Search results for: cancer network

Authors: Diwei Lin, Amanda Jh. Tan

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We present a very rare case of de novo large cell neuroendocrine carcinoma of the prostate (LCNEC) in an 84-year-old male on a background of high-grade, muscle-invasive transitional cell carcinoma of the bladder. While NE tumours account for 1% to 5% of all cases of prostate cancer and scattered NE cells can be found in 10% to 100% of prostate adenocarcinomas, pure LCNEC of the prostate is extremely rare. Most LCNEC of the prostate is thought to originate by clonal progression under the selection pressure of therapy and refractory to long-term hormonal treatment for adenocarcinoma of the prostate. De novo LCNEC is only described in case reports and is thought to develop via direct malignant transformation. Limited data in the English literature makes it difficult to accurately predict the prognosis of LCNEC of the prostate. However, current evidence suggesting that increasing NE differentiation in prostate adenocarcinoma is associated with a higher stage, high-grade disease, and a worse prognosis.

Keywords: large cell neuroendocrine cancer, prostate cancer, refractory cancer, medical and health sciences

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Authors: Wilfred Elliam

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Background: Pain is a prevalent and debilitating symptom among breast cancer patients, impacting their quality of life and overall well-being. The experience of pain in this population is multifaceted, influenced by a combination of disease-related factors, treatment side effects, and individual characteristics. Despite advancements in cancer treatment and pain management, many breast cancer patients continue to suffer from chronic pain, which can persist long after the completion of treatment. Understanding the progression of pain in breast cancer patients over time and identifying its correlates is crucial for effective pain management and supportive care strategies. The purpose of this research is to understand the patterns and progression of pain experienced by breast cancer survivors over time. Methods: Data were collected from breast cancer patients at Hartford Hospital at four time points: baseline, 3, 6 and 12 weeks. Key variables measured include pain, body mass index (BMI), fatigue, musculoskeletal pain, sleep disturbance, and demographic variables (age, employment status, cancer stage, and ethnicity). Binomial generalized linear mixed models were used to examine changes in pain and symptoms over time. Results: A total of 100 breast cancer patients aged  18 years old were included in the analysis. We found that the effect of time on pain (p = 0.024), musculoskeletal pain (p= <0.001), fatigue (p= <0.001), and sleep disturbance (p-value = 0.013) were statistically significant with pain progression in breast cancer patients. Patients using aromatase inhibitors have worse fatigue (<0.05) and musculoskeletal pain (<0.001) compared to patients with Tamoxifen. Patients who are obese (<0.001) and overweight (<0.001) are more likely to report pain compared to patients with normal weight. Conclusion: This study revealed the complex interplay between various factors such as time, pain, sleep disturbance in breast cancer patient. Specifically, pain, musculoskeletal pain, sleep disturbance, fatigue exhibited significant changes across the measured time points, indicating a dynamic pain progression in these patients. The findings provide a foundation for future research and targeted interventions aimed at improving pain in breast cancer patient outcomes.

Keywords: breast cancer, chronic pain, pain management, quality of life

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Authors: Nima Samie, Batoul Sadat Haerian, Sekaran Muniandy, M. S. Kanthimathi

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Colon and breast cancers are categorized as the most prevalent types of cancer worldwide. Recently, the broad clinical application of metal complex compounds has led to the discovery of potential therapeutic drugs. The aim of this study was to evaluate the cytotoxic action of a selected nickel complex compound (NCC) against human colon and breast cancer cells. In this context, we determined the potency of the compound in the induction of apoptosis, cell cycle arrest, and cytoskeleton rearrangement. HT-29, WiDr, CCD-18Co, MCF-7 and Hs 190.T cell lines were used to determine the IC50 of the compound using the MTT assay. Analysis of apoptosis was carried out using immunofluorescence, acridine orange/ propidium iodide double staining, Annexin-V-FITC assay, evaluation of the translocation of NF-kB, oxygen radical antioxidant capacity, quenching of reactive oxygen species content , measurement of LDH release, caspase-3/-7, -8 and -9 assays and western blotting. The cell cycle arrest was examined using flowcytometry and gene expression was assessed using qPCR array. Results showed that our nickel complex compound displayed a potent suppressive effect on HT-29, WiDr, MCF-7 and Hs 190.T after 24 h of treatment with IC50 value of 2.02±0.54, 2.13±0.65, 3.76±015 and 3.14±0.45 µM respectively. This cytotoxic effect on normal cells was insignificant. Dipping in the mitochondrial membrane potential and increased release of cytochrome c from the mitochondria indicated induction of the intrinsic apoptosis pathway by the nickel complex compound. Activation of this pathway was further evidenced by significant activation of caspase 9 and 3/7.The nickel complex compound (NCC) was also shown activate the extrinsic pathways of apoptosis by activation of caspase-8 which is linked to the suppression of NF-kB translocation to the nucleus. Cell cycle arrest in the G1 phase and up-regulation of glutathione reductase, based on excessive ROS production were also observed. The results of this study suggest that the nickel complex compound is a potent anti-cancer agent inducing both intrinsic and extrinsic pathways as well as cell cycle arrest in colon and breast cancer cells.

Keywords: nickel complex, apoptosis, cytoskeletal rearrangement, colon cancer, breast cancer

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Authors: Zakaria Baka, Halima Alem

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Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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Authors: Vidhula Ahire, Amit Kumar, K. P. Mishra, Gauri Kulkarni

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Herbal polyphenols have gained significance because of their increasing promise in prevention and treatment of cancer. Therefore, development of a dietary compound as an effective radiosensitizer and a radioprotector is highly warranted for cervical cancer patients undergoing therapy. This study describes the cytotoxic effects of the flavonoid, ellagic acid (EA) when administered either alone or in combination with gamma radiation on cervical cancer HeLa cells in vitro. Apoptotic index and proliferation were measured by using trypan blue assay. Reproductive cell death was analyzed by clonogenic assay. Propidium iodide staining for flowcytometry was performed to analyze cell cycle modulation. Nuclear and mitochondrial changes were studied with specific dyes. DNA repair kinetics was analyzed by immunofluorescence assay. Evaluation and comparison of EA effects were performed with other clinically used breast cancer drugs. When tumor cells were exposed to 2 and 4 Gy of irradiation in presence of EA (10 μM), it yielded a synergistic cytotoxic effect on cervical cancer cells whereas in NIH3T3 cells it reversed the injury caused by irradiation and abetted in the regaining of normal healthy cells. At 24h ~25foci/cell was observed and 2.6 fold decrease in the mitochondrial membrane potential. Up to 40% cell were arrested in the G1 phase and 20-36% cells exhibited apoptosis. Our results demonstrate the role of increased apoptosis and cell cycle modulation in the mechanism of EA mediated radiosensitization of cervical cancer cells and thus advocating EA as an adjuvant for preclinical trials in cancer chemo- radiotherapy.

Keywords: cervical cancer, ellagic acid, sensitization, radiation therapy

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Authors: Nigar Kantarci Carsibasi

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Coarse-grained elastic network models, namely Gaussian network model (GNM) and Anisotropic network model (ANM), are utilized in order to investigate the fluctuation dynamics of Murine Double Minute 2 (MDM2), which is the native inhibitor of p53. Conformational dynamics of MDM2 are elucidated in unbound, p53 bound, and non-peptide small molecule inhibitor bound forms. With this, it is aimed to gain insights about the alterations brought to global dynamics of MDM2 by native peptide inhibitor p53, and two small molecule inhibitors (HDM201 and NVP-CGM097) that are undergoing clinical stages in cancer studies. MDM2 undergoes significant conformational changes upon inhibitor binding, carrying pieces of evidence of induced-fit mechanism. Small molecule inhibitors examined in this work exhibit similar fluctuation dynamics and characteristic mode shapes with p53 when complexed with MDM2, which would shed light on the design of novel small molecule inhibitors for cancer therapy. The results showed that residues Phe 19, Trp 23, Leu 26 reside in the minima of slowest modes of p53, pointing to the accepted three-finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct regions are identified in MDM2, for which significant conformational changes are observed upon binding. Regions I (residues 50-77) and III (residues 90-105) correspond to the binding interface of MDM2, including (α2, L2, and α4), which are stabilized during complex formation. Region II (residues 77-90) exhibits a large amplitude motion, being highly flexible, both in the absence and presence of p53 or other inhibitors. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 domains, clearly distinguishing the kinetically hot regions. Mode shape analysis revealed that the α4 domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states for proper penetration and binding of p53 and inhibitors, which points to the induced-fit mechanism of p53 binding. P53 interacts with α2 and α4 in a synchronized manner. Collective modes are shifted upon inhibitor binding, i.e., second mode characteristic motion in MDM2-p53 complex is observed in the first mode of apo MDM2; however, apo and bound MDM2 exhibits similar features in the softest modes pointing to pre-existing modes facilitating the ligand binding. Although much higher amplitude motions are attained in the presence of non-peptide small molecule inhibitor molecules as compared to p53, they demonstrate close similarity. Hence, NVP-CGM097 and HDM201 succeed in mimicking the p53 behavior well. Elucidating how drug candidates alter the MDM2 global and conformational dynamics would shed light on the rational design of novel anticancer drugs.

Keywords: cancer, drug design, elastic network model, MDM2

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Authors: Lamis Naddaf, Yuval Tabach

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We identified missense genetic variants with the potential to enhance resistance against cancer. Such a field has not been widely explored as researchers tend to investigate the mutations that cause diseases, in response to the suffering of patients, rather than those mutations that protect from them. In conjunction with the genomic revolution and the advances in genetic engineering and synthetic biology, identifying the protective variants will increase the power of genotype-phenotype predictions and have significant implications for improved risk estimation, diagnostics, prognosis, and even personalized therapy and drug discovery. To approach our goal, we systematically investigated the sites of the coding genomes and selected the alleles that showed a correlation with the species’ cancer resistance. Interestingly, we found several amino acids that are more generally preferred (like the Proline) or avoided (like the Cysteine) by the resistant species. Furthermore, Cancer resistance in mammals and reptiles is significantly predicted by the number of the predicted protecting variants (PVs) a species has. Moreover, PVs-enriched-genes are enriched in pathways relevant to tumor suppression. For example, they are enriched in the Hedgehog signaling and silencing pathways, which its improper activation is associated with the most common form of cancer malignancy. We also showed that the PVs are mostly more abundant in healthy people compared to cancer patients within different human races.

Keywords: cancer resistance, protecting variant, naked mole rat, comparative genomics

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Authors: Fatemeh Zeinali Sehrig

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Background: miRNAs play an important role in the post-transcriptional regulation of genes, including genes involved in DNA methylation (DNMTs), and are also important regulators of oncogenic pathways. The study of microRNAs and DNMTs in breast cancer allows the development of targeted treatments and early detection of this cancer. Methods and Materials: Clinical Patients and Samples: Institutional guidelines, including ethical approval and informed consent, were followed by the Ethics Committee (Ethics code: IR.IAU.TABRIZ.REC.1401.063) of Tabriz Azad University, Tabriz, Iran. In this study, tissues of 100 patients with breast cancer and tissues of 100 healthy women were collected from Noor Nejat Hospital in Tabriz. The basic characteristics of the patients with breast cancer included: 1)Tumor grade(Grade 3 = 5%, Grade 2 = 87.5%, Grade 1 = 7.5%), 2)Lymph node(Yes = 87.5%, No = 12.5%), 3)Family cancer history(Yes = 47.5%, No = 41.3%, Unknown = 11.2%), 4) Abortion history(Yes = 36.2%).In silico methods (data gathering, process, and build networks): Gene Expression Omnibus (GEO), a high-throughput genomic database, was queried for miRNAs expression profiles in breast cancer. For Experimental protocol Tissue Processing, Total RNA isolation, complementary DNA(cDNA) synthesis, and quantitative real time PCR (QRT-PCR) analysis were performed. Results: In the present study, we found significant (p.value<0.05) changes in the expression level of miRNAs and DNMTs in patients with breast cancer. In bioinformatics studies, the GEO microarray data set, similar to qPCR results, showed a decreased expression of miRNAs and increased expression of DNMTs in breast cancer. Conclusion: According to the results of the present study, which showed a decrease in the expression of miRNAs and DNMTs in breast cancer, it can be said that these genes can be used as important diagnostic and therapeutic biomarkers in breast cancer.

Keywords: gene expression omnibus, microarray dataset, breast cancer, miRNA, DNMT (DNA methyltransferases)

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Authors: Animish Jain

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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

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Authors: Sajjad Jafari, Reza Akbari

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Background and Aim: Chrysin, a flavonoid compound found in medicinal plants, honey, and propolis, has potential biological activities that make it an important perspective in the treatment of infectious and cancer diseases. The aim of this review study is to evaluate the biological activities of chrysin in the treatment of infectious and cancer diseases. Material and Methods: The present study is a review study that searched reputable scientific databases such as PubMed, Google Scholar, Scopus, and Web of Science from 2000 to 2023 using keywords such as antimicrobial, antifungal, chrysin, anticancer, antioxidants, and infectious diseases. The researchers examined 25 articles to determine the biological activities of chrysin. Results: Chrysin has high inhibitory or lethal activities on gram-positive and gram-negative bacteria, including Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, Bacillus subtilis, and Enterococcus faeces. It also has anti-biofilm effects and antifungal effects on strains such as Aspergillus niger and Candida albicans. Chrysin also has anticancer effects on various cancers, including colorectal cancer, pancreatic cancer, breast cancer, and MCF-7 cancer, which have been confirmed in vitro and in vivo. Conclusion: Chrysin has the potential as an important therapeutic option in the treatment of infectious and cancer diseases. Its high antimicrobial and anticancer activities, combined with its low toxicity in nanoparticle form, make it a promising candidate for further clinical trials. The production of anti-microbial and anti-cancer drugs from natural substances, such as chrysin, is a valuable contribution to the field of medicine.

Keywords: chrysin, antimicrobial, anticancer, infectious diseases

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Authors: Memnun Seven, Mine Bahar, Aygül Akyüz, Hatice Erdoğan

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Background: The workplace has been deemed a suitable location for educating many women at once about cancer screening. Objective: To determine how group education about early diagnostic methods for breast and cervical cancer affects women’s behavior and readiness to receive mammography and Pap smears. Methods: This semi-interventional study was conducted at a textile factory in Istanbul, Turkey. Female workers (n = 125) were included in the study. A participant identification form and knowledge evaluation form developed for this study, along with the trans-theoretical model, were used to collect data. A 45-min interactive group education was given to the participants. Results: Upon contacting participants 3 months after group education, 15.4% (n = 11) stated that they had since received a mammogram and 9.8% (n = 7) a Pap smear. As suggested by the trans-theoretical model, group education increased participants’ readiness to receive cancer screening, along with their knowledge of breast and cervical cancer. Conclusions: Group education positively impacted women’s knowledge of cancer and their readiness to receive mammography and Pap smears. Group education can therefore potentially create awareness of cancer screening tests among women and improve their readiness to receive such tests.

Keywords: cancer screening, educational intervention, participation, women

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Authors: Nashrawan Naser Taha, Andrew M. Cox

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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

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Authors: C. Panebianco, K. Adamberg, S. Adamberg, C. Saracino, M. Jaagura, K. Kolk, A. Di Chio, P. Graziano, R. Vilu, V. Pazienza

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Background/Aims: Despite recent advances in treatment options, a modest impact on the outcome of the pancreatic cancer (PC) is observed so far. Short-term fasting cycles have the potential to improve the efficacy of chemotherapy against PC. However, diseased people may refuse to follow the fasting regimen and fasting may worsen the weight loss often occurring in cancer patients. Therefore, alternative approaches are needed. The aim of this study was to assess the effect of Engineered Low glycemic food ELGIF mimicking diet on growth of cancer cell lines in vitro and in an in vivo pancreatic cancer mouse xenograft model. Materials and Methods: BxPC-3, MiaPaca-2 and Panc-1 cells were cultured in control and ELGIF mimicking diet culturing condition to evaluate the tumor growth and proliferation pathways. Pancreatic cancer xenograft mice were subjected to ELGIF to assess the tumor volume and weight as compared to mice fed with control diet. Results: Pancreatic cancer cells cultured in ELGIF mimicking medium showed decreased levels of proliferation as compared to those cultured in the standard medium. Consistently, xenograft pancreatic cancer mice subjected to ELGIF diet displayed a significant decrease in tumor growth. Conclusion: A positive effect of ELGIF diet on proliferation in vitro is associated with the decrease of tumor progression in the in vivo PC xenograft mouse model. These results suggest that engineered dietary interventions could be supportive as synergistic approach to enhance the efficacy of existing cancer treatments in pancreatic cancer patients.

Keywords: functional food, microbiota, mouse model, pancreatic cancer

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: Valerie A. Conrade

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Introduction: A large body of literature suggests patients who complete fecal immunochemical testing (FIT) kits are likely to identify colorectal cancer sooner than those who do not complete FIT kits. Background: Patients who do not participate in preventative measures such as the FIT kit are at a higher risk of colorectal cancer growing unnoticed. The objective was to see if the method the principal investigator (PI) uses to educate clinical staff on the importance of FIT kit administration provides an increased amount of FIT kit dissemination to patients post clinical education. Methodologies: Data collection via manual tallies took place before and after the clinical staff was educated on the importance of FIT kits. Results: The results showed an increase in FIT kit dissemination post clinical staff education. Through enhanced instruction to the clinical staff regarding the importance of FIT kits, expanding their knowledge on preventative measures to detect colorectal cancer positively impacted nurses and, in turn, their patients.

Keywords: colon cancer, education, fecal immunochemical testing, nursing

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Authors: Arindam Pramanik, Parimal Karmakar

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We have explored the synergistic anti-cancer activity of copper ion and acetylacetone complex containing 1,3 diketone group (like curcumin) in metallorganic compound “Copper acetylacetonate” (CuAA). The cytotoxicity mechanism of CuAA complex was evaluated on various cancer cell lines in vitro. Among these, reactive oxygen species (ROS), glutathione level (GSH) in the cell was found to increase. Further mitochondrial membrane damage was observed. The fate of cell death was found to be induced by apoptosis. For application purpose, we have developed a novel biodegradable, non-toxic polymer-based nanoparticle which has hydrophobically modified core for loading of the CuAA. Folic acid is conjugated on the surface of the polymer (chitosan) nanoparticle for targeting to cancer cells for minimizing toxicity to normal cells in-vivo. Thus, this novel drug CuAA has an efficient anticancer activity which has been targeted specifically to cancer cells through polymer nanoparticle.

Keywords: anticancer, apoptosis, copper nanoparticle, targeted drug delivery

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Authors: Mohsen Dourandish

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Iran has a huge pipeline network in every state of country which is the longest and vastest pipeline network after Russia and USA (360,000 Km high pressure pipelines and 250,000 Km distribution networks). Furthermore in recent years National Iranian Gas Company is planning to develop natural gas network to cover all cities and villages above 20 families, in a way that 97 percent of Iran population will be gas consumer by 2020. In this condition, network resiliency will be the first priority of NIGC and due to that several planning for increasing resiliency of gas network is under construction. The most important strategy of NIGC is converting tree form pattern network to loop gas networks and developing underground gas storage near main gas consuming centers. In this regard NIGC is planning for construction of over 3500 km high-pressure pipeline and also 10 TCM gas storage capacities in UGSs.

Keywords: Iranian gas network, peak shaving, resiliency, underground gas storage

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Authors: Christopher G. Harris, Guy D. Eslick

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Purpose: Lobular carcinoma in situ (LCIS) is a known risk factor for breast cancer of unclear significance when detected in association with invasive carcinoma. This meta-analysis aims to determine the impact of LCIS on local recurrence risk for individuals with breast cancer treated with breast conservation therapy to help guide appropriate treatment strategies. Methods: We identified relevant studies from five electronic databases. Studies were deemed suitable for inclusion where they compared patients with invasive breast cancer and concurrent LCIS to those with breast cancer alone, all patients underwent breast conservation therapy (lumpectomy with adjuvant radiation therapy), and local recurrence was evaluated. Recurrence data were pooled by use of a random effects model. Results: From 1488 citations screened by our search, 8 studies were deemed suitable for inclusion. These studies comprised of 908 cases and 10638 controls. Median follow-up time was 90 months. There was a significantly increased overall risk of local breast cancer recurrence for individuals with LCIS in association with breast cancer following breast conservation therapy [pOR 1.87; 95% CI 1.14-3.04; p = 0.012]. The risk of local recurrence was non-significantly increased at 5 [pOR 1.09; 95% CI 0.48-2.48; p = 0.828] and 10 years [pOR 1.90; 95% CI 0.89-4.06; p = 0.096]. Conclusions: Individuals with LCIS in association with invasive breast cancer have an increased risk of local recurrence following breast conservation therapy. This supports consideration of aggressive local control of LCIS by way of completion mastectomy or re-excision for certain high-risk patients.

Keywords: breast cancer, breast conservation therapy, lobular carcinoma in situ, lobular neoplasia, local recurrence, meta-analysis

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Authors: Alireza Barari, Maryam Firoozi, Maryam Ebrahimzadeh, Romina Roohan Ardeshiri, Maryam Kamarloeei

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Background: The The purpose of this study was to evaluate the effect of six-week aerobic training and taxol consumption on interleukin 8 and Plasminogen Activator Inhibitor-1 (PAI-1) in mice with cervical cancer. Material and method: In this experimental study, 40 female C57 mice, eight weeks old, were randomly divided into 4 groups: cancer, cancer-taxol complement, cancer-training and cancer-training - taxol complement with 10 mice in each group. The implantation of cancerous tumors was performed under the skin of the upper pelvis. The training group completed the endurance training protocol, which included 3 sessions per week, 50 minutes per session, at a speed of 14-18 m/s for six weeks. A dose of 60 mg/ kg/day, a pure extract of Taxol was injected peritoneal Data were analyzed by t-test, One-way ANOVA and post hoc Bonferron's at the significant level P<0. 05. Results: The results showed that there was a significant difference between mean values of interleukin-8 (P < 0.05, F = 12.25) and the plasminogen activator inhibitor-1 (P < 0.05, P=0.10737) in four groups. A significance level of less than 0.05 in Tukey test for both variables also showed a significant difference between the "control" group and the complementary "exercise" group. Namely, six weeks of aerobic training, along with taxol, have a significant effect on the level of plasminogen activator inhibitor-1 and interleukin-8 mice with cervical cancer. Conclusion: Considering the effect of training on these variables, this type of exercise can be used as a complementary therapeutic approach along with other therapies for cervical cancer.

Keywords: cervical cancer, taxol, endurance training, interleukin 8, plasminogen activator inhibitor-1

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Authors: Xiaoping Su, Gabriel G. Malouf

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Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor.

Keywords: lncRNA profiling, breast cancer, HOTAIRM1, tumor suppressor

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Authors: Neda Menbari, Ramin Mehdiabadi

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Background: breast cancer remains a critical global health issue, constituting a leading cause of cancer-related mortality in women. MicroRNAs (miRs) are natural RNA molecules that play an important role in cellular processes and regulate post-transcriptional gene expression. MiR-216b-5p is a miR that acts as a tumor suppressor. The expression levels of FoxM1 and miR-216b-5p in malignant and control cells have been evaluated by quantitative polymerase chain reaction (qPCR) technique and flow cytometry. Results: the results of this study revealed a significant downregulation of miR-216b-5p in cancerous cells compared to the control MCF-10A cells (P=0.0004). Interestingly, the expression of miR-216b-5p exhibited an inverse relationship with key clinical indicators such as tumor size, grade, and lymph node invasion. Conclusion: The study's findings showed the prognostic value of miR-216b-5p levels in breast cancer, and its reduced expression correlates with unfavorable tumor characteristics. This research recommends performing more studies on the role of FoxM1 and miR-216b-5p in breast cancer pathology which potentially paving the way for targeted therapeutic interventions.

Keywords: breast cancer, gene expression, FOXM1, microRNA

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Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: Omer Ibrahim Abdallh Omer

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Cancer patients often face complex medication regimens, leading to challenges in treatment adherence and clinical outcomes. Pharmacist-led medication therapy management (MTM) has emerged as a potential solution to optimize medication use and improve patient outcomes in oncology settings. In this prospective intervention study, we aimed to evaluate the impact of pharmacist-led MTM on treatment adherence and clinical outcomes among cancer patients. Participants were randomized to receive either pharmacist-led MTM or standard care, with assessments conducted at baseline and follow-up visits. Pharmacist interventions included medication reconciliation, adherence counseling, and personalized care plans. Our findings reveal that pharmacist-led MTM significantly improved medication adherence rates and clinical outcomes compared to standard care. Patients receiving pharmacist interventions reported higher satisfaction levels and perceived value in pharmacist involvement in their cancer care. These results underscore the critical role of pharmacists in optimizing medication therapy and enhancing patient-centered care in oncology settings. Integration of pharmacist-led MTM into routine cancer care pathways holds promise for improving treatment outcomes and quality of life for cancer patients.

Keywords: cancer, medications adherence, medication therapy management, pharmacist

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Gunasekaran Raja, Ramkumar Jayaraman, Rajakumar Arul, Kottilingam Kottursamy

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Broadband Wireless Network (BWN) is the promising technology nowadays due to the increased number of smartphones. Buffering scheme using network coding considers the reliability and proper degree distribution in Worldwide interoperability for Microwave Access (WiMAX) multi-hop network. Using network coding, a secure way of transmission is performed which helps in improving throughput and reduces the packet loss in the multicast network. At the outset, improved network coding is proposed in multicast wireless mesh network. Considering the problem of performance overhead, degree distribution makes a decision while performing buffer in the encoding / decoding process. Consequently, BuS (Buffer Scheme) based on network coding is proposed in the multi-hop network. Here the encoding process introduces buffer for temporary storage to transmit packets with proper degree distribution. The simulation results depend on the number of packets received in the encoding/decoding with proper degree distribution using buffering scheme.

Keywords: encoding and decoding, buffer, network coding, degree distribution, broadband wireless networks, multicast

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Authors: Iliya Musa Adamu

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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

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Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

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INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

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Authors: Rizwan Arshad, Alessio Panza, Nimra Inayat, Syeda Mariam Batool Kazmi, Shawana Azmat

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The rapidly expanding use of immunotherapy for a wide range of cancers from late to early stages has, predictably, been accompanied by evidence of inequities in access to these highly effective but costly treatments. In this survey-based case study, we aimed to develop a One-window services model (OWSM) based on Anderson’s behavioral model to enhance competence in accessing cancer medications, particularly immunotherapies, through the analysis of 20 patient surveys conducted in the Armed forces bone marrow transplant center of the district, Rawalpindi from November to December 2022. The purposive sampling technique was used. Cronbach’s alpha coefficient was found to be 0.71. It was analyzed using SPSS version 26 with descriptive analysis, and results showed that the majority of the cancer patients were non-competent to access their prescribed cancer immunotherapy because of individual-level, socioeconomic, and organizational barriers.

Keywords: cancer immunotherapy, one-window services model, accessibility, competence

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Zhaojunfeng

Abstract:

Driven by the national policy of "East Data and Western Calculation", the computing first network will attract a new wave of development. As the foundation of the development of the computing first network, the computing force bearer network has become the key direction of technology research and development in the industry. This article will analyze typical computing force application scenarios and bearing requirements and sort out the SLA indicators of computing force applications. On this basis, this article carries out research and discussion on the key technologies of computing force bearer network in a slice packet network, and finally, gives evolution policy for SPN computing force bearer network to support the development of SPN computing force bearer network technology and network deployment.

Keywords: component-computing force bearing, bearing requirements of computing force application, dual-SLA indicators for computing force applications, SRv6, evolution strategies

Procedia PDF Downloads 116