{"title":"Olfactory Dysfunction as a Clinical Marker of Early Glymphatic Failure in Neurodegenerative Diseases.","authors":"Gonzalo Sánchez-Benavides, Alex Iranzo, Oriol Grau-Rivera, Darly Milena Giraldo, Mariateresa Buongiorno","doi":"10.3390/diagnostics15060719","DOIUrl":"10.3390/diagnostics15060719","url":null,"abstract":"<p><p>An abnormal accumulation of misfolded proteins is a common feature shared by most neurodegenerative disorders. Olfactory dysfunction (OD) is common in the elderly population and is present in 90% of patients with Alzheimer's or Parkinson's disease, usually preceding the cognitive and motor symptoms onset by several years. Early Aβ, tau, and α-synuclein protein aggregates deposit in brain structures involved in odor processing (olfactory bulb and tract, piriform cortex, amygdala, entorhinal cortex, and hippocampus) and seem to underly OD. The glymphatic system is a glial-associated fluid transport system that facilitates the movement of brain fluids and removes brain waste during specific sleep stages. Notably, the glymphatic system became less functional in aging and it is impaired in several conditions, including neurodegenerative diseases. As the nasal pathway has been recently described as the main outflow exit of cerebrospinal fluid and solutes, we hypothesized that OD may indeed be a clinical marker of early glymphatic dysfunction through abnormal accumulation of pathological proteins in olfactory structures. This effect may be more pronounced in peri- and postmenopausal women due to the well-documented impact of estrogen loss on the locus coeruleus, which may disrupt multiple mechanisms involved in glymphatic clearance. If this hypothesis is confirmed, olfactory dysfunction might be considered as a clinical proxy of glymphatic failure in neurodegenerative diseases.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060714
Teng-Li Lin, Riya Karmakar, Arvind Mukundan, Sakshi Chaudhari, Yu-Ping Hsiao, Shang-Chin Hsieh, Hsiang-Chen Wang
{"title":"Assessing the Efficacy of the Spectrum-Aided Vision Enhancer (SAVE) to Detect Acral Lentiginous Melanoma, Melanoma In Situ, Nodular Melanoma, and Superficial Spreading Melanoma: Part II.","authors":"Teng-Li Lin, Riya Karmakar, Arvind Mukundan, Sakshi Chaudhari, Yu-Ping Hsiao, Shang-Chin Hsieh, Hsiang-Chen Wang","doi":"10.3390/diagnostics15060714","DOIUrl":"10.3390/diagnostics15060714","url":null,"abstract":"<p><p><b>Background:</b> Melanoma, a highly aggressive form of skin cancer, necessitates early detection to significantly improve survival rates. Traditional diagnostic techniques, such as white-light imaging (WLI), are effective but often struggle to differentiate between melanoma subtypes in their early stages. <b>Methods:</b> The emergence of the Spectrum-Aided Vison Enhancer (SAVE) offers a promising alternative by utilizing specific wavelength bands to enhance visual contrast in melanoma lesions. This technique facilitates greater differentiation between malignant and benign tissues, particularly in challenging cases. In this study, the efficacy of the SAVE is evaluated in detecting melanoma subtypes including acral lentiginous melanoma (ALM), melanoma in situ (MIS), nodular melanoma (NM), and superficial spreading melanoma (SSM) compared to WLI. <b>Results:</b> The findings demonstrated that the SAVE consistently outperforms WLI across various key metrics, including precision, recall, F1-scorw, and mAP, making it a more reliable tool for early melanoma detection using the four different machine learning methods YOLOv10, Faster RCNN, Scaled YOLOv4, and YOLOv7. <b>Conclusions:</b> The ability of the SAVE to capture subtle spectral differences offers clinicians a new avenue for improving diagnostic accuracy and patient outcomes.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941011/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060716
Nadav Dekel, Ekaterina Laukhtina, Andrey Morozov, Eva Compérat, Eddie Fridman, Shay Golan, Jeremy Yuen-Chun Teoh, Yossef Molchanov, Maxim Yakimov, Thomas R W Herrmann, Dmitry Pushkar, Jesús Moreno Sierra, Juan Gómez Rivas, Shahrokh F Shariat, Dmitry Enikeev
{"title":"The Role of Morcellation in En Bloc Resection of Large Bladder Tumors.","authors":"Nadav Dekel, Ekaterina Laukhtina, Andrey Morozov, Eva Compérat, Eddie Fridman, Shay Golan, Jeremy Yuen-Chun Teoh, Yossef Molchanov, Maxim Yakimov, Thomas R W Herrmann, Dmitry Pushkar, Jesús Moreno Sierra, Juan Gómez Rivas, Shahrokh F Shariat, Dmitry Enikeev","doi":"10.3390/diagnostics15060716","DOIUrl":"10.3390/diagnostics15060716","url":null,"abstract":"<p><p><b>Background/Objectives</b>: Conventional transurethral resection of bladder tumor (TURBT) for non-muscle invasive bladder cancer (NMIBC) is usually performed in a piecemeal manner, leading to difficulties in accurate pathological assessment. En bloc resection of bladder tumor (ERBT) has been developed to address these limitations, offering improved specimen quality. So far, ERBT has been restricted to small bladder tumors due to difficulties in en bloc extraction of large ones (>3 cm). Recently, the morcellation technique has been proposed to facilitate the removal of large bladder tumors during ERBT. This narrative review aims to evaluate the feasibility of ERBT with subsequent morcellation for large bladder tumors, focusing on its role in tumor extraction and its impact on pathological assessment. <b>Methods</b>: A comprehensive literature search was conducted across multiple databases to identify studies evaluating the use of morcellation in ERBT for large bladder tumors. Inclusion criteria comprised studies reporting recurrence rates, detrusor muscle (DM) presence in pathological specimens, and perioperative complications. Additionally, we offered uropathologists a questionnaire to gather their perspectives on the use of morcellation following ERBT, focusing on its impact on pathological assessment, margin evaluation, and staging accuracy. <b>Results</b>: While there is limited evidence on the use of morcellation in ERBT for tumors larger than 3 cm and its impact on oncologic outcomes, morcellation has shown potential in facilitating the retrieval of large tumor specimens, ensuring clear resection margins and accurate staging. However, the learning curve for morcellation techniques and the need for specialized equipment may limit widespread adoption. <b>Conclusions</b>: Morcellation in ERBT for large bladder tumors represents a promising advancement in the management of these challenging cases, offering adequate pathological assessment and oncologic outcomes. Pathologists' reviews of morcellated specimens will likely further validate the technique. Continued research and technological innovations are necessary to optimize its implementation in clinical practice.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11940964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060722
Mónica López-Redondo, Juan Antonio Valera-Calero, Javier Álvarez-González, Alberto Roldán-Ruiz, Sandra Sánchez-Jorge, Jorge Buffet-García, Germán Monclús-Díez, Davinia Vicente-Campos
{"title":"Reliability of Shear Wave Elastography for Measuring the Elastic Properties of the Quadratus Lumborum Muscle.","authors":"Mónica López-Redondo, Juan Antonio Valera-Calero, Javier Álvarez-González, Alberto Roldán-Ruiz, Sandra Sánchez-Jorge, Jorge Buffet-García, Germán Monclús-Díez, Davinia Vicente-Campos","doi":"10.3390/diagnostics15060722","DOIUrl":"10.3390/diagnostics15060722","url":null,"abstract":"<p><p><b>Background/Objectives</b>: The quadratus lumborum (QL) muscle is a key structure involved in patients with low back pain (LBP). Since the discriminative capability of morphological descriptors is uncertain and considering the high prevalence of myofascial trigger points and the poor reliability of manual palpation in this condition, developing a reliable procedure for assessing the QL's tenderness is needed for facilitating the diagnosis and monitoring changes over time. We aimed to analyze the intra- and inter-examiner reliability of SWE for calculating the QL tenderness in patients with LBP. <b>Methods</b>: Using a convex transducer, longitudinal shear wave elastography (SWE) images of the QL muscle were acquired bilaterally twice in 52 volunteers with moderate LBP and disability by one experienced examiner and one novel examiner to measure shear wave speed and Young's modulus as stiffness metrics. <b>Results</b>: Intra-examiner reliability estimates demonstrated high consistency independently of the examiner's experience (intraclass correlation coefficients (ICCs) > 0.930) for both metrics. However, experienced examiners showed smaller minimal detectable changes. Additionally, inter-examiner reliability was lower, with ICCs ranging from 0.57 to 0.68, and significant differences in mean values between examiners (<i>p</i> < 0.01) were found. <b>Conclusions</b>: This procedure exhibited excellent intra-examiner reliability for assessing QL muscle stiffness in patients suffering LBP, indicating high repeatability of measurements when performed by the same examiner. In addition, experienced examiners demonstrated greater sensitivity in detecting real changes not attributed to measurement errors. However, inter-examiner reliability was moderate, highlighting the need for consistent examiner use to avoid measurement variability and averaging multiple measurements to enhance the accuracy.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11940973/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060721
Fernando Gil-Lopez, Fausto Alfredo Rios-Olais, Lydia A Mercado, Denise M Harnois
{"title":"Portal Vein Thrombosis in Patients Without Cirrhosis: Current Practical Approaches and Treatment Strategies.","authors":"Fernando Gil-Lopez, Fausto Alfredo Rios-Olais, Lydia A Mercado, Denise M Harnois","doi":"10.3390/diagnostics15060721","DOIUrl":"10.3390/diagnostics15060721","url":null,"abstract":"<p><p>Portal vein thrombosis in non-cirrhotic individuals, although uncommon, is an increasingly explored condition that affects mainly young people, consequently representing a significant disease burden. Reports primarily including western European populations have recently shed light regarding the pathophysiology, risk factors, natural history, treatment, and prognosis of this entity. Underlying predisposing conditions are documented in ~70% of cases, encompassing local risk factors, inherited and acquired thrombophilia, cancer, and systemic inflammatory conditions. Non-cirrhotic portal vein thrombosis can cause significant portal hypertension in the acute setting, but, more frequently, significant portal hypertension-related complications arise when the condition becomes chronic and portosystemic collaterals develop, increasing the risk for variceal bleeding and ascites. The diagnostic approach to screen for underlying thrombophilia remains a challenge, and recommendations in this regard, although scarce and backed by scarce evidence, have changed notably in the last years, leaning toward a universal screen in patients who develop this condition without a clear provoking factor. Recently, studies have shown that long-term anticoagulation may be appropriate even in the absence of clear provoking factors or underlying thrombophilia. Future studies should address which patients may benefit from this approach, which patients may not need it, and what the most appropriate strategies are to approach patients who do not recover portal vein patency with anticoagulation to further prevent portal hypertension-related complications.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060718
Lama A Aldakhil, Shuaa S Alharbi, Abdulrahman Aloraini, Haifa F Alhasson
{"title":"Leveraging Attention-Based Deep Learning in Binary Classification for Early-Stage Breast Cancer Diagnosis.","authors":"Lama A Aldakhil, Shuaa S Alharbi, Abdulrahman Aloraini, Haifa F Alhasson","doi":"10.3390/diagnostics15060718","DOIUrl":"10.3390/diagnostics15060718","url":null,"abstract":"<p><p><b>Background:</b> Breast cancer diagnosis is a global health challenge, requiring innovative methods to improve early detection accuracy and efficiency. This study investigates the integration of attention-based deep learning models with traditional machine learning (ML) methods to classify histopathological breast cancer images. Specifically, the Efficient Channel-Spatial Attention Network (ECSAnet) is utilized, optimized for binary classification by leveraging advanced attention mechanisms to enhance feature extraction across spatial and channel dimensions. <b>Methods:</b> Experiments were conducted using the BreakHis dataset, which includes histopathological images of breast tumors categorized as benign or malignant across four magnification levels: 40×, 100×, 200×, and 400×. ECSAnet was evaluated independently and in combination with traditional ML models, such as Decision Trees and Logistic Regression. The study also analyzed the impact of magnification levels on classification accuracy, robustness, and generalization. <b>Results:</b> Lower magnification levels consistently outperformed higher magnifications in terms of accuracy, robustness, and generalization, particularly for binary classification tasks. Additionally, combining ECSAnet with traditional ML models improved classification performance, especially at lower magnifications. These findings highlight the diagnostic strengths of attention-based models and the importance of aligning magnification levels with diagnostic objectives. <b>Conclusions:</b> This study demonstrates the potential of attention-based deep learning models, such as ECSAnet, to improve breast cancer diagnostics when integrated with traditional ML methods. The findings emphasize the diagnostic utility of lower magnifications and provide a foundation for future research into hybrid architectures and multimodal approaches to further enhance breast cancer diagnosis.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941347/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060715
Trevor Winger, Cagri Ozdemir, Shanti L Narasimhan, Jaideep Srivastava
{"title":"Time-Adaptive Machine Learning Models for Predicting the Severity of Heart Failure with Reduced Ejection Fraction.","authors":"Trevor Winger, Cagri Ozdemir, Shanti L Narasimhan, Jaideep Srivastava","doi":"10.3390/diagnostics15060715","DOIUrl":"10.3390/diagnostics15060715","url":null,"abstract":"<p><p><b>Background:</b> Heart failure with reduced ejection fraction is a complex condition that necessitates adaptive, patient-specific management strategies. This study aimed to evaluate the effectiveness of a time-adaptive machine learning model, the Passive-Aggressive classifier, in predicting heart failure with reduced ejection fraction severity and capturing individualized disease progression. <b>Methods:</b> A time-adaptive Passive-Aggressive classifier was employed, using clinical data and Brain Natriuretic Peptide levels as class designators for heart failure with reduced ejection severity. The model was personalized for individual patients by sequentially incorporating clinical visit data from 0-9 visits. The model's adaptability and effectiveness in capturing individual health trajectories were assessed using accuracy and reliability metrics as more data were added. <b>Results:</b> With the progressive introduction of patient-specific data, the model demonstrated significant improvements in predictive capabilities. By incorporating data from nine visits, significant gains in accuracy and reliability were achieved, with the One-Versus-Rest AUC increasing from 0.4884 with no personalization (zero visits) to 0.8253 (nine visits). This demonstrates the model's ability to handle diverse patient presentations and the dynamic nature of disease progression. <b>Conclusions:</b> The findings show the potential of time-adaptive machine learning models, particularly the Passive-Aggressive classifier, in managing heart failure with reduced ejection fraction and other chronic diseases. By enabling precise, patient-specific predictions, these approaches support early detection, tailored interventions, and improved long-term outcomes. This study highlights the feasibility of integrating adaptive models into clinical workflows to enhance the management of heart failure with reduced ejection fraction and similar chronic conditions.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060723
Andrew Macnab, Lynn Stothers
{"title":"Upright Open MRI (MRO) Evaluation of the Anatomic Effects of Yoga Postures on the Bladder Neck and Urethra.","authors":"Andrew Macnab, Lynn Stothers","doi":"10.3390/diagnostics15060723","DOIUrl":"10.3390/diagnostics15060723","url":null,"abstract":"<p><p><b>Background/Objectives</b>: Upright open magnetic resonance imaging allows the impact of posture and gravity to be evaluated. Randomized controlled trials of yoga for treating urinary incontinence (UI) in women show significant clinical benefit, yet the anatomic impact of this therapy on the lower urinary tract remains unelucidated. This study tested the hypothesis that open MRI scans can be obtained with sufficient detail to visualize the bladder neck and urethra. <b>Methods</b>: We scanned a volunteer subject using a 0.5 Tesla MRO Open Evo scanner to obtain axial and sagittal T2-weighted pelvic scans during poses used in yoga therapy. To obtain images with the necessary detail, we employed variations in sequencing during scanning of each individual pose. The changes observed in the bladder neck and urethral outline in each pose were then compared to baseline supine images. <b>Results</b>: Images with sufficient anatomic detail were obtained in each of the four poses studied. These scans identified that the urethral outline changes anatomically based on the posture adopted and is dynamic with regional alternations evident in caliber during specific yoga poses. <b>Conclusions</b>: Open MRI can identify anatomical changes involving the bladder neck and urethra that occur during yoga poses used in the treatment of UI in women; these likely relate to effects of posture and gravity. Open MRI offers a way to elucidate the anatomic effects that specific yoga poses generate and to identify those with the potential to be most beneficial clinically to women as a form of therapy.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11940940/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-13DOI: 10.3390/diagnostics15060717
Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young Im Cho
{"title":"Multi-Modal Fusion and Longitudinal Analysis for Alzheimer's Disease Classification Using Deep Learning.","authors":"Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young Im Cho","doi":"10.3390/diagnostics15060717","DOIUrl":"10.3390/diagnostics15060717","url":null,"abstract":"<p><p><b>Background:</b> Addressing the complex diagnostic challenges of Alzheimer's disease (AD), this study introduces FusionNet, a groundbreaking framework designed to enhance AD classification through the integration of multi-modal and longitudinal imaging data. <b>Methods:</b> FusionNet synthesizes inputs from Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), and Computed Tomography (CT) scans, harnessing advanced machine learning strategies such as generative adversarial networks (GANs) for robust data augmentation, lightweight neural architectures for efficient computation, and deep metric learning for precise feature extraction. The model uniquely combines cross-sectional and temporal data, significantly enhancing diagnostic accuracy and enabling the early detection and ongoing monitoring of AD. The FusionNet architecture incorporates specialized feature extraction pathways for each imaging modality, a fusion layer to integrate diverse data sources effectively, and attention mechanisms to focus on salient diagnostic features. <b>Results:</b> Demonstrating superior performance, FusionNet achieves an accuracy of 94%, with precision and recall rates of 92% and 93%, respectively. <b>Conclusions:</b> These results underscore its potential as a highly reliable diagnostic tool for AD, facilitating early intervention and tailored treatment strategies. FusionNet's innovative approach not only improves diagnostic precision but also offers new insights into the progression of Alzheimer's disease, supporting personalized patient care and advancing our understanding of this debilitating condition.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941453/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
DiagnosticsPub Date : 2025-03-12DOI: 10.3390/diagnostics15060701
Guven Yenmis, Ilayda Kallenci, Mehmet Dokur, Suna Koc, Sila Basak Yalinkilic, Evren Atak, Mahmut Demirbilek, Hulya Arkan
{"title":"The Distribution of Sport Performance Gene Variations Through COVID-19 Disease Severity.","authors":"Guven Yenmis, Ilayda Kallenci, Mehmet Dokur, Suna Koc, Sila Basak Yalinkilic, Evren Atak, Mahmut Demirbilek, Hulya Arkan","doi":"10.3390/diagnostics15060701","DOIUrl":"10.3390/diagnostics15060701","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Since its emergence in 2020, researchers worldwide have been collaborating to better understand the SARS-CoV-2 disease's pathophysiology. Disease severity can vary based on several factors, including comorbidities and genetic variations. Notably, recent studies have highlighted the role of genes associated with athletic performance, such as ACE, ACTN3, and PPARGC1A, in influencing muscle function, cardiovascular health, and the body's metabolic response. Given that these genes also impact oxidative metabolism, inflammation, and respiratory efficiency, we hypothesized that they might play a critical role in the host's response to SARS-CoV-2 infection. This study aimed to investigate the association between disease severity and genetic polymorphisms in these sport performance-related genes, specifically ACE rs4646994, ACTN3 rs1815739, and PPARGC1A rs8192678. <b>Methods:</b> A total of 422 COVID-19-positive patients were included in this study. The participants were divided into three groups: a severe group (77 patients) requiring intensive care unit (ICU) admission, a mild group (300 patients) exhibiting at least one symptom, and an asymptomatic control group. Genotyping was performed using restriction fragment length polymorphism PCR. <b>Results:</b> The D allele and DD genotype of ACE and the T allele and TT genotype of ACTN3 were found to confer protective effects against severe SARS-CoV-2 infection. Conversely, the PPARGC1A TC genotype and the ACE-PPARGC1A ins/ins + TC combined genotype were associated with increased disease severity (<i>p</i> < 0.05). <b>Conclusions:</b> Although vaccination has reduced the severity of SARS-CoV-2, the virus continues to impact human health. Inter-individual differences due to these genetic variations will broaden the horizon of knowledge on the pathophysiology of the disease.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 6","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11941099/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}