and MTD ≤ 2 cm (43% vs, 11%, p=0.06). LNM was found in 15% of cases in which lymphadenectomy was performed based on current practices, whereas if the criteria of EB FIGO 3 and MTD > 2 cm were used the incidence of LNM would have been 44% cases. However, using this criterion, two patients would not have had their nodal metastases detected. Compared to the current practice, the sensitivity and specificity of the proposed criteria would be 60% and 81%, respectively. The PPV and NPV would be 43% and 90%, respectively. Conclusion: The results indicate that MTD combined with EB FIGO grade can detect LNM in a higher proportion of cases when compared to current practice. MTD combined with EB FIGO grade may eliminate the need of frozen section sampling in a substantial number of cases.

Keywords: endometrial cancer, FIGO grade, lymphadenectomy, tumor size

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Authors: Angelis P. Barlampas

Abstract:

The aim of this work is to denote that during an emergency state, an examination study may not be accomplished by state-of-the-art of imaging and, therefore, cannot obviously reveal all the existing findings. But, such a situation may have disastrous consequences for the patient. When interpreting radiological images, one must try to be as meticulous as possible, especially if the patient has alerting clinical symptoms. A case may be missed because its findings are not so obvious in rapid uncompleted radiological imaging. A thirty-seven years old female patient visited the emergency department because of a headache and hemiparesis of her left leg. Firstly, a CT examination without contrast was done, and mild serpentinous hyperintensities were depicted at the right parietal lobe. In addition to that, there was a linear, mildly hyperattenuating structure resembling a vessel in the nearby middle line. At first, an AVM was suspected, so an MRI examination with i.v. Gd was prescribed. The patient returned a few days later, not having done the MRI and complaining of persisting symptomatology. A new CT examination without and with i.v.c administration was done that showed no hyperintensities but a type-enhancing vessel in the posterior interhemispheric fissure. The latest findings are consistent with a venous malformation with previous bleeding.

Keywords: bleeding, brain, CNS, hemorrhage, CT, venous malformation

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Authors: Chieh-Nan Chen, Ji-Yu Lin, I-Ming Chu

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Polypeptide thermosensitive hydrogel is an excellent candidate as a smart device to deliver drugs and cells due to its remarkable biocompatibility, low gelation concentration, and respond to temperature stimuli, it can be easily injected as a polymer solution into the patient’s body where it undergoes gelation due to an elevation in temperature. Poly (ethylene glycol) monomethyl ether-poly (ethyl-l-glutamate) (mPEG-PELG) contains a hydrophobic side chain –C2H5 which is useful in encapsulating and stabilizing hydrophobic drugs. In this study, we plan to focus on the hydrophobic anti-carcinogenic and anti-inflammatory drug curcumin, which due its insolubility in water, requires a proper carrier for delivery into the body. Our main concept is to use mPEG-PELG to stabilize curcumin, inject the curcumin-loaded hydrogel into the tumor site, and allow the enzymatically-sensitive hydrogel to be degraded by bodily fluids and release the drug. The polymers of interest have been successfully synthesized and characterized by 1H-NMR, FT-IR, SEM, and CMC. Curcumin loading content and drug release were assayed using HPLC. Preliminary results show that these materials have potential as a delivery vehicle for poorly soluble drugs.

Keywords: curcumin, drug release, hydrogel, polypeptide material

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Authors: Varsha V. Rohini, P. R. Shreya, B. Renukadevi

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In the web analytics the information delivery and the web usage is optimized and the analysis of data is done. The analytics is the measurement, collection and analysis of webpage data. Page statistics and user metrics are the important factor in most of the web analytics tool. This is the limitation of the existing tools. It does not provide design inputs for the optimization of information. This paper aims at providing an extension for the scope of web analytics to provide analysis and statistics of each segment of a webpage. The number of click count is calculated and the concentration of links in a web page is obtained. Its user metrics are used to help in proper design of the displayed content in a webpage by Vision Based Page Segmentation (VIPS) algorithm. When the algorithm is applied on the web page it divides the entire web page into the visual block tree. The visual block tree generated will further divide the web page into visual blocks or segments which help us to understand the usage of each segment in a page and its content. The dynamic web pages and deep web pages are used to extend the scope of web page segment analytics. Space optimization concept is used with the help of the output obtained from the Vision Based Page Segmentation (VIPS) algorithm. This technique provides us the visibility of the user interaction with the WebPages and helps us to place the important links in the appropriate segments of the webpage and effectively manage space in a page and the concentration of links.

Keywords: analytics, design optimization, visual block trees, vision based technology

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Authors: Zhaoguo Liu, Cunsi Shen, Yin Lu

Abstract:

Growing evidence has shown that menthol has potent anticancer activity in various human cancers. However, its effect on skin cancer remains largely unknown. In the present study, we investigated the chemopreventive potential of menthol against 7, 12-dimethylbenz[a] anthracene(DMBA)/12-O-tetradecanoylphorbol 13-acetate (TPA)-induced skin tumorigenesis in ICR mice. Our results showed that menthol significantly inhibited TPA-induced inflammatory responses and pro-inflammatory cytokine release. We also found that menthol treatment significantly inhibited TPA-induced lipid peroxidation (LPO), mouse UDP-glucumno-syltransferase (UGT), mouse NADH Dehydrogenase, Quinone 1 (NQO1) release. Furthermore, we found menthol treatment significantly inhibited the tumor incidence and number of tumors (P < 0.001). Interestingly, we observed that menthol treatment significantly inhibited TPA-induced altered activity of NF-κB in skin tumor. Consistently, menthol-treated tumors also showed significantly suppressed the Ras-Raf-ERK signaling pathway. Thus, our results suggest that menthol inhibits DMBA/TPA-induced skin tumorigenesis by attenuating the Ras and inhibiting NF-κB activity via inhibition of inflammation responses and pro-inflammatory cytokine release.

Keywords: DMBA/TPA, NF-κB, Ras-Raf-ERK, skin tumorigenesis

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Authors: S. Sakhri

Abstract:

Background: The use of Zoledronic acid (ZA) is an established place in the treatment of malignant tumors with a predilection for the skeleton of interest (in particular metastasis). Although the main target of Zoledronic acid was osteoclasts, there are preclinical data suggest that Zoledronic acid may have an antitumor effect on cells other than osteoclasts, including tumor cells. Antitumor activity, including the inhibition of tumor cell growth and the induction of apoptosis of tumor cells, inhibition of tumor cell adhesion and invasion, and anti-angiogenic effects have been demonstrated. Methods. From (2012 to 2014), 438 patients were included respondents the inclusion criteria, respectively. This is a prospective study over a 4 year period. Of all patients (N=438), 432 received neoadjuvant chemotherapy with Zoledronic acid. The primary end point was the pathologic complete response in advancer breast cancer stage. The secondary end point is to evaluate Clinical response according to RECIST criteria; estimate the bone density before and at the end of chemotherapy in women with locally advanced breast cancer, Toxicity Evaluation and Overall survival using Kaplan-Meier and log test. Result: The Objective response rate was 97% after (C4) with 3% stabilizations and 99, 3% of which 0.7% C8 after stabilization. The clinical complete response was 28% after C4 respectively, and 46.8% after C8, the pathologic complete response rate was 40.13% according to the classification Sataloff. We observed that the pathologic complete response rate was the most raised in the group including Her2 (luminal Her2 and Her2) the lowest in the triple negative group as classified by Sataloff. We found that the pCR is significantly higher in the age group (35-50 years) with 53.17%. Those who have more than 50 years in 2nd place with 27.7% and the lower in young woman 35 years pCR was 19%, not statistically significant, -The pCR was also in favor of the menopausal group in 51, 4%, and 48, 55% for non-menopausal women. The average duration of overall survival was also significantly in the subgroup (Luminal -Her2, Her2) compared with triple negative. It is 47.18 months in the luminal group vs. 38.95 in the triple negative group. -Was observed in our study a difference in quality of life between (C1) was the admission of the patient, and after (C8), we found an increase in general signs and a deterioration in the psychological state C1, in contrast to the C8 these general signs and mental status improves, up to 12, and 24 months. Conclusion The results of this study suggest that the addition of ZA to néoadjuvant CT has potential anti-cancer benefit in patients (Luminal -Her2, Her2) compared with triple negative with or without menopause status.

Keywords: HER2+, RH+, breast cancer, tyrosine kinase

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Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

Abstract:

Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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Authors: Ping Tan, Xiaomeng Su, Yi Shen

Abstract:

The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

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Authors: Spyridon Komaitis, Christos Koutsarnakis, Evangelos Drosos, Aristotelis Kalyvas

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This study opts to investigate the intrinsic architecture, morphology, and spatial relationship of the subcortical pathways implicated in the connectivity of the motor/premotor cortex and SMA/pre-SMA complex. Twenty normal, adult, formalin-fixed cerebral hemispheres were explored through the fiber micro-dissection technique. Lateral to medial and medial to lateral dissections focused on the area of interest were performed in a tandem manner and under the surgical microscope. We traced the subcortical architecture, spatial relationships, and axonal connectivity of four major pathways: a) the dorsal component of the SLF (SLF-I) was found to reside in the medial aspect of the hemisphere and seen to connect the precuneus with the SMA and pre-SMA complex, b) the frontal longitudinal system (FLS) was consistently encountered as the natural anterior continuation of the SLF-II and SLF-III and connected the premotor and prefrontal cortices c) the fronto-caudate tract (FCT), a fan-shaped tract, was documented to participate in connectivity of the prefrontal and premotor cortices to the head and body of the caudate nucleus and d) the cortico-tegmental tract(CTT) was invariably recorded to subserve the connectivity of the tegmental area with the fronto-parietal cortex. No hemispheric asymmetries were recorded for any of the implicated pathways. Sub-segmentation systems were also proposed for each of the aforementioned tracts. The structural connectivity and functional specialization of motor and premotor areas in the human brain remain vague to this day as most of the available evidence derives either from animal or tractographic studies. By using the fiber-microdissection technique as our main method of investigation, we provide sound structural evidence on the delicate anatomy of the related white matter pathways.

Keywords: neuroanatomy, premotor, motor, connectivity

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Authors: V. A. Doss, R. Sowndarya, K. Juila Rose Mary

Abstract:

Objective: Amino acid neurotransmitter system dysfunction plays a major role in the pathophysiology of depression. The objective of the present study was to identify the amino acids as possible metabolite biomarkers for depression using GCMS (Gas Chromatography Mass Spectrometry) before and after exercise regimen in brain samples of depression induced animal models. Methods: Depression-like behaviour was induced by Chronic Unpredictable mild stress (CUMS). Severity of depression was measured by forced swim test (FST) and sucrose consumption test (SCT). Swimming protocol was followed for 4 weeks of exercise treatment. Brain obtained from depressed and exercise treated rats were used for the metabolite analysis by GCMS. Subsequent statistical analysis obtained by ANOVA followed by post hoc test revealed significant metabolic changes. Results: Amino acids such as alanine, glycine, serine, glutamate, homocysteine, proline and branched chain aminoacids (BCAs) Leucine, Isoleucine, Valine were determined in brain samples of control, depressed and exercised groups. Among these amino acids, the levels of D-Serine and branched chain amino acids were found to be decreased in depression induced rats. After four weeks of swimming exercise regimen, there were improvements in the levels of serine and Branched chain amino acids. Conclusion: We suggest that Serine and BCAs may be investigated as potential metabolite markers using GCMS and their beneficial metabolic changes in Exercise.

Keywords: metabolomics, depression, forced swim test, exercise, amino acid metabolites, GCMS, biomarker

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Authors: Georges F. Hatoum, Thomas H. Temple, Silvio Garcia, Xiaodong Wu

Abstract:

Soft Tissue Sarcomas (STS) represent a diverse group of malignancies with heterogeneous clinical and pathological features. The treatment of extremity STS aims to achieve optimal local tumor control, improved survival, and preservation of limb function. The National Comprehensive Cancer Network guidelines, based on the cumulated clinical data, recommend radiation therapy (RT) in conjunction with limb-sparing surgery for large, high-grade STS measuring greater than 5 cm in size. Such treatment strategy can offer a cure for patients. However, when recurrence occurs (in nearly half of patients), the prognosis is poor, with a median survival of 12 to 15 months and with only palliative treatment options available. The spatially-fractionated-radiotherapy (SFRT), with a long history of treating bulky tumors as a non-mainstream technique, has gained new attention in recent years due to its unconventional therapeutic effects, such as bystander/abscopal effects. Combining single fraction of GRID, the original form of SFRT, with conventional RT was shown to have marginally increased the rate of pathological necrosis, which has been recognized to have a positive correlation to overall survival. In an effort to consistently increase the pathological necrosis rate over 90%, multiple fractions of Lattice RT (LRT), a newer form of 3D SFRT, interdigitated with the standard RT as neoadjuvant therapy was conducted in a preliminary clinical setting. With favorable results of over 95% of necrosis rate in a small cohort of patients, a Phase I/II clinical study was proposed to exam the safety and feasibility of this new strategy. Herein the design of the clinical study is presented. In this single-arm, two-stage phase I/II clinical trial, the primary objectives are >80% of the patients achieving >90% tumor necrosis and to evaluation the toxicity; the secondary objectives are to evaluate the local control, disease free survival and overall survival (OS), as well as the correlation between clinical response and the relevant biomarkers. The study plans to accrue patients over a span of two years. All patient will be treated with the new neoadjuvant RT regimen, in which one of every five fractions of conventional RT is replaced by a LRT fraction with vertices receiving dose ≥10Gy while keeping the tumor periphery at or close to 2 Gy per fraction. Surgical removal of the tumor is planned to occur 6 to 8 weeks following the completion of radiation therapy. The study will employ a Pocock-style early stopping boundary to ensure patient safety. The patients will be followed and monitored for a period of five years. Despite much effort, the rarity of the disease has resulted in limited novel therapeutic breakthroughs. Although a higher rate of treatment-induced tumor necrosis has been associated with improved OS, with the current techniques, only 20% of patients with large, high-grade tumors achieve a tumor necrosis rate exceeding 50%. If this new neoadjuvant strategy is proven effective, an appreciable improvement in clinical outcome without added toxicity can be anticipated. Due to the rarity of the disease, it is hoped that such study could be orchestrated in a multi-institutional setting.

Keywords: lattice RT, necrosis, SFRT, soft tissue sarcoma

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Authors: Hyeon Su Kim, Sungjin Park, Hae Ryung Chang, Hae Rim Jung, Young Zoo Ahn, Yon Hui Kim, Seungyoon Nam

Abstract:

Ependymoma, one of the most common parenchymal spinal cord tumor, represents 3-6% of all CNS tumor. Especially intracranial ependymomas, which are more frequent in childhood, have a more poor prognosis and more malignant than spinal ependymomas. Although there are growing needs to understand pathogenesis, detailed molecular understanding of pathogenesis remains to be explored. A cancer cell is composed of complex signaling pathway networks, and identifying interaction between genes and/or proteins are crucial for understanding these pathways. Therefore, we explored each ependymoma in terms of differential expressed genes and signaling networks. We used Microsoft Excel™ to manipulate microarray data gathered from NCBI’s GEO Database. To analyze and visualize signaling network, we used web-based PATHOME algorithm and Cytoscape. We show HOX family and NEFL are down-regulated but SCL family is up-regulated in cerebrum and posterior fossa cancers over a spinal cancer, and JAK/STAT signaling pathway and Chemokine signaling pathway are significantly different in the both intracranial ependymoma comparing to spinal ependymoma. We are considering there may be an age-dependent mechanism under different histological pathogenesis. We annotated mutation data of each gene subsequently in order to find potential target genes.

Keywords: systems biology, ependymoma, deg, network analysis

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