Research square最新文献

{"title":"An Open-Source Deep Learning-Based GUI Toolbox for Automated Auditory Brainstem Response Analyses (ABRA).","authors":"Abhijeeth Erra, Jeffrey Chen, Cayla M Miller, Elena Chrysostomou, Shannon Barret, Yasmin M Kassim, Rick A Friedman, Amanda Lauer, Federico Ceriani, Walter Marcotti, Cody Carroll, Uri Manor","doi":"10.21203/rs.3.rs-6735294/v1","DOIUrl":"10.21203/rs.3.rs-6735294/v1","url":null,"abstract":"<p><p>Hearing loss is a pervasive global health challenge with profound impacts on communication, cognitive function, and quality of life. Recent studies have established age-related hearing loss as a significant risk factor for dementia, highlighting the importance of hearing loss research. Auditory brainstem responses (ABRs), which are electrophysiological recordings of synchronized neural activity from the auditory nerve and brainstem, serve as in vivo readouts for sensory hair cell, synaptic integrity, hearing sensitivity, and other key features of auditory pathway functionality, making them highly valuable for both basic neuroscience research and clinical diagnostics. Despite their utility, traditional ABR analyses rely heavily on subjective manual interpretation, leading to considerable variability and limiting reproducibility across studies. Here, we introduce Auditory Brainstem Response Analyzer (ABRA), a novel open-source graphical user interface powered by deep learning, which automates and standardizes ABR waveform analysis. ABRA employs convolutional neural networks trained on diverse datasets collected from multiple experimental settings, achieving rapid and unbiased extraction of key ABR metrics, including peak amplitude, latency, and auditory threshold estimates. We demonstrate that ABRA's deep learning models provide performance comparable to expert human annotators while dramatically reducing analysis time and enhancing reproducibility across datasets from different laboratories. By bridging hearing research, sensory neuroscience, and advanced computational techniques, ABRA facilitates broader interdisciplinary insights into auditory function. An online version of the tool is available for use at no cost at https://abra.ucsd.edu.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204367/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532586","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":"Multimodal Prediction of Psychosis in the Prospective MoBa Birth Cohort.","authors":"Viktoria Birkenæs, Pravesh Parekh, Alexey Shadrin, Piotr Jaholkowski, Lars A R Ystaas, Carolina Makowski, Nora R Bakken, Espen Hagen, Evgeniia Frei, Dominic Oliver, Paolo Fusar-Poli, Anders Dale, John P John, Alexandra Havdahl, Ida E Sønderby, Ole A Andreassen","doi":"10.21203/rs.3.rs-6783339/v1","DOIUrl":"10.21203/rs.3.rs-6783339/v1","url":null,"abstract":"<p><p>There is a need for improved early psychosis detection beyond the traditional clinical high-risk strategy. Using the Norwegian Mother, Father and Child cohort study, we examined the predictive ability of self-reported psychotic experiences (Community Assessment of Psychic Experiences; CAPE) at age 14, in addition to general mental health factors, parent and childhood psychiatric diagnoses, schizophrenia polygenic risk scores, and birth-related factors, to predict subsequent psychosis onset using three machine learning approaches for imbalanced data. We explored also a multimodal prediction framework. For unimodal classification, we observed best balanced accuracies with general mental health factors (67.27 ± 1.76%), and CAPE (65.95 ± 1.09%). Multimodal models improved classification accuracy (68.38 ± 2.16%). With validation and additional model refinement, these features may be useful for initial screening within clinical stepped assessment frameworks.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532599","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":"Skeletonization of neuronal processes using Discrete Morse techniques from computational topology.","authors":"Samik Banerjee, Caleb Stam, Daniel J Tward, Steven Savoia, Yusu Wang, Partha P P Mitra","doi":"10.21203/rs.3.rs-6642891/v1","DOIUrl":"10.21203/rs.3.rs-6642891/v1","url":null,"abstract":"<p><p>To understand biological intelligence we need to map neuronal networks in vertebrate brains. Mapping mesoscale neural circuitry is done using injections of tracers that label groups of neurons whose axons project to different brain regions. Since many neurons are labeled, it is difficult to follow individual axons. Previous approaches have instead quantified the regional projections using the total label intensity within a region. However, such a quantification is not biologically meaningful. We propose a new approach better connected to the underlying neurons by skeletonizing labeled axon fragments and then estimating a volumetric length density. Our approach uses a combination of deep nets and the Discrete Morse (DM) technique from computational topology. This technique takes into account nonlocal connectivity information and therefore provides noise-robustness. We demonstrate the utility and scalability of the approach on whole-brain tracer injected data. We also define and illustrate an information theoretic measure that quantifies the additional information obtained, compared to the skeletonized tracer injection fragments, when individual axon morphologies are available. Our approach is the first application of the DM technique to computational neuroanatomy. It can help bridge between single-axon skeletons and tracer injections, two important data types in mapping neural networks in vertebrates.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204360/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532561","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":"Empiric Azithromycin in COVID-19 Impacts the Respiratory Microbiome and Antimicrobial Resistome without Anti-inflammatory Benefit.","authors":"Charles Langelier, Abigail Glascock, Cole Maguire, Hoang Van Phan, Emily Lydon, Carolyn Calfee, David Corry, Farrah Kheradmand, Lindsey Baden, Rafick-Pierre Sekaly, Grace McComsey, Elias Haddad, Charles Cairns, Bali Pulendran, Ana Fernandez-Sesma, Viviana Simon, Jordan Metcalf, Nelson Higuita, William Messer, Mark Davis, Kari C Nadeau, Monica Kraft, Chris Bime, Joanna Schaenman, David Erle, Mark Atkinson, Lauren I R Ehrlich, Esther Melamed, Ruth Montgomery, Albert Shaw, Catherine Hough, Linda Geng, Annmarie Hoch, David Hafler, Alison Augustine, Patrice Becker, Bjoern Peters, Al Ozonoff, Seunghee Kim-Schulze, Florian Krammer, Steven Bosinger, Walter Eckalbar, Matthew Altman, Michael Wilson, Leying Guan, Holden Maecker, Hanno Steen, Joann Diray-Arce, Nadine Rouphael, Steven Kleinstein, Elaine Reed, Ofer Levy, Victoria Chu","doi":"10.21203/rs.3.rs-6875205/v1","DOIUrl":"10.21203/rs.3.rs-6875205/v1","url":null,"abstract":"<p><p>Azithromycin is often prescribed unnecessarily for respiratory infections, many of which are viral. During the COVID-19 pandemic, its use was widespread, in part due to alleged therapeutic benefits, which have since been disproven. Here, we sought to understand the impact of azithromycin exposure on the respiratory microbiome, antimicrobial resistome, and host immune response in a prospective multicenter cohort of 1164 patients hospitalized for SARS-CoV-2 infection. Using longitudinal nasal metatranscriptomics, we compared patients treated with azithromycin (n=366, 31.4%) to those who received no antibiotics (n=474, 40.7%) or antibiotics other than azithromycin (n=324, 27.8%). We found that azithromycin treatment altered the community composition of the nasal microbiome, reducing bacterial relative abundance, increasing fungal relative abundance, and increasing potentially pathogenic taxa such as <i>Klebsiellaand Staphylococcus</i>. Azithromycin treatment was most notably associated with increases in the number of detectably expressed macrolide/lincosamide/streptogramin (MLS) antimicrobial resistance genes, as well as their relative proportion in the resistome, with changes observable after one day of exposure. Of the MLS resistance genes, the expression of <i>ermC, msrA</i> and <i>ermX</i> increased the most in patients receiving azithromycin. Correlation analyses demonstrated that MLS resistance gene expression was significantly associated with the abundance of several taxa, including both commensal (e.g., <i>Dolosigranulum, Corynebacterium</i>) and potentially pathogenic genera (e.g., <i>Streptococcus, Staphylococcus</i>). Assessment of the peripheral blood and upper airway host transcriptome demonstrated no differences in the expression of inflammatory genes. Taken together, our findings demonstrate that azithromycin treatment in COVID-19 leads to dysbiosis of the upper respiratory microbiome and changes in the expression of MLS resistance genes, without apparent anti-inflammatory benefit.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532625","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":"Engaging English- and Spanish-speaking older adults with and without possible cognitive impairment in advance care planning group visits: Protocol for the ENgaging in Advance Care Planning Talks (ENACT) Randomized Controlled Trial.","authors":"Hillary Lum, Samantha Farro, Elizabeth Juarez-Colunga, Chandni Patel, Brianne Bettcher, Christine Haynes, Amy Huebschmann, David Nowels, Caroline Tietbohl, Jiayuan Shi, Carly Ritger, Prajakta Shanbhag, Kathleen Resman, Rebecca Sudore","doi":"10.21203/rs.3.rs-6560971/v1","DOIUrl":"10.21203/rs.3.rs-6560971/v1","url":null,"abstract":"<p><strong>Background: </strong>Advance care planning (ACP) helps patients identify and communicate their preferences for medical care and prepares them for decision-making related to future care. While ACP is recommended for older adults with cognitive impairment, few interventions have been tested in primary care for this population. The ENACT trial tests the efficacy of the ENgaging in Advance Care planning Talks (ENACT) Group Visits intervention, which engages older adults with and without possible cognitive impairment in group medical visits focused on the ACP process.</p><p><strong>Methods: </strong>This two-arm randomized trial compares the efficacy of the ENACT Group Visits intervention arm to a control arm at 6-month follow-up. The trial will enroll at least 480 patients across 8 primary care clinics. Notable inclusion criteria include English or Spanish-speaking, age 70 or older, and no ACP documents in the electronic health record (EHR) in the past 2 years. The Montreal Cognitive Assessment screener will be administered at study enrollment to identify whether the participant has possible cognitive impairment. Participants will be randomized 1:1 to the ENACT Group Visits arm or control arm. The ENACT Group Visits intervention entails two group visits, facilitated by multidisciplinary clinic staff. The control arm entails sending ACP materials via mail. The primary outcome is new documentation of ACP in the EHR at 6-month follow up, and it will be analyzed using logistic regression with random effects for site. Secondary outcomes include patient-level ACP readiness, decision self-efficacy, and quality of communication. The impact of possible cognitive impairment on ENACT intervention efficacy will be examined. Survival analyses will be used to examine time-to-new ACP documentation. Mixed methods, including multiple qualitative methods, will be used to assess acceptability, feasibility, intervention fidelity, and other implementation outcomes of the ENACT intervention among patients with possible cognitive impairment.</p><p><strong>Discussion: </strong>This study will determine the efficacy of the ENACT Group Visits intervention among diverse older adults, including those with possible cognitive impairment, as evidenced by increased documentation of ACP in the medical record. If efficacious, primary care clinics may implement this ACP intervention that leverages peer interactions and goal setting to support a person-centered ACP process.</p><p><strong>Trial registration: </strong>Clinicaltrials.gov: NCT05421728. Registered on 13 June 2022, https://clinicaltrials.gov/study/NCT05421728.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532626","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":"Multi-omics machine learning classifier and blood transcriptomic signature of Parkinson's disease.","authors":"Xianjun Dong, Ruifeng Hu, Ruoxuan Wang, Jie Yuan, Zechuan Lin, Elizabeth Hutchins, Barry Landin, Zhixiang Liao, Ganqiang Liu, Clemens Scherzer","doi":"10.21203/rs.3.rs-6837659/v1","DOIUrl":"10.21203/rs.3.rs-6837659/v1","url":null,"abstract":"<p><p>Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale, whole-blood total RNA and DNA sequencing data from the Accelerating Medicines Partnership in Parkinson's Disease (AMP PD) program to identify PD-associated RNAs, including both known genes and novel circular RNAs (circRNA) and enhancer RNAs (eRNAs). Initially, 874 known genes, 783 eRNAs, and 35 circRNAs were found differentially expressed in PD blood in the PPMI cohort (FDR < 0.05). Based on these findings, a novel multi-omics machine learning model was built to predict PD diagnosis with high performance (AUC = 0.89), which was superior to previous models. We further replicated this discovery in an independent PDBP/BioFIND cohort and confirmed 1,111 significant marker genes, including 491 known genes, 599 eRNAs, and 21 circRNAs. Functional enrichment analysis showed that the PD-associated genes are involved in neutrophil activation and degranulation, as well as the TNF-α signaling pathway. By comparing the PD-associated genes in blood with those in human brain dopamine neurons in our BRAINcode cohort, we found only 44 genes (9% of the known genes) showing significant changes with the same direction in both PD brain neurons and PD blood, among which are neuroinflammation-associated genes IKBIP, CXCR2, and NFKBIB. Our findings demonstrated consistently lower SNCA mRNA levels and the increased expression levels of VDR gene in the blood of early-stage PD patients. In summary, this study provides a generally useful computational framework for further biomarker development and early disease prediction. We also delineate a wide spectrum of the known and novel RNAs linked to PD that are detectable in circulating blood cells in a harmonized, large-scale dataset.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204338/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532600","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":"Tumoroid model recreates clinically relevant phenotypes of high grade serous ovarian cancer (HGSC) cells, carcinoma associated fibroblasts, and macrophages.","authors":"Kathleen M Burkhard, Ayush Semwal, Benjamin K Johnson, Kristina C Chu, Riley J Kranick, Mihika Rayan, Analisa DiFeo, Hui Shen, Geeta Mehta","doi":"10.21203/rs.3.rs-6614892/v1","DOIUrl":"10.21203/rs.3.rs-6614892/v1","url":null,"abstract":"<p><p>Ovarian cancer, the gynecological malignancy with the lowest survival rate, is significantly influenced by the tumor microenvironment. The mesenchymal subtype of high-grade serous carcinoma (HGSC) shows poor outcomes due to high stromal and low immune response. Single-cell RNA sequencing (scRNA-seq) of HGSC metastatic ascites has identified carcinoma-associated fibroblasts (CAFs), macrophages, and carcinoma-associated mesenchymal stem cells (CA-MSCs) as crucial drivers of immune exclusion, chemotherapy resistance, metastasis, and stem-like cell propagation. To explore this complex signaling, we developed heterogeneous tri-component tumoroids, incorporating HGSC cells (OVCAR3, OVCAR4, OVCAR8), primary MSCs, and U937-derived M2-like macrophages (M2-AAM) in defined ratios, each labeled with a fluorescent protein for distinct analysis. Upon a 48-hour treatment with carboplatin and/or paclitaxel, HGSC cells in tri-component tumoroids exhibited higher chemoresistance than HGSC-only spheroids. Flow cytometry revealed significant increases in cancer stem-like cell (CSC) markers CD44 and CD90 in the tri-component tumoroids. Conditioned medium from the tri-component tumoroids significantly enhanced HGSC cell migration compared to spheroids. Invasion assays further demonstrated that tri-component tumoroids penetrated monolayer of mCherry-labeled LP-9 mesothelial cells more effectively than spheroids. Additionally, scRNA-seq of tri-component tumoroids identified a unique cancer cell cluster enriched in epithelial-mesenchymal transition (EMT) and matrisome signatures, featuring a 14-gene signature linked to poor survival. MSCs in these tri-component tumoroids displayed a myofibroblastic-CAF signature, while macrophages indicated an ECM-associated and immunosuppressive phenotype. In conclusion, our 3D heterogenous tri-component tumoroids replicate key HGSC phenotypes, such as chemoresistance, CSC enrichment, migration, invasion, and EMT. This platform is invaluable for studying HGSC microenvironment interactions and preclinical testing of targeted therapies.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204350/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532637","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":"Genetics of <i>PLCG2</i> expression and splicing relative to Alzheimer's disease risk.","authors":"Andrew K Turner, Kennedy Dotson, Qi Qiao, Kailey Cain, James F Simpson, David W Fardo, Steven Estus","doi":"10.21203/rs.3.rs-6735123/v1","DOIUrl":"10.21203/rs.3.rs-6735123/v1","url":null,"abstract":"<p><strong>Background: </strong>PLCG2 is associated with the risk of Alzheimer's disease (AD) through a rare missense polymorphism, rs72824905 (P522R) as well as a common variant, rs12445675, within a long non-coding RNA adjacent to <i>PLCG2</i>. Elucidating the impact of genetics on PLCG2 expression and splicing will provide insights into the role of PLCG2 in AD risk and, potentially, treatments that might reduce AD risk.</p><p><strong>Objective: </strong>To evaluate <i>PLCG2</i> expression and splicing as a function of AD genetics.</p><p><strong>Methods: </strong><i>PLCG2</i> isoform expression was detected by PCR and quantified by qPCR in AD and non-AD brain samples and in blood buffy coat samples. The function of a genetic variant, rs107164, was tested by using a minigene approach with both alleles in murine BV-2 microglial cells. The impact of ectopic splicing factor expression on PLCG2 minigene splicing was also tested in BV-2 cells. The extent that endogenous levels of a novel <i>PLCG2</i> mRNA isoform lacking 65 bp within exon 28 (D65-PLCG2) were affected by nonsense mediated decay (NMD) was determined by using cycloheximide <i>in vitro</i>. Lastly, whether <i>D65-PLCG2</i> manifested a Ca + 2 response similar to <i>PLCG2</i> was tested by comparing D65-PLCG2-GFP and PLCG2-GFP fusion proteins in transfected HEK293 cells.</p><p><strong>Results: </strong>We report <i>PLCG2</i> isoforms that include (i) a transcript that replaces <i>PLCG2</i> exon 1 with sequence from an adjacent long noncoding (LNC) RNA (<i>LNC-PLCG2</i>) and (ii) a transcript that lacks 65 bp from the beginning of exon 28 (<i>D65-PLCG2</i>). The ratio of <i>LNC-PLCG2</i> to canonical <i>PLCG2</i> was associated with rs12445675 genotype in both human brain and buffy coat samples. The proportion of <i>PLCG2</i> expressed as <i>D65-PLCG2</i> was increased by the T allele of rs1071644, a T/C SNP within the 65bp variably spliced portion of exon 28. This SNP was demonstrated to be functional in a minigene splicing assay. Moreover, the rs1071644-T allele was found to be associated with increased AD risk, independent of rs72824905 (P522R) and rs12445675. <i>D65-PLCG2</i> was susceptible to nonsense mediated RNA decay. D65-PLCG2 was not responsive to Ca^{+ 2} in a fashion similar to that observed for PLCG2. Hence, the rs1071644-T allele appears to increase AD risk by increasing the proportion of <i>PLCG2</i> expressed as <i>D65-PLCG2</i>, representing a loss of PLCG2 function.</p><p><strong>Conclusions: </strong>We report that two AD genetic risk factors, rs12445675 and rs1071644, affect AD risk by impacting the <i>LNC-PLCG2</i> to <i>PLCG2</i> ratio and <i>PLCG2</i> exon 28 splicing, respectively.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204370/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532533","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":"Targeting Artemis Sensitizes B Cells to Topoisomerase 2 Poisons by Disrupting DNA-PKcs-Dependent Repair.","authors":"Melissa L Folkerts, Cameron Hom, Angie Nguyen, Kaiyuan V Shen, Valeria Rangel, Pedro Ortega, Rémi Buisson, Selma Masri, Noritaka Adachi, Katheryn Meek, Nicholas R Pannunzio","doi":"10.21203/rs.3.rs-6317145/v1","DOIUrl":"10.21203/rs.3.rs-6317145/v1","url":null,"abstract":"<p><p>Topoisomerase 2 (Top2) poisons are widely used in cancer therapy but are associated with toxicity and secondary malignancies. Removing Top2 adducts requires endonuclease activity and repair by non-homologous end joining (NHEJ). We show that the NHEJ enzyme Artemis is a promising target for co-treatment with Top2 poisons. Inhibition of the Artemis activator, DNA-PKcs, with peposertib (M3814) sensitizes B cells to Top2 poisons while ATM or ATR inhibition does not. Interestingly, while M3814 treatment blocks Artemis endonuclease activity, Artemis phosphorylation is still detectible and is only affected upon inhibiting ATM, suggestive of an additional role for Artemis in DNA damage response signaling. Additionally, Artemis loss results in a significant accumulation of Top2 DNA adducts following treatment, indicating Artemis may act outside its canonical role in NHEJ to reduce adduct burden. Clinical data demonstrates that high Artemis expression correlates with poor survival in several cancers, and we demonstrate that Artemis function is critical for survival following combination drug treatment. These insights can be leveraged to unlock new avenues for the treatment of aggressive cancers by enhancing the cytotoxicity of agents through blockade of DNA break repair.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532632","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":"Back to the Future: Predicting Individual Tau Progression in Alzheimer's Disease.","authors":"Robin Sandell, Justin Torok, Kamalini G Ranasinghe, Srikantan S Nagarajan, Ashish Raj","doi":"10.21203/rs.3.rs-6772220/v1","DOIUrl":"10.21203/rs.3.rs-6772220/v1","url":null,"abstract":"<p><p>Alzheimer's Disease (AD) is characterized by the spread of tau neurofibrillary tangles along the brain's structural network. The marked variability in pathology spread patterns across individuals necessitates a precision medicine approach. Here we introduce Stage-based Network Diffusion (StaND), a novel algorithm that combines statistical staging with biophysical modeling to predict patient-specific tau progression. Using data from 650 subjects in the Alzheimer's Disease Neuroimaging Initiative, StaND first estimates each subject's disease stage and then infers their individual tau seeding pattern, agglomeration rate, and transmission rate. The model is applied forward in time to predict regional tau distributions cross-sectionally and longitudinally. StaND outperforms benchmark models in both instances. Inferred tau seed patterns capture spatial heterogeneity, while rate parameters explain temporal and cognitive variability. Despite diverse initial seeding patterns, tau distributions converge across subjects over time. We also identify two distinct tau seeding archetypes with distinct clinical and demographic profiles. StaND offers a powerful new approach for understanding and forecasting the spatiotemporal dynamics of AD and is widely applicable to other neurodegenerative diseases.</p>","PeriodicalId":519972,"journal":{"name":"Research square","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12204357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532590","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}