CMUNeXt: An Efficient Medical Image Segmentation Network based on Large Kernel and Skip Fusion

The U-shaped architecture has emerged as a crucial paradigm in the design of medical image segmentation networks. However, due to the inherent local limitations of convolution, a fully convolutional segmentation network with U-shaped architecture struggles to effectively extract global context information, which is vital for the precise localization of lesions. While hybrid architectures combining CNNs and Transformers can address these issues, their application in real medical scenarios is limited due to the computational resource constraints imposed by the environment and edge devices. In addition, the convolutional inductive bias in lightweight networks adeptly fits the scarce medical data, which is lacking in the Transformer based network. In order to extract global context information while taking advantage of the inductive bias, we propose CMUNeXt, an efficient fully convolutional lightweight medical image segmentation network, which enables fast and accurate auxiliary diagnosis in real scene scenarios. CMUNeXt leverages large kernel and inverted bottleneck design to thoroughly mix distant spatial and location information, efficiently extracting global context information. We also introduce the Skip-Fusion block, designed to enable smooth skip-connections and ensure ample feature fusion. Experimental results on multiple medical image datasets demonstrate that CMUNeXt outperforms existing heavyweight and lightweight medical image segmentation networks in terms of segmentation performance, while offering a faster inference speed, lighter weights, and a reduced computational cost. The code is available at https://github.com/FengheTan9/CMUNeXt.Comment: 8 pages, 3 figure

Augmented reality in medical education: a systematic review

Introduction: The field of augmented reality (AR) is rapidly growing with many new potential applications in medical education. This systematic review investigated the current state of augmented reality applications (ARAs) and developed an analytical model to guide future research in assessing ARAs as teaching tools in medical education. Methods: A literature search was conducted using PubMed, Embase, Web of Science, Cochrane Library, and Google Scholar. This review followed PRISMA guidelines and included publications from January 1, 2000 to June 18, 2018. Inclusion criteria were experimental studies evaluating ARAs implemented in healthcare education published in English. Our review evaluated study quality and determined whether studies assessed ARA validity using criteria established by the GRADE Working Group and Gallagher et al., respectively. These findings were used to formulate an analytical model to assess the readiness of ARAs for implementation in medical education. Results: We identified 100,807 articles in the initial literature search; 36 met inclusion criteria for final review and were categorized into three categories: Surgery (23), Anatomy (9), and Other (4). The overall quality of the studies was poor and no ARA was tested for all five stages of validity. Our analytical model evaluates the importance of research quality, application content, outcomes, and feasibility of an ARA to gauge its readiness for implementation. Conclusion: While AR technology is growing at a rapid rate, the current quality and breadth of AR research in medical training is insufficient to recommend the adoption into educational curricula. We hope our analytical model will help standardize AR assessment methods and define the role of AR technology in medical education

Environmental controls, emergent scaling, and predictions of greenhouse gas (GHG) fluxes in coastal salt marshes

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 123 (2018): 2234-2256, doi:10.1029/2018JG004556.Coastal salt marshes play an important role in mitigating global warming by removing atmospheric carbon at a high rate. We investigated the environmental controls and emergent scaling of major greenhouse gas (GHG) fluxes such as carbon dioxide (CO2) and methane (CH4) in coastal salt marshes by conducting data analytics and empirical modeling. The underlying hypothesis is that the salt marsh GHG fluxes follow emergent scaling relationships with their environmental drivers, leading to parsimonious predictive models. CO2 and CH4 fluxes, photosynthetically active radiation (PAR), air and soil temperatures, well water level, soil moisture, and porewater pH and salinity were measured during May–October 2013 from four marshes in Waquoit Bay and adjacent estuaries, MA, USA. The salt marshes exhibited high CO2 uptake and low CH4 emission, which did not significantly vary with the nitrogen loading gradient (5–126 kg · ha−1 · year−1) among the salt marshes. Soil temperature was the strongest driver of both fluxes, representing 2 and 4–5 times higher influence than PAR and salinity, respectively. Well water level, soil moisture, and pH did not have a predictive control on the GHG fluxes, although both fluxes were significantly higher during high tides than low tides. The results were leveraged to develop emergent power law‐based parsimonious scaling models to accurately predict the salt marsh GHG fluxes from PAR, soil temperature, and salinity (Nash‐Sutcliffe Efficiency = 0.80–0.91). The scaling models are available as a user‐friendly Excel spreadsheet named Coastal Wetland GHG Model to explore scenarios of GHG fluxes in tidal marshes under a changing climate and environment.National Oceanic and Atmospheric Administration Grant Numbers: NA09NOS4190153, NA14NOS4190145; National Science Foundation (NSF) Grant Numbers: 1705941, 1561941/1336911; USGS LandCarbon Program; NOAA National Estuarine Research Reserve Science Collaborative Grant Number: NA09NOS4190153 and NA14NOS41901452019-01-2

Soil carbon consequences of historic hydrologic impairment and recent restoration in coastal wetlands

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Eagle, M. J., Kroeger, K. D., Spivak, A. C., Wang, F., Tang, J., Abdul-Aziz, O. I., Ishtiaq, K. S., O’Keefe Suttles, J., & Mann, A. G. Soil carbon consequences of historic hydrologic impairment and recent restoration in coastal wetlands. The Science of the Total Environment, 848, (2022): 157682, https://doi.org/10.1016/j.scitotenv.2022.157682.Coastal wetlands provide key ecosystem services, including substantial long-term storage of atmospheric CO2 in soil organic carbon pools. This accumulation of soil organic matter is a vital component of elevation gain in coastal wetlands responding to sea-level rise. Anthropogenic activities that alter coastal wetland function through disruption of tidal exchange and wetland water levels are ubiquitous. This study assesses soil vertical accretion and organic carbon accretion across five coastal wetlands that experienced over a century of impounded hydrology, followed by restoration of tidal exchange 5 to 14 years prior to sampling. Nearby marshes that never experienced tidal impoundment served as controls with natural hydrology to assess the impact of impoundment and restoration. Dated soil cores indicate that elevation gain and carbon storage were suppressed 30–70 % during impoundment, accounting for the majority of elevation deficit between impacted and natural sites. Only one site had substantial subsidence, likely due to oxidation of soil organic matter. Vertical and carbon accretion gains were achieved at all restored sites, with carbon burial increasing from 96 ± 33 to 197 ± 64 g C m−2 y−1. The site with subsidence was able to accrete at double the rate (13 ± 5.6 mm y−1) of the natural complement, due predominantly to organic matter accumulation rather than mineral deposition, indicating these ecosystems are capable of large dynamic responses to restoration when conditions are optimized for vegetation growth. Hydrologic restoration enhanced elevation resilience and climate benefits of these coastal wetlands.This project was supported by the U.S. Geological Survey Coastal and Marine Hazards and Resources Program and the USGS Land Change Science Program's LandCarbon program, NOAA National Estuarine Research Reserve Science Collaborative NA14NOS4190145, and MIT Sea Grant 2015-R/RC-141. Contributions of Abdul-Aziz were also supported by NSF CBET Environmental Sustainability Award No. 1705941. Our stakeholder partners, including the Cape Cod National Seashore, Waquoit Bay National Estuarine Research Reserve, and the Bringing Wetlands to Market project team, and Towns and Conservation Commissions, including Eastham, Barnstable, Brewster, Yarmouth, Denis, Sandwich and Orleans, were instrumental in providing research support and site access

The interplay of growth differentiation factor 15 (GDF15) expression and M2 macrophages during prostate carcinogenesis

M2 (tumor-supportive) macrophages may upregulate growth differentiation factor 15 (GDF15), which is highly expressed in prostate tumors, but the combined utility of these markers as prognostic biomarkers are unclear. We retrospectively studied 90 prostate cancer cases that underwent radical prostatectomy as their primary treatment and were followed for biochemical recurrence (BCR). These cases also had a benign prostate biopsy at least 1 year or more before their prostate cancer surgery. Using computer algorithms to analyze digitalized immunohistochemically stained slides, GDF15 expression and the presence of M2 macrophages based on the relative density of CD204- and CD68-positive macrophages were measured in prostate: (i) benign biopsy, (ii) cancer and (iii) tumor-adjacent benign (TAB) tissue. Both M2 macrophages (P = 0.0004) and GDF15 (P \u3c 0.0001) showed significant inter-region expression differences. Based on a Cox proportional hazards model, GDF15 expression was not associated with BCR but, in men where GDF15 expression differences between cancer and TAB were highest, the risk of BCR was significantly reduced (hazard ratio = 0.26; 95% confidence interval = 0.09-0.94). In addition, cases with high levels of M2 macrophages in prostate cancer had almost a 5-fold increased risk of BCR (P = 0.01). Expression of GDF15 in prostate TAB was associated with M2 macrophage levels in both prostate cancer and TAB and appeared to moderate M2-macrophage-associated BCR risk. In summary, the relationship of GDF15 expression and CD204-positive M2 macrophage levels is different in a prostate tumor environment compared with an earlier benign biopsy and, collectively, these markers may predict aggressive disease

Racial differences in the systemic inflammatory response to prostate cancer

Systemic inflammation may increase risk for prostate cancer progression, but the role it plays in prostate cancer susceptibility is unknown. From a cohort of over 10,000 men who had either a prostate biopsy or transurethral resection that yielded a benign finding, we analyzed 517 incident prostate cancer cases identified during follow-up and 373 controls with one or more white blood cell tests during a follow-up period between one and 18 years. Multilevel, multivariable longitudinal models were fit to two measures of systemic inflammation, neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR), to determine NLR and MLR trajectories associated with increased risk for prostate cancer. For both measures, we found no significant differences in the trajectories by case/control status, however in modeling NLR trajectories there was a significant interaction between race (white or Black and case-control status. In race specific models, NLR and MLR values were consistently higher over time among white controls than white cases while case-control differences in NLR and MLR trajectories were not apparent among Black men. When cases were classified as aggressive as compared to non-aggressive, the case-control differences in NLR and MLR values over time among white men were most apparent for non-aggressive cases. For NLR among white men, significant case-control differences were observed for the entire duration of observation for men who had inflammation in their initial prostate specimen. It is possible that, among white men, monitoring of NLR and MLR trajectories after an initial negative biopsy may be useful in monitoring prostate cancer risk

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure

Carbon Dioxide Fluxes Reflect Plant Zonation and Belowground Biomass in a Coastal Marsh

Coastal wetlands are major global carbon sinks; however, they are heterogeneous and dynamic ecosystems. To characterize spatial and temporal variability in a New England salt marsh, greenhouse gas (GHG) fluxes were compared among major plant-defined zones during growing seasons. Carbon dioxide (CO2) and methane (CH4) fluxes were compared in two mensurative experiments during summer months (2012–2014) that included low marsh (Spartina alterniflora), high marsh (Distichlis spicata and Juncus gerardiidominated), invasive Phragmites australis zones, and unvegetated ponds. Day- and nighttime fluxes were also contrasted in the native marsh zones. N2O fluxes were measured in parallel with CO2 and CH4 fluxes, but were not found to be significant. To test the relationships of CO2 and CH4 fluxes with several native plant metrics, a multivariate nonlinear model was used. Invasive P. australis zones (−7 to −15 μmol CO2·m−2·s−1) and S. alterniflora low marsh zones (up to −14 μmol CO2·m−2·s−1) displayed highest average CO2 uptake rates, while those in the native high marsh zone (less than −2 μmol CO2·m−2·s−1) were much lower. Unvegetated ponds were typically small sources of CO2 to the atmosphere (\u3c0.5 μmol CO2·m−2·s−1). Nighttime emissions of CO2 averaged only 35% of daytime uptake in the low marsh zone, but they exceeded daytime CO2 uptake by up to threefold in the native high marsh zone. Based on modeling, belowground biomass was the plant metric most strongly correlated with CO2 fluxes in native marsh zones, while none of the plant variables correlated significantly with CH4 fluxes. Methane fluxes did not vary between day and night and did not significantly offset CO2 uptake in any vegetated marsh zones based on sustained global warming potential calculations. These findings suggest that attention to spatial zonation as well as expanded measurements and modeling of GHG emissions across greater temporal scales will help to improve accuracy of carbon accounting in coastal marshe

Carbon Dioxide Fluxes Reflect Plant Zonation and Belowground Biomass in a Coastal Marsh

Coastal wetlands are major global carbon sinks; however, they are heterogeneous and dynamic ecosystems. To characterize spatial and temporal variability in a New England salt marsh, greenhouse gas (GHG) fluxes were compared among major plant-defined zones during growing seasons. Carbon dioxide (CO2) and methane (CH4) fluxes were compared in two mensurative experiments during summer months (2012–2014) that included low marsh (Spartina alterniflora), high marsh (Distichlis spicata and Juncus gerardiidominated), invasive Phragmites australis zones, and unvegetated ponds. Day- and nighttime fluxes were also contrasted in the native marsh zones. N2O fluxes were measured in parallel with CO2 and CH4 fluxes, but were not found to be significant. To test the relationships of CO2 and CH4 fluxes with several native plant metrics, a multivariate nonlinear model was used. Invasive P. australis zones (−7 to −15 μmol CO2·m−2·s−1) and S. alterniflora low marsh zones (up to −14 μmol CO2·m−2·s−1) displayed highest average CO2 uptake rates, while those in the native high marsh zone (less than −2 μmol CO2·m−2·s−1) were much lower. Unvegetated ponds were typically small sources of CO2 to the atmosphere (\u3c0.5 μmol CO2·m−2·s−1). Nighttime emissions of CO2 averaged only 35% of daytime uptake in the low marsh zone, but they exceeded daytime CO2 uptake by up to threefold in the native high marsh zone. Based on modeling, belowground biomass was the plant metric most strongly correlated with CO2 fluxes in native marsh zones, while none of the plant variables correlated significantly with CH4 fluxes. Methane fluxes did not vary between day and night and did not significantly offset CO2 uptake in any vegetated marsh zones based on sustained global warming potential calculations. These findings suggest that attention to spatial zonation as well as expanded measurements and modeling of GHG emissions across greater temporal scales will help to improve accuracy of carbon accounting in coastal marshe