Search results for: cancer tissue classification

Authors: Nouf A. Aldarmahi, Nesrin I. Tarbiah, Nuha A. Alkhattabi, Huda F. Alshaibi

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Nigella sativa which is known as dark cumin is a well-known example for a widely applicable herbal medicine. Nigella sativa can be effective in a variety of diseases such as hypertension, diabetes, bronchitis, gastrointestinal upset, and cancer. The anticancer effect of Nigella sativa appeared to be mediated by immune-modulatory effect through stimulating human natural killer (NK) cells. This is a type of lymphocytes which is part of the innate immunity, also known as the first line of defense in the body against pathogens. This study investigated the effect of thymoquinone as a major component of Nigella sativa on the molecular cytotoxic pathway of NK cell and the role of thymoquinone therapeutic effect on NK cells. NK cells were cultured with breast tumor cells in different ways and cultured media was collected and the concentration of perforin, granzyme B and interferon-α were measured by ELISA. The cytotoxic effect of NK cells on breast tumor cells was enhanced in the presence of thymoquinone, with increased activity of perforin in NK cells. This improved anticancer effect of thymoquinone on breast cancer cells.

Keywords: breast cancer, cancer cells, natural killer cells, thymoquinone

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Authors: Ji Won Kim, Moo Yeol Lee, Keon Wook Kang

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GV-1001, 16 amino acid fragment of human telomerase reverse transcriptase catalytic subunit (hTERT), has been developed as an injectable cancer vaccine for many types of solid tumors showing high-level of telomerase activity. In the present study, we evaluated the anti-cancer effect of GV-1001 on androgen-receptor-positive prostate cancer. Two signaling pathways, Gs-adenylate cyclase-cAMP and Gq-IP3-Ca2+ pathways play a central role in GnRH receptor (GnRHR)-mediated activities. We found that leuprolide acetate (LA) mainly acted on Gq-mediated Ca2+ signaling, while GV-1001 preferentially acted on cAMP signaling; and both the effects were counteracted by cetrorelix, a GnRHR antagonist. We further tested whether GV-1001 affects tumor growth of human prostate cancer cells in vivo. Prostate tumor xenografts were established using LNCap, androgen receptor-positive prostate cancer cells, and the nude mice bearing tumors were subcutaneously injected with GV-1001 (0.01, 0.1, 1, 10 microg/kg/day) and LA (0.01 microg/kg/day) for 2 weeks. GV-1001 (1 and 10 microg/kg/day) significantly inhibited tumor growth of LNCap xenografts. Interestingly, mRNA expression of MMP2 and MMP9 was significantly suppressed by GV-1001 injection, but not by LA administration. Boyden chamber assay revealed that GV-1001 potently inhibited cell migration of LNCap. Our finding suggests that GV-1001 as a novel GnRHR ligand, has anti-proliferative and anti-migratory effects on androgen receptor-positive prostate cancer cells.

Keywords: GV-1001, GnRH, hTERT, prostate cancer

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Authors: Farideh Halakou, Emel Sen, Attila Gursoy, Ozlem Keskin

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Protein–Protein Interactions (PPIs) mediate major biological processes in living cells. The study of PPIs as networks and analyze the network properties contribute to the identification of genes and proteins associated with diseases. In this study, we have created the sub-networks of brain and lung metastasis from primary tumor in breast cancer. To do so, we used seed genes known to cause metastasis, and produced their interactions through a network-topology based prioritization method named GUILDify. In order to have the experimental support for the sub-networks, we further curated them using STRING database. We proceeded by modeling structures for the interactions lacking complex forms in Protein Data Bank (PDB). The functional enrichment analysis shows that KEGG pathways associated with the immune system and infectious diseases, particularly the chemokine signaling pathway, are important for lung metastasis. On the other hand, pathways related to genetic information processing are more involved in brain metastasis. The structural analyses of the sub-networks vividly demonstrated their difference in terms of using specific interfaces in lung and brain metastasis. Furthermore, the topological analysis identified genes such as RPL5, MMP2, CCR5 and DPP4, which are already known to be associated with lung or brain metastasis. Additionally, we found 6 and 9 putative genes that are specific for lung and brain metastasis, respectively. Our analysis suggests that variations in genes and pathways contributing to these different breast metastasis types may arise due to change in tissue microenvironment. To show the benefits of using structural PPI networks instead of traditional node and edge presentation, we inspect two case studies showing the mutual exclusiveness of interactions and effects of mutations on protein conformation which lead to different signaling.

Keywords: breast cancer, metastasis, PPI networks, protein conformational changes

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Authors: Vivek Bhat, Rohini Kelkar, Sanjay Biswas

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Introduction: Cancer patients are at increased risk of bacterial infections. This may due to the disease process itself, the effect of chemotherapeutic drugs or invasive procedures such as catheterization. A wide variety of bacteria including some emerging pathogens are increasingly being reported from these patients. The incidence of multidrug-resistant organisms particularly in the Gram negative group is also increasing, with higher resistance rates seen to cephalosporins, β-lactam/β-lactam inhibitor combinations, and the carbapenems. This study documents the bacteriological spectrum of infections and their resistance patterns in cancer patients. Methods: This study includes all bacterial isolates recovered from infections cancer patients over a period of 18 months. Samples included Blood cultures, Pus/wound swabs, urine, tissue biopsies, body fluids, catheter tips and respiratory specimens such as sputum and bronchoalveolar lavage (BAL). All samples were processed in the microbiology laboratory as per standard laboratory protocols. Organisms were identified to species level and antimicrobial susceptibility testing was performed manually by the disc diffusion technique or in the Vitek-2 (Biomereux, France) instrument. Interpretations were as per Clinical laboratory Standards Institute (CLSI) guidelines. Results: A total of 1150 bacterial isolates were cultured from 884 test samples during the study period. Of these 227 were Gram-positive and 923 were Gram-negative organisms. Staphylococcus aureus (99 isolates) was the commonest Gram-positive isolate followed by Enterococcus (79) and Gr A Streptococcus (30). Among the Gram negatives, E. coli (304), Pseudomonas aeruginosa (201) and Klebsiella pneumoniae (190) were the most common. Of the Staphylococcus aureus isolates 27.2% were methicillin resistant. Only 5.06% enterococci were vancomycin resistant. High rates of resistance to cefotaxime and ciprofloxacin were seen amongst E. coli (84.8% & 83.55%) and Klebsiella pneumoniae (71 & 62.1%) respectively. Resistance to carbapenems (meropenem) was high at 70% in Acinetobacter spp.; however all isolates were sensitive to colistin. Among the aminoglycosides, amikacin retained good efficacy against Escherichia coli (82.9%) and Pseudomonas aeruginosa (78.1%). Occasional isolates of emerging pathogens such as Chryseobacterium indologens, Roseomonas, and Achromobacter xyloxidans were also recovered. Conclusion: The common infections in cancer patients include respiratory, wound, tract infections and sepsis. The commonest isolates include Staphylococcus aureus, Enterococci, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa. There is a high level of resistance to the commonly used antibiotics among Gram-negative organisms.

Keywords: bacteria, resistance, infection, cancer

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Authors: Maria L. McLeod

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This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers –The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, ten from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting repeated use of specific metaphors and tropes while charting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals with university affiliations, that emphasizes an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. Thus, the use of anecdotal evidence presented in patient narratives could be perceived as being in conflict with this evidence-based model, as the patient stories are not an accurate representation of scientific outcomes related to developing cancer, cancer reoccurrence, or cancer outcomes. The representative patient narratives tend to exclude or downplay adverse responses to treatment, survival rates, integrative and/or complementary cancer treatments, cancer prevention and causes, and barriers to treatment, such as the limitation of insurance plans, costs of treatment, and/or other issues related to access, potentially contributing to false narratives and inaccurate notions of cancer prevention, cancer care treatment and the potential for a cure. Both quantitative and qualitative findings demonstrate that cancer patient stories featured on the blogsites of the nation’s top cancer care centers deemphasize patient agency and, instead, emphasize deference and gratitude toward the institutions where the featured patients received treatment. Along these lines, language choices reflect positive framing of the cancer experience. Accompanying portrait photos of healthy appearing subjects as well as positive-framed headlines, subheads, and pull quotes function similarly, reflecting hopeful, transformative experiences and outcomes over hardship and suffering. Although patient narratives include real, factual scientific details and descriptions of actual events, the stories lack references to more negative realities of cancer diagnosis and treatment. Instead, they emphasize the triumph of survival by which the cancer care center, in the savior/hero role, enables the patient’s success, represented as a cathartic medical journey.

Keywords: cancer framing, cancer stories, medical gaze, patient narratives

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Authors: Kornkanok Noulta, Pornsri Pakeyangkoon, Stephen T. Dubas, Pomthong Malakul, Manit Nithithanakul

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In recent years, interest in the development of material for tissue engineering application has increased considerably. Poly(High Internal Phase Emulsion) (PolyHIPE) foam is a material that is good candidate for used in tissue engineering application due to its 3D structure and highly porous with interconnected pore. The PolyHIPE was prepared from poly (styrene/ethylene glycol dimethacrylate) through high internal phase emulsion polymerization technique and loaded with hydroxyapatite (HA) to improve biocompatibility. To further increase hydrophilicity of the obtained polyHIPE, layer-by-layer polyelectrolyte multilayers (PEM) technique was used. A surface property of polyHIPE was characterized by contact angle measurement. Morphology and pore size was observed by scanning electron microscope (SEM). The cell viability was revealed by the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay technique.

Keywords: polyelectrolyte multilayer thin film, high internal phase emulsion, polyhipe foam, scaffold, tissue engineering

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Authors: Anne Nattembo

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Cervical cancer remains a major public health problem in developing countries, especially in Africa. Effective cervical cancer prevention communication requires identification of behaviors, attitudes and increasing awareness of a given population; thus this study focused on investigating awareness, attitudes, and behavior among female university students towards cervical cancer messages. The study objectives sought to investigate the communication behavior of young adults towards cervical cancer, to understand female students recognition of cervical cancer as a problem, to identify the frames related to cervical cancer and their impact towards audience communication and participation behaviors, to identify the factors that influence behavioral intentions and level of involvement towards cervical cancer services and to make recommendations on how to improve cervical cancer communication towards female university students. The researcher obtained data using semi-structured interviews and focus group discussions targeting 90 respondents. The semi-structured in-depth interviews were carried out through one-on-one discussions basis using a set of prepared questions among 53 respondents. All interviews were audio-tape recorded. Each interview was directly typed into Microsoft Word. 4 focus group discussions were conducted with a total of 37 respondents; 2 female only groups with 10 respondents in one and 9 respondents in another, 1 mixed with 12 participants 5 of whom were male, and 1 male only group with 6 participants. The key findings show that the participants preferred to receive and access cervical cancer information from doctors although they were mainly receiving information from the radio. In regards to the type of public the respondents represent, majority of the respondents were non-publics in the sense that they did not have knowledge about cervical cancer, had low levels of involvement and had high constraint recognition their cervical cancer knowledge levels. The researcher identified the most salient audience frames among female university students towards cervical cancer and these included; death, loss, and fear. These frames did not necessarily make cervical cancer an issue of concern among the female university students but rather an issue they distanced themselves from as they did not perceive it as a risk. The study also identified the constraints respondents face in responding to cervical cancer campaign calls-to-action which included; stigma, lack of knowledge and access to services as well as lack of recommendation from doctors. In regards to sex differences, females had more knowledge about cervical cancer than the males. In conclusion the study highlights the importance of interpersonal communication in risk or health communication with a focus on health providers proactively sharing cervical cancer prevention information with their patients. Health provider’s involvement in cervical cancer is very important in influencing behavior and compliance of cervical cancer calls-to-action. The study also provides recommendations for designing effective cervical cancer campaigns that will positively impact on the audience such as packaging cervical cancer messages that also target the males as a way of increasing their involvement and more campaigns to increase awareness of cervical cancer as well as designing positive framed messages to counter the negative audience frames towards cervical cancer.

Keywords: cervical cancer communication, health communication, university students, risk communication

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Authors: Asma Zaib, Saeed Khan, Ayaz Ahmed Noonari, Sehrish Bint-e-Mohsin

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Breast cancer is the most common cancer among females worldwide and is estimated that more than 450,000 deaths are reported each year. It accounts for about 14% of all female cancer deaths. Angiogenesis plays an essential role in Breast cancer development, invasion, and metastasis. Breast cancer predominantly begins in luminal epithelial cells lining the normal breast ducts. Breast carcinoma likely requires coordinated efforts of both increased proliferation and increased motility to progress to metastatic stages.Resveratrol: a natural stilbenoid, has anti-inflammatory and anticancer effects that inhibits proliferation of variety of human cancer cell lines, including breast, prostate, stomach, colon, pancreatic, and thyroid cancers.The objective of this study is:To investigate anti-neoangiogenesis effects of Resveratrol in breast cancer and to analyze inhibitory effects of resveratrol on aromatase, Erα, HER2/neu, and VEGFR.Docking is the computational determination of binding affinity between molecule (protein structure and ligand).We performed molecular docking using Swiss-Dock and to determine docking effects of (1) Resveratrol with Aromatase, (2) Resveratrol with ERα (3) Resveratrol with HER2/neu and (4) Resveratrol with VEGFR2.Docking results of resveratrol determined inhibitory effects on aromatase with binding energy of -7.28 kcal/mol which shows anticancerous effects on estrogen dependent breast tumors. Resveratrol also show inhibitory effects on ERα and HER2/new with binging energy -8.02, and -6.74 respectively; which revealed anti-cytoproliferative effects upon breast cancer. On the other hand resveratrol v/s VEGFR showed potential inhibitory effects on neo-angiogenesis with binding energy -7.68 kcal/mol, angiogenesis is the important phenomenon that promote tumor development and metastasis. Resveratrol is an anti-breast cancer agent conformed by in silico studies, it has been identified that resveratrol can inhibit breast cancer cells proliferation by acting as competitive inhibitor of aromatase, ERα and HER2 neo, while neo-angiogemesis is restricted by binding to VEGFR which authenticates the anti-carcinogenic effects of resveratrol against breast cancer.

Keywords: angiogenesis, anti-cytoproliferative, molecular docking, resveratrol

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Authors: Ika Wulansari, Yati Afiyanti, Indang Trihandini

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Sleeping disorder experienced by patients with breast cancer can affect the physical, mental, health, and well-being. This study examines the effect of progressive muscle relaxation training and sleep hygiene education to change sleep quality scores of the patient with breast cancer. The study design using quasi-experiment with pre-post test within the control group, involving 62 breast cancer patients using consecutive sampling method in Jakarta. Statistical test results with independent t-test showed a significant difference in score of sleep quality between in intervention group and the control group (6,66±3,815; 9,30±3,334, p-value = 0,005). Progressive muscle relaxation exercise and sleep hygiene education proven to be affective to change the patients sleeping quality, so that it can be an alternative therapeutic option to overcome sleeping disorders.

Keywords: sleeping disorders, breast cancer, progressive muscle relaxation, sleep hygiene education

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Authors: Jing Chen, Jun-E Liu, Peng Yue

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Objective: The objective of this study was to develop a psychological adjustment and adaptation status scale for breast cancer survivors, and to examine the reliability and validity of the scale. Method: 37 breast cancer survivors were recruited in qualitative research; a five-subject theoretical framework and an item pool of 150 items of the scale were derived from the interview data. In order to evaluate and select items and reach a preliminary validity and reliability for the original scale, the suggestions of study group members, experts and breast cancer survivors were taken, and statistical methods were used step by step in a sample of 457 breast cancer survivors. Results: An original 24-item scale was developed. The five dimensions “domestic affections”, “interpersonal relationship”, “attitude of life”, “health awareness”, “self-control/self-efficacy” explained 58.053% of the total variance. The content validity was assessed by experts, the CVI was 0.92. The construct validity was examined in a sample of 264 breast cancer survivors. The fitting indexes of confirmatory factor analysis (CFA) showed good fitting of the five dimensions model. The criterion-related validity of the total scale with PTGI was satisfactory (r=0.564, p<0.001). The internal consistency reliability and test-retest reliability were tested. Cronbach’s alpha value (0.911) showed a good internal consistency reliability, and the intraclass correlation coefficient (ICC=0.925, p<0.001) showed a satisfactory test-retest reliability. Conclusions: The scale was brief and easy to understand, was suitable for breast cancer patients whose physical strength and energy were limited.

Keywords: breast cancer survivors, rehabilitation, psychological adaption and adjustment, development of scale

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Authors: Sungsoo Na, Chanho Park

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Lung cancer is one of the most common severe diseases driving to the death of a human. Lung cancer can be divided into two cases of small-cell lung cancer (SCLC) and non-SCLC (NSCLC), and about 80% of lung cancers belong to the case of NSCLC. From several studies, the correlation between epidermal growth factor receptor (EGFR) and NSCLCs has been investigated. Therefore, EGFR inhibitor drugs such as gefitinib and erlotinib have been used as lung cancer treatments. However, the treatments result showed low response (10~20%) in clinical trials due to EGFR mutations that cause the drug resistance. Patients with resistance to EGFR inhibitor drugs usually are positive to KRAS mutation. Therefore, assessment of EGFR and KRAS mutation is essential for target therapies of NSCLC patient. In order to overcome the limitation of conventional therapies, overall EGFR and KRAS mutations have to be monitored. In this work, the only detection of EGFR will be presented. A variety of techniques has been presented for the detection of EGFR mutations. The standard detection method of EGFR mutation in ctDNA relies on real-time polymerase chain reaction (PCR). Real-time PCR method provides high sensitive detection performance. However, as the amplification step increases cost effect and complexity increase as well. Other types of technology such as BEAMing, next generation sequencing (NGS), an electrochemical sensor and silicon nanowire field-effect transistor have been presented. However, those technologies have limitations of low sensitivity, high cost and complexity of data analyzation. In this report, we propose a label-free and high-sensitive detection method of lung cancer using quartz crystal microbalance based platform. The proposed platform is able to sense lung cancer mutant DNA with a limit of detection of 1nM.

Keywords: cancer DNA, resonance frequency, quartz crystal microbalance, lung cancer

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Authors: C. Romero, R. Ortega, P. Sánchez-Camacho, P. Aguilar, V. Segur, J. Ruiz, G. Gutiérrez

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Introduction: Breast cancer is a leading cause of death in CLM. (2.8% of all deaths in women and 13,8% of deaths from tumors in womens). It is the most tumor incidence in CLM region with 26.1% from all tumours, except nonmelanoma skin (Cancer Incidence in Five Continents, Volume X, IARC). Cancer registries are a good information source to estimate cancer incidence, however the data are usually available with a lag which makes difficult their use for health managers. By contrast, mortality and survival statistics have less delay. In order to serve for resource planning and responding to this problem, a method is presented to estimate the incidence of mortality and survival data. Objectives: To estimate the incidence of breast cancer by age group in CLM in the period 1991-2013. Comparing the data obtained from the model with current incidence data. Sources: Annual number of women by single ages (National Statistics Institute). Annual number of deaths by all causes and breast cancer. (Mortality Registry CLM). The Breast cancer relative survival probability. (EUROCARE, Spanish registries data). Methods: A Weibull Parametric survival model from EUROCARE data is obtained. From the model of survival, the population and population data, Mortality and Incidence Analysis MODel (MIAMOD) regression model is obtained to estimate the incidence of cancer by age (1991-2013). Results: The resulting model is: Ix,t = Logit [const + age1*x + age2*x2 + coh1*(t – x) + coh2*(t-x)2] Where: Ix,t is the incidence at age x in the period (year) t; the value of the parameter estimates is: const (constant term in the model) = -7.03; age1 = 3.31; age2 = -1.10; coh1 = 0.61 and coh2 = -0.12. It is estimated that in 1991 were diagnosed in CLM 662 cases of breast cancer (81.51 per 100,000 women). An estimated 1,152 cases (112.41 per 100,000 women) were diagnosed in 2013, representing an increase of 40.7% in gross incidence rate (1.9% per year). The annual average increases in incidence by age were: 2.07% in women aged 25-44 years, 1.01% (45-54 years), 1.11% (55-64 years) and 1.24% (65-74 years). Cancer registries in Spain that send data to IARC declared 2003-2007 the average annual incidence rate of 98.6 cases per 100,000 women. Our model can obtain an incidence of 100.7 cases per 100,000 women. Conclusions: A sharp and steady increase in the incidence of breast cancer in the period 1991-2013 is observed. The increase was seen in all age groups considered, although it seems more pronounced in young women (25-44 years). With this method you can get a good estimation of the incidence.

Keywords: breast cancer, incidence, cancer registries, castilla-la mancha

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Authors: Alaa T. Ali, Nevine H. Kheir El Din, Ehab S. Abdelhamid, Ahmed E. Amr

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Objective: Severe alveolar bone resorption is usually associated with a deficient amount of soft tissues. soft tissue expansion is introduced to provide an adequate amount of soft tissue over the grafted area. This study aimed to assess the efficacy of sub-periosteal self-inflating osmotic tissue expanders used as preparatory surgery before horizontal alveolar ridge augmentation using autogenous onlay block bone graft. Methods: A prospective randomized controlled clinical trial was performed. Sixteen partially edentulous patients demanding horizontal bone augmentation in the anterior maxilla were randomly assigned to horizontal ridge augmentation with autogenous bone block grafts harvested from the mandibular symphysis. For the test group, soft tissue expanders were placed sub-periosteally before horizontal ridge augmentation. Impressions were taken before and after STE, and the cast models were optically scanned and superimposed to be used for volumetric analysis. Horizontal ridge augmentation was carried out after STE completion. For the control group, a periosteal releasing incision was performed during bone augmentation procedures. Implants were placed in both groups at re-entry surgery after six months period. A core biopsy was taken. Histomorphometric assessment for newly formed bone surface area, mature collagen area fraction, the osteoblasts count, and blood vessel count were performed. The change in alveolar ridge width was evaluated through bone caliper and CBCT. Results: Soft tissue expander successfully provides a Surplus amount of soft tissues in 5 out of 8 patients in the test group. Complications during the expansion period were perforation through oral mucosa occurred in two patients. Infection occurred in one patient. The mean soft tissue volume gain was 393.9 ± 322mm. After 6 months. The mean horizontal bone gains for the test and control groups were 3.14 mm and 3.69 mm, respectively. Conclusion: STE with a sub-periosteal approach is an applicable method to achieve an additional soft tissue and to reduce bone block graft exposure and wound dehiscence.

Keywords: soft tissue expander, ridge augmentation, block graft, symphysis bone block

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Authors: Hala M. El-hanbuli, Mohammed F. Darweesh

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The incidence rates of any tumor vary hugely with geographical location. Basal Cell Carcinoma (BCC) is one of the most common skin cancer that has many histopathologic subtypes. Objective: The aim was to study the histopathological features of BCC cases that were received in the Pathology Department, Kasr El-Aini hospital, Cairo University, Egypt during the period from Jan 2004 to Dec 2013 and to evaluate the clinical characters through the patient data available in the request sheets. Methods: Slides and data of BCC cases were collected from the archives of the pathology department, Kasr El-Aini hospital. Revision of all available slides and histological classification of BCC according to WHO (2006) was done. Results: A total number of 310 cases of BCC representing about 65% from the total number of malignant skin tumors examined during the 10-years duration in the department. The age ranged from 8 to 84 years, the mean age was (55.7 ± 15.5). Most of the patients (85%) were above the age of 40 years. There was a slight male predominance (55%). Ulcerated BCC was the most common gross picture (60%), followed by nodular lesion (30%) and finally the ulcerated nodule (10%). Most of the lesions situated in the high-risk sites (77%) where the nose was the most common site (35%) followed by the periocular area (22%), then periauricular (15%) and finally perioral (5%). No lesion was reported outside the head. The tumor size was less than 2 centimeters in 65% of cases, and from 2-5 centimeters in the lesions' greatest dimension in the rest of cases. Histopathological reclassification revealed that the nodular BCC was the most common (68%) followed by the pigmented nodular (18.75%). The histologic high-risk groups represented (7.5%) about half of them (3.75%) being basosquamous carcinoma. The total incidence for multiple BCC and 2nd primary was 12%. Recurrent BCC represented 8%. All of the recurrent lesions of BCC belonged to the histologic high-risk group. Conclusion: Basal Cell Carcinoma is the most common skin cancer in the 10-year survey. Histopathological diagnosis and classification of BCC cases are essential for the determination of the tumor type and its biological behavior.

Keywords: basal cell carcinoma, high risk, histopathological features, statistical analysis

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: Julianne Macmullen

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Due to advances in technology and early detection and treatment of cancer, many cancer patients are surviving longer than five years post-diagnosis. Most cancer patients suffer from depression, anxiety, and post-traumatic stress disorder (PTSD) at some point during diagnosis, treatment, and survivorship. A subgroup of patients will continue to suffer from depression and PTSD and require early intervention. Support groups provide patients with the emotional and informational support they require while also giving survivors a sense of community, friendship, and purpose. This type of support is recognized by researchers to improve the quality of life while also decreasing depression and PTSD symptoms. The gaps in the literature include cultural diversity, minorities, and support groups involving cancer types other than breast cancer. Another gap in the literature includes the perceptions of cancer patients as well as longitudinal studies to determine the relationships between support groups and decreased depression and PTSD rates over time. Future research is required to fill the gaps in the literature mentioned previously. Future research is also needed to analyze the difference in age groups and different types of support groups such as professionally-led, peer-led, and online. Implications for practice involve providers assessing for the symptoms of depression and PTSD in order to offer prompt treatment and support services to those patients. In conclusion, social support by way of support groups improves the quality of life, gives survivors a sense of purpose to help others while also gaining the support they need, and reduces the rate of depressive episodes related to PTSD.

Keywords: cancer survivor, survivorship, post-traumatic stress disorder (PTSD), depression, support groups

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Authors: Faezah Shekh Abdullah, Mohd. Azizuddin Mohd. Yussof, Komathy Thiagarajan, Hasnoorina Husin, Noor Azreena Abd Aziz

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Polycystic ovary syndrome has been associated with multiple disorders such as endocrine disorder, metabolic syndrome, infertility, and endometrial cancer. Women with polycystic ovary syndrome (PCOS) are anticipated to develop three times more chances for endometrial cancer than women without PCOS. This study, therefore, was conducted to determine the association between polycystic ovary syndrome and endometrial cancer and to determine the cervical cytology features of PCOS. Patients attending the Subfertility Clinic of the National Population and Family Development Board were recruited and examined physically by medical practitioners. They were categorized into two groups; i) the PCOS group if they met Rotterdam Criteria 2004 and ii) the control group if they did not meet Rotterdam Criteria 2004. Cervical sampling was done on all patients via the Liquid-Based Cytology (LBC) method in the pre-and post-subfertility treatment. A total of 167 patients participated in the study, of which 79 belonged to the PCOS group and 88 to the control group. The findings showed no cervical and endometrial cancer cases in both groups. The Liquid-Based Cytology results in the PCOS group displayed more cases with cellular changes, i.e., benign inflammation, atrophic smear and Candida sp. infection. To conclude, no association was found between polycystic ovary syndrome and endometrial cancer. A more holistic study with a higher number of participants can further determine the association between endometrial cancer and PCOS. Furthermore, a longer duration between LBC pre- and post-subfertility treatment should be implied to observe changes in the cervical cells.

Keywords: endometrial cancer, liquid-based cytology, PCOS, polycystic ovary syndrome

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Authors: Yiannis G. Smirlis

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The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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Authors: Michael Aupetit, Mahmoud Al-ismail, Khaled Mohamed

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Cancer is a major public health problem all over the world. Breast cancer has the highest incidence rate over all cancers for women in Qatar making its study a top priority of the country. Human cancer is a dynamic disease that develops over an extended period through the accumulation of a series of genetic alterations. A Darwinian process drives the tumor cells toward higher malignancy growing the branches of a progression tree in the space of genes expression. Although it is not possible to track these genetic alterations dynamically for one patient, it is possible to reconstruct the progression tree from the aggregation of thousands of tumor cells’ genetic profiles from thousands of different patients at different stages of the disease. Analyzing the progression tree is a way to detect pivotal molecular events that drive the malignant evolution and to provide a guide for the development of cancer diagnostics, prognostics and targeted therapeutics. In this work we present the development of a Visual Analytic web platform CanVis enabling users to upload gene-expression data and analyze their progression tree. The server computes the progression tree based on state-of-the-art techniques and allows an interactive visual exploration of this tree and the gene-expression data along its branching structure helping to discover potential driver genes.

Keywords: breast cancer, progression tree, visual analytics, web platform

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Authors: Mais Nijim, Rama Devi Chennuboyina, Waseem Al Aqqad

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Advances in spatial and spectral resolution of satellite images have led to tremendous growth in large image databases. The data we acquire through satellites, radars and sensors consists of important geographical information that can be used for remote sensing applications such as region planning, disaster management. Spatial data classification and object recognition are important tasks for many applications. However, classifying objects and identifying them manually from images is a difficult task. Object recognition is often considered as a classification problem, this task can be performed using machine-learning techniques. Despite of many machine-learning algorithms, the classification is done using supervised classifiers such as Support Vector Machines (SVM) as the area of interest is known. We proposed a classification method, which considers neighboring pixels in a region for feature extraction and it evaluates classifications precisely according to neighboring classes for semantic interpretation of region of interest (ROI). A dataset has been created for training and testing purpose; we generated the attributes by considering pixel intensity values and mean values of reflectance. We demonstrated the benefits of using knowledge discovery and data-mining techniques, which can be on image data for accurate information extraction and classification from high spatial resolution remote sensing imagery.

Keywords: remote sensing, object recognition, classification, data mining, waterbody identification, feature extraction

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Authors: Rina Lee, Chung-Hun Oh, Eunjin Lee, Jeongyun Kim

Abstract:

The Photodynamic therapy (PDT) is a treatment that uses a photosensitizer as a drug to damage and kill cancer cells. After injecting the photosensitizer into the bloodstream, the drug is absorbed by cancer cells selectively. Then the area to be treated is exposed to specific wavelengths of light and the photosensitizer produces a form of oxygen that kills nearby cancer cells. PDT is has an advantage to destroy the tumor with minimized side-effects on normal cells. But, PDT is not a completed method for cancer therapy. Because the mechanism of PDT is quite clear yet and the parameters such as intensity of light and dose of photosensitizer are not optimized for different types of cancers. To optimize these parameters, we suggest a novel microfluidic system to automatically control intensity of light exposure with a personal computer (PC). A polydimethylsiloxane (PDMS) microfluidic chip is composed with (1) a cell culture channels layer where cancer cells were trapped to be tested with various dosed photofrin (1μg/ml used for the test) as the photosensitizer and (2) a color dye layer as a neutral density (ND) filter to reduce intensity of light which exposes the cell culture channels filled with cancer cells. Eight different intensity of light (10%, 20%, …, 100%) are generated through various concentrations of blue dye filling the ND filter. As a light source, a light emitting diode (LED) with 635nm wavelength was placed above the developed PDMS microfluidic chip. The total time for light exposure was 30 minutes and HeLa and PC3 cell lines of cancer cells were tested. The cell viability of cells was evaluated with a Live/Dead assay kit (L-3224, Invitrogen, USA). The stronger intensity of light exposed, the lower viability of the cell was observed, and vice versa. Therefore, this system was demonstrated through investigating the PDT against cancer cell to optimize the parameters as critical light intensity and dose of photosensitizer. Our results suggest that the system can be used for optimizing the combinational parameters of light intensity and photosensitizer dose against diverse cancer cell types.

Keywords: photodynamic therapy, photofrin, high throughput screening, hela

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Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri, S. Kakaei

Abstract:

Despite the appropriate characteristics of ¹⁷⁷Lu and DOTATOC, to our best knowledge, the therapeutic benefit of ¹⁷⁷Lu-DOTATOC complex in breast cancer has not been reported until now. In this study, biodistribution of ¹⁷⁷Lu-DOTA-TOC in mouse tumor model for evaluation of possible utilization of this complex in breast cancer treatment was investigated.¹⁷⁷Lu was prepared with the specific activity of 2.6-3 GBq.mg^-1 and radionuclidic purity higher than 99%. The radiolabeled complex was prepared in the optimized conditions with the radiochemical purity higher than 99%. The final solution was injected to the BALB/c mice with adenocarcinoma breast cancer. The biodistribution results showed major accumulation in the kidneys as the major excretion route and the somatostatin receptor-positive tissues such as pancreas compared with the other tissues. Also, significant uptake was observed in tumor even in longer time after injection. According to the results obtained in this research study, somatostatin receptors expressed in breast cancers can be targeted with DOTATOC analogues especially with ¹⁷⁷Lu-DOTATOC as an ideal therapeutic agent.

Keywords: ¹⁷⁷Lu, adenocarcinoma breast cancer, DOTATOC, BALB/c mice

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Authors: Faisal Muhibuddin, Ani Dijah Rahajoe

Abstract:

This in-depth exploration, through a systematic literature review, scrutinizes the nuanced role of data mining in the classification of criminal activities. The research focuses on investigating various methodological aspects and recent developments in leveraging data mining techniques to enhance the effectiveness and precision of crime categorization. Commencing with an exposition of the foundational concepts of crime classification and its evolutionary dynamics, this study details the paradigm shift from conventional methods towards approaches supported by data mining, addressing the challenges and complexities inherent in the modern crime landscape. Specifically, the research delves into various data mining techniques, including K-means clustering, Naïve Bayes, K-nearest neighbour, and clustering methods. A comprehensive review of the strengths and limitations of each technique provides insights into their respective contributions to improving crime classification models. The integration of diverse data sources takes centre stage in this research. A detailed analysis explores how the amalgamation of structured data (such as criminal records) and unstructured data (such as social media) can offer a holistic understanding of crime, enriching classification models with more profound insights. Furthermore, the study explores the temporal implications in crime classification, emphasizing the significance of considering temporal factors to comprehend long-term trends and seasonality. The availability of real-time data is also elucidated as a crucial element in enhancing responsiveness and accuracy in crime classification.

Keywords: data mining, classification algorithm, naïve bayes, k-means clustering, k-nearest neigbhor, crime, data analysis, sistematic literature review

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Authors: Kemal Polat

Abstract:

In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.

Keywords: machine learning, data weighting, classification, data mining

Procedia PDF Downloads 316

Authors: Peter J. Riley

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Medical Imaging students must understand the roles of Photo-electric Absorption (PE) and Compton Scatter (CS) interactions in patients to enable optimal X-ray imaging in clinical practice. A simulator has been developed that shows relative interaction probabilities, color bars for patient dose from PE, % penetration to the detector, and obscuring CS as Peak Kilovoltage (kVp) changes. Additionally, an anthropomorphic chest X-ray image shows the relative tissue contrasts and overlying CS-fog at that kVp, which determine the detectability of a lesion in the image. A series of interactive exercises with MCQs evaluate the student's understanding; the simulation has improved student perception of the need to acquire "sufficient" rather than maximal contrast to enable patient dose reduction at higher kVp.

Keywords: patient dose optimization, radiological physics, simulation, tissue contrast

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Authors: Su Chul Han, Seungwoo Park

Abstract:

As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

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Authors: Lukas Ded

Abstract:

Studying the tissue structure and histogenesis in the natural, 3D context is challenging but highly beneficial process. Contrary to classical approach of the physical tissue sectioning and subsequent imaging, it enables to study the relationships of individual cellular and histological structures in their native context. Recent developments in the tissue clearing approaches and microscopic volume imaging/data processing enable the application of these methods also in the areas of developmental and reproductive biology. Here, using the CLARITY tissue procedure and 3D confocal volume imaging we optimized the protocol for clearing, staining and imaging of the mice seminiferous tubules isolated from the testes without cardiac perfusion procedure. Our approach enables the high magnification and fine resolution axial imaging of the whole diameter of the seminiferous tubules with possible unlimited lateral length imaging. Hence, the large continuous pieces of the seminiferous tubule can be scanned and digitally reconstructed for the study of the single tubule seminiferous stages using nuclear dyes. Furthermore, the application of the antibodies and various molecular dyes can be used for molecular labeling of individual cellular and subcellular structures and resulting 3D images can highly increase our understanding of the spatiotemporal aspects of the seminiferous tubules development and sperm ultrastructure formation. Finally, our newly developed algorithms for 3D data processing enable the massive parallel processing of the large amount of individual cell and tissue fluorescent signatures and building the robust spermatogenic models under physiological and pathological conditions.

Keywords: CLARITY, spermatogenesis, testis, tissue clearing, volume imaging

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Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

Abstract:

This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

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Authors: Ashwani Kumar Aggarwal

Abstract:

NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: Anna Rudzińska, Katarzyna Szklener, Pola Juchaniuk, Anna Rodzajweska, Katarzyna Machulska-Ciuraj, Monika Rychlik- Grabowska, Michał łOziński, Agnieszka Kolak-Bruks, SłAwomir Mańdziuk

Abstract:

Introduction: Immune checkpoint inhibition (ICI) belongs to the modern forms of anti-cancer treatment. Due to the constant development and continuous research in the field of ICI, many aspects of the treatment are yet to be discovered. One of the less researched aspects of ICI treatment is the influence of the adverse effects on the treatment success rate. It is suspected that adverse events in the course of the ICI treatment indicate a better response rate and correlate with longer progression-free- survival. Methodology: The research was conducted with the usage of the documentation of the Department of Clinical Oncology and Chemotherapy. Data of the patients with a lung cancer diagnosis who were treated between 2019-2022 and received ICI treatment were analyzed. Results: Out of over 133 patients whose data was analyzed, the vast majority were diagnosed with non-small cell lung cancer. The majority of the patients did not experience adverse effects. Most adverse effects reported were classified as grade 1 or grade 2 according to CTCAE classification. Most adverse effects involved skin, thyroid and liver toxicity. Statistical significance was found for the adverse effect incidence and overall survival (OS) and progression-free survival (PFS) (p=0,0263) and for the time of toxicity onset and OS and PFS (p<0,001). The number of toxicity sites was statistically significant for prolonged PFS (p=0.0315). The highest OS was noted in the group presenting grade 1 and grade 2 adverse effects. Conclusions: Obtained results confirm the existence of the prolonged OS and PFS in the adverse-effects-charged patients, mostly in the group presenting mild to intermediate (Grade 1 and Grade 2) adverse effects and late toxicity onset. Simultaneously our results suggest a correlation between treatment response rate and the toxicity grade of the adverse effects and the time of the toxicity onset. Similar results were obtained in several similar research conducted - with the proven tendency of better survival in mild and moderate toxicity; meanwhile, other studies in the area suggested an advantage in patients with any toxicity regardless of the grade. The contradictory results strongly suggest the need for further research on this topic, with a focus on additional factors influencing the course of the treatment.

Keywords: adverse effects, immunotherapy, lung cancer, PD-1/PD-L1 inhibitors

Procedia PDF Downloads 79