High Sensitivity Area Research Articles

Sensitivity Analysis of Bistatic Scattering for Soil Moisture Retrieval

Soil moisture is one of the vital environmental variables in the land–atmosphere cycle. A study of the sensitivity analysis of bistatic scattering coefficients from bare soil at the Ku-band is presented, with the aim of deepening our understanding of the bistatic scattering features and exploring its potential in soil moisture retrieval. First, a well-established advanced integral method was adopted for simulating the bistatic scattering response of bare soil. Secondly, a sensitivity index and a normalized weight quality index were proposed to evaluate the effect of soil moisture on the bistatic scattering coefficient in terms of polarization and angular diversity, and the combinations thereof. The results of single-polarized VV data show that the regions with the maximum sensitivity and high quality index, simultaneously, to soil moisture are in the forward off-specular direction. However, due to the effect of surface roughness and surface autocorrelation function (ACF), the single-polarized data have some limitations for soil moisture inversion. By contrast, the results of two different polarization combinations, as well as a dual-angular simulation of one transmitter and two receivers, show significant estimation benefits. It can be seen that they all provide better ACF suppression capabilities, larger high-sensitivity area, and higher quality indices compared to single-polarized estimation. In addition, dual polarization or dual angular combined measurement provides the possibility of retrieving soil moisture in backward regions. These results are expected to contribute to the design of future bistatic observation systems.

Prioritization of potential soil erosion susceptibility region using fuzzy logic and analytical hierarchy process, upper Blue Nile Basin, Ethiopia

Soil erosion poses a global threat to soil loss, agricultural land deterioration, and crop yield decreases. This paper accounts for the establishment of sustainable land planning, and methods for evaluating soil erosion rates. The study was conducted based on the system complex analysis to prioritize soil erosion in Ribb watershed to improve soil and water conservation planning. Several geographical-environmental factors affecting soil erosion (land use, soil, slope, SPI, TWI, river Proximity, curvature, aspect) considered to assess potential soil erosion risk. The information levels were focused on expert experience, and the dynamic decision-making process built in a network framework. The weights for each layer were computed by R Studio fuzzy AHP package. The map of soil erosion susceptibility was developed by combining layers in a platform based on their weights and means of erosion-related incidents in regional surveys. Hence, the soil erosion map's overall results showed very high, high, moderate, low, and very low vulnerability to erosion with areal coverage of 13.4 %, 27.93 %, 32.74 %, 17.42 %, and 8.5 %, respectively. The susceptibility map demonstrates that high soil erosion sensitive areas with Fuzzy and AHP respectively cover 11.05 % and 15.75 %. The study indicates that priority should be given to high and very high erosion-prone areas in Rib watershed to adapt to climate change and control sedimentation problems in the Rib reservoir and Lake Tana.

Fuzzy-based multiple decision method for landslide susceptibility and hazard assessment: A case study of Tabriz, Iran

Due to the complexity of the causes of the sliding mass instabilities, landslide susceptibility and hazard evaluation are difficult, but they can be more carefully considered and regionally evaluated by using new programming technologies to minimize the hazard. This study aims to evaluate the landslide hazard zonation in the Tabriz region, Iran. A fuzzy logic-based multi-criteria decision-making method was proposed for susceptibility analysis and preparing the hazard zonation maps implemented in MATLAB programming language and Geographic Information System (GIS) environment. In this study, five main factors have been identified as triggering including climate (i.e., precipitation, temperature), geomorphology (i.e., slope gradient, slope aspect, land cover), tectonic and seismic parameters (i.e., tectonic lineament congestion, distribution of earthquakes, the unsafe radius of main faults, seismicity), geological and hydrological conditions (i.e., drainage patterns, hydraulic gradient, groundwater table depth, weathered geo-materials), and human activities (i.e., distance to roads, distance to the municipal areas) in the study area. The results of analyses are presented as a landslide hazard map which is classified into 5 different sensitive categories (i.e., insignificant to very high potential). Then, landslide susceptibility maps were prepared for the Tabriz region, which is categorized in a high-sensitive area located in the northern parts of the area. Based on these maps, the Bozgoosh-Sahand mountainous belt, Misho-Miro Mountains and western highlands of Jolfa have been delineated as risk-able zones.

N6-methyladenine-related genes affect biological behavior and the prognosis of glioma.

BackgroundAlthough aberrant expression of N6‐methyladenine (m6A) methylation‐related genes contribute to tumorigenesis in many solid tumors, the prognostic value of the m6A‐related genes and their correlation with clinicopathological features in gliomas need advanced study.MethodsThe clinical and sequencing data of 288 patients with glioma were extracted from Chinese Glioma Genome Atlas database. By univariate and multivariable Cox regression analysis, the m6A‐related prognostic genes were identified, and their correlation with clinicopathological features was further analysis. A nomogram was constructed by R software and the performance of it was assessed by calibration and time‐dependent receiver operating characteristic curve.ResultsNine m6A‐related genes were identified as independent prognostic factors, which were mostly enriched in RNA splicing, regulation of immune response and vesicle‐mediated transport. By expression value and regression coefficient of these genes, we constructed risk score of each patient, which was highly associated with clinicopathological features. Kaplan–Meier curve showed that the prognosis of patients with high‐risk scores was significantly worse than that with low‐risk scores (HR = 4.30, 95% CI = 3.16–5.85, p < 0.0001). A nomogram was constructed based on the nine m6A‐related genes signature and clinicopathological features with well‐fitted calibration curves (c‐index = 0.82), showing high specificity and sensitivity (area under the curve for 1‐, 3‐, and 5‐years survival probability = 0.874, 0.918, and 0.934).ConclusionsA nine m6A‐related genes signature was identified in gliomas. The m6A‐related risk score is a novel prognostic factor for patients with glioma, and is associated with clinicopathological features. Moreover, the nomogram based on the nine m6A‐related genes signature and clinicopathological features had good efficacy in predicting the survival probability.

Quantifying the Transition from Spiral Waves to Spiral Wave Chimeras in a Lattice of Self-sustained Oscillators

The present work is devoted to the detailed quantification of the transition from spiral waves to spiral wave chimeras in a network of self-sustained oscillators with two-dimensional geometry. The basic elements of the networks are the van der Pol oscillator and the FitzHugh-Nagumo neuron. Both models are in the regime of relaxation oscillations. We analyze the regime by using the indices of local sensitivity which enables us to evaluate the sensitivity of each individual oscillator at finite time. Spi-ral waves are observed in both lattices when the interaction between elements have the local character. The dynamics of all the elements is regular. There are no high-sensitive regions. We have discovered that when the coupling becomes nonlocal, the features of the systems significantly changes. The oscillation regime of the spiral wave center element switches to chaotic one. Besides this, a region with high sensitivity occurs around this oscillator. Moreover, we show that the latter expands in space with elongation of the coupling range. As a result, an incoherence cluster of the spiral wave chimera is formed exactly within this high-sensitive area. Formation of this cluster is accompanied by the sharp increase in values of the maximal Lyapunov exponent to the positive region. Furthermore, we explore that the system can even switch to hyperchaotic regime, when several Lyapunov exponents becomes positive.

Value of Neuropsychological Tests to Identify Patients with Depressive Symptoms on the Alzheimer's Disease Continuum.

Background:Depressive symptoms often co-occur with Alzheimer’s disease (AD) and can impact neuropsychological test results. In early stages of AD, disentangling cognitive impairments due to depression from those due to neurodegeneration often poses a challenge.Objective:We aimed to identify neuropsychological tests able to detect AD-typical pathology while taking into account varying degrees of depressive symptoms.Methods:A battery of neuropsychological tests (CERAD-NP) and the Geriatric Depression Scale (GDS) were assessed, and cerebrospinal fluid (CSF) biomarkers were obtained. After stratifying patients into CSF positive or negative and into low, moderate, or high GDS score groups, sensitivity and specificity and area under the curve (AUC) were calculated for each subtest.Results:497 participants were included in the analyses. In patients with low GDS scores (≤10), the highest AUC (0.72) was achieved by Mini-Mental State Examination, followed by Constructional Praxis Recall and Wordlist Total Recall (AUC = 0.714, both). In patients with moderate (11–20) and high (≥21) GDS scores, Trail Making Test-B (TMT-B) revealed the highest AUCs with 0.77 and 0.82, respectively.Conclusion:Neuropsychological tests showing AD-typical pathology in participants with low GDS scores are in-line with previous results. In patients with higher GDS scores, TMT-B showed the best discrimination. This indicates the need to focus on executive function rather than on memory task results in depressed patients to explore a risk for AD.

Monitoring Canine Myocardial Infarction Formation and Recovery via Transthoracic Cardiac Strain Imaging

Myocardial elastography (ME) is an ultrasound-based strain imaging method that aims to determine the degree of ischemia or infarction as a result of the change in the elastic properties of the myocardium. A survival canine model (n = 11) was employed to investigate the ability of ME to image myocardial infarction formation and recovery. Infarcts were generated by ligation of the left anterior descending coronary artery. Canines were survived and imaged for 4 days (n = 7) or 4 weeks (n = 4), allowing sufficient time for recovery via collateral perfusion. A radial strain-based metric, percentage of healthy myocardium by strain (PHMε), was developed as a marker for healthy myocardial tissue. PHMε was strongly linearly correlated with actual infarct size as determined by gross pathology (R2 = 0.80). Mean PHMε was reduced 1–3 days post-infarction (p < 0.05) at the papillary and apical short-axis levels; full infarct recovery was achieved by day 28, with mean PHMε returning to baseline levels. ME was capable of diagnosing individual myocardial segments as non-infarcted or infarcted with high sensitivity (82%), specificity (92%) and precision (85%) (area under the receiver operating characteristic curve = 0.90). The study therefore strengthens the ME premise that it can detect and assess myocardial infarction progression and recovery in vivo and could thus provide an important role in both disease diagnosis and treatment assesssment.

Producing forest fire susceptibility map via multi-criteria decision analysis and frequency ratio methods

Located in the Mediterranean basin, one of the world’s leading places in terms of forest fires, Turkey is one of the countries where forest fires are experienced very often due to both natural and socio-economic conditions. The objective of this study is to conduct a forest fire susceptibility analysis within the boundaries of Karabuk Forestry Directorate. This analysis was conducted considering the factors affecting the forest fire risk (elevation, slope, aspect, distance to road lines, distance to settlement, land surface temperature and stand type). The factors used in the study were analyzed using geographic information systems (GIS) techniques and analytic hierarchy process method and frequency ratio method. The forest fire susceptibility map produced was classified in 5 categories including very low, low, moderate, high and very fire susceptibility. In order to see how much the forest fire susceptibility map produced corresponds to reality, the forest fire susceptibility maps and the forest fire inventory map were highly compared, and a 73.92% correspondence was detected according to the multi-criteria decision analysis method, while a 76.42% correspondence was detected in the frequency ratio method. As a result, it was concluded that high- and very high-sensitive areas were dominant in the study area, and the site had a high forest fire potential. Ultimately, this study indicated that GIS could be used as a tool to help make effective decisions during forest fire planning.

Chromatic Pupilloperimetry Measures Correlate With Visual Acuity and Visual Field Defects in Retinitis Pigmentosa Patients

PurposeTo evaluate the ability of chromatic pupilloperimetry to identify visual field (VF) defects in patients with retinitis pigmentosa (RP) and to test the correlation between pupilloperimetry impairment and retinal structural and functional measures.MethodsThe pupil responses of 10 patients with RP (mean age, 41.3 ± 16.2 years) and 32 healthy age-similar controls (mean age, 50.7 ± 15.5 years) for 54 focal blue and red stimuli presented in a 24-2 VF were recorded. The pupilloperimetry measures were correlated with Humphrey VF mean deviation, best-corrected visual acuity, and ellipsoid zone area.ResultsSubstantially lower percentage of pupil contraction and maximal pupil contraction velocity (MCV) were recorded in patients with RP throughout the VF in response to blue and red stimuli. The mean absolute deviation (MADEV) in the latency of MCV (LMCV) was significantly larger in patients compared with controls for blue and red stimuli (P = 1.0 × 10−7 and P = 1.0 × 10−6, respectively). The LMCV MADEV differentiated between patients and controls with high specificity and sensitivity (area under the receiver operating characteristic curve, 0.987 and 0.973 for blue and red, respectively). The MADEV of LMCV for blue stimuli correlated with best-corrected visual acuity (ρ = 0.938, P = 5.9 × 10−5) and ellipsoid zone area (ρ = −0.857; P = 0.002). The MADEV of LMCV for red stimuli correlated with Humphrey VF mean deviation (ρ = −0.709; P = 0.022). Minimizing the test to 15 targets maintained a diagnosis of retinal damage in patients with RP with high sensitivity and specificity (area under the receiver operating characteristic curve, 0.927).ConclusionsThe chromatic pupilloperimetry measures significantly correlated with retinal function and structure in patients with RP at various disease stages.Translational RelevanceChromatic pupilloperimetry may enable objective assessment of visual field defects and visual acuity in RP.

Evaluating the Sensitivity of Growing Degree Days as an Agro-Climatic Indicator of the Climate Change Impact: A Case Study of the Russian Far East

Climate is a key factor in agriculture, but we are unable to adequately predict future climates. Although some studies have addressed the short and long-run impacts of climate change on agriculture, few of them specifically focused on the analysis of its thermal component. Climatic regions with an extreme thermal range are a special case, as seasonal contrasts complicate the picture. Based on the above, the purpose of the paper is twofold. First, we review methods and indices used for the estimation of changes in the thermal component of the climate and demonstrate the usefulness of a sensitivity assessment methodology that gives some indication of the likely spatial extent of areas of high or low sensitivity to climate change and the size of the potential impact of that change, which is specifically beneficial in regions with high temperature extremes. Secondly, we constructed a composite indicator, called the Growing Degree Day Sensitivity Index (GDDSI) and defined as the percentage change in Growing Degree Day (GDD) for warming scenarios +1, +2 and +3 °C. GDDs were calculated for threshold base air temperatures of 0, 5, 10 and 15 °C, and a high-temperature limit of 30 °C. A GDD sensitivity analysis was applied to the thermally extreme climate of the Russian Far East. We analyzed the data of 50 weather stations across the study region over the period 1966–2017. The results show a strong GDDSI north-to-south gradient. In most cases, the sensitivity does not increase significantly as the warming rate increases. The higher the base threshold, the higher the sensitivity: GDDs with a threshold at 15 °C had the highest sensitivity in the far north of the study area where conditions are currently marginal for crop growth. The sensitivity analysis circumnavigates the difficulty of uncertainty in knowing what future climate to expect and informs planning decisions. The mapped results are useful for identifying areas of high sensitivity to climate change as well as the magnitude of the potential impact of that change.

Screening for arrhythmia with the new portable single-lead electrocardiographic device (SnapECG): an application study in community-based elderly population in Nanjing, China.

SnapECG is a new handheld single-lead electrocardiograph (ECG) device used for arrhythmia screening, it is widely used in clinical practice but not in primary care. To evaluate the arrhythmia screening value of SnapECG among a community-based population. A cross-sectional community-based study of multistage stratified cluster sampling was conducted from March 1st to April 30th 2019. The sensitivities, specificities and the area under the receiver operating characteristic (AUCROC) curves of the SnapECG and reference 12-lead ECG on arrhythmia were calculated in three age-groups [50-64years, 65-74years, and over-75years]. A total of 2263 participants took part in the arrhythmia screening, these included 1479 aged 50-64 years, 602 aged 65-74years and 182 aged over-75years. The SnapECG categorized 1828 (80.8%) as sinus rhythm, 161 (7.1%) as premature atrial/ventricular contractions (PAVs/PCVs), 32 (1.4%) as possible atrial fibrillation (AF), 56 (2.5%) as supraventricular tachycardias or sinus bradycardia (SVT/SB) and 186 (8.2%) as unreadable. SnapECG had 89% sensitivity (95% CI 0.52-1.00) and 99% specificity (95% CI 0.97-0.99) of detecting AF in the 65-74years age-group. The AUCROC to detect AF was 0.94 for the 65-74years age-group, 0.77 for over-75years, 0.62 for the 50-64years. This study is the first community screening application of SnapECG. Main limitation is the SnapECG and the 12-lead ECG were not done simultaneously. In the people aged 65-74years, AF can be detected accurately by the SnapECG with high sensitivity, specificity and large area under the ROC curve, which might have the highest screening predictive accuracy.

Driving forest succession in karst areas of Chongqing municipality over the past decade

BackgroundKarst areas in southwestern China exhibit ecological degradation in the form of rocky desertification. Local governments launched large-scale afforestation and other ecological restoration programs to curb this trend. Soil thickness is a key limiting factor for vegetation restoration in Karst areas, but the relationship between ecological restoration and soil thickness remains unclear. Further, afforestation consumes large amounts of water, which impacts water supply in karst areas. In this study, we used GIS and statistical analyses to determine rocky desertification sensitivity and its driving factors in karst areas of Chongqing municipality over the past decade.ResultsSoil thickness is one of the key factors that restrict ecological restoration of rocky desertification. From 2000 to 2010, rocky desertification sensitivity in karst areas was on the rise along with an increase in afforestation. Areas of high sensitivity were mainly distributed in Pengshui County, Wulong District, and Youyang County; Shizhu County had the lowest overall incidence of desertification. Spatial distribution of rocky desertification was significantly affected by rainfall and soil thickness. Regression analysis showed that the main factors controlling changes in rocky desertification in natural forest over time were precipitation which explained 23.73% of total variance, and soil thickness which explained 23.42% of total variance. Soil thickness and soil water content had a higher correlation coefficient (at 0.516) in natural forests than in planted forests.ConclusionThis study showed that increases in soil thickness in a karst area had a significant positive impact on the fragile ecological environment. This indicates that ecosystem restoration in karst areas will benefit from addressing soil thickness.

Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network

Detection of cutaneous cancer on the face using deep-learning algorithms has been challenging because various anatomic structures create curves and shades that confuse the algorithm and can potentially lead to false-positive results. To evaluate whether an algorithm can automatically locate suspected areas and predict the probability of a lesion being malignant. Region-based convolutional neural network technology was used to create 924 538 possible lesions by extracting nodular benign lesions from 182 348 clinical photographs. After manually or automatically annotating these possible lesions based on image findings, convolutional neural networks were trained with 1 106 886 image crops to locate and diagnose cancer. Validation data sets (2844 images from 673 patients; mean [SD] age, 58.2 [19.9] years; 308 men [45.8%]; 185 patients with malignant tumors, 305 with benign tumors, and 183 free of tumor) were obtained from 3 hospitals between January 1, 2010, and September 30, 2018. The area under the receiver operating characteristic curve, F1 score (mean of precision and recall; range, 0.000-1.000), and Youden index score (sensitivity + specificity -1; 0%-100%) were used to compare the performance of the algorithm with that of the participants. The algorithm analyzed a mean (SD) of 4.2 (2.4) photographs per patient and reported the malignancy score according to the highest malignancy output. The area under the receiver operating characteristic curve for the validation data set (673 patients) was 0.910. At a high-sensitivity cutoff threshold, the sensitivity and specificity of the model with the 673 patients were 76.8% and 90.6%, respectively. With the test partition (325 images; 80 patients), the performance of the algorithm was compared with the performance of 13 board-certified dermatologists, 34 dermatology residents, 20 nondermatologic physicians, and 52 members of the general public with no medical background. When the disease screening performance was evaluated at high sensitivity areas using the F1 score and Youden index score, the algorithm showed a higher F1 score (0.831 vs 0.653 [0.126], P < .001) and Youden index score (0.675 vs 0.417 [0.124], P < .001) than that of nondermatologic physicians. The accuracy of the algorithm was comparable with that of dermatologists (F1 score, 0.831 vs 0.835 [0.040]; Youden index score, 0.675 vs 0.671 [0.100]). The results of the study suggest that the algorithm could localize and diagnose skin cancer without preselection of suspicious lesions by dermatologists.

Development of a balloon-style pressure vessel gondola for balloon-borne emulsion gamma-ray telescopes

A gamma-ray telescope using nuclear emulsions allows observations of stellar objects in the 0.01–100 GeV energy region with high angular resolution, polarization sensitivity, and large aperture area. The Gamma-Ray Astro-Imager with Nuclear Emulsion (GRAINE) project is designed to enable high-precision observation of cosmic gamma rays through the use of balloon-borne emulsion telescopes. We have developed a balloon-style pressure vessel gondola for the GRAINE 2018 balloon-borne experiment. It enables us to maintain robust and vacuum-packed emulsion chambers even at balloon altitudes. The greater part of the vessel is made of membrane materials consisting of ultra-thin polyurethane-coated polyester fabric. It is lightweight and portable, and can be used to expand the mounting area of the detector, unlike mostly metal vessels. Moreover, the absorption of signal gamma rays and background gamma-ray production due to interactions between cosmic rays and the vessel can be minimized. The pressure vessel gondola, equipped with a 0.38-m2 emulsion telescope and other equipment, was launched on April 26, 2018. During the whole observation (17 h 21 m), the internal pressure was kept above 230 hPa. The GRAINE project will start scientific observation using enlarged telescopes and the pressure vessel gondola is planned to include an expansion of the mounting area of the detector to ∼10 m2 while following the design on the GRAINE 2018 model.

Bioimaging of Pb and STIM1 in mice liver, kidney and brain using Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) and immunohistochemistry

Lead (Pb) pollution is one of the most serious environmental problems and has attracted worldwide attention. Pb causes hematological, central nervous system, as well as renal toxicity, and so on. Although many investigations about Pb in blood to evaluate pollution status and toxic effects have been reported, there are open question about biological behavior of Pb. In order to reveal any toxicological mechanisms or influences, we focused on the local distribution of Pb in mice organs. Lead acetate (100 mg/L and 1000 mg/L) in drinking water were given to the BALB/c mice (male, seven weeks of age, N = 24) for three weeks. Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) analysis revealed a homogenous distribution of Pb in the liver and inhomogeneous distribution in the kidney and brain. The hippocampus, thalamus, and hypothalamus had higher concentrations than other areas such as the white matter. Surprisingly, in the kidney, Pb tended to accumulate in the medulla rather than the cortex, strongly suggesting that high sensitivity areas and high accumulation areas differ. Moreover, distribution of stromal interacting protein 1 (STIM1) which is candidate gene of Pb pathway to the cells was homogenous in the liver and kidney whereas inhomogeneous in the brain. In contrast to our hypothesis, interestingly, Pb exposure under the current condition did not induce mRNA expressions for any candidate channel or transporter genes. Thus, further study should be conducted to elucidate the local distribution of Pb and other toxic metals, and pathway that Pb takes to the cells.

Impact of atmospheric turbulence and weather conditions on the performance of satellite-to-ground optical communication system based on multiaperture coherent receivers

For satellite-to-ground downlink optical communication systems, it is desirable to reduce the size, weight, and power profiles of the space terminals by employing high sensitivity and large collection area ground terminals. Multiaperture coherent receivers utilizing spatial diversity techniques can satisfy this requirement and have many advantages over the single large aperture coherent receivers. The influence of both atmospheric turbulence and weather conditions on the bit error rate performance of multiaperture coherent receivers utilizing maximum ratio combining, equal gain combining, and selection combining techniques is systematically investigated and compared for the satellite-to-ground downlink communication system. The results are useful for the design and adaptive optimization of the multiaperture coherent receiver-based downlink communication systems.

Toward GIS-Based Approach for Identification of Ecological Sensitivity Areas: Multi-Criteria Evaluation Technique for Promotion of Tourism in Soon Valley, Pakistan

Ecologically sensitive areas are sensitive regions which provide natural habitat to native and migratory wildlife. The area under study is Soon Valley which is of significant value since it is rich in natural resources and an important tourist attraction. It has the potential to benefit the communities’ environment, along with providing aesthetic, recreational and economical benefits. Special attention is required for the preservation of these areas to develop the tourism industry in this region. This paper aims to highlight the spatial locations of Soon Valley according to the ecological sensitivity. To achieve this purpose, ecological knowledge is integrated with geographic information system (GIS) and remote sensing techniques. An ecological assessment study was conducted based on the ecological indicators and their synthesis to identify ecologically significant and preference areas within the area under study. For this purpose, eight ecological indicators were defined and the spatial extent for each indicator was mapped in GIS. For analysis purpose, weightage factor and buffer area for each class were defined in accordance with the significance of the feature. The final analysis revealed four classes including very high (6%), high (20%), moderate (39%) and low (34%) ecological sensitive areas.

Ovarian Cancer Detection Using Plasma Metabolic Profiling

Ovarian cancer (OC) is a rare but potentially fatal disease, with increases in 5‐year survival rates associated with early diagnosis and timely treatment. Previous studies have shown that detectable disturbances in metabolite profiles are indicative of subtle pathophysiological or oncogenic changes. Consequently, metabolite markers may provide better diagnostic performance and earlier detection. Despite the important role of metabolism and product metabolites in the molecular pathogenesis of cancer, robust metabolic markers to enable screening, surveillance, and therapeutic monitoring of OC are still lacking. In this study, we present a mass spectrometry (MS)‐based metabolic profiling approach for identifying metabolic marker candidates that could enable highly sensitive and specific OC detection using human plasma samples.In this approach, both aqueous metabolites as well as lipids were detected. These metabolites, which are representative of many metabolic pathways of potential biological significance, were monitored in 218 plasma samples taken from three groups of patients (78 ovarian cancer patients, 50 patients with benign disease and 90 healthy controls) using LC‐MS/MS. Univariate methods were applied for significance testing. Multivariate statistical analyses were applied to determine latent factor structure as well build a predictive model using these 218 plasma samples. Resampling was performed to validate the diagnostic model using random subsets.Significance testing and fold change (FC) analysis were performed to determine candidate markers warranting further analysis. Of the detected compounds, a substantial portion of metabolites exhibited statistically significant differences between OC patients and healthy controls (q &lt; 0.05), and a robust number of metabolites demonstrated both q &lt; 0.05 and FC &gt; 2. The latter set of metabolites comprised the biomarker panel. A partial least squares discriminant analysis (PLS‐DA) model was established using the panel metabolites. This model proved to be powerful for distinguishing OC patients from healthy controls and showed strong potential for use as an early‐stage diagnostic. A receiver operating characteristic (ROC) curve generated based on the PLS‐DA model showed high sensitivity, good specificity, and excellent area under the curve. Permutation testing (cross validation) was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach. Pathway and enrichment analyses were conducted to resolve affected metabolic pathways. Results of the aforementioned analyses ubiquitously connoted alterations in pathways essential for tumor growth, metastasis, and immune escape mechanisms. The results of our pathway and enrichment analysis are highly commensurate with one another, suggesting high confidence in affected metabolic pathways. Our results indicate the effectiveness of this metabolomics approach for ovarian cancer diagnosis. Future studies should examine larger cohorts from multiple locations in addition to the altered metabolic pathways related to OC pathogenesis discovered in our study.Support or Funding InformationSupport from the College of Health Solutions at ASU is appreciated.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

GIS-Based Multi-Criteria Assessment and Seasonal Impact on Plantation Forest Landscape Visual Sensitivity

Visual sensitivity assessments identify the location of the high-sensitivity areas in terms of visual change. Studying the visual sensitivity of plantation forest landscapes and their seasonal changes can help resolve increasingly frequent conflicts between tourism and forest management activities, in the context of the multi-functional management of plantation forests. In this study, we used the geographic information system (GIS) and multi-criteria evaluation (MCE) methods combined with the analytic hierarchy process (AHP) to perform a visual sensitivity evaluation. Nine map-based criteria were selected, and the visual sensitivity of summer and autumn values were calculated, using data from sources including inventory data for forest management planning and design, digital elevation model (DEM), and aerial photographs. Vegetation uniformity (VU) and color diversity (CD) indices were constructed using three patch-level-based landscape indices, including area (AREA), fractal dimension index (FRAC), and proximity (PROX), to visualize the summer and autumn vegetation characteristics of a plantation forest landscape. We conducted a case study on the Saihanba Mechanical Forest Plantation, China’s largest forest plantation. The results were evaluated by experts, confirming the method to be reliable. This study provides an accurate, objective, and visualized evaluation method for the visual sensitivity of plantations for forest management units at the landscape scale. In analyzing the visual sensitivity of plantation forest landscapes, appropriate criteria, e.g., uniformity or diversity should be selected based on forest vegetation characteristics. When identifying high-sensitivity regions, it is necessary to simultaneously analyze areas with high visual sensitivity in different seasons and then superimpose the results.

Procalcitonin as an early marker of invasive bacterial infection in febrile children aged 1 month to 5 years of age

Objectives: To evaluate the role of serum procalcitonin as a marker of invasive bacterial infection in febrile children between 1 month to 5 years of age. METHOD: Febrile Children aged between 1 month to 5 years with temperature at admission of ≥ 38 0C (100.4 0F) and with no prior antibiotic use during the current febrile illness were studied prospectively. Results: At a cutoff value of 2 ng/ml for serum PCT levels the sensitivity of 90%, specificity 76%, positive predictability value 78%, negative predictability value of 88%, area under curve (AUC) of 0.935 with standard error of 0.0221 and 95% confidence interval of 0.892 to 0.979 was obtained. The optimum sensitivity and specificity was 86% and 84% respectively at PCT level of ≥ 2.27 ng/ml. Conclusions: Considering this high sensitivity and significant area under curve (AUC) it could be concluded that Serum PCT levels could serve a reliable early biomarker of invasive bacterial infection.