Spearman Correlation Matrix Research Articles

Expression pattern of long non-coding RNAs in treatment-naïve and medicated schizophrenia patients.

Schizophrenia is a disabling mental disorder that affects 1% of people over their lifetime. The etiology and mechanism of schizophrenia are very complex, and many genes are involved in many different signaling pathways in the etiology of this disease. According to recent studies, one of the important mechanisms altered in this disorder is the regulation of immune system and the inflammation mechanism. In the present study, we evaluated the peripheral blood expression pattern of four lncRNAs and three protein-coding genes in the treatment- naïve patients, and medicated patients compared with sex and age-matched controls. In the medicated-patients, expression levels of IFNG, IL18RAP, AC007278.2 were significantly up-regulated (P < 0.05); and the expression level of IFNG-AS1-001 was significantly down-regulated compared to healthy controls (P < 0.05). However, levels of IL18R1, AC007278.3 and IFNG-AS1-003 were not different between these groups. In the treatment-naïve patients, IFNG, IL18R1, IL18RAP, IFNG-AS1-001, AC007278.2, and AC007278.3 were significantly up-regulated compared to controls. On the other hand, IFNG-AS1-003 was significantly down-regulated in the treatment-naïve patients compared to controls. Based on the Spearman correlation matrix, there was a significant correlation between genes in the treatment-naïve patients. We also showed the high sensitivity and specificity of IFNG-AS1-003, IFNG, IL18R1, and AC007278.3 in the identification of treatment-naïve patients from controls. The current study contributes further evidence to the understanding of the role of lncRNAs in the pathogenesis of schizophrenia. Future research is necessary to establish the validity of lncRNAs as peripheral markers for this condition.

Robust Estimation for Number of Factors in High Dimensional Factor Modeling via Spearman Correlation Matrix

Determining the number of factors in high-dimensional factor modeling is essential but challenging, especially when the data are heavy-tailed. In this article, we introduce a new estimator based on the spectral properties of Spearman sample correlation matrix under the high-dimensional setting, where both dimension and sample size tend to infinity proportionally. Our estimator is robust against heavy tails in either the common factors or idiosyncratic errors. The consistency of our estimator is established under mild conditions. Numerical experiments demonstrate the superiority of our estimator compared to existing methods. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Peracetic acid treatment for removing steroid hormones in a pilot-scale wastewater installation

The global water scarcity challenge urges sustainable solutions such as wastewater reuse, which is crucial to alleviate pressure on dwindling freshwater sources. However, this approach must address the presence of emerging pollutants (EPs), demanding specific treatment processes to ensure water safety and environmental protection. Peracetic acid (PAA) has garnered global interest due to its high oxidation potential and production of low-toxicity byproducts, making it a promising alternative for wastewater decontamination. This study aimed to assess PAA efficacy in removing three EPs: estrone (E1), 17β-estradiol (E2), and 17α-ethinylestradiol (EE2). Conducted in a pilot-scale wastewater treatment facility using real wastewater, the study explored six operational conditions, with varying PAA concentrations (5 mg/L to 15 mg/L) and hydraulic retention times (HRT) of 5, 10, and 15 min. Control parameters were monitored throughout the study. The condition with 15 mg/L PAA and 15 min HRT was the most efficient achieving over 85 % removal efficiency for all three compounds. The condition with 15 mg/L PAA and 10 min HRT was less efficient, achieving 70 % removal for E1 and 60 % and 44 % for E2 and EE2, respectively. A Spearman correlation matrix identified temperature and E. coli as strongly correlated with EPs removal, potentially influencing PAA decay. Overall, PAA demonstrated effective removal of target EPs under real wastewater conditions, underscoring its viability as a sustainable alternative for enhancing wastewater treatment processes, contributing to environmental protection and public health. Future studies could explore the long-term efficiency of PAA application and its scalability.

Assessing water quality of kazerun county in southwest Iran: Multi-analytical techniques, deterministic vs. probabilistic water quality index, geospatial analysis, fuzzy C-means clustering, and machine learning

Water quality is critical to human health and the environment, especially in arid and semi-arid regions. Hence, the objectives of this study were to assess drinking water quality, identify critical parameters, investigate spatial patterns, and investigate accurate predictive models for the water quality index (WQI) in the Kazerun county in southwest Iran. To address this issue using deterministic and probabilistic WQI, correlation matrix, fuzzy C-Means (FCM) clustering, geostatistics, and adaptive network-based fuzzy inference system (ANFIS) with FIS generation by fuzzy C-Means (FCM-ANFIS) and sub-clustering (SC-ANFIS).Various software tools, including Excel, MATLAB, Python, and GIS were used to analyze groundwater data collected from 25 sampling sites. Water parameters, including pH, Cl−, SO4−2, EC, NO3−, NO2−, Ca2+, Mg2+, and F−, were examined. The results showed that F− levels were within acceptable limits set by the US EPA, but about one-third of sites posed potential health risks based on WHO guidelines. In one-third of regions, the levels of Mg2+ exceeded the recommended guidelines. In deterministic and probabilistic approaches, water quality was excellent in 68% and 81.3% of sites, respectively. Sobol sensitivity analysis identified SO4−2> Mg2+>Cl− > EC > F− > NO3− as significant WQI variables. Spearman correlation matrix shows substantial positive correlations between WQI and EC, F−, SO4−2, Mg2+, and Cl− were shown by the Spearman correlation matrix. Based on the FCM results, the southeast and central sites (56% of sites) have similar water quality. In comparison, the northern and four central sites (28% of sites) have distinct regional features, and the southern sites (16% of sites) had unique water quality characteristics. Geostatistical analyses showed that pH had the most substantial local clustering, while SO4−2 had significant high-value clustering. Furthermore, hot spot research revealed specific sites with high pH, F−, NO3−, and Cl− levels. The FCM-ANFIS model outperformed the SC-ANFIS model, emphasizing FCM clustering's importance in water quality forecasting accuracy.

Insights into the baseline blood pH homeostasis at admission and the risk of in-hospital mortality in COVID-19 patients.

Aim: A laboratory finding in critically ill COVID-19 patients is blood academia (pH <7.35). We investigated its cause in connection with the admission baseline blood pH homeostasis.Patients & methods: We retrospectively monitored the baseline blood pH homeostasis of 1215 COVID-19 patients who were admitted with pneumonia using data-driven knowledge. Two categories of patients were identified: non-survivors (107) and survivors (1108).Results: Non-survivors showed greater levels of lactate and lower blood pH, saturation, and partial pressure of oxygen than survivors. A bivariate Spearman's correlation matrix showed that the [HCO3-]/pCO2 and pCO2 of non-survivors exhibited an unmatched connection, but not in the survivor group. When comparing non-survivors to survivors, the dendrograms derived from the bivariate comparison matrix showed differences in gasometry parameters like blood pH, [HCO3-]/pCO2 ratio, anion gap and pO2.Conclusion: The little variations in the gasometry readings between survivors and non-survivors upon admission suggested abnormal changes in the complementary renal and respiratory systems that bring blood pH back to normal. In advanced COVID-19, modest blood acid-base imbalances could become blood acidemia if these compensatory strategies were overused. Data-driven monitoring of acid-base parameters may help predict abnormal blood pH and the advancement of metabolic acidemia before it is too late.

Hypoxic burden and sleep hypoventilation in obese patients

IntroductionNovel biomarkers of hypoxic load have emerged, as sleep apnea-specific hypoxic burden which provides more precise assessment of intermittent hypoxemia severity. Our main objective was to assess the potential benefit of hypoxic burden to identify obesity-related sleep hypoventilation. We hypothesized that hypoxic burden may help diagnose obesity-related sleep hypoventilation better than usual sleep respiratory measures (i.e., apnea-hypopnea index (AHI), mean SpO2, time with SpO2 < 90 %). MethodsThis retrospective study was conducted from June 2022 to October 2023 at the University Hospital of Rouen, France. All consecutive obese patients (BMI ≥30 kg/m2), adults, with no other respiratory or neurological diseases who underwent a polysomnography or polygraphy with concomitant capnography were included. Sleep hypoventilation was defined according to American Academy of Sleep Medicine criteria based on transcutaneous CO2 monitoring (PtcCO2). Diagnostic performance of sleep-related respiratory measures i.e., sleep apnea-specific hypoxic burden, apnea-hypopnea index (AHI), mean SpO2, time with SpO2 < 90 % was evaluated using Receiver Operating Characteristic (ROC) curves. Correlations between sleep-related respiratory measures were assessed by a Spearman correlation matrix. ResultsAmong 107 obese patients with analyzed capnography, 37 (35 %) had sleep hypoventilation. Patients were 53 ± 14 years old, mean BMI = 38 ± 6 kg/m2, mean AHI = 26.5 ± 25/h, mean hypoxic burden = 67 ± 109 %min/h, mean SpO2 = 91.5 ± 3 %, mean time with SpO2<90 % = 19.4 ± 28 %, mean PtcCO2 = 6.2 ± 0.7 kPa. A low positive correlation was found between hypoxic burden and mean PtcCO2 (r = 0.4, p < 0.001). Multivariate logistic regression model explaining sleep hypoventilation was insufficient with area under ROC curve of hypoxic burden estimated at 0.74 (95 % CI 0.65 to 0.84). ConclusionHypoxic burden has low correlation with transcutaneous CO2 pressure and a low ability to diagnose obesity-related sleep hypoventilation.

Fertility and quality of arable soils in Poland: spatial–temporal analysis of long-term monitoring

Soil quality is a globally important issue from the point of view of food production, maintenance of appropriate environmental quality and ecological balance. Assessing its quality and fertility using indices is one of the methods that make it possible to formulate recommendations for good soil management. The aim of the study was, therefore, to determine the spatial and temporal distribution of soil properties in the context of soil quality assessment (SQI) and soil fertility assessment (SFI, SEF, NIV, and SSFI) using the example of a Central European country (Poland). The inverse distance-weighted spatial interpolation technique was used to estimate the spatial distribution of soil quality and fertility indicators. So far, no research has been carried out that would include a comprehensive analysis of soil fertility and quality indicators in such a large research area over many years. The results of 216 points of monitoring the chemistry of arable soils in Poland from the period 1995–2020 for 28 physicochemical soil parameters were considered. The analyses carried out showed significant variability in the properties of the described soils in Poland, as evidenced by the principal component analysis (PCA) and the coefficient of variation (exceptions: bulk density, pH). It was found that heavy metals (Zn, Cd, Cu) were responsible for the deterioration of soil properties. The results obtained for different indices were different (SFI – most soils with good fertility, SEF – high fertility, NIV – soils highly enriched with nutrients, SQI – average soil quality). It was found that the SSFI is the most appropriate indicator among the analyzed indicators for Polish conditions in relation to arable soils, as it is adapted and calibrated to the specifics of this area. The Spearman correlation matrix showed that the largest group of statistically highly significant parameter pairs belonged to heavy metals (Ni/Zn, Zn/Pb, Zn/Cu, Ni/Cu). In contrast, the strongest correlations were recorded for Ni (with effective cation exchange capacity (ECEC), Mn, Mgav, Zn, Cu). The assessment revealed limiting factors and temporal trends in the overall evaluation of the quality of the country’s agricultural soils, which are important from the point of view of both sustainable development and agricultural production.

Immune cell infiltration and inflammatory landscape in primary brain tumours

BackgroundPrimary malignant brain tumours are more than one-third of all brain tumours and despite the molecular investigation to identify cancer driver mutations, the current therapeutic options available are challenging due to high intratumour heterogeneity. In addition, an immunosuppressive and inflammatory tumour microenvironment strengthens cancer progression. Therefore, we defined an immune and inflammatory profiling of meningioma and glial tumours to elucidate the role of the immune infiltration in these cancer types.MethodsUsing tissue microarrays of 158 brain tumour samples, we assessed CD3, CD4, CD8, CD20, CD138, Granzyme B (GzmB), 5-Lipoxygenase (5-LOX), Programmed Death-Ligand 1 (PD-L1), O-6-Methylguanine-DNA Methyltransferase (MGMT) and Transglutaminase 2 (TG2) expression by immunohistochemistry (IHC). IHC results were correlated using a Spearman correlation matrix. Transcript expression, correlation, and overall survival (OS) analyses were evaluated using public datasets available on GEPIA2 in Glioblastoma (GBM) and Lower Grade Glioma (LGG) cohorts.ResultsSeven out of ten markers showed a significantly different IHC expression in at least one of the evaluated cohorts whereas CD3, CD4 and 5-LOX were differentially expressed between GBMs and astrocytomas. Correlation matrix analysis revealed that 5-LOX and GzmB expression were associated in both meningiomas and GBMs, whereas 5-LOX expression was significantly and positively correlated to TG2 in both meningioma and astrocytoma cohorts. These findings were confirmed with the correlation analysis of TCGA-GBM and LGG datasets. Profiling of mRNA levels indicated a significant increase in CD3 (CD3D, CD3E), and CD138 (SDC1) expression in GBM compared to control tissues. CD4 and 5-LOX (ALOX5) mRNA levels were significantly more expressed in tumour samples than in normal tissues in both GBM and LGG. In GBM cohort, GzmB (GZMB), SDC1 and MGMT gene expression predicted a poor overall survival (OS). Moreover, in LGG cohort, an increased expression of CD3 (CD3D, CD3E, CD3G), CD8 (CD8A), GZMB, CD20 (MS4A1), SDC1, PD-L1, ALOX5, and TG2 (TGM2) genes was associated with worse OS.ConclusionsOur data have revealed that there is a positive and significant correlation between the expression of 5-LOX and GzmB, both at RNA and protein level. Further evaluation is needed to understand the interplay of 5-LOX and immune infiltration in glioma progression.

Body condition scoring facilitates healthcare monitoring in Hermann's Tortoises (Testudo hermanni ssp.).

Clinical assessment of body condition is crucial in captive and free-ranging reptiles, since a large percentage of diseases result from inadequate nutrition. However, preventive health care is restricted by the lack of a practical method for the assessment in tortoises. Pre-existing evaluation systems based on weight and shell measurements are laborious and ignore the clinical presentation of the animal. The present study aimed to facilitate the assessment by establishing a body condition score. A total of 373 Hermann's Tortoises (Testudo hermanni) (n = 281 tortoises kept as pets in Germany and n = 92 tortoises originating from a free-ranging population (68) or a rearing station (24) in France) were examined and data (weight (g), carapace length (cm), width (cm), height (cm)) were recorded in a standard protocol between October 2020 and October 2021. A modified version of a body condition score for Mojave Desert Tortoises (Gopherus agassizii) (1 = cachectic, 3 = ideal, 5 = obese) was utilized and tested against pre-existing shell measurement systems (Jackson's ratio, body condition index, volume condition index, circumferential product). German captive tortoises were significantly heavier and larger than French specimens. In the Spearman's correlation matrix, the body condition score showed a statistically significant correlation with all measurement methods in the total population of captive tortoises (Testudo hermanni boettgeri), with a medium correlation strength, and a lack of correlation in free-ranging tortoises (Testudo hermanni hermanni). However, individual animal data suggested misleading results of mathematical equations in terms of body condition. Clinical evaluation of tortoises, including a body condition score, should be considered essential to provide good healthcare and should be an integral part of general examination.

Comparative study of biomodels manufactured using 3D printing techniques for surgical planning and medical training

ABSTRACT Objectives To obtain 3D printed bone models with a haptic sensation similar to that of the real bone, which will help the surgeon to learn and improve based on practice. Methods From computed tomography, 3 digital anatomical models of the human proximal femur were created and, by modifying the printing parameters, both cortical and trabecular tissues were simulated, which were combined in a different cortico-cancellous interface depending on the bone segment. The 3 equivalent models obtained were compared with a commercial Sawbone synthetic model and subjected to a series of blind surgical practice trials performed by 5 TOC specialists from a hospital, each of them with different degrees of expertise. A statistical analysis of the qualitative data collected based on the Wilcoxon test, the Spearman correlation matrix, and the Validity Ratio Coefficient was performed. Results The deviations observed in the dimensional study are less than 0.2 millimeter, which confirms the validity of the 3DP-FFF technology to geometrically recreate personalized biomodels with high anatomical precision. Conclusions The reproductions obtained have given rise to a reliable method that professionals can refine to plan operations with the consequent reduction of time and risks for the patient, as well as for medical training.

New approach into human health risk assessment associated with heavy metals in surface water and groundwater using Monte Carlo Method

This study assessed the environmental and health risks associated with heavy metals in the water resources of Egypt's northwestern desert. The current approaches included the Spearman correlation matrix, principal component analysis, and cluster analysis to identify pollution sources and quality-controlling factors. Various indices (HPI, MI, HQ, HI, and CR) were applied to evaluate environmental and human health risks. Additionally, the Monte Carlo method was employed for probabilistic carcinogenic and non-carcinogenic risk assessment via oral and dermal exposure routes in adults and children. Notably, all water resources exhibited high pollution risks with HPI and MI values exceeding permissible limits (HPI > 100 and MI > 6), respectively. Furthermore, HI oral values indicated significant non-carcinogenic risks to both adults and children, while dermal contact posed a high risk to 19.4% of samples for adults and 77.6% of samples for children (HI > 1). Most water samples exhibited CR values exceeding 1 × 10–4 for Cd, Cr, and Pb, suggesting vulnerability to carcinogenic effects in both age groups. Monte Carlo simulations reinforced these findings, indicating a significant carcinogenic impact on children and adults. Consequently, comprehensive water treatment measures are urgently needed to mitigate carcinogenic and non-carcinogenic health risks in Siwa Oasis.

Biochar derived from traditional Chinese medicine residues: An efficient adsorbent for heavy metal Pb(II)

Biochar (BC) is widely used in the remediation of soil and wastewater polluted by heavy metals, but there are few reports on the characteristics of biochar derived via pyrolysis from different traditional Chinese medicine residues (TCMRs). In this study, biochars were prepared by slow pyrolysis of five common Chinese medicine residues, namely, Salvia miltiorrhiza (DNS), Ligusticum striatum (CX), Angelica sinensis (DG), Codonopsis pilosula (DGS), and Astragalus membranaceus (HQ). The biochars were systematically investigated by determining their physicochemical properties and using common characterization techniques. The Spearman correlation matrix between factors was used to examine relationships between properties of different biochars. Batch adsorption experiments were carried out to investigate the adsorption characteristics of biochar on Pb(II) and the mechanisms involved. The results showed that the physicochemical properties and adsorption performance of biochar were related to the type of its pharmaceutical residue. Biochar produced from materials with higher lignin content showed a better adsorption of the heavy metal Pb(II). All biochars were alkaline, with yields ranging from 29.30 to 38.65 %, and the main structure comprised of mesopores and macropores. The FT-IR and Boehm experiments revealed that the various TCMR biochars contained comparable functional groups, but their content varied. XRD and TEM results show that all biochar is amorphous with a crystalline structure, with the surface dominated by cellulose crystals and graphitic carbon. The O/C ratio (<0.2) and H/C ratio (<0.6) of biochars suggested that it had a desirable half-life. The TGA results confirmed its stability in the environment. The results of mineral experiments confirm the enrichment of the mineral content of biochar during biomass pyrolysis.The biochars' adsorption kinetics followed pseudo-second-order models (R2 > 0.99), and their isotherms were consistent with the Langmuir model (R2 > 0.99), indicating a monolayer chemisorption process. The biochar samples exhibited varying adsorption capacities for Pb(II), with the highest capacity observed for BDNS (36.42 mg/g). The adsorption mechanism mainly involved precipitation, complexation with oxygen-containing functional groups, and ion exchange. This study indicates that biochars from herbal residues exhibit promising potential for adsorbing heavy metal Pb(II), suggesting biochar production as a viable method for recycling herbal residues.

Evaluation of Lead and Iron Content in Different Stages of Water Treatment Facilities within Otuoke and Yenagoa Metropolis, Bayelsa State, Nigeria

The mechanism of keeping water safe by improving its quality makes it easily accessible for community health. The objective of this work was to evaluate the levels of lead and Iron in the domestic water supply system at Ekeki Housing Estate Yenegoa local government and Otuoke community in Ogbia local government in Bayelsa State, Nigeria. AAS version 5.0 Model was used to analyze Iron and Lead after acid digestion. Results obtained were compared with WHO standard, and statistically inferences were drawn using ANOVA and Spearman correlation matrix. All water sampled presented values of lead between (0.02-0.64) mg/L expect for point I3 and I4 which conformed to 0.01mg/L, while Iron values ranged from (0.01-5.3) mg/L. Most of the results obtained exceeded the WHO standard of 0.01 mg/L for lead and 0.03mg/L respectively. The research findings had shown that most treatment processes adopted were not suitable for treatment of the contaminants, hence the need to review treatment processes, distribution and monitoring of the source.

Low-Income Older Adults' Vulnerability to Anticholinergic Medication-Associated Frailty.

A growing body of research supports the negative impact of anticholinergic drug burden on physical frailty. However, prior research has been limited to homogeneous white European populations, and few studies have evaluated how anticholinergic burden tools compare in their measurement function and reliability with minority community-dwelling adult populations. This study investigated the association between anticholinergic drug exposure and frailty by conducting a sensitivity analysis using multiple anticholinergic burden tools in a diverse cohort. A comprehensive psychometric approach was used to assess the performance of five clinical Anticholinergic Burden Tools: Anticholinergic Cognitive Burden Scale (ACB), Anticholinergic Drug Scale (ADS), average daily dose, total standardized daily doses (TSDD), and Cumulative Anticholinergic Burden scale (CAB). Spearman correlation matrix and intraclass correlation coefficients (ICC) were used to determine the association among the variables. Ordinal logistic regression is used to evaluate the anticholinergic burden measured by each scale to determine the prediction of frailty. Model performance is determined by the area under the curve (AUC). The cohort included 80 individuals (mean age 69 years; 55.7% female, 71% African American). All anticholinergic burden tools were highly correlated (p < 0.001), ICC3 0.66 (p < 0.001, 95% confidence interval (CI) 0.53-0.73). Among individuals prescribed anticholinergics, 33% were robust, 44% were prefrail, and 23% were frail. All five tools predicted prefrail and frail status (p < 0.05) with low model misclassification rates for frail individuals (AUC range 0.78-0.85). Anticholinergic burden tools evaluated in this cohort of low-income African American older adults were highly correlated and predicted prefrail and frail status. Findings indicate that clinicians can select the appropriate instrument for the clinic setting and research question while maintaining confidence that all five tools will produce reliable results. Future anticholinergic research is needed to unravel the association between interventions such as deprescribing on incident frailty in longitudinal data.

Relationship between swimming speed, intra-cycle variation of horizontal speed, and Froude efficiency during consecutive stroke cycles in adolescent swimmers.

The purpose of this study was to investigate the relationship between swimming speed, intra-cycle variation of horizontal speed of displacement (dv), and Froude efficiency (ηF) in front-crawl during three consecutive stroke cycles. The sample consisted of 15 boys aged 16.07 ± 0.77 years and 15 girls aged 15.05 ± 1.07 years. Swimming speed, dv and ηF were measured during a 25 m front-crawl trial. Three consecutive stroke cycles were measured. Swimming speed showed a non-significant stroke-by-stroke effect (F = 2.55, p = 0.087, η2 = 0.08), but a significant sex effect (F = 90.46, p < 0.001, η2 = 0.76). The dv and ηF had the same trend as the swimming speed for the stroke-by-stroke effect, but a non-significant sex effect (p > 0.05). The Spearman correlation matrix between swimming speed and dv, and swimming speed and ηF showed non-significant correlations for the three stroke cycles in both sexes. However, the tendency of the former was not always inverse, and the latter was not always direct. Coaches and swimmers need to be aware that lower dvs are not always associated with faster swimming speeds and vice-versa, and that ηF is a predictor of swimming speed, not dv.

Salivary Biomarkers and their Relationship with Periodontal Clinical Parameters: A Cross-Sectional Study

Background: Traditionally, periodontal clinical parameters are used to diagnose and design standardized treatment plans. The scientific literature has not widely reported the inclusion of salivary biomarkers in this diagnostic and therapeutic process. Objectives: To analyze the correlation between salivary biomarkers and periodontal clinical parameters of a group of patients undergoing the periodontal maintenance phase in a private dental office located in the southwest of Colombia. Material and Methods: A cross-sectional study was carried out. A sample of 92 patients undergoing the periodontal maintenance phase was analyzed. Conventional periodontal parameters were determined, and salivary biomarkers were measured by chromatography (cariogenic bacteria, acidity, buffering capacity, blood, and erythrocytes). To determine its correlation, a bivariate statistical analysis was developed. Results: According to Spearman's correlation matrix, among the periodontal clinical parameters, there were statistically significant correlations between the extension and severity of the complete and proximal attachment loss (r=0.93) and between the bleeding on probing (BOP) and the plaque index (PI) (r= 0.37). Within the salivary biomarkers, a statistically significant correlation was found between acidity and the buffering capacity of saliva (r= -0.54); between buffering capacity and proteins (r=0.36); between blood and erythrocytes (r=0.42); between blood and proteins (r=0.58), and between erythrocytes and proteins (r=0.48). Finally, a statistically significant correlation between periodontal parameters and salivary biomarkers was observed between teeth lost due to periodontal disease and acidity (r=0.26) and between teeth lost and buffer capacity (r=0.30). Conclusion: Periodontal parameters and salivary biomarkers correlate with variables of the same group to which they belong. Still, only the variable teeth lost due to periodontal disease correlates with acidity and buffer capacity. The findings suggest that both periodontal parameters and salivary biomarkers should be evaluated throughout the periodontal process. It is possible that both parameters could express different moments of the pathophysiology of the disease.

Quantifying quantitative correlation of provider selection influences cloud security

The cloud computing has been able to help users to access the data easily and effectively. However, cloud security is highly emphasized to cloud users to ensure data is securely stored. The cloud security can be handled well by chosen trusted cloud service provider in getting high impact on the cloud security. The relationship between cloud security with the provider selection is much needed to ensure the extent to which data is securely stored in a cloud. Therefore, in this paper the quantitative method was conducted to measure the correlation between the selected the right cloud service provider influence the cloud security. Thus, knowledgeable person in having the experiences in using the cloud service was taking from two institution of higher learning (IHL) as a respondent. In addition, variability and normality data analysis was firstly conducted to obtain the consistency of the data. Then, the correlation between cloud security factor and provider selection factor was conducted using spearman correlation matrix and scatter graph in identifying the closely and significant the value in influencing between the factors. Thus, the correlation relationship analysis result shown the selected the right cloud provider’s give higher impact to cloud security.

Machine learning prediction of delignification and lignin structure regulation of deep eutectic solvents pretreatment processes

Prediction of the pretreatment efficiency of lignocellulosic biomass with ternary deep eutectic solvents (DES) containing Lewis acids by machine learning (ML). Principal component analysis, partial least square method, spearman correlation matrix, random forest, extreme gradient boosting and deep neural network were used to elucidate the correlation between 77 variables and the mechanism of lignin depolymerization. The effects of raw material composition, reaction conditions, physicochemical properties of DES and structural parameters in lignin on 9 target variables including β-O-4 bond, β-β bond, β-5 bond, weight average molecular weight, number average molecular weight, polydispersity index, ratio of syringyl units to guaiacyl units, content of phenolic hydroxyl groups and delignification were analyzed. Multivariate analysis showed that temperature, polarity related parameters of HBD and acidity of Lewis acids contributed significantly to the degree of lignin depolymerization. The types and fracture mechanisms of the bonds between different structural units of lignin can be determined by the analysis of structural parameters. XGBoost model has the best performance among all the ML models, and the R square of the test sets for the target variables is above 0.76. Feature importance analysis showed that structural parameters significantly affected the pretreatment effect. The physical and chemical parameters of HBD, such as dipole moment, Log P and surface tension should be paid attention to in the design of DES. The study of the weak intermolecular forces in the lignin and DES systems is beneficial to reveal the mechanism of the pretreatment process. This study provides novel insights into the structural regulation and high-value utilization of lignin in the process of DES pretreatment of lignocellulosic biomass.

Development of a Quality Index to Evaluate the Impact of Abiotic Stress in Saline Soils in the Geothermal Zone of Los Negritos, Michoacán, Mexico

In recent years, salinity-induced soil quality impairment and the misuse of management practices have led to the reduced productivity of agroecosystems. This has prompted a search for simple and effective agricultural management strategies that improve the sustainability of agricultural production through soil quality assessments. In this context, the objective of this study was to establish an integrated soil quality index (SQI) by assessing the influence of different types of abiotic stress in two different seasons, using physical, chemical and biological indicators at three sites in the geothermal zone of “Los Negritos”, Michoacán, Mexico. Thirty-nine indicators related to soil fertility attributes and C, N, P, and S cycling—identified as the total dataset (TDS)—were evaluated. Principal component analysis (PCA) and the Spearman correlation matrix (r2 ≥ 0.6) were used to calculate the SQI using an integrated quality index (IQI) equation, with the indicators total nitrogen (TN), cation exchange capacity (CEC), lithium (Li), and zinc (Zn) identified as the minimum dataset (MDS). Significantly higher SQI values related to the better performance of soil functions were detected during the rainy season.

Spatio-temporal evolution of eutrophication and water quality in the Turawa dam reservoir, Poland

The objectives of the article are: to assess spatio-temporal evolution of eutrophication and water quality of the Turawa dam reservoir, located in south-western Poland on the Mała Panew River; to identify location and relationship between potential sources of physicochemical pollution related to the progressing process of eutrophication; and to determine trophic status and water quality indices of the selected research object. The analysis (Mann–Whitney U test, PCA, HCA, Spearman correlation matrix) showed a high susceptibility of the reservoir to eutrophication processes, especially due to the influence of dangerous loads of compounds emerging from areas with high tourist intensity and pollutants flowing from the Mała Panew River. The parameters deteriorating the ecological status were TP, DO, BOD5, and COD. Considering the cumulative results of water quality indices for the period 1998–2020, the average water quality was in classes II or III. A noticeable deterioration appeared in water quality for the years 2016–2020, which proves the progressing eutrophication in the Turawa reservoir. In 1998–2020, the reservoir was classified as eutrophic or mesoeutrophic based on the calculated three trophic status indices. This article would help in developing a strategy for dealing with water blooms, a reliable system for monitoring pressures causing eutrophication, and optimal technologies for the reconstruction of multifunctional reservoirs.