The Hidden Treasures of Preoperative Blood Assessment in Oral Cancer: A Potential Source of Biomarkers

(1) Background: Oral squamous cell carcinoma (OSCC) is a common malignancy, and the impact of immune and inflammatory mechanisms in its development and progression are of major interest. The aim of our study is to assess the prognostic potential of circulating immune and inflammatory elements determined preoperatively in patients with OSCC, as well as the development of a new compound parameter with predictive value. (2) Methods: We assessed preoperative fibrinogen (Fib) and the platelet-to-lymphocyte ratio (PLR) in 111 OSCC patients. Using a mathematic algorithm, we determined a composite parameter with cumulative information from Fib and PLR, named Fibrinogen-PLR Algorithm (FiPLA). Survival analysis, followed by bivariate and multivariate analyses, was subsequently conducted. (3) Results: Increased preoperative Fib and PLR levels were associated with poor outcome in OSCC (p = 0.0001 and p = 0.0015, respectively). Preoperative FiPLA values were also associated with poor patient survival (p < 0.0001). Multivariate analysis confirmed the independent prognostic role for FiPLA only (CI95% 1.232–67.770, p = 0.03), showing the superior predictive value of FiPLA compared to its individual components. (4) Conclusions: Preoperative assessments of circulating immune and inflammatory elements can provide high-quality prognostic information, and they represent valuable tools in clinical practice, facilitating the early risk stratification of patients with OSCC.

Differences between Severe and Nonsevere Warm-Season, Nocturnal Bow Echo Environments

Nocturnal bow echoes can produce wind damage, even in situations where elevated convection occurs. Accurate forecasts of wind potential tend to be more challenging for operational forecasters than for daytime bows because of incomplete understanding of how elevated convection interacts with the stable boundary layer. The present study compares the differences in warm-season, nocturnal bow echo environments in which high intensity [>70 kt (1 kt ≈ 0.51 m s−1)] severe winds (HS), low intensity (50–55 kt) severe winds (LS), and nonsevere winds (NS) occurred. Using a sample of 132 events from 2010 to 2018, 43 forecast parameters from the SPC mesoanalysis system were examined over a 120 km × 120 km region centered on the strongest storm report or most pronounced bowing convective segment. Severe composite parameters are found to be among the best discriminators between all severity types, especially derecho composite parameter (DCP) and significant tornado parameter (STP). Shear parameters are significant discriminators only between severe and nonsevere cases, while convective available potential energy (CAPE) parameters are significant discriminators only between HS and LS/NS bow echoes. Convective inhibition (CIN) is among the worst discriminators for all severity types. The parameters providing the most predictive skill for HS bow echoes are STP and most unstable CAPE, and for LS bow echoes these are the V wind component at best CAPE (VMXP) level, STP, and the supercell composite parameter. Combinations of two parameters are shown to improve forecasting skill further, with the combination of surface-based CAPE and 0–6-km U shear component, and DCP and VMXP, providing the most skillful HS and LS forecasts, respectively.

Establishing seasonal and alert influenza thresholds in Morocco

Background: Several statistical methods of variable complexity have been developed to establish thresholds for influenza activity that may be used to inform public health guidance. We compared the results of two methods and explored how they worked to characterize the 2017-2018 season.Methods: Historical data from the 2005/2006 to 2016/2017 seasons were provided by a network of 412 primary health centers in charge of influenza like illness (ILI) sentinel surveillance. We used the WHO averages and the moving epidemic method (MEM) to evaluate the proportion of ILI visits among all outpatient consultations (ILI%) as a proxy for influenza activity. We also used the MEM method to evaluate three seasons of composite data (ILI% multiplied by percent of ILI with laboratory-confirmed influenza) as recommended by WHO. Results: The WHO method estimated the seasonal ILI% threshold at 0.9%. The annual epidemic period began on average at week 46 and lasted an average of 18 weeks. The MEM model estimated the epidemic threshold (corresponding to the WHO seasonal threshold) at 1.5% of ILI visits among all outpatient consultations. The annual epidemic period began on week 49 and lasted on average 14 weeks. Intensity thresholds were similar using both methods. When using the composite measure, the MEM method showed a clearer estimate of the beginning of the influenza epidemic, which was coincident with a sharp increase in confirmed ILI cases. Conclusions: We found that the threshold methodology presented in the WHO manual is simple to implement and easy to adopt for use by the Moroccan influenza surveillance system. The MEM method is more statistically sophisticated and may allow a better detection of the start of seasonal epidemics. Incorporation of virologic data into the composite parameter as recommended by WHO has the potential to increase the accuracy of seasonal threshold estimation.

Establishing seasonal and alert influenza thresholds in Morocco

Background: Several statistical methods of variable complexity have been developed to establish thresholds for influenza activity that may be used to inform public health guidance. We compared the results of two methods and explored how they worked to characterize the 2017-2018 season.Methods: Historical data from the 2005/2006 to 2016/2017 seasons were provided by a network of 412 primary health centers in charge of influenza like illness (ILI) sentinel surveillance. We used the WHO averages and the moving epidemic method (MEM) to evaluate the proportion of ILI visits among all outpatient consultations (ILI%) as a proxy for influenza activity. We also used the MEM method to evaluate three seasons of composite data (ILI% multiplied by percent of ILI with laboratory-confirmed influenza) as recommended by WHO. Results: The WHO method estimated the seasonal ILI% threshold at 0.9%. The annual epidemic period began on average at week 46 and lasted an average of 18 weeks. The MEM model estimated the epidemic threshold (corresponding to the WHO seasonal threshold) at 1.5% of ILI visits among all outpatient consultations. The annual epidemic period began on week 49 and lasted on average 14 weeks. Intensity thresholds were similar using both methods. When using the composite measure, the MEM method showed a clearer estimate of the beginning of the influenza epidemic, which was coincident with a sharp increase in confirmed ILI cases. Conclusions: We found that the threshold methodology presented in the WHO manual is simple to implement and easy to adopt for use by the Moroccan influenza surveillance system. The MEM method is more statistically sophisticated and may allow a better detection of the start of seasonal epidemics. Incorporation of virologic data into the composite parameter as recommended by WHO has the potential to increase the accuracy of seasonal threshold estimation.

Arylesterase Activity of Paraoxonase-1 in Serum and Cerebrospinal Fluid of Patients with Alzheimer’s Disease and Vascular Dementia

Background: It has been suggested that circulating Paraoxonase-1 (PON1) and apolipoprotein A1 (APOA1), which closely interacts with the antioxidant enzyme, could be implicated in Alzheimer’s disease (AD) and vascular dementia (VaD) development. This study aimed to evaluate PON1 changes in serum and cerebrospinal fluid (CSF) as evidence for its association with AD or VaD. Methods: Serum PON-arylesterase activity was measured in patients with AD, VaD, and CONTROLS distributed in two cohorts: Ferrara cohort (FC: n = 503, age = 74 years) and Amsterdam Dementia cohort (ADC: n = 71, age = 65 years). In the last cohort, CSF PON-arylesterase, CSF β-amyloid1-42, p-tau and t-tau, and imaging biomarkers were also measured. Results: AD and VaD patients of FC showed significantly lower levels of serum PON-arylesterase compared to CONTROLS, but this outcome was driven by older subjects (>71 years, p < 0.0001). In the younger ADC, a similar decreasing (but not significant) trend was observed in serum and CSF. Intriguingly, PON-arylesterase per APOA1 correlated with t-tau in AD group (r = −0.485, p = 0.002). Conclusion: These results suggest that decreased peripheral PON-arylesterase might be a specific feature of older AD/VaD patients. Moreover, we showed that PON-arylesterase/APOA1 is inversely related to neurodegeneration in AD patients, suggesting a prognostic usefulness of this composite parameter.

Establishing seasonal and alert influenza thresholds in Morocco

Background: Several statistical methods of variable complexity have been developed to establish thresholds for influenza activity to inform public health guidance. We compared the results of two methods and explored how they worked to characterize the 2017-2018 season.Methods: Historical data from the 2005/2006 to 2016/2017 seasons were provided by a network of 412 primary health centers in charge of influenza like illness (ILI) sentinel surveillance. We used the WHO averages and the moving epidemic method (MEM) to evaluate the proportion of ILI visits among all outpatient consultations (ILI%) as a proxy for influenza activity. We also used the MEM method to evaluate three seasons of composite data (ILI% multiplied by percent of ILI with laboratory-confirmed influenza) as recommended by WHO.Results: The WHO method estimated the seasonal ILI% threshold at 0.9%. The annual epidemic period begins on average at week 46 and lasts an average of 18 weeks. The MEM model estimated the epidemic threshold (corresponding to the WHO seasonal threshold) at 1.5% of ILI visits among all consultations. The annual epidemic period began on week 49 and lasted on average 14 weeks. Intensity thresholds were similar using both methods. When using the composite measure, the MEM method showed a clearer estimate of the beginning of the influenza epidemic, which was coincident with a sharp increase in confirmed ILI cases.Conclusions: We found that the threshold methodology presented in the WHO manual is simple to implement and easy to adopt for use by the Moroccan influenza surveillance system. The MEM method is more statistically sophisticated and may allow a better detection of the start of seasonal epidemics. Incorporation of virologic data into the composite parameter as recommended by WHO has the potential to increase the accuracy of seasonal threshold estimation.

Parameter Optimization on FNN/PID Compound Controller for a Three-Axis Inertially Stabilized Platform for Aerial Remote Sensing Applications

This paper presents a composite parameter optimization method based on the chaos particle swarm optimization and the back propagation algorithms for a fuzzy neural network/proportion integration differentiation compound controller, which is applied for an aerial inertially stabilized platform for aerial remote sensing applications. Firstly, a compound controller combining both the adaptive fuzzy neural network and traditional PID control methods is developed to deal with the contradiction between the control precision and robustness due to disturbances. Then, on the basis of both the chaos particle swarm optimization and the back propagation compound algorithms, the parameters of the fuzzy neural network/PID compound controller are optimized offline and fine-tuned online, respectively. In this way, the compound controller can achieve good adaptive convergence so as to get high stabilization precision under the multisource dynamic disturbance environment. To verify the method, the simulations are carried out. The results show that the composite parameter optimization method can effectively enhance the convergence of the controller, by which the stabilization precision and disturbance rejection capability of the proposed fuzzy neural network/PID compound controller are improved obviously.

Entraining CAPE for Better Assessment of Tornado Outbreak Potential in the Warm Sector of Extratropical Cyclones

Convective available potential energy (CAPE) is known to lack skill in discussing the environments of tornadic and nontornadic storms, or those of tornado outbreaks and nonoutbreaks. In this paper, a composite analysis of extratropical cyclones that caused 15 or more tornadoes [outbreak cyclones (OCs)] and 5 or fewer tornadoes [nonoutbreak cyclones (NOCs)] in the United States in April and May between 1995 and 2012 shows that entraining-CAPE (E-CAPE), which considers the effects of the entrainment of environmental air, is useful in the analysis of the environments of OCs and NOCs. E-CAPE in the warm sector of OCs is larger than that in the warm sector of NOCs (statistically significant at the 95%–99% level). Moreover, the regions with large E-CAPE for both OCs and NOCs are more closely correlated with the locations of tornadoes than those with large CAPE. The larger E-CAPE near the center in the warm sector of OCs is due to greater moisture at low and midlevels that results from advection by strong southerly winds and synoptic-scale ascent, respectively. The composite analysis also shows that E-EHI, E-SCP, and E-STP, for which traditional CAPE used in the energy helicity index (EHI), supercell composite parameter (SCP), and significant tornado parameter (STP) is substituted by E-CAPE, are more strongly correlated with tornado locations than are the original EHI, SCP, and STP, respectively.

North American Supercell Environments in Atmospheric Reanalyses and RUC-2

A suite of modern atmospheric reanalyses is analyzed to determine how they represent North American supercell environments. This analysis is performed by comparing a database of Rapid Update Cycle (RUC-2) proximity soundings with profiles derived from the nearest grid point in each reanalysis. Parameters are calculated using the Sounding and Hodograph Analysis and Research Program in Python (SHARPpy), an open-source Python sounding-analysis package. Representation of supercell environments varies across the reanalyses, and the results have ramifications for climatological studies that use these datasets. In particular, thermodynamic parameters such as the convective available potential energy (CAPE) show the widest range in biases, with reanalyses falling into two camps. The North American Regional Reanalysis (NARR) and the Japanese 55-year Reanalysis (JRA-55) are similar to RUC-2, but other reanalyses have a substantial negative bias. The reasons for these biases vary and range from thermodynamic biases at the surface to evidence of convective contamination. Overall, it is found that thermodynamic biases feed back to other convective parameters that incorporate CAPE directly or indirectly via the effective layer. As a result, significant negative biases are found for indices such as the supercell composite parameter. These biases are smallest for NARR and JRA-55. Kinematic parameters are more consistent across the reanalyses. Given the issues with thermodynamic properties, better segregation of soundings by storm type is found for fixed-layer parameters than for effective-layer shear parameters. Although no reanalysis can exactly reproduce the results of earlier RUC-2 studies, many of the reanalyses can broadly distinguish between environments that are significantly tornadic versus nontornadic.

Use of Artificial Neural Network in Determination of Shade, Light Curing Unit, and Composite Parameters’ Effect on Bottom/Top Vickers Hardness Ratio of Composites

Objective.To assess the influence of light emitting diode (LED) and quartz tungsten halogen (QTH) light curing unit (LCU) on the bottom/top (B/T) Vickers Hardness Number (VHN) ratio of different composites with different shades and determination of the most significant effect on B/T VHN ratio of composites by shade, light curing unit, and composite parameters using artificial neural network.Method.Three composite resin materials [Clearfil Majesty Esthetic (CME), Tetric N Ceram (TNC), and Tetric Evo Ceram (TEC)] in different shades (HO, A2, B2, Bleach L, Bleach M) were used. The composites were polymerized with three different LED LCUs (Elipar S10, Bluephase 20i, Valo) and halogen LCU (Hilux). Vickers hardness measurements were made at a load of 100 g for 10 sec on the top and bottom surfaces and B/T VHN ratio calculated. The data were statistically analyzed with three-way ANOVA and Tukey test at a significance level of 0.05. The obtained measurements and data were then fed to a neural network to establish the correlation between the inputs and outputs.Results.There were no significant differences between the B/T VHN ratio of LCUs for the HO and B shades of CME (p>0.05), but there were significant differences between the B/T VHN ratio of LCUs for shade A2 (p<0.05). No significant difference was determined between the B/T VHN ratio of LCUs for all shades of TNC (p>0.05). For TEC, there was no significant difference between the B/T VHN ratio of halogen and LED LCUs (p>0.05), but a significant difference was determined among the LED LCUs (p<0.05). The artificial neural network results showed that a combination of the curing light and composite parameter had the most significant effect on the B/T VHN ratio of composites. Shade has the lowest effect on the B/T VHN ratio of composites.Conclusion.The B/T VHN ratio values of different resin-based composite materials may vary depending on the light curing device. In addition, the artificial neural network results showed that the LCU and composite parameter had the most significant effect on the B/T VHN ratio of the composites. Shade has the lowest effect on the B/T VHN ratio of composites.