<?xml version="1.0" encoding="utf-8"?>
<XML>
<JOURNAL>
<YEAR>2024</YEAR>
<VOL>16</VOL>
<NO>4</NO>
<MOSALSAL>0</MOSALSAL>
<PAGE_NO>113</PAGE_NO>


<ARTICLES>

	<ARTICLE> 
		<TitleF>F8 Gene Splice Donor Mutation (c.1271+1G>A) in Individual with Mild Hemophilia A in Indonesia: A Case Study</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Introduction: Hemophilia A is a bleeding disorder caused by a deficiency of coagulation factor VIII. Hemophilia A is an X-linked recessive disorder. Depending on the level of blood coagulation factor VIII, hemophilia severity is classified as mild (5-40%), moderate (1-5%), or severe (&#60;1%). The absence of hemophilia A mutation studies in Indonesia makes this topic important to study.
Methods: This study detected and classified F8 gene mutations. A member of the Indonesian Hemophilia Society Association for the Special Region of Yogyakarta provided saliva for DNA testing. Long-read sequencing data were performed using the next-generation sequencing (NGS) technique via the Oxford Nanopore Technologies plc (ONT) PromethION 24 platform. The mutation was confirmed using Sanger sequencing, after amplifying intron 8 of the F8 gene with the PCR technique. The F8 gene intron 8 nucleotide sequence was aligned using the alignment tool on the Benchling website.
Results: The results of this study showed that there was a splice donor site mutation in intron 8 of the F8 gene (c.1271+1G&#62;A) in one patient. This mutation can cause the occurrence of cryptic splice donor sites. Cryptic splice donor site prediction was carried out using the splice donor prediction tool available on the NNSPLICE website. The appearance of cryptic splice donor sites can lead to the formation of out-of-frame proteins.
Conclusions: The F8 gene mutation causing hemophilia A was detected using long-read sequencing and the next-generation sequencing (NGS) technique. The type of mutation identified is a splice donor site mutation, specifically the variant c.1271+1G&#62;A, in sample code HM13.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>1</FPAGE>
			<TPAGE>8</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/26
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/5
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/24
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/10/4
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Ni Gusti Ayu Galuh Candra</Name>
				<MidName></MidName>
				<Family>Kirana</Family>
				<NameE>Ni Gusti Ayu Galuh Candra</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Kirana</FamilyE>
				<Organizations>
				<Organization>Faculty of Biology, Universitas Gadjah Mada, Yogyakarta, Indonesia</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>nigustiayugaluhcandrakirana@mail.ugm.ac.id</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Suprianto</Name>
				<MidName></MidName>
				<Family>Suprianto</Family>
				<NameE>Suprianto</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Suprianto</FamilyE>
				<Organizations>
				<Organization>Faculty of Biology, Universitas Gadjah Mada, Yogyakarta, Indonesia</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>Suprianto1997@mail.ugm.ac.id</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Indra</Name>
				<MidName></MidName>
				<Family>Lesmana</Family>
				<NameE>Indra</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Lesmana</FamilyE>
				<Organizations>
				<Organization>Department of Tropical Biology, Faculty of Biology, Universitas Gadjah Mada, Yogyakarta, Indonesia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>indra.lesmana@ugm.ac.id</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Usi</Name>
				<MidName></MidName>
				<Family>Sukorini</Family>
				<NameE>Usi</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Sukorini</FamilyE>
				<Organizations>
				<Organization>Department of Clinical Pathology and Laboratory Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>ussi@ugm.ac.id</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Niken Satuti Nur</Name>
				<MidName></MidName>
				<Family>Handayani</Family>
				<NameE>Niken Satuti Nur</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Handayani</FamilyE>
				<Organizations>
				<Organization>Department of Tropical Biology, Faculty of Biology, Universitas Gadjah Mada, Yogyakarta, Indonesia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>niken_satuti@ugm.ac.id</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Hemophilia A</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>F8 gene</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Intron 8</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Donor splice mutation</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>c.1271+1G</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>## ##</REF>
			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Hematology and Hematopathology Insights Powered by Machine Learning: Shaping the Future of Blood Disorder Management</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Introduction: The field of hematology faces significant challenges in data analysis, especially in the diagnosis and prediction of diseases. Traditional methods of analysis are often time-consuming, complex, or inadequate to handle the complex nature of blood-related data. This requires the development of advanced techniques for accurate prediction and classification. Artificial Intelligence (AI)-based methods have emerged as a powerful solution that enables more efficient and accurate analysis of hematological data. This study aims to systematically review published research on the use of different artificial intelligence algorithms in the analysis of this field of data.
Methods: Using a combination of keywords related to blood data analysis and artificial intelligence, we searched medical and scientific databases to identify relevant articles. A data extraction form was developed to collect relevant information from selected studies based on predefined inclusion and exclusion criteria. The content analysis method was used to analyze the extracted data and the findings were organized in tables and figures to meet the research objectives.
Results: After reviewing 7300 studies, 25 full-text studies were selected for final analysis based on their relevance to the research objectives. The findings showed that AI methods, especially deep learning (DL), are widely used to predict and diagnose hematological and Hematopathological diseases. Among the most common algorithms used in ML were XGBoost, which was one of the most important deep learning algorithms, as well as Convolutional Neural Networks (CNN). AI-based models had Accuracy, Specificity, and Sensitivity of 96.6%, 95%, and 96%, respectively.
Conclusion: This review shows that AI-based models have the potential to be significantly applied to the analysis of blood data. As artificial intelligence continues to evolve, medical professionals and researchers will have access to powerful ML-based tools to quickly and accurately diagnose.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>9</FPAGE>
			<TPAGE>19</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/19
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/29
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/2
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/9/12
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Rahime</Name>
				<MidName></MidName>
				<Family>Tajvidi Asr</Family>
				<NameE>Rahime</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Tajvidi Asr</FamilyE>
				<Organizations>
				<Organization>Health and biomedical informatics Research Centers, Urmia University of Medical Sciences,Urmia,Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>rahimetajvidy@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Milad</Name>
				<MidName></MidName>
				<Family>Rahimi</Family>
				<NameE>Milad</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Rahimi</FamilyE>
				<Organizations>
				<Organization>Health and biomedical informatics Research Centers, Urmia University of Medical Sciences,Urmia,Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>rahimimiladofficial@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Mohammad</Name>
				<MidName></MidName>
				<Family>Hossein Pourasad</Family>
				<NameE>Mohammad</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Hossein Pourasad</FamilyE>
				<Organizations>
				<Organization>School of paramedical, Kermanshah University of Medical Sciences, Kermanshah, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>pourasad.mh@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Salar</Name>
				<MidName></MidName>
				<Family>Zayer</Family>
				<NameE>Salar</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Zayer</FamilyE>
				<Organizations>
				<Organization>School of Medicine, Urmia University of Medical Sciences, Urmia, West Azerbaijan, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>dr.salarzayer@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Mohammadreza</Name>
				<MidName></MidName>
				<Family>Momenzadeh</Family>
				<NameE>Mohammadreza</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Momenzadeh</FamilyE>
				<Organizations>
				<Organization>Department of Artificial Intelligence in Medical Sciences, Smart University of Medical Sciences.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>momenzadeh.mr@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Mustafa</Name>
				<MidName></MidName>
				<Family>Ghaderzadeh</Family>
				<NameE>Mustafa</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Ghaderzadeh</FamilyE>
				<Organizations>
				<Organization>Boukan Faculty of Medical Sciences, Urmia University of Medical Sciences, Urmia, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>mustafa.ghaderzadeh@gmail.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Hematology</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Hematopathology</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Machine Learning</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Blood Disorder</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>M. Ghaderzadeh, A. Shalchian, G. Irajian, H. Sadeghsalehi, and B. Sabet, "Artificial intelligence in drug discovery and development against antimicrobial resistance: A narrative review," Iran. J. Med. Microbiol., vol. 18, no. 3, pp. 135-147, 2024.##M. Ghaderzadeh, M. Aria, A. Hosseini, F. Asadi, D. Bashash, and H. Abolghasemi, "A fast and efficient CNN model for B-ALL diagnosis and its subtypes classification using peripheral blood smear images," Int. J. Intell. Syst., vol. 37, no. 8, pp. 5113-5133, 2022.##A. Bazinet et al., "Automated quantification of measurable residual disease in chronic lymphocytic leukemia using an artificial intelligence‐assisted workflow," Cytom. Part B Clin. Cytom., vol. 106, no. 4, pp. 264-271, 2024.##T. Dehkharghanian, Y. Mu, H. R. Tizhoosh, and C. J. V Campbell, "Applied machine learning in hematopathology," Int. J. Lab. Hematol., vol. 45, no. S2, pp. 87-94, 2023.##Y. Hu, Y. Luo, G. Tang, Y. Huang, J. Kang, and D. Wang, "Artificial intelligence and its applications in digital hematopathology," Blood Sci., vol. 4, no. 3, pp. 136-142, 2022.##D. Moher et al., "Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement," Syst. Rev., vol. 4, pp. 1-9, 2015.##P. F. Whiting et al., "QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies," Ann. Intern. Med., vol. 155, no. 8, pp. 529-536, 2011.##S. El Hussein, P. Chen, L. J. Medeiros, J. D. Hazle, J. Wu, and J. D. Khoury, "Artificial intelligence-assisted mapping of proliferation centers allows the distinction of accelerated phase from large cell transformation in chronic lymphocytic leukemia," Mod. Pathol., vol. 35, no. 8, pp. 1121-1125, 2022.##N. Aydin Atasoy and A. Faris Abdulla Al Rahhawi, "Examining the classification performance of pre-trained capsule networks on imbalanced bone marrow cell dataset," Int. J. Imaging Syst. Technol., vol. 34, no. 3, p. e23067, May 2024.##S. Koga, "Exploring the pitfalls of large language models: Inconsistency and inaccuracy in answering pathology board examination-style questions," Pathol. Int., vol. 73, no. 12, pp. 618-620, Dec. 2023.##J. S. Mohlman, S. D. Leventhal, T. Hansen, J. Kohan, V. Pascucci, and M. E. Salama, "Improving Augmented Human Intelligence to Distinguish Burkitt Lymphoma from Diffuse Large B-Cell Lymphoma Cases," Am. J. Clin. Pathol., vol. 153, no. 6, pp. 743-759, 2020.##A. M. Tsakiroglou et al., "Lymphoma triage from H&#59;E using AI for improved clinical management," J. Clin. Pathol., vol. 78, no. 1, pp. 28-33, 2025.##K. Sasaki et al., "The LEukemia Artificial Intelligence Program (LEAP) in chronic myeloid leukemia in chronic phase: A model to improve patient outcomes," Am. J. Hematol., vol. 96, no. 2, pp. 241-250, 2021.##S. Fazeli, A. Samiei, T. D. Lee, and M. Sarrafzadeh, "Beyond Labels: Visual Representations for Bone Marrow Cell Morphology Recognition," in Proceedings - 2023 IEEE 11th International Conference on Healthcare Informatics, ICHI 2023, 2023, pp. 111-117.##M. Osman et al., "Classification of monocytes, promonocytes and monoblasts using deep neural network models: An area of unmet need in diagnostic hematopathology," J. Clin. Med., vol. 10, no. 11, 2021.##Z. Lu et al., "Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders," Diagnostics, vol. 14, no. 4, 2024.##E. Hasan, Q. Eichbaum, A. C. Seegmiller, C. Stratton, and J. S. Trueblood, "Improving Medical Image Decision-Making by Leveraging Metacognitive Processes and Representational Similarity," Top. Cogn. Sci., vol. 14, no. 2, pp. 400-413, Apr. 2022,##Y. Mu, H. R. Tizhoosh, T. Dehkharghanian, and C. J. V Campbell, "Whole slide image representation in bone marrow cytology," Comput. Biol. Med., vol. 166, p. 107530, 2023.##S. Saxena, P. Sanyal, M. Bajpai, R. Prakash, and S. Kumar, "Trials and tribulations: Developing an artificial intelligence for screening malaria parasite from peripheral blood smears," Med. J. Armed Forces India, 2023.##Z. Zhang et al., "The Diagnosis of Chronic Myeloid Leukemia with Deep Adversarial Learning," Am. J. Pathol., vol. 192, no. 7, pp. 1083-1091, 2022.##N. Abele et al., "Noninferiority of Artificial Intelligence-Assisted Analysis of Ki-67 and Estrogen/Progesterone Receptor in Breast Cancer Routine Diagnostics," Mod. Pathol., vol. 36, no. 3, p. 100033, 2023.##G. S. Raju et al., "Natural language processing as an alternative to manual reporting of colonoscopy quality metrics," Gastrointest. Endosc., vol. 82, no. 3, pp. 512-519, 2015.##Y. Mu, H. R. Tizhoosh, T. Dehkharghanian, S. Alfasly, and C. J. V Campbell, "Model-Agnostic Binary Patch Grouping for Bone Marrow Whole Slide Image Representation," Am. J. Pathol., vol. 194, no. 5, pp. 721-734, 2024.##C.-W. Wang, S.-C. Huang, Y.-C. Lee, Y.-J. Shen, S.-I. Meng, and J. L. Gaol, "Deep learning for bone marrow cell detection and classification on whole-slide images," Med. Image Anal., vol. 75, p. 102270, 2022.##T. J. Brinker et al., "Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours," Eur. J. Cancer, vol. 154, pp. 227-234, 2021.##K. Sirinukunwattana et al., "Artificial intelligence-based morphological fingerprinting of megakaryocytes: a new tool for assessing disease in MPN patients," Blood Adv., vol. 4, no. 14, pp. 3284-3294, 2020.##S. El Hussein et al., "Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia," J. Pathol., vol. 256, no. 1, pp. 4-14, Jan. 2022.##J. Su, S. Liu, and J. Song, "A segmentation method based on HMRF for the aided diagnosis of acute myeloid leukemia," Comput. Methods Programs Biomed., vol. 152, pp. 115-123, 2017.##Z. Y. Xu-Monette et al., "A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL," Blood Adv., vol. 4, no. 14, pp. 3391-3404, 2020.##A. Acevedo, A. Merino, L. Boldú, Á. Molina, S. Alférez, and J. Rodellar, "A new convolutional neural network predictive model for the automatic recognition of hypogranulated neutrophils in myelodysplastic syndromes," Comput. Biol. Med., vol. 134, p. 104479, 2021.##A. K. Yenamandra, C. Hughes, and A. S. Maris, "Artificial Intelligence in Plasma Cell Myeloma: Neural Networks and Support Vector Machines in the Classification of Plasma Cell Myeloma Data at Diagnosis," J. Pathol. Inform., vol. 12, no. 1, p. 35, 2021.## ##</REF>
			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Predictive Modeling and Spatial Analysis of Cervix Uteri and Breast Cancer in India using Machine Learning and Big Data Frameworks</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Background: Cancer remains a critical public health issue in India, with rising cases of breast cancer and cervical cancer. Accurate predictions and spatial analysis of cancer incidence are essential for shaping prevention strategies and targeting interventions in high-risk regions.
Methods: This study utilized a big data framework employing machine learning techniques from the SparkML library to predict cancer cases and analyze spatial distributions across Indian states from 2016 to 2021. Three machine learning models used Random Forest Regressor, Gradient Boosting Regressor, and Geographically Weighted Regression (GWR) were applied to the dataset. Spatial autocorrelation analysis used Moran&#8217;s I statistic to identify clustering patterns.
Results: The spatial analysis revealed significant clustering of cancer cases, particularly in 2020, with a z-score of 2.23, a p-value of 0.02, and a Moran&#8217;s index of 0.15. Among the machine learning models, GWR achieved a predictive accuracy of 98% for both breast cancer and cervical cancer, while the Random Forest Regressor and Gradient Boosting Regressor achieved 95% and 97% accuracy, respectively, over the six-year period. Gradient Boosting outperformed other models in identifying key predictors and ensuring high predictive accuracy.
Conclusions: The findings highlight the efficacy of Gradient Boosting and GWR in predicting cancer incidence and analyzing spatial patterns. These models provide critical insights into cancer clustering and risk factors, supporting the development of targeted prevention strategies and policy interventions for high-risk regions in India. The results emphasize the utility of machine learning techniques in public health research and cancer control.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>20</FPAGE>
			<TPAGE>29</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/11
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/21
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/25
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/10/5
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Durga pujitha</Name>
				<MidName></MidName>
				<Family>Krotha</Family>
				<NameE>Durga pujitha</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Krotha</FamilyE>
				<Organizations>
				<Organization>Department of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>durgapujitha135@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Fathimabi</Name>
				<MidName></MidName>
				<Family>Shaik</Family>
				<NameE>Fathimabi</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Shaik</FamilyE>
				<Organizations>
				<Organization>Department of Information Technology, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>fathimabi@vrsiddhartha.ac.in</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Cancer</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Big data</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Machine Learning</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Gradient boosting</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Geographically weighted Regression</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>## ##</REF>
			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Flow Cytometry-based Functional Assay is a Valuable Diagnostic Approach for Confirmation of Heparin-Induced Thrombocytopenia</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Background: Heparin-induced thrombocytopenia (HIT) is a serious immunological adverse drug reaction that rarely occurs in patients receiving heparin. The heparin-induced platelet activation (HIPA) test, a gold-standard assay for HIT, is time-consuming, challenging, and produces qualitative results. We aimed to compare the performance properties of a flow cytometry-based functional assay for HIT diagnosis with HIPA assay.
Materials and Methods: This research was carried out on HIT-suspected patients referred to the Iranian Blood Transfusion Organization between 2021 and 2023. After clinical evaluation and 4Ts scores calculation, anti-PF4 screening and HIPA test were conducted. Thirty HIPA-positive and 30 HIPA-negative samples were selected. Subsequently, a flow cytometry-based functional assay, Emo-Test HIT confirm, was performed, and the sensitivity and specificity for HIT diagnosis were measured.
Results: Among the 30 samples with negative HIPA results, one was positive with the Emo-test HIT Confirm&#174; assay, and the remaining were negative. Among 30 positive HIPA samples, the result of one sample was inconclusive, two samples were negative with flowcytometry Emo-test and the others were positive. The sensitivity and specificity of this flow cytometry-based functional assay were 90% (95% CI: 79.3-100) and 96.6% (95% CI:90.2-100). The negative predictive value and positive predictive value were 93.5% and 96.4% respectively.
Conclusion: Flow cytometry-based functional assay has a good sensitivity and specificity for HIT diagnosis confirmation, indicating that it may be a promising approach in the clinical setting.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>30</FPAGE>
			<TPAGE>38</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/10
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/20
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/3
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/9/13
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Mahshaad</Name>
				<MidName></MidName>
				<Family>Norouzi</Family>
				<NameE>Mahshaad</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Norouzi</FamilyE>
				<Organizations>
				<Organization>Blood Transfusion Research Center, High Institute for Education and Research in Transfusion Medicine, Tehran, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>Mahshaadnorozi@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Sahar</Name>
				<MidName></MidName>
				<Family>Balagholi</Family>
				<NameE>Sahar</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Balagholi</FamilyE>
				<Organizations>
				<Organization>Blood Transfusion Research Center, High Institute for Education and Research in Transfusion Medicine, Tehran, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>saharbalagholi@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Amir</Name>
				<MidName></MidName>
				<Family>Teimourpour</Family>
				<NameE>Amir</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Teimourpour</FamilyE>
				<Organizations>
				<Organization>Blood Transfusion Research Center, High Institute for Education and Research in Transfusion Medicine, Tehran, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>amir.teimourpour@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Minoo</Name>
				<MidName></MidName>
				<Family>Ahmadinejad</Family>
				<NameE>Minoo</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Ahmadinejad</FamilyE>
				<Organizations>
				<Organization>Blood Transfusion Research Center, High Institute for Education and Research in Transfusion Medicine, Tehran, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>minooam@gmail.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Heparin-induced thrombocytopenia (HIT)</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Diagnosis</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Flow cytometry</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Functional assay</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>McFarland J, Lochowicz A, Aster R, Chappell B, Curtis B. Improving the specificity of the PF4 ELISA in diagnosing heparin‐induced thrombocytopenia. Am J Hematol. 2012;87(8):776-81.##May J, Westbrook B, Cuker A. Heparin-induced thrombocytopenia: An illustrated review. Res Pract Thromb Haemost. 2023;7(5).##Martel N, Lee J, Wells PS. Risk for heparin-induced thrombocytopenia with unfractionated and low-molecular-weight heparin thromboprophylaxis: a meta-analysis. Blood. 2005;106(8):2710-5.##Arepally GM, Cines DB. Pathogenesis of heparin-induced thrombocytopenia. Transl Res. 2020;225:131-40.##Warkentin TE, Greinacher A, Gruel Y, Aster RH, Chong BH. Laboratory testing for heparin-induced thrombocytopenia: a conceptual framework and implications for diagnosis. J Thromb Haemost. 2011;9(12):2498-500.##Sahu KK, Jindal V, Anderson J, Siddiqui AD, Jaiyesimi IA. Current Perspectives on Diagnostic Assays and Anti-PF4 Antibodies for the Diagnosis of Heparin-Induced Thrombocytopenia. J Blood Med. 2020;11:267-77.##Greinacher A, Eichler P, Lubenow N, Kwasny H, Luz M. Heparin-induced thrombocytopenia with thromboembolic complications: meta-analysis of 2 prospective trials to assess the value of parenteral treatment with lepirudin and its therapeutic aPTT range. Blood. 2000;96(3):846-51.##https://doi.org/10.1182/blood.V96.3.846##Lo GK, Sigouin CS, Warkentin TE. What is the potential for overdiagnosis of heparin-induced thrombocytopenia? Am J Hematol. 2007;82(12):1037-43.##Shaikh N. Heparin Induced Thrombocytopenia: Can Be Excluded. Journal of Blood Disorders and Transfusion. 2013;2011:1-4.##Cuker A, Arepally G, Crowther M, Rice L, Datko F, Hook K, et al. The HIT Expert Probability (HEP) Score: a novel pre‐test probability model for heparin‐induced thrombocytopenia based on broad expert opinion. J Thromb Haemost. 2010;8(12):2642-50.##Younis M, Ya'qoub L, Ali Z, Grover P, Ya'acoub R, Hamarshi MS. Comparison of a clinical-laboratory algorithm, 4t and heparin-induced thrombocytopenia expert probability scores in the diagnosis of heparin-induced thrombocytopenia in the critical care setting. Am J Blood Res. 2019;9(3):25-33.##Cuker A, Gimotty PA, Crowther MA, Warkentin TE. Predictive value of the 4Ts scoring system for heparin-induced thrombocytopenia: a systematic review and meta-analysis. Blood. 2012;120(20):4160-7.##Warkentin TE, Sheppard J-AI. Testing for heparin-induced thrombocytopenia antibodies. Transfus Med Rev. 2006;20(4):259-72.##Minet V, Dogné J-M, Mullier F. Functional assays in the diagnosis of heparin-induced thrombocytopenia: a review. Molecules. 2017;22(4):617.##Greinacher A, Juhl D, Strobel U, Wessel A, Lubenow N, Selleng K, et al. Heparin‐induced thrombocytopenia: a prospective study on the incidence, platelet‐activating capacity and clinical significance of antiplatelet factor 4/heparin antibodies of the IgG, IgM, and IgA classes. J Thromb Haemost. 2007;5(8):1666-73.##Warkentin TE, Sheppard J-AI, Horsewood P, Simpson PJ, Moore JC, Kelton JG. Impact of the patient population on the risk for heparin-induced thrombocytopenia. Blood Adv. 2000;96(5):1703-8.##https://doi.org/10.1182/blood.V96.5.1703##Pouplard C, May MA, Regina S, Marchand M, Fusciardi J, Gruel Y. Changes in platelet count after cardiac surgery can effectively predict the development of pathogenic heparin‐dependent antibodies. Br J Haematol. 2005;128(6):837-41.##Warkentin TE, Sheppard J-AI, Moore JC, Cook RJ, Kelton JG. Studies of the immune response in heparin-induced thrombocytopenia. Blood Adv. 2009;113(20):4963-9.##Althaus K, Pelzl L, Hidiatov O, Amiral J, Marini I, Bakchoul T. Evaluation of a flow cytometer-based functional assay using platelet-rich plasma in the diagnosis of heparin-induced thrombocytopenia. Thromb Res. 2019;180:55-61.##Brodard J, Benites V, Zeerleder DS, Nagler M. Accuracy of the functional, flow cytometer-based Emo-Test HIT Confirm® for the diagnosis of heparin-induced thrombocytopenia. Thromb Res. 2021;203:22-6.##Lo G, Juhl D, Warkentin T, Sigouin C, Eichler P, Greinacher A. Evaluation of pretest clinical score (4 T's) for the diagnosis of heparin‐induced thrombocytopenia in two clinical settings. J Thromb Haemost. 2006;4(4):759-65.##Gonthier M-C, Gendron N, Eloy P, Bourrienne M-C, Alhenc-Gelas M, Pouplard C, et al. Heparin-induced thrombocytopenia diagnosis: a retrospective study comparing heparin-induced platelet activation test to 14C-serotonin release assay. TH Open. 2021;5(04):e507-e12.##Eichler P, Budde U, Haas S, Kroll H, Loreth R, Meyer O, et al. First workshop for detection of heparin-induced antibodies: validation of the heparin-induced platelet-activation test (HIPA) in comparison with a PF4/heparin ELISA. J Thromb Haemost. 1999;81(04):625-9.##Warmerdam P, Van de Winkel J, Gosselin EJ, Capel P. Molecular basis for a polymorphism of human Fc gamma receptor II (CD32). J Exp Med. 1990;172(1):19-25.##Norris CF, Pricop L, Millard SS, Taylor SM, Surrey S, Schwartz E, et al. A naturally occurring mutation in FcγRIIA: AQ to K127 change confers unique IgG binding properties to the R131 allelic form of the receptor. Blood Adv. 1998;91(2):656-62.##https://doi.org/10.1182/blood.V91.2.656##Patel P, Michael JV, Naik UP, McKenzie SE. Platelet FcγRIIA in immunity and thrombosis: adaptive immunothrombosis. J Thromb Haemost. 2021;19(5):1149-60.##ARNOLD D, WARKENTIN T, WARKENTIN A, KELTON J. An algorithm for resolving 'indeterminate'test results in the platelet serotonin release assay for investigation of heparin‐induced thrombocytopenia. J Thromb Haemost. 2008;6(9):1595-7.##Horne III MK, Hutchison KJ. Simultaneous binding of heparin and platelet factor‐4 to platelets: Further insights into the mechanism of heparin‐induced thrombocytopenia. Am J Hematol. 1998;58(1):24-30.##https://doi.org/10.1002/(SICI)1096-8652(199805)58:13.0.CO;2-2##Rauova L, Zhai L, Kowalska MA, Arepally GM, Cines DB, Poncz M. Role of platelet surface PF4 antigenic complexes in heparin-induced thrombocytopenia pathogenesis: diagnostic and therapeutic implications. Blood. 2006;107(6):2346-53.##Maličev E, Kozak M, Rožman P. Evaluation of a flow cytometric assay for the confirmation of heparin‐induced thrombocytopenia. International Journal of Laboratory Hematology. 2016;38(3):240-5.##Sheridan D, Carter C, Kelton JG. A diagnostic test for heparin-induced thrombocytopenia. Blood. 1986;67(1):27-30.##https://doi.org/10.1182/blood.V67.1.27.27##Tardy B, Lecompte T, Mullier F, Vayne C, Pouplard C. Detection of platelet-activating antibodies associated with heparin-induced thrombocytopenia. J Clin Med. 2020;9(4):1226.##Warkentin TE. Clinical picture of heparin-induced thrombocytopenia (HIT) and its differentiation from non-HIT thrombocytopenia. J Thromb Haemost. 2016;116(11):813-22.##Warkentin TE, Greinacher A. Spontaneous HIT syndrome: knee replacement, infection, and parallels with vaccine-induced immune thrombotic thrombocytopenia. Thromb Res. 2021;204:40-51.##Schultz NH, Sørvoll IH, Michelsen AE, Munthe LA, Lund-Johansen F, Ahlen MT, et al. Thrombosis and thrombocytopenia after ChAdOx1 nCoV-19 vaccination. N Engl J Med. 2021;384(22):2124-30.##Horlait G, Minet V, Mullier F, Michaux I. Persistent heparin-induced thrombocytopenia: Danaparoid cross-reactivity or delayed-onset heparin-induced thrombocytopenia? A case report. Blood Coagul Fibrinolysis. 2017;28(2):193-7.##Runser A, Schaning C, Allemand F, Amiral J. An optimized and standardized rapid flow cytometry functional method for heparin-induced thrombocytopenia. Biomedicines. 2021;9(3):296.## ##</REF>
			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Effects of the Amino Acid Complex on Biochemical and Morphological Parameters of Hemostasis at Chronic Cadmium Intoxication</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Background: The present study was conducted to investigate the biochemical and morphological changes in the blood coagulation system caused by chronic cadmium intoxication and the anticoagulant activity of the amino acid complex (&#947;-aminobutyric acid, &#946;-alanine, glutamine, ethanolamine-O-sulphate). Previous studies have investigated the effect of the amino acid complex (AAc) on blood glucose levels in animals with experimental alloxan diabetes. The use of this complex demonstrated the ability to suppress the hyperglycaemic effect of alloxan, while also exhibiting anticoagulant activity.
Materials and methods: The experiments were carried out on non-linear white male rats divided into 3 groups: control rats, rats receiving cadmium sulphate and rats with cadmium intoxication injected with AAc. Biochemical (recalcification, prothrombin time, international sensitivity index, thrombin time, activated partial thromboplastin time, fibrinogen level, calcium level) and histological (Haematoxylin &#38; Eosin and Giemsa staining) methods were used in the studies.
Results and conclusion: Chronic cadmium intoxication leads to alterations in several blood coagulation parameters, suggesting a predisposition to hypercoagulation. However, administration of AAc reduces blood coagulation. Blood samples from poisoned rats showed the presence of red blood cells and leukocytes with morphological changes, including the presence of numerous platelets in clusters or groups. Conversely, when AAc was administered to cadmium poisoned rats, erythrocytes and neutrophils showed morphologically normal characteristics. &#160;The results obtained confirm the anticoagulant activity of AAc, which may be used in the future for the treatment of various thrombotic conditions.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>39</FPAGE>
			<TPAGE>46</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/102024/11/26
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/9/6
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/32024/12/23
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/10/3
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Zoya</Name>
				<MidName></MidName>
				<Family>Paronyan</Family>
				<NameE>Zoya</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Paronyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>aregarpi4@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Inesa</Name>
				<MidName></MidName>
				<Family>Sahakyan</Family>
				<NameE>Inesa</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Sahakyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>inesasahakyan5@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Hasmik</Name>
				<MidName></MidName>
				<Family>Stepanyan</Family>
				<NameE>Hasmik</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Stepanyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>stepanyan.hasmik@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Narine</Name>
				<MidName></MidName>
				<Family>Tumasyan</Family>
				<NameE>Narine</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Tumasyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>ntumasyan@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Lyudmila</Name>
				<MidName></MidName>
				<Family>Araqelyan</Family>
				<NameE>Lyudmila</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Araqelyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>aragelyanlyuda3@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Nune</Name>
				<MidName></MidName>
				<Family>Kocharyan</Family>
				<NameE>Nune</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Kocharyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>nunekocharyan466@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Ani</Name>
				<MidName></MidName>
				<Family>Suqiasyan</Family>
				<NameE>Ani</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Suqiasyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>anisuqiasyan2001@mail.ru</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Torgom</Name>
				<MidName></MidName>
				<Family>Seferyan</Family>
				<NameE>Torgom</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Seferyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>seferyant@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Lusine</Name>
				<MidName></MidName>
				<Family>Grigoryan</Family>
				<NameE>Lusine</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Grigoryan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>lusokgrig@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Silva</Name>
				<MidName></MidName>
				<Family>Abrahamyan</Family>
				<NameE>Silva</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Abrahamyan</FamilyE>
				<Organizations>
				<Organization>H. Buniatian Institute of Biochemistry NAS Armenia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>silva.abrahamyan@gmail.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Amino acid complex (AAc)</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Hemostasis</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Cadmium intoxication</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Indirect anticoagulant</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Cytotoxicity</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Hemolysis</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>Ilyinov A.N., Ryazanov I.A., Osipov A.N. Acid erythrograms of mice poisoned with Zn, Cd and Pb. Toxicological Bulletin.1997; 14: 10-14.##Wang Bo, Yanli Du. Cadmium and Its Neurotoxic Effects. Oxid Med Cell Longev. 2013; 2013: 898034.##Charkiewicz A.E., Omeljaniuk W.J., Nowak K.K., Garley M., and Niklinski J. Cadmium Toxicity and Health Effects-A Brief Summary. Molecules. 2023; 28(18): 6620.##Blainey JD, Adams RG, Brewer DB, Harvey TC. Cadmium-induced osteomalacia. Br J Ind Med. 1980; 37(3): 278-84.##Fiévez L., Kirschvink N., Zhang W., Lagente V., Lekeux P., Bureau F., Gustin P. Effects of betamethasone on inflammation and emphysema induced by cadmium nebulisation in rats. Pulmonary, Gastrointestinal and Urogenital Pharmacology. 2009; 606(1-3): 210-214.##Gallagher CM, Meliker JR. Blood and urine cadmium, blood pressure, and hypertension: a systematic review and meta-analysis. Environ Health Perspect.2010;118 (12):1676-84.##Thévenod F. Nephrotoxicity and the Proximal Tubule: Insights from Cadmium Subject Area. Nephron Physiology.2003; 93(4): 87-93..##Helmestam M., Stavreus-Evers A., Olovsson M. Cadmium chloride alters mRNA levels of angiogenesis related genes in primary human endometrial endothelial cells grown in vitro. Reprod.Toxicol. 2010; 30(3): 370-376.doi: 10.1016/j.reprotox.2010.05.003.##Waalkes MP, Rehm S. Cadmium and prostate cancer. J Toxicol Environ Health. 1994 Nov; 43(3):251-69.##Prozialek WC, Edwards JR, Woods JM. The vascular endothelium as a target of cadmium toxicity. Life Sci. 2006; 79: 1493-1506.##Wang X. et al. Low doze cadmium upregulates the expression of von Willebrand factor in endothelial cells. Toxicol. Lett. 2018; 290: 46-54.##Kokame K, Sakata T, Kokiwo Y, Miyata T. von Willebrand factor-to. ADAMTS13 ratio increases with age in a Japanese population. J.Thromb. Haemost. 2011; 9: 1426-1428.##Hasimoto Y, et al. Relationship between age and plasma t-PA, PA-inhibitor, and PA activity. Thromb. Res. 1987; 46: 625-633.##Samoilov M.V., Naumov A.G. Morphofunctional characteristics of erythrocytes as a criterion of the severity of endogenous intoxication. Russian medical journal. 2000; 1: 31-33.##Suwalsky M. , Villena F., Norris B., Cuevas F., Sotomayor C․ Cadmium-induced changes in the membrane of human erythrocytes and molecular models․ J Inorg Biochem, 2004; 98(6): 1061-6. DOI:##Verbost P.M., Flik G., Pang P.K., Lock R.A., Wendelaar Bonga S.E. Cadmium inhibition of the erythrocyte Ca2+ pump. Jour. Biol. Chem. 1989; 264: 5613.##Paronyan, Z. Kh., Khachatryan R. S., Stepanyan A. A., Grigoryan L. S., Arakelyan L. N. Changes in glucose levels and some blood coagulation parameters in rats with experimental alloxan-induced diabetes under the influence of a new amino acid complex. Medical Science of Armenia. NAS RA; 2021: 61(3): 64-72.##Paronyan Z.Kh.,Araqelyan L.N., Grigoryan L.S., Khachatryan R.S., Galstyan A.Z., Stepanyan A.A. The influence of an antidiabetic amino acid complex on some parameters of plasma hemostasis. Medical Science of Armenia. 2023; 63(3): 64-71. doi:10.54503/0514-7484-2023-63.3-64.##Edigarova L.V., Akopyan V.G. Antiplatelet activity of the vascular wall and the possibility of its correction with GABAergic agents in conditions of hypokinesia. Experimental and clinical pharmacology, 2000. 5, p. 41 - 43.##Fischer A, Jacobson KA, Rose J and Zeller R: Hematoxylin and eosin staining of tissue and cell sections. CSH Protoc pdb.prot4986, 2008.##Redginal H: Giemsa preparation for staining blood films. Science 86: 548, 1937.##Zubairov D.M. Coagulation disorders due to vitamin K deficiency and indirect anticoagulants. KAZAN MEDICAL JOURNAL. 1995; 76(4):344-346. doi: ##https://doi.org/10.17816/kazmj105001##Beth H.Shar MD, Christofer D. Hillyer MD. Cryoprecipitate and Fibrinogen Concentrates Transfusion Medicine and Hemostasis (Second Edition). 2013.##Barbier O, Iacqullet G.,Taic M. et al. Acute study of interaction between cadmium, calcium and zinc transport along the rat nephron in vivo, Am. I.Physiol. Renal. Physiol. 2004; 287:1067-1075.##Kranias E.G., Bers D.M. Calcium and cardiomyopathies, Subcell. Biochem. 2007; 45: 523-537.##Chandrasekar Palaniswamy MD, Arunabh Sekhri MD, Wilbert S. Aronow MD, Ankur Kalra MD, Stephen J. Peterson MD, MACP. Association of Warfarin Use With Valvular and Vascular Calcification: A Review. Clinical Cardiology. 2011;34(2): 74-81.##Shea M.K., Cushman, S.L. Booth, G.L. Burke and HCSB Krichevsky, Vitamin K status and vascular calcification: evidence from observational and clinical studies. Advances in Nutrition. 2012; 3(2): 158-165.##Krüger T., Westenfeld R., Schurgers L., Vincent M. Brandenburg. Coagulation Meets Calcification: The Vitamin K System. The International journal of artificial organs. 2009; 32(2): 67-74.##Prorialeck WC, Edwards JR, Woods JM. The vascular endothelium as a target of cadmium toxicity. Life Sci. 2006; 79: 1493-1506.##Wang X, et al. Low doze cadmium upregulates the expression if von Willebrand factor in endothelial cells. Toxicol. Lett. 2018; 290: 46-54.##Albanes S. et al. Aging and ABO blood type influence von Willebrand factor and factor VIII levels through interrelated mechanisms. J. Thromb. Haemost. 2016; 14: 953- 963.## ##</REF>
			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Analysis of Coagulation Parameters in Patients with Breast Pathology and Their Possible Relevance to a Hypercoagulable State</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Background:&#160;To study the alteration in coagulation parameters such as activated partial thromboplastin time (APTT), prothrombin time (PT), thrombin time (TT), D-dimer and fibrinogen among patients with benign and malignant breast lesions when compared to normal controls.
Materials and methods: The present study was a prospective cross-sectional study conducted among 50 cases diagnosed with benign and malignant breast cancer and comparing them with 20 age-matched controls. Coagulation parameters such as PT, TT, APTT, fibrinogen, and D-dimer were collected and compared between the malignant cases, benign cases, and age-matched control groups based on clinical and demographic details, the status of Progesterone receptor, Estrogen receptor, Her2 Neu, side and grading of cancer.
Results: Significant difference was reported with regard to mean age (p=0.0103) between malignant and benign tumor group (p=0.0103). Mean fibrinogen (p&#60;0.001), thrombin time (p=0.007), and D-dimer (p&#60;0.001) between the three groups also showed a statistically significant difference.
Conclusion: Of the biological parameters assessed in the present study; thrombin time, D-dimer and fibrinogen levels show significant differences in patients with benign and malignant breast diseases. This may serve as a biological marker to evaluate the beginning of Cancer-associated venous thrombosis (CAT) in breast cancer patients.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>47</FPAGE>
			<TPAGE>55</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/102024/11/262024/11/7
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/17
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/32024/12/232024/12/3
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/9/13
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Nidhya</Name>
				<MidName></MidName>
				<Family>Ganesan</Family>
				<NameE>Nidhya</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Ganesan</FamilyE>
				<Organizations>
				<Organization>Department of Pathology, PSG Institute of Medical Sciences and Research, Off, Avinashi Rd, Peelamedu, Coimbatore, Tamil Nadu 641004.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>nidhyaganesan@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Stefan</Name>
				<MidName></MidName>
				<Family>Mariano</Family>
				<NameE>Stefan</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Mariano</FamilyE>
				<Organizations>
				<Organization>Department of Pathology, PSG Institute of Medical Sciences and Research, Off, Avinashi Rd, Peelamedu, Coimbatore, Tamil Nadu 641004.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>snmariano@icloud.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>R</Name>
				<MidName></MidName>
				<Family>Chitra</Family>
				<NameE>R</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Chitra</FamilyE>
				<Organizations>
				<Organization>Department of Surgery, PSG Institute of Medical Sciences &#38; Research, Avinashi Rd, Peelamedu, Coimbatore, Tamil Nadu 641004.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>drchitrar@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Prasanna N</Name>
				<MidName></MidName>
				<Family>Kumar</Family>
				<NameE>Prasanna N</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Kumar</FamilyE>
				<Organizations>
				<Organization>Department of Pathology, PSG Institute of Medical Sciences and Research, Off, Avinashi Rd, Peelamedu, Coimbatore, Tamil Nadu 641004.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>drpnkumar2008@gmail.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Biomarkers</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Blood coagulation</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Breast neoplasm</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Fibrin fragments</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Thrombosis</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>Kyriazi V. Breast cancer as an acquired thrombophilic state. J Breast Cancer. 2012 Jun;15(2):148-56.##Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA A Cancer J Clin. 2021 May;71:209-49.##Heer E, Harper A, Escandor N, Sung H, McCormack V, Fidler-Benaoudia MM. Global burden and trends in premenopausal and postmenopausal breast cancer: a population-based study. Lancet Glob Health. 2020 Aug;8(8):e1027-37.##Arnold M, Morgan E, Rumgay H, Mafra A, Singh D, Laversanne M, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. Breast. 2022 Dec; 66:15-23.##Sathishkumar K, Chaturvedi M, Das P, Stephen S, Mathur P. Cancer incidence estimates for 2022 &#38; projection for 2025: Result from National Cancer Registry Programme, India. Indian J Med Res. 2022 Oct-Nov;156(4&#59;5):598-607.##Beinse G, Berger F, Cottu P, Dujaric ME, Kriegel I, Guilhaume MN, et al. Circulating tumor cell count and thrombosis in metastatic breast cancer. J Thromb Haemost. 2017 Oct;15(10):1981-1988.##Rückerl R, Schneider A, Hampel R, Breitner S, Cyrys J, Kraus U, et al. Association of novel metrics of particulate matter with vascular markers of inflammation and coagulation in susceptible populations -results from a panel study. Environ Res. 2016 Oct; 150:337-347.##Campello E, Spiezia L, Radu CM, Simioni P. Microparticles as biomarkers of venous thromboembolic events. Biomark Med. 2016 Jul;10(7):743-55.##Snoderly HT, Boone BA, Bennewitz MF. Neutrophil extracellular traps in breast cancer and beyond: current perspectives on NET stimuli, thrombosis and metastasis, and clinical utility for diagnosis and treatment. Breast Cancer Res. 2019 Dec;21(1):145.##Madhav MR, Nayagam SG, Biyani K, Pandey V, Kamal DG, Sabarimurugan S, et al. Epidemiologic analysis of breast cancer incidence, prevalence, and mortality in India: Protocol for a systematic review and meta-analyses. Medicine (Baltimore). 2018 Dec;97(52):e13680.##Gochhait S, Sahoo SS, Chhabra G, Mukhopahay AK, Sharma S. Role of D-dimer in patients of operable breast cancer withlymph node metastases: A matched cross-sectional study. Oncol J India. 2020 May-Aug;4(2):39-42.##Okello CD, Mulumba Y, Omoding A, Ddungu H, Orem J. Survival of patients with cancer associated thrombosis at the Uganda Cancer Institute. Ecancermedicalscience. 2021 Mar; 15:1212.##Kovac M, Kovac Z, Tomasevic Z, Tomic B, Gvozdenov M, Radojkovic D. Breast cancer and recurrent thrombosis - Results from prospective single center study. Breast J. 2019 Jul;25(4):783-785.##Wang L, Wang J, Li P, Wang X, Wu S, Shi B. Association between short-term heart rate variability and blood coagulation in patients with breast cancer. Sci Rep. 2021 Jul;11(1):15414.##Pang M, Zhao F, Yu P, Zhang X, Xiao H, Qiang W, et al. The significance of coagulation and fibrinolysis-related parameters in predicting postoperative venous thrombosis in patients with breast cancer. Gland Surg. 2021 Apr;10(4):1439-1446.##Hill CN, Hernández-Cáceres MP, Asencio C, Torres B, Solis B, Owen GI. Deciphering the Role of the Coagulation Cascade and Autophagy in Cancer-Related Thrombosis and Metastasis. Front Oncol. 2020 Dec;10:605314.##Mandoj C, Pizzuti L, Sergi D, Sperduti I, Mazzotta M, Lauro LD, et al. Observational study of coagulation activation in early breast cancer: Development of a prognostic model based on data from the real-world setting. J Transl Med. 2018 May;16(1):129.##Dirix LY, Oeyen S, Buys A, Liégois V, Prové A, Van De Mooter T, et al. Coagulation/fibrinolysis and circulating tumor cells in patients with advanced breast cancer. Breast Cancer Res Treat. 2022 Apr;192(3):583-591.##Mi XK, Liu QR, Zhu L, Sang MX, Guo LR, Shan BE. Mechanism of the high coagulation state of breast cancer tissue factor. Eur Rev Med Pharmacol Sci. 2017 May;21(9):2167-2171.##Khan UT, Walker AJ, Baig S, Card TR, Kirwan CC, Grainge MJ. Venous thromboembolism and mortality in breast cancer: cohort study with systematic review and meta-analysis. BMC Cancer. 2017 Nov;17(1):747.## ##</REF>
			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Exploring the Basic Molecular Pathways: Metformin as a Potential Treatment Option for Pancreatic Cancer</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Background: Pancreatic cancer is one of the most aggressive and lethal malignancies, with limited treatment options and a poor prognosis. Recent research has highlighted the potential role of metformin, a widely used antidiabetic drug, in modulating cancer risk and progression. This review aims to explore the current evidence on the impact of metformin on pancreatic cancer outcomes and its potential mechanisms of action.
Materials and Methods: A comprehensive literature search was conducted using databases such as PubMed, Scopus, and Web of Science to identify studies investigating the relationship between metformin use and pancreatic cancer. Inclusion criteria encompassed clinical trials, cohort studies, and laboratory research published in the last two decades. Data extraction focused on patient outcomes, metformin dosage, study design, and proposed mechanisms of action.
Results: The review indicates that metformin use is associated with improved overall survival and reduced cancer incidence in patients with pancreatic cancer, particularly among those with concurrent diabetes. Mechanistic studies suggest that metformin exerts its anticancer effects through the inhibition of the mTOR pathway, reduction of insulin-like growth factors, and induction of autophagy. However, the results are heterogeneous, and several studies highlight the need for further clinical trials to establish causality and optimal therapeutic regimens.
Conclusion: While current evidence supports a potentially beneficial role of metformin in pancreatic cancer management, the findings are preliminary and require further validation through randomized controlled trials. The heterogeneity of the studies underscores the necessity for standardized protocols to assess the efficacy and safety of metformin as an adjunct therapy in pancreatic cancer treatment.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>56</FPAGE>
			<TPAGE>68</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/102024/11/262024/11/72024/11/9
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/19
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/32024/12/232024/12/32024/12/22
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/10/2
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Sepehr</Name>
				<MidName></MidName>
				<Family>Ramezani</Family>
				<NameE>Sepehr</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Ramezani</FamilyE>
				<Organizations>
				<Organization>Babol University of Medical Science, Babol, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>sepehr.ramezany74@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Dariush</Name>
				<MidName></MidName>
				<Family>Moslemi</Family>
				<NameE>Dariush</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Moslemi</FamilyE>
				<Organizations>
				<Organization>Babol University of Medical Science, Babol, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>moslemi_d@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Faezeh</Name>
				<MidName></MidName>
				<Family>Firuzpour</Family>
				<NameE>Faezeh</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Firuzpour</FamilyE>
				<Organizations>
				<Organization>Babol University of Medical Science, Babol, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>faezeh.1997@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Hamidreza</Name>
				<MidName></MidName>
				<Family>Didar</Family>
				<NameE>Hamidreza</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Didar</FamilyE>
				<Organizations>
				<Organization>Shahid Beheshti University of Medical Science, Tehran, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>hamidreza.didar@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Seyedamirmohammad</Name>
				<MidName></MidName>
				<Family>Mazloumi</Family>
				<NameE>Seyedamirmohammad</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Mazloumi</FamilyE>
				<Organizations>
				<Organization>Babol University of Medical Science, Babol, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>Amir.mazloumi1996@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Narjes</Name>
				<MidName></MidName>
				<Family>rezaeiroushan</Family>
				<NameE>Narjes</NameE>
				<MidNameE></MidNameE>
				<FamilyE>rezaeiroushan</FamilyE>
				<Organizations>
				<Organization>Azad University Sari Branch Faculty of Medicine, Sari, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>narjes.rezaee@gmail.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Metformin</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Pancreatic Cancer</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Molecular Pathways</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Cancer Treatment</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Cellular Energy</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Metabolism</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
				<REF>Miller KD, Fidler‐Benaoudia M, Keegan TH, Hipp HS, Jemal A, Siegel RL. Cancer statistics for adolescents and young adults, 2020. CA: a cancer journal for clinicians. 2020;70(6):443-59.##Zyromski NJ, White PB. Pancreatic cancer in obesity: epidemiology, clinical observations, and basic mechanisms. Anticancer Agents Med Chem. 2011;11(5):470-8.##Zhu L, Yang K, Ren Z, Yin D, Zhou Y. Metformin as anticancer agent and adjuvant in cancer combination therapy: Current progress and future prospect. Transl Oncol. 2024;44:101945.##Shi Y-Q, Zhou X-C, Du P, Yin M-Y, Xu L, Chen W-J, Xu C-F. Relationships are between metformin use and survival in pancreatic cancer patients concurrent with diabetes: A systematic review and meta-analysis. Medicine. 2020;99(37):e21687.##Evans JM, Donnelly LA, Emslie-Smith AM, Alessi DR, Morris AD. Metformin and reduced risk of cancer in diabetic patients. Bmj. 2005;330(7503):1304-5.##Sadeghi N, Abbruzzese JL, Yeung S-CJ, Hassan M, Li D. Metformin use is associated with better survival of diabetic patients with pancreatic cancer. Clinical cancer research. 2012;18(10):2905-12.##Bhaw-Luximon A, Jhurry D. Metformin in pancreatic cancer treatment: from clinical trials through basic research to biomarker quantification. Journal of cancer research and clinical oncology. 2016;142:2159-71.##Hu J, Fan H-D, Gong J-P, Mao Q-S. The relationship between the use of metformin and the risk of pancreatic cancer in patients with diabetes: a systematic review and meta-analysis. BMC Gastroenterology. 2023;23(1):50.##Cantoria MJ, Patel H, Boros LG, Meuillet EJ. Metformin and pancreatic cancer metabolism. Pancreatic Cancer-Insights into Molecular Mechanisms and Novel Approaches to Early Detection and Treatment: IntechOpen; 2014.##Wen J, Yi Z, Chen Y, Huang J, Mao X, Zhang L, et al. Efficacy of metformin therapy in patients with cancer: a meta-analysis of 22 randomised controlled trials. BMC Medicine. 2022;20(1):402.##Suissa S, Azoulay L. Metformin and Cancer: Mounting Evidence Against an Association. Diabetes Care. 2014;37(7):1786-8.##Zhu W, Xu H, Ma J, Guo J, Xue W, Gu B, et al. An Open-Label Pilot Study of Metformin as a Concomitant Therapy on Patients with Prostate Cancer Undergoing Androgen Deprivation Treatment. Urol Int. 2017;98(1):79-84.##Zell JA, McLaren CE, Morgan TR, Lawson MJ, Rezk S, Albers CG, et al. A Phase IIa Trial of Metformin for Colorectal Cancer Risk Reduction among Individuals with History of Colorectal Adenomas and Elevated Body Mass Index. Cancer Prev Res (Phila). 2020;13(2):203-12.##van Eijck CWF, Vadgama D, van Eijck CHJ, Wilmink JW, Group DPC. Metformin boosts antitumor immunity and improves prognosis in upfront resected pancreatic cancer: an observational study. JNCI: Journal of the National Cancer Institute. 2024.##Hu J, Fan HD, Gong JP, Mao QS. The relationship between the use of metformin and the risk of pancreatic cancer in patients with diabetes: a systematic review and meta-analysis. BMC Gastroenterol. 2023;23(1):50.##van Eijck CWF, Vadgama D, van Eijck CHJ, Wilmink JW. Metformin boosts anti-tumor immunity and improves prognosis in upfront resected pancreatic cancer: an observational study. J Natl Cancer Inst. 2024.##Kim J, Bae YJ, Kang HT. Metformin Use May Increase Risk of Pancreatic Cancer in Diabetic Women: An Analysis of the Korean National Health Insurance Service-National Health Screening Cohort Database. Korean J Fam Med. 2022;43(5):327-33.##https://doi.org/10.4082/kjfm.2013.34.5.327##Andersen HB, Ialchina R, Pedersen SF, Czaplinska D. Metabolic reprogramming by driver mutation-tumor microenvironment interplay in pancreatic cancer: new therapeutic targets. Cancer Metastasis Rev. 2021;40(4):1093-114.##Bhaw-Luximon A, Jhurry D. Metformin in pancreatic cancer treatment: from clinical trials through basic research to biomarker quantification. Journal of Cancer Research and Clinical Oncology. 2016;142(10):2159-71.##Velazquez-Torres G, Fuentes-Mattei E, Choi HH, Yeung S-CJ, Meng X, Lee M-H. Diabetes mellitus type 2 drives metabolic reprogramming to promote pancreatic cancer growth. Gastroenterology Report. 2020;8(4):261-76.##Marini C, Salani B, Massollo M, Amaro A, Esposito AI, Orengo AM, et al. Direct inhibition of hexokinase activity by metformin at least partially impairs glucose metabolism and tumor growth in experimental breast cancer. Cell Cycle. 2013;12(22):3490-9.##Cerullo M, Gani F, Chen SY, Canner J, Pawlik TM. Metformin Use Is Associated with Improved Survival in Patients Undergoing Resection for Pancreatic Cancer. J Gastrointest Surg. 2016;20(9):1572-80.##Qin C, Yang G, Yang J, Ren B, Wang H, Chen G, et al. Metabolism of pancreatic cancer: paving the way to better anticancer strategies. Molecular Cancer. 2020;19(1):50.##Cheong JH, Park ES, Liang J, Dennison JB, Tsavachidou D, Nguyen-Charles C, et al. Dual inhibition of tumor energy pathway by 2-deoxyglucose and metformin is effective against a broad spectrum of preclinical cancer models. Mol Cancer Ther. 2011;10(12):2350-62.##Tennakoon JB, Shi Y, Han JJ, Tsouko E, White MA, Burns AR, et al. Androgens regulate prostate cancer cell growth via an AMPK-PGC-1α-mediated metabolic switch. Oncogene. 2014;33(45):5251-61.##Hardie DG, Schaffer BE, Brunet A. AMPK: An Energy-Sensing Pathway with Multiple Inputs and Outputs. Trends Cell Biol. 2016;26(3):190-201.##Faubert B, Vincent EE, Poffenberger MC, Jones RG. The AMP-activated protein kinase (AMPK) and cancer: many faces of a metabolic regulator. Cancer letters. 2015;356(2):165-70.##Kennedy MSN, Masharani U. Pancreatic hormones &#38; antidiabetic drugs. Basic &#38; clinical pharmacology. 2018;13:723-47.##Ferretti AC, Hidalgo F, Tonucci FM, Almada E, Pariani A, Larocca MC, Favre C. Metformin and glucose starvation decrease the migratory ability of hepatocellular carcinoma cells: targeting AMPK activation to control migration. Sci Rep. 2019;9(1):2815.##Wheaton WW, Weinberg SE, Hamanaka RB, Soberanes S, Sullivan LB, Anso E, et al. Metformin inhibits mitochondrial complex I of cancer cells to reduce tumorigenesis. Elife. 2014;3:e02242.##Zuo L, Wijegunawardana D. Redox Role of ROS and Inflammation in Pulmonary Diseases. Adv Exp Med Biol. 2021;1304:187-204.##El-Benna J, Dang P, Gougerot-Pocidalo M-A, Elbim C. Phagocyte NADPH oxidase: a multicomponent enzyme essential for host defenses. Archivum immunologiae et therapiae experimentalis. 2005;53(3):199-206.##Harrison IP, Selemidis S. Understanding the biology of reactive oxygen species and their link to cancer: NADPH oxidases as novel pharmacological targets. Clinical and Experimental Pharmacology and Physiology. 2014;41(8):533-42.##Tan H-Y, Wang N, Li S, Hong M, Wang X, Feng Y. The reactive oxygen species in macrophage polarization: reflecting its dual role in progression and treatment of human diseases. Oxidative medicine and cellular longevity. 2016;2016.##Nassif RM, Chalhoub E, Chedid P, Hurtado-Nedelec M, Raya E, Dang PM-C, et al. Metformin Inhibits ROS Production by Human M2 Macrophages via the Activation of AMPK. Biomedicines. 2022;10(2):319.##Zhu Z, Jiang T, Suo H, Xu S, Zhang C, Ying G, Yan Z. Metformin Potentiates the Effects of Anlotinib in NSCLC via AMPK/mTOR and ROS-Mediated Signaling Pathways. Front Pharmacol. 2021;12:712181.##Melnik BC, Schmitz G. Metformin: an inhibitor of mTORC1 signaling. J Endocrinol Diabetes Obes. 2014;2(2):1029.##Roccio M, Bos J, Zwartkruis F. Regulation of the small GTPase Rheb by amino acids. Oncogene. 2006;25(5):657-64.##Paudel S, Wu G, Wang X. Amino Acids in Cell Signaling: Regulation and Function. In: Wu G, editor. 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			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>The Potential Role of microRNAs in the Progression and Aggressiveness of Gallbladder Cancer: Molecular Markers to Therapeutic Interventions</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Gallbladder cancer (GBC) is among the utmost pervasive form of biliary tract cancers and remains relatively under-researched. Its prognosis is generally poor, with survival rates varying based on diagnostic stage, from 20% to 65%. The hallmarks of cancer, such as proliferation of cells, migration of cells, invasion, process of programmed cell death, radio/chemosensitivity, and cancer stem cell phenotype, are all influenced by miRNAs, which have been found to be essential actuators in the process of gene expression. This review is an attempt to reveal the molecular pathways influenced by miRNAs that could be targeted for therapeutic purposes in gallbladder cancer (GBC) and also emphasizes the need for precision medicine to target potent pathways, utilizing not only inhibiting receptor or antibody but also investigating miRNAs as a potential treatment strategy.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>69</FPAGE>
			<TPAGE>85</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/102024/11/262024/11/72024/11/92024/10/19
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/7/28
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/32024/12/232024/12/32024/12/222024/12/24
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/10/4
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Naseem</Name>
				<MidName></MidName>
				<Family>Fatima</Family>
				<NameE>Naseem</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Fatima</FamilyE>
				<Organizations>
				<Organization>Department of Biochemistry, Era’s Lucknow Medical College and Hospital, Lucknow, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>naseemfatima.fatima@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Syed Tasleem</Name>
				<MidName></MidName>
				<Family>Raza</Family>
				<NameE>Syed Tasleem</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Raza</FamilyE>
				<Organizations>
				<Organization>Department of Biochemistry, Era’s Lucknow Medical College and Hospital, Lucknow, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>tasleem24@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Vijay</Name>
				<MidName></MidName>
				<Family>Kumar</Family>
				<NameE>Vijay</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Kumar</FamilyE>
				<Organizations>
				<Organization>Department of Surgical Oncology, King George’s Medical University, Lucknow, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>drvkumar2007@gmil.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Saliha</Name>
				<MidName></MidName>
				<Family>Rizvi</Family>
				<NameE>Saliha</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Rizvi</FamilyE>
				<Organizations>
				<Organization>Department of Biotechnology, Era University, Lucknow, India</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>rizvi_saliha@rediffmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Farheen</Name>
				<MidName></MidName>
				<Family>Khan</Family>
				<NameE>Farheen</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Khan</FamilyE>
				<Organizations>
				<Organization>Department of Biotechnology, Era University, Lucknow, India</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>Farheenkh19@gmail.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Gallbladder cancer</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>MicroRNAs</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Molecular Pathways</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Target therapy</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Promising biomarker</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
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			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Poly (amidoamine) Dendrimers in Cancer Therapy: Chemotherapy, Radiotherapy and Imaging Advances</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Cancer is estimated to overtake cardiovascular diseases and take the top spot as the leading and most important cause of mortality globally in the near future. Given the importance of early diagnosis to reduce mortality, many efforts have been made to discover a theranostic system for simultaneous cancer diagnosis and treatment. So far, the use of nanotechnology has greatly contributed to the improvement and development of these systems. Meanwhile, dendrimer nanoparticles have attracted considerable attention in medical research due to their unique properties. Poly(amidoamine) (PAMAM) dendrimers have become the primary category of dendrimers and have been widely studied for their possible application in cancer treatments. These nanoparticles have features including interior cavities and peripheral functional groups that allow the encapsulation of diverse medications or diagnostic agents. As a result, these particles can function as efficient nanocarriers and vectors for medical applications. This capability allows for the resolution of the obstacles presented by the tumor microenvironment. The prospective use of multifunctional PAMAM holds promise in enabling thorough monitoring of different stages of treated cancer tissue, hence providing substantial support in the early detection and prediction of tumor response. The primary focus of this study will be to investigate the most recent developments of PAMAM dendrimers in the field of cancer theranostics. The employment of NPs in anticancer medicine administration for radiation treatment, chemotherapy, and diagnostic imaging is underscored due to its significant potential.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>86</FPAGE>
			<TPAGE>104</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/102024/11/262024/11/72024/11/92024/10/192024/11/20
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/30
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/32024/12/232024/12/32024/12/222024/12/242024/12/17
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/9/27
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Mahdieh</Name>
				<MidName></MidName>
				<Family>Ahmadi Kamalabadi</Family>
				<NameE>Mahdieh</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Ahmadi Kamalabadi</FamilyE>
				<Organizations>
				<Organization>Social Determinants of Health Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>mkniloo@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Somayeh</Name>
				<MidName></MidName>
				<Family>Kazempour</Family>
				<NameE>Somayeh</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Kazempour</FamilyE>
				<Organizations>
				<Organization>Department of Radiology, Faculty of Allied Medical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>skazempour.sunny@gmail.com.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Asieh</Name>
				<MidName></MidName>
				<Family>Fatemidokht</Family>
				<NameE>Asieh</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Fatemidokht</FamilyE>
				<Organizations>
				<Organization>Department of Radiology, Faculty of Allied Medical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>a_fatemidokht@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Mikaeil</Name>
				<MidName></MidName>
				<Family>Molazadeh</Family>
				<NameE>Mikaeil</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Molazadeh</FamilyE>
				<Organizations>
				<Organization>Department of Medical Physics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email></Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Fereshteh</Name>
				<MidName></MidName>
				<Family>Koosha</Family>
				<NameE>Fereshteh</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Koosha</FamilyE>
				<Organizations>
				<Organization>Department of Radiology Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>frshtkoosha@yahoo.com</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>PAMAM dendrimers</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Chemotherapy</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Radio sensitization</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Imaging</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
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			</REFRENCE>
		</REFRENCES>

	</ARTICLE>


	<ARTICLE> 
		<TitleF>Nutritional Supportive Care in Head and Neck Cancer Patients – A Narrative Review</TitleF>
		<TitleE></TitleE>
		<TitleLang_ID>2</TitleLang_ID>
		<ABSTRACTS>
			<ABSTRACT>
			<Language_ID>2</Language_ID>
			<CONTENT>Head and neck cancer patients are more at high risk for malnutrition before, during, and after the cancer treatment procedures due to the proximity of key anatomical structures that are essential for mastication and deglutition. A multidisciplinary approach beginning with preliminary nutritional screening, comprehensive assessment, and nutritional supportive care is mandatory for all head and neck cancer patients. Such interventions not only improve quality of life but also increase the survival rate of the head and neck cancer patients. This updated narrative review focused on the recent updates of the various steps involved in the nutritional management of head and neck cancer patients, like pre-treatment nutritional care, screening and assessment, and nutritional interventions during and after cancer therapy with updates on nanoformulations of nutraceuticals. We reviewed all published literature between 2014 and 2024 about nutrition in head and neck cancer patients from major databases such as Embase, Web of Science, and PubMed. In addition to the nutritional parameters that should be considered during the nutritional assessment of patients with head and neck cancer, this review underscores the therapeutic efficacy of nutraceuticals in treating this disease. This narrative review added a note on recent updates on the use of a combination of novel nanoformulated nutraceuticals with chemotherapeutic agents, which were known for the improved drug delivery, such as targeting the neoplastic cells and thus preventing adverse effects.</CONTENT>
			</ABSTRACT>
		</ABSTRACTS>

		<PAGES>
			<PAGE>
			<FPAGE>105</FPAGE>
			<TPAGE>113</TPAGE>
			</PAGE>
		</PAGES>

		<RECEIVE_DATE>
			2024/10/262024/11/192024/11/112024/11/102024/11/262024/11/72024/11/92024/10/192024/11/202024/11/5
		</RECEIVE_DATE>

		<RECEIVE_DATE_FA>
			1403/8/15
		</RECEIVE_DATE_FA>

		<ACCEPT_DATE>
			2024/12/242024/12/22024/12/252024/12/32024/12/232024/12/32024/12/222024/12/242024/12/172024/12/4
		</ACCEPT_DATE>

		<ACCEPT_DATE_FA>
			1403/9/14
		</ACCEPT_DATE_FA>

		<AUTHORS>
			<AUTHOR>
				<Name>Doppalapudi</Name>
				<MidName></MidName>
				<Family>Radhika</Family>
				<NameE>Doppalapudi</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Radhika</FamilyE>
				<Organizations>
				<Organization>Department of Oral Medicine and Radiology, Saveetha Dental college and hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamilnadu, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>radhikav21@gmail.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Arvind</Name>
				<MidName></MidName>
				<Family>Muthukrishnan</Family>
				<NameE>Arvind</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Muthukrishnan</FamilyE>
				<Organizations>
				<Organization>Department of Oral Medicine and Radiology, Saveetha Dental college and hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, Tamilnadu, India.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>arvindm@saveetha.com</Email>
				</EMAILS>
			</AUTHOR>

			<AUTHOR>
				<Name>Rakhi</Name>
				<MidName></MidName>
				<Family>Issrani</Family>
				<NameE>Rakhi</NameE>
				<MidNameE></MidNameE>
				<FamilyE>Issrani</FamilyE>
				<Organizations>
				<Organization>Department of Preventive Dentistry, College of Dentistry, Jouf University, Sakaka, Kingdom of Saudi Arabia.</Organization>
				</Organizations>
				<Countries>
				<Country></Country>
				</Countries>
				<EMAILS>
				<Email>dr.rakhi.issrani@jodent.org</Email>
				</EMAILS>
			</AUTHOR>
		</AUTHORS>


		<KEYWORDS>
			<KEYWORD>
				<KeyText>Cancer</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Immunonutrition</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Malnutrition</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Nutritional support</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Nano formulations</KeyText>
			</KEYWORD>

			<KEYWORD>
				<KeyText>Nutraceuticals</KeyText>
			</KEYWORD>
		</KEYWORDS>

		<REFRENCES>
			<REFRENCE>
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