Research square最新文献

{"title":"Fluorescence-illuminated Diffraction Tomography using Explicit Neural Fields.","authors":"Yi Xue, Renzhi He, Yucheng Li, Junjie Chen","doi":"10.21203/rs.3.rs-6442385/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6442385/v1","url":null,"abstract":"<p><p>Multimodal imaging of fluorescence and phase provides distinct and complementary insights into biological samples. Current multimodal techniques for simultaneous phase and fluorescent imaging primarily operate in transmission mode and are limited to thin samples, restricting their applications to bulky tissues and in vivo animals. While multiphoton microscopy has enabled deeptissue fluorescence imaging, integrating it with phase imaging remains challenging due to the limited availability of methods capable of reconstructing the 3D refractive index (RI) of bulky, label-free tissues in reflection mode at subcellular resolution. To bridge the technical gap, we develop fluorescence-illuminated diffraction tomography (FDT) that reconstructs the 3D RI of label-free objects from diffracted fluorescence images acquired in reflection mode under two-photon excitation. The RI reconstruction leverages the transport of intensity equation (TIE) and is solved by a self-supervised neural network based on explicit neural fields. Compared to the state-of-the-art implicit neural fields, the explicit neural fields significantly improve computational speed, reconstruction accuracy, and interpretability. Using FDT, we successfully reconstruct the 3D RI of a 300 µmthick label-free bovine myotube sample over a 530 × 530 µm2 field-of-view at subcellular resolution within 20 min. FDT is the first technique to extract 3D RI from diffracted fluorescence images in reflection mode for thick tissues, overcoming key limitations of existing multimodal systems. This work lays the foundation for broadly accessible, reflection-mode multimodal fluorescence-phase imaging in complex biological systems in the future.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A pseudouridine synthase shapes tRNA structural dynamics through both catalysis and remodeling.","authors":"Julia Widom, Emily Dennis, Nico Conoan Nieves, Abigail Vaaler, Madison Kadrmas, Maggie Barry, David Garcia","doi":"10.21203/rs.3.rs-6597546/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6597546/v1","url":null,"abstract":"<p><p>Transfer RNA has long served as an exemplar of a thermodynamically stable, structured RNA. Yet it undergoes significant structural changes upon binding and catalysis by diverse modification enzymes. We leveraged optical binding assays and single-molecule FRET to observe tRNA structural dynamics before and upon interaction with the conserved pseudouridine synthase Pus4/TruB. We show that unmodified and pseudouridylated tRNA similarly sample one open and two closed conformations, dynamically. Binding by Pus4 to unmodified tRNA populates additional conformational states, gradually approaching an ensemble that is adopted sooner by tRNA that was pseudouridylated prior to engaging Pus4. A catalytically incompetent mutant of Pus4 binds more slowly and remodels unmodified and pre-modified tRNAs into different conformational ensembles than wild-type enzyme. Thus, Pus4 both catalyzes a lasting chemical change on tRNA and remodels it over time, perhaps to advance subsequent steps of tRNA maturation.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeted Nanoencapsulation of Tunicamycin Reduces Toxicity While Improving its Therapeutic Effectiveness in Pancreatic Cancer Cells.","authors":"Debasmita Dutta, Sunil Upadhyay, Archana De, Inamul Haque, Axel H Breier, Alok De, Daniel J Mettman, Suman Kambhampati, Mohiuddin Quadir, Francisco Diaz, Sushanta K Banerjee, Stefan H Bossmann, Snigdha Banerjee","doi":"10.21203/rs.3.rs-6711378/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6711378/v1","url":null,"abstract":"<p><p>Pancreatic ductal adenocarcinoma (PDAC) remains one of the leading sources of cancer mortality worldwide. An initial response to chemotherapy, such as Gemcitabine (GEM) alone or in combination with other chemotherapies, is often followed by emergent resistance, underscoring the urgent need for targeted therapies. PDAC cells are highly addicted to oncogenic K-RAS mutations for their growth, progression, immunosuppression, and drug resistance, but mutant K-RAS in PDAC is still challenging to target. A glycosylation inhibitor, Tunicamycin (TM), is a potent killer of PDAC cells. However, the free TM is very toxic in clinical settings. We developed a pH/Hypoxia-responsive iRGD-tagged biodegradable nano-encapsulated TM ( ^NP TM) that overcomes the limitations of free TM and shows promising results inhibiting PDAC cell growth via apoptosis. The ^NP TM has shown significant promise, reducing cellular heterogeneity, drug resistance, in vitro desmoplasia, and subcutaneous tumor growth and markedly prolonging the survival in a KPC-xenograft mouse model. The studies suggest that TM targets K-Ras ^G12D -dependent multiple signaling pathways such as eIF4E, STAT3, and STAT5 activities and CCN1 to promote its anticancer efficacy. Together, these studies reveal the potential of simultaneously targeting a K-Ras ^G12D -dependent signal and CCN1 with first-line chemotherapy and provide a rationale for future clinical testing of ^NP TM for PDAC therapy.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Dual Fluorescent-Raman Bioorthogonal Probe for Specific Biosynthetic Labeling of Gangliosides.","authors":"John Hanover, Mana Mukherjee, Matthew Watson, Devin Biesbrock, Lara Abramowitz, Steven Drake, Jennifer Lee","doi":"10.21203/rs.3.rs-5611903/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-5611903/v1","url":null,"abstract":"<p><p>Gangliosides are sialic acid-containing glycosphingolipids integral to the cell membrane and are particularly abundant in the nervous system. Aberrant ganglioside metabolism contributes to pathological conditions including neurodegenerative diseases, lysosomal storage disorders, and cancer. Currently, tools to visualize and detect gangliosides are very limited and non-specific. Here, we describe a dual fluorescent and Raman-active ManNAlk derivative, phenanthrene-9-Pr4ManNAlk (MM-JH-2), capable of one-step selective labeling of gangliosides in cells. This modified ManNAlk derivative produces a biologically unique Raman spectral signature, which arise from the carbon-carbon triple bond augmented by conjugation to a fluorescent phenanthrene moiety. By using this dual probe, unambiguous identification is achieved within cells. Raman maps generated using the alkyne stretching frequency indicate a distribution of MM-JH-2 overlapping with intracellular membrane lipids. Using confocal fluorescence imaging, the cellular transport of labeled gangliosides was tracked from synthesis to recycling in the acidic compartments. Notably, MM-JH-2 can differentiate between cells that differ in ganglioside biosynthetic flux, such as malignant and nonmalignant cells, as well as distinguish between B cells and T cells. Thus, MM-JH-2 is a novel next-generation metabolic chemical reporter (MCR) that is Raman-active, fluorescent, and can be broadly applied to cellular studies investigating ganglioside biosynthetic flux.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Psychosocial Stress in Early Life on Pace of Aging in Young Adulthood.","authors":"Shaoyong Su, Tené T Lewis, Daniel W Belsky, Yutao Liu, Kai Zhang, Harold Snieder, Xiaoling Wang","doi":"10.21203/rs.3.rs-6630823/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6630823/v1","url":null,"abstract":"<p><strong>Background: </strong>Early-life psychosocial stress is increasingly recognized as a contributor to accelerated biological aging and health disparities, yet its impact during young adulthood remains underexplored.​ Existing studies often focus on one or two dimensions of stress exposure and rely on retrospective assessments. Utilizing data from a longitudinal cohort initiated in 1989, we aim to examine the impact of early life psychosocial stress on accelerated aging in young adulthood, as well as its potential contribution to health disparities between Black and White Americans. Participants included 470 individuals (223 Black and 247 White Americans) with DNA samples collected at age > 20 years.​ Psychosocial stress exposures in the first 20 years of life were assessed prospectively using validated instruments across individual, family, and neighborhood domains. DunedinPACE, a novel biomarker of the pace of aging, was calculated from DNA methylation data generated from peripheral blood using the Illumina 450K array. The joint effect of early life psychosocial factors on DunedinPACE and the relative importance of each stressor were estimated using the Weighted Quantile Sum (WQS) approach. Mediation analysis was conducted to evaluate the contribution of early life stress to racial disparities in aging.</p><p><strong>Results: </strong>Compared to White Americans, Black Americans reported higher overall levels of early life stress (mean = 1.54 vs. 1.40, adjusted p = 0.003) and exhibited a faster pace of aging in young adulthood (DunedinPACE z-score mean = 0.21 vs. -0.19, adjusted p < 0.001). WQS analysis revealed a positive joint effect of early life psychosocial stress on DunedinPACE (β = 0.26, 95% CI: 0.167-0.353), with the top four contributors being parental socioeconomic status, peer pressure, family emotional expression, and neighborhood safety conditions. Mediation analysis indicated that early-life stress accounted for 22% of the racial disparity in biological aging (p = .01).​ Conclusion: Our findings suggest that exposure to disadvantaged psychosocial environments in early life is associated with accelerated biological aging in young adulthood. Racial differences in stress exposure partially explain disparities in aging, underscoring the importance of early interventions to reduce health disparities across the life course.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136749/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Treatment for Depression in Primary Care Using Psychotherapy Versus Antidepressant Medication in a Low-Resource Setting: Protocol for the OptimizeD Randomized Controlled Trial.","authors":"Julia R Pozuelo, Anuja Lahiri, Rahul S P Singh, Arvind Kushwah, Mimansa Khanduri, Akanksha Shukla, Azaz Khan, Sruthi G, Varun Shende, Yashika Parashar, Yashwant K Mehra, Anant Bhan, Ronald C Kessler, Daisy R Singla, John A Naslund, Karmel Choi, Pim Cuijpers, Robert DeRubeis, Mohammad Herzallah, Chunling Lu, Jordan W Smoller, Tyler J VanderWeele, Abhijit Rozatkar, Michelle Melwyn Joel, Debasis Biswas, Shubham Atal, Umay Kulsum, Steven D Hollon, Vikram Patel","doi":"10.21203/rs.3.rs-6716211/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6716211/v1","url":null,"abstract":"<p><p><b>Background:</b> Psychotherapy and antidepressant medications are first-line treatments for depression, and they both have significant treatment effects on average. However, treatment response varies widely across patients, and neither approach is universally effective. Identifying the most effective treatment for each patient is critical everywhere, but particularly in low-resource settings where access to mental health care is limited. The Optimizing Depression (OptimizeD) trial aims to explore whether different patients respond differently to behavioral activation therapy versus antidepressant medication and if providing each patient with their optimal treatment improves outcomes in primary care. <b>Methods:</b> We plan to randomize 1,500 patients with moderate to severe depression (defined as a Patient Health Questionnaire [PHQ-9] score ≥10) from primary healthcare settings in Bhopal, India, with equal allocation either to a culturally adapted behavioral activation therapy delivered by trained counselors (Healthy Activity Program) or to antidepressant medication (fluoxetine). Treatment will last 3 months, with remission (defined as PHQ-9 score <5) at 3 months as the primary endpoint. Using machine learning, we will attempt to develop a precision treatment rule that leverages baseline clinical, psychological, cognitive, socioeconomic, and biological data to predict which treatment is most likely to achieve remission for each patient. Cost-effectiveness analysis will then assess whether the added costs of optimizing treatment are justified by improvements in remission, recovery, and cost savings at the health system and societal levels. Secondary and exploratory objectives include assessing the effectiveness of optimization in a range of secondary outcomes, evaluating treatment mechanisms, and exploring whether incorporating genetic and biological markers as predictors improves treatment optimization. <b>Discussion:</b> The OptimizeD trial will evaluate whether baseline information collected in routine care can inform optimal depression treatment selection and identify predictors of nonresponse to facilitate timely specialist referrals. Findings have the potential to enhance personalized depression care in primary health systems, particularly in low-resource settings, with broader implications for global public health. <b>Trial registration:</b> ClinicalTrials.gov (NCT05944926; registered July 2, 2023) and Clinical Trials Registry India (CTRI/2024/01/061932; registered January 29, 2024).</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Label-Free Fluorescence Lifetime Imaging for Intraoperative Tumor Margin Delineation in Head and Neck Cancer using Data-Centric AI.","authors":"Mohamed Abul Hassan, Lisanne Kraft, Muhammad Adeel Azam, Julien Bec, Kelsey T Hadfield, Jinyi Qi, Dorina Gui, Arnaud Bewley, Marianne Abouyared, Jonathan Sorger, Gregory Farwell, Andrew C Birkeland, Laura Marcu","doi":"10.21203/rs.3.rs-6673642/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6673642/v1","url":null,"abstract":"<p><p>Precise intraoperative delineation of tumor margin is critical for maximizing resection completeness and minimizing recurrence in head and neck cancers (HNC). Label-free Fluorescence Lifetime Imaging (FLIm), which captures the fluorescence decay characteristics of endogenous molecules, offers a real-time method for differentiating malignant from healthy tissue during surgery without the need of contrast agents. Here, we present a data-centric artificial intelligence (AI) framework to enhance the robustness and accuracy of FLIm-based classification models for HNC. FLIm data were collected in vivo from 92 patients undergoing both transoral robotic surgery (TORS) and non-TORS procedures for HNC using a multispectral FLIm device with 355 nm excitation. To improve model performance, a data-centric approach leveraging confident learning was implemented to identify and exclude instances with low quality. An interpretability framework was further integrated to quantify feature contributions and elucidate FLIm-derived sources of contrast. Under a leave-one-patient-out cross-validation scheme, the model demonstrated a strong discriminative ability with an area under the receiver operating characteristic curve of 0.94 in differentiating healthy versus cancerous tissue. In tumor boundary regions, borderline predictions revealed transitional tissue properties, with strong correlations observed between model predictions and FLIm parameters in spectral channels corresponding to NADH and FAD-key metabolic cofactors indicative of cellular metabolic shifts at tumor margins. The impact of tumor anatomical site (base of tongue, palatine tonsil, oral tongue) and p16+ (HPV) status on classification performance was also assessed. These findings underscore the potential of label-free FLIm to provide accurate, real-time guidance for intraoperative margin assessment and dysplasia grading, advancing surgical precision in head and neck surgical oncology.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136734/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Redefining PH Domain Function: An Active Allosteric Mechanism in ASAP1-Mediated Arf1 GTP Hydrolysis.","authors":"Paul Randazzo, Olivier Soubias, Samuel Foley, Xiaoying Jian, Rebekah Jackson, Yue Zhang, Eric Rosenberg, Jess Li, Frank Heinrich, Margaret Johnson, Alexander Sodt, R Andrew Byrd, Benjamin Hu","doi":"10.21203/rs.3.rs-6702895/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6702895/v1","url":null,"abstract":"<p><p>GTPase-activating proteins (GAPs) are important regulators of small GTPases with a wide range of cellular functions; among these, ASAP1 stimulates GTP hydrolysis on Arf1 and is implicated in cancer progression. ASAP1 contains a Pleckstrin Homology (PH) domain critical for maximum hydrolysis of GTP bound to the small GTPase Arf. The prevailing view of PH domains is that they regulate proteins by passive mechanisms such as recruitment to the membrane surface. In sharp contrast to this model of regulation, our research reveals that the PH domain of ASAP1 actively contributes to Arf1 GTP hydrolysis. By combining NMR, molecular dynamics simulations, kinetic assays, and mutational analysis, we found that the PH domain directly interacts with Arf·GTP at the membrane, to drive conformational rearrangements of the GTP binding site. These structural changes establish an active state primed for GTP hydrolysis, facilitating charge stabilization which in turn, significantly enhances the catalytic rate of the GTPase reaction. Specifically, we identified key residues on both the PH domain and Arf responsible for this allosteric mechanism. Further, through mathematical modeling, we quantified the contribution of this newly discovered allosteric mechanism to ASAP1 GTPase-activating protein activity and found that it contributes equally to GTPase activation as membrane recruitment. The discovery that PH domains can directly affect nucleotide hydrolysis by a small GTPase has ramifications for the larger group of small GTPases, that include Ras and Rho proteins, that are regulated by proteins with PH domains, control diverse cellular functions and are oncoproteins.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Random field image representations speed up binary discrimination of brain scans and estimate a phenotype glioblastoma cancer cell model.","authors":"William D ONeill, Julian Najera, Meenal Datta","doi":"10.21203/rs.3.rs-6641557/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6641557/v1","url":null,"abstract":"<p><p>MRI brain scans alone are not a definitive measure of dementia. Deep-learning algorithms (DLA) and professional human opinion are necessary for diagnosis. Yet, sample sizes are prohibitively large to train a typical DLA, which itself takes considerable computation time to produce diagnostically useful information from contrasting image features. We introduce analytic simplifications to this process to speed it up and reduce data requirements by modeling individual images as solutions of spatially autoregressive (AR) partial difference equations. Image features are the unique individual image AR parameters. Spatially lagged image pixels are explanatory variables for estimating a random-field representation (RFR) of the proposed AR difference equation. RFR model parameters are also those of the image autocorrelation function (ACF). An image pixel matrix-to-vector transformation allows AR parameters to be estimated by ordinary least squares (OLS) regression in millisecond time. Regression degrees of freedom (DOF) -- the number of image pixels -- are unusually large, leading to remarkably precise estimates of AR model parameters. These estimates support a solution of the binary dementia-normal classification of MRI axial brain scans (ADNI and OASIS archives). They also support the AR-RFR process applied to an original microscopic image of a glioblastoma cancer cell. In the face of formidable noise, a sharply defined and robust cancer cell model is estimated, which is an essential tool for cancer - type discrimination exercises and is parametrically plastic enough to serve a wide range of cells.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"clinical characteristsics of adolescents and adults with sickle cell disease and barriers to transition to adult care at Mulago Hospital Uganda; A mixed methods study.","authors":"Racheal Owomuhangi, Charles Karamagi, Grace Ndeezi, Japheth Kwiringira, Deogratias Munube, Sarah Kiguli, Robert Opika Opoka, Ruth Namazzi","doi":"10.21203/rs.3.rs-6234847/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-6234847/v1","url":null,"abstract":"<p><p><b>Background</b> Over the past six decades, advancements in medical care have significantly enhanced outcomes for individuals with sickle cell disease (SCD), with studies demonstrating increased survival rates into adulthood. A smooth transition from pediatric to adult care is essential for maintaining positive health outcomes. Nevertheless, healthcare systems have struggled to adapt, leaving gaps in support for the expanding adult SCD Population. Mulago Pediatric Sickle Cell Clinic has faced multiple challenges with the transition to adult care that are not well documented. The objective of this study was to describe the clinical characteristics of adolescents and adults with sickle cell disease and barriers to adult care at Mulago Hospital. <b>Methods</b> This was a mixed method cross-sectional study with both qualitative and quantitative data collection methods conducted among patients attending the pediatric sickle cell clinic at Mulago Hospital, their caregivers, and health care workers. A registry and medical records review was done to obtain data for the quantitative arm. The qualitative component consisted of 30 in-depth interviews involving patients and caregivers and 10 key informant interviews with healthcare workers. Quantitative data was coded and entered into Epidata version 4.6 and then exported to STATA 14 for analysis. Qualitative data was analyzed using the content thematic approach. <b>Results</b> The proportion of patients aged 14 years and above still attending the pediatric clinic was 21.6%. Barriers to the transition of care as expressed by caregivers and patients were limited knowledge of transition, attachment to their pediatric careers, and negative experiences in the adult clinics. Health care system barriers included poorly organized adult clinics with few working days compared to the pediatric clinic that operates daily. This was compounded by a lack of policies and guidelines on transition, inadequate human resources, and limited access to the essential drugs in the adult clinics. <b>Conclusions and recommendations</b> There is still a large proportion of adolescents and young adults still attending the pediatric sickle cell clinic and barriers to transition were not only sociodemographic but also psychosocial and health system related. There is a need for better planning and preparation with better patient-centred interventions to improve transition.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144228279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}