scholarly journals PATH-04. AN ENHANCED AI-DRIVEN PLATFORM FOR PRECISION MOLECULAR BRAIN TUMOR DIANOSTICS

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii425-iii425
Author(s):  
Martin Sill ◽  
Felix Sahm ◽  
Daniel Schrimpf ◽  
David Capper ◽  
Stefan M Pfister ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Human Cancer ◽  
Clinical Care ◽  
Vast Number ◽  
Primary Output ◽  
Anatomic Locations ◽  
First Time ◽  
Molecular Brain ◽  
Methylation Profiling

Abstract Tumors of the CNS represent one of the most complex groups of human cancer, with a vast number of different entities occurring across a spectrum of ages and anatomic locations. This heterogeneity makes accurate diagnosis challenging, with the current gold standard relying on multiple subjective elements. We recently proposed a classification algorithm based on tumor DNA methylation profiling as an objective way to assign samples to over 80 distinct molecular classes. Here we present a substantial update to our machine learning-based algorithm, with more than 170 molecular classes now being represented amongst the 5,915 samples in our reference cohort. These new classes include further subclassification of known groups such as medulloblastoma and ependymoma, as well as multiple new molecular entities described here for the first time. A further improvement is the introduction of a more rationally layered output, making use of ‘families’ of closely-related molecular classes to improve the compatibility with the current WHO classification of CNS tumors. This approach is designed to increase the clinical relevance of the primary output, while also retaining the full information content from the random forest-driven classification. Benchmarking our new algorithm by cross-validation and on an independent validation cohort indicates a retention of the excellent accuracy of diagnosis (error-rate < 4%), with a significant improvement in the proportion of confidently classifiable tumors compared with our previous tool. We believe that this approach, freely accessible through an online web portal, has the potential to enhance diagnostic precision and thereby support clinical care for brain tumor patients.

Structure-Reactivity Relationships on Substrates and Inhibitors of the Lysine Deacylase Sirtuin 2 from Schistosoma Mansoni (SmSirt2)

2019 ◽  
Author(s):  
Daria Monaldi ◽  
Dante Rotili ◽  
Julien Lancelot ◽  
Martin Marek ◽  
Nathalie Wössner ◽  
...  
Keyword(s):  
Schistosoma Mansoni ◽  
Human Cancer ◽  
Egg Laying ◽  
Human Cancer Cells ◽  
Parasite Survival ◽  
Survival And Reproduction ◽  
Emergence Of Resistance ◽  
First Time ◽  
Parasitic Life Cycle

The only drug for treatment of Schistosomiasis is Praziquantel, and the possible emergence of resistance makes research on novel therapeutic agents necessary. Targeting of Schistosoma mansoni epigenetic enzymes, which regulate the parasitic life cycle, emerged as promising approach. Due to the strong effects of human Sirtuin inhibitors on parasite survival and reproduction, Schistosoma sirtuins were postulated as therapeutic targets. In vitro testing of synthetic substrates of S. mansoni Sirtuin 2 (SmSirt2) and kinetic experiments on a myristoylated peptide demonstrated lysine long chain deacylation as an intrinsic SmSirt2 activity for the first time. Focused in vitro screening of the GSK Kinetobox library and structure-activity relationships (SAR) of identified hits, led to the first SmSirt2 inhibitors with activity in the low micromolar range. Several SmSirt2 inhibitors showed potency against both larval schistosomes (viability) and adult worms (pairing, egg laying) in culture without general toxicity to human cancer cells.<br>

СОЦИАЛЬНАЯ КОНФЛИКТОЛОГИЯ: ТЕОРЕТИКО-ИСТОРИЧЕСКИЙ АСПЕКТ

2020 ◽  
Vol 15 (2) ◽  
pp. 68
Author(s):  
А. Н. Сухов
Keyword(s):  
Theory And Practice ◽  
Important Task ◽  
Social Conflicts ◽  
Psychological Approach ◽  
Structure Dynamics ◽  
History Of ◽  
The Subject ◽  
First Time

This given article reveals the topicality not only of destructive, but also of constructive, as well as hybrid conflicts. Practically it has been done for the first time. It also describes the history of the formation of both foreign and domestic social conflictology. At the same time, the chronology of the development of the latter is restored and presented objectively, in full, taking into account the contribution of those researchers who actually stood at its origins. The article deals with the essence of the socio-psychological approach to understanding conflicts. The subject of social conflictology includes the regularities of their occurrence and manifestation at various levels, spheres and conditions, including normal, complicated and extreme ones. Social conflictology includes the theory and practice of diagnosing, resolving, and resolving social conflicts. It analyzes the difficulties that occur in defining the concept, structure, dynamics, and classification of social conflicts. Therefore, it is no accident that the most important task is to create a full-fledged theory of social conflicts. Without this, it is impossible to talk about effective settlement and resolution of social conflicts. Social conflictology is an integral part of conflictology. There is still a lot of work to be done, both in theory and in application, for its complete design. At present, there is an urgent need to develop conflict-related competence not only of professionals, but also for various groups of the population.

scholarly journals Morphological and Ultrastructural Characterization of Hemocytes in an Insect Model, the Hematophagous Dipetalogaster maxima (Hemiptera: Reduviidae)

Insects ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 640
Author(s):  
Natalia R. Moyetta ◽  
Fabián O. Ramos ◽  
Jimena Leyria ◽  
Lilián E. Canavoso ◽  
Leonardo L. Fruttero
Keyword(s):  
Cell Biology ◽  
Cell Types ◽  
Transmission Electron ◽  
Ultrastructural Characterization ◽  
Current Classification ◽  
Contrast Microscopy ◽  
First Time ◽  
Controversial Aspect

Hemocytes, the cells present in the hemolymph of insects and other invertebrates, perform several physiological functions, including innate immunity. The current classification of hemocyte types is based mostly on morphological features; however, divergences have emerged among specialists in triatomines, the insect vectors of Chagas’ disease (Hemiptera: Reduviidae). Here, we have combined technical approaches in order to characterize the hemocytes from fifth instar nymphs of the triatomine Dipetalogaster maxima. Moreover, in this work we describe, for the first time, the ultrastructural features of D. maxima hemocytes. Using phase contrast microscopy of fresh preparations, five hemocyte populations were identified and further characterized by immunofluorescence, flow cytometry and transmission electron microscopy. The plasmatocytes and the granulocytes were the most abundant cell types, although prohemocytes, adipohemocytes and oenocytes were also found. This work sheds light on a controversial aspect of triatomine cell biology and physiology setting the basis for future in-depth studies directed to address hemocyte classification using non-microscopy-based markers.

scholarly journals Differential Deep Convolutional Neural Network Model for Brain Tumor Classification

2021 ◽  
Vol 11 (3) ◽  
pp. 352
Author(s):  
Isselmou Abd El Kader ◽  
Guizhi Xu ◽  
Zhang Shuai ◽  
Sani Saminu ◽  
Imran Javaid ◽  
...  
Keyword(s):  
Neural Network ◽  
Magnetic Resonance Imaging ◽  
Brain Tumor ◽  
Magnetic Resonance ◽  
Brain Tumors ◽  
Medical Image ◽  
Resonance Imaging ◽  
Feature Maps ◽  
Deep Cnn

The classification of brain tumors is a difficult task in the field of medical image analysis. Improving algorithms and machine learning technology helps radiologists to easily diagnose the tumor without surgical intervention. In recent years, deep learning techniques have made excellent progress in the field of medical image processing and analysis. However, there are many difficulties in classifying brain tumors using magnetic resonance imaging; first, the difficulty of brain structure and the intertwining of tissues in it; and secondly, the difficulty of classifying brain tumors due to the high density nature of the brain. We propose a differential deep convolutional neural network model (differential deep-CNN) to classify different types of brain tumor, including abnormal and normal magnetic resonance (MR) images. Using differential operators in the differential deep-CNN architecture, we derived the additional differential feature maps in the original CNN feature maps. The derivation process led to an improvement in the performance of the proposed approach in accordance with the results of the evaluation parameters used. The advantage of the differential deep-CNN model is an analysis of a pixel directional pattern of images using contrast calculations and its high ability to classify a large database of images with high accuracy and without technical problems. Therefore, the proposed approach gives an excellent overall performance. To test and train the performance of this model, we used a dataset consisting of 25,000 brain magnetic resonance imaging (MRI) images, which includes abnormal and normal images. The experimental results showed that the proposed model achieved an accuracy of 99.25%. This study demonstrates that the proposed differential deep-CNN model can be used to facilitate the automatic classification of brain tumors.

scholarly journals COVD-07. THE IMPACT OF COVID-19 ON PATIENTS AND CAREGIVERS AFFECTED BY BRAIN TUMORS: THE PATIENT NAVIGATOR PERSPECTIVE

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii22-ii22
Author(s):  
Kyle Walsh
Keyword(s):  
Clinical Trials ◽  
Brain Tumor ◽  
Clinical Care ◽  
Structured Interview ◽  
Patient Navigator ◽  
Structured Interviews ◽  
Social Distancing ◽  
Tumor Patient ◽  
Patient Navigators ◽  
The Impact

Abstract BACKGROUND Preliminary evidence indicates that glioma patients are at higher risk for COVID-19 complications due to systemic immunosuppression. Interruptions in cancer care may exacerbate patient and caregiver anxiety, but surveying patients/caregivers about their COVID-19 experiences is often limited by attainable sample sizes and over-reliance upon single-institution experiences. METHODS To explore how COVID-19 is impacting brain tumor patients/caregivers across the U.S., we performed semi-structured interviews with brain tumor patient navigators employed by two different 501(c)3 nonprofit organizations. A semi-structured interview guide was used, utilizing prompts and open-ended questions to facilitate dialogue. A core set of COVID-19 topics were covered, including: financial issues, coping strategies, geographic variability, variability by tumor grade/histology, disruptions in care continuity, accessing clinical trials, psychosocial issues, and end-of-life care. Interviews were audio-recorded, transcribed, and organized by discussion topic to identify emerging themes. Inductive sub-coding was completed using the constant comparison method, within and between transcripts. RESULTS/CONCLUSIONS Ten patient navigators were interviewed between April 15th and May 8th, with interviews lasting approximately one hour (range 38-77minutes). Navigators reported having contact with 183 unique brain tumor families during the pandemic (range 7–38 families per navigator). High concordance emerged across narratives, revealing important considerations for the neuro-oncology workforce. The most prominent theme was increased caregiver burden, attributed to maintaining social distancing by reducing visits from home-health aides and friends/family. A related theme that applied to both patients and caregivers was increased social isolation due to social distancing, suspension of in-person support groups, and church/temple closures. Accessing clinical trials was a recurrent issue, exacerbated by patients’ increasing unwillingness to travel. Glioblastoma patients, especially those with recurrent tumors, expressed greater reluctance to travel. Access to standard-of-care treatment was rarely interrupted, but reduced access to supportive services – especially physical and occupational therapy – was identified as an emerging COVID-related deficiency in clinical care.

scholarly journals Autophagy augments the self-renewal of lung cancer stem cells by the degradation of ubiquitinated p53

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jianyu Wang ◽  
Doudou Liu ◽  
Zhiwei Sun ◽  
Ting Ye ◽  
Jingyuan Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Cell Lines ◽  
Human Cancer ◽  
Suppressor Activity ◽  
Self Renewal ◽  
Tumor Suppressor Activity ◽  
Lung Cancer Stem Cells ◽  
First Time

AbstractIt has been postulated that cancer stem cells (CSCs) are involved in all aspects of human cancer, although the mechanisms governing the regulation of CSC self-renewal in the cancer state remain poorly defined. In the literature, both the pro- and anti-oncogenic activities of autophagy have been demonstrated and are context-dependent. Mounting evidence has shown augmentation of CSC stemness by autophagy, yet mechanistic characterization and understanding are lacking. In the present study, by generating stable human lung CSC cell lines with the wild-type TP53 (A549), as well as cell lines in which TP53 was deleted (H1229), we show, for the first time, that autophagy augments the stemness of lung CSCs by degrading ubiquitinated p53. Furthermore, Zeb1 is required for TP53 regulation of CSC self-renewal. Moreover, TCGA data mining and analysis show that Atg5 and Zeb1 are poor prognostic markers of lung cancer. In summary, this study has elucidated a new CSC-based mechanism underlying the oncogenic activity of autophagy and the tumor suppressor activity of p53 in cancer, i.e., CSCs can exploit the autophagy-p53-Zeb1 axis for self-renewal, oncogenesis, and progression.

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