Index Values Research Articles

Donut-shaped [NaP5W30O110]14- polyoxometalate as a promising antidiabetic drug-candidate: putative mechanisms of action.

The aim of this study was to elucidate the potential mechanism of the antihyperglycemic action of the donut-shaped Preyssler-Pope-Jeannin polyanion salt (NH4)14[NaP5W30O110] 31H2O (NaP5W30) and its effect on metabolic disorders associated with diabetes. For this purpose, relevant parameters of blood glucose regulation, lipid profile, and electrolyte status were monitored in streptozotocin (STZ)-induced diabetic rats that were orally treated with 20mg/kg/day NaP5W30 for three weeks. The serum insulin concentration was increased in diabetic animals treated with NaP5W30 (20mg/kg/day, per os, three weeks), which could be one of the possible mechanisms of the confirmed antihyperglycemic effect. In addition, the administration of NaP5W30 significantly reduced hyperglycemia and glycated haemoglobin A1c (HbA1c) in STZ-induced diabetic rats, although normoglycemic values were not achieved. Furthermore, a statistically significant 1.3-fold reduction in serum total cholesterol and a 1.7-fold reduction in high-density lipoprotein (HDL) cholesterol were observed in the NaP5W30 treatment group compared to the diabetic control group. In contrast, NaP5W30 had no effect on homeostasis model assessment of insulin resistance (HOMA-IR) index values, electrolyte concentrations, or serum concentrations of low-density lipoprotein (LDL) cholesterol, apolipoprotein A1 (Apo A1), apolipoprotein B (Apo B), or total triglycerides. In summary, NaP5W30 effectively improved glycoregulation in diabetic rats via the considerable stimulation of insulin as a putative mechanism. Moreover, NaP5W30 did not affect rat weight or disrupt lipid and electrolyte status, common diabetes-followed side effects and risk factors for various life-threatening complications. Thus, NaP5W30 could be considered a promising antidiabetic drug-candidate that deserves further investigation.

The Effect of Repetitive Mechanical Perturbations on Lower Limb Symmetry in Postural Control

Background: Postural symmetry ensures balanced alignment and equal weight distribution, promoting optimal function and minimizing stress on muscles and joints. This study aimed to evaluate lower limb movement symmetry in response to mechanical perturbations. Methods: Twelve healthy young women were subjected to mechanical perturbation tests while standing on the Motek GRAIL system treadmill. Maximum values of kinematic and kinetic parameters and symmetry indices were counted to compare the responses of dominant and non-dominant limbs. Results: The study identified symmetrical and asymmetrical features in lower limb dynamics. Symmetry nearness was observed in the ankle joint angle (SI = 0.03), the hip torque (SI = 0.03), and the vertical component of the ground reaction force (SI = 0.04). However, significant asymmetries were found in the medio-lateral component of the ground reaction force (SI = 1.84), ankle torque (SI = 0.23), knee torque (SI = 0.19), hip angle (SI = 0.15), and knee angle (SI = 0.08). The anterior–posterior component of the ground reaction force (SI = 0.14) showed asymmetry but was not statistically significant. Conclusions: Perturbations impact lower limb dynamics, revealing dominance- and joint-specific asymmetries. Bilateral assessment is crucial for understanding postural control, guiding rehabilitation to restore symmetry, and reducing the risk of injuries, falls, and musculoskeletal strain, particularly in athletes and older adults. These findings emphasize the value of symmetry indices in optimizing therapy and prevention strategies.

Genetic and structural factors contributing to the dominance and persistence of goose astrovirus type 2

ABSTRACT Goose astrovirus (GoAstV) has emerged as a significant pathogen affecting the goose industry in China, with GoAstV-2 becoming the dominant genotype since 2017. This study explored the genetic and structural factors underlying the prevalence of GoAstV-2, focusing on codon usage bias, spike protein variability, and structural stability. Phylogenetic and effective population size analyses revealed that GoAstV-2 underwent rapid expansion between 2017 and 2018, followed by population stabilization. Codon usage analysis indicated that GoAstV-2 exhibited a weaker codon usage bias compared to GoAstV-1, suggesting greater flexibility in synonymous codon usage and potentially enhanced adaptability across host environments. Additionally, the lower codon adaptation index values of GoAstV-2 point to a divergence from the host’s optimal codon usage, which may reduce competition with host tRNA pools and facilitate viral replication. The spike protein of GoAstV-2 demonstrated significantly lower variability than GoAstV-1, as shown by Shannon entropy analysis, indicating greater structural stability. This stability may reduce the need for frequent mutations, allowing GoAstV-2 to persist in host populations without undergoing constant evolution. The lower antigenic variability likely decreases immune-driven selective pressure, contributing to the sustained viral transmission and long-term persistence. These findings provide new insights into the evolutionary advantages of GoAstV-2 and its epidemiological success, which could inform future control strategies aimed at mitigating its impact on poultry populations. RESEARCH HIGHLIGHTS Goose astrovirus type 2 (GoAstV-2) became the dominant strain in China post-2017. GoAstV-2 exhibits weaker codon usage bias, enhancing adaptability across hosts. The stability of GoAstV-2 spike protein reduces mutation needs and selective pressure. GoAstV-2 low spike protein variability supports long-term persistence in host populations.

ОЦЕНКА СОРТОВОЙ РЕАКЦИИ ОВСА НА ПОЧВЕННУЮ ЗАСУХУ ПО ХЛОРОФИЛЛОВОМУ ИНДЕКСУ

The purpose of the study is to evaluate the use of chlorophyll index values obtained through rapid diagnostics in the selection of promising genotypes for the selection of drought-resistant oat varieties. For research in 2020–2022 40 varieties of oats of domestic selection were used. The experiment was carried out in greenhouse conditions, where soil drought was artificially created during the period of tillering and flowering. A comparison of the response of varieties to soil drought was carried out by calculating the degree of decrease in the chlorophyll index relative to the control, as well as by calculating the decrease in oat biomass. It has been established that oats respond maximally to soil drought during the flowering period. A minimal decrease in the chlorophyll index was recorded in the varieties Peredovik, Sig, Chisch, CROSS, Horizont, Privet, Barguzin, which can be used as valuable breeding material for creating drought-resistant varieties. Their chlorophyll index decreased during drought during tillering by 6.1–8.7 %, and during flowering by 3.7–5.1 % against the background of a general decrease in the collection of 13.0 and 7.8 %, respectively. Varieties Pokrovsky 9, Tigroviy, Tayoschnik, Avatar, Talisman, Express, Narymsky 943, Orion, Bulany, Tubinsky had the strongest decrease in the chlorophyll index, which indicates the manifestation of severe stress caused by soil drought. A correlation was established between the degree of decrease in the chlorophyll index and plant biomass under the influence of soil drought during tillering (r = –0.65) and flowering (r = –0.55). The chlorophyll index values depend 46% on the genotype and 35 % on stress caused by soil drought.

LeafLaminaMap: Exploring Leaf Color Patterns Using RGB Color Indices

The color of the plant leaves is a major concern in many areas of agriculture. Pigmentation and its pattern provide the possibility to distinguish genotypes and a basis for annual crop management practices. For example, the nutrient and water status of plants is reflected in the chlorophyll content of leaves that are strongly linked to the lamina coloration. Pests and diseases (virus or bacterial infections) also cause symptoms on the foliage. These symptoms induced by biotic and abiotic stressors often have a specific pattern, which allows for their prediction based on remote sensing. In this report, an RGB (red, green and blue) image processing system is presented to determine leaf lamina color variability based on RGB-based color indices. LeafLaminaMap was developed in Scilab with the Image Processing and Computer Vision toolbox, and the code is available freely at GitHub. The software uses RGB images to visualize 29 color indices and the R, G and B values on the lamina, as well as to calculate the statistical parameters. In this case study, symptomatic (senescence, fungal infection, etc.) and healthy grapevine (Vitis vinifera L.) leaves were collected, digitalized and analyzed with the LeafLaminaMap software according to the mean, standard deviation, contrast, energy and entropy of each channel (R, G and B) and color index. As an output for each original image in the sample set, the program generates 32 images, where each pixel is constructed using index values calculated from the RGB values of the corresponding pixel in the original image. These generated images can subsequently be used to help the end-user identify locally occurring symptoms that may not be visible in the original RGB image. The statistical evaluation of the samples showed significant differences in the color pattern between the healthy and symptomatic samples. According to the F value of the ANOVA analysis, energy and entropy had the largest difference between the healthy and symptomatic samples. Linear discriminant analysis (LDA) and support vector machine (SVM) analysis provided a perfect recognition in calibration and confirmed that energy and entropy have the strongest discriminative power between the healthy and symptomatic samples. The case study showed that the LeafLaminaMap software is an effective environment for the leaf lamina color pattern analysis; moreover, the results underline that energy and entropy are valuable features and could be more effective than the mean and standard deviation of the color properties.

Dynamical Complexity in Geomagnetically Induced Current Activity Indices Using Block Entropy

Geomagnetically Induced Currents (GICs) are a manifestation of space weather events at ground level. GICs have the potential to cause power failures in electric grids. The GIC index is a proxy of the ground geoelectric field derived solely from geomagnetic field data. Information theory can be used to shed light on the dynamics of complex systems, such as the coupled solar wind–magnetosphere–ionosphere–ground system. We performed block entropy analysis of the GIC activity indices at middle-latitude European observatories around the St. Patrick’s Day March 2015 intense magnetic storm and Mother’s Day (or Gannon) May 2024 superintense storm. We found that the GIC index values were generally higher for the May 2024 storm, indicating elevated risk levels. Furthermore, the entropy values of the SYM-H and GIC indices were higher in the time interval before the storms than during the storms, indicating transition from a system with lower organization to one with higher organization. These findings, including the temporal dynamics of the entropy and GIC indices, highlight the potential of this method to reveal pre-storm susceptibility and relaxation processes. This study not only adds to the knowledge of geomagnetic disturbances but also provides valuable practical implications for space weather forecasting and geospatial risk assessment.

Forecasting the Incidence of Mumps Based on the Baidu Index and Environmental Data in Yunnan, China: Deep Learning Model Study.

Mumps is a viral respiratory disease characterized by facial swelling and transmitted through respiratory secretions. Despite the availability of an effective vaccine, mumps outbreaks have reemerged globally, including in China, where it remains a significant public health issue. In Yunnan province, China, the incidence of mumps has fluctuated markedly and is higher than that in mainland China, underscoring the need for improved outbreak prediction methods. Traditional surveillance methods, however, may not be sufficient for timely and accurate outbreak prediction. Our study aims to leverage the Baidu search index, representing search volumes from China's most popular search engine, along with environmental data to develop a predictive model for mumps incidence in Yunnan province. We analyzed mumps incidence in Yunnan Province from 2014 to 2023, and used time series data, including mumps incidence, Baidu search index, and environmental factors, from 2016 to 2023, to develop predictive models based on long short-term memory networks. Feature selection was conducted using Pearson correlation analysis, and lag correlations were explored through a distributed nonlinear lag model (DNLM). We constructed four models with different combinations of predictors: (1) model BE, combining the Baidu index and environmental factors data; (2) model IB, combining mumps incidence and Baidu index data; (3) model IE, combining mumps incidence and environmental factors; and (4) model IBE, integrating all 3 data sources. The incidence of mumps in Yunnan showed significant variability, peaking at 37.5 per 100,000 population in 2019. From 2014 to 2023, the proportion of female patients ranged from 41.3% in 2015 to 45.7% in 2020, consistently lower than that of male patients. After excluding variables with a Pearson correlation coefficient of <0.10 or P values of <.05, we included 3 Baidu index search term groups (disease name, symptoms, and treatment) and 6 environmental factors (maximum temperature, minimum temperature, sulfur dioxide, carbon monoxide, particulate matter with a diameter of 2.5 µm or less, and particulate matter with a diameter of 10 µm or less) for model development. DNLM analysis revealed that the relative risks consistently increased with rising Baidu index values, while nonlinear associations between temperature and mumps incidence were observed. Among the 4 models, model IBE exhibited the best performance, achieving the coefficient of determination of 0.72, with mean absolute error, mean absolute percentage error, and root-mean-square error values of 0.33, 15.9%, and 0.43, respectively, in the test set. Our study developed model IBE to predict the incidence of mumps in Yunnan province, offering a potential tool for early detection of mumps outbreaks. The performance of model IBE underscores the potential of integrating search engine data and environmental factors to enhance mumps incidence forecasting. This approach offers a promising tool for improving public health surveillance and enabling rapid responses to mumps outbreaks.

Combined Use of Pan-Immune-Inflammation Value and Triglyceride-Glucose Index for Risk Prediction of Contrast-Induced Nephropathy After Coronary Angiography in Patients with STEMI

Abstract Aim The pan-immune-inflammation value (PIV) and triglyceride-glucose (TyG) index are very important parameters that predict contrast-induced nephropathy (CIN) well in patients with ST-elevation myocardial infarction (STEMI) underwent percutaneous coronary intervention (PCI). There are limited data on the predictive value of CIN derived from the combination of PIV and TyG index compared to the use of PIV and CIN alone in patients with STEMI who underwent PCI. We aimed to evaluate the ability of the combination of PIV and TyG index, routinely obtained on admission, to identify STEMI patients at risk of CIN. Method Between 2018 and 2024, 2367 patients with STEMI who underwent PCI were included. CIN was defined as a 25% or 0.5 mg/dL increase in creatinine from baseline within 48–72 h after PCI. Receiver operating curve (ROC) analysis was performed to predict the development of CIN. Results In ROC analysis, the cut-off values of PIV and TyG index for best predicting CIN were 548, and 8.97 respectively. The combination of two markers was the most powerful predictor of CIN risk when included in a single variable such as high PIV or high TyG index. Furthermore, the co-presence of high PIV and high TyG index exhibited the highest specificity for CIN(82%) compared to high PIV(77%) or TyG index(71%) alone. Conclusion The combination of PIV and TyG index, a simple and cost-effective risk assessment, may be a more reliable prognostic indicator for predicting the development of CIN in STEMI patients undergoing PCI than the use of PIV and TyG index alone.

The Effect of Lower Eyelid Blepharoplasty on Corneal Biomechanical Parameters

Purpose: To determine the effect of lower eyelid blepharoplasty (LEB) surgery on corneal biomechanical parameters before and 4 months after the procedure.Methods: In this prospective longitudinal study, corneal biomechanical parameters measured by Corneal Visualization Scheimpflug Technology device were evaluated before and 4 months after LEB surgery.Results: The study included 19 eyelids of the right eyes of 19 patients who underwent LEB, with a mean age of 49.0 ± 10.1 years (range, 37–72 years). Four months after the procedure, significant increases were observed in the first applanation time (&lt;i&gt;p&lt;/i&gt; = 0.007), second applanation time (&lt;i&gt;p&lt;/i&gt; &lt; 0.001), highest concavity time (&lt;i&gt;p&lt;/i&gt; = 0.004), intraocular pressure (&lt;i&gt;p&lt;/i&gt; = 0.009), and biomechanical-compensated intraocular pressure (&lt;i&gt;p&lt;/i&gt; = 0.007). In addition, the absolute value of highest concavity delta arc length and stress-strain index showed a significant decrease after the LEB (&lt;i&gt;p&lt;/i&gt; = 0.021 and &lt;i&gt;p&lt;/i&gt; = 0.037, respectively). Other corneal biomechanical parameters did not show significant differences following the LEB procedure (&lt;i&gt;p&lt;/i&gt; &lt; 0.05).Conclusions: The resection and repositioning of the fat pockets in LEB lead to biomechanical changes of the cornea in the direction of increasing corneal stiffness.

Predictive value of the perivascular fat attenuation index for MACE in young people suspected of CAD

ObjectiveThe perivascular fat attenuation index (FAI) evaluated by coronary computed tomographic angiography (CCTA) has been reported to have strong prognostic value, but few studies have focused on young people. This study aimed to assess the predictive value of the perivascular FAI in young people suspected of having coronary atherosclerotic disease (CAD).MethodA retrospective analysis was performed on adults aged ≤ 45 years who underwent CCTA due to suspected CAD between 2015 and 2016 and who were followed up for at least 5 years following their visit (n = 503). The perivascular FAI at the proximal segment of the right coronary artery (RCA) was measured and grouped into high FAI and low FAI according to the optimal cut-off value, and the association between a high FAI and major adverse cardiac events (MACE) was evaluated by Cox hazard regression. K‒M survival analysis was conducted to assess the prognostic value of the perivascular FAI and improvement over traditional risk factor prediction methods.ResultsThe event-free survival of patients in the high FAI group (FAI≥-75.2 HU) was significantly lower than that of patients in the low FAI group (FAI<-75.2 HU) at a median follow-up of 72.7 months (93.9% vs. 99.7%, P < 0.001). A high FAI (HR = 19.257, 95% CI: 2.504-148.107, P = 0.004) showed a significant correlation with an increased risk of MACE in young people. The prediction accuracy of MACE can be improved by including a high FAI on the basis of the traditional risk factor model, and the area under the curve (AUC) increased from 0.728 to 0.845 (P < 0.001). Moreover, the new model revealed significant improvements in integrated discrimination (IDI = 0.033, 95% CI: 0.009–0.103, P = 0.014) and the net reclassification index (NRI = 0.597, 95% CI: 0.000-0.699, P = 0.024).ConclusionThe high perivascular FAI at the proximal segment of the RCA is significantly associated with an increased risk of long-term MACE and may be a potential tool for cardiovascular risk stratification in young people suspected of CAD.

Mine water inflow prediction model based on variational mode decomposition and gated recurrent units optimized by improved chimp optimization algorithm

Water damage accidents occur frequently in mines in China, and accurate prediction of incoming water has become an important guarantee for the safe and efficient mining of coal resources. To improve the accuracy of mine water prediction, this paper proposes the VMD-iCHOA-GRU mine water prediction model by selecting and improving it according to the previous research results in decomposition method, time series prediction model and optimization algorithm. After processing the raw data and setting the model parameters, MAE, RMSE, MAPE and R2 are selected as the evaluation indexes of prediction accuracy, and VMD-GRU model, iCHOA-GRU model, CHOA-GRU model and GRU model are selected as the comparison models to validate the advantages of the VMD-iCHOA-GRU model in the prediction of mine inrush water. The results show that the VMD-iCHOA-GRU model has the best prediction effect on the trend of water inflow, with the evaluation index values of 0.00862, 0.01059, 0.02189%, 0.87079, respectively, and with the smallest MAE, RMSE, MAPE, and the largest R2, and the highest prediction accuracy of the VMD-iCHOA-GRU model.

Climate change hazard index reveals combined risks to United States drinking water utilities

Abstract Drinking water utilities are exposed to a range of climate change hazards that can affect their ability to deliver safe drinking water. We use climate change mid-century projections to assess seven hazards for 42 786 utility systems (serving 283 million people) across the contiguous United States and develop a combined climate hazard index that allows for risk comparisons. All utilities are exposed to climate hazards, and around half, serving 178 million people (53% of current population), could experience large changes in one or more climate hazards that could affect an aspect of system reliability, including water resources, infrastructure, or operations. While utilities located in Western regions and coastal areas have higher climate hazard index values, there are utilities serving different population sizes in all geographic regions with elevated climate risk. Few utilities have developed climate adaptation plans and many may have existing vulnerabilities. This index provides multiple stakeholders, including utilities, regulators, and investors, with usable and accessible climate information.

Extraction of Grape Juice: Impact of Laboratory-Scale Pressing Methods on the Chemical Composition

The monitoring of grape maturity is essential for determining the ideal harvest time as well as for obtaining the expected characteristics of grape juice and, consequently, of wine. This study aimed to examine the impact of various laboratory-scale pressing methods on key chemical parameters (sugars, pH, and titratable acidity), as well as on phenolic-related indexes and antioxidant activity, in juices from Chardonnay (six grape samples) and Pinot blanc (two grape samples) across two vintages (2022 and 2023). The grape samples were characterized in terms of total and extractable flavonoids and extractability (%). Four different methods (manual pressing, vacuum pressing, small screw press, and juicer) were applied for producing grape juice. The results showed relevant differences in the extractability among the grape samples up to 64.1% and 43.8% for harvests 2022 and 2023, respectively. Comparable sugar content, pH, and titratable acidity were found in the juice samples independently from the method used. On the contrary, notable variability among the different pressing methods was revealed for phenolic-related indexes and antioxidant activity. The small screw press led to lower total phenol index values across grape batches compared to other methods, while the juice samples obtained with the juicer revealed a composition consistently differing in comparison to the other methods. Raman spectroscopy allowed to clearly classify the juice samples based on the pressing method. Good predictive models were obtained due to the composition of juice samples being clearly distinct among methods. This data suggests that an appropriate pressing method should be adopted for monitoring the grape ripening as well as for simulating the pressing under industrial scale.

Analyzing the correlation between acute ischemic stroke and triglyceride-glucose index based on ordered logistic regression

ObjectiveTo investigate the association between insulin resistance, measured by the triglyceride-glucose (TyG) index, and clinical outcomes in patients with acute ischemic stroke who underwent intravenous thrombolysis with alteplase.MethodsThis retrospective study included 165 patients with acute ischemic stroke treated with intravenous alteplase. Insulin resistance was evaluated using the TyG index, and its relationship with the modified Rankin Scale (mRS) scores was analyzed. The analysis was conducted using R software (version R 4.1.3) to evaluate the correlation between the TyG index and functional outcomes at 14, 30, and 90 days post-stroke.ResultsThe study found that each unit increase in the TyG index significantly raised the risk of poor functional outcomes at 14 days (OR 9.86; 95% CI: 3.32–32.21; P &amp;lt; 0.001), 30 days (OR 5.82; 95% CI: 2.08–17.45; P = 0.001), and 90 days (OR 9.79; 95% CI: 3.33–31.66; P &amp;lt; 0.001) following a stroke. Higher TyG index values were associated with worse neurological outcomes. Although male gender, older age, and smoking were also linked to poorer outcomes, these associations did not reach statistical significance.ConclusionThe findings suggest that a higher TyG index, indicating greater insulin resistance, is associated with worse neurological outcomes in stroke patients. Early intervention targeting insulin resistance may improve clinical outcomes in ischemic stroke patients, and further research is needed to explore additional factors affecting neurological recovery.

Impact of age on the reliability of GE Entropy™ module indices for guidance of maintenance of anaesthesia in adult patients: a single-centre retrospective analysis.

The GE Entropy™ module uses frontal EEG to compute the processed indices state entropy (SE), response entropy (RE), and burst suppression ratio (BSR) to guide maintenance of anaesthesia by supposedly minimising overly 'deep' or 'light' anaesthesia. It remains unclear whether the manufacturer-recommended index ranges accurately reflect anaesthesia levels or prevent complications such as burst suppression or arousal reactions. We retrospectively analysed 15 608 patient records, evaluating 14 770 adult patients (18-90 yr old) undergoing general anaesthesia. Age-dependent effects on processed index values were assessed using linear regression and Spearman's correlation coefficients (rho). During steady-state anaesthesia (BSR=0), only 38.4% (32.5-42.4%) of SE values were within the recommended range, with most values below the target. Age was positively associated with an increase in age-adjusted minimal alveolar concentration for volatile anaesthetics (adjusted [adj.] R2=0.18, P<0.001, rho=0.47 [0.20-0.70]). Despite this, SE paradoxically increased with age (adj. R2=0.45, P<0.001, rho=0.67 [0.51-0.79]). This trend persisted even during periods with positive BSR despite supposedly adequate SE values (adj. R2=0.73, P<0.001, rho=0.90 [0.80-0.95]). Maintaining anaesthesia within the recommended index range did not prevent positive BSR. Additionally, both frequency (adj. R2=0.70, P<0.001, rho=0.92 [0.85-0.95]) and duration (adj. R2=0.73, P<0.001, rho=0.89 [0.82-0.93]) of ΔRE-SE≥10, indicating arousal, increased with age. Despite their intuitive appeal, the processed EEG index values SE, RE, ΔRE-SE, and BSR showed limited reliability in guiding maintenance of anaesthesia, especially in older patients. Anaesthesiologists should not rely exclusively on the recommended index value range, as it is often unattainable and does not prevent burst suppression or arousal indicators.

Prognostic value of systemic immune-inflammation index for patients undergoing radical prostatectomy: a systematic review and meta-analysis

ObjectiveThe prognostic value of the systemic immune-inflammation index (SII) for prostate cancer (PCa) patients receiving different treatments remains unclear. This research examined the relevance of SII in individuals undergoing radical prostatectomy (RP).MethodsPubMed, Embase, Web of Science, Cochrane, Wanfang, and China National Knowledge Infrastructure (CNKI) dat3 abases were used to search literature up to May 2024. The quality was evaluated with Newcastle-Ottawa Scale. Outcomes examined were associations between SII and overall survival (OS), biochemical recurrence-free survival (BFS), and cancer-specific survival (CSS). Pooled analysis, Egger’s test, and sensitivity analysis were conducted using Review Manager 5.4.1 and Stata 15.1. The GRADE system was employed to evaluate and grade the evidence for each outcome. Subgroup analyses were performed for outcomes with significant heterogeneity to evaluate the possible confounders, if data were sufficient.ResultsOut of 101 identified studies, eight studies involving 8,267 individuals were included. Patients with higher SII had shorter overall survival (HR: 1.89; 95% CI: 1.31-2.71; P = 0.0006), biochemical recurrence-free survival (HR: 1.55; 95% CI: 1.08-2.22; P = 0.02), and cancer-specific survival (HR: 3.63; 95% CI: 1.66-7.94; P = 0.001). The evidence for OS and CSS was rated very low-quality due to serious heterogeneity and/or imprecision. The prognostic value of SII for BFS was rated as low-quality evidence, given no serious risk observed. Subgroup analysis showed that, except for the subgroup aged &amp;gt;65 years (HR: 3.70; 95%CI: 0.91, 15.06, P=0.07), the prognostic value of SII for OS was not significant, but the prognostic value of SII for OS in other subgroups was still significant.ConclusionsHigh SII was linked to shorter OS, BFS, and CSS in patients undergoing RP. However, the quality of the evidence provided by this study was low.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024558431.

A Body Shape Index as a Simple Anthropometric Marker for the Risk of Cardiovascular Events.

To provide an overview of the predictive value of A Body Shape Index (ABSI) for the risk of cardiovascular events. ABSI has been reported to have an association with development of cardiovascular diseases, and its usefulness for predicting major cardiovascular events including cardiovascular mortality, nonfatal coronary syndrome and nonfatal stroke has been investigated. The formula for ABSI includes waist circumference, which is not included in the conventional calculation of body mass index (BMI), along with BMI and height. High ABSI is independently associated with a high incidence of cardiovascular events. ABSI with specific cutoff values can be a useful tool for cardiovascular risk stratification by detecting the presence of abdominal obesity and it can be used for evaluation of the risk of cardiovascular events. Nonetheless, other factors such as race, gender, age, and physical, environmental and socioeconomic purviews also need be taken into consideration.

The associations of obesity with demographic and lifestyle factors among Hong Kong adults.

Background: Obesity is a risk factor for leading causes of death. Aim: This study investigated the associations of obesity with demographic and lifestyle factors among adults aged 18-64 in Hong Kong. Methods: The study uses data (n = 24,855) from the government online database. It uses T-tests to compare mean values for body mass index (BMI), waist circumference, and weight-to-height ratio obese; analysis of variance for not-obese, BMI-obese-only, central-obese, and BMI + central-obese; Pearson chi-square tests for categorical variables; and multinomial logistic regression to obtain the odd ratios. It uses IBM SPSS version 26 to conduct all analyses, and at a 95% confidence level. Results: The analyses show that the risks of central-obese, and BMI + central-obese increase by 4%, and 4%/year of age, respectively. Females have 60%, 38%, and 60% lower risks of BMI-obese-only, central-obese, and BMI + central-obese, respectively, and people with tertiary education have 28%, 20%, and 20% lower risks, respectively. Employed people have a 40% higher risk of BMI-obese-only when compared with the unemployed; students have a 46% lower risk of BMI + central-obese and home-makers have a 38% higher risk. The risk of central-obese decreases by 14%/10 min/day of moderate physical activity, but could be different among females, and vigorous physical activity yielded mixed results. The risk of BMI + central-obese decreases by 9%/day/week of vegetable intake. Conclusions: Obesity is associated with multiple demographic and lifestyle factors. Keep doing vigorous and moderate physical activity but state alert to obesity risk factors, and frequent vegetable intake are recommended. Lifelong learning and continuing education could be an effective strategy to combat obesity.

Dynamic Behavior of the Glassy and Supercooled Liquid States of Aceclofenac Assessed by Dielectric and Calorimetric Techniques

Aceclofenac (ACF), a non-steroidal anti-inflammatory drug, was obtained in its amorphous state by cooling from melt. The glass transition was investigated using dielectric and calorimetric techniques, namely, dielectric relaxation spectroscopy (DRS), thermally stimulated depolarization currents (TSDC), and conventional and temperature-modulated differential scanning calorimetry (DSC and TM-DSC). The dynamic behavior in both the glassy and supercooled liquid states revealed multiple relaxation processes. Well below the glass transition, DRS was able to resolve two secondary relaxations, γ and β, the latter of which was also detectable by TSDC. The kinetic parameters indicated that both processes are associated with localized motions within the molecule. The main (α) relaxation was clearly observed by DRS and TSDC, and results from both techniques confirmed a non-Arrhenian temperature dependence of the relaxation times. However, the glass transition temperature (Tg) extrapolated from DRS data significantly differed from that obtained via TSDC, which in turn showed reasonable agreement with the calorimetric Tg (Tg-DSC = 9.2 °C). The values of the fragility index calculated by the three experimental techniques converged in attributing the character of a moderately fragile glass former to ACF. Above the α relaxation, TSDC showed a well-defined peak. In DRS, after “removing” the high-conductivity contribution using ε’ derivative analysis, a peak with shape parameters αHN = βHN = 1 was also detected. The origin of these peaks, found in the full supercooled liquid state, has been discussed in the context of structural and dynamic heterogeneity. This is supported by significant differences observed between the FTIR spectra of the amorphous and crystalline samples, which are likely related to aggregation differences resulting from variations in the hydrogen bonds between the two phases. Additionally, the pronounced decoupling between translational and relaxational motions, as deduced from the low value of the fractional exponent x = 0.72, derived from the fractional Debye–Stokes–Einstein (FDSE) relationship, further supports this interpretation.

PID CONTROLLER FOR SPEED CONTROL OF PMSM BASED ON MAYFLY OPTIMIZATION ALGORITHM

Permanent magnet synchronous motor (PMSM) is extensively employed in AC servo drives owing to their superior torque-to-inertia ratio, power density, efficiency, and power factor compared to other motors. So, it is a crucial point to regulate the PMSM speed. Conventional proportional, integral, and differential (PID) is a simple controller and easy to implement but it is coefficients are essentially determined by experience when used in PMSM to control the speed. This invariably produces unacceptable outcomes, in addition when it comes to low-power application drives, PID controller gains typically produce adequate results but, when it comes to high-power application drives, an untuned PID does not deliver satisfactory performance. The optimization algorithm offers an effective method to produce optimal PID gains. Therefore, to optimize the PID coefficients to regulate the PMSM speed, this study suggests a mayfly optimization algorithm (MA). Recently, the MA was introduced as a new intelligent optimization method with exceptional optimization capabilities. Nuptial dancing and random flight improve the ability of the algorithm to balance its features of exploitation and exploration while assisting in its escape from local optima. This suggested approach has been verified with MATLAB, and the outcomes are compared with the standard particle swarm optimization technique (PSO) and conventional PID. The outcomes show that compared to the standard PSO or conventional PID, the PID parameters adjusted by the MA method can produce faster speed responses and less overshoot. Furthermore, the system's optimal ITAE index value, as determined by the MA technique, is smaller (0.794) as compared to other techniques 1.503 and 1.906 respectively.