scholarly journals CausalTab: PSI-MITAB 2.8 updated format for signaling data representation and dissemination

2018 ◽  
Author(s):  
L. Perfetto ◽  
M.L. Acencio ◽  
G. Bradley ◽  
G. Cesareni ◽  
N.Del Toro ◽  
...  
Keyword(s):  
Molecular Interaction ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Data Representation ◽  
Research Field ◽  
Controlled Vocabulary ◽  
Causal Interaction ◽  
Signalling Network ◽  
Cellular Phenotypes ◽  
Biological Entities

AbstractCombining multiple layers of information underlying biological complexity into a structured framework, and in particular deciphering the molecular mechanisms behind cellular phenotypes, represent two challenges in systems biology. A key task is the formalisation of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signaling information, such as SIGNOR, SignaLink and IntAct, focus on capturing, organising and displaying signaling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources, through the development of a standardized exchange format, ontologies and controlled vocabularies supporting the domain of causal interactions. Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signaling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated MITAB2.8. We define the new term “causal interaction”, and related child terms, which are children of the PSI-MI “molecular interaction” term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signaling networks more precisely and with higher coverage than before.

scholarly journals CausalTAB: the PSI-MITAB 2.8 updated format for signalling data representation and dissemination

2019 ◽  
Vol 35 (19) ◽  
pp. 3779-3785 ◽  
Author(s):  
L Perfetto ◽  
M L Acencio ◽  
G Bradley ◽  
G Cesareni ◽  
N Del Toro ◽  
...  
Keyword(s):  
Molecular Interaction ◽  
Large Scale ◽  
Data Representation ◽  
Research Field ◽  
Controlled Vocabulary ◽  
Supplementary Information ◽  
Causal Interaction ◽  
Signalling Network ◽  
Information Focus ◽  
Biological Entities

Abstract Motivation Combining multiple layers of information underlying biological complexity into a structured framework represent a challenge in systems biology. A key task is the formalization of such information in models describing how biological entities interact to mediate the response to external and internal signals. Several databases with signalling information, focus on capturing, organizing and displaying signalling interactions by representing them as binary, causal relationships between biological entities. The curation efforts that build these individual databases demand a concerted effort to ensure interoperability among resources. Results Aware of the enormous benefits of standardization efforts in the molecular interaction research field, representatives of the signalling network community agreed to extend the PSI-MI controlled vocabulary to include additional terms representing aspects of causal interactions. Here, we present a common standard for the representation and dissemination of signalling information: the PSI Causal Interaction tabular format (CausalTAB) which is an extension of the existing PSI-MI tab-delimited format, now designated PSI-MITAB 2.8. We define the new term ‘causal interaction’, and related child terms, which are children of the PSI-MI ‘molecular interaction’ term. The new vocabulary terms in this extended PSI-MI format will enable systems biologists to model large-scale signalling networks more precisely and with higher coverage than before. Availability and implementation PSI-MITAB 2.8 format and the new reference implementation of PSICQUIC are available online (https://psicquic.github.io/ and https://psicquic.github.io/MITAB28Format.html). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Large Scale Molecular Studies of Pituitary Neuroendocrine Tumors: Novel Markers, Mechanisms and Translational Perspectives

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1395
Author(s):  
Raitis Peculis ◽  
Helvijs Niedra ◽  
Vita Rovite
Keyword(s):  
Neuroendocrine Tumors ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Research Field ◽  
Driver Mutations ◽  
Cell Cycle Regulators ◽  
Circulating Nucleic Acids ◽  
Molecular Studies ◽  
Insight Into ◽  
Modern Technologies

Pituitary neuroendocrine tumors (PitNETs) are non-metastatic neoplasms of the pituitary, which overproduce hormones leading to systemic disorders, or tumor mass effects causing headaches, vertigo or visual impairment. Recently, PitNETs have been investigated in large scale (exome and genome) molecular analyses (transcriptome microarrays and sequencing), to uncover novel markers. We performed a literature analysis on these studies to summarize the research data and extrapolate overlapping gene candidates, biomarkers, and molecular mechanisms. We observed a tendency in samples with driver mutations (GNAS, USP8) to have a smaller overall mutational rate, suggesting driver-promoted tumorigenesis, potentially changing transcriptome profiles in tumors. However, direct links from drivers to signaling pathways altered in PitNETs (Notch, Wnt, TGF-β, and cell cycle regulators) require further investigation. Modern technologies have also identified circulating nucleic acids, and pinpointed these as novel PitNET markers, i.e., miR-143-3p, miR-16-5p, miR-145-5p, and let-7g-5p, therefore these molecules must be investigated in the future translational studies. Overall, large-scale molecular studies have provided key insight into the molecular mechanisms behind PitNET pathogenesis, highlighting previously reported molecular markers, bringing new candidates into the research field, and reapplying traditional perspectives to newly discovered molecular mechanisms.

scholarly journals EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jing Zhao ◽  
Alan Blayney ◽  
Xiaorong Liu ◽  
Lauren Gandy ◽  
Weihua Jin ◽  
...  
Keyword(s):  
Large Scale ◽  
Molecular Mechanisms ◽  
Epigallocatechin Gallate ◽  
Cancer Drug ◽  
Dynamic Interactions ◽  
Cancer Drug Discovery ◽  
Intrinsically Disordered ◽  
Terminal Domain ◽  
Cancerous Cells

AbstractEpigallocatechin gallate (EGCG) from green tea can induce apoptosis in cancerous cells, but the underlying molecular mechanisms remain poorly understood. Using SPR and NMR, here we report a direct, μM interaction between EGCG and the tumor suppressor p53 (KD = 1.6 ± 1.4 μM), with the disordered N-terminal domain (NTD) identified as the major binding site (KD = 4 ± 2 μM). Large scale atomistic simulations (>100 μs), SAXS and AUC demonstrate that EGCG-NTD interaction is dynamic and EGCG causes the emergence of a subpopulation of compact bound conformations. The EGCG-p53 interaction disrupts p53 interaction with its regulatory E3 ligase MDM2 and inhibits ubiquitination of p53 by MDM2 in an in vitro ubiquitination assay, likely stabilizing p53 for anti-tumor activity. Our work provides insights into the mechanisms for EGCG’s anticancer activity and identifies p53 NTD as a target for cancer drug discovery through dynamic interactions with small molecules.

scholarly journals Integrative cBioPortal Analysis Revealed Molecular Mechanisms That Regulate EGFR-PI3K-AKT-mTOR Pathway in Diffuse Gliomas of the Brain

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3247
Author(s):  
Petar Brlek ◽  
Anja Kafka ◽  
Anja Bukovac ◽  
Nives Pećina-Šlaus
Keyword(s):  
Large Scale ◽  
Molecular Mechanisms ◽  
In Silico Analysis ◽  
Total Sample ◽  
Mtor Signaling ◽  
Biological Behavior ◽  
Mrna Transcription ◽  
Diffuse Gliomas ◽  
New Treatment ◽  
Using Data

Diffuse gliomas are a heterogeneous group of tumors with aggressive biological behavior and a lack of effective treatment methods. Despite new molecular findings, the differences between pathohistological types still require better understanding. In this in silico analysis, we investigated AKT1, AKT2, AKT3, CHUK, GSK3β, EGFR, PTEN, and PIK3AP1 as participants of EGFR-PI3K-AKT-mTOR signaling using data from the publicly available cBioPortal platform. Integrative large-scale analyses investigated changes in copy number aberrations (CNA), methylation, mRNA transcription and protein expression within 751 samples of diffuse astrocytomas, anaplastic astrocytomas and glioblastomas. The study showed a significant percentage of CNA in PTEN (76%), PIK3AP1 and CHUK (75% each), EGFR (74%), AKT2 (39%), AKT1 (32%), AKT3 (19%) and GSK3β (18%) in the total sample. Comprehensive statistical analyses show how genomics and epigenomics affect the expression of examined genes differently across various pathohistological types and grades, suggesting that genes AKT3, CHUK and PTEN behave like tumor suppressors, while AKT1, AKT2, EGFR, and PIK3AP1 show oncogenic behavior and are involved in enhanced activity of the EGFR-PI3K-AKT-mTOR signaling pathway. Our findings contribute to the knowledge of the molecular differences between pathohistological types and ultimately offer the possibility of new treatment targets and personalized therapies in patients with diffuse gliomas.

scholarly journals Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images

2021 ◽  
Vol 13 (16) ◽  
pp. 3065
Author(s):  
Libo Wang ◽  
Rui Li ◽  
Dongzhi Wang ◽  
Chenxi Duan ◽  
Teng Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
Texture Features ◽  
Semantic Segmentation ◽  
Autonomous Driving ◽  
Research Field ◽  
Learning Approaches ◽  
Fine Grained ◽  
Urban Scene ◽  
Fine Resolution ◽  
With Memory

Semantic segmentation from very fine resolution (VFR) urban scene images plays a significant role in several application scenarios including autonomous driving, land cover classification, urban planning, etc. However, the tremendous details contained in the VFR image, especially the considerable variations in scale and appearance of objects, severely limit the potential of the existing deep learning approaches. Addressing such issues represents a promising research field in the remote sensing community, which paves the way for scene-level landscape pattern analysis and decision making. In this paper, we propose a Bilateral Awareness Network which contains a dependency path and a texture path to fully capture the long-range relationships and fine-grained details in VFR images. Specifically, the dependency path is conducted based on the ResT, a novel Transformer backbone with memory-efficient multi-head self-attention, while the texture path is built on the stacked convolution operation. In addition, using the linear attention mechanism, a feature aggregation module is designed to effectively fuse the dependency features and texture features. Extensive experiments conducted on the three large-scale urban scene image segmentation datasets, i.e., ISPRS Vaihingen dataset, ISPRS Potsdam dataset, and UAVid dataset, demonstrate the effectiveness of our BANet. Specifically, a 64.6% mIoU is achieved on the UAVid dataset.

scholarly journals The Cardiovascular Phenotype in Fabry Disease: New Findings in the Research Field

2021 ◽  
Vol 22 (3) ◽  
pp. 1331
Author(s):  
Daniela Sorriento ◽  
Guido Iaccarino
Keyword(s):  
Fabry Disease ◽  
Molecular Mechanisms ◽  
Cell Damage ◽  
Research Field ◽  
Cardiac Cell ◽  
Lysosomal Storage ◽  
Clinical Level ◽  
New Findings ◽  
Alpha Gene ◽  
Alpha Galactosidase

Fabry disease (FD) is a lysosomal storage disorder, depending on defects in alpha-galactosidase A (GAL) activity. At the clinical level, FD shows a high phenotype variability. Among them, cardiovascular dysfunction is often recurrent or, in some cases, is the sole symptom (cardiac variant) representing the leading cause of death in Fabry patients. The existing therapies, besides specific symptomatic treatments, are mainly based on the restoration of GAL activity. Indeed, mutations of the galactosidase alpha gene (GLA) cause a reduction or lack of GAL activity leading to globotriaosylceramide (Gb3) accumulation in several organs. However, several other mechanisms are involved in FD’s development and progression that could become useful targets for therapeutics. This review discusses FD’s cardiovascular phenotype and the last findings on molecular mechanisms that accelerate cardiac cell damage.

scholarly journals The Chinese Medicinal Formulation Guzhi Zengsheng Zhitongwan Modulates Chondrocyte Structure, Dynamics, and Metabolism by Controlling Multiple Functional Proteins

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Baojin Yao ◽  
Bocheng Lu ◽  
Mei Zhang ◽  
Hongwei Gao ◽  
Xiangyang Leng ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Current Knowledge ◽  
Research Field ◽  
Medical Systems ◽  
Cellular Processes ◽  
Structure Dynamics ◽  
National Medical ◽  
Medicinal Formulation

Traditional Chinese medicine is one of the oldest medical systems in the world and has its unique principles and theories in the prevention and treatment of human diseases, which are achieved through the interactions of different types of materia medica in the form of Chinese medicinal formulations. GZZSZTW, a classical and effective Chinese medicinal formulation, was designed and created by professor Bailing Liu who is the only national medical master professor in the clinical research field of traditional Chinese medicine and skeletal diseases. GZZSZTW has been widely used in clinical settings for several decades for the treatment of joint diseases. However, the underlying molecular mechanisms are still largely unknown. In the present study, we performed quantitative proteomic analysis to investigate the effects of GZZSZTW on mouse primary chondrocytes using state-of-the-art iTRAQ technology. We demonstrated that the Chinese medicinal formulation GZZSZTW modulates chondrocyte structure, dynamics, and metabolism by controlling multiple functional proteins that are involved in the cellular processes of DNA replication and transcription, protein synthesis and degradation, cytoskeleton dynamics, and signal transduction. Thus, this study has expanded the current knowledge of the molecular mechanism of GZZSZTW treatment on chondrocytes. It has also shed new light on possible strategies to further prevent and treat cartilage-related diseases using traditional Chinese medicinal formulations.

scholarly journals Antihyperglycaemic therapies and cancer risk

2014 ◽  
Vol 11 (6) ◽  
pp. 371-389 ◽  
Author(s):  
Stefan Z Lutz ◽  
Harald Staiger ◽  
Andreas Fritsche ◽  
Hans-Ulrich Häring
Keyword(s):  
Cancer Risk ◽  
Large Scale ◽  
Tumour Growth ◽  
Molecular Mechanisms ◽  
Growth Promotion ◽  
Protective Effects ◽  
Antidiabetic Drug ◽  
Safety Issues ◽  
Drug Classes ◽  
Few Data

Aims: This review is aimed at highlighting the potential mitogenic/tumour growth–promoting or antimitogenic/tumour growth–inhibiting effects of the main antihyperglycaemic drug classes. Methods: We review and discuss the most current studies evaluating the association between antidiabetic medications used in clinical practice and malignancies as described so far. Results: Metformin seems to be the only antidiabetic drug to exert protective effects both on monotherapy and also when combined with other oral antidiabetic drugs or insulins in several site-specific cancers. In contrast, several other drug classes may increase cancer risk. Some reason for concern remains regarding sulphonylureas and also the incretin-based therapies regarding pancreas and thyroid cancers and the sodium glucose cotransporter-2 inhibitors as well as pioglitazone regarding bladder cancer. The majority of meta-analyses suggest that there is no evidence for a causal relationship between insulin glargine and elevated cancer risk, although the studies have been controversially discussed. For α-glucosidase inhibitors and glinides, neutral or only few data upon cancer risk exist. Conclusion: Although the molecular mechanisms are not fully understood, a potential risk of mitogenicity and tumour growth promotion cannot be excluded in case of several antidiabetic drug classes. However, more large-scale, randomized, well-designed clinical studies with especially long follow-up time periods are needed to get reliable answers to these safety issues.

Sex differences in white adipose tissue expansion: emerging molecular mechanisms

2021 ◽  
Vol 135 (24) ◽  
pp. 2691-2708
Author(s):  
Simon T. Bond ◽  
Anna C. Calkin ◽  
Brian G. Drew
Keyword(s):  
Sex Differences ◽  
Sexual Dimorphism ◽  
Gene Networks ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Tissue Expansion ◽  
Economic Systems ◽  
Genomic Association ◽  
Males And Females

Abstract The escalating prevalence of individuals becoming overweight and obese is a rapidly rising global health problem, placing an enormous burden on health and economic systems worldwide. Whilst obesity has well described lifestyle drivers, there is also a significant and poorly understood component that is regulated by genetics. Furthermore, there is clear evidence for sexual dimorphism in obesity, where overall risk, degree, subtype and potential complications arising from obesity all differ between males and females. The molecular mechanisms that dictate these sex differences remain mostly uncharacterised. Many studies have demonstrated that this dimorphism is unable to be solely explained by changes in hormones and their nuclear receptors alone, and instead manifests from coordinated and highly regulated gene networks, both during development and throughout life. As we acquire more knowledge in this area from approaches such as large-scale genomic association studies, the more we appreciate the true complexity and heterogeneity of obesity. Nevertheless, over the past two decades, researchers have made enormous progress in this field, and some consistent and robust mechanisms continue to be established. In this review, we will discuss some of the proposed mechanisms underlying sexual dimorphism in obesity, and discuss some of the key regulators that influence this phenomenon.

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