Academic literature on the topic 'Disease'
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Journal articles on the topic "Disease"
Shanmugam, Sriram, Jaean Kennady, and Jaleel Ahamed. "A CASE STUDY ON WILSON'S DISEASE." International Journal of Medical Reviews and Case Reports 2, Reports in Surgery and Dermatolo (2019): 1. http://dx.doi.org/10.5455/ijmrcr.wilson-disease.
Full textLimpert, E., and P. Bartoš. "Wind-Dispersed Nomadic Diseases: Conclusions for Disease Resistance." Czech Journal of Genetics and Plant Breeding 38, No. 3-4 (August 1, 2012): 150–52. http://dx.doi.org/10.17221/6256-cjgpb.
Full textDehuri, Priyadarshini, Debasis Gochhait, Debdatta Basu, and Neelaiah Siddaraju. "Rosai-Dorfman Disease: An Imposter of Plasma Cell Rich Diseases." Annals of Pathology and Laboratory Medicine 2, no. 12 (December 17, 2018): C178–181. http://dx.doi.org/10.21276/apalm.2102.
Full textNakashima, Tsutomu, Koichi Tsuzuki, and Kishiko Sugiyama. "Menière’s Disease or Ménière’s Disease or Meniere’s Disease?" Practica Oto-Rhino-Laryngologica 111, no. 1 (2018): 75–77. http://dx.doi.org/10.5631/jibirin.111.75.
Full textL Pathan, Fayaj. "Nonalcoholic Fatty Liver Disease (NAFLD) A Chronic Liver Disease." Acta Scientifci Nutritional Health 4, no. 1 (December 9, 2019): 58. http://dx.doi.org/10.31080/asnh.2020.04.nonalcoholic-fatty-liver-disease-nafld-a-chronic-liver-disease.
Full textAlthaf, Shebin, Manoj Khanal, Anita Rawat, and Kishalay Datta. "Devic’s Disease: The Confusing CNS Disease." Indian Journal of Emergency Medicine 9, no. 3 (September 15, 2023): 107–9. http://dx.doi.org/10.21088/ijem.2395.311x.9323.10.
Full textHananeh, W., and M. Ababneh. "Spotty liver disease in Jordan: An emerging disease." Veterinární Medicína 66, No. 3 (March 2, 2021): 94–98. http://dx.doi.org/10.17221/73/2020-vetmed.
Full textVerma, Dr Amit Kumar. "Periodontal Disease with Diabetes or Diabetes Kidney Disease." International Journal of Trend in Scientific Research and Development Volume-3, Issue-1 (December 31, 2018): 1043–51. http://dx.doi.org/10.31142/ijtsrd19176.
Full textITABASHI, Mizuo. "Eponymic Diseases (1): Topics of Takayasu Disease, Hashimoto Disease and Kawasaki Disease." Igaku Toshokan 41, no. 3 (1994): 313–18. http://dx.doi.org/10.7142/igakutoshokan.41.313.
Full textDassy, Cylia, Manou Saramba, and Dongchi Zhao. "Treatment Options for Complications of Sickle-cell Disease in Children." International Journal of Medical Reviews and Case Reports 4, Reports in Microbiology, Infecti (2020): 1. http://dx.doi.org/10.5455/ijmrcr.sickle-cell-disease-children.
Full textDissertations / Theses on the topic "Disease"
Franco, Iborra Sandra. "Mitochondrial quality control in neurodegenerative diseases: focus on Parkinson’s disease and Huntington’s disease." Doctoral thesis, Universitat Autònoma de Barcelona, 2018. http://hdl.handle.net/10803/565668.
Full textIn the past years, several important advances have expanded our understanding of the pathways that lead to cell dysfunction and death in Parkinson’s disease (PD) and Huntington’s disease (HD). Both diseases are movement disorders characterized by the loss of a specific subset of neurons within the basal ganglia, dopaminergic neurons in the substantia nigra pars compacta (SNpc), in the case of PD, and medium spiny neurons in the striatum, in the case of HD,. Despite distinct clinical and pathological features, these two neurodegenerative disorders share critical underlying pathogenic mechanisms such as the presence of misfolded and/or aggregated proteins, oxidative stress and mitochondrial anomalies. Mitochondria are the prime energy source in most eukaryotic cells, but these highly dynamic organelles are also involved in a multitude of cellular events. Disruption of mitochondrial homeostasis and the subsequent mitochondrial dysfunction plays a key role in the pathophysiology of neurodegenerative diseases. Therefore, maintenance of mitochondrial integrity through different surveillance mechanisms is critical for neuronal survival. In this thesis I have studied in depth some mitochondrial quality control mechanisms in the context of PD and HD, in order to broaden the knowledge about the pathomechanisms leading to cell death. In the first chapter I have studied mitochondrial protein import in in vitro and in vivo models of PD. In vitro, complex I inhibition, a characteristic pathological hallmark in PD, impaired mitochondrial protein import. This was associated with OXPHOS protein downregulation, accumulation of aggregated proteins inside mitochondria and downregulation of mitochondrial chaperones. Therefore, we aimed to reestablish the mitochondrial protein import by overexpressing two key components of the system: translocase of the outer membrane 20 (TOM20) and translocase of the inner membrane 23 (TIM23). Overexpression of TOM20 and TIM23 in vitro restored protein import into mitochondria and ameliorated mitochondrial dysfunction and cell death. Complex I inhibition also impaired mitochondrial protein import and led to dopaminergic neurodegeneration in vivo. Overexpression of TIM23 partially rescued protein import into mitochondria and slightly protected dopaminergic neurons in the SNpc. On the contrary, TOM20 overexpression did not rescue protein import into mitochondria and exacerbated neurodegeneration in both SNpc and striatum. These results highlight mitochondrial protein import dysfunction and the distinct role of two of their components in the pathogenesis of PD and suggest the need for future studies to target other elements in the system. In the second chapter, I have studied the role of huntingtin in mitophagy and how the polyglutamine expansion present in mutant huntingtin can affect its function. For such, I worked with differentiated striatal ST-Q7 (as control) and ST-Q111 (as mutant) cells, expressing full length huntingtin. In these conditions, induced mitophagy was not mediated by Parkin recruitment into depolarized mitochondria. Mutant huntingtin impaired induced mitophagy by altering wildtype huntingtin scaffolding activity at different steps of mitophagy process: (i) ULK1 activation through its release from the mTORC1, (ii) Beclin1-Vps15 complex formation, (iii) interaction of the mitophagy adapters OPTN and NDP52 with huntingtin and (iv) with LC3. As a result, mitochondria from ST-Q111 cells exhibited increased damage and altered mitochondrial respiration. These results uncover impaired mitophagy as a potential pathological mechanism linked with HD. In conclusion, we have discovered new mitochondrial targets for PD and HD emphasizing the important role that mitochondrial quality control plays in neurodegeneration
Mekaru, Sumiko Rachel. "Environmental risk factors in infectious diseases: studies in waterborne disease outbreaks, Ebola, and Lyme disease." Thesis, Boston University, 2013. https://hdl.handle.net/2144/11144.
Full textThe resurgence of infectious diseases and global climate change's potential impact on them has refocused public health's attention on the environment's role in infectious disease. The studies in this dissertation utilize the increased availability of satellite image-derived data sets with fine temporal and geographic granularity and the expansion of epidemiologic methods to explore the relationship between the environment and infectious disease in three settings. The first study employed a novel study design and analytic methods to investigate the hypothesis that heavy rainfall is an independent risk factor for waterborne disease outbreaks (WBDOs). We found that a location experiencing a heavy rainfall event had about half the odds of a WBDO two or four weeks later than did a location without a heavy rainfall event. The location-based case-crossover study design utilized in this study may help to expand the research methods available to epidemiologists working in this developing field. The second study employed a location-based case-crossover study design to evaluate standardized differences from historic average of weekly rainfall in locations with a recorded introduction of Ebola into a human. For each 1.0 unit z-score decrease in total rainfall, the odds of an Ebola introduction three weeks later increased by 75%. Given the severity of Ebola outbreaks and the dearth of knowledge about indicators of increased risk, this finding is an important step in advancing our understanding of Ebola ecology. The third study used GIS methods on remote sensing data to estimate the association between peridomestic forest/non-forest interface within 100, 150, 250 meters and Lyme-associated peripheral facial palsy (LAPFP) among pediatric facial palsy patients. After adjustment for sex, age, and socio-economic status, children with the highest level of forest edge in the three radii of analysis had 2.74 (95% CI 1.15, 6.53), 4.58 (1.84, 11.41), and 5.88 (2.11, 16.4) times the odds of LAPFP compared to children with zero forest edge in those radii. This study is the first to examine environmental risk factors for LAPFP. Each of these studies advances the techniques used to investigate environmental risk factors for infectious disease through study design, case definition, data used, or exposure definitions.
Pietravalle, SteÌphane. "Modelling weather/disease relationships in winter wheat diseases." Thesis, University of Reading, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402602.
Full textHaslam, Bryan (Bryan Todd). "Learning diseases from data : a disease space odyssey." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/114002.
Full textCataloged from PDF version of thesis.
Includes bibliographical references (pages 253-280).
Recent commitments to enhance the use of data for learning in medicine provide the opportunity to apply instruments and abstractions from computational learning theory to systematize learning in medicine. The hope is to accelerate the rate at which we incorporate knowledge and improve healthcare quality. In this thesis, we work to bring further clarity to the ways in which computational learning theory can be applied to update the collective knowledge about diseases. Researchers continually study and learn about the complex nature of the human body. They summarize this knowledge with the best possible set of diseases and how those diseases relate to each other. We draw on computational learning theory to understand and broaden this form of collective learning. This mode of collective learning is regarded as unsupervised learning, as no disease labels are initially available. In unsupervised learning, variance is typically reduced to find an optimal function to organize the data. A significant challenge that remains is how to measure variance in the definition of diseases in a comprehensive way. Variance in the definition of a disease introduces a systematic error in both basic and clinical research. If measured, it would also be possible to use computers to efficiently minimize variance, providing a great opportunity for learning by utilizing medical data. In this thesis, we demonstrate that it is possible to estimate variance in the disease taxonomy, effectively estimating an error bar for the current definitions of diseases. We do so using the history of the disease taxonomy and comparing it with a variety of external data sets that relate diseases to attributes such as symptoms, drugs and genes. We demonstrate that variance can be significant over relatively short time periods. We further present methods for updating the disease taxonomy by reducing variance based on external disease data sets. This makes it possible to automatically incorporate information contained in disease data sets into the disease taxonomy. The approach also makes it possible to use expert information encoded in the taxonomy to systematically transfer knowledge and update other biomedical data sets that are often sparse (e.g. - symptoms associated with diseases). A natural question stemming from these results is how granular does data need to be to make improvements? For instance, is patient-level data necessary to enable learning at the macro level of disease? Or are there strategies to extract information from other kinds of data to alleviate the need for very granular data. We show that detailed, patient-level data is not necessarily needed to extract detailed biological data. We do so by comparing disease relationships learned from clinical trial metadata to disease relationships learned from a detailed genetic database and show we can achieve similar results. This result shows that we can use currently available data and take advantage of computational learning to improve disease learning, which suggests a new avenue to improving patient outcomes. By reducing variance within diseases using data available today, we can quickly update the space of diseases to be more precise. Precise diseases lead to better learning in other areas of medicine and ultimately improved healthcare quality.
by Bryan Haslam.
Ph. D.
Guallar-Hoyas, Cristina. "Prospecting for markers of disease in respiratory diseases." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/12415.
Full textGeorge, Charles Raymond Pax. "Disease Explicated And Disease Defined." Thesis, The University of Sydney, 2005. http://hdl.handle.net/2123/654.
Full textGeorge, Charles Raymond Pax. "Disease Explicated And Disease Defined." University of Sydney. History and Philosophy of Science, 2005. http://hdl.handle.net/2123/654.
Full textMancini, Sabrina. "Assessment of a screening test for MMP-8 activity in the diagnosis of periodontal diseases." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0028/MQ40755.pdf.
Full textGu, Mei. "Mitochondrial function in Parkinson's disease and other neurodegenerative diseases." Thesis, University College London (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322371.
Full textUllah, Naseem. "Disease modules identification in heterogenous diseases with WGCNA method." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-16692.
Full textBooks on the topic "Disease"
Filer, Joyce. Disease. London, UK: British Museum Press, 1995.
Find full textFiler, Joyce. Disease. Austin: University of Texas Press, 1996.
Find full textRidley, Matt. Disease. London: Phoenix, 1997.
Find full text1943-, Stein Mark R., ed. Gastroesophageal reflux disease and airway disease. New York: Marcel Dekker, 1999.
Find full textMulder, Chris J. J., and Guido N. J. Tytgat, eds. Is Crohn’s Disease a Mycobacterial Disease? Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-1830-9.
Full textJ, Mulder C. J., and Tytgat G. N. J, eds. Is Crohn's disease a mycobacterial disease? Dordrecht: Kluwer Academic Publishers, 1992.
Find full textLLC, National Health Information, ed. Heart disease: Disease management strategies & programs. Atlanta, GA: National Health Information, 2005.
Find full textR, Nichols, ed. Mycoplasma diseases of ruminants: Disease, diagnosis and control. Wallingford: CABI, 2006.
Find full textWerker, Paul M. N., Joseph Dias, Charles Eaton, Bert Reichert, and Wolfgang Wach, eds. Dupuytren Disease and Related Diseases - The Cutting Edge. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-32199-8.
Full textMonette, P. L. Grape diseases: Corky bark disease and stem pitting. Toronto, Ont: Ministry of Agriculture and Food, 1993.
Find full textBook chapters on the topic "Disease"
Weis, Serge, Michael Sonnberger, Andreas Dunzinger, Eva Voglmayr, Martin Aichholzer, Raimund Kleiser, and Peter Strasser. "Neurodegenerative Diseases: Parkinson Disease." In Imaging Brain Diseases, 1001–20. Vienna: Springer Vienna, 2019. http://dx.doi.org/10.1007/978-3-7091-1544-2_37.
Full textWeis, Serge, Michael Sonnberger, Andreas Dunzinger, Eva Voglmayr, Martin Aichholzer, Raimund Kleiser, and Peter Strasser. "Neurodegenerative Diseases: Huntington Disease." In Imaging Brain Diseases, 1059–68. Vienna: Springer Vienna, 2019. http://dx.doi.org/10.1007/978-3-7091-1544-2_40.
Full textGregori, Maria, and Francesca Re. "Neurodegenerative Diseases - Alzheimer's Disease." In Pharmaceutical Nanotechnology: Innovation and Production, 649–60. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2016. http://dx.doi.org/10.1002/9783527800681.ch27.
Full textTamma, Filippo. "Extrapyramidal Diseases: Parkinson’s Disease." In Prognosis of Neurological Diseases, 363–68. Milano: Springer Milan, 2015. http://dx.doi.org/10.1007/978-88-470-5755-5_28.
Full textValzania, Franco. "Extrapyramidal Diseases: Huntington’s Disease." In Prognosis of Neurological Diseases, 375–79. Milano: Springer Milan, 2015. http://dx.doi.org/10.1007/978-88-470-5755-5_30.
Full textKenanidis, Eustathios, Andreas Leonidou, Michael Potoupnis, Eleftherios Tsiridis, Aristotelis Kourtis, and Richard P. Baker. "Neurologic Diseases: Parkinson’s Disease." In The Adult Hip - Master Case Series and Techniques, 327–37. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-64177-5_11.
Full textMuñoz, Melissa, Elizabeth Cieniewicz, and James E. Faust. "Diseases and disease management." In Cut flowers and foliages, 258–315. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789247602.0006.
Full textWeis, Serge, Michael Sonnberger, Andreas Dunzinger, Eva Voglmayr, Martin Aichholzer, Raimund Kleiser, and Peter Strasser. "Neurodegenerative Diseases: Alzheimer Disease (AD)." In Imaging Brain Diseases, 897–931. Vienna: Springer Vienna, 2019. http://dx.doi.org/10.1007/978-3-7091-1544-2_32.
Full textKanki, Phyllis J. "Infectious Diseases infectious disease , Introduction." In Encyclopedia of Sustainability Science and Technology, 5378–82. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-0851-3_927.
Full textChen, Yen-Ping, Chao-Fang Yu, and Yu-Hua Shih. "Duck Diseases and Disease Management." In Duck Production and Management Strategies, 549–79. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6100-6_14.
Full textConference papers on the topic "Disease"
Olshevskaya, A. V., M. Yu Gapon, N. V. Gapon, M. M. Zhdanova, A. T. Rybak, A. V. Vershinina, S. A. Marchenko, A. E. Аzhinov, and D. V. Rudoy. "RECOGNITION OF THE STATE OF CROPS USING NEURAL NETWORK MONITORING TOOLS." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. ООО «ДГТУ-Принт» Адрес полиграфического предприятия: 344003, г. Ростов-на-Дону, пл. Гагарина,1., 2024. http://dx.doi.org/10.23947/interagro.2024.115-118.
Full textCollar, Giovanna Carello, Marco Antônio De Bastiani, and Eduardo R. Zimmer. "HUNTINGTON’S DISEASE AND EARLYONSET ALZHEIMER’S DISEASE SHARE A TRANSCRIPTOMIC SIGNATURE." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda082.
Full text"Skin Disease Classification Using Deep Learning CNN." In The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/ngnt7820/ngcesi23p151.
Full textHELIALDO SOUSA DE OLIVEIRA FILHO, FRANCISCO, PRISCILA DOURADO EVANGELISTA, PRISCILA GARCIA CÂMARA CABRAL TAVARES, LUIZ VALÉRIO COSTA VASCONCELOS, MARINA PINTO ROCHA, ANA CAROLINA CAVALCANTE MENDONÇA, ADAH SOPHIA RODRIGUES VIEIRA, et al. "LEPROSY: INFECTIOUS DISEASE MIMICKING RHEUMATIC DISEASES." In SBR 2021 Congresso Brasileiro de Reumatologia. Sociedade Brasileiro de Reumatologia, 2021. http://dx.doi.org/10.47660/cbr.2021.1806.
Full textGómez, Carlota, Irene Jimeno, Leonardo De la Torre, and Monika Wozniak. "VISIBILIZING INVISIBLE DISEASES: FACE CHAGAS DISEASE." In 11th International Conference on Education and New Learning Technologies. IATED, 2019. http://dx.doi.org/10.21125/edulearn.2019.0932.
Full textP., Deepthi, Dhinakaran M., and Yoganapriya R. "Fruit Disease Detection Using Image Processing." In The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/bfbm3617/ngcesi23p87.
Full textSandeep Kumar, S., and Usha Divakarla. "Mulberry Leaves Diseases and Disease Identification Techniques." In 2023 International Conference on Integrated Intelligence and Communication Systems (ICIICS). IEEE, 2023. http://dx.doi.org/10.1109/iciics59993.2023.10421635.
Full textHu, Yaojun, Jintai Chen, Lianting Hu, Dantong Li, Jiahuan Yan, Haochao Ying, Huiying Liang, and Jian Wu. "Personalized Heart Disease Detection via ECG Digital Twin Generation." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/649.
Full textGuelli, Mariana Sandoval Terra Campos, Daniela Bastos de Almeida Zampier, Lorena Araújo Silva Dias, and Marina de Oliveira Nunes Ibrahim. "Creutzfeldt-Jakob Disease - a literature review." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.126.
Full textGreenstein, Vivienne C., and Donald C. Hood. "A Test of the Decreased Responsiveness Hypothesis in Retinitis Pigmentosa." In Noninvasive Assessment of Visual Function. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/navf.1985.tua2.
Full textReports on the topic "Disease"
Del Valle, Sara. Disease Precognition. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1812633.
Full textOster, Emily. Does Disease Cause Vaccination? Disease Outbreaks and Vaccination Response. Cambridge, MA: National Bureau of Economic Research, July 2016. http://dx.doi.org/10.3386/w22464.
Full textZhao, Junyu, Yutian Tian, Haipeng Wang, Jinming Yao, Wang Song, and Yaru Mou. Thyroid diseases are associated with coronavirus disease 2019 (COVID-19) infection. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2021. http://dx.doi.org/10.37766/inplasy2021.9.0079.
Full textEvans, Celia A., Jennifer A. Lucas, and Mark J. Twery. Beech Bark Disease: Proceedings of the Beech Bark Disease Symposium. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station, 2005. http://dx.doi.org/10.2737/ne-gtr-331.
Full textLi, Jiawang, Xiangyun Chen, Hongrui Zhang, Wei Ding, Danni Chen, Ning Liang, Haiying Tong, Zhenhong Liu, and Zhen Yang. A Systematic Review of the Capsaicin and other TRPV1 agonists effects on three neurodegenerative diseases: Alzheimer's disease, Parkinson's disease and Ischemic Stroke. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, April 2024. http://dx.doi.org/10.37766/inplasy2024.4.0115.
Full textKostoff, Ronald N. Literature-Related Discovery: Common Factors for Parkinson's Disease and Crohn's Disease. Fort Belvoir, VA: Defense Technical Information Center, January 2010. http://dx.doi.org/10.21236/ada525269.
Full textSomerville, Shauna C. Powdery Mildew Disease Resistance. Office of Scientific and Technical Information (OSTI), August 2010. http://dx.doi.org/10.2172/1123169.
Full textPellegrino, Bruno, and Luigi Zingales. Diagnosing the Italian Disease. Cambridge, MA: National Bureau of Economic Research, October 2017. http://dx.doi.org/10.3386/w23964.
Full textLicht, Mark A., and Wayne B. Roush. Insects and Disease Update. Ames: Iowa State University, Digital Repository, 2010. http://dx.doi.org/10.31274/farmprogressreports-180814-112.
Full textLicht, Mark A., Joel L. DeJong, and Wayne B. Roush. Insects and Disease Update. Ames: Iowa State University, Digital Repository, 2011. http://dx.doi.org/10.31274/farmprogressreports-180814-1248.
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