Communications medicine最新文献

{"title":"Understanding and mitigating the impact of race with adversarial autoencoders","authors":"Kathryn Sarullo, S. Joshua Swamidass","doi":"10.1038/s43856-024-00627-3","DOIUrl":"10.1038/s43856-024-00627-3","url":null,"abstract":"Artificial intelligence carries the risk of exacerbating some of our most challenging societal problems, but it also has the potential of mitigating and addressing these problems. The confounding effects of race on machine learning is an ongoing subject of research. This study aims to mitigate the impact of race on data-derived models, using an adversarial variational autoencoder (AVAE). In this study, race is a self-reported feature. Race is often excluded as an input variable, however, due to the high correlation between race and several other variables, race is still implicitly encoded in the data. We propose building a model that (1) learns a low dimensionality latent spaces, (2) employs an adversarial training procedure that ensure its latent space does not encode race, and (3) contains necessary information for reconstructing the data. We train the autoencoder to ensure the latent space does not indirectly encode race. In this study, AVAE successfully removes information about race from the latent space (AUC ROC = 0.5). In contrast, latent spaces constructed using other approaches still allow the reconstruction of race with high fidelity. The AVAE’s latent space does not encode race but conveys important information required to reconstruct the dataset. Furthermore, the AVAE’s latent space does not predict variables related to race (R2 = 0.003), while a model that includes race does (R2 = 0.08). Though we constructed a race-independent latent space, any variable could be similarly controlled. We expect AVAEs are one of many approaches that will be required to effectively manage and understand bias in ML. Computer models used in healthcare can sometimes be biased based on race, leading to unfair outcomes. Our study focuses on understanding and reducing the impact of self-reported race in computer models that learn from data. We use a model called an Adversarial Variational Autoencoder (AVAE), which helps ensure that the models don’t accidentally use race in their calculations. The AVAE technique creates a simplified version of the data, called a latent space, that leaves out race information but keeps other important details needed for accurate predictions. Our results show that this approach successfully removes race information from the models while still allowing them to work well. This method is one of many steps needed to address bias in computer learning and ensure fairer outcomes. Our findings highlight the importance of developing tools that can manage and understand bias, contributing to more equitable and trustworthy technology. Sarullo and Swamidass use an adversarial variational autoencoder (AVAE) to remove race information from computer models while retaining essential data for accurate predictions, effectively reducing bias. This approach highlights the importance of developing tools to manage bias, ensuring fairer and more trustworthy technology.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496710/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142514037","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":"Oral and gut microbiome profiles in people with early idiopathic Parkinson’s disease","authors":"Keaton Stagaman, Matthew J. Kmiecik, Madeleine Wetzel, Stella Aslibekyan, Teresa Filshtein Sonmez, Pierre Fontanillas, 23andMe Research Team, Joyce Tung, Michael V. Holmes, Seth T. Walk, Madelyn C. Houser, Lucy Norcliffe-Kaufmann","doi":"10.1038/s43856-024-00630-8","DOIUrl":"10.1038/s43856-024-00630-8","url":null,"abstract":"Early detection of Parkinson’s disease (PD), a neurodegenerative disease with central and peripheral nerve involvement, ensures timely treatment access. Microbes influence nervous system health and are altered in PD. We examined gut and mouth microbiomes from recently diagnosed patients in a geographically diverse, matched case-control, shotgun metagenomics study. Here, we show greater alpha-diversity in 445 PD patients versus 221 controls. The microbial signature of PD includes overabundance of 16 OTUs, including Streptococcus mutans and Bifidobacterium dentium, and depletion of 28 OTUs. Machine learning models indicate that subspecies level oral microbiome abundances best distinguish PD with reasonably high accuracy (area under the curve: 0.758). Microbial networks are disrupted in cases, with reduced connectivity between short-chain fatty acid-producing bacteria the the gut. Importantly, microbiome diversity metrics are associated with non-motor autonomic symptom severity. Our results provide evidence that predictive oral PD microbiome signatures could possibly be used as biomarkers for the early detection of PD, particularly when there is peripheral nervous system involvement. Stagaman et al. investigate the associations between early idiopathic Parkinson’s disease (PD) and the diversity and composition of both saliva and stool microbiomes in a large, geographically diverse US cohort. Abundances of saliva microbes, particularly Prevotella, Neisseria, and Streptococcus OTUs, best distinguish between controls and cases. Parkinson’s disease (PD) is a neurodegenerative disease that is characterized by both motor symptoms, such as tremors, and non-motor symptoms, such as constipation. Our aim was to determine whether there were differences in the number and types of microbes living in the saliva and intestines of people with and without PD. We saw significant differences in the microbial communities living in healthy controls compared to people with PD. Additionally, we found that the proportions of microbe types in saliva were the best at distinguishing between controls and cases, and identified the specific kinds of microbes that were driving this distinction. These results highlight the potential importance of the saliva microbiome in understanding the causes and symptomatology of PD.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11499922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142514036","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 click-based electrocorticographic brain-computer interface enables long-term high-performance switch scan spelling","authors":"Daniel N. Candrea, Samyak Shah, Shiyu Luo, Miguel Angrick, Qinwan Rabbani, Christopher Coogan, Griffin W. Milsap, Kevin C. Nathan, Brock A. Wester, William S. Anderson, Kathryn R. Rosenblatt, Alpa Uchil, Lora Clawson, Nicholas J. Maragakis, Mariska J. Vansteensel, Francesco V. Tenore, Nicolas F. Ramsey, Matthew S. Fifer, Nathan E. Crone","doi":"10.1038/s43856-024-00635-3","DOIUrl":"10.1038/s43856-024-00635-3","url":null,"abstract":"Brain-computer interfaces (BCIs) can restore communication for movement- and/or speech-impaired individuals by enabling neural control of computer typing applications. Single command click detectors provide a basic yet highly functional capability. We sought to test the performance and long-term stability of click decoding using a chronically implanted high density electrocorticographic (ECoG) BCI with coverage of the sensorimotor cortex in a human clinical trial participant (ClinicalTrials.gov, NCT03567213) with amyotrophic lateral sclerosis. We trained the participant’s click detector using a small amount of training data (<44 min across 4 days) collected up to 21 days prior to BCI use, and then tested it over a period of 90 days without any retraining or updating. Using a click detector to navigate a switch scanning speller interface, the study participant can maintain a median spelling rate of 10.2 characters per min. Though a transient reduction in signal power modulation can interrupt usage of a fixed model, a new click detector can achieve comparable performance despite being trained with even less data (<15 min, within 1 day). These results demonstrate that a click detector can be trained with a small ECoG dataset while retaining robust performance for extended periods, providing functional text-based communication to BCI users. Amyotrophic lateral sclerosis (ALS) is a progressive disease of the nervous system that causes muscle weakness and leads to paralysis. People living with ALS therefore struggle to communicate with family and caregivers. We investigated whether the brain signals of a participant with ALS could be used to control a spelling application. Specifically, when the participant attempted a grasping movement, a computer method detected increased brain signals from electrodes implanted on the surface of his brain, and thereby generated a mouse-click. The participant clicked on letters or words from a spelling application to type sentences. Our method was trained using 44 min’ worth of brain signals and performed reliably for three months without any retraining. This approach can potentially be used to restore communication to other severely paralyzed individuals over an extended time period and after only a short training period. Candrea et al. develop a brain-computer interface click detection algorithm using electrocorticographic signals. Using this click detector, a clinical trial participant with amyotrophic lateral sclerosis was able to control a switch-scanning spelling application and achieve high rates of spelling without model retraining.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494178/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482293","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":"Advanced three-dimensional X-ray imaging unravels structural development of the human thymus compartments","authors":"Savvas Savvidis, Roberta Ragazzini, Valeria Conde de Rafael, J. Ciaran Hutchinson, Lorenzo Massimi, Fabio A. Vittoria, Sara Campinoti, Tom Partridge, Olumide K. Ogunbiyi, Alessia Atzeni, Neil J. Sebire, Paolo De Coppi, Alberto Mittone, Alberto Bravin, Paola Bonfanti, Alessandro Olivo","doi":"10.1038/s43856-024-00623-7","DOIUrl":"10.1038/s43856-024-00623-7","url":null,"abstract":"The thymus, responsible for T cell-mediated adaptive immune system, has a structural and functional complexity that is not yet fully understood. Until now, thymic anatomy has been studied using histological thin sections or confocal microscopy 3D reconstruction, necessarily for limited volumes. We used Phase Contrast X-Ray Computed Tomography to address the lack of whole-organ volumetric information on the microarchitecture of its structural components. We scanned 15 human thymi (9 foetal and 6 postnatal) with synchrotron radiation, and repeated scans using a conventional laboratory x-ray system. We used histology, immunofluorescence and flow cytometry to validate the x-ray findings. Application to human thymi at pre- and post-natal stages allowed reliable tracking and quantification of the evolution of parameters such as size and distribution of Hassall’s Bodies and medulla-to-cortex ratio, whose changes reflect adaptation of thymic activity. We show that Hassall’s bodies can occupy 25% of the medulla volume, indicating they should be considered a third thymic compartment with possible implications on their role. Moreover, we demonstrate compatible results can be obtained with standard laboratory-based x-ray equipment, making this research tool accessible to a wider community. Our study allows overcoming the resolution and/or volumetric limitations of existing approaches for the study of thymic disfunction in congenital and acquired disorders affecting the adaptive immune system. The thymus is the organ responsible for programming the immune system. It consists of two main compartments, named medulla and cortex. The medulla contains onion-shaped parts known as “Hassall’s bodies”. By imaging thymi at different stages of development with advanced x-ray methods, we gain understanding of changes that occur over time in 3D. We quantified how much of the thymus was occupied by these different components as they change with age, showing that Hassall’s bodies can take up 25% of the medulla, and should therefore be considered a proper part of the thymus with a purpose. Having a better understanding of the thymus can prove important in targeting conditions such as Down syndrome and thymic tumours, as well as provide information about structure. Savvidis et al. present x-ray 3D imaging visualizing the internal anatomy of the human thymus across developmental stages. Quantification and evolution of Hassall’s bodies and medulla-to-cortex ratio, indicate they should be considered a third compartment of the thymic anatomy.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142514025","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":"Biomarkers and point of care screening approaches for the management of preeclampsia","authors":"Ka Wai Ng, Nandita Chaturvedi, Gerard L. Coté, Stephanie A. Fisher, Samuel Mabbott","doi":"10.1038/s43856-024-00642-4","DOIUrl":"10.1038/s43856-024-00642-4","url":null,"abstract":"Preeclampsia is a multi-organ pregnancy complication, that is primarily detected when pregnant people have high blood pressure, and is confirmed by testing for the presence of protein in the urine. While more specific and accurate diagnostic and imaging tests are becoming available, they are still in the process of undergoing widespread regulatory adoption, and so are not yet the standard of care. Since biochemical processes are a precursor to the systemic progression of disease, we review some established, emerging, and promising biomarkers that are proposed to be associated with preeclampsia, and newly developed approaches for screening them at the point of care, to reduce the burden of the disease. Ng, Chaturvedi et al. discuss established, emerging, and promising biomarkers related to preeclampsia. They highlight novel approaches for screening these biomarkers at the point of care, aiming to democratize testing and reduce the burden of the disease.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482296","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":"High-resolution modeling and projection of heat-related mortality in Germany under climate change","authors":"Junyu Wang, Nikolaos Nikolaou, Matthias an der Heiden, Christopher Irrgang","doi":"10.1038/s43856-024-00643-3","DOIUrl":"10.1038/s43856-024-00643-3","url":null,"abstract":"Heat has become a leading cause of preventable deaths during summer. Understanding the link between high temperatures and excess mortality is crucial for designing effective prevention and adaptation plans. Yet, data analyses are challenging due to often fragmented data archives over different agglomeration levels. Using Germany as a case study, we develop a multi-scale machine learning model to estimate heat-related mortality with variable temporal and spatial resolution. This approach allows us to estimate heat-related mortality at different scales, such as regional heat risk during a specific heatwave, annual and nationwide heat risk, or future heat risk under climate change scenarios. We estimate a total of 48,000 heat-related deaths in Germany during the last decade (2014–2023), and the majority of heat-related deaths occur during specific heatwave events. Aggregating our results over larger regions, we reach good agreement with previously published reports from Robert Koch Institute (RKI). In 2023, the heatwave of July 7–14 contributes approximately 1100 cases (28%) to a total of approximately 3900 heat-related deaths for the whole year. Combining our model with shared socio-economic pathways (SSPs) of future climate change provides evidence that heat-related mortality in Germany could further increase by a factor of 2.5 (SSP245) to 9 (SSP370) without adaptation to extreme heat under static sociodemographic developments assumptions. Our approach is a valuable tool for climate-driven public health strategies, aiding in the identification of local risks during heatwaves and long-term resilience planning. Heat is becoming a major cause of preventable deaths during the summer. We developed a computer model to estimate heat-related deaths at specific times and in different districts. Using this model for Germany, we estimate that over the past decade (2014–2023), around 48,000 deaths were heat-related, with most occurring during heatwaves. For example, a heatwave from July 7–14, 2023, contributed to 1100 out of 3900 heat-related deaths that year. Our model also suggests that, without adaptation, heat-related deaths in Germany could increase remarkably due to climate change. The insights from our model can help identify areas at high risk and support long-term public health planning to reduce the impact of heatwaves. Wang et al. developed a multi-scale machine learning model with high spatial and temporal resolution to estimate heat-related mortality in Germany. The model indicates that 48,000 deaths between 2014 and 2023 were heat related, and, without adaptation, climate change could increase heat-related mortality by 2.5 to 9 times by 2100.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482297","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":"Author Correction: Mpox virus infection in women and outbreak sex disparities: A Systematic Review and Meta-analysis","authors":"Prakasini Satapathy, Muhammad Aaqib Shamim, Bijaya K. Padhi, Aravind P. Gandhi, Mokanpally Sandeep, Tarun Kumar Suvvari, Jogender Kumar, Gunjeet Kaur, Joshuan J. Barboza, Patricia Schlagenhauf, Ranjit Sah","doi":"10.1038/s43856-024-00640-6","DOIUrl":"10.1038/s43856-024-00640-6","url":null,"abstract":"","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11490540/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482295","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 convolutional attention model for predicting response to chemo-immunotherapy from ultrasound elastography in mouse tumor models","authors":"Chrysovalantis Voutouri, Demetris Englezos, Constantinos Zamboglou, Iosif Strouthos, Giorgos Papanastasiou, Triantafyllos Stylianopoulos","doi":"10.1038/s43856-024-00634-4","DOIUrl":"10.1038/s43856-024-00634-4","url":null,"abstract":"In the era of personalized cancer treatment, understanding the intrinsic heterogeneity of tumors is crucial. Despite some patients responding favorably to a particular treatment, others may not benefit, leading to the varied efficacy observed in standard therapies. This study focuses on the prediction of tumor response to chemo-immunotherapy, exploring the potential of tumor mechanics and medical imaging as predictive biomarkers. We have extensively studied “desmoplastic” tumors, characterized by a dense and very stiff stroma, which presents a substantial challenge for treatment. The increased stiffness of such tumors can be restored through pharmacological intervention with mechanotherapeutics. We developed a deep learning methodology based on shear wave elastography (SWE) images, which involved a convolutional neural network (CNN) model enhanced with attention modules. The model was developed and evaluated as a predictive biomarker in the setting of detecting responsive, stable, and non-responsive tumors to chemotherapy, immunotherapy, or the combination, following mechanotherapeutics administration. A dataset of 1365 SWE images was obtained from 630 tumors from our previous experiments and used to train and successfully evaluate our methodology. SWE in combination with deep learning models, has demonstrated promising results in disease diagnosis and tumor classification but their potential for predicting tumor response prior to therapy is not yet fully realized. We present strong evidence that integrating SWE-derived biomarkers with automatic tumor segmentation algorithms enables accurate tumor detection and prediction of therapeutic outcomes. This approach can enhance personalized cancer treatment by providing non-invasive, reliable predictions of therapeutic outcomes. Voutouri, Englezos et al. present a convolutional attention model utilizing ultrasound elastography for predicting chemo-immunotherapy responses in mouse tumors. Through training optimization on a large number of images, this approach highlights the potential of combining shear wave elastography with deep learning to enhance personalized cancer treatment. In personalized cancer treatment, it is important to understand that not all tumors respond the same way to therapy. While some patients may benefit from a particular treatment, others may not, leading to different outcomes. This study focuses on predicting how tumors will respond to a combination of chemotherapy and immunotherapy. Specifically, we looked at difficult-to-treat tumors with very stiff structures. These tumors can be softened with certain drugs making them more responsive to treatment. We developed a computer method to analyze medical images that measure the stiffness of tumors. Our method was trained on a large set of tumor images and was able to predict how well a tumor would respond to treatment. Overall, this approach could improve personalized cancer treatment using non-invasive medical imaging to predi","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11487255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482294","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":"Impacts of testing and immunity acquired through vaccination and infection on covid-19 cases in Massachusetts elementary and secondary students","authors":"Westyn Branch-Elliman, Melissa Zeynep Ertem, Richard E. Nelson, Anseh Danesharasteh, David Berlin, Lloyd Fisher, Elissa M. Schechter-Perkins","doi":"10.1038/s43856-024-00619-3","DOIUrl":"10.1038/s43856-024-00619-3","url":null,"abstract":"During the 2021–22 academic year, Massachusetts supported several in-school testing programs to facilitate in-person learning. Additionally, COVID-19 vaccines became available to all school-aged children and many were infected with SARS-CoV-2. There are limited studies evaluating the impacts of these testing programs on SARS-CoV-2 cases in elementary and secondary school settings. The aim of this state-wide, retrospective cohort study was to assess the impact of testing programs and immunity on SARS-CoV-2 case rates in elementary and secondary students. Community-level vaccination and cumulative incidence rates were combined with data about participation in and results of in-school testing programs (test-to-stay, pooled surveillance testing). School-level impacts of surveillance testing programs on SARS-CoV-2 cases in students were estimated using generalized estimating equations within a target trial emulation approach stratified by school type (elementary/middle/high). Impacts of immunity and vaccination were estimated using random effects linear regression. Here we show that among N = 652,353 students at 2141 schools participating in in-school testing programs, surveillance testing is associated with a small but measurable decrease in in-school positivity rates. During delta, pooled testing positivity rates are higher in communities with higher cumulative incidence of infection. During omicron, when immunity from prior infection became more prevalent, the effect reversed, such that communities with lower burden of infection during the earlier phases of the pandemic had higher infection rates. Testing programs are an effective strategy for supporting in-person learning. Fluctuating levels of immunity acquired via natural infection or vaccination are a major determinant of SARS-CoV-2 cases in schools. During the height of the Covid-19 pandemic, multiple strategies were used to enable students to participate in in-person elementary and secondary schools. Little is known about the overall impact of prior immunity and in-person testing programs on the ability to maintain protection from Covid-19 in schools. This study, conducted in Massachusetts during the 2021-2022 academic year, found that community immunity gained through prior infection or vaccination, combined with testing strategies including testing programs to monitor infection and test to-stay modified quarantine programs, were safe and effective for allowing in-person learning. These data can be used to shape policy about in-school practices during future respiratory virus pandemics. Branch-Elliman et. al assess the impact of testing programs and immunity on SARS-CoV-2 case rates in elementary and secondary students in Massachusetts. They find that testing strategies are an effective intervention for supporting in-person learning and that immunity acquired from natural infection or vaccination mitigate COVID cases in schools.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43856-024-00619-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443638","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":"Evaluation of an engineered vascular graft exhibiting somatic growth in lambs to model repair of absent pulmonary artery branch","authors":"Zeeshan H. Syedain, Matthew Lahti, Gurumurthy Hiremath, James Berry, John P. Carney, Jill Schappa Faustich, Tate Shannon, Andrea Rivera, Hadi Wiputra, Zhitian Shi, Richard Bianco, Robroy MacIver, John E. Mayer, Robert T. Tranquillo","doi":"10.1038/s43856-024-00614-8","DOIUrl":"10.1038/s43856-024-00614-8","url":null,"abstract":"Growth is the holy grail of tissue implants in pediatrics. No vascular graft currently in use for surgical repairs of congenital heart defects has somatic growth capacity. Biologically-engineered grafts (6 mm) grown from donor ovine fibroblasts in a sacrificial fibrin gel were implanted into the left pulmonary branch of 3-month old lambs for 3, 6, and 18 months. A control group of Propaten® PTFE grafts was implanted for 6 months. The engineered grafts exhibit extensive site-appropriate recellularization after only 3 months and near-normal increase of diameter from the preimplant value of 6 mm to 12.9 mm and also a doubling of length from 6.0 mm to 13.0 mm at 6 months (n = 3) associated with apparent somatic graft growth (collagen content increase of 265% over 18-month, n = 2), along with excellent hemodynamics and no calcification, in contrast to the Propaten® grafts. The left-right flow distribution is nearly 50–50 for the engineered grafts at 6 months (n = 3) compared to about 20–80 for the Propaten® grafts (n = 3), which have less than one-half the diameter, a 6-fold higher pressure gradient, and stunted vascular development downstream of the graft. The engineered grafts exhibit a stable diameter over months 12–18 when the lambs become adult sheep (n = 2). This study supports the use of these regenerative grafts with somatic growth capacity for clinical trial in patients born with a unilateral absent pulmonary artery branch, and it shows their potential for improving development of the downstream pulmonary vasculature. Blood vessel implants that are currently used to repair heart defects at birth do not grow with the child. This means that children need to have multiple open heart surgeries to replace implants with larger implants as they grow. We grew implants from a donor sheep’s skin cells, and then completely removed the cells from the graft. We then implanted the grafts in 3-month old lambs. The lambs’ cells repopulated the implants and the implants increased in size as the lambs grew. Further experiments are required first, but our preliminary findings suggest that using a similar implant in children could improve the quality of life of children with heart defects by avoiding the need for them to have multiple surgeries to replace implants as the child grows. Syedain et al. evaluate growth of biologically-engineered grafts grown from donor ovine fibroblasts in a sacrificial fibrin gel implanted into the left pulmonary branch of 3-month old lambs. The grafts exhibit extensive site-appropriate recellularization and increase in diameter and length until the lambs reach adulthood.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43856-024-00614-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439131","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}