Model Assessment Research Articles

Index construction and real-time hazard assessment of rice sterile-type chilling injury process in Northeast China

Rice is a warm-temperature crop, and sterile-type chilling injuries may be induced by acute periods of low-temperature weather during the reproductive growth period. This study considered the daily mean and minimum temperatures in Northeast China from 1979 to 2018 as influencing factors to construct a process-based rice accumulated intensity index (PARII) and hazard assessment model based on known crop disaster periods, analyzed the spatiotemporal distribution characteristics of chilling injury during the rice growth period (booting and flowering stages), used solar-induced chlorophyll fluorescence (SIF) and yield fluctuation data to calculate the adaptability of the hazard assessment model, and selected two typical events of disaster processes to verify the proposed real-time hazard assessment model. The change in the cumulative intensity index of rice sterile-type chilling injury indicated an increasing trend in chilling injury in the rice booting stage . Based on the probability density static hazard and cumulative probability dynamics, the results of real-time hazard analysis showed that the chilling injury hazard area was significantly expanded compared with the sterile-type chilling injury during the booting and flowering periods. The hazard value was greater than 0.2 in central and southeastern Heilongjiang, and the static hazard index was significantly negatively correlated with SIF and fluctuating yield, which indicated the chilling injury impacted rice yield and physiology. Regional-scale hazard levels were assessed by daily real-time hazard evaluation to highlight spatial heterogeneity in crop stress and damage. The results of this study provide a scientific basis for real-time risk assessment and management of chilling injury in rice crops and may support future adaptation strategies for addressing risks associated with severe low-temperature events.

Comparison of Triglyceride–Glucose (TyG) Index and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) Index in Prediction of Male Hypogonadism

Several studies have shown the association between decreased insulin sensitivity and the risk of male hypogonadism. Homeostatic model assessment of insulin resistance (HOMA-IR) is a well-established marker of decreased insulin sensitivity. The triglyceride–glucose index (TyG), calculated as ln fasting triglyceride mg/dL× fasting glucose mg/dL/2, was recently suggested to be a cheaper and a reliable surrogate marker to detect insulin resistance (IR). Our aim was to compare the performance of those two indexes in the prediction of male hypogonadism. The data on 192 men from infertile couples (18–50 years; sperm concentration <20 x 106/mL) and 199 population-based matched controls collected during the years 2009–2012 (baseline) were evaluated retrospectively. Half of these subjects (72 subfertile men and 122 controls) were reinvestigated 5–10 years later (median year (range): 7 (5–10)). The patients receiving any hormonal therapy were excluded. Hypogonadism was defined as fasting, morning serum testosterone below 12 nmol/L. In receiver operating characteristic curve analysis, the optimal diagnostic cutoff values for baseline HOMA-IR and TyG to predict MetS at re-examination were 2.68 (Area Under Curve (AUC) = 0.886, p < 0.001) and 8.60 (AUC = 0.816, p <0.001), respectively. Moreover, in binary logistic regression analysis performed on the whole cohort using these thresholds for high values of HOMA-IR and high TyG, the odds-ratios (ORs) for hypogonadism were 6.48 (95% Confidence Interval (CI): 3.77–11.2; p <0.001) and 3.58 (95% CI: 2.17–5.94; p <0.001), respectively. Even though high HOMA-IR levels provided better risk estimates, high TyG was also highly related to the risk of hypogonadism. These markers can be utilized to identify men being at high risk of hypogonadism.

Associations of sedentary behavior and screen time with biomarkers of inflammation and insulin resistance.

Sedentary behavior (SB) has been linked to risk factors of cardiometabolic disease, with inconsistent findings reported in the literature. We aimed to assess the associations of SB with multiple biomarkers of inflammation and insulin resistance in adults. Domain-specific SB, sitting time and moderate-to-vigorous physical activity (MVPA) were measured in 78 adults (mean ± SD 52.0 ± 10.8 y). Body fat percentage (BF%) was assessed using multi-frequency bioelectrical impedance. A blood draw assessed glucose, insulin, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), leptin, and adiponectin. Adiponectin-leptin ratio (ALR), homeostasis model assessment of insulin resistance (HOMA-IR) and beta-cell function (HOMA-β) were calculated. Multivariable linear regression analyses, controlling for age, sex, MVPA, and BF%, were used to assess associations. After adjustment for age, sex and MVPA, total SB (7.5 ± 2.5h/day) was positively associated with leptin, insulin, HOMA-IR, HOMA-β (Standardized Beta (β) range 0.21-0.32) and negatively associated with ALR (β = -0.24, p < 0.05 for all). Similarly, total sitting time (7.2 ± 2.9h/day) was associated with TNF-α (β = 0.22) and ALR (β = -0.26). These associations were attenuated to non-significance after adjustment for BF%. Leisure screen time was detrimentally associated with IL-6 (β = 0.24), leptin (β = 0.21), insulin (β = 0.37), HOMA-IR (β = 0.37), and HOMA-β (β = 0.34), independent of age, sex and MVPA (p < 0.05 for all). Only the associations with insulin (β = 0.26), HOMA-IR (β = 0.26), and HOMA-β (β = 0.23) remained significant after further controlling BF% (p < 0.05). Self-reported SB is associated with biomarkers of inflammation and insulin resistance, independent of MVPA, and in some cases BF%.

Measurement and Comparison of Total Electron Content for Assessment of Ionospheric Models during April 7, 2000 Geomagnetic Storms

Measurement and Comparison of Total Electron Content for Assessment of Ionospheric Models during April 7, 2000 Geomagnetic Storms

Childhood Apraxia of Speech: A Descriptive and Prescriptive Model of Assessment and Diagnosis.

Childhood apraxia of speech (CAS) represents a significant diagnostic and therapeutic challenge within the field of clinical neuropsychology, characterized by its nuanced presentation and multifactorial nature. The aim of this study was to distil and synthesize the broad spectrum of research into a coherent model for the assessment and diagnosis of CAS. Through a mixed-method design, the quantitative phase analyzed 290 studies, unveiling 10 clusters: developmental apraxia, tabby talk, intellectual disabilities, underlying speech processes, breakpoint localization, speech characteristics, functional characteristics, clinical practice, and treatment outcome. The qualitative phase conducted a thematic analysis on the most cited and recent literature, identifying 10 categories: neurobiological markers, speech motor control, perceptual speech features, auditory processing, prosody and stress patterns, parent- and self-report measures, intervention response, motor learning and generalization, comorbidity analysis, and cultural and linguistic considerations. Integrating these findings, a descriptive and prescriptive model was developed, encapsulating the complexities of CAS and providing a structured approach for clinicians. This model advances the understanding of CAS and supports the development of targeted interventions. This study concludes with a call for evidence-based personalized treatment plans that account for the diverse neurobiological and cultural backgrounds of children with CAS. Its implications for practice include the integration of cutting-edge assessment tools that embrace the heterogeneity of CAS presentations, ensuring that interventions are as unique as the children they aim to support.

Integrated assessment modeling of a zero-emissions global transportation sector

Currently responsible for over one fifth of carbon emissions worldwide, the transportation sector will need to undergo a substantial technological transition to ensure compatibility with global climate goals. Few studies have modeled strategies to achieve zero emissions across all transportation modes, including aviation and shipping, alongside an integrated analysis of feedbacks on other sectors and environmental systems. Here, we use a global integrated assessment model to evaluate deep decarbonization scenarios for the transportation sector consistent with maintaining end-of-century warming below 1.5 °C, considering varied timelines for fossil fuel phase-out and implementation of advanced alternative technologies. We highlight the leading low carbon technologies for each transportation mode, finding that electrification contributes most to decarbonization across the sector. Biofuels and hydrogen are particularly important for aviation and shipping. Our most ambitious scenario eliminates transportation emissions by mid-century, contributing substantially to achieving climate targets but requiring rapid technological shifts with integrated impacts on fuel demands and availability and upstream energy transitions.

Taking stock of carbon dioxide removal policy in emerging economies: developments in Brazil, China, and India

ABSTRACT Deliberately removing carbon dioxide from the atmosphere is an important element of bringing mitigation pathways in line with the climate goals of the Paris Agreement. To reach global net-zero CO2 emissions and limit global warming to 1.5°C with no or limited overshoot, global mitigation pathways assessed by IPCC’s Sixth Assessment Report require some world regions to achieve net-negative CO2 emissions with large-scale carbon dioxide removal (CDR) deployment. This raises important questions about the availability and feasibility of CDR deployment in different societal and political contexts. This paper therefore combines an analysis of CDR deployment in a sample of scenarios from the IPCC AR6 database with a bottom-up analysis of the state of CDR governance and policy in countries considered key in scaling up CDR capacity and not yet covered by existing research. In particular, the paper focuses on Brazil, China, and India as important emerging economies and large emitters. We highlight the expected use of CDR methods in those regions in scenarios and systematically assess and compare the level of CDR regulation and innovation across these countries. This comparative perspective has the potential to broaden the understanding of existing and emerging CDR policies and politics. The synthesis of the case studies provides three key contributions to existing literature: First, we explore the state of CDR governance and policymaking in key emerging economies. As in OECD countries, there is a notable lack of CDR regulation and innovation to enable the scale of CDR required in the short- and medium term. Second, we identify that repurposing policies is a key type of emerging CDR policymaking in these countries targeting CDR methods in the land use, land use change and forestry (LULUCF) sector. We find that the repurposing efforts strengthen the level of regulation and innovation for this group of methods. Third, we explore three building blocks (regional differentiation, delay of upscaling, sustainability thresholds) of plausible CDR deployment narratives that could help bridge integrated assessment models and comparative case studies in future research.

Improved digraph and matrix assessment model using bipolar fuzzy numbers

Improved digraph and matrix assessment model using bipolar fuzzy numbers

Mesenchymal stem cells improve cardiac function in diabetic rats by reducing cardiac injury biomarkers and downregulating JAK/STAT/iNOS and iNOS/Apoptosis signaling pathways

Cardiovascular complications are prevalent manifestations of type 2 diabetes mellitus (T2DM) and are usually the main cause of death. This study aims to show the underlying mechanisms of the potential therapeutic effect of mesenchymal stem cells (MSCs) on diabetic cardiac dysfunction. Twenty-four male Wistar rats were randomly assigned to one of three groups The control group received standard laboratory chow, and the groups with T2DM received a single dose of 45 mg/kg body weight of streptozotocin (STZ) after 3 weeks of pretreatment with a high-fat diet (HFD). Eight weeks after the diagnosis of T2DM, rats were divided into two groups: the T2DM model group and the T2DM + MSCs group. BM-MSCs were administered systemically at 2 × 106 cells/rat doses.A Significant amelioration in Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and dyslipidemia was noted 2 weeks post-administration of MSCs. Administration of MSCs improved dyslipidemia, the altered cardiac injury biomarkers (p ≤ 0.0001), downregulated Janus kinase 2/signal transducer and activator of transcription 3(JAK2/STAT3)/inducible Nitric oxide synthase (iNOS) and iNOS/Apoptosis signaling pathways. This was associated with improved cardiac dysfunction (impaired left ventricular performance and decreased contractility index).Our results show that MSCs ameliorate cardiac dysfunction associated with diabetic cardiomyopathy by lowering dyslipidemia and insulin resistance, inhibiting oxidative stress, and inflammation, downregulating JAK2/STAT3/iNOS and iNOS/Apoptosis signaling pathways.

#2623 Homeostatic Model Assessment (HOMA) in pediatric patients with nephrotic syndrome receiving tacrolimus

Abstract Background and Aims Children with nephrotic syndrome (NS) receive diabetogenic drugs like tacrolimus (TAC) and steroids. TAC is toxic to pancreatic β-cells and suppresses insulin production in a time and dose dependent manner. This is well documented in renal transplant patients who develop post-transplant diabetes mellitus (PTDM). Although overt diabetes is uncommon in children receiving TAC for NS, the subclinical effect on β cell function has not been studied. Our aim was to study pancreatic beta cell function as assessed by homeostasis model assessment (HOMA) indices in children with NS who received TAC therapy for at least 1 year duration. Method We performed a prospective descriptive study where we followed children (1-18 years) with NS who received TAC therapy for at least 1 year. We noted patient demographics, clinical and histologic pattern of NS, cumulative steroid dose (mg/kg/day) received 90 days prior and TAC C0 levels. Fasting insulin, blood sugar to calculate HOMA indices for IR (insulin resistance), HOMA % β for beta cell function, HOMA-IS (insulin sensitivity), C-peptide and HbA1C were done once at study inclusion and yearly intervals when required. Statistical analysis included Pearson's correlation, paired t test and regression analysis. Results We performed HOMA indices in 37 children (19 males, 18 females) between September 2021-February 2023. Six patients had 2 measurements during the study period. The mean age of onset of NS was 28 months (95% CI [20; 36]) and mean age at HOMA indices measurement was 69 months (95% CI [59; 79]). Of the 37 patients, 54% (20/37) had late steroid resistance, 32% (12/37) had early steroid resistance, 8% (3/37) had steroid dependent NS, 6% (2/37) had frequently relapsing NS. Kidney biopsy performed in 36 children showed minimal change disease in 55.5% (20/36) and focal segmental glomerulosclerosis in 44.5% (16/36). The mean TAC duration, TAC Co level and mean cumulative steroid dose received in last 90 days were 27 months (95% CI [22;32]), 4.54 ng/ml (95% CI [4.12;4.97]) and 0.36 mg/kg/d (95% CI [0.28;0.44]) respectively. Eleven (30%) patients had cutaneous signs of insulin resistance like acanthosis nigricans and 9 (24%) patients had fasting blood sugar of &amp;gt;100 mg/dl. In Pearson's correlation analysis we found positive correlation between TAC Co level, HOMA IR (r = 0.4, P = 0.008) and TAC Co, HOMA %β (r = 0.44, P = 0.003) and cumulative steroid dose, fasting blood glucose (r = 0.3, P = 0.46). There was negative correlation between TAC Co level, HOMA IS (r = −0.4, P = 0.007). In regression analysis, only TAC Co level significantly influenced all HOMA indices including insulin resistance, insulin sensitivity and beta cell function. A HbA1C of &amp;gt; 5.7 (pre-diabetes range) was found in 32.4% (12/37) patients which warrants further monitoring. C-peptide levels were significantly higher after 12 months of TAC therapy in 6 patients who had two measurements (p = 0.032). Conclusion Tacrolimus therapy for nephrotic syndrome in children can affect pancreatic beta cell function as assessed by HOMA indices. Long term monitoring of pancreatic beta cell function in children with NS on TAC is needed to assess the full extent of these subclinical alterations.

Unravelling the influence of heterogeneities and abstraction on groundwater flow and solute transport in a fractured carbonate aquifer, Sicily, Italy

The migration of a groundwater contaminant plume consisting of light nonaqueous phase liquids (LNAPLs) along the Ionian coastline of Sicily, Italy, has been reported to follow a trajectory that is inconsistent with the regional hydraulic gradient. The influence of several faults affecting the fractured carbonate bedrock aquifer, and groundwater abstraction from a well, were hypothesized to be responsible for the anomalous trajectory of the contaminant plume. A conceptual hydrogeological model was developed for the study area that incorporated structural information derived from geophysical surveys and the mapping of fractures in bedrock outcrops. This conceptual model was incorporated into numerical groundwater flow and solute transport models to simulate the groundwater transport of the light nonaqueous phase liquids. Four model scenarios representing different levels of complexity were tested to assess the relative influence of geological heterogeneity and groundwater abstraction on the migration of the contaminant plume. Results show that underground major discontinuity systems, invoking the presence of the faults in the model domain accounted for the observed migration of the contaminant plume, act as conduits for groundwater flow. Conversely, groundwater abstraction from a well was found to result in relatively minor, localized impacts to the migration of the contamination plume. This study demonstrates the importance of incorporating geological heterogeneity into groundwater modelling and environmental risk assessments associated with the storage of LNAPLs.

#1624 The association between serum beclin 1 level and the presence of aortic valve calcification among individuals on hemodialysis

Abstract Background and Aims The autophagy pathway, a crucial regulator of cellular health and metabolism, plays a fundamental role in maintaining healthy blood vessel function. Studies have established its critical involvement in endothelial cell stability, vascular smooth muscle cell (VSMC) phenotype control, and VSMC calcium balance. Recent evidence, further, underlines autophagy's direct protective role against vascular calcification. It has been shown that autophagy can modulate different cardiovascular pathologies, including valvular calcification. We aimed to explore the potential link between the protein beclin 1 and heart valve calcification in dialysis patients. Method We compared two groups of 51 haemodialysis patients each, defined by the presence (Group 1) or absence of valve calcification (Group 2) on echocardiograms. Both groups underwent beclin 1 level measurements and other assessments (lipid profile). Cardiac valve calcification was diagnosed through echocardiography by identifying dense echoes exceeding 1 millimeter in thickness on one or more aortic valve cusps. The severity of calcification was then classified into three stages: Mild: Calcification thickness ranged from 1 to 3 millimeters and involved less than 50% of the valve leaflet. Moderate: Calcification thickness exceeded 3 millimeters but still affected less than half of the valve leaflet. Severe: Calcification thickness surpassed 3 millimeters and encompassed more than 50% of the valve leaflet. Results Our analysis demonstrated a statistically significant increase in beclin 1 levels in Group 2 compared to Group 1 (p&amp;lt;0.001), a striking relationship between lower beclin 1 levels and more severe valve calcification. Interestingly, a specific beclin 1 cutoff below 35.5 ng/ml offered the highest accuracy (98% sensitivity and 92% specificity) in predicting valve calcification. Notably, significant differences were found in lipid profiles (Analysis of the lipid profile revealed a striking trend in Group I, with significant elevations in cholesterol, triglycerides, and LDL. Conversely, HDL levels were significantly higher in Group II). and prevalence of heart disease between the groups. Analysis of IHD prevalence across the two groups yielded a striking result. Group 1 displayed a significantly higher proportion of individuals with IHD (17 cases) compared to group 2 (3 cases), with a statistically significant difference (p&amp;lt;0.001). Conclusion Based on these results, it appears promising to integrate serum Beclin 1 measurements into a risk assessment model for the development of heart valve calcification in dialysis patients.

Enhancing Thrombophilia Risk Prediction Through AI-Based Methodologies.

Thrombophilia, a predisposition to thrombosis, poses significant diagnostic challenges due to its multi-factorial nature, encompassing genetic and acquired factors. Current diagnostic paradigms, primarily relying on a combination of clinical assessment and targeted laboratory tests, often fail to capture the complex interplay of factors contributing to thrombophilia risk. This paper proposes an innovative artificial intelligence (AI)-based methodology aimed to enhance the prediction of thrombophilia risk. The designed multidimensional risk assessment model integrates and elaborates through AI a comprehensive collection of patient data types, including genetic markers, clinical parameters, patient history, and lifestyle factors, in order to obtain advanced and personalized explainable diagnoses.

Risk assessment of organ transplant operation: A fuzzy hybrid MCDM approach based on fuzzy FMEA.

Nowadays, most fatal diseases are attributed to the malfunction of bodily. Sometimes organ transplantation is the only possible therapy, for instance for patients with end-stage liver diseases, and the preferred treatment, for instance for patients with end-stage renal diseases. However, this surgical procedure comes with inherent risks and effectively managing these risks to minimize the likelihood of complications arising from organ transplantation (maximizing life years from transplant and quality-adjusted life years) is crucial. To facilitate this process, risk ranking is used to identify and promptly address potential risks. Over recent years, considerable efforts have been made, and various approaches have been proposed to enhance Failure Modes and Effects Analysis (FMEA). In this study, taking into account the uncertainty in linguistic variables (F-FMEA), we introduce an approach based on Fuzzy Multi Criteria Decision Making (F-MCDM) for effectively evaluating scenarios and initial failure hazards. Nevertheless, the results of ranking failure modes generated by different MCDM methods may vary. This study is a retrospective study that suggests a comprehensive unified risk assessment model, integrating multiple techniques to produce a more inclusive ranking of failure modes. Exploring a broad spectrum of risks associated with organ transplant operations, we identified 20 principal hazards with the assistance of literature and experts. We developed a questionnaire to examine the impact of various critical factors on the survival of transplanted organs, such as irregularities in immunosuppressive drug consumption, inappropriate dietary habits, psychological disorders, engaging in strenuous activities post-transplant, neglecting quarantine regulations, and other design-related factors. Subsequently, we analyzed the severity of their effects on the durability of transplanted organs. Utilizing the Mamdani algorithm as a fuzzy inference engine and the Center of Gravity algorithm for tooling, we expressed the probability and severity of each risk. Finally, the failure mode ranking obtained from the F-FMEA method, three fuzzy MCDM methods, and the proposed combined method were identified. Additionally, the results obtained from various methods were evaluated by an expert team, demonstrating that the highest consistency and effectiveness among different methods are attributed to the proposed method, as it achieved a 91.67% agreement with expert opinions.

The Development of a Cold-Chain-Packaging Risk Management Model Based on Fuzzy Bayesian Network

Cold chain packaging faces high levels of uncertainty due to its complex nature and dynamic environments during transportation, and the importance of safety and risk management. This study aims to propose a risk assessment model for cold chain packaging based on a fuzzy Bayesian Network. A case study on vaccine cold chain shipping containers is conducted for the illustration of the risk management model, and risk factors like container risk, packaging risk, monitoring risk and handling risk, occupational and product safety risk have been identified and assessed. This paper will add new knowledge to the field of cold chain packaging, which still lacks research attention, and will be useful for industry managers to gain a better understand of the dynamics and risks of cold chain packaging.

#673 Predictive value of insulin resistance and GFR-adjusted uricemia on all-cause mortality: the URRAH study

Abstract Background and Aims Uric acid (UA) and insulin resistance (IR) are interlinked: UA contributes to adversely affects the insulin signaling pathway, while IR predicts the development of hyperuricemia. Both UA and IR are related to metabolic syndrome, which is nowadays one of the most prevalent risk factors for mortality. In the clinical scenario, the triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio has been proved to have a high correlation with IR. Lipoprotein-based markers of IR are at least as strongly associated with subclinical atherosclerosis and with newly developing atherosclerotic manifestations than Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). The aim of the research was to explore the extent of interaction between IR and GFR-adjusted uricemia in determining mortality risk in a large population cohort study. Method data from 18,694 subjects were included from Uric acid Right foR heArt Healt (URRAH) database. Differences between TG/HDL-C ratio quintiles were evaluated by t-test or chi-square test. We evaluated the association between TG/HDL-C ratio and GFR-adjusted uricemia, and the development of outcomes during the follow-up study period. The primary endpoint was all-cause mortality. The Kaplan-Meier method was used to calculate the cumulative survival rate. Cox proportional hazard regression models were used to analyze the prognosis associated with IR. Results after a mean follow-up of 124 ± 64 months, there were 2,665 (14.2%) deaths for all causes. The incidence of fatal, non-fatal cardiovascular events, and all-cause mortality increased in parallel with the increase of TG/HDL-C quintiles. In both diabetic and non-diabetic patients, TG/HDL-C ratio showed a positive association with increasing of GFR-adjusted uricemia (UA/GFR ratio). TG/HDL-C ratio and GFR-adjusted uricemia significantly interact in determining all-cause mortality, even in non-diabetic patients (P &amp;lt; 0.0001). Subjects with higher TG/HDL-C ratio quintile had a statistically significantly higher rate of mortality than patients with lower quintiles (Fig. 1, log rank test P &amp;lt; 0.0001), independently by uricemia, GFR, the presence of diabetes and body mass index (BMI). Multivariate analysis showed that the TG/HDL-C ratio increase the mortality risk even after adjustment for potential confounding factors included age, diabetes, UA/GFR, BMI and statins treatment (Table 1). Conclusion For practical purposes, the easily obtainable TG/HDL-C ratio may suffice to determine the impact of insulin resistance as a risk factor. TG/HDL-C ratio interacts with GFR-adjusted uricemia in predicting mortality, even in non-diabetic patients. In conclusion, Both IR and GFR-adjusted UA levels seems to have an important predictive role on all-cause mortality, independently of age, gender, diabetes, hypertension and statins.

Prevalence of insulin resistance and its associated factors in drug-naïve patients with bipolar disorder among Han Chinese population

BackgroundMetabolic syndrome (Mets) is commonly seen in bipolar disorder (BD). As the key component and early biological index of Mets, insulin resistance (IR) among BD has received more and more attention. However, little is known about the prevalence of IR and its associated factors in drug-naïve patients with (BD), especially among Han Chinese population.MethodsA cross-sectional study was conducted on 125 drug-naïve patients with bipolar disorder (BD) and 85 healthy controls (HC). The Homeostatic Model Assessment of insulin resistance (HOMA-IR) was calculated, and IR was defined as HOMA-IR greater than the 75th percentile value for health controls (2.35). Clinical characteristics of BD were collected through semi-structural interview performed by a trained interviewer with background of psychiatric education.ResultsAmong the measured anthropocentric variables including BMI, waist circumference, abdomen circumference, hipline, and hip-waist ratio, waist circumference was found to be the most closely related to IR (0R = 1.070, 95%CI = 1.031–1.110, P < 0.001). Male was another factor that was associated with IR (OR = 2.281, 95%CI = 1.107–4.702, P = 0.025). After adjusted for gender and waist circumference, the risk of IR was significantly higher in bipolar disorder than in healthy controls (OR = 2.66, 95%CI = 1.364–5.214, P = 0.004). No significant association was found between IR and any of the observed physical and mental comorbidities, any characteristic of illness course including age onset, number of mixed episodes, types of current state, duration of current episode, duration of illness course, rapid cycling, number of mood episodes, and subgroup of BD. Hypersomnia was the only symptomatic feature that was significantly associated with IR (OR = 0.316, 95%CI = 0.124–0.803, P = 0.016).ConclusionsBipolar disorder increases two-to-three-fold risk of IR, both circumference and male are the risk factors of IR but hypersomnia act as a protective factor.

Negative correlation between metabolic score for insulin resistance index and testosterone in male adults

BackgroundInsulin resistance (IR) is strongly correlated with the decreased deficiency of testosterone levels in males. The metabolic score for insulin resistance (METS-IR) index is regarded as an innovative measure for the assessment on IR. The research aims to explore the correlation between the METS-IR index and the testosterone levels in males.MethodsIn this study, a cross-sectional design was made through the data obtained from the National Health and Nutrition Examination Survey (NHANES) from 2013 to 2020. Besides, the METS-IR index was derived from serum triglyceride levels, fasting plasma glucose, HDL-C and BMI.ResultsA total of 2082 participants were included in the final analysis. After controlling for confounding variables, it was found that METS-IR was independently and negatively correlated with testosterone levels (β = −3.88, 95% CI = −4.49, −3.27, P < 0.001). As shown by the generalized smooth curve fitting, METS-IR had a linear correlation with testosterone levels without threshold or saturation effects, which was consistently observed across all subgroups through stratified analysis (all P > 0.05). As revealed by the analysis on the ROC curve, the area under the curve (AUC) for the METS-IR index (0.732, 95% CI = 0.705, 0.760) was significantly larger than that of homeostatic model assessment of insulin resistance (HOMA-IR), TG/HDL ratio, triglyceride-glucose index (TyG) and body mass index (BMI).ConclusionThe findings suggest a negative relationship between the METS-IR index and the testosterone levels in male adults. Furthermore, the METS-IR index demonstrates superior predictive ability for testosterone deficiency in comparison to HOMA-IR, TG/HDL ratio, TyG and BMI.

#1427 Comparison of METS-IR and HOMA-IR for predicting new-onset CKD in middle-aged and older adults

Abstract Background and Aims Chronic kidney disease (CKD) has emerged as a mounting public health issue worldwide; therefore, prompt identification and prevention are imperative in mitigating CKD-associated complications and mortality rate. We aimed to compare the predictive powers of the homeostatic model assessment for insulin resistance (HOMA-IR) and the metabolic score for insulin resistance (METS-IR) for CKD incidence in middle-aged and older adults. Method This study used longitudinal prospective cohort data from the Korean Genome and Epidemiology Study. A total of 10,030 participants, aged 40–69 years, residing in the Ansung or Ansan regions of the Republic of Korea, were recruited between 2001 and 2002 through a two-stage cluster sampling method. We compared the predictive powers of METS-IR and HOMA-IR for CKD prevalence and incidence, respectively. CKD prevalence was measured by the area under the receiver operating characteristic (ROC) curve (AUC), and the indices’ predictive performance for CKD incidence were assessed using Harrell's concordance index and time-dependent ROC curve analysis. Results A total of 9261 adults aged 40–69 years at baseline and 8243 adults without CKD were included in this study. The AUCs and 95% confidence intervals (CIs) of HOMA-IR and METS-IR for CKD prevalence at baseline were 0.577 (0.537–0.618) and 0.599 (0.560–0.637), respectively, with no significant difference (p = 0.337). The Heagerty's integrated AUC for METS-IR in predicting CKD incidence was 0.772 (95% CI 0.750–0.799), which was significantly higher than that of HOMA-IR (0.767 [95% CI 0.742–0.791], p = 0.015). Conclusion METS-IR surpassed HOMA-IR in predicting CKD incidence and was as effective as HOMA-IR in predicting CKD prevalence. This implies that METS-IR could be a valuable indicator for early detection and prevention of CKD among Korean adults.

Eco‐Friendly Analytical Approaches for the Quantification of Molnupiravir and Favipiravir Using Capillary Zone Electrophoresis and Derivative Ratio Spectrophotometry

AbstractDesigning new validated analytical procedures with a focus on many objectives, such as simplicity, environmental friendliness, analytical effectiveness, and sustainability, has grown to be a top priority in quality control departments. Applying green and white analytical chemistry concepts is no longer a luxury. In this report, two new approaches, Capillary Zone Electrophoresis (CZE) with Photo Diode Array (PDA) detection and derivative ratio spectrophotometric methods, are established and validated for the simultaneous analysis of molnupiravir (MLP) and favipiravir (FAV) in bulk, single dosage forms, and their expected combined dosage forms. For the two drugs, linearity ranges of 5–50 μg/mL and 1–30 μg/mL were achieved using the CZE and spectrophotometric methods, respectively. Both techniques have been validated and used for the estimation of the two medications in lab‐made capsules in accordance with the International Council for Harmonization's (ICH) recommendations. Seven assessment models were used to evaluate the greenness and sustainability of the introduced approaches compared to three previously published HPLC, chemometric, and HPTLC techniques. ChlorTox and BAGI tools are applied for the first time for the evaluation of an analytical procedure. Higher green and sustainable qualities were declared by suggested approaches than by earlier ones.