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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Machine-learning-based prediction of disability progression in multiple sclerosis: an observational, international, multi-center study(Public Library of Science, 2024) De Brouwer, Edward; Becker, Thijs; Werthen-Brabants, Lorin; Dewulf, Pieter; Iliadis, Dimitrios; Dekeyser, Cathérine; Laureys, Guy; Van Wijmeersch, Bart; Popescu, Veronica; Dhaene, Tom; Deschrijver, Dirk; Waegeman, Willem; De Baets, Bernard; Stock, Michiel; Horakova, Dana; Patti, Francesco; Izquierdo, Guillermo; Eichau, Sara; Girard, Marc; Prat, Alexandre; Lugaresi, Alessandra; Grammond, Pierre; Kalincik, Tomas; Alroughani, Raed; Grand’Maison, Francois; Skibina, Olga; Terzi, Murat; Lechner-Scott, Jeannette; Gerlach, Oliver; Khoury, Samia J.; Cartechini, Elisabetta; Van Pesch, Vincent; Sà, Maria José; Weinstock-Guttman, Bianca; Blanco, Yolanda; Ampapa, Radek; Spitaleri, Daniele; Solaro, Claudio; Maimone, Davide; Soysal, Aysun; Iuliano, Gerardo; Gouider, Riadh; Castillo-Triviño, Tamara; Sánchez-Menoyo, José Luis; Laureys, Guy; van der Walt, Anneke; Oh, Jiwon; Aguera-Morales, Eduardo; Al-Asmi, Abdullah; de Gans, Koen; Fragoso, Yara; Csepany, Tunde; Hodgkinson, Suzanne; Deri, Norma; Al-Harbi, Talal; Taylor, Bruce; Gray, Orla; Lalive, Patrice; Rozsa, Csilla; McGuigan, Chris; Kermode, Allan; Sempere, Angel Pérez; Mihaela, Simu; Simo, Magdolna; Hardy, Todd; Decoo, Danny; Hughes, Stella; Grigoriadis, Nikolaos; Sas, Attila; Vella, Norbert; Moreau, Yves; Peeters, Liesbet; Altıntaş, Ayşe; ; School of Medicine;Background Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking. Methods Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS. Findings Machine learning models achieved a ROC-AUC of 0.71 ± 0.01, an AUC-PR of 0.26 ± 0.02, a Brier score of 0.1 ± 0.01 and an expected calibration error of 0.07 ± 0.04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history. Conclusions Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study. Copyright: © 2024 De Brouwer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Publication Metadata only Difficulties faced in standardized receptor stimulation and in standardized analysis of muscle responses to a stimulus(Springer international Publishing ag, 2017) Türker, Kemal Sıtkı; Faculty Member; School of Medicine; 6741This presentation will cover the methods used to investigate neuronal circuitries between peripheral receptors and skeletal muscles in human subjects. there are a number of problems regarding reflex studies using experimental animals. there are also problems in the recording and analysis aspects of these experiments. To overcome these problems we have utilized precisely-controlled mechanical or electrical stimuli to activate receptors and single motor units from human muscles. We also used classical and novel methods to analyze the results to indicate neuronal networks.Publication Metadata only Challenges of the nose-to-brain route(Academic Press Ltd-Elsevier Science Ltd, 2017) Şekerdağ, Emine; PhD Student; Graduate School of Health Sciences; N/AThe main goal for investigating new techniques for brain drug delivery is to improve and/or elevate treatment outcomes. Targeted nose-to-brain delivery is a potential noninvasive drug delivery technique with many benefits, such as optimized drug distribution, reduced side effects, and improved patient compliance. Despite the fact that transport mechanism of drugs administered nasally are not fully understood, this pathway is still under investigation by many research groups to optimize the search for evidence and/or improve the direct nose-to-brain route. The most important challenges are translating study designs and obtaining data. Furthermore, the low drug uptake by the brain and environmental tissues in the nasal cavity is an issue that needs to be overcome by the utilization of nanotechnology-based techniques, which incorporate drugs in nanoparticles and or other drug delivery systems.Publication Metadata only Jaw reflexes originating from the periodontal and muscle spindle receptors to the jaw muscles(Springer International Publishing Ag, 2017) Ugincius, P.; Yılmaz, Gizem; Türker, Kemal Sıtkı; PhD Student; Faculty Member; Graduate School of Health Sciences; School of Medicine; N/A; 6741We investigated the jaw reflexes using both the probability- and the discharge rate-based analysis methods. While recording the masseter muscle activity, computer controlled slow-rate "push" and rapid rate "tap" stimuli were delivered to the upper right central incisor before and during local anesthetic block. While preceding local anesthesia, the tap stimuli induced inhibitory reflex responses; during local anesthetic block, the same stimulus induced excitatory and inhibitory reflex responses. The push stimuli generated a combination of inhibitory and excitatory responses that disappeared during the local anesthetic block. We found that the discharge rate-based method was better for indicating the duration of earlier responses and the existence, sign, and duration of later responses.Publication Metadata only Trigeminal nerve stimulation: a recently approved treatment approach in attention deficit hyperactivity disorder(Springer, 2021) Çöpür, Mazlum; N/A; Çöpür, Sidar; Researcher; School of Medicine; 368625Attention-deficit hyperactivity disorder (ADHD) with its high prevalence is a growing area of concern and research, whereas exact underlying pathophysiology remains unknown. Behavioral therapy and multiple medications include methylphenidate, atomoxetine, and amphetamines while trigeminal nerve stimulator (TNS) is the first medical device in ADHD with FDA approval. The aim of this article is to evaluate the latest studies in this field.Publication Metadata only Stroke(Academic Press Inc Elsevier Science, 2017) N/A; N/A; Çakmak, Özgür Öztop; Vanlı-Yavuz, Ebru Nur; Özdemir, Yasemin Gürsoy; Faculty Member; Doctor; Faculty Member; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; School of Medicine; School of Medicine; N/A; Koç University Hospital; N/A; 299358; 251177; 170592Stroke is a devastating neurological disease with a few therapeutic approaches. Despite the acute and prophylactic treatment options, novel effective treatments are required. The main limitation for effective treatment strategies to be developed is the presence of the blood–brain barrier. Targeted nanoparticulate treatment options may help to overcome this issue. This chapter deals with novel studies performed for targeted drug delivery technologies for stroke.Publication Metadata only Nasal physiology and drug transport(academic Press Ltd-Elsevier Science Ltd, 2017) Şekerdağ, Emine; PhD Student; Graduate School of Health Sciences; N/AOnce a compound enters the nasal cavity, it can be navigated along several pathways. There is a chance for a drug to be: (1) rapidly cleared by the mucociliary mechanism, (2) absorbed and reach the systemic circulation (lipophilic compounds mostly), and (3) absorbed by the olfactory epithelium and reach the olfactory bulb. When a drug compound is cleared away in the nasal cavity, it is degraded by enzymes in the nasal mucus, which therefore interrupts the drug delivery to the target zone. A drug compound can also enter the systemic circulation and may effectively reach the target area followed by elimination from the blood by clearance mechanisms present throughout the body. In case of the latter, to reach the brain the drug has to bypass the BBB, which is an obstacle for most hydrophilic and/or large compounds. Moreover, once the compound passes through the BBB into the brain it can still be eliminated from the CSF back into the blood circulation. Furthermore, a drug compound entering the nasal cavity can also pass through the olfactory epithelium and reach the olfactory bulb, which can transport the drug into the brain without facing the BBB.Publication Metadata only Nanotechnology methods for neurological diseases and brain tumors drug delivery across the blood-brain barrier future outlook(Academic Press Inc Elsevier Science, 2017) Bozdağ Pehlivan, Sibel; Özdemir, Yasemin Gürsoy; Şekerdağ, Emine; Faculty Member; PhD Student; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; Graduate School of Health Sciences; 170592; N/AN/APublication Metadata only Tumor-to-tumor metastasis: lung adenocarcinoma into a clinically non-functioning gonadotroph pituitary adenoma: a rare case(Ege University, 2018) Sav, Aydin; Altinoz, Meric Adil; Rotondo, Fabio; Cykowski, Matthew; Kovacs, Kalman; N/A; Özer, Ali Fahir; Faculty Member; School of Medicine; 1022We report a rare case of a metastatic lung adenocarcinoma to a clinically non-functioning pituitary gonadotroph adenoma in a 66-year-old male experiencing progressive headaches and diminished vision. Magnetic resonance imaging revealed a large tumor containing cystic cavity and acute hemorrhagic areas in the sella turcica and extending into the suprasellar cistern. Pathologic examination was consistent with a metastasizing lung adenocarcinoma to a clinically non-functioning pituitary adenoma. Immunohistochemistry revealed both pituitary adenoma and metastatic adenocarcinoma containing FSH and LH immunoreactive cells in the pituitary adenoma whereas napsin A, TTF-1, cytokeratin7, Pancytokeratin and galectin-3 immunopositivity were evidenced by adenocarcinoma cells within sinusoids and around blood vessels. The patient underwent a transthoracic fine needle biopsy that was positive for adenocarcinoma (Napsin-A positive, p63 negative). It was therefore concluded that the primary site for the sellar metastasis was in the lung. Primary metastasis to pituitary gland is rare with the most common primary sites include lung, breast, kidney and the gastrointestinal tract. Although rare, any case with progressive local pressure symptoms and endocrinologic stigmata with or without other signs of malignancy requires further examination to rule out pituitary metastasis.Publication Metadata only Expanding PRDX3 disease: broad range of onset age and infratentorial MRI signal changes(Oxford Univ Press, 2022) Rebelo, Adriana P.; Bender, Benjamin; Haack, Tobias B.; Zuchner, Stephan; Basak, A. Nazli; Synofzik, Matthis; N/A; Başak, Ayşe Nazlı; Faculty Member; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); School of Medicine; 1512N/A