Traditional Indicators Research Articles

The Role of Private Funding and Collaborative Networks in Southern Italy's Socioeconomic Development: Insights from The Fondazione Con Il Sud

This study examines the impact of private funding and collaborative networks on socio-economic development in Southern Italy, with a specific focus on Fondazione Con il Sud’s (FCS) strategy. The Foundation strongly emphasizes social cohesion and social capital, moving beyond traditional economic indicators such as GDP to drive sustainable development in marginalized regions. The evaluative study examines the effectiveness of FCS's funded projects using a "positive thinking approach" as a framework. It aims to identify the key factors contributing to long-lasting positive changes in local communities, offering hope and optimism for socioeconomic development in Southern Italy. A mixed-methods approach applied to 205 projects funded by the Foundation, covering a wide range of sectors, including social, educational, environmental, and cultural domains. The results indicate that the type of network strategy used during project implementation significantly influences medium—to long-term outcomes. These strategies, including opportunistic collaborations, third-sector networks, and community-based relations, have significant implications for socioeconomic development. Projects that foster stable partnerships and active community involvement tend to create more sustainable and enduring impacts. In contrast, opportunistic collaborations, primarily driven by short-term funding goals, cannot often generate lasting structural change. The findings suggest that long-term success is more likely when projects emphasize inclusive, multi-stakeholder collaborations and prioritize the active engagement of local actors.

Enhancing Student Comprehension of Glucose Metabolism Visualization Through Virtual Simulation Platform: An Educational Approach.

With the rapid progression of biotechnology, the significance translational research on glycolysis in molecular pharmacology has become increasingly evident. To deepen students' understanding of glycolytic processes and facilitate their comprehension of drug action mechanisms, we have developed a visual virtual simulation platform dedicated glycolysis. The educational approach commenced with theoretical lectures on glycolysis, followed by practical laboratory sessions where students measured glycolysis-related parameters such as hexokinase, pyruvate kinase, and lactate. Students then engaged with the virtual simulation training platform to explore glycolytic stress tests and positron emission tomography/computed tomography (PET/CT) imaging, with their progress tracked through an assessment mode. The study involved 67 s-year undergraduate students majoring in biomedical sciences, all of whom had received instruction in glucose metabolism theories and completed the associated questionnaires. The results showed that the students gained a deeper understanding of glycolysis and the clinical application of PET/CT imaging in the context of glycolysis. The majority also agreed that the integration of scientific and clinical cases in teaching is beneficial and that the project sparked their interest in scientific research. These findings align with existing literature that emphasizes the importance of innovative educational tools in enhancing student engagement and understanding of the underlying theories of the curriculum. This project designed an innovative glycolytic metabolism teaching system encompassing the monitoring of traditional glycolytic indicators, glycolytic stress tests, and PET/CT imaging based on glycolysis. The visual virtual simulation platform for glycolysis can serve as an innovative educational tool in the molecular pharmacology curriculum or other courses involving glycolysis, assisting students in deeply understanding the molecular mechanisms of glycolysis and its significance in disease and drug action.

Grammatical Redundancy in Scales: Using the “ConGRe” Process to Create Better Measures

As theoretical models become more complex, there is more pressure to use less time-consuming methods generally, and shorter scales specifically. Although reliability is related to scale length, reliability cutoffs are easily met, even in very short scales, by writing or selecting items that are worded in nearly identical ways, that is, grammatical redundancy. However, grammatical redundancy increases reliability at the cost of domain sampling—a crucial early step in scale construction and one of the two pillars of content validity. Without it, a scale cannot capture the intended construct. The purpose of this paper is to provide scale developers (and shorteners) with a process for quantifying, identifying, and reducing grammatical redundancy without compromising conceptual redundancy, a process that we label ConGRe. Our process involves indices from the linguistics literature that can be used to guide decisions during item writing, that is, prior to data collection. We examine their relation to more traditional psychometric indicators and provide a set of benchmarks. Overall, we demonstrate that it is possible to reduce grammatical redundancy, thus avoiding scale deficiency, without sacrificing traditional psychometric properties.

The association between hypoxic burden and the risk of cognitive impairment in patients with obstructive sleep apnea.

Obstructive sleep apnea (OSA) is associated with increasing risk of cognitive impairment, but traditional hypoxic indicators can not accurately identify cognitive impairment. This study aimed to assess a new indicator, hypoxic burden, in cognitive impairment in OSA. A total of 116 patients with OSA were enrolled in this study. Daytime sleepiness and cognition were assessed by Epworth Sleepiness Scales (ESS) and Montreal Cognitive Assessment (MoCA), respectively. All participants underwent polysomnography. Hypoxic burden was derived from polysomnography and calculated according to a specific algorithm. All the subjects were divided into two groups. 77 were OSA with mild cognitive impairment (OSA+MCI) and 39 were OSA without mild cognitive impairment (OSA-MCI). The relationship between hypoxic burden and cognitive impairment was analyzed by establishing a series of logistic regression models. Hypoxic burden was higher in OSA+MCI group compared with OSA-MCI group, while there was no significance found for the apnea-hypopnea index (AHI) between the two groups. After adjusting for various confounders, patients with OSA who had a higher total hypoxic burden and REM-hypoxic burden in the fourth quartile were found to have an increased risk of MCI compared to those in the first quartile. The adjusted ORs were 7.69 (95%CI 1.15-51.55) and 8.87 (95%CI 1.22-64.34), respectively. However, There was no significant association between the other traditional hypoxic parameters and cognitive function after adjusting for various confounders. Compared to the conventional hypoxic parameter, higher hypoxic burden is associated with cognition and may be an important indicator for assessing MCI in OSA.

The Interplay of Happiness and Sustainability: A Multidimensional Scaling and K-Means Cluster Approach

This study examines the intricate relationship between national happiness and sustainability by analyzing data from the 2024 World Happiness Report (WHR) and the Sustainable Development Goal (SDG) Index across 74 countries. Employing multidimensional scaling (MDS) and K-means clustering, we investigate the interplay of economic, social, and environmental factors that contribute to subjective well-being. Our results indicate that high-income countries, particularly those characterized by secular–rational values, tend to achieve elevated scores in both happiness and sustainability. In contrast, lower-income nations exhibit diverse cultural value systems that significantly influence their happiness and sustainability outcomes. This analysis identifies distinct clusters of countries with unique governance and cultural profiles, underscoring the inadequacies of traditional economic indicators in measuring societal well-being. By integrating sustainability metrics into happiness assessments, we propose a comprehensive framework for understanding and promoting human happiness. These findings offer critical insights for policymakers aiming to address pressing global challenges, including inequality and health disparities.

Corporate sustainability and value

Purpose This study aims to explore the influence of corporate sustainability on organizational value, specifically focusing on companies ranked in the Just Capital Market ranking. The aim is to establish whether higher sustainability rankings are associated with increased firm value and to investigate how corporate social responsibility (CSR) activities affect both financial and non-financial outcomes. Design/methodology/approach This study uses the Ohlson model to assess the value-generation potential of the top and bottom ten companies in the Just Capital Market ranking from 2013 to 2018. The analysis involves evaluating stock prices and other financial metrics and incorporating non-financial indicators related to CSR activities to gain a comprehensive understanding of their impact on firm valuation. Findings The results indicate a strong connection between high sustainability rankings and increased market value. Companies such as Microsoft, Intel and Alphabet, which have robust CSR initiatives, have shown significant improvements in market performance due to greater stakeholder engagement and detailed non-financial disclosures. On the other hand, companies with low sustainability ratings have demonstrated weaker market performance, which indicates the financial risks associated with neglecting CSR activities. This study underscores the critical importance of integrating CSR into fundamental business strategies to create sustainable value. Originality/value This study addresses the limitations of traditional financial indicators by incorporating non-financial factors into the valuation process. The study offers a more comprehensive assessment of firm value, reflecting modern business practices and the evolving global economy landscape. Integrating nonfinancial indicators enhances valuation accuracy and provides a holistic view of company performance, enabling stakeholders to make informed decisions based on a broader range of factors. This innovative method may reshape firm valuations, leading to more accurate and reliable assessments in contemporary business contexts.

A Rapid Quantitative Assessment Method for Liver Damage Effects of Compounds Based on Zebrafish Liver Partition Area Ratio.

Total liver area is a traditional indicator in evaluating compound liver damage with zebrafish models. However, in some experiments, compounds changed zebrafish liver morphology but total liver area showed no significant difference, indicating it is inaccurate for evaluating compound effects on zebrafish liver damage. Therefore, in this study, transgenic zebrafish Tg(l-fabp:EGFP) labeled with liver cells using green fluorescent protein was used to evaluate compound effects on liver by the liver partition area ratio. The coefficient of variation of the total liver area and the liver partition area ratio of normal zebrafish at different development stages was calculated to determine the precision and dispersion of the liver partition area ratio. Three known hepatotoxic compounds (water extract of psoralea, alcohol, and α-naphthalene isothiocyanate) were used to treat zebrafish, and liver partition area ratio was calculated and verified by liver tissue pathological sections. The Pearson correlation coefficient was used to analyze the correlation between the liver partition area ratio, total liver area, and alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Results showed significant difference in liver partition area ratio between hepatotoxic compound treated group and control group, and it could accurately reflect liver morphology changes. There was a strong correlation between liver partition area ratio and ALT and AST level, whereas that between total liver area and ALT and AST level was low. Therefore, the change in zebrafish liver partition area ratio can be an evaluation indicator for rapid assessment of compound effects on zebrafish liver function damage, more sensitive and accurate than total liver area.

Emerging socioeconomic correlates of loneliness. Evidence from the Barcelona Health Survey 2021

Abstract Purpose Recent evidence shows that loneliness is associated with socioeconomic factors. However, studies often focus on traditional socioeconomic indicators (income, occupation, educational level) only, disregarding other important socioeconomic determinants, such as job insecurity, housing conditions or material deprivation. Therefore, we analyse the association of a broad range of socioeconomic indicators with loneliness. Moreover, we investigate potential age and gender differences in this relationship. Methods We used cross-sectional data from the Barcelona Health Survey 2021, representative of the population of Barcelona (Spain). Individuals over the age of 14 were selected (n = 3,337). The outcome was a loneliness score based on 4 items of the UCLA scale. Loneliness was regressed on a series of sociodemographic and emerging socioeconomic correlates. Linear regression models were fitted, and potential age and gender moderation effects were tested by means of two-way interactions. Results Job insecurity and precarity-related factors, such as having a temporary job or working without a contract, material deprivation and financial difficulties, as well as poor housing conditions and facing housing insecurity were associated with increased loneliness levels. While the association between loneliness and precarity-related factors is stronger among younger individuals, material deprivation is associated with increased loneliness among older workers and women. Conclusion Beyond sociodemographic individual characteristics, socioeconomic factors are strongly associated with loneliness levels in the population. Findings support the relevance of broadening the scope of socioeconomic indicators, assessing both material conditions as well as perceived insecurity.

Assessing coronary artery stenosis exacerbated impact on left ventricular function and deformation in metabolic syndrome patients by 3.0 T cardiac magnetic resonance imaging

BackgroundMetabolic syndrome (MetS) and coronary artery stenosis (CAS) independently increase the risk of cardiovascular events, while the impact of CAS on left ventricular (LV) function and deformation in MetS patients remains unclear. This study investigates how varying degrees of CAS exacerbate LV function and myocardial deformation in MetS patients.MethodsOne hundred thirty-one MetS patients who underwent CMR examinations were divided into two groups: the MetS(CAS−) group (n = 47) and the MetS(CAS+) group (n = 84). The MetS(CAS+) group was divided into MetS with non-obstructive CAS(NOCAS+) (n = 30) and MetS with obstructive CAS(OCAS+) group (n = 54). Additionally, 48 age- and sex-matched subjects were included as a control group. LV functional and deformation parameters were measured and compared among subgroups. The determinants of decreased LV global peak strains in all MetS patients were identified using linear regression. The receiver operating characteristic (ROC) curve and logistic regression model (LRM) evaluated the diagnostic accuracy of the degree of CAS for identifying impaired LV strain.ResultsCompared to MetS(CAS−), MetS(NOCAS+) showed a significantly increased LV mass index (p < 0.05). Global longitudinal peak strain was decreased gradually from MetS(CAS−) through MetS(NOCAS+) to MetS(OCAS+) (− 13.02 ± 2.32% vs. − 10.34 ± 4.05% vs. − 7.55 ± 4.48%, p < 0.05). MetS(OCAS+) groups showed significantly decreased LV global peak strain (GPS), PSSR and PDSR in radial and circumferential directions compared with MetS(NOCAS+) (all p < 0.05). The degree of CAS was independently associated with impaired global radial peak strain (GRPS) (β = − 0.289, p < 0.001) and global longitudinal peak strain (GLPS) (β = 0.254, p = 0.004) in MetS patients. The ROC analysis showed that the degree of CAS can predict impaired GRPS (AUC = 0.730) and impaired GLPS (AUC = 0.685).ConclusionBesides traditional biochemical indicators, incorporating CAS assessment and CMR assessment of the LV into routine evaluations ensures a more holistic approach to managing MetS patients. Timely intervention of CAS is crucial for improving cardiovascular outcomes in this high-risk population.

BN SO58 - Patient Reported Outcome Measures in Hiatal Surgery: A Feasibility Study

Abstract Background Hiatal surgery is predominantly a quality-of-life procedure rather than a lifesaving intervention. Whilst procedural complications are well understood, they do not necessarily reflect the patient experience. Traditional indicators of patient care are insufficient. Patient Reported Outcome Measures (PROM) are robust indicators of care quality (1) and are being used across surgical specialities to benchmark success and identify areas for improvement (2). We present a three-year review of our PROM data to demonstrate feasibility of data collection. Method Patient reported outcome measure data were collected from the National Hiatal Surgery Registry (3) for our benign centre over a three-year period (November 2021-January 2024). Consent was obtained from all patients for research purposes. Surgical procedures included: anti-reflux surgery, hiatus hernia repair and cardiomyotomy. All patients were asked to complete pre-operative quality of life surveys. Patients are automatically contacted through the registry at 6months, 1 year and then annually for five years and prompted to complete quality of life surveys. Ekhardt score is used in achalasia. GORD-QoL score was used for anti-reflux procedures, with the Hernia-QoL score for hiatal hernia. Results Data were collected for 20 patients. Mean BMI was 28.2. All completed preoperative surveys. At six months there was attrition of one patient, who has since completed 1-year and 2-year data. At the time of writing, six patients have completed 6month data, 5 patients have completed 1-year data and 3 patients have completed 2-year data. Mean Ekhardt score was 9.25 preoperatively; at six months mean score was 0. Five patients underwent LINX, eleven underwent fundoplication; one Dor, ten Toupet. Mean pre-operative quality of life score was 31.1; at six months mean score was 15.5. At one year this was 4. Conclusion The National Hiatal Surgery Registry facilitates easy acquisition of surgeon specific PROM data over a short- and long-term period. Patient attrition is low, demonstrating acceptability. Our data demonstrate significantly improved patient reported quality of life postoperatively for all hiatal surgery.

Identifying Hemolytic Disease of the Fetus and Newborn within a Large Integrated Health Care System.

This study aims to identify hemolytic disease of the fetus and newborn (HDFN) pregnancies using electronic health records (EHRs) from a large integrated health care system. A retrospective cohort study was performed among pregnant patients receiving obstetrical care at Kaiser Permanente Southern California health care system between January 1, 2008, and June 30, 2022. Using structured (diagnostic/procedural codes, medication, and laboratory records) and unstructured (clinical notes analyzed via natural language processing) data abstracted from EHRs, we extracted HDFN-specific "indicators" (maternal positive antibody test and abnormal antibody titer, maternal/infant HDFN diagnosis and blood transfusion, hydrops fetalis, infant intravenous immunoglobulin [IVIG] treatment, jaundice/phototherapy, and first administrated Rho[D] Immune Globulin) to identify potential HDFN pregnancies. Chart reviews and adjudication were then performed on select combinations of indicators for case ascertainment. HDFN due to ABO alloimmunization alone was excluded. The HDFN frequency and proportion of each combination were fully analyzed. Among the 464,711 eligible pregnancies, a total of 136 pregnancies were confirmed as HDFN pregnancies. The percentage of the HDFN-specific indicators ranged from 0.02% (infant IVIG treatment) to 34.53% (infant jaundice/phototherapy) among the eligible pregnancies, and 32.35% (infant IVIG treatment) to 100% (maternal positive antibody test) among the 136 confirmed HDFN pregnancies. Four combination groups of four indicators, four combination groups of five indicators, and the unique combination of six indicators showed 100% of HDFN pregnancies, while 80.88% of confirmed HDFN pregnancies had the indicator combination of maternal positive antibody test, maternal/infant HDFN diagnosis, and infant jaundice/phototherapy. We successfully identified HDFN pregnancies by leveraging a combination of medical indicators extracted from structured and unstructured data that may be used in future pharmacoepidemiologic studies. Traditional indicators (positive antibody test results, high titers, and clinical diagnosis codes) alone did not accurately identify HDFN pregnancies, highlighting an unmet need for improved practices in HDFN coding. · A case ascertainment method was developed to identify HDFN from structured and unstructured data.. · The method used in this study may be used in future pharmacoepidemiologic studies.. · The study highlighted an unmet need for improved practices in HDFN coding..

Higher education investment, human capital, and high-quality economic development

While extensive research has examined economic growth in China, the complex relationship between knowledge-based inputs and comprehensive development remains poorly understood, particularly at the provincial level. Previous studies have largely focused on traditional economic indicators, overlooking how education investment and human capital collectively shape multidimensional development outcomes across China's diverse regions. To address this gap, we construct a novel development index incorporating innovation, sustainability, and social progress metrics, analyzing panel data from 31 Chinese provinces (2000–2020) through two-way fixed effects models with instrumental variables. Our findings reveal that higher education investment significantly enhances comprehensive development, with this effect amplified in regions with greater human capital accumulation. Notably, regional heterogeneity analysis demonstrates stronger investment effectiveness in eastern provinces compared to central regions, while western provinces show no significant relationship. These results underscore the importance of regionally differentiated approaches to educational investment and human capital development, offering valuable insights for policymakers seeking to promote balanced growth across China's economically diverse landscape.

Temporal inequality of RR intervals like a new psychophysiological indicator of mental stress

Introduction: Gini coefficient (Gini index or Gini ratio) is a parameter that is normally used in economy to measure the income distribution in a country or in the whole wide world, but it can be used to measure any kind of distribution. In the present study it is exposed an innovative proposal of application of the Gini coefficient to Heart Rate Variability (HRV) like a psychophysiological indicator of mental stress.Objective: to assess the application of the Gini coefficient as a psychophysiological indicator of mental stress.Methods: a non-observational crossover study, carried out in the biomedical laboratory of the Medical University of Santiago de Cuba. The involved participants are 13 healthy individuals (age 19 ± 1,5 years). Heart rate was continuously recorded at rest (5 minutes) and during a mental stress (5 minutes). Linear and nonlinear methods of heart rate variability were assessed, and 2 new indicators (Sequential and Non-Sequential Gini) were calculated and proposed to measure HRV differences between states.Results: when comparing rest and mental stress conditions, a sensible decrease of the traditional indicators of the HRV was founded (p&lt;0,05), an increase of the heart rate (p=0,004) and of the Sequential Gini (p=0,004) and Non-Sequential Gini (p=0,04).Conclusions: the results suggest that temporary inequality of the RR intervals analyzed from the Gini coefficient could be an adequate indicator of sympathetic activity present during the mental stress

Symmetry in Signals: A New Insight.

Symmetry is a fundamental property of many natural systems, which is observable through signals. In most out-of-equilibrium complex dynamic systems, the observed signals are asymmetric. However, for certain operating modes, some systems have demonstrated a resurgence of symmetry in their signals. Research has naturally focused on examining time invariance to quantify this symmetry. Measures based on the statistical and harmonic properties of signals have been proposed, but most of them focused on harmonic distortion without explicitly measuring symmetry. This paper introduces a new mathematical framework based on group theory for analyzing signal symmetry beyond time invariance. It presents new indicators to evaluate different types of symmetry in non-stochastic symmetric signals. Both periodic and non-periodic symmetric signals are analyzed to formalize the problem. The study raises critical questions about the completeness of symmetry in signals and proposes a new classification for periodic and non-periodic signals that goes beyond the traditional classification based on Fourier coefficients. Furthermore, new measures such as "symmetrometry" and "distorsymmetry" are introduced to quantify symmetry. These measures outperform traditional indicators like Total Harmonic Distortion (THD) and provide a more accurate measurement of symmetry in complex signals from applications where duty cycle plays a major role.

The use of PROMs (patient-reported outcome measures) and PREMs (patient-reported experience measures) in Cardiology: current state and applications to improve patient care

The integration of patient-reported outcomes and experiences through PROMs and PREMs tools represents a significant evolution in the quality of care and clinical practice. This article reviews the state of the art and the application experiences of these tools, focusing on their impact on the management of cardiovascular diseases. The use of PROMs and PREMs allows for a more comprehensive assessment of patient well-being by integrating with traditional clinical indicators. An increasing number of studies suggests that the systematic collection of these data can help physicians in better identifying individual patient's needs, improving doctor-patient communication, and personalizing therapies. In aggregate form, these data can be used to improve the quality of services. This article explores the main international experiences, starting from the activities carried out in this field by the European Society of Cardiology, the challenges in implementing such tools, and the prospects for a more widespread adoption in daily clinical practice. It emphasizes the activities carried out in Italy by the Fondazione Toscana Gabriele Monasterio and the Management and Healthcare Laboratory of the Scuola Superiore Sant'Anna of Pisa, highlighting the importance of validated tools, appropriate technologies, and a cultural change to promote patient-centered care.

Quality of Life in Women After Total Knee Arthroplasty With Valgus Deformity

Objectives While traditional indicators focus on implant survivor, the assessment of quality of life encompasses broader dimensions, such as the experience of pain, mobility, the ability to perform daily activities, and mental well-being. Given the anatomical, psychological, and cultural differences found in females, and the rarity of valgus deformity, which comprises only 10% of total knee arthroplasty cases, there is a significant gap in available data, highlighting the importance of research directed towards this specific group of patients. Methods This observational study involved 20 participants with valgus deformity who underwent total knee arthroplasty at an university hospital. The study was previously approved by the Research Ethics Committee (CAAE: 58487222.5.0000.5404). The assessment of function, quality of life and pain was carried out using the WOMAC, EuroQol-5D 3L, Kujala and Visual Analogue Scale for pain (VASpain) questionnaires. Results The participants, all female, had an average age of 68.3 years ∓ 9.4SD, with an average weight of 78.6 kg ∓ 13.5SD, average height of 1.57 m ∓ 0.07SD and Average BMI of 24.7 ∓ 4.4 SD. Post-surgical follow-up time was on average 79.6 months ∓ 37.3SD, with 73.9% of cases on the right knee and 26.1% on the left side. The average pain VAS was 2.9 points. The Kujala scale presented an average of 66.9 points. WOMAC presented an average of 15.6 points ∓ 12.2 SD, with a minimum of 3.1 and a maximum of 61.5. EuroQol 5D 3L demonstrated good quality of life, with at least 61 points in 80% of all cases. Conclusion In conclusion, most participants experienced mild to moderate post-surgery pain, but the intervention substantially improved quality of life, enabling daily activities resumption.

What Is My Plaza for? Implementing a Machine Learning Strategy for Public Events Prediction in the Urban Square

Plazas are an essential pillar of public life in our cities. Historically, they have been seen as public fora, hosting public events that fostered trade, interaction, and debate. However, with the rise of modern urbanism, city planners considered them as part of a larger strategic development scheme overlooking their social importance. As a result, plazas have lost their function and value. In recent years, awareness has risen of the need to re-activate these public spaces to strive for social inclusion and urban resilience. Geometric and urban features of plazas and their surroundings often suggest what kinds of usage the public can make of them. In this project, we explore the application of machine learning to predict the suitability of events in public spaces, aiming to enhance urban plaza design. Learning from traditional urbanism indicators, we consider factors associated with the features of the public space, such as the number of people and the high degree of comfort, which are evolved from three subcategories: external factors, geometric shape, and design factors. We acknowledge that the predictive capability of our model is constrained by a relatively small dataset, comprising 15 real plazas in Madrid augmented digitally to 2025 fictional scenarios through self-organising maps. The article details the methods to quantify and enumerate quantitative urban features. With a categorical target variable, a classification model is trained to predict the type of event in the urban space. The model is then evaluated locally in Grasshopper by visualising a parametric verified geometry and deploying the model on other existing plazas worldwide regarding geographical proximity to Madrid, where to share or not the same cultural and environmental conditions. Despite these limitations, our findings offer valuable insights into the potential of machine learning in urban planning, suggesting pathways for future research to expand upon this foundational study.

The clinical potential of 1,5-anhydroglucitol as biomarker in diabetes mellitus.

A crucial measure of diabetes management is to monitor blood glucose, which often requires continuous blood collection, leading to economic burden and discomfort. Blood glucose and glycated hemoglobin A1c serve as traditional indicators of glucose monitoring. But now glycated albumin, fructosamine, and 1,5-anhydroglucitol (1,5-AG) have been gaining more attention. 1,5-AG is a chemically stable monosaccharide that exists in the human body. Its serum concentration remains stable when blood glucose levels are normal. However, it decreases when blood glucose exceeds the renal glucose threshold. Studies have shown that 1.5-AG reflects blood glucose changes in 1 to 2 weeks; therefore, decreased levels of serum 1,5-AG can serve as a clinical indicator of short-term blood glucose disturbances. Recent studies have shown that 1,5-AG can be used not only for the screening and managing of diabetes but also for predicting diabetes-related adverse events and islet β cell function in prediabetic patients. In addition, saliva 1,5-AG demonstrates potential value in the screening and diagnosis of diabetes. This review focuses on the biological characteristics, detection methods, and clinical application of 1,5-AG to promote understanding and applicable research of 1,5-AG in the future.

Electrocardiograph analysis for risk assessment of heart failure with preserved ejection fraction: A deep learning model.

Heart failure with preserved ejection fraction (HFpEF) requires an efficient screening method. We developed a deep learning model (DLM) to screen HFpEF risk using electrocardiograms (ECGs). A cohort study was conducted utilising data from Cohorts A and B. A convolutional neural network-long short-term memory (CNN-LSTM) DLM was employed. HFpEF risk was determined by left ventricular end-diastolic pressure (LVEDP) and clinical symptoms. The DLM was trained by ECGs. LVEDP for each patient was collected through invasive left ventricular catheterisation. Cohort A and B comprised data from individuals at high risk for HFpEF (LVEDP>12mmHg) and low risk for HFpEF (LVEDP≤12mmHg). The model was trained on Cohort A and prospectively validated on Cohort B. A total of 238 patients underwent ECG and left ventricular catheterisation for model training in Cohort A, and 117 patients for validation in Cohort B. The DLM achieved 78% accuracy in assessing HFpEF risk in Cohort A, while in Cohort B, it demonstrated 78% accuracy, 71.9% specificity, and 71.7% sensitivity. In the validation Cohort B, the DLM-identified high-risk HFpEF group exhibited significantly higher prevalence of diabetes (22.03%-11.86%, P<0.01), higher BMI indices (25.92-24.22kg/cm2, P<0.01), and lower usage history of calcium channel blockers (CCB) (11.76%-28.81%, P<0.01) compared with the DLM-identified low-risk HFpEF group. Traditional HFpEF indicators, including B-type natriuretic peptide (BNP) (22-20pg/mL, P=0.71) and E/E' (8.25-8.5, P=0.66), did not exhibit significant differences between the two groups. The DLM offers an accurate, cost-effective tool for HFpEF risk assessment, potentially facilitating early detection and improved clinical management.

The synergy of renewable energy consumption, green technology, and environmental quality: Designing sustainable development goals policies

AbstractGreen technology (GT) and the utilization of renewable energy (RE) are widely acknowledged as a catalyst for energy efficiency, economic growth, and a tool for combating environmental degradation. Although various studies have examined the ecological repercussions of these two improvements, they have primarily used traditional pollution indicators (namely, carbon emissions and ecological footprint) and ignored nations with the highest cleaner energy adoption. To bridge this gap, the present research seeks to analyze the relationship between GT, RE consumption, economic growth, trade, and load capacity factor in the top‐10 renewable economies. In addition to environmental pollution indicators, the study utilizes the load capacity factor as a novel proxy for environmental quality and investigates the load capacity curve hypothesis using the Cross‐sectional‐autoregressive distributed lag model from 1990 to 2021. According to the empirical findings, all explanatory variables have a significant long‐term effect on the load capacity. More precisely, GT and RE consumption contribute to the sustainability of the ecosystem, while trade increases the ecological deficit. Furthermore, the findings do not support the validity of the load capacity curve hypothesis, implying that the environmental restorative benefits of economic well‐being may not manifest in the latter stages of economic growth. Given these findings, policymakers in the top‐10 renewable economies should seize the environmental prospects offered by GT and RE and update trade and growth policies in a way that promotes biocapacity while simultaneously reducing the ecological footprint to reach the long‐term sustainable development goals (SDGs), particularly SDGs 7 and 13.