cancer diseases
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2022 ◽  
Vol 7 (1) ◽  
Author(s):  
Jiaqi Liu ◽  
Qing Xiao ◽  
Jiani Xiao ◽  
Chenxi Niu ◽  
Yuanyuan Li ◽  
...  

AbstractThe Wnt/β-catenin pathway comprises a family of proteins that play critical roles in embryonic development and adult tissue homeostasis. The deregulation of Wnt/β-catenin signalling often leads to various serious diseases, including cancer and non-cancer diseases. Although many articles have reviewed Wnt/β-catenin from various aspects, a systematic review encompassing the origin, composition, function, and clinical trials of the Wnt/β-catenin signalling pathway in tumour and diseases is lacking. In this article, we comprehensively review the Wnt/β-catenin pathway from the above five aspects in combination with the latest research. Finally, we propose challenges and opportunities for the development of small-molecular compounds targeting the Wnt signalling pathway in disease treatment.


Author(s):  
Noé Rodríguez-Barajas ◽  
Luis Miguel Anaya-Esparza ◽  
Zuami Villagrán-de la Mora ◽  
Jorge Alberto Sánchez-Burgos ◽  
Alejandro Pérez-Larios

Abstract: Recently, Titanium dioxide (TiO2) has been studied as an alternative to treat cancer diseases under different activation therapies. The aim of this review was to describe the effect of TiO2 nanoparticles (NPs) on some cancer cell lines and their interaction with phototherapies such as photodynamic therapy (PDT), photothermal therapy (PTT), sonodynamic therapy (SDT), and ultraviolet therapy (UV) for anticancer treatment. The use of TiO2 combined with PDT, PTT, SDT, or UV has shown a remarkable capacity to enhance the killing of cancer cells through reactive oxygen species formation. Thus, the combination of TiO2 and activation therapies exhibited great potential and could be a viable anticancer treatment strategy. However, more studies on phototherapies in combination with TiO2 and their effects at under different experimental conditions (TiO2 concentration, type of cancer cells, and intensity and frequency of therapies) are necessary to guarantee the safe use of this kind of therapy.


2021 ◽  
Vol 10 (1) ◽  
pp. 9
Author(s):  
Leandro Gammuto ◽  
Carolina Chiellini ◽  
Marta Iozzo ◽  
Renato Fani ◽  
Giulio Petroni

Azurin is a bacterial-derived cupredoxin, which is mainly involved in electron transport reactions. Interest in azurin protein has risen in recent years due to its anticancer activity and its possible applications in anticancer therapies. Nevertheless, the attention of the scientific community only focused on the azurin protein found in Pseudomonas aeruginosa (Proteobacteria, Gammaproteobacteria). In this work, we performed the first comprehensive screening of all the bacterial genomes available in online repositories to assess azurin distribution in the three domains of life. The Azurin coding gene was not detected in the domains Archaea and Eucarya, whereas it was detected in phyla other than Proteobacteria, such as Bacteroidetes, Verrucomicrobia and Chloroflexi, and a phylogenetic analysis of the retrieved sequences was performed. Observed patchy distribution and phylogenetic data suggest that once it appeared in the bacterial domain, the azurin coding gene was lost in several bacterial phyla and/or anciently horizontally transferred between different phyla, even though a vertical inheritance appeared to be the major force driving the transmission of this gene. Interestingly, a shared conserved domain has been found among azurin members of all the investigated phyla. This domain is already known in P. aeruginosa as p28 domain and its importance for azurin anticancer activity has been widely explored. These findings may open a new and intriguing perspective in deciphering the azurin anticancer mechanisms and to develop new tools for treating cancer diseases.


Author(s):  
Hannah Case ◽  
Tyler Benning ◽  
Zachary Lovig ◽  
Jeramy Girard ◽  
Megan Thorvilson ◽  
...  

Author(s):  
Elena S. Stepanova

The article deals with the question of cancer myth representation in the popular science medical discourse. This study is carried out according to the linguocultural approach to the study of the cancer myth, which is based on the reconsideration of linguocultural phenomena. Myths about diseases are of linguistic and cultural significance and they are passed down from generation to generation. Those of phenomena that are incomprehensible and frightening are considered to cause additional associations. Cancer diseases refer to such linguocultural phenomena. Myths about diseases reflect the results of this or that form of reconsideration or experience of some phenomena by a particular linguocultural society. The work provides the definitions of the notions myth and disease. The methodology of the study is based on the research by foreign and Russian scientists in the field of study of the notions of myth and disease as semiotic systems. The popular science medical survey The Emperor of All Maladies: A Biography of Cancer by Siddhartha Mukherjee served as a research background. It analyses the way the disease myth actualizes in the popular science medical discourse. It shows a mythological plot (or mythological information) to get actualized in a particular situation by means of reference, and the way it contributes to the explication of a particular disease myth. Neither the subject of the message nor the plot of the myth is of importance for the reader, only the influence of the myth on the patients representations of disorder and his emotional state and on the society as a whole makes sense. The study helps conclude that mythological information representing the disease myth is nationally and socially marked, and is characterized by a particular conceptual presentation and is expressed by different linguistic means.


2021 ◽  
Vol 10 ◽  
pp. 51-76
Author(s):  
Dwight L. McKee ◽  
Mamoona S. Lodhi

About 60% of chemotherapeutic agents used for the treatment of cancer diseases today have been derived from natural products. While some of these agents are identical to the natural molecules found in plants; the others are semisynthetic derivative of the foundational molecule found naturally in the raw sources. Cancers have been reported to express 10 specific hallmark which are used as the key points or steps for targeted therapy against these cancers. Extending the number of these hallmarks to 12 this review article throws light on 44 natural products classifying them according to their target of action. Further, the natural products under consideration are categorized according to the level of evidence present for their anticancer activities.


2021 ◽  
pp. 1-23
Author(s):  
Mohammad Hassan Houshdar Tehrani
Keyword(s):  

2021 ◽  
Vol 25 (12) ◽  
pp. 38-43
Author(s):  
E.V. Kalinina ◽  
L.V. Rudakova

The results of the life cycle assessment (LCA) of oil waste (OW) management and disposal of refineries are presented, which include environmental impacts beyond the implementation of the techniques themselves, but also the production of the necessary material (reagents, materials) and energy (electricity, fuel, steam). LCA demonstrated that the most significant impacts of oil-containing waste treatment and disposal methods are in the categories Ecotoxicity (for freshwater)" and "Human toxicity" (cancer and non-cancer diseases)" resulting from the burning of fossil fuels and the emission of heavy metals (zinc, copper, vanadium, cobalt, chromium, nickel and lead).


2021 ◽  
Vol 2128 (1) ◽  
pp. 012013
Author(s):  
Laila Moataz ◽  
Gouda I. Salama ◽  
Mohamed H. Abd Elazeem

Abstract Skin cancer is becoming increasingly common. Fortunately, early discovery can greatly improve the odds of a patient being healed. Many Artificial Intelligence based approaches to classify skin lesions have recently been proposed. but these approaches suffer from limited classification accuracy. Deep convolutional neural networks show potential for better classification of cancer lesions. This paper presents a fine-tuning on Xception pretrained model for classification of skin lesions by adding a group of layers after the basic ones of the Xception model and all model weights are set to be trained. The model is fine-tuned over HAM10,000 dataset seven classes by augmentation approach to mitigate the data imbalance effect and conducted a comparative study with the most up to date approaches. In comparison to prior models, the results indicate that the proposed model is both efficient and reliable.


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