Search results for: molecular mechanisms of cancer

Authors: Ambika Selvaraj

Abstract:

Magnetic iron oxide nanoparticles (IO) of < 20nm (superparamagnetic) become promising tool in cancer therapy, and integrated nanodevices for cancer detection and screening. The obstacles include particle heterogeneity and cost. It can be overcome by developing monodispersed nanoparticles in economical approach. We have successfully synthesized < 7 nm IO by low temperature controlled technique, in which Fe0 is sandwiched between stabilizer and Fe2+. Size analysis showed the excellent size control from 31 nm at 33°C to 6.8 nm at 10°C. Resultant monodispersed IO were found to be stable for > 50 reuses, proved its applicability in biomedical applications.

Keywords: low temperature synthesis, hybrid iron nanoparticles, cancer therapy, biomedical applications

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Authors: Joseph George, Anne Kotteswara Roa

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Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

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Authors: Zahra Solgi, Hossein Rassi

Abstract:

Colorectal cancer (CRC) is a multi-step disease, and chronic gastric infection with H. pylori could play a role in one or more of the steps in this pathogenic process. Polymorphisms in several miRNAs are considered to increase the risk for the development of CRC by controlling proliferation, apoptosis and H. pylori pathogenesis. Therefore, the aim of this study was to investigate miRNA146a rs2910164 polymorphism and Helicobacter pylori infection in CRC. A total of 65 patients with CRC were divided into 2 groups: 28 patients < 50 years of age and 37 patients ≥ 50 years of age. DNA was extracted from all samples by a standard method and H. pylori cagA and miRNA146a rs2910164 genotypes were determined by PCR method. The results show that there was no significant difference in the frequency of H. pylori cagA gene between the two groups but there was a significant difference in the distribution of rs2910164 genotypes in patients < 50 years of age with the p-value of 0.05 and odds ratio equal to 2.69. On other hand, patients < 50 years of age with genotype CC of miRNA146a showed a significant difference in CRC risk. Furthermore, there was a significant correlation between rs2910164 CC genotype with Helicobacter pylori infection in patients < 50 years of age. The present study suggests that the CC genotype of miRNA146a in combination with H. pylori infection can be effective as risk factors and molecular markers for early diagnosis and treatment of CRC.

Keywords: colorectal cancer, Helicobacter pylori, miRNA146a, rs2910164 polymorphism

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Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular/nanoscale models is demonstrated.

Keywords: cement composite, mechanical properties, molecular dynamics, plasticizer additives

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Authors: Fouzia Perveen, Rumana Qureshi

Abstract:

The presently studied twelve anticancer drugs are the cytotoxic agents which inhibit the replication of DNA and activity of enzymes involved in DNA replication namely topoisomerase-II, polymerase and helicase and have shown remarkable anticancer activity in clinical trials. In this study, we performed molecular docking studies of twelve antitumor drugs against DNA and DNA enzymes in the presence and absence of ascorbic acid (AA) and developed the quantitative structure-activity relationship (QSAR) model for anticancer activity screening. A number of electronic and steric descriptors were calculated using MOE software package. QSAR was established showing a correlation of binding strength with various physicochemical descriptors. Out of these twelve, eight cytotoxic drugs were tested on Non-Small Cell Lung Cancer cell lines (H-157 and H-1299) in the absence and presence of ascorbic acid and experimental IC50 values were calculated. From the docking studies, binding constants were calculated indicating the strength of drug-DNA and drug-enzyme complex formation and it was correlated to the IC50 values (both experimental and theoretical). These results can offer useful references for directing the molecular design of DNA enzyme inhibitor with improved anticancer activity.

Keywords: ascorbic acid, binding constant, cytotoxic agents, cell culture, DNA, DNA enzymes, molecular docking

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Authors: Rahul Agarwal, Ashutosh Singh

Abstract:

Colorectal cancer (CRC) also refers as bowel cancer or colon cancer. It involves the development of abnormal growth of cells in colon or rectum part of the body. This work leads to the development of a miRNA database in colorectal cancer. We named this database- miCoRe. This database comprises of all validated colon-rectal cancer miRNAs information from various published literature with an effectual knowledge based information retrieval system. miRNAs have been collected from various published literature reports. MySQL is used for main-framework of miCoRe while the front-end was developed in PHP script. The aim of developing miCoRe is to create a comprehensive central repository of colorectal carcinoma miRNAs with all germane information of miRNAs and their target genes. The current version of miCoRe consists of 238 miRNAs which are known to be implicated in malignancy of CRC. Alongside with miRNA information, miCoRe also contains the information related to the target genes of these miRNA. miCoRe furnishes the information about the mechanism of incidence and progression of the disease, which would further help the researchers to look for colorectal specific miRNAs therapies and CRC specific targeted drug designing. Moreover, it will also help in development of biomarkers for the better and early detection of CRC and will help in better clinical management of the disease.

Keywords: colorectal cancer, database, miCoRe, miRNAs

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Authors: Ali Azeem, Seung-Cheol Hong

Abstract:

This study focuses on the epidemiological association between childhood leukaemia & adult brain cancer to offer strong evidence that extremely low-frequency magnetic field (ELF-MF) produced from power lines caused cancer. It also gives a comprehensive literature review on epidemiological studies of ELF-MF risk associated with HVTL and childhood leukaemia & adult brain cancer. From the literature review, it is concluded that there is a weak association present between ELF-MF and childhood leukaemia. No consistent association was present between brain cancer and ELF-MF. This study is done on Scielo data and PubMed using the terms extremely low-frequency magnetic field (ELF-MF+cancer), adult brain cancer, high power transmission lines, etc., for the past 10 years.

Keywords: childhood leukaemia, high voltage transmission lines, acute lymphoblastic leukaemia, power lines

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Authors: Leah Ning

Abstract:

This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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Authors: Richard Renou, Laurent Soulard

Abstract:

Lasers are widely used in glass material processing, from waveguide fabrication to channel drilling. The gradual damage of glass optics under UV lasers is also an important issue to be addressed. Glass materials (including metallic glasses) can undergo a permanent densification under laser-induced shock loading. Despite increased interest on interactions between laser and glass materials, little is known about the structural mechanisms involved under shock loading. For example, the densification process in silica glasses occurs between 8 GPa and 30 GPa. Above 30 GPa, the glass material returns to the original density after relaxation. Investigating these unusual mechanisms in silica glass will provide an overall better understanding in glass behaviour. Non-Equilibrium Molecular Dynamics simulations (NEMD) were carried out in order to gain insight on the silica glass microscopic structure under shock loading. The shock was generated by the use of a piston impacting the glass material at high velocity (from 100m/s up to 2km/s). Periodic boundary conditions were used in the directions perpendicular to the shock propagation to model an infinite system. One-dimensional shock propagations were therefore studied. Simulations were performed with the STAMP code developed by the CEA. A very specific structure is observed in a silica glass. Oxygen atoms around Silicon atoms are organized in tetrahedrons. Those tetrahedrons are linked and tend to form rings inside the structure. A significant amount of empty cavities is also observed in glass materials. In order to understand how a shock loading is impacting the overall structure, the tetrahedrons, the rings and the cavities were thoroughly analysed. An elastic behaviour was observed when the shock pressure is below 8 GPa. This is consistent with the Hugoniot Elastic Limit (HEL) of 8.8 GPa estimated experimentally for silica glasses. Behind the shock front, the ring structure and the cavity distribution are impacted. The ring volume is smaller, and most cavities disappear with increasing shock pressure. However, the tetrahedral structure is not affected. The elasticity of the glass structure is therefore related to a ring shrinking and a cavity closing. Above the HEL, the shock pressure is high enough to impact the tetrahedral structure. An increasing number of hexahedrons and octahedrons are formed with the pressure. The large rings break to form smaller ones. The cavities are however not impacted as most cavities are already closed under an elastic shock. After the material relaxation, a significant amount of hexahedrons and octahedrons is still observed, and most of the cavities remain closed. The overall ring distribution after relaxation is similar to the equilibrium distribution. The densification process is therefore related to two structural mechanisms: a change in the coordination of silicon atoms and a cavity closing. To sum up, non-equilibrium molecular dynamics were carried out to investigate silica behaviour under shock loading. Analysing the structure lead to interesting conclusions upon the elastic and the densification mechanisms in glass materials. This work will be completed with a detailed study of the mechanism occurring above 30 GPa, where no sign of densification is observed after the material relaxation.

Keywords: densification, molecular dynamics simulations, shock loading, silica glass

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Authors: Ravinder Bahl, Jamini Sharma

Abstract:

The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

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Authors: Yemane Tadesse Gebreslassie, Fisseha Guesh Gebremeskel

Abstract:

Nanotechnology has made remarkable advancements in recent years, revolutionizing various scientific fields, industries, and research institutions through the utilization of metal and metal oxide nanoparticles. Among these nanoparticles, copper oxide nanoparticles (CuO NPs) have garnered significant attention due to their versatile properties and wide-range applications, particularly, as effective antimicrobial and anticancer agents. CuO NPs can be synthesized using different methods, including physical, chemical, and biological approaches. However, conventional chemical and physical approaches are expensive, resource-intensive, and involve the use of hazardous chemicals, which can pose risks to human health and the environment. In contrast, biological synthesis provides a sustainable and cost-effective alternative by eliminating chemical pollutants and allowing for the production of CuO NPs of tailored sizes and shapes. This comprehensive review focused on the green synthesis of CuO NPs using various biological resources, such as plants, microorganisms, and other biological derivatives. Current knowledge and recent trends in green synthesis methods for CuO NPs are discussed, with a specific emphasis on their biomedical applications, particularly in combating cancer and microbial infections. This review highlights the significant potential of CuO NPs in addressing these diseases. By capitalizing on the advantages of biological synthesis, such as environmental safety and the ability to customize nanoparticle characteristics, CuO NPs have emerged as promising therapeutic agents for a wide range of conditions. This review presents compelling findings, demonstrating the remarkable achievements of biologically synthesized CuO NPs as therapeutic agents. Their unique properties and mechanisms enable effective combating against cancer cells and various harmful microbial infections. CuO NPs exhibit potent anticancer activity through diverse mechanisms, including induction of apoptosis, inhibition of angiogenesis, and modulation of signaling pathways. Additionally, their antimicrobial activity manifests through various mechanisms, such as disrupting microbial membranes, generating reactive oxygen species, and interfering with microbial enzymes. This review offers valuable insights into the substantial potential of biologically synthesized CuO NPs as an alternative approach for future therapeutic interventions against cancer and microbial infections.

Keywords: copper oxide nanoparticles, green synthesis, nanotechnology, microbial infection

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

Abstract:

Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: Abuelquasim. M. Hassan, Namarig .S. Mohammed, Samah F. Mohammed, Wafaa. A. Mohammed, Wafaa M. Edriss, Amel A. Ahmed, Elfadil M. Abass

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Introduction: Cytomegalovirus (CMV), a common virus, usually causes asymptomatic infections in immunocompetent hosts; however, it may lead to serious complications especially in cancer patients. Objectives: This study was conducted to determine the seroprevalence of human cytomegalovirus (HCMV) among leukemia, breast and prostate cancer patients attending at Radiation Isotope-Center-Khartoum (RICK) from April to August 2016. Material and Methods: A total of 91 subjects were included: 30 leukemic, 22 breast cancer and 29 prostate cancer patients.10 of them were healthy and used as control group, serum samples were collected and tested for CMV IgG & IgM using enzyme-linked immune sorbent assay (ELISA). Result: Of the control group, 9/10 (9.9%) were seropositive for CMV IgG and 1/10 (1.09%) were sero positive for IgM. Also, all cancer groups demonstrated presence of IgG antibody classes as: The percentage of positive results in prostate, breast cancer and leukemia were 35.8 %, 37.2%, and 35.3% respectively. Conclusion: There was no significant correlation between leukemia, breast, prostate and HCMV.

Keywords: cytomegalovirus, serodiagnostic, breast cancer, leukemia

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Authors: Eddy K. Mukadi

Abstract:

This work is a documentary and descriptive study devoted to the epidemiological, clinical, histopathological and therapeutic profile of breast cancer deals with the department of gynecology and obstetrics of the university clinics of Kinshasa during the period from 1 January 2014 to 31 December 2014. We have identified 56 cases of breast cancer. These cancers accounted for 45.2% of gynecological mammary cancers. The youngest in our series was 18 years old while the oldest was 74 years old; And the mean age of these patients was 43.4 years and mostly multiparous (35.7%). Brides (60.7%) and bachelors (26.8%) were the most affected by breast cancer. The reasons for consultation were dominated by nodules in the breast (48.2%) followed by pain (35.7%) and nipple discharge (14.3%). In 89.2% of the cases, it was the advanced clinical stage (stage 3 and 4) and the infiltrating ductal carcinoma was the most frequent histological type (75%) The malignant tumor was mainly in the left breast (55.3%), and chemotherapy with hormone therapy and patey was the most convenient treatment (42.8%), while patey mastectomy was performed in 12.5% of patients. Because of the high incidence of breast cancer identified in our study, some preventive measures must be taken into account to address this public health problem, including breast autopalpation once a month, Early detection system development of a national breast cancer policy and the implementation of a national breast cancer control program.

Keywords: breast cancer, histopathological profile, epidemiological profile, Kinshasa

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Authors: Farman Ali, Asif Mahmood

Abstract:

The utilization of genetic markers in prostate cancer management represents a significant advance in personalized medicine, offering the potential for more precise diagnosis and tailored treatment strategies. This paper explores the pivotal role of genetic markers in the diagnosis and treatment of prostate cancer, emphasizing their contribution to the identification of individual risk profiles, tumor aggressiveness, and response to therapy. By integrating current research findings, we discuss the application of genetic markers in developing targeted therapies and the implications for patient outcomes. Despite the promising advancements, challenges such as accessibility, cost, and the need for further validation in diverse populations remain. The paper concludes with an outlook on future directions, underscoring the importance of genetic markers in revolutionizing prostate cancer care.

Keywords: prostate cancer, genetic markers, personalized medicine, BRCA1 and BRCA2

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Authors: Maria Pintea, Nigel Mason

Abstract:

Induced chemistry is one of the newest pathways in the nanotechnology field with applications in the focused electron beam induced processes for deposition of nm scale structures. Si(OPr)₄ and Ti(OEt)₄ are two of the precursors that have not been so extensively researched, though highly sought for semiconductor and medical applications fields, the two compounds make good candidates for FEBIP and are the subject of velocity slice map imaging analysis for deposition purposes, offering information on kinetic energies, fragmentation channels, and angular distributions. The velocity slice map imaging technique is a method used for the characterization of molecular dynamics of the molecule and the fragmentation channels as a result of induced chemistry. To support the gas-phase analysis, Meso-Bio-Nano simulations of irradiation dynamics studies are employed with final results on Fe(CO)₅ deposited on various substrates. The software is capable of running large scale simulations for complex biomolecular, nano- and mesoscopic systems with applications to thermos-mechanical DNA damage, complex materials, gases, nanoparticles for cancer research and deposition applications for nanotechnology, using a large library of classical potentials, many-body force fields, molecular force fields involved in the classical molecular dynamics.

Keywords: focused electron beam induced deposition, FEBID, induced chemistry, molecular dynamics, velocity map slice imaging

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Authors: Nadeem A. Kizilbash

Abstract:

The study aimed to compare the histopathological characterization of prostate cancer using the conventional and 2005 ISUP modified Gleason system. It employed samples from 40 prostate cancer patients employing resection, biopsies and RP. The majority of cases (95%) comprised adenocarcinoma of the prostate. The results showed that there is migration or upgrading of scores to higher values on using the 2005 ISUP modified Gleason system and an increase in a score of 7 in more than 45% of the cases.

Keywords: prostate cancer, conventional gleason grading, 2005 ISUP modified gleason system, histopathology

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Authors: Desta Gebretekle Shiferaw, Balakrishna Kalluraya

Abstract:

Oxadiazoles and their derivatives with thioether functionalities represent a new and exciting class of physiologically active heterocyclic compounds. Several molecules with these moieties play a vital role in pharmaceuticals because of their diverse biological activities. This paper describes a new class of 1,3,4- oxadiazole-2-thioethers with acetophenone, coumarin, and N-phenyl acetamide residues (S-alkylation), with the hope that the addition of various biologically active molecules will have a synergistic effect on anticancer activity. The structure of the synthesized title compounds was determined by the combined methods of IR, proton-NMR, carbon-13-NMR, and mass spectrometry. Further, all the newly prepared molecules were assessed against their antioxidant activity. Furthermore, four compounds were assessed for their molecular docking interactions and cytotoxicity activity. The synthesized derivatives have shown moderate antioxidant activity compared to the standard BHA. The IC50 of the tilted molecules (11b, 11c, 13b, and 14b) observed for in vitro anti-cancer activities were 11.20, 15.73, 59.61, and 27.66 g/ml at 72-hour treatment time against the A549 cell lines, respectively. The tested compounds' biological evaluation showed that 11b is the most effective molecule in the series.

Keywords: antioxidant activity, cytotoxicity activity, molecular docking, 1, 3, 4-Oxadiazole-2 thioether derivatives

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Authors: Yemane Tadesse Gebreslassie, Fisseha Guesh Gebremeskel

Abstract:

Nanotechnology has made remarkable advancements in recent years, revolutionizing various scientific fields, industries, and research institutions through the utilization of metal and metal oxide nanoparticles. Among these nanoparticles, copper oxide nanoparticles (CuO NPs) have garnered significant attention due to their versatile properties and wide-range applications, particularly, as effective antimicrobial and anticancer agents. CuO NPs can be synthesized using different methods, including physical, chemical, and biological approaches. However, conventional chemical and physical approaches are expensive, resource-intensive, and involve the use of hazardous chemicals, which can pose risks to human health and the environment. In contrast, biological synthesis provides a sustainable and cost-effective alternative by eliminating chemical pollutants and allowing for the production of CuO NPs of tailored sizes and shapes. This comprehensive review focused on the green synthesis of CuO NPs using various biological resources, such as plants, microorganisms, and other biological derivatives. Current knowledge and recent trends in green synthesis methods for CuO NPs are discussed, with a specific emphasis on their biomedical applications, particularly in combating cancer and microbial infections. This review highlights the significant potential of CuO NPs in addressing these diseases. By capitalizing on the advantages of biological synthesis, such as environmental safety and the ability to customize nanoparticle characteristics, CuO NPs have emerged as promising therapeutic agents for a wide range of conditions. This review presents compelling findings, demonstrating the remarkable achievements of biologically synthesized CuO NPs as therapeutic agents. Their unique properties and mechanisms enable effective combating against cancer cells and various harmful microbial infections. CuO NPs exhibit potent anticancer activity through diverse mechanisms, including induction of apoptosis, inhibition of angiogenesis, and modulation of signaling pathways. Additionally, their antimicrobial activity manifests through various mechanisms, such as disrupting microbial membranes, generating reactive oxygen species, and interfering with microbial enzymes. This review offers valuable insights into the substantial potential of biologically synthesized CuO NPs as an alternative approach for future therapeutic interventions against cancer and microbial infections.

Keywords: biological synthesis, copper oxide nanoparticles, microbial infection, nanotechnology

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Authors: Yong Chen

Abstract:

To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Bouchaïb Gazzaz, Hamid El Amri, Hind Dehbi, Abderraouf Hilali

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Medical cannabis has been cultivated and used in many countries around the world. The story of the use of cannabis as a therapeutic agent is difficult to trace, in particular, because the laws regulating its production, distribution, possession, and consumption are relatively recent. Nowadays, in countries where it is authorized, medical cannabis is used in a very wide variety of illnesses and pathologies, particularly in cancer cures. Presently, cannabinoid receptor agonists (like nabilone and dronabinol) are used for reducing chemotherapy induced vomiting. This review aims to discuss a recent finding on the use of therapeutic cannabis in patients with cancer. First, this work addresses the progress made in the use of cannabinoids as therapeutic agent and their application in the treatment of different types of cancer. Secondly, a detailed analysis of the pharmacogenetic aspect of cannabis will be discussed.

Keywords: cannabinoids, endocannabinoids system, cancer treatment, cannabinoid receptors, genetic polymorphism, pharmacogenomics

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Authors: Ziyun Li, Jiudi Zhong, June Zhang

Abstract:

Background: The diagnosis and treatment of lung cancer lead to varying degrees of psychological and social maladjustment among patients with lung cancer. Understanding psychosocial adjustment (PA) and its influencing factors in young and middle-aged lung cancer patients is essential to help them return to society and lead a normal life. Objectives: This study aims to examine the mediating role of resilience in the association between stigma and psychosocial adjustment among young and middle-aged patients with lung cancer. Methods: A total of 235 patients with lung cancer were recruited from a tertiary grade A cancer center in southern China and investigated using a self-designed general information questionnaire, Psychosocial Adjustment to Illness Scale Self-Report, Social Impact Scale, and Conner-Davidson Resilience Scale. Results: The mean score of PA was (32.61±14.75), and its influencing factors included treatment modalities, stigma, and resilience. The total effect of stigma on PA was significant (total effect=0.418, SE=0.045, 95%CI [0.310-0.497]), and a positive indirect effect was identified for stigma on PA via resilience (indirect effect=0.143, SE=0.041, 95% CI [0.075-0.236]). Conclusion: Stigma and resilience are significantly associated with PA, and resilience is also a mediating variable between stigma and PA. This study suggests that individualized interventions can be made to improve the PA by alleviating their stigma, or by enhancing their resilience in young and middle-aged lung cancer patients.

Keywords: psychosocial adjustment, lung cancer, cancer caring, nursing, young and middle-aged

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Authors: Monisha Isaac

Abstract:

Use of molecular markers for selecting plants with desired traits has been started long back. Due to their heritable characteristics, they are useful for identification and characterization of specific genotypes. The study involves various types of molecular markers used to select multiple desired characters in plants, their properties, and advantages to improve crop productivity in adverse climatological conditions for the purpose of providing food security to fast-growing global population. The study shows that genetic similarities obtained from molecular markers provide more accurate information and the genetic diversity can be better estimated from the genetic relationship obtained from the dendrogram. The information obtained from markers assisted characterization is more suitable for the crops of economic importance like sugarcane.

Keywords: molecular markers, crop productivity, genetic diversity, genotype

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Authors: Juliani Rianto, Emma Lumby, Tracey Smith

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Cancer patients’ survival are growing with the new approach and therapy in oncology medicine. Cancer is now a new chronic disease, and rehabilitation program has become an ongoing program as part of cancer care. The focus of Cancer rehabilitation is maximising person’s physical and emotional function, stabilising general health and reducing unnecessary hospital admission. In Australia there are 150000 newly diagnosed cancer every year, and the most common Cancer are prostate, Breast, Colorectal, Melanoma and Lung Cancer. Through referral from the oncology team, we recruited cancer patient into our cancer rehabilitation program. Patients are assessed by our multi-disciplinary team including rehabilitation specialist, physiotherapist, occupational therapist, dietician, exercise physiologist, and psychologist. Specific issues are identified, including pain, side effect of chemo and radiation therapy and mental well-being. The goals were identified and reassessed every fortnight. Common goals including nutritional status, improve endurance and exercise performance, working on balance and mobility, improving emotional and vocational state, educational program for insomnia and tiredness, and reducing hospitalisation are identified and assessed. Patients are given 2 hours exercise program twice a week for 6 weeks with focus on aerobic and weight exercises and education sessions. Patients are generally benefited from the program. The quality of life is improved, support and interaction from the therapist has played an important factor in directing patient for their goals.

Keywords: cancer, exercises, benefit, mental health

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Authors: Nan Deng, Zhenqiu Liu

Abstract:

Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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Authors: Kamta P. Namdeo

Abstract:

Novel thiazolidino-(3,2-b)-1, 2,4-triazole-5(6H)-one derivatives were synthesized, and anticancer activity was studied on human breast cancer cell line MFC7. It showed a significant decrease in cell viability with reference to the standard. The findings suggest that nitro-substituted compound showed best anticancer activity and activity was due to the triazole and thiazolidinone hetero nucleus present in the structure.

Keywords: anti-cancer, adriamycine, thiazolidinone, 1, 2, 4-triazole, thiazolidino-triazolone

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Authors: K. R. Thabethe, G. A. Adefolaju, M. J. Hosie

Abstract:

Cervical cancer is the third most commonly diagnosed cancer globally and it is one of three AIDS defining malignancies. Highly active antiretroviral therapy (HAART) is a combination of three or more antiretroviral drugs and has been shown to play a significant role in reducing the incidence of some AIDS defining malignancies, although its effect on cervical cancer is still unclear. The aim of this study was to investigate the relationship between cervical cancer and HAART. This was achieved by studying the expression of two signalling molecules expressed in cervical cancer; MUC1 and P65. Following the 24 hour treatment of a cervical cancer cell line, HCS-2, with drugs which are commonly used as part of HAART at their clinical plasma concentrations, real-time qPCR and immunofluorescence were used in order to study gene and protein expression. A one way ANOVA followed by a Tukey Kramer Post Hoc test was conducted using JMP 11 software on both sets of data. The drug classified as a protease inhibitor (PI) (i.e. LPV/r) reduced MUC1 and P65 gene and protein expression more than the other drug tested. PIs are known to play a significant role in cell death, therefore the cells were thought to be more susceptible to cell death following treatment with PIs. In conclusion, the drugs used, especially the PI showed some anticancer effects by facilitating cell death through decreased gene and protein expression of MUC1 and P65 and present promising agents for cancer treatment.

Keywords: cervical cancer, haart, MUC1, P65

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Authors: Suveen Kumar

Abstract:

Oral cancer (OC) is the sixth most death causing cancer in world which includes tumour of lips, floor of the mouth, tongue, palate, cheeks, sinuses, throat, etc. Conventionally, the techniques used for OC detection are toluidine blue staining, biopsy, liquid-based cytology, visual attachments, etc., however these are limited by their highly invasive nature, low sensitivity, time consumption, sophisticated instrument handling, sample processing and high cost. Therefore, we developed biosensing chips for non-invasive detection of OC via CYFRA-21-1 biomarker. CYFRA-21-1 (molecular weight: 40 kDa) is secreted in saliva of OC patients which is a non-invasive biological fluid with a cut-off value of 3.8 ng mL-1, above which the subjects will be suffering from oral cancer. Therefore, in first work, 3-aminopropyl triethoxy silane (APTES) functionalized zirconia (ZrO2) nanoparticles (APTES/nZrO2) were used to successfully detect CYFRA-21-1 in a linear detection range (LDR) of 2-16 ng mL-1 with sensitivity of 2.2 µA mL ng-1. Successively, APTES/nZrO2-RGO was employed to prevent agglomeration of ZrO2 by providing high surface area reduced graphene oxide (RGO) support and much wider LDR (2-22 ng mL-1) was obtained with remarkable limit of detection (LOD) as 0.12 ng mL-1. Further, APTES/nY2O3/ITO platform was used for oral cancer bioseneor development. The developed biosensor (BSA/anti-CYFRA-21-1/APTES/nY2O3/ITO) have wider LDR (0.01-50 ng mL-1) with remarkable limit of detection (LOD) as 0.01 ng mL-1. To improve the sensitivity of the biosensing platform, nanocomposite of yattria stabilized nanostructured zirconia-reduced graphene oxide (nYZR) based biosensor has been developed. The developed biosensing chip having ability to detect CYFRA-21-1 biomolecules in the range of 0.01-50 ng mL-1, LOD of 7.2 pg mL-1 with sensitivity of 200 µA mL ng-1. Further, the applicability of the fabricated biosensing chips were also checked through real sample (saliva) analysis of OC patients and the obtained results showed good correlation with the standard protein detection enzyme linked immunosorbent assay (ELISA) technique.

Keywords: non-invasive, oral cancer, nanomaterials, biosensor, biochip

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Authors: Sajadian Akram, Tavasoli F.

Abstract:

Breast cancer is the second most common cancer in the world and certainly the most frequent cancer mostly among women. This study was aimed to compare the effectiveness of individual counseling and group narrative therapy on female patients' life expectancy afflicted by breast cancer. The present study is a pre-test-post-test clinical trial. Fifty-five patients with breast cancer were randomly selected in the follow-up period and after their active medical treatment completion. Then, they were randomly divided into two groups: individual counseling and group counseling. Herth hope index (HHI) was used to measure the patients' hope level. Data were analyzed using t-test and SPSS software. hope rate was statistically significant in both groups receiving individual and group narrative therapy in the post-test compared to the pre-test (P <00000). Moreover, the comparative evaluation of hope in both groups (individual & group counseling) in the post-test showed that group narrative counseling is more effective than individual narrative counseling (P <00000). Conclusion: Narrative therapy promotes hope in breast cancer patients effectively. Due to the nature of breast cancer and its psychological effects in the post-treatment period, providing narrative group therapy can improve life quality. Patients' life quality changes in tandem with changes in hope.

Keywords: hope, narrative therapy, counseling, breast cancer

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Authors: Abdul-Monim Batiha

Abstract:

Aim: The aim of this study were to correlate Jordanian cancer patients’ quality of life and fatigue with selected variables (age, sex, religion, marital status, level of education, type of cancer, number of people living in the same household, type of radiotherapy, dose of radiotherapy, and hemoglobin level). Background: Radiotherapy and chemotherapy remain devastating agents that altered patients’ normal lives. Methods: A correlational design was used in this study to 80 cancer patients and required radiotherapy treatment using a convenience sampling procedure. Results: No significant differences were found in the relationship between quality of life scores and selected variables. A significant negative relationship was found between quality of life scores and the side effects of radiotherapy treatment. Significant positive relationships were found between fatigue scores measured by Piper Fatigue Scale and cancer complications, and radiotherapy side effects. Conclusion: Cancer patients’ quality of life and fatigue are affected by radiotherapy’s side effects and cancer complications. Implications for Nursing: Nurses should try to prevent and manage the negative side effects of radiotherapy and complications of cancer. Such an initiative would serve to design specific nursing interventions that have the potential to help patients enjoy their lives and perform their activities.

Keywords: cancer patients, piper fatigue scale, fatigue, quality of life, radiotherapy

Procedia PDF Downloads 538