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16 pages, 2653 KiB  
Review
Electrospun Nanofiber-Based Biosensors for Foodborne Bacteria Detection
by Haoming Yang, Song Yan and Tianxi Yang
Molecules 2024, 29(18), 4415; https://doi.org/10.3390/molecules29184415 (registering DOI) - 17 Sep 2024
Abstract
Food contamination has emerged as a significant global health concern, posing substantial challenges to the food industry. Bacteria are the primary cause of foodborne diseases. Consequently, it is crucial to develop accurate and efficient sensing platforms to detect foodborne bacteria in food products. [...] Read more.
Food contamination has emerged as a significant global health concern, posing substantial challenges to the food industry. Bacteria are the primary cause of foodborne diseases. Consequently, it is crucial to develop accurate and efficient sensing platforms to detect foodborne bacteria in food products. Among various detection methods, biosensors have emerged as a promising solution due to their portability, affordability, simplicity, selectivity, sensitivity, and rapidity. Electrospun nanofibers have gained increasing popularity in enhancing biosensor performance. These nanofibers possess a distinctive three-dimensional structure, providing a large surface area and ease of preparation. This review provides an overview of the electrospinning technique, nanofibers and nanofiber-based biosensors. It also explores their mechanisms and applications in the detection of foodborne bacteria such as Salmonella, Listeria monocytogenes (L. monocytogenes), Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and Pseudomonas putida (P. putida). Full article
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<p>Comparison of different <span class="html-italic">Salmonella</span> detection methods in milk, including culture-based method [<a href="#B13-molecules-29-04415" class="html-bibr">13</a>], immunodiffusion assay [<a href="#B14-molecules-29-04415" class="html-bibr">14</a>], RT-qPCR [<a href="#B15-molecules-29-04415" class="html-bibr">15</a>], Immunomagnetic separation–Fourier-Transform Infrared Spectroscopy (IMS-FTIR) [<a href="#B16-molecules-29-04415" class="html-bibr">16</a>], immunomagnetic separation–loop-mediated isothermal amplification–nucleic acid lateral flow strip (IMS-LAMP-NALFS) [<a href="#B17-molecules-29-04415" class="html-bibr">17</a>], voltammetric biosensor [<a href="#B18-molecules-29-04415" class="html-bibr">18</a>], and impedimetric biosensor [<a href="#B19-molecules-29-04415" class="html-bibr">19</a>], in terms of (<b>a</b>) limit of detection and (<b>b</b>) time. It shows that both biosensors demonstrate lower limit of detection and less time compared to other methods.</p>
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<p>Various morphologies of nanostructured materials range from 0 D to 3 D [<a href="#B12-molecules-29-04415" class="html-bibr">12</a>].</p>
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<p>Three basic components of a biosensor: a bioreceptor for reacting with analytes and generating biological signals, a transducer for converting the biological reactions into measurable signals, and a signal display system [<a href="#B20-molecules-29-04415" class="html-bibr">20</a>].</p>
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<p>Electrospinning setup with a plate collector and a rotary collector [<a href="#B20-molecules-29-04415" class="html-bibr">20</a>].</p>
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<p>A schematic diagram of the nanofiber membrane-based biosensor [<a href="#B21-molecules-29-04415" class="html-bibr">21</a>].</p>
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<p>(<b>a</b>) Functionalizing nanofibers through two approaches: (1) direct incorporation; and (2) surface modification [<a href="#B46-molecules-29-04415" class="html-bibr">46</a>]. In direct incorporation, new molecules and polymer solution are mixed prior to electrospinning. In surface modification, new compounds are deposited onto electrospun nanofibers. (<b>b</b>) Advantageous features of electrospun nanofibers for biosensing applications [<a href="#B10-molecules-29-04415" class="html-bibr">10</a>].</p>
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<p>(<b>a</b>) Fabrication steps of carbon nanowire biosensor for <span class="html-italic">Salmonella</span> detection [<a href="#B52-molecules-29-04415" class="html-bibr">52</a>]. (<b>b</b>) A nanofiber-based colorimetric platform for <span class="html-italic">E. coli</span> detection [<a href="#B56-molecules-29-04415" class="html-bibr">56</a>]. (<b>c</b>) Immunoelectrode fabrication by physical and chemical immobilization methods for <span class="html-italic">L. monocytogenes</span> detection [<a href="#B62-molecules-29-04415" class="html-bibr">62</a>]. (<b>d</b>) Electrospun nanofiber membranes prepared from PAN and pVDB for <span class="html-italic">S. aureus</span> and <span class="html-italic">P. putida</span> detection [<a href="#B64-molecules-29-04415" class="html-bibr">64</a>].</p>
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24 pages, 706 KiB  
Review
Cross-Disciplinary Rapid Scoping Review of Structural Racial and Caste Discrimination Associated with Population Health Disparities in the 21st Century
by Drona P. Rasali, Brendan M. Woodruff, Fatima A. Alzyoud, Daniel Kiel, Katharine T. Schaffzin, William D. Osei, Chandra L. Ford and Shanthi Johnson
Societies 2024, 14(9), 186; https://doi.org/10.3390/soc14090186 - 16 Sep 2024
Viewed by 332
Abstract
A cross-disciplinary rapid scoping review was carried out, generally following the PRISMA-SCR protocol to examine historical racial and caste-based discrimination as structural determinants of health disparities in the 21st century. We selected 48 peer-reviewed full-text articles available from the University of Memphis Libraries [...] Read more.
A cross-disciplinary rapid scoping review was carried out, generally following the PRISMA-SCR protocol to examine historical racial and caste-based discrimination as structural determinants of health disparities in the 21st century. We selected 48 peer-reviewed full-text articles available from the University of Memphis Libraries database search, focusing on three selected case-study countries: the United States (US), Canada, and Nepal. The authors read each article, extracted highlights, and tabulated the thematic contents on structural health disparities attributed to racism or casteism. The results link historical racism/casteism to health disparities occurring in Black and African American, Native American, and other ethnic groups in the US; in Indigenous peoples and other visible minorities in Canada; and in the Dalits of Nepal, a population racialized by caste, grounded on at least four foundational theories explaining structural determinants of health disparities. The evidence from the literature indicates that genetic variations and biological differences (e.g., disease prevalence) occur within and between races/castes for various reasons (e.g., random gene mutations, geographic isolation, and endogamy). However, historical races/castes as socio-cultural constructs have no inherently exclusive basis of biological differences. Disregarding genetic discrimination based on pseudo-scientific theories, genetic testing is a valuable scientific means to achieve the better health of the populations. Epigenetic changes (e.g., weathering—the early aging of racialized women) due to the DNA methylation of genes among racialized populations are markers of intergenerational trauma due to racial/caste discrimination. Likewise, chronic stresses resulting from intergenerational racial/caste discrimination cause an “allostatic load”, characterized by an imbalance of neuronal and hormonal dysfunction, leading to occurrences of chronic diseases (e.g., hypertension, diabetes, and mental health) at disproportionate rates among racialized populations. Major areas identified for reparative policy changes and interventions for eliminating the health impacts of racism/casteism include areas of issues on health disparity research, organizational structures, programs and processes, racial justice in population health, cultural trauma, equitable healthcare system, and genetic discrimination. Full article
(This article belongs to the Topic Diversity Competence and Social Inequalities)
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<p>Flowchart of the literature search strategy.</p>
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18 pages, 1515 KiB  
Article
Energy and Economic Assessment of Oxy-Fuel Combustion CO2 Capture in Coal-Fired Power Plants
by Yuyang Yuan, Lei Wang, Yaming Zhuang, Ying Wu and Xiaotao Bi
Energies 2024, 17(18), 4626; https://doi.org/10.3390/en17184626 - 15 Sep 2024
Viewed by 265
Abstract
Oxy-fuel combustion technology replaces air with a mixture of pure O2 and recycled flue gas for coal combustion, which leads to difficulties in the waste heat recovery of flue gas in the boiler tail of coal-fired power plants. This paper proposes a [...] Read more.
Oxy-fuel combustion technology replaces air with a mixture of pure O2 and recycled flue gas for coal combustion, which leads to difficulties in the waste heat recovery of flue gas in the boiler tail of coal-fired power plants. This paper proposes a new integration scheme for waste heat recovery of flue gas in coal-fired power plants with oxy-fuel combustion CO2 capture. By introducing an oxygen preheater, a recycled flue gas preheater, and a low-pressure economizer, the waste heat of flue gas is fully recovered to preheat oxygen, recycled flue gas, and feed water, respectively. The proposed scheme simultaneously ensures the safe operation of the recycled fan and improves the thermal performance of the coal-fired power plants. Compared to the air combustion configuration, the boiler’s efficiency and gross power efficiency in the oxy-fuel combustion configuration are increased by 0.42% and 1.29%, respectively. Due to power consumption for the added equipment, the net power efficiency is reduced by 10.41%. A techno-economic analysis shows that the cost of electricity for oxy-fuel combustion in coal-fired power plants has increased from USD 46.45/MWh to USD 80.18/MWh, and the cost of the CO2 avoided reaches USD 43.24/t CO2. Full article
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<p>Flow diagram of boiler system under air combustion configuration. Solid black line: coal and air; solid red line: flue gas; solid blue line: feed water; dotted blue line: steam.</p>
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<p>Flow diagram of steam/water cycle under air combustion configuration. Solid blue line: feed water; dotted blue line: steam.</p>
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<p>Simplified flowsheet for oxy-fuel combustion with flue gas recycling.</p>
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<p>Flow diagram of boiler system under oxy-fuel combustion configuration. Solid black line: coal and air; solid red line: flue gas; solid blue line: feed water; dotted blue line: steam; solid purple solid line: mixed recycled flue gas (RFG) and pure O<sub>2</sub>; solid yellow line: separation gas.</p>
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<p>Tail arrangement of boiler system under different configurations: (<b>a</b>) air combustion configuration; (<b>b</b>) oxy-fuel combustion configuration. Black line: coal and air; red line: flue gas; blue line: feed water; green line: separation gas O<sub>2</sub>; yellow line: separated gas N<sub>2</sub>.</p>
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<p>Flow diagram of steam/water cycle under oxy-fuel combustion configuration. Solid red line: flue gas; solid blue line: feedwater; dotted blue line: steam.</p>
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<p>Detailed parameters of steam/water cycle under two different configurations. Solid red line: flue gas; solid blue line: feed water; dotted blue line: steam.</p>
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15 pages, 1231 KiB  
Article
Genomic Insights into Disease Resistance in Sunflower (Helianthus annuus): Identifying Key Regions and Candidate Genes for Verticillium dahliae Resistance
by Yue Yu, Jianfeng Yang, Jian Zhang, Loren H. Rieseberg and Jun Zhao
Plants 2024, 13(18), 2582; https://doi.org/10.3390/plants13182582 - 14 Sep 2024
Viewed by 378
Abstract
Sunflower (Helianthus annuus) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. Verticillium dahliae is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, [...] Read more.
Sunflower (Helianthus annuus) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. Verticillium dahliae is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, we conducted a comprehensive assessment of sunflower resistance to V. dahliae across 231 sunflower cultivar lines, from the Sunflower Association Mapping (SAM) population. We employed EMMAX and ridge regression best linear unbiased prediction (rrBLUP) and identified 148 quantitative trait loci (QTLs) and 23 putative genes associated with V. dahliae resistance, including receptor like kinases, cell wall modification, transcriptional regulation, plant stress signalling and defense regulation genes. Our enrichment and quantitative real-time PCR validation results highlight the importance of membrane vesicle trafficking in the sunflower immune system for efficient signaling and defense upon activation by V. dahliae. This study also reveals the polygenic architecture of V. dahliae resistance in sunflowers and provides insights for breeding sunflower cultivars resistant to VW. This research contributes to ongoing efforts to enhance crop resilience and reduce yield losses due to VW, ultimately benefiting sunflower growers and the agricultural sector. Full article
(This article belongs to the Special Issue Disease Resistance Breeding of Field Crops)
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<p>Genome-wide association mapping results for 3,699,248 single-nucleotide polymorphisms (SNPs) and for 7,541,946 presence–absence variants (PAVs). Manhattan plot of SNPs (<b>a</b>) and PAVs (<b>c</b>) with −log<sub>10</sub>P &gt; 2.5; each point represents a single marker. Candidate marker threshold in black dashed horizontal lines, and candidate markers within QTLs highlighted as black points; non-candidate markers are in orange and blue. Changes in predictive ability for top markers identified with EMMAX (high −log<sub>10</sub>P) for SNPs (<b>b</b>) and PAVs (<b>d</b>). From top five to top 1000 markers (increments of five) using rrBLUP. Candidate marker threshold in black dashed vertical lines.</p>
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<p>Gene expression of Ha412HOChr08g0327051 before and after <span class="html-italic">Verticillium dahliae</span> inoculation over time using quantitative real-time PCR in three resistance categories: immune, resistant and susceptible. Results for all sunflower lines in each category (<b>a</b>) and for two selected sunflower lines in each category (<b>b</b>). <span class="html-italic">X</span>-axis represents the treatment time: 0, 1, 3, 5 and 7 dpi. <span class="html-italic">Y</span>-axis represents the gene expression levels. Different colors represent different group conditions: grey for control group, and blue, orange and light yellow for treatment in immune, resistant and susceptible lines, respectively. (<b>a</b>) Median gene expression data for five tested lines in each resistance category for the control and treatment group. Points represent the median gene expression levels at each time point, and the error bars extending from each point indicate the interquartile range, with the lower bound representing the 25th percentile and the upper bound representing the 75th percentile of the gene expression levels. (<b>b</b>) Paired gene expression in selected line over time. DIcorr stands for corrected disease index.</p>
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22 pages, 3621 KiB  
Article
Estimating Non-Stationary Extreme-Value Probability Distribution Shifts and Their Parameters Under Climate Change Using L-Moments and L-Moment Ratio Diagrams: A Case Study of Hydrologic Drought in the Goat River Near Creston, British Columbia
by Isaac Dekker, Kristian L. Dubrawski, Pearce Jones and Ryan MacDonald
Hydrology 2024, 11(9), 154; https://doi.org/10.3390/hydrology11090154 - 14 Sep 2024
Viewed by 278
Abstract
Here, we investigate the use of rolling-windowed L-moments (RWLMs) and L-moment ratio diagrams (LMRDs) combined with a Multiple Linear Regression (MLR) machine learning algorithm to model non-stationary low-flow hydrological extremes with the potential to simultaneously understand time-variant shape, scale, location, and probability distribution [...] Read more.
Here, we investigate the use of rolling-windowed L-moments (RWLMs) and L-moment ratio diagrams (LMRDs) combined with a Multiple Linear Regression (MLR) machine learning algorithm to model non-stationary low-flow hydrological extremes with the potential to simultaneously understand time-variant shape, scale, location, and probability distribution (PD) shifts under climate change. By employing LMRDs, we analyse changes in PDs and their parameters over time, identifying key environmental predictors such as lagged precipitation for September 5-day low-flows. Our findings indicate a significant relationship between total August precipitation L-moment ratios (LMRs) and September 5-day low-flow LMRs (τ2-Precipitation and τ2-Discharge: R2 = 0.675, p-values < 0.001; τ3-Precipitation and τ3-Discharge: R2 = 0.925, p-value for slope < 0.001, intercept not significant with p = 0.451, assuming α = 0.05 and a 31-year RWLM), which we later refine and use for prediction within our MLR algorithm. The methodology, applied to the Goat River near Creston, British Columbia, aids in understanding the implications of climate change on water resources, particularly for the yaqan nuʔkiy First Nation. We find that future low-flows under climate change will be outside the Natural Range of Variability (NROV) simulated from historical records (assuming a constant PD). This study provides insights that may help in adaptive water management strategies necessary to help preserve Indigenous cultural rights and practices and to help sustain fish and fish habitat into the future. Full article
(This article belongs to the Section Hydrological and Hydrodynamic Processes and Modelling)
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<p>L-moment ratio diagrams (LMRDs) for: (<b>a</b>) August total precipitation (mm) and (<b>b</b>) September 5-day low-flow (<math display="inline"><semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mn>3</mn> </msup> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>). Each panel includes the L-Coefficient of Variation (L-CV;<math display="inline"><semantics> <msub> <mi>τ</mi> <mn>2</mn> </msub> </semantics></math>) versus L-skewness (<math display="inline"><semantics> <msub> <mi>τ</mi> <mn>3</mn> </msub> </semantics></math>) and L-kurtosis versus L-skewness ratios.</p>
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<p>Relationship between L-moment ratios (LMRs) of August total precipitation (mm) and September 5-day low-flow (<math display="inline"><semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mn>3</mn> </msup> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>): (<b>a</b>) <math display="inline"><semantics> <msub> <mi>τ</mi> <mn>2</mn> </msub> </semantics></math> and (<b>b</b>) <math display="inline"><semantics> <msub> <mi>τ</mi> <mn>3</mn> </msub> </semantics></math>. <math display="inline"><semantics> <msub> <mi>τ</mi> <mn>2</mn> </msub> </semantics></math>-Precipitation and <math display="inline"><semantics> <msub> <mi>τ</mi> <mn>2</mn> </msub> </semantics></math>-Discharge: <span class="html-italic">p</span>-values &lt; 0.001; <math display="inline"><semantics> <msub> <mi>τ</mi> <mn>3</mn> </msub> </semantics></math>-Precipitation and <math display="inline"><semantics> <msub> <mi>τ</mi> <mn>3</mn> </msub> </semantics></math>-Discharge: <span class="html-italic">p</span>-value for slope &lt; 0.001, intercept not significant with <span class="html-italic">p</span> = 0.451, assuming <math display="inline"><semantics> <mi>α</mi> </semantics></math> = 0.05 and a 31-year rolling-windowed L-moments (RDLMs).</p>
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<p>Comparison of predicted and observed L-moments (LMs; testing during training) using a 31-year rolling-window. The plots display the predicted (green) and observed (blue) values for the first (<b>a</b>), second (<b>b</b>), third (<b>c</b>), and fourth (<b>d</b>) LMs. Each subplot includes the Overall Mean Squared Error (MSE) between the predicted and observed values computed by summing and averaging the best-fit model Squared Error (SE) for each step in the forward chaining process. The equations plotted alongside the model are derived from the final (best-fit) iteration (index 38), which demonstrated the lowest SE.</p>
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<p>Location, scale, and shape parameters estimated using [<a href="#B45-hydrology-11-00154" class="html-bibr">45</a>]’s method of L-moments (LMs) for the Generalized Extreme Value (GEV) probability distribution (PD) for the observed (blue) and predicted (testing during training; dashed red) LMs under a 31-year rolling-window.</p>
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<p>LMRDs using 31-year windows under two Representative Concentration Pathways (RCP) scenarios. Panels (<b>a</b>–<b>c</b>) correspond to the RCP 4.5 scenario, while panels (<b>d</b>–<b>f</b>) correspond to the RCP 8.5 scenario. Diagrams show: (<b>a</b>,<b>d</b>) L-CV/L-skewness, (<b>b</b>,<b>e</b>) L-kurtosis/L-skewness, with theoretical PDs described in [<a href="#B45-hydrology-11-00154" class="html-bibr">45</a>] (distributions include Generalized Logistic (GLO), Generalized Extreme Value (GEV), Generalized Pareto (GPA), Generalized Normal (GNO), Pearson Type III (PE3), Wakeby Lower Bound (WAK_LB), and All Distribution Lower Bound (ALL_LB)). Plots (<b>c</b>,<b>f</b>) show the distribution count for each window. The observed LMRs for the 5-day September low-flow at the Water Survey of Canada (WSC) Goat River Near Erikson Hydrometric Gauge Station (<a href="https://wateroffice.ec.gc.ca/report/data_availability_e.html?type=historical&amp;station=08NH004&amp;parameter_type=Flow&amp;wbdisable=true" target="_blank">08NH004</a>) are plotted alongside simulated future data derived from Multiple Linear Regression (MLR) driven with total August precipitation LMs. Future data are generated using a splice of six Coupled Model Intercomparison Project Phase 5 (CMIP5) series downscaled climate models (median of “ACCESS1-0”, “CanESM2”, “CCSM4”, “CNRM-CM5”, “HadGEM2-ES”, and “MPI-ESM-LR” from 2018 to 2100) downloaded using the single cell extraction tool from the Pacific Climate Impacts Consortium (<a href="https://pacificclimate.org/data/gridded-hydrologic-model-output" target="_blank">PCIC</a>). Historical climate data are downloaded from Historical Climate Data Online (HCDO) repository for the Creston station (Climate ID <a href="https://climate.weather.gc.ca/climate_data/daily_data_e.html?hlyRange=%7C&amp;dlyRange=1912-06-01%7C2017-12-31&amp;mlyRange=1912-01-01%7C2007-02-01&amp;StationID=1111&amp;Prov=BC&amp;urlExtension=_e.html&amp;searchType=stnName&amp;optLimit=yearRange&amp;StartYear=1840&amp;EndYear=2024&amp;selRowPerPage=25&amp;Line=0&amp;searchMethod=contains&amp;Month=12&amp;Day=2&amp;txtStationName=Creston&amp;timeframe=2&amp;Year=2017" target="_blank">1142160</a>; available from 1996 to 2017).</p>
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<p>Results of the L-moments (LMs) derived from Multiple Linear Regression (MLR) fit to a Generalized Extreme Value (GEV) probability distribution (PD) to produce shape, scale, and location parameters: (<b>a</b>) GEV parameters (shape, scale, and location) over 144 rolling windowed time units under Representative Concentration Pathway (RCP) 4.5 and (<b>b</b>) RCP 8.5.</p>
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<p>LMs derived from MLR fit to a GEV PD to produce shape, scale, and location parameters to derive median flows (<math display="inline"><semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mn>3</mn> </msup> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>) and confidence intervals (CIs) estimated from percentiles: (<b>a</b>) simulated September 5-day low-flows driven by MLR regression using August total precipitation LMs over a 31-year rolling time window under (<b>a</b>) RCP 4.5 and (<b>b</b>) RCP 8.5. The dashed red line denotes a flow of &lt;1 m<sup>3</sup>/s. Note: each simulation is based on <span class="html-italic">n</span> = 1000 iterations for both panels.</p>
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<p>Results of the LMs derived from MLR fit to the best-fit probability distribution (PD) (distributions described in [<a href="#B45-hydrology-11-00154" class="html-bibr">45</a>]) to produce shape, scale, and location parameters to derive median flows (<math display="inline"><semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mn>3</mn> </msup> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>) and confidence intervals (CIs) estimated numerically from percentiles: (<b>a</b>) simulated September 5-day low-flows driven by MLR regression using August total precipitation LMs over a 31-year moving window under RCP 4.5 and (<b>b</b>) RCP 8.5. The dashed red line denotes a flow of &lt;1 m<sup>3</sup>/s. Note: each simulation is based on <span class="html-italic">n</span> = 1000 iterations for both panels.</p>
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<p>Overall standardized Mean Square Error (MSE) across different window sizes during model training.</p>
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<p>Sensitivity of window size on location, scale, and shape parameters for September 5-day low-flow estimated using the method of LMs described in [<a href="#B45-hydrology-11-00154" class="html-bibr">45</a>] derived from MLR driven by total August precipitation LMs for six common distributions described in [<a href="#B45-hydrology-11-00154" class="html-bibr">45</a>] (Generalized Extreme Value (GEV; (<b>a</b>–<b>c</b>)), Generalized Logistic (GLO; (<b>d</b>–<b>f</b>)), Generalized Normal (GNO; (<b>g</b>–<b>i</b>)), Pearson Type III (PE3; (<b>j</b>–<b>l</b>)), and Generalized Pareto (GPA; (<b>m</b>–<b>o</b>)). The solid line displays data under the Representative Concentration Pathway (RCP) 4.5 emission scenario, while the dashed line displays the RCP 8.5 emissions scenario.</p>
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<p>Low-flow exceedance and cumulative exceedance probability for the Goat River near Erikson Gauge Station, showing values less than 2.7 cubic meters per second (<math display="inline"><semantics> <mrow> <msup> <mi mathvariant="normal">m</mi> <mn>3</mn> </msup> <mo>/</mo> <mi mathvariant="normal">s</mi> </mrow> </semantics></math>) assuming <span class="html-italic">n</span> = 1000 simulations and a Generalized Extreme Value (GEV) probability distribution (PD). Future data assume a Representative Concentration Pathway (RCP) 4.5 emissions scenario.</p>
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10 pages, 549 KiB  
Article
Using Vaccine Safety Data to Demonstrate the Potential of Pooled Data Analysis
by Steven Hawken, Lindsay A. Wilson and Kumanan Wilson
Vaccines 2024, 12(9), 1052; https://doi.org/10.3390/vaccines12091052 - 14 Sep 2024
Viewed by 314
Abstract
In Canada, vaccine safety studies are often conducted at the provincial/territorial level where the primary data on vaccination reside. Combining health services data from multiple jurisdictions using a pooled data analytic approach would reduce the amount of time needed to detect vaccine safety [...] Read more.
In Canada, vaccine safety studies are often conducted at the provincial/territorial level where the primary data on vaccination reside. Combining health services data from multiple jurisdictions using a pooled data analytic approach would reduce the amount of time needed to detect vaccine safety signals. To determine the difference in the time it would take to identify safety signals using different proportions of the Canadian population, we conducted power and sample size calculations for a hypothetical self-controlled case series-based surveillance analysis. We used scenarios modeled after the real-world examples of myocarditis and vaccine-induced immune thrombotic thrombocytopenia (VITT) following COVID-19 vaccination as our base cases. Our calculations demonstrated that in the case of a myocarditis-type event, a pooled analysis would reduce the time needed to detect a safety signal by over 60% compared to using Ontario data alone. In the case of a VITT-type event, a pooled analysis could detect a safety signal 49 days sooner than using Ontario data alone, potentially averting as many as 30 events. Our analysis demonstrates that there is substantial value in using pan-Canadian health services data to evaluate the safety of vaccines. Efforts should be made to develop a pan-Canadian vaccine data source to allow for an earlier evaluation of suspected adverse events following immunization. Full article
(This article belongs to the Section Vaccine Efficacy and Safety)
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<p>Days of mass vaccination throughput required to accrue sufficient events to detect: (1) myocarditis assuming relative incidence (RI) = 3.0, incidence = 1/100,000 in overall population, and (2) vaccine-induced immune thrombocytopenia and thrombosis assuming RI = 5.0, incidence = 1.5/100,000 in M/F 18–39 yrs. Assumptions: Power: 90%; two-sided alpha: 0.05; risk period: 28 days; observation window: 180 days. The same relative throughput achieved in Ontario has been assumed to be possible in other jurisdictions (~0.35% of the eligible population/day). Abbreviations: AB, Alberta; BC, British Columbia; MB, Manitoba; ON, Ontario; PQ, Province of Quebec; SK, Saskatchewan.</p>
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18 pages, 1385 KiB  
Article
Histopathological Growth Patterns Determine the Outcomes of Colorectal Cancer Liver Metastasis Following Liver Resection
by Lucyna Krzywoń, Anthoula Lazaris, Stephanie K. Petrillo, Oran Zlotnik, Zu-Hua Gao and Peter Metrakos
Cancers 2024, 16(18), 3148; https://doi.org/10.3390/cancers16183148 - 13 Sep 2024
Viewed by 289
Abstract
Introduction: Colorectal cancer liver metastasis (CRCLM) remains a lethal diagnosis, with an overall 5-year survival rate of 5–10%. Two distinct histopathological growth patterns (HGPs) of CRCLM are known to have significantly differing rates of patient survival and response to treatment. We set out [...] Read more.
Introduction: Colorectal cancer liver metastasis (CRCLM) remains a lethal diagnosis, with an overall 5-year survival rate of 5–10%. Two distinct histopathological growth patterns (HGPs) of CRCLM are known to have significantly differing rates of patient survival and response to treatment. We set out to review the results of 275 patients who underwent liver resection for CRCLM at the McGill University Health Center (MUHC) and analyze their clinical outcome, mutational burden, and pattern of cancer progression in light of their HGPs, and to consider their potential effect on surgical decision making. Methods: We performed a retrospective multivariate analysis on clinical data from patients with CRCLM (n = 275) who underwent liver resection at the McGill University Health Center (MUHC). All tumors were scored using international consensus guidelines by pathologists trained in HGP scoring. Results: A total of 109 patients (42.2%) were classified as desmoplastic and angiogenic, whereas 149 patients (57.7%) were non-desmoplastic and vessel co-opting. The 5-year survival rates for angiogenic patients compared with vessel co-opting patients were 47.1% and 13%, respectively (p < 0.0001). Multivariate analysis showed patients with vessel co-opting CRCLM had a higher incidence of extrahepatic metastatic disease (p = 0.0215) compared with angiogenic CRCLM. Additionally, KRAS mutation status was a marker of increased likelihood of disease recurrence (p = 0.0434), as was increased number of liver tumors (p = 0.0071) and multiple sites of extrahepatic metastatic disease (p < 0.0001). Conclusions: Multivariate analysis identified key clinical prognostic and molecular features correlating with the two HGPs. Determining liver tumor HGPs is essential for patient prognostication and treatment optimization. Full article
(This article belongs to the Section Cancer Metastasis)
15 pages, 6338 KiB  
Article
Climate Classification in the Canadian Prairie Provinces Using Day-to-Day Thermal Variability Metrics
by William A. Gough and Zhihui Li
Atmosphere 2024, 15(9), 1111; https://doi.org/10.3390/atmos15091111 - 13 Sep 2024
Viewed by 180
Abstract
The data from thirty-one climate stations in the Canadian Prairie provinces of Alberta, Saskatchewan, and Manitoba are analyzed using a number of day-to-day thermal variability metrics. These are used to classify each climate station location using a decision tree developed previously. This is [...] Read more.
The data from thirty-one climate stations in the Canadian Prairie provinces of Alberta, Saskatchewan, and Manitoba are analyzed using a number of day-to-day thermal variability metrics. These are used to classify each climate station location using a decision tree developed previously. This is the first application of the decision tree to identify stations as having rural, urban, peri-urban, marine, island, airport, or mountain climates. Of the thirty-one, eighteen were identified as peri-urban, with fourteen of these being airports; six were identified as marine or island; four were identified as rural; one as urban was identified; and two were identified as mountain. The two climate stations at Churchill, Manitoba, located near the shores of Hudson Bay, were initially identified as peri-urban. This was re-assessed after adjusting the number of “winter” months used in the metric for identifying marine and island climates (which, for all other analyses, excluded only December, January, and February). For Churchill, to match the sea ice season, the months of November, March, April, and May were also excluded. Then, a strong marine signal was found for both stations. There is a potential to use these thermal metrics to create a sea ice climatology in Hudson Bay, particularly for pre-satellite reconnaissance (1971). Lake Louise and Banff, Alberta, are the first mountain stations to be identified as such outside of British Columbia. Five airport/non-airport pairs are examined to explore the difference between an airport site and a local site uninfluenced by the airport. In two cases, the expected outcome was not realized through the decision tree analysis. Both Jasper and Edmonton Stony Plain were classified as peri-urban. These two locations illustrated the influence of proximity to large highways. In both cases the expected outcome was replaced by peri-urban, reflective of the localized impact of the major highway. This was illustrated in both cases using a time series of the peri-urban metric before and after major highway development, which had statistically significant differences. This speaks to the importance of setting climate stations appropriately away from confounding influences. It also suggests additional metrics to assess the environmental consistency of climate time series. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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<p>Thermal metrics decision tree developed in [<a href="#B8-atmosphere-15-01111" class="html-bibr">8</a>].</p>
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<p>Map of 31 Stations used in this study in the Canadian provinces of Alberta, Saskatchewan, and Manitoba.</p>
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<p>The 31 stations plotted by classification type (colour) and as a function of RΔT<sub>min</sub>. Blue represents marine and island stations (dark blue for marine and lighter blue for island). Darker orange are peri-urban climates, not at airports, and lighter orange are peri-urban climates at airports. Green designates rural climates, and red denotes urban climates. Purple signifies a mountain classification.</p>
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<p>RΔT<sub>min</sub> for Edmonton Stony Plain, decadal average from the 1970s to the 2010s. Blue indicates below the peri-urban threshold and red indicates above the peri-urban threshold.</p>
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<p>Gimli and Gimli A. Scale 1:50,000.</p>
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<p>Flin Flon and Flin Flon A. Scale 1:15,000.</p>
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<p>Regina A and Regina University. Scale 1:30,000.</p>
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<p>Prince Albert and Prince Albert A. Scale 1:25,000.</p>
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<p>Edmonton Stony Plan and Edmonton A. Scale 1:6000.</p>
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<p>Location of Churchill Marine and Churchill A stations. Scale 1:50,000.</p>
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<p>Lake Louise. Scale 1:25,000.</p>
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<p>Banff. Scale 1:10,000.</p>
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<p>Jasper. Jasper TS is the train station. Jasper TC is the town centre. “Jasper” is located at the coordinates provided by the climate data archive. The locations A, B, C, and D define the area in which, given the uncertainty in the coordinates, the station could be located. Scale 1:150,000.</p>
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<p>Jasper, 1941–1990, RΔTmin, decadal averaging. Red dots indicate decades above the 1.05 threshold, and blue dots indicate those below the 1.05 threshold.</p>
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16 pages, 2806 KiB  
Article
Coxsackievirus B3 Activates Macrophages Independently of CAR-Mediated Viral Entry
by Yasir Mohamud, Jingfei Carly Lin, Sinwoo Wendy Hwang, Amirhossein Bahreyni, Zhihan Claire Wang and Honglin Luo
Viruses 2024, 16(9), 1456; https://doi.org/10.3390/v16091456 - 13 Sep 2024
Viewed by 231
Abstract
Enteroviruses are a genus of small RNA viruses that are responsible for approximately one billion global infections annually. These infections range in severity from the common cold and flu-like symptoms to more severe diseases, such as viral myocarditis, pancreatitis, and neurological disorders, that [...] Read more.
Enteroviruses are a genus of small RNA viruses that are responsible for approximately one billion global infections annually. These infections range in severity from the common cold and flu-like symptoms to more severe diseases, such as viral myocarditis, pancreatitis, and neurological disorders, that continue to pose a global health challenge with limited therapeutic strategies currently available. In the current study, we sought to understand the interaction between coxsackievirus B3 (CVB3), which is a model enterovirus, and macrophage cells, as there is limited understanding of how this virus interacts with macrophage innate immune cells. Our study demonstrated that CVB3 can robustly activate macrophages without apparent viral replication in these cells. We also showed that myeloid cells lacked the viral entry receptor coxsackievirus and adenovirus receptor (CAR). However, the expression of exogenous CAR in RAW264.7 macrophages was unable to overcome the viral replication deficit. Interestingly, the CAR expression was associated with altered inflammatory responses during prolonged infection. Additionally, we identified the autophagy protein LC3 as a novel stimulus for macrophage activation. These findings provide new insights into the mechanisms of CVB3-induced macrophage activation and its implications for viral pathogenesis. Full article
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<p>CVB3 induced pro-inflammatory gene expression in macrophages independent of the viral replication. (<b>A</b>) HL1 cardiomyocytes or RAW264.7 macrophage cells were subjected to CVB3 infection (MOI = 100) for the indicated timepoints. Lysates were subjected to Western analysis for the viral capsid protein (VP1) and normalized to the loading control ACTB. Densitometric analysis results are shown in the adjacent bar plot. (<b>B</b>) RAW264.7 murine macrophages and (<b>C</b>) THP1-derived human macrophages were infected with CVB3 (MOI = 10; 4 h). RNA was harvested and subjected to qPCR analysis for inflammatory gene markers IFNB, TNFA, IL-1B, and IL-6. Viral gene marker 2A was utilized as a control to assess the viral treatment. The results are presented as the relative gene fold change expression between sham- and CVB3-infected groups (mean ± S.D., n = 3), where they were statistically evaluated via an unpaired Student’s <span class="html-italic">t</span>-test.</p>
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<p>CVB3-induced macrophage activation was independent of the cGAS-STING pathway. (<b>A</b>) RAW264.7 murine macrophages were subjected to a dose ramp of the STING agonist 2′3′-cGAMP (10 and 20 μg/mL, 4 h) and subjected to Western analysis for STING and p-TBK1 protein expression; ACTB was used as the loading control. (<b>B</b>) RAW264.7 macrophages were treated with STING agonists 2′3′-cGAMP (20 ug/mL) and diABZI (10 μM) or cGAS agonists herring testis (HT)-DNA (3 μg/mL) or poly-dAdT (3 μg/mL). cGAS-STING pathway activation was assessed via Western analysis of the STING and p-TBK1 protein expressions. (<b>C</b>) STING was not activated following CVB3 infection. RAW264.7 cells were infected with CVB3 (MOI = 10; 4 h) as above, and lysates were harvested for Western analysis of the STING activation, p-TBK1, and ACTB loading control. The RAW264.7 cells were subjected to a timecourse STING agonist treatment with diABZI (10 μM), and cGAMP (32 μM) was the positive control. (<b>D</b>) RAW264.7 macrophages were subjected to a time-course infection with CVB3 (MOI = 10), and cell lysates were analyzed by Western blot for macrophage activation marker COX2 and cGAS-STING pathway activation (anti-STING, anti-p-STING). ACTB was used as the loading control. (<b>E</b>) RAW264.7 macrophages were infected with CVB3 (MOI = 10; 5 h) and the cells were fixed for confocal microscopy imaging of the dsDNA/mtDNA release. Scale bars: 20 µm. (<b>F</b>) RAW264.7 macrophages were sham or CVB3 infected (MOI = 10; 8 h) in the presence of cGAS and STING inhibitors RU.521 (10 μM) and H151 (10 μM), respectively. Cell lysates were subjected to Western analysis for macrophage activation (COX2), STING activation (anti-STING, anti-p-STING, anti p-TBK1), and viral replication (VP1). (<b>G</b>) RAW264.7 macrophages were treated with cGAS and STING inhibitors RU.521 (10 μM) and H-151 (10 μM) as above, and the drug efficacy was evaluated with a qPCR assessment of the relative IFNB gene expression (mean ± S.D., n = 3).</p>
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<p>CVB3-induced macrophage activation was dependent on NF-κB (<b>A</b>) RAW 264.7 macrophages were infected with CVB3 (MOI = 10; 5 h), and the cells were fixed for confocal microscopy imaging of NFkB activation and COX2 expression. Scale bars: 20 µm. White arrows denote the nuclear-localized p65 present in CVB3- but not sham-infected cells. (<b>B</b>) RAW264.7 macrophages were infected with CVB3 (MOI = 10; 3 h) and subjected to specific inhibitors of TLR1/2, CU-CPT22 (500 nM), TLR3-inhibitor, CU-CPT4A (27 μM), TLR4-inhibitor C34 (10 μM), or NFkB inhibitor peptide (50 ug/mL). Cell lysates were subjected to Western analysis for the macrophage activation marker (COX2). (<b>C</b>) RAW264.7 macrophages were infected as in (<b>A</b>) and subjected to a dose ramp of the NFkB peptide inhibitor. Lysates were subjected to Western analysis for the macrophage activation marker COX2.</p>
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<p>CVB3-induced macrophage activation was independent of the viral replication, CAR expression, and phagocytosis. (<b>A</b>) RAW264.7 macrophages were sham or CVB3 infected (MOI = 10; 8 h) in the presence of the phagocytosis inhibitor cytochalasin D (1 μM) or a DMSO control. Cell lysates were assessed by Western blotting for the macrophage activation marker COX2. Densitometry results of the COX2 activation are presented in the right-hand panel (mean ± S.D., n = 3). (<b>B</b>) The SIM-A9 murine microglia cell line was assessed for myeloid activation through Western analysis with a COX2 marker following sham or CVB3 infection as above. (<b>C</b>) CVB3 replication and virus-induced autophagy was assessed in the NSC-34 murine motor neuron cells and SIM-A9 macrophages (MOI = 10; 8 h). Lysates were subjected to Western analysis for the autophagy marker protein LC3 and viral replication marker VP1. (<b>D</b>) The specificity of the COX2 myeloid expression marker was assessed in the NSC-34 motor neuron cells and SIM-A9 microglia cell line through Western analysis in the presence or absence of CVB3 infection (MOI = 10; 8 h). ACTB served as the loading control. (<b>E</b>) Virus-induced COX2 expression in SIM-A9 microglia was assessed with a control CVB3 virus and UV-inactivated CVB3 (MOI = 10; 8 h). UV inactivation of CVB3 was verified in the CVB3-susceptible cell line HEK293 through Western analysis for the viral replication marker VP1. (<b>F</b>) Expression of the coxsackievirus entry receptor CAR was assessed in HL-1, NSC-34, SIM-A9, HeLa, and RAW264.7 cells through Western analysis with the anti-CAR antibody. ACTB served as a protein loading control. (<b>G</b>) Schematic illustration of CVB3-susceptible cells and CVB3-resistant cells. * Denotes NSC-34 as the only CVB3-susceptible cell line that did not have detectable CAR expression.</p>
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<p>CAR expression regulated the late, but not early, response to the CVB3 infection. (<b>A</b>) RAW264.7 cells were transduced with either a control GFP- or hCAR-expressing lentivirus for 72 h, followed by CVB3 infection (MOI = 10) for 24 h. Cell lysates were harvested and subjected to Western analysis for anti-VP1 and anti-CAR antibody. Ponceau Red was used as a total protein loading stain. (<b>B</b>) Densitometry of VP1 expression from (<b>A</b>) was quantified and normalized to the total protein and presented in the bar plot (mean ± S.D., n = 3). (<b>C</b>) RAW264.7 cells were transduced as above and subjected to confocal analysis for GFP (green) and CAR (red) expression. Nuclei were stained with DAPI (blue). Scale bar: 20 µm. (<b>D</b>,<b>E</b>) RAW264.7 cells transduced with a GFP or hCAR lentivirus as above were subsequently infected with CVB3 (MOI = 10) for 2 h (<b>D</b>) or 24 h (<b>E</b>). RNA was harvested and subjected to qPCR analysis for viral RNA (2A) replication or inflammatory markers IL-1β, IL-6, or TNFA and presented as a relative quantitation where the first group was set to 1 (mean ± S.D., n = 3).</p>
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<p>Viral-induced LC3 stimulated macrophage activation. (<b>A</b>) Recombinant LC3 (rLC3) activated the SIMA-A9 myeloid cells. SIM-A9 were incubated with increasing doses of rLC3 for 4 h. Lysates were harvested and subjected to Western analysis for COX2 expression. ACTB was used as a loading control. (<b>B</b>) rLC3 potentiated CVB3-induced activation of the SIM-A9. SIM-A9 cells were co-incubated with CVB3 (MOI = 10) and increasing doses of rLC3 for 4 h. Lysates were harvested as above and subjected to Western analysis (<b>C</b>) SIM-A9 cells were infected with CVB3 (MOI = 10; 24 h). Lysates were harvested and subjected to Western analysis for autophagy marker LC3 and normalized to ACTB. (<b>D</b>) Densitometry of panel (<b>C</b>) where LC3-I and LC3-II were quantified and normalized to ACTB and presented as the mean ± S.D., n = 3.</p>
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13 pages, 652 KiB  
Article
Self-Screening for Cervical Cancer Offered through a Digital Platform in a Region of British Columbia with Lower Screening Rates
by Laurie W. Smith, Amy Booth, C. Sarai Racey, Brenda Smith, Ashwini Prabhakaran, Smritee Dabee, Quan Hong, Nazia Niazi and Gina S. Ogilvie
Curr. Oncol. 2024, 31(9), 5399-5411; https://doi.org/10.3390/curroncol31090399 - 13 Sep 2024
Viewed by 245
Abstract
Cervical cancer is highly preventable through vaccination, early detection, and treatment, yet is the fourth most common cancer globally. HPV testing is superior to cytology for the detection of cervical pre-cancer, and jurisdictions around the world are implementing HPV primary screening, which offers [...] Read more.
Cervical cancer is highly preventable through vaccination, early detection, and treatment, yet is the fourth most common cancer globally. HPV testing is superior to cytology for the detection of cervical pre-cancer, and jurisdictions around the world are implementing HPV primary screening, which offers the opportunity for self-screening, an important self-care intervention. Digital health solutions are also increasingly important components of self-care. In this study, we assessed the acceptability and completion of self-screening for cervical cancer offered through a digital platform within a low screening uptake region of British Columbia. The primary objective of this study was to evaluate the acceptability of self-screening for cervical cancer offered through a digital platform as measured by return rates of self-screening kits. Patients due or overdue for cervix screening were invited to participate. Eligible participants registered online to receive a self-screening kit, which included a device for vaginal self-screening, instructions, and a return envelope, sent to their home. After self-screening using the vaginal device, HPV testing was conducted. HPV-negative participants were returned to routine screening, and HPV-positive participants were recommended for cytology or colposcopy. Attendance rates at follow-up were evaluated. Participants were invited to complete an acceptability survey. From April 2019 to December 2023, 283 participants were sent kits, with 207 kits returned for a completion rate of 73%. Of valid samples (n = 202), 15 were HPV positive, and 93% attended follow-up care. Most respondents found the CervixCheck website easy to use, informative, and secure and were satisfied with receiving their results online. CervixCheck had a high completion rate among participants who were sent a self-screening kit. High compliance with recommended follow-up and high acceptability of self-screening for cervical cancer was observed. Most participants indicated they would self-screen again in the future. Innovative approaches to cervical screening, including self-screening and the use of digital health interventions, are ways to enhance equity and improve uptake of cervical screening. Full article
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<p>Participation in CervixCheck. Any participants who withdrew from this study are not included in this analysis.</p>
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14 pages, 1318 KiB  
Article
Anaerobic Digestion of Food Waste with the Addition of Biochar Derived from Microwave Catalytic Pyrolysis of Solid Digestate
by Sofia Lucero Saucedo and Anthony Lau
Sustainability 2024, 16(18), 7997; https://doi.org/10.3390/su16187997 - 13 Sep 2024
Viewed by 626
Abstract
This study explores the potential of biochar derived from microwave-assisted catalytic pyrolysis of solid digestate as an additive to enhance the stability and performance of the anaerobic digestion process. The focus was placed on the effects of biochar dosage, pyrolysis temperature, and pyrolysis [...] Read more.
This study explores the potential of biochar derived from microwave-assisted catalytic pyrolysis of solid digestate as an additive to enhance the stability and performance of the anaerobic digestion process. The focus was placed on the effects of biochar dosage, pyrolysis temperature, and pyrolysis catalyst on methane production. Biochemical methane potential (BMP) tests using synthetic food waste as the substrate revealed a dosage-dependent relationship with specific methane yield (SMY). At a low biochar dosage of 0.1 g/g total solids (TS), improvement in methane (CH4) production was marginal, whereas a high dosage of 0.6 g/g TS increased CH4 content by at least 10% and improved yield by 35–52%. ANOVA analysis indicated that biochar dosage level significantly influenced CH4 yield, while pyrolysis temperature (400 °C vs. 500 °C) and catalyst (20 wt% K3PO4 vs. 10 wt% K3PO4/10 wt% clinoptilolite) did not lead to significant differences in CH4 yield between the treatments. Correlation analysis results suggested that biochar’s most impactful properties on methane yield would be dosage-adjusted specific surface area (or total surface area per unit volume of substrate) and aromaticity index. The findings underscore the potential of solid-digestate-derived biochar as a beneficial additive for anaerobic digestion and hence the sustainability of food waste management system. Full article
(This article belongs to the Section Pollution Prevention, Mitigation and Sustainability)
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<p>Schematic diagram of experimental setup. Created with BioRender.com.</p>
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<p>Methane generation profiles for the experimental treatments: (<b>a</b>) with a low biochar dosage of 0.1 g/g TS; (<b>b</b>) with a high biochar dosage of 0.6 g/g TS as compared to the control.</p>
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<p>Comparison of specific methane yield (SMY) among the experimental treatments.</p>
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19 pages, 8280 KiB  
Article
Estimating Three-Dimensional Resistivity Distribution with Magnetotelluric Data and a Deep Learning Algorithm
by Xiaojun Liu, James A. Craven, Victoria Tschirhart and Stephen E. Grasby
Remote Sens. 2024, 16(18), 3400; https://doi.org/10.3390/rs16183400 - 13 Sep 2024
Viewed by 338
Abstract
In this study, we describe a deep learning (DL)-based workflow for the three-dimensional (3D) geophysical inversion of magnetotelluric (MT) data. We derived a mathematical connection between a 3D resistivity model and the surface-observed electric/magnetic field response by using a fully connected neural network [...] Read more.
In this study, we describe a deep learning (DL)-based workflow for the three-dimensional (3D) geophysical inversion of magnetotelluric (MT) data. We derived a mathematical connection between a 3D resistivity model and the surface-observed electric/magnetic field response by using a fully connected neural network framework (U-Net). Limited by computer hardware functionality, the resistivity models were generated by using a random walk technique to enlarge the generalization coverage of the neural network model, and 15,000 paired datasets were utilized to train and validate it. Grid search was used to select the optimal configuration parameters. With the optimal model framework from the parameter tuning phase, the metrics showed stable convergence during model training/validation. In the test period, the trained model was applied to predict the resistivity distribution by using both the simulated synthetic and the real MT data from the Mount Meager area, British Columbia. The reliability of the model prediction was verified with noised input data from the synthetic model. The calculated results can be used to reconstruct the position and shape trends of bodies with anomalous resistivity, which verifies the stability and performance of the DL-based 3D inversion algorithm and showcases its potential practical applications. Full article
(This article belongs to the Topic AI and Data-Driven Advancements in Industry 4.0)
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<p>Diagram illustrating the principles of an MT survey (Ex and Ey: electric fields; Hx, Hy and Hz are magnetic fields).</p>
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<p>A schematic of the 3D U-Net architecture, consisting of an encoder analysis path and a decoder synthesis path.</p>
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<p>A sample of the resistivity model from the random walk generator (the color represents resistivity values in common logarithmic space).</p>
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<p>Plane (<b>left</b>) and vertical (<b>right</b>) views of the synthetic model mesh grid with MT stations indicated (blue dots).</p>
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<p>The convergence curves of model training and validation with different loss functions ((<b>a</b>) MAE, (<b>b</b>) MSE and (<b>c</b>) RMSE).</p>
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<p>Learning rate search showing the metric curves of minimized loss function vs. learning rates ((<b>a</b>) training and (<b>b</b>) validation; the green double arrows display the optimal range of the learning rate).</p>
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<p>The grid search layout results showing the distribution contour and minimized metric values, where (<b>a</b>) model training and (<b>b</b>) model validation.</p>
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<p>The schematic workflow of DL-based 3D inversion, including dataset preparation, parameter tuning and model training/validation/testing.</p>
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<p>Three-dimensional view of single slipped dike synthetic model ((<b>a</b>) true model; (<b>b</b>) predicted model).</p>
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<p>The model sensitivity testing with synthetic models including an anomaly with the same shape and different resistivity ((<b>a</b>,<b>b</b>) conductor anomaly model and prediction; (<b>c</b>,<b>d</b>) resistor anomaly model and prediction).</p>
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<p>Synthetic models of two anomalies at different depths and the DL 3D inversion results ((<b>a</b>,<b>c</b>) true models; (<b>b</b>,<b>d</b>) predicted results).</p>
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<p>The comparison of simulated impedance at two different frequencies from the true model and the predicted results of the two-body synthetic model ((<b>a</b>,<b>b</b>) real part; (<b>c</b>,<b>d</b>) imaginary part; (<b>a</b>,<b>c</b>) 3.5 Hz; (<b>b</b>,<b>d</b>) 0.0044 Hz).</p>
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<p>The synthetic model containing two anomalous conductors at the same depth.</p>
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<p>The horizontal slice of model and predicted results with different noise levels (0%, 5% and 10%).</p>
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<p>MT site distribution with cross section B-B’ location in Mount Meager study area, British Columbia, Canada.</p>
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<p>Horizontal sliced iso-resistivity maps at different depths between 0.5 and 10 km (the purple dashed line indicates the main resistivity anomaly).</p>
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<p>Slices of the inversion results with DL-based inversion and ModEM iterative inversion. (<b>a</b>–<b>d</b>) Horizontal slices at depths of 6.0 and 7.0 km; (<b>e</b>,<b>f</b>) vertical slices along profile B-B’ in <a href="#remotesensing-16-03400-f015" class="html-fig">Figure 15</a>; (<b>a</b>,<b>c</b>,<b>e</b>) 3D DL-based inversion; (<b>b</b>,<b>d</b>,<b>f</b>) ModEM iterative inversion.</p>
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20 pages, 6004 KiB  
Article
The Effects of Auxin Transport Inhibition on the Formation of Various Leaf and Vein Patterns
by Carol L. Wenzel, David M. Holloway and Jim Mattsson
Plants 2024, 13(18), 2566; https://doi.org/10.3390/plants13182566 - 12 Sep 2024
Viewed by 230
Abstract
Polar auxin transport (PAT) is a known component controlling leaf complexity and venation patterns in some model plant species. Evidence indicates that PAT generates auxin converge points (CPs) that in turn lead to local leaf formation and internally into major vein formation. However, [...] Read more.
Polar auxin transport (PAT) is a known component controlling leaf complexity and venation patterns in some model plant species. Evidence indicates that PAT generates auxin converge points (CPs) that in turn lead to local leaf formation and internally into major vein formation. However, the role of PAT in more diverse leaf arrangements and vein patterns is largely unknown. We used the pharmacological inhibition of PAT in developing pinnate tomato, trifoliate clover, palmate lupin, and bipinnate carrot leaves and observed dosage-dependent reduction to simple leaves in these eudicots. Leaf venation patterns changed from craspedodromous (clover, carrot), semi-craspedodromous (tomato), and brochidodromous (lupin) to more parallel patterning with PAT inhibition. The visualization of auxin responses in transgenic tomato plants showed that discrete and separate CPs in control plants were replaced by diffuse convergence areas near the margin. These effects indicate that PAT plays a universal role in the formation of different leaf and vein patterns in eudicot species via a mechanism that depends on the generation as well as the separation of auxin CPs. Computer simulations indicate that variations in PAT can alter the number of CPs, corresponding leaf lobe formation, and the position of major leaf veins along the leaf margin in support of experimental results. Full article
(This article belongs to the Special Issue Advances in Plant Auxin Biology)
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<p>PAT inhibition reduced leaf complexity in ca 4 week old tomato plants ((<b>A</b>); leaf 3) and ca 2 weeks old clover ((<b>B</b>); leaf 2 and 3), lupin ((<b>C</b>); leaf 2 and 3), and carrot ((<b>D</b>); leaf 1 and 2). Images show control leaves (0) or leaves exposed to various concentrations (µM) of NPA (N), HFCA (H), or TIBA (T). The apparent absence of a lateral leaflet (arrow in (<b>A</b>)) and fusion between adjacent leaflets (arrowheads in (<b>A</b>–<b>C</b>)) are indicated. Scale bars are 5 mm ((<b>A</b>); control and NPA-treated), 2 mm ((<b>A</b>); HFCA-treated), or 0.5 mm ((<b>B</b>–<b>D</b>); except that (i) fourth image from left in (<b>B</b>) and (ii) third and fourth images from left in (<b>D</b>) are 0.2 mm).</p>
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<p>PAT inhibition induced more parallel-like leaf vein patterning. Dark-field images of tomato (Tiny Tom), clover, lupin, or carrot venation patterning on individual leaflets (control) or entire PAT-inhibited leaves (weak and strong phenotypes). Inset for lupin (100 N) shows very strong phenotype with parallel venation throughout lamina. Images show control leaves (0) or leaves exposed to various concentrations (µM) of NPA (N), HFCA (H) or TIBA (T). Scale bars are 1 mm.</p>
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<p>Leaf primordia venation and <span class="html-italic">pIAA2</span>::GUS expression in tomato (variety Alicia Craig). Tomato leaf primordia of plants grown for 6, 8, or 10 days in media with 0, 1, or 10 µM NPA. Primordia are viewed with darkfield optics to see differentiated venation patterns (<b>A</b>) or with brightfield optics to view <span class="html-italic">pIAA2</span>::GUS expression (<b>B</b>). NPA decreased leaflet outgrowth and induced vascular overgrowth and IAA2 accumulation near the leaf apex. (<b>A</b>) all 8 DAG primordia had a portion of the lamina cut off (left side of image) to assist visualization. Scale bars are 50 µm (6 DAG) or 100 µm (8 and 10 DAG).</p>
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<p><span class="html-italic">pDR5</span>::GUS expression in tomato (variety Alicia Craig) leaf primordia. NPA treatment induced broad <span class="html-italic">pDR5</span>::GUS expression in the apex of 6 DAG L2 leaf primordia ((<b>A</b>), lower image) compared to the discrete auxin response maximum in control plants ((<b>A</b>), arrows in upper image). 7 DAG control L2 leaf primordia had discrete auxin response maxima in the emerging leaflets (arrows in (<b>B</b>)). Each developing leaflet had <span class="html-italic">pDR5</span>::GUS expression in a discrete auxin maxima below the epidermis as well as in the developing primary provascular cells of the midvein (arrows in (<b>C</b>)). Exposure of 8 DAG seedlings to 10 µM 2,4-D induced broad <span class="html-italic">pDR5</span>::GUS expression along most of the margin of L4 leaf primordia, with expression becoming restricted to more basal regions in older L3, L2, and L1 primordia ((<b>D</b>); insets show controls). Scale bars are 20 µm (<b>A</b>,<b>C</b>), 100 µm (<b>B</b>), or 50 µm ((<b>D</b>), except that L1 is 500 µm).</p>
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<p>Computer simulations of the effect of PAT inhibitor treatment on leaf margin complexity. Images show the terminal lobe (Zone 1) and first two lateral lobes (Zone 2; only left side is marked in (<b>A</b>)), with black arrows delimiting the zone boundaries. Auxin-synthesizing cells in the margin grew in proportion to auxin concentration (green intensity). PIN1 concentration (red) was either cytosolic or in the membrane (shown at the walls). Yellow indicates high PIN1 and auxin concentrations within a cell; black indicates a lack of auxin and PIN1. White arrows indicate the net auxin flux for each cell. All results are shown at the same time (5 h 30 min computational units). PIN1-auxin dynamics in normal conditions (<b>A</b>) formed CPs (black asterisks) from which the midvein extended to the base of the leaf and the existing plant vasculature (represented by the blue-walled cells, red arrow) and from which secondary veins extended to the midvein. CPs are local auxin maxima in the margin (with marginal PIN1 polarization into the CPs), causing lobed outgrowth. As transmission through PIN1 (T parameter) was decreased (<b>B</b>–<b>D</b>), corresponding to increasing PAT inhibitor concentration, the leaf margin changed from lobed (<b>A</b>) to smooth (<b>B</b>–<b>D</b>), extra CPs formed (black asterisks), and secondary veins could run parallel to the midvein (red asterisks and red arrowheads in (<b>B</b>)). At low T (<b>C</b>), the mid-vein was lost, and the extra CPs extended short ‘strands’. At very low T (<b>D</b>), vein extension was lost. The smoother margins reflect the more uniform marginal auxin distributions (less localization to a few ‘discrete’ CPs) as PIN1 transmission was lost.</p>
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<p>Exogenous IAA affected tomato (variety Tiny Tom) leaflet formation. Images show tomato leaves from ca 10-week-old control plants (<b>A</b>) or plants treated with 1% (<b>B</b>,<b>F</b>,<b>G</b>) or 10% (<b>C</b>–<b>E</b>) <span class="html-italic">w</span>/<span class="html-italic">w</span> IAA. IAA application resulted in leaves having broad bases fused along the petiole or rachis (arrows in (<b>B</b>,<b>C</b>) and/or fused with other leaflets (arrows in (<b>C</b>–<b>F</b>)). Scale bars are 10 mm.</p>
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<p>IAA treatment did not alter overall tomato leaf venation patterning. Magnified images (<b>B</b>,<b>C</b>) of a leaf (<b>A</b>) treated with 10% <span class="html-italic">w</span>/<span class="html-italic">w</span> IAA. Darkfield images were inverted to show leaf venation patterning, and numerous starch granules are also present. IAA treatment induced primary-like (arrows in (<b>B</b>); large arrows in (<b>C</b>)) veins extending towards the lobe apex and secondary-like (small arrows in (<b>C</b>)) vein loops. Scale bars are 10 mm (<b>A</b>) or 1 mm (<b>B</b>,<b>C</b>).</p>
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<p>Computer simulations of the effect of exogenous IAA on leaf margin complexity. Model parameters and visualization are as in <a href="#plants-13-02566-f005" class="html-fig">Figure 5</a>. (<b>A</b>–<b>C</b>) Increasing auxin production, corresponding to exogenous IAA application, produced smoother margins (auxin precursor concentration, A<sub>prec</sub>, was boosted at the time the lateral lobes became auxin-synthesizing). Larger boosts created broader lobes and shallower clefts: (<b>A</b>) 0.7 added to A<sub>prec</sub>; (<b>B</b>) 1.7 added to A<sub>prec</sub>; (<b>C</b>) 2.2 added to A<sub>prec</sub>. (<b>A</b>–<b>C</b>) Transport from the margin was not sufficient to reduce auxin levels to normal, resulting in the extra growth of the lobes. (<b>D</b>) The leaflets had the same A<sub>prec</sub> boost as (<b>C</b>), but PIN1 was also boosted in the terminal lobe and midvein to simulate established vasculature in more mature leaflets. In this case, the high doses of exogenous auxin could be sufficiently drained, resulting in a narrower, more normal lobe shape (compare region between black arrows delimiting zone 1 in (<b>C</b>,<b>D</b>)). Asterisks indicate CPs.</p>
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15 pages, 63594 KiB  
Article
Single-Shot Ultra-Widefield Polarization-Diversity Optical Coherence Tomography for Assessing Retinal and Choroidal Pathologies
by Tiffany Tse, Hoyoung Jung, Mohammad Shahidul Islam, Jun Song, Grace Soo, Khaldon Abbas, Shuibin Ni, Fernando Sumita, Katherine Paton, Yusi Miao, Yifan Jian, Zaid Mammo, Eduardo V. Navajas and Myeong Jin Ju
J. Clin. Med. 2024, 13(18), 5415; https://doi.org/10.3390/jcm13185415 - 12 Sep 2024
Viewed by 523
Abstract
Background: Optical coherence tomography (OCT) is a leading ocular imaging modality, known for delivering high-resolution volumetric morphological images. However, conventional OCT systems are limited by their narrow field-of-view (FOV) and their reliance on scattering contrast, lacking molecular specificity. Methods: To address [...] Read more.
Background: Optical coherence tomography (OCT) is a leading ocular imaging modality, known for delivering high-resolution volumetric morphological images. However, conventional OCT systems are limited by their narrow field-of-view (FOV) and their reliance on scattering contrast, lacking molecular specificity. Methods: To address these limitations, we developed a custom-built 105 ultra-widefield polarization-diversity OCT (UWF PD-OCT) system for assessing various retinal and choroidal conditions, which is particularly advantageous for visualizing peripheral retinal abnormalities. Patients with peripheral lesions or pigmentary changes were imaged using the UWF PD-OCT to evaluate the system’s diagnostic capabilities. Comparisons were made with conventional swept-source OCT and other standard clinical imaging modalities to highlight the benefits of depolarization contrast for identifying pathological changes. Results: The molecular-specific contrast offered by UWF PD-OCT enhanced the detection of disease-specific features, particularly in the peripheral retina, by capturing melanin distribution and pigmentary changes in a single shot. This detailed visualization allows clinicians to monitor disease progression with greater precision, offering more accurate insights into retinal and choroidal pathologies. Conclusions: Integrating UWF PD-OCT into clinical practice represents a major advancement in ocular imaging, enabling comprehensive views of retinal pathologies that are difficult to capture with current modalities. This technology holds great potential to transform the diagnosis and management of retinal and choroidal diseases by providing unique insights into peripheral retinal abnormalities and melanin-specific changes, critical for early detection and timely intervention. Full article
(This article belongs to the Special Issue Clinical Utility of Optical Coherence Tomography in Ophthalmology)
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<p>(<b>a</b>) Schematic diagram of PD-OCT system. (<b>b</b>) Polarization diversity detection unit (PDD). (<b>c</b>) SolidWorks design of the ultra-wide-field retinal scanner. L1–4: Lens; LP: linear polarizer; PC: polarization controller; FC: fiber collimator; NC: not connected; M: mirror; GS-X and -Y: galvanometer scanner; DC: dispersion compensation block; ETL: electrically tunable lens; PBS: polarizing beam splitter; BS: beam splitter; H- and V-BPD: balanced photo-detector for horizontally and vertically polarized signals, respectively.</p>
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<p>Comparative images of two distinct FOVs (55<sup>∘</sup> and 105<sup>∘</sup>). (<b>a</b>) Phantom eye featuring a resolution target with structured concentric circles that serve as a visual guide for FOV and resolution calibration. (<b>b</b>,<b>c</b>) OCT en face and B-scan images of healthy control subject where the green rectangular box highlights the 55<sup>∘</sup> FOV and the encompassing orange box designates the 105<sup>∘</sup> FOV.</p>
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<p>Illustration of post-processing pipeline: (<b>a</b>) raw OCT intensity images detected by the PDD unit of P-polarization (horizontal) and S-polarization (vertical) channels; (<b>b</b>) scattering OCT B-scan obtained by coherent averaging of P- and S-channels; (<b>c</b>) noise-corrected DOPU B-scan kernel averaging [<a href="#B27-jcm-13-05415" class="html-bibr">27</a>]; (<b>d</b>) OCT and DOPU B-scan composite.</p>
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<p>Retinitis pigmentosa patient, a 38-year-old South Asian male with heterozygous RHO GLu181Lys genetic mutation (left eye): (<b>a</b>) SLO fundus photograph; (<b>b</b>) short-wavelength autofluorescence; (<b>c</b>) 105<sup>∘</sup> ultra-wide FOV OCT <span class="html-italic">en-face</span> projection image captured by PD-OCT; (<b>d</b>) 105<sup>∘</sup> ultr-awide FOV DOPU <span class="html-italic">en-face</span> projection image of the inner retina after segmentation; (<b>e</b>,<b>f</b>) 105<sup>∘</sup> FOV OCT and DOPU B-scans at location marked by dotted blue line in (<b>d</b>). Bone spicules in the peripheral retina are highlighted by the white arrows in (<b>f</b>).</p>
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<p>Close-up 55<sup>∘</sup> FOV marked by the yellow dashed square in <a href="#jcm-13-05415-f004" class="html-fig">Figure 4</a>c: (<b>a</b>) OCT <span class="html-italic">en-face</span> projection image captured by PD-OCT; (<b>b</b>) DOPU <span class="html-italic">en-face</span> projection image of the RPE after segmentation; (<b>c</b>) DOPU en face projection image of the inner retina after segmentation; (<b>d</b>,<b>e</b>) OCT and DOPU B-scans at location marked by dotted blue line in (<b>b</b>). The ellipsoid zone is highlighted by the dotted red rectangle in (<b>d</b>).</p>
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<p>Peripheral flat melanotic choroidal nevus of a 55-year-old Caucasian female (left eye): (<b>a</b>) fundus photograph with lesion highlighted by white dotted circle; (<b>b</b>) 105<sup>∘</sup> ultra-wide FOV OCT <span class="html-italic">en-face</span> projection with lesion highlighted by white dotted circle; (<b>c</b>) 105<sup>∘</sup> ultra-wide FOV DOPU <span class="html-italic">en-face</span> projection; (<b>d</b>,<b>e</b>) OCT B-scan and DOPU B-scan of lesion at location marked by blue dotted line in (<b>c</b>). The area of depolarization consistent with the melanin-rich area is highlighted by a white dotted rectangle in (<b>e</b>).</p>
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<p>Mixed melanotic/amelanotic choroidal nevus of a 53-year-old Caucasian female (left eye): (<b>a</b>) Fundus photograph with lesion highlighted by white dotted circle; (<b>b</b>) 105<sup>∘</sup> ultra-wide FOV OCT <span class="html-italic">en-face</span> projection with lesion highlighted by white dotted circle; (<b>c</b>) 105<sup>∘</sup> ultra-wide FOV DOPU <span class="html-italic">en-face</span> projection. (<b>d</b>) OCT B-scan of lesion at location marked by dotted blue line in (<b>c</b>); Retinal elevation highlighted in orange; (<b>e</b>) Magnified view of area highlighted by red dotted rectangle in (<b>d</b>), showing subretinal fluid (red arrows) and intraretinal fluid (yellow arrows); (<b>f</b>) DOPU B-scan of lesion at location marked by dotted blue line in (<b>c</b>). A strong melanin signal at the edge of the lesion is indicated by a dotted white rectangle, and loss of melanin signal at the RPE is indicated by white arrows.</p>
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<p>Multifocal choroiditis of a 26-year-old female. Best corrected visual acuity: 20/60. (<b>a</b>) Fundus photograph; (<b>b</b>) short-wavelength autofluorescence; (<b>c</b>) fluorescein angiography; (<b>d</b>) 105<sup>∘</sup> ultra-wide FOV OCT <span class="html-italic">en-face</span> projection captured by PD-OCT; (<b>e</b>) 105<sup>∘</sup> ultra-wide FOV DOPU <span class="html-italic">en-face</span> projection of the RPE; (<b>f</b>) 105<sup>∘</sup> ultra-wide FOV DOPU <span class="html-italic">en-face</span> projection of the choroid; (<b>g</b>,<b>h</b>) 105<sup>∘</sup> ultra-wide FOV OCT and DOPU B-scans at the location marked by the dotted blue line in (<b>d</b>). Green arrows mark decreased RPE reflectivity. Red arrows show increased light transmission through the choroid and sclera at the sites of the scars. White arrows show the absence of depolarization signal at the level of the RPE and choriocapillaris.</p>
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<p>Choroideremia carrier, a 41-year-old Asian female: (<b>a</b>) fundus photograph; (<b>b</b>) short-wavelength autofluorescence; (<b>c</b>) 105<sup>∘</sup> ultra-wide FOV OCT <span class="html-italic">en-face</span> projection; (<b>d</b>) 105<sup>∘</sup> ultra-wide FOV DOPU <span class="html-italic">en-face</span> projection; (<b>e</b>) OCT B-scan at location marked by dotted blue line in (<b>c</b>); (<b>f</b>) PD-OCT B scan projection at location marked by dotted blue line in (<b>c</b>).</p>
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10 pages, 214 KiB  
Article
Evaluating a Digitally Delivered, Multi-Modal Intervention for Parents of Children with Type 1 Diabetes: A Proof-of-Concept Study
by Tricia S. Tang, Niloufar Sharif, Crystal Ng, Logan McLean, Gerri Klein and Shazhan Amed
Children 2024, 11(9), 1114; https://doi.org/10.3390/children11091114 - 12 Sep 2024
Viewed by 267
Abstract
Background/Objectives: We examined the feasibility, acceptability, and potential mental health impact of a digital peer support intervention involving videoconferencing and text-based support for parents of school-aged children living with T1D and analyzed posts exchanged by parents on a texting platform. Methods: Eighteen parents [...] Read more.
Background/Objectives: We examined the feasibility, acceptability, and potential mental health impact of a digital peer support intervention involving videoconferencing and text-based support for parents of school-aged children living with T1D and analyzed posts exchanged by parents on a texting platform. Methods: Eighteen parents were recruited for Huddle4Parents, a 4-month digital intervention that involved four synchronous group-based Zoom sessions coupled with an asynchronous 24/7 peer support texting room. Primary outcomes were feasibility (i.e., ability to recruit n = 20 parents and retain at least 75%) and acceptability (i.e., satisfaction ratings of “good” to “very good”). Baseline and 4-month assessments also measured diabetes distress, quality of life, and perceived support. A content analysis of text exchanges was also performed. Results: All 15 parents who completed the intervention attended at least one Huddle and posted at least one message on the 24/7 peer support room. The retention rate was 83%, with 100% indicating that they would “definitely” or “probably yes” recommend both platforms to other parents. They also rated the topics, facilitator, and overall Huddles as “good” to “excellent.” No changes were observed for psychosocial endpoints. Of the 1084 texts posted, core support themes included the following: (1) dealing with technology and devices; (2) seeking and providing emotional support; (3) managing T1D in the school setting; and (4) exchanging tips and strategies. Conclusions: Huddle4Parents, a digital T1D caregiver intervention offering synchronous and asynchronous support, is feasible based on recruitment, participation, and attrition rates and acceptable as demonstrated by engagement and satisfaction ratings for the Huddles and 24/7 peer support room. Full article
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