Split-spectrum amplitude decorrelation angiography for spectral-domain optical coherence tomography has enabled detailed, non-invasive assessment of vascular flow. This study evaluates ...choriocapillaris and retinal capillary perfusion density (CPD) in diabetic eyes using optical coherence tomography angiography (OCTA).
Records of 136 eyes that underwent OCTA imaging at a single institution were reviewed. Eyes were grouped as non-diabetic controls (37 eyes), patients with diabetes mellitus (DM) without diabetic retinopathy (DM without DR, 31 eyes), non-proliferative diabetic retinopathy (NPDR, 41 eyes) and proliferative diabetic retinopathy (PDR, 27 eyes). Quantitative CPD analyses were performed on OCTA images for assessing perfusion density of the choriocapillaris and retinal plexus for all patients and compared between groups.
Eyes with NPDR and PDR showed significantly decreased choriocapillaris CPD compared with controls, while DM eyes without DR did not show significant change. Choriocapillaris whole-image CPD was decreased by 8.3% in eyes with NPDR (p<0.01) and decreased by 7.1% in eyes with PDR (p<0.01). Choriocapillaris parafoveal CPD was decreased by 8.9% in eyes with NPDR (p<0.01) and decreased by 8.2% in eyes with PDR (p<0.01). Compared with controls, only eyes with PDR showed significantly decreased retinal CPD, as well as significantly increased foveal avascular zone (FAZ) area. In those patients, retinal whole-image CPD was decreased by 9.7% (p<0.01), retinal foveal CPD was decreased by 20.5% (p<0.01) and retinal parafoveal CPD was decreased by 11.4% (p<0.01). FAZ area was increased by 50.9% (p<0.01).
Choriocapillaris and retinal CPD are reduced in diabetic retinopathy, while FAZ area is increased in eyes with PDR. Vascular changes captured by new imaging modalities can further characterise diabetic choroidopathy.
•Data-mining techniques were applied to data from sugarcane production.•The impact of different approaches to include weather data was evaluated.•The RReliefF algorithm is used to evaluate feature ...engineering.•We evaluated the impact of tuning, feature selection, and feature engineering in error.•Sixty-six combinations were evaluated to quantify the impacts on model performance.
Crop yield models can assist decision makers within any agro-industrial supply chain, even with regard to decisions that are unrelated to the crop production. Considering the characteristics of the mechanisms and data related to yield, data mining techniques are suitable candidates for modelling. The use of these techniques within a context with feature engineering, feature selection, and proper tuning can further improve performance beyond a simple replacement of multiple linear regression. To evaluate the impact of the different steps in the mentioned context, we evaluated sugarcane (Saccharum spp.) yield modelling with data obtained from a sugarcane mill. For a combination of six techniques, tuning, feature selection, and feature engineering, leading to 66 combinations, we assessed final model performance. Average performance across combinations resulted in a mean absolute error (MAE) of 6.42Mgha−1. Using different techniques led to a range of MAE from 4.57 to 8.80Mgha−1 on average. The best and worst performances for an individual model were MAEs of 4.11 and 9.00Mgha−1. Models with lower performance were close to simply predicting yield from the average yield for each number of cuts (MAE of 9.86Mgha−1). Tuning and feature engineering reduced the MAE on average by 1.17 and 0.64Mgha−1, respectively. Feature selection removed nearly 40% of the features but increased the MAE by 0.19Mgha−1. The performance of models was improved by simple strategies such as decomposing weather attributes and detailing fertilisation. Evaluation of feature importance provided by the RReliefF feature selection algorithm was used to explain the performance gains. If empirical models are needed, they will rely on using advanced techniques, but they will need proper algorithm tuning and feature engineering to extract most of the information from datasets. Based on the results, we recommend following the presented workflow for the development of yield models.
In April 2021, the province of Ontario, Canada, was at the peak of its third wave of the COVID-19 pandemic. Intensive Care Unit (ICU) capacity in the Toronto metropolitan area was insufficient to ...handle local COVID patients. As a result, some patients from the Toronto metropolitan area were transferred to other regions.
A spreadsheet-based Monte Carlo simulation tool was built to help a large tertiary hospital plan and make informed decisions about the number of transfer patients it could accept from other hospitals. The model was implemented in Microsoft Excel to enable it to be widely distributed and easily used. The model estimates the probability that each ward will be overcapacity and percentiles of utilization daily for a one-week planning horizon.
The model was used from May 2021 to February 2022 to support decisions about the ability to accept transfers from other hospitals. The model was also used to ensure adequate inpatient bed capacity and human resources in response to various COVID-related scenarios, such as changes in hospital admission rates, managing the impact of intra-hospital outbreaks and balancing the COVID response with planned hospital activity.
Coordination between hospitals was necessary due to the high stress on the health care system. A simple planning tool can help to understand the impact of patient transfers on capacity utilization and improve the confidence of hospital leaders when making transfer decisions. The model was also helpful in investigating other operational scenarios and may be helpful when preparing for future outbreaks or public health emergencies.
Semiaquatic bugs (Hemiptera: Heteroptera: Gerromorpha) are distributed worldwide and play fundamental roles in limnic ecosystems. They are the most successful group of organisms to occupy the ...air-water interface, are important models to study ecology and evolution, and can be relevant tools in biomonitoring. Veliidae is the second most speciose family of semiaquatic bugs, but its internal classification, including subfamilies and genera, is artificial and based on symplesiomorphies. One of these non-monophyletic entities is
Breddin, 1898, the largest genus in the subfamily Veliinae.
In an effort to better classify the Veliinae, we describe
to hold five South American species previously placed in
. The new genus is characterized by the following combination of features: unusual coarse cuticular punctures throughout the thorax and abdomen; a pair of small, frosty, pubescent areas formed by a very dense layer of short setae on the anterior lobe of the pronotum; fore tibial grasping comb present only in males; middle tibia with a row of elongate dark-brown trichobothria-like setae on the distal third, decreasing in size distally; macropterous specimens with the apical macula of the forewings elongate and constricted at mid-length, reaching the wing apex; and the male proctiger with a pair of anterodorsal projections. Besides the description, a key to the species of
is provided, accompanied by illustrations and a species distribution map.
Eosinophils have been long associated with helminthic infections, although their functions in these diseases remain unclear. During schistosomiasis caused by the trematode
, eosinophils are ...specifically recruited and migrate to sites of granulomatous responses where they degranulate. However, little is known about the mechanisms of eosinophil secretion during this disease. Here, we investigated the degranulation patterns, including the cellular mechanisms of major basic protein-1 (MBP-1) release, from inflammatory eosinophils in a mouse model of
infection (acute phase). Fragments of the liver, a major target organ of this disease, were processed for histologic analyses (whole slide imaging), conventional transmission electron microscopy (TEM), and immunonanogold EM using a pre-embedding approach for precise localization of major basic protein 1 (MBP-1), a typical cationic protein stored pre-synthesized in eosinophil secretory (specific) granules. A well-characterized granulomatous inflammatory response with a high number of infiltrating eosinophils surrounding
eggs was observed in the livers of infected mice. Moreover, significant elevations in the levels of plasma Th2 cytokines (IL-4, IL-13, and IL-10) and serum enzymes (alanine aminotransferase and aspartate aminotransferase) reflecting altered liver function were detected in response to the infection. TEM quantitative analyses revealed that while 19.1% of eosinophils were intact, most of them showed distinct degranulation processes: cytolysis (13.0%), classical and/or compound exocytosis identified by granule fusions (1.5%), and mainly piecemeal degranulation (PMD) (66.4%), which is mediated by vesicular trafficking. Immunonanogold EM showed a consistent labeling for MBP-1 associated with secretory granules. Most MBP-1-positive granules had PMD features (79.0 ± 4.8%). MBP-1 was also present extracellularly and on vesicles distributed in the cytoplasm and attached to/surrounding the surface of emptying granules. Our data demonstrated that liver-infiltrating mouse eosinophils are able to degranulate through different secretory processes during acute experimental
infections with PMD being the predominant mechanism of eosinophil secretion. This means that a selective secretion of MBP-1 is occurring. Moreover, our study demonstrates, for the first time, a vesicular trafficking of MBP-1 within mouse eosinophils elicited by a helminth infection. Vesicle-mediated secretion of MBP-1 may be relevant for the rapid release of small concentrations of MBP-1 under cell activation.
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•We evaluated how auto-correlation affects machine learning sugarcane yield models.•We adapted the feature selection RReliefF algorithm for use with auto-correlated data.•Naive ...assumption of data-independence leads to underestimated generalization error.•Proposed protocol improves estimates of generalization error.•Model performance slightly improved without changing the machine learning techniques.
With the increased application of information technology in agriculture, data is being produced and used in an unprecedented scale. While these advances, combined with machine learning techniques, benefited yield modeling, most of the current literature about data-driven yield modeling has not yet accounted for potential sources of correlation in data, assuming independence between samples. In this scenario, random sampling can lead to correlated samples across sets being used for model evaluation. We implemented a spatially-aware protocol and compared it with the naive approach of assuming independence between samples. The protocols were applied through all the model development pipeline: data splitting for hold-out sets, feature selection, cross-validation for model adjustment and model evaluation. Three different machine learning techniques were used to create models in each protocol. The resulting models were evaluated both in the validation set created by each protocol and in a manually created independent set. This independent set ensured there was no auto-correlation between the samples used for modeling. We showed that assuming independence when modeling yield leads to underestimating model errors and overfit during model adjustment. Despite better error tracking, the model with the smallest error in the test set was not the model with the smallest validation error, suggesting overfit for the model selection. While this effect was small for the spatially-aware protocol, the effect was a lot stronger in the naive protocol. Future efforts in yield modeling should address the effect of spatial auto-correlation and other potential sources of correlation to improve correctness and robustness of the results.
Abstract Research on Pleistocene Amazonian refugia has predominantly targeted forest-dwelling taxa, although evidence suggests that endemic species have also evolved in peripheral Amazonian enclaves ...of open–dry habitats. In Rondônia, Brazil, Tropidurus lizards are restricted to savannah relicts that were once connected to the core Cerrado biome. These populations are currently allocated under Tropidurus oreadicus but hypothesized to comprise allopatric species that evolved in response to landscape changes induced by Pleistocene climatic fluctuations. Phylogenetic analyses support the monophyly of populations from savannah enclaves from Rondônia but place them as distantly related to T. oreadicus. We describe these populations as a new species with unprecedented levels of chromatic polymorphism. A pre-Pleistocene origin is inferred for this new taxon, and dating analysis indicates that Tropidurus species endemic to savannah enclaves diverged from relatives distributed in core open–dry biomes in a non-temporally overlapping fashion. Species distribution models estimate vast climatically suitable areas for the new species during the Last Interglacial, followed by significant contraction during the Last Glacial Maximum, and subsequent expansion and northward displacement towards the Holocene and the present. We conclude that landscape transformations played an important role in the evolution of lizards from enclaves, but their speciation history is temporally deeper than previously thought.
The log-logistic regression model is one of the most commonly used accelerated failure time (AFT) models in survival analysis, for which statistical inference methods are mainly established under the ...frequentist framework. Recently, Bayesian inference for log-logistic AFT models using Markov chain Monte Carlo (MCMC) techniques has also been widely developed. In this work, we develop an alternative approach to MCMC methods and infer the parameters of the log-logistic AFT model via a mean-field variational Bayes (VB) algorithm. A piecewise approximation technique is embedded in deriving the VB algorithm to achieve conjugacy. The proposed VB algorithm is evaluated and compared with frequentist and MCMC techniques using simulated data under various scenarios. A publicly available dataset is employed for illustration. We have demonstrated that our proposed Variational Bayes (VB) algorithm consistently produces satisfactory estimation results and, in most scenarios, outperforms the likelihood-based method in terms of empirical mean squared error (MSE). When compared to MCMC, similar performance was achieved by our proposed VB, and, in certain scenarios, VB yielded the lowest MSE. Furthermore, the proposed VB algorithm offers a significantly reduced computational cost compared to MCMC, with an average speedup of 300 times.
This study determines the relative efficiencies of a number of cancer treatment centers in Ontario, taking into account the differences among them so that their performances can be compared against ...the provincial targets. These differences can be in physical and financial resources, and patient demographics. An analytical framework is developed based on a three-step data envelopment analysis (DEA) model to build efficiency metrics for planning, delivery, and quality of treatment at each center. Regression analysis is used to explain the efficiency metrics and demonstrates how these findings can inform continuous improvement efforts.
Gerromorpha (Hemiptera: Heteroptera) comprises more than 2100 species of semiaquatic bugs, most of which have the ability to walk on the surface of the water. So far, 238 species have been recorded ...from Brazil, but several portions of the country remain poorly explored. The Metropolitan Region of Santarém (MRS), Pará State, Brazil, lacks faunistic and taxonomic studies concerning this group and the local fauna is under threat due to human actions.
Aiming to fill gaps concerning the diversity and distribution of Gerromorpha in the Amazon, a survey of the semi-aquatic bugs from the MRS is presented. Collections were made in 33 aquatic ecosystems in the different phytophysiognomies within this area from July 2019 to October 2020. As a result, a checklist with 44 species recorded from the three municipalities of the MRS is presented. Furthermore, three new species of the genus
Westwood, 1834 (
,
and
) are described, two species are recorded for the first time from Brazil (
Makhan, 2014 and
Galindo-Malagón, Morales & Moreira, 2021), two from Pará State (
Uhler, 1894 and
Polhemus & Polhemus, 1984) and 15 from the MRS (
Shaw, 1933,
Hungerford & Matsuda, 1957,
(Drake, 1942),
Westwood, 1834,
Magalhães & Moreira, 2016,
Bacon, 1948,
Bacon, 1948,
(Hungerford, 1929),
Drake & Maldonado-Capriles, 1952,
Polhemus & Polhemus, 1984,
(Drake, 1957),
(Hungerford, 1929),
(Hungerford, 1929),
(Drake & Harris, 1941) and
(Hungerford, 1929)).
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