Plasma oxylipin levels may predict Covid-19 patient outcomes. An observational and retrospective study.

Background The key role of inflammation in the progression of COVID-19 was evident right from the beginning of the pandemic. Consequently, many authors studied the onset and evolution of the cytokine storm. In contrast, other inflammatory mediators such as oxylipins have received almost no attention. Methods We conducted a monocentric observational and retrospective study (IMPRE-COVID-19) with patients (aged ≥ 18 years) admitted to Pisa University Hospital with COVID-19 related pneumonia. SARS-CoV-2 infection was confirmed by polymerase chain reaction in a nasopharyngeal swab, while pneumonia was demonstrated by CT scan. Oxylipin plasma levels were analysed in a convenient sample of 52 patients randomly selected from those that had a complete set of cytokine values evaluated for clinical purposes. In 12 cases, plasma samples collected on different days were available at the BMS Multispecialistic Biobank of Pisa University Hospital and were analysed to understand the evolution of the oxylipin levels during hospitalization. The two datasets that included oxylipin and cytokine values were analysed by principal component analysis (PCA), computation of Fisher s canonical variable, and a multivariate receiver operating characteristic (ROC) curve. Findings Between March and April 2020, 52 patients were enrolled of which 28 were hospitalised in COVID-19 wards, 20 in ICUs, and 4 who were initially hospitalised in the wards and who were then transferred to the ICUs due to deteriorating health conditions. Plasma samples collected on different days were available from 7 patients in the wards, 1 from an ICU, and 4 from patients who were hospitalised in both. The mean age of participants was 61 years (SD 16), 11 were females (21%), and 41 were males (79%), without significant differences between groups in terms of age and gender. PCA of oxylipin data led to a clear differentiation of samples collected in COVID-19 wards and ICUs. This differentiation had not been obtained with cytokine data. In addition, borderline samples were from patients hospitalised in COVID-19 wards that were about to be transferred to the ICUs, thus suggesting that differentiation is not a consequence of a different treatment, but somehow related to a diverse evolution of the pathology. Computation of Fisher s canonical variable identified the original input variables that were the most effective in discriminating between the two classes. The combination of the two datasets did not improve the discrimination, thus suggesting that oxylipins are more informative than cytokines for this purpose. A multivariate class model built using the four lowest-order principal components as the input variables, and COVID-19 ward samples as the target class, produced a ROC curve with a resulting area under the curve (AUC) equal to 0·92 – which is much higher than most AUC outcomes obtained for individual oxylipins. Interpretation After analysing the metabolic pathways of the most informative oxylipins, we speculate that more severe COVID-19 is associated with a selective deficiency of pro-resolving oxylipins leading to ineffective resolutive mechanisms of inflammation, likely worsened by endothelial damage. We believe that our oxylipin data suggest the possibility to predict the evolution of COVID-19 in individual patients at an early stage. Funding Institutional funds from the University of Pisa supported the study.

A correlation analysis of english learning strategies and english reading competencies of Aatthayomsueksa 1 students under Nakhon Ratchasima Provincial Administration organization in Thailand

English reading competencies and English learning strategies are fundamental both in studying academic subjects and in the field of technology. If both of them are necessities, they should be related and developed to improve our students’ learning. It was found that students’ mean score was low in an English reading competencies test; however, students’ scores were average in English learning strategies. Canonical variable analysis indicated that affective, compensatory and metacognitive strategies were efficiently related to literal comprehension. Moreover, memory strategies were efficiently related to critical comprehension.

Incipient fault detection of chiller based on improved CVA

The chiller plays an important role for providing comfort environment. Once, the incipient faults are missed, they may develop to be fatal faults and further lead to equipment damage and casualties. Nevertheless, the incipient fault in the running process of the chiller are easily neglected in noise. Moreover, the running variables of the chiller have dynamic characteristics, and each process variable is correlated with each other in each process, and a certain variable is interrelated at different times. To tackle these problems, we develop an improved canonical variable analysis (ICVA) method to detect the incipient fault in chiller units with significant dynamic characteristics. In the proposed method, the exponentially weighted moving average (EWMA) is first applied to filter the data. Then the canonical variable analysis is used to detect the fault. In this paper, ASHRAE RP-1043 experimental data are used to verify the proposed method. Simulation results show that compared with traditional CVA method, ICVA method has a higher fault detection rate for incipient fault.

A new fault detection scheme based on canonical independent component analysis with application to hot strip mill process

Aiming at the problems of inaccurate fault detection and error alarm in the process of hot strip mill process, a fault detection scheme of canonical independent component analysis is proposed. The new scheme first uses canonical variable analysis to calculate the canonical variable matrix of observation data, which effectively solves the problem of autocorrelation and cross-correlation. Then the canonical variable matrix is decomposed by independent component analysis to obtain independent elements. Finally, the data are monitored online through constructing statistics. It is proved that the accuracy of the scheme for identifying fault data is reached to 100%, and the misjudgment rate data are reduced to less than 0.6% through the simulation study of the hot strip mill process data.

Dynamics of defoliation of associated grasses

The behavior of variables related to defoliation dynamics was evaluated, and their respective oscillations in two intercropping of tropical climate grasses managed under two grazing intensities. We used pastures formed with two intercropping (BRS Zuri, Xaraés and Basilisk; BRS Quênia, Marandu and BRS Paiaguás), managed in two grazing intensities: 40 and 60% of the pre-grazing height. In the consortium between BRS Zuri, Xaraés and Basilisk, the first canonical variable explained 72.1 and 79.2% of the total variation of the defoliation pattern for the grazing intensity levels of 40 and 60%. In the consortium between BRS Quênia, Marandu and BRS Paiaguás, the first canonical variable explained 84.3 and 89.0% of the total variation of the defoliation pattern for the grazing intensity levels of 40 and 60%. The choice of forage species of tropical climate to form the consortium may be decisive in order to perpetuate plant diversity. From the population density of tillers, it is possible to observe that grasses belonging to functional groups A and B (Zuri, Xaraés, BRS Quênia and Marandu) have a higher probability of coexisting in the same area. The choice of forage species for the establishment of intercropped pastures is important to ensure the coexistence between them and the persistence of the consortium. The analysis of canonical variables assists in explaining the dynamics of defoliation of intercropping through the estimates of severity and frequency of defoliation of extended tiller and pseudostem.

Canonical analysis of climatic factors associated with the quality characteristics of drinking water of a city in São Paulo State

Several factors may contribute to changes in monitoring parameters of drinking water quality, especially climatic characteristics. Behavioral studies of these characteristics are relevant to the rational and sustainable use of water resources and better monitoring of the quality of water available for the population. To assess the association between water quality and climate, this research explored physical-chemical and microbiological characteristics considered important for the monitoring of water quality, analyzed in casual samples collected daily from the distribution system of a city, and considered monthly data of climatic characteristics from 2007 to 2011. The associations between these two sets of variables were assessed by the multivariate procedure of the canonical correlation analysis. The results indicate a positive correlation between the canonical variable formed by the linear combination of climatic variables and the canonical variable formed by the linear combination of water quality variables.