Lower Insulin Sensitivity Through 36 Months of Life With in Utero HIV and Antiretroviral Exposure in Botswana: Results From the Tshilo Dikotla Study.

BACKGROUND: There are little data on changes in insulin sensitivity during the first few years of life following in utero human immunodeficiency virus (HIV) and antiretroviral (ARV) exposure. METHODS: The Tshilo Dikotla study enrolled pregnant persons with HIV (PWH) (receiving tenofovir/emtricitabine or lamivudine plus dolutegravir or efavirenz) and pregnant individuals without HIV, as well as their liveborn children. Newborns were randomized to receive either zidovudine (AZT) or nevirapine (NVP) postnatal prophylaxis. Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) was assessed at birth and 1, 18, 24, and 36 months of life. We fit linear mixed-effects models to evaluate the association between in utero HIV/ARV exposure and average HOMA-IR from birth through 36 months of life, adjusting for confounders. RESULTS: A total of 419 children were included (287 with in utero HIV/ARV exposure and uninfected [CHEU] and 132 without in utero HIV/ARV exposure [CHUU]). CHEU were born to older women (29.6 vs 25.3 years of age) with higher gravidity (3 vs 1). HOMA-IR was persistently higher in CHEU versus CHUU in adjusted analyses (mean difference of 0.07 in log10 HOMA-IR, P  = .02) from birth through 36 months of life. Among CHEU, no differences in HOMA-IR were observed from birth through 36 months by in utero ARV exposure status or between AZT and NVP infant prophylaxis arms. CONCLUSIONS: In utero HIV/ARV exposure was associated with lower insulin sensitivity throughout the first 36 months of life, indicating persistent early life metabolic disturbances which may raise concern for poorer metabolic health later in life.

Factors associated with treatment responses to pioglitazone in patients with steatotic liver disease: A 3-year prospective cohort study.

AIM: The response rate to pioglitazone and the predictive factors for its effects on improving liver biochemistry in patients with steatotic liver disease (SLD) remain elusive, so we aimed to investigate these issues. METHODS: A 3-year prospective cohort study of 126 Taiwanese patients with SLD treated with pioglitazone (15-30 mg/day) was conducted. Phospholipase domain-containing protein 3 I148M rs738409, methylenetetrahydrofolate reductase rs1801133, aldehyde dehydrogenase 2 (ALDH2) rs671 and lipoprotein lipase rs10099160 single nucleotide polymorphisms were assessed in the patients. RESULTS: Of 126 patients, 78 (61.9%) were men, and the mean and median ages were 54.3 and 56.5 years, respectively. Pioglitazone responders were defined as those with decreased alanine aminotransferase (ALT) levels at 6 months post-treatment, and 105 (83.3%) patients were responders. Compared with non-responders, responders were more frequently women and had higher baseline ALT levels. The proportion of patients with the ALDH2 rs671 GG genotype was lower among responders (38.6% vs. 66.6%, p = .028). Female sex [odds ratio (OR): 4.514, p = .023] and baseline ALT level (OR: 1.015, p = .046; cut-off level: ≥82 U/L) were associated with pioglitazone response. Among responders, the liver biochemistry and homeostasis model assessment of insulin resistance improved from 6 to 24 months post-treatment. The total cholesterol levels decreased within 6 months, while increases in high-density lipoprotein cholesterol levels and decreases in triglyceride levels and fibrosis-4 scores were noted only at 24 months post-treatment. The 2-year cumulative incidences of cardiovascular events, cancers and hepatic events were similar between responders and non-responders. CONCLUSIONS: Regarding liver biochemistry, over 80% of Taiwanese patients with SLD had a pioglitazone response, which was positively associated with female sex and baseline ALT levels. Insulin resistance improved as early as 6 months post-treatment, while liver fibrosis improvement was not observed until 24 months post-treatment. The link between the pioglitazone response and the ALDH2 genotype warrants further investigation.

Redefining 'state-of-the-art' for integrated population models with immigration.

Research Highlight: Christian, M., Oosthuizen, W. C., Bester, M. N., & de Bruyn, P. N. (2024). Robustly estimating the demographic contribution of immigration: Simulation, sensitivity analysis and seals. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.14053. Immigration can have profound consequences for local population dynamics and demography, but collecting data to accurately quantifying it is challenging. The recent rise of integrated population models (IPMs) offers an alternative by making it possible to estimate immigration without the need for explicit data, and to quantify its contribution to population dynamics through transient Life Table Response Experiments (tLTREs). Simulation studies have, however, highlighted that this approach can be prone to bias and overestimation. In their new study, Christian et al. address one of the root causes of this issue by improving the estimation of time variation in vital rates and immigration using Gaussian processes in lieu of traditionally used temporal random effects. They demonstrate that IPM-tLTRE frameworks with Gaussian processes produce more accurate and less biased estimates of immigration and its contribution to population dynamics and illustrate the applicability of this approach using a long-term data set on elephant seals (Mirounga leonida). Results are validated with a simulation study and suggest that immigration of breeding females has been central for population recovery of elephant seals despite the species' high female site fidelity. Christian et al. thus present new insights into population regulation of long-lived marine mammals and highlight the potential for using Gaussian process priors in IPMs. They also illustrate a suite of 'best practices' for state-of-the-art IPM-tLTRE analyses and provide an inspirational example for the kind of ecological modelling workflow that can be invaluable not just as a starting point for fellow ecologists picking up or improving their own IPM-tLTRE analyses, but also for teaching and in contexts where model estimates are used for informing management and conservation decision-making.

Joint association of weight-adjusted-waist index and physical activity with insulin resistance in adolescents: a cross-sectional study.

BACKGROUND: The weight-adjusted waist index (WWI) is a recently developed obesity metric, and the aim of this study was to investigate the relationship between physical activity (PA) and WWI and the homeostasis model assessment of insulin resistance (HOMA-IR) in adolescents, as well as the joint association of HOMA-IR. METHODS: This study was based on the National Health and Nutrition Survey conducted between 2013 and 2016 and included 1024 adolescents whose median age was 15.4. Multivariate linear regression was used to examine the associations between HOMA-IR and PA and WWI. Using generalized additive models, a potential nonlinear link between WWI and HOMA-IR was evaluated. Subgroup analysis was also carried out. RESULTS: The fully adjusted model revealed a positive association (ß: 0.48, 95% CI: 0.43, 0.53) between the WWI and HOMA-IR. The HOMA-IR was lower in physically active (ß: -0.16, 95% CI: -0.26, -0.05) participants versus inactive participants. Participants who had higher WWI and were not physically active (ß: 0.69; 95% CI: 0.56, 0.82) had the highest levels of HOMA-IR compared to participants who had lower WWI and were physically active. Subgroup analysis revealed that these correlations were similar in males and females. CONCLUSION: Our results demonstrated that higher WWI and PA were associated with a lower HOMA-IR and that WWI and PA had a combined association with HOMA-IR. The findings of this study are informative for the preventing insulin resistance in adolescents.

Reduced gray matter volume in the default-mode network associated with insulin resistance.

Insulin resistance may lead to structural and functional abnormalities of the human brain. However, the mechanism by which insulin resistance impairs the brain remains elusive. In this study, we used two large neuroimaging databases to investigate the brain regions where insulin resistance was associated with the gray matter volume and to examine the resting-state functional connectivity between these brain regions and each hypothalamic nucleus. Insulin resistance was associated with reduced gray matter volume in the regions of the default-mode and limbic networks in the cerebral cortex in older adults. Resting-state functional connectivity was prominent between these networks and the paraventricular nucleus of the hypothalamus, a hypothalamic interface connecting functionally with the cerebral cortex. Furthermore, we found a significant correlation in these networks between insulin resistance-related gray matter volume reduction and network paraventricular nucleus of the hypothalamus resting-state functional connectivity. These results suggest that insulin resistance-related gray matter volume reduction in the default-mode and limbic networks emerged through metabolic homeostasis mechanisms in the hypothalamus.

Non-linear associations of HOMA2-IR with all-cause mortality in general populations: insights from NHANES 1999-2006.

BACKGROUND: The association between homeostatic model assessment (HOMA2-IR) and mortality in obese and non-obese populations has not been clearly explained. METHODS: A total of 7,085 individuals aged ≥ 20 years from the 1999-2006 National Health and Nutrition Examination Survey were included in the study. Study endpoints were all-cause and cardiovascular mortality. Multivariate Cox proportional hazards regression models with restricted cubic spline analysis were used for analysis. RESULTS: In the study populations, a total of 1666 all-cause deaths and 555 cardiovascular (CV) deaths were recorded during a mean follow-up of 195.53 months. Notably, a significant difference in obesity was observed in the association between HOMA2-IR and mortality. After adjustment for multiple variables, HOMA2-IR was positively associated with all-cause mortality in all participants, in those with normal BMI, and in those with obesity. Conversely, tertile 2 of HOMA2-IR was associated with a lower risk of all-cause mortality in participants with obesity compared with tertile 1 (adjusted hazard ratio, 0.68; 95% confidence interval, 0.52-0.89; P = 0.005). Results from restricted cubic spline analysis showed a J-shaped association between HOMA2-IR and all-cause and CV mortality. In addition, a nonlinear U-shaped correlation with all-cause (P for nonlinear < 0.001) and CV (P for nonlinear = 0.002) mortality was observed in the population with obesity, with inflection points of HOMA2-IR identified at 1.85 and 1.75. Below the inflection point of 1.85, a negative relationship between HOMA2-IR and all-cause mortality was observed. CONCLUSIONS: Elevated HOMA2-IR showed a notable correlation with increased risk of all-cause mortality. It was noteworthy that excessively reduced levels of insulin resistance showed a distinct association with increased mortality in individuals with obesity.

A Nonlinear Relation between Body Mass Index and Long-Term Poststroke Functional Outcome-The Importance of Insulin Resistance, Inflammation, and Insulin-like Growth Factor-Binding Protein-1.

Both high serum insulin-like growth factor-binding protein-1 (s-IGFBP-1) and insulin resistance (IR) are associated with poor functional outcome poststroke, whereas overweight body mass index (BMI; 25-30) is related to fewer deaths and favorable functional outcome in a phenomenon labeled "the obesity paradox". Furthermore, IGFBP-1 is inversely related to BMI, in contrast to the linear relation between IR and BMI. Here, we investigated s-IGFBP-1 and IR concerning BMI and 7-year poststroke functional outcome. We included 451 stroke patients from the Sahlgrenska Study on Ischemic Stroke (SAHLSIS) with baseline measurements of s-IGFBP1, homeostasis model assessment of IR (HOMA-IR), BMI (categories: normal-weight (8.5-25), overweight (25-30), and obesity (>30)), and high-sensitivity C-reactive protein (hs-CRP) as a measure of general inflammation. Associations with poor functional outcome (modified Rankin scale [mRS] score: 3-6) after 7 years were evaluated using multivariable binary logistic regression, with overweight as reference due to the nonlinear relationship. Both normal-weight (odds-ratio [OR] 2.32, 95% confidence interval [CI] 1.30-4.14) and obese (OR 2.25, 95% CI 1.08-4.71) patients had an increased risk of poor functional outcome, driven by deaths only in the normal-weight. In normal-weight, s-IGFBP-1 modestly attenuated (8.3%) this association. In the obese, the association was instead attenuated by HOMA-IR (22.4%) and hs-CRP (10.4%). Thus, a nonlinear relation between BMI and poor 7-year functional outcome was differently attenuated in the normal-weight and the obese.

Multi-model assessment of potential natural vegetation to support ecological restoration.

Ecological restoration is imperative for controlling desertification. Potential natural vegetation (PNV), the theoretical vegetation succession state, can guides near-natural restoration. Although a rising transition from traditional statistical methods to advanced machine learning and deep learning is observed in PNV simulation, a comprehensive comparison of their performance is still unexplored. Therefore, we overview the performance of PNV mapping in terms of 12 commonly used methods with varying spatial scales and sample sizes. Our findings indicate that the methodology should be carefully selected due to the variation in performance of different model types, with Area Under the Curve (AUC) values ranging from 0.65 to 0.95 for models with sample sizes up to 80% of the total sample size. Specifically, semi-supervised learning performs best with small sample sizes (i.e., 10 to 200), while Random Forest, XGBoost, and artificial neural networks perform better with large sample sizes (i.e., over 500). Further, the performance of all models tends to improve significantly as the sample size increases and the grain size of the crystals becomes smaller. Take the downstream Tarim River Basin, a hyper-arid region undergoing ecological restoration, as a case study. We showed that its potential restored areas were overestimated by 2-3 fold as the spatial scale became coarser, revealing the caution needed while planning restoration projects at coarse resolution. These findings enhance the application of PNV in the design of restoration programs to prevent desertification.

Triglyceride-glucose index: A surrogate marker of homeostasis model assessment of insulin resistance to predict diabetic nephropathy.

Objectives: To determine the association of triglyceride-glucose index with homeostasis model assessment of insulin resistance in type 2 diabetes mellitus patients, and to determine the association of triglyceride-glucose index with urinary albumin-to-creatinine ratio for predicting diabetic nephropathy. METHODS: The observational, cross-sectional study was conducted from September 2021 to September 2022 at the Department of Chemical Pathology, Pakistan Railway Hospital, Rawalpindi, Pakistan and comprised recently-diagnosed type 2 diabetes mellitus patients. Recorded data included age, gender, vitals, diabetes duration, body mass index and other pertinent demographic and clinical information. Measurements included spot urine albumin-to-creatinine ratio, triglycerideglucose index, homeostasis model assesment of insulin resistance as well as fasting serum insulin, fasting plasma glucose, glycosylated haemoglobin, triglycerides, total cholesterol and serum creatinine. On the basis of triglyceride-glucose index scores, the participants were divided into 4 quartiles; Q1=4.5-5, Q2=5.1-5.5, Q3=5.6-6, and Q4=>6. Data was analysed using SPSS 26. RESULTS: Of the 218 patients, 141(64.7%) were females and 77(35.3%) were males. The overall mean age was 49.22±11.46 years. There were 102(46.8%) overweight patients, 33(15.1%) obese and 82(37.2%) had normal weight. There were 58(26.6%) patients in Q1, 86(39.4%) in Q2, 46(21.1%) in Q3 and 28(12.8%) in Q4. Those in Q4 showed elevated fasting plasma glucose, glycated haemoglobin, triglycerides, total cholesterol, low-density lipoprotein cholesterol, homeostasis model assessment of insulin resistance and urine albumin-to-creatinine ratio (p<0.05), as well as low values for high-density lipoprotein cholesterol and estimated glomerular filtration rate(p<0.05). Fasting serum insulin was negatively linked to glycated haemoglobin (r=-0.12, p=0.07). Triglyceride-glucose index (r=0.76, p<0.001), homeostasis model assessment of insulin resistance (r=0.48, p<0.001), and urine albumin-to-creatinine ratio (r=0.10,p=0.05) positively correlated with glycated haemoglobin. Fasting serum insulin (r=-0.13, p=0.05), negatively correlated with triglyceride-glucose index, while homeostasis model assessment of insulin resistance (r= 0.32, p<0.001) and urine albumin-to-creatinine ratio (r=0.28, p=0.05) had a positive correlation. The estimated glomerular filtration rate was significantly positively linked with fasting serum insulin (r=0.05, p=0.05), and correlated significantly negatively with triglyceride-glucose index (r=-0.35, p=0.01), homeostasis model assessment of insulin resistance (r=-0.01, p=0.86) and urine albumin-to-creatinine ratio (r=-0.02, p=0.8). CONCLUSIONS: The triglyceride-glucose index showed a strong association with homeostasis model assessment of insulin resistance, and surpassed it in terms of predicting diabetic nephropathy in type 2 diabetes mellitus patients.

Maternal insulin resistance in pregnancy is associated with fetal fat deposition: findings from a longitudinal study.

BACKGROUND: Newborns exhibit substantial variation in fat mass accretion over gestation. These individual differences in newborn adiposity extend into infancy and childhood and relate to subsequent risk of obesity and metabolic dysregulation. Maternal glucose homeostasis in pregnancy has been proposed as an underlying mechanism; however, the timing in gestation when maternal glucose regulation influences the progression of fetal fat deposition remain unclear. OBJECTIVE: This study aimed to investigate the cross-sectional and longitudinal association of maternal insulin resistance in early, mid, and late pregnancy with fetal fat deposition in uncomplicated pregnancies. We hypothesized that maternal insulin resistance at early, mid, and late gestation is positively associated with fetal fat deposition, and that the magnitude of the association is greater for the mid and late gestation measures than for the early gestation measure. STUDY DESIGN: In a longitudinal study of 137 low-risk pregnancies, a fasting maternal blood sample was obtained and fetal ultrasonography was performed at ≈ 12, 20, and 30 weeks' gestation. Maternal insulin resistance was quantified using the homeostasis model assessment of insulin resistance (fasting insulin×fasting glucose/405). Estimated fetal adiposity was calculated by integrating measurements of cross-sectional arm and thigh percentage fat area and anterior abdominal wall thickness. The associations between maternal homeostasis model assessment of insulin resistance and estimated fetal adiposity and estimated fetal weight were determined by multiple linear regression adjusted for potential confounding factors including maternal age, parity, race and ethnicity, prepregnancy body mass index, gestational weight gain per week, fetal sex, and gestational age at assessments. RESULTS: Maternal homeostasis model assessment of insulin resistance at ≈ 12, 20, and 30 weeks was 2.79±1.79 (±standard deviation), 2.78±1.54, and 3.76±2.30, respectively. Homeostasis model assessment of insulin resistance at 20 weeks was positively associated with estimated fetal adiposity at 20 weeks (r=0.261; P=.005). Homeostasis model assessment of insulin resistance at 20 weeks (r=0.215; P=.011) and 30 weeks (r=0.285; P=.001) were also positively associated with estimated fetal adiposity at 30 weeks. These relationships remained significant after adjustment for confounding factors. There was no significant correlation between homeostasis model assessment of insulin resistance and estimated fetal weight at 20 and 30 weeks' gestation. CONCLUSION: In low-risk pregnancies, maternal insulin resistance at mid and late but not early pregnancy is significantly associated with fetal adiposity but not with fetal weight. Maternal insulin resistance in mid-gestation could provide a basis for risk identification and interventions that target child adiposity.

Prevalence estimates of the insulin resistance and associated prevalence of heart failure among United Status adults.

BACKGROUND: The triglyceride glucose (TyG) index, a metric for estimating insulin resistance (IR), is linked with cardiovascular disease (CVD) morbidity and mortality among the population regardless of diabetic status. However, IR prevalence and the association between the TyG index and heart failure (HF) in Americans is unclear. METHODS: The Nation Health and Nutrition Examination Survey (NHANES) (2009-2018) dataset was used. IR was defined by homeostatic model assessment of insulin resistance (HOMA-IR) > 2.0 and 1.5. The TyG index was calculated as Ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]. A weighted logistic regression was applied to evaluate the association between the TyG index and the prevalence of HF. RESULTS: This study comprised 12,388 people, including 322 (2.6%) individuals with HF. The average prevalence of IR was found to be 13.9% and 22.7% for cutoff values greater than 2.0 and 1.5, respectively. HOMA-IR and the TyG index showed a moderate correlation (r = 0.30). There is a significant positive association between the TyG index and HF prevalence (per 1-unit increment; adjusted OR [aOR]: 1.34; 95% confidence interval [CI]: 1.02-1.76). Patients with higher TyG values were associated with a prevalence of HF (OR:1.41; 95% CI: 1.01,1.95) (quartiles 4 vs 1-3). The TyG index is associated with a higher prevalence of dyslipidemia, coronary heart disease, and hypertension but not a stroke (cerebrovascular disease). CONCLUSIONS: Our results show that IR does not considerably increase from 2008 to 2018 in American adults. A moderate correlation is noted between HOMA-IR and the TyG index. TyG index is associated with the prevalence of HF, as were other cardiovascular diseases.

Usefulness of SPISE Index for Screening and Detection of Early Stages of Insulin Resistance among Chilean Young Adults.

BACKGROUND: As the gold standard test to quantify insulin resistance (IR) involves intravenous insulin loading and repeated blood glucose monitoring, many indexes have been developed for IR assessment for convenience. OBJECTIVE: The objective of this study was to evaluate the agreement of the Single-Point Insulin Sensitivity Estimator (SPISE) by comparing it with the homeostasis model assessment of insulin resistance (HOMA-IR) in identifying IR. METHOD: Data came from the ongoing LIMACHE BIRTH COHORT. 1,948 individuals (aged 22-28 years) were studied. We performed an agreement plot called a Bangdiwala's Observer Agreement to evaluate patterns in departures from agreement in ordinal categorical variables. RESULTS: According to the Bangdiwala-Weighted statistics, we found that the agreement between both indexes was 0.14; this value would be considered a slight agreement. Thus, we found bias in the marginal distributions, and we noticed that the SPISE has a bias toward the central quintiles of the index. CONCLUSIONS: The identification of IR in young adult individuals by the SPISE index has slight agreement with HOMA-IR. Therefore, caution would be taken when considering SPISE index among young Chilean adults.

Triglyceride-Glucose Index Cutoff Point Is an Accurate Marker for Predicting the Prevalence of Metabolic Syndrome in Obese Caucasian Subjects.

BACKGROUND: Recently, the triglyceride-glucose (TyG) index has been suggested as a surrogate insulin resistance marker. This index could act as an early screening marker in individuals with a high risk of metabolic syndrome (MS) such as obese subjects. AIMS: The objective of this work was to detect the cutoff point of the TyG index for the diagnosis of MS according to ATPIII criteria on obese subjects and to compare with HOMA-IR. METHODS: We conducted a cross-sectional study in 1,494 obese subjects. Measurements of adiposity parameters, blood pressure, fasting blood glucose, insulin concentration, insulin resistance (HOMA-IR), lipid profile, C-reactive protein, adipokines, and the prevalence of MS were determined. The TyG index was calculated from the next equation: Ln (fasting triglycerides (mg/dL) × fasting glucose (mg/dL))/2. RESULTS: A total of 1,494 subjects were recruited, 421 males (28.1%) and 1,073 females (71.8%), with an average age of 45.8 ± 15.3 years (range: 29-62). A total of 677 subjects had MS (45.5%) and 817 did not show MS (54.6%). The averages of HOMA-IR and TyG index values increased as the components of MS were aggregated, and both indexes were higher in subjects with MS. The area under the curve (AUC) of the TyG index according to ATPIII criteria showed values of 0.746 (0.721-0.771; p = 0.001). The cutoff point according to the Youden index was 4.72, with sensitivity and specificity of 87% and 88.2%, respectively. For the HOMA-IR, AUC showed values of 0.682 (0.654-0.710; p = 0.01). The cutoff point was 3.23, with sensitivity and specificity of 78% and 70.1%, respectively. CONCLUSIONS: The TyG index is more powerful for predicting MS than HOMA-IR in Caucasian obese subjects.

Enhancing the Biofidelity of an Upper Cervical Spine Finite Element Model Within the Physiologic Range of Motion and Its Effect on the Full Ligamentous Neck Model Response.

Contemporary finite element (FE) neck models are developed in a neutral posture; however, evaluation of injury risk for out-of-position impacts requires neck model repositioning to non-neutral postures, with much of the motion occurring in the upper cervical spine (UCS). Current neck models demonstrate a limitation in predicting the intervertebral motions within the UCS within the range of motion, while recent studies have highlighted the importance of including the tissue strains resulting from repositioning FE neck models to predict injury risk. In the current study, the ligamentous cervical spine from a contemporary neck model (GHBMC M50 v4.5) was evaluated in flexion, extension, and axial rotation by applying moments from 0 to 1.5 N·m in 0.5 N·m increments, as reported in experimental studies and corresponding to the physiologic loading of the UCS. Enhancements to the UCS model were identified, including the C0-C1 joint-space and alar ligament orientation. Following geometric enhancements, an analysis was undertaken to determine the UCS ligament laxities, using a sensitivity study followed by an optimization study. The ligament laxities were optimized to UCS-level experimental data from the literature. The mean percent difference between UCS model response and experimental data improved from 55% to 23% with enhancements. The enhanced UCS model was integrated with a ligamentous cervical spine (LS) model and assessed with independent experimental data. The mean percent difference between the LS model and the experimental data improved from 46% to 35% with the integration of the enhanced UCS model.

Assessing the performance of QSP models: biology as the driver for validation.

Validation of a quantitative model is a critical step in establishing confidence in the model's suitability for whatever analysis it was designed. While processes for validation are well-established in the statistical sciences, the field of quantitative systems pharmacology (QSP) has taken a more piecemeal approach to defining and demonstrating validation. Although classical statistical methods can be used in a QSP context, proper validation of a mechanistic systems model requires a more nuanced approach to what precisely is being validated, and what role said validation plays in the larger context of the analysis. In this review, we summarize current thoughts of QSP validation in the scientific community, contrast the aims of statistical validation from several contexts (including inference, pharmacometrics analysis, and machine learning) with the challenges faced in QSP analysis, and use examples from published QSP models to define different stages or levels of validation, any of which may be sufficient depending on the context at hand.

Association between C-Reactive Protein and low-grade Inflammation among Nigerian women with Polycystic Ovarian Syndrome.

BACKGROUND: There is evidence of a low-grade chronic inflammation reflected by minor but significant increases in circulating levels of inflammatory mediators in polycystic ovary syndrome (PCOS). There is uncertainty about the causal relationship whether it is obesity, insulin resistance, or PCOS. There is a paucity of studies from the West African subregion. OBJECTIVES: The study investigated C-reactive protein (CRP) concentration in Nigerian women with PCOS, and determined the factors that affect their concentration. METHODS: The study was conducted on 71 Nigerian women with PCOS and 76 normal ovulating women, recruited from the University of Benin Teaching Hospital and the Women's Health and Action Research Centre, in Nigeria. CRP levels were measured by the enzyme-linked immunosorbent assay (ELISA) method. Insulin resistance and insulin sensitivity were estimated using the Homeostatic Model Assessment Index and Quantitative Insulin-sensitivity Check Index respectively. RESULTS: The CRP levels were significantly elevated in Nigerian women with PCOS compared to controls (9.93 ± 8.38 vs 5.54 ± 5.93 mg/L; p=0.000). It positively correlated with age (r = 0.297, p = 0.012), Weight (r =0.313, p = 0.008) and BMI (r = 0.339, p = 0.004). Multiple linear regression analysis revealed that CRP values are positively associated with BMI (ß = 0.274, p = 0.001) and PCOS (ß = 0.382, p = 0.001). The CRP values were positively associated with BMI (ß = 0.372, p = 0.012) and negatively associated with QUICKI (ß = -0.644, p = 0.073). CONCLUSIONS: Among Nigerian women with PCOS, inflammation may be mediated through adiposity since the main predicting factor for increased CRP is BMI.

CONTEXTE: Il existe des preuves d'une inflammation chronique de faible intensité, se manifestant par des augmentations mineures mais significatives des taux circulants de médiateurs inflammatoires, dans le syndrome des ovaires polykystiques (SOPK). Il existe une incertitude quant à la relation causale, qu'il s'agisse de l'obésité, de la résistance à l'insuline ou du SOPK. Les études de cette région d'Afrique de l'Ouest sont rares. OBJECTIFS: L'étude a examiné la concentration de la protéine C-réactive (CRP) chez les femmes nigérianes atteintes du SOPK et a déterminé les facteurs qui influent sur leur concentration. MÉTHODES: L'étude a été menée auprès de 71 femmes nigérianes atteintes du SOPK et de 76 femmes à ovulation normale, recrutées à l'hôpital universitaire de Benin et au Centre de recherche sur la santé des femmes et l'action (Women's Health and Action Research Centre) au Nigéria. Les niveaux de CRP ont été mesurés à l'aide de laméthode ELISA (dosage immuno-enzymatique). La résistance à l'insuline et la sensibilité à l'insuline ont été estimées à l'aide de l'indice du modèle homéostatique d'évaluation et de l'indice de vérification quantitative de la sensibilité à l'insuline. RÉSULTATS: Les taux de CRP étaient significativement élevés chez les femmes nigérianes atteintes du SOPK par rapport aux témoins (9,93 ± 8,38 contre 5,54 ± 5,93 mg/L ; p = 0,000). Ils étaient positivement corrélés à l'âge (r = 0,297, p = 0,012), au poids (r = 0,313, p = 0,008) et à l'IMC (r = 0,339, p = 0,004). L'analyse de régression linéaire multiple a révélé que les valeurs de la CRP sont positivement associées à l'IMC (ß = 0,274, p = 0,001) et au SOPK (ß = 0,382, p = 0,001). Les valeurs de la CRP étaient positivement associées à l'IMC (ß = 0,372, p = 0,012) et négativement associées au QUICKI (ß = -0,644, p = 0,073). CONCLUSIONS: Chez les femmes nigérianes atteintes du SOPK, l'inflammation pourrait être médiée par l'adiposité, car le principal facteur prédictif d'une augmentation de la CRPest l'IMC. Mots-clés: Protéine C-réactive, inflammation chronique, syndrome des ovaires polykystiques, indice de vérification quantitative de la sensibilité à l'insuline, indice du modèle homéostatique d'évaluation.

Growth hormone treatment does not to lead to insulin resistance nor excessive rise in IGF-1 levels, while improving height in patients small for gestational age A long-term observational study.

OBJECTIVE: In children born small for gestational age (SGA), the relationship between growth hormone (GH) treatment and insulin resistance (IR) has only been investigated for a short period, necessitating a longer observation period. This study aimed to evaluate the long-term (10 years) effect of GH to SGA-children on IR and safety during treatment. DESIGN: This was a multicenter observational study. PATIENTS: SGA-children who received GH treatment in Spain (stratified by Tanner-stage and age at GH onset [two groups: ≤6 years old or >6 years old]). MEASUREMENTS: The analysed variables (yearly measures) included auxologic, metabolic (insulin-like growth factor-1 (IGF-1), height velocity [HV], weight and homeostatic model assessment-IR [HOMA-IR]) and safety data. Data were collected prospectively (since the study approval: 2007) and retrospectively (since the initiation of GH treatment: 2005-2007). RESULTS: A total of 389 SGA children (369 Tanner-I) were recruited from 27 centres. The mean age (standard deviation) of the children at GH treatment onset was 7.2 (2.8) years old. IGF-1 (standard deviation score [SDS]) and HOMA-IR values tended to increase until the sixth year of GH-treatment, with significant differences being observed only during the first year, while these remained stable in the later years (within normal ranges). Height (SDS) increased significantly (basal: -3.0; tenth year: -1.13), and the maximum HV (SDS) occurred during the first year (2.75 ± 2.39). CONCLUSIONS: HOMA-IR values increased significantly in SGA-children during the first year of GH-treatment, remained stable and were within normal ranges in all cases. Our 10-year data suggests that long-term GH treatment does not promote IR and is well-tolerated, safe and effective.

Effect of acupuncture and metformin on insulin sensitivity in women with polycystic ovary syndrome and insulin resistance: a three-armed randomized controlled trial.

STUDY QUESTION: Does acupuncture improve insulin sensitivity more effectively than metformin or sham acupuncture in women with polycystic ovary syndrome (PCOS) and insulin resistance (IR)? SUMMARY ANSWER: Among women with PCOS and IR, acupuncture was not more effective than metformin or sham acupuncture in improving insulin sensitivity. WHAT IS KNOWN ALREADY: Uncontrolled trials have shown that acupuncture improved insulin sensitivity with fewer side effects compared with metformin in women with PCOS and IR. However, data from randomized trials between acupuncture and metformin or sham acupuncture are lacking. STUDY DESIGN, SIZE, DURATION: This was a three-armed randomized controlled trial enrolling a total of 342 women with PCOS and IR from three hospitals between November 2015 and February 2018, with a 3-month follow-up until October 2018. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women aged from 18 to 40 years with PCOS and homeostasis model assessment of insulin resistance (HOMA-IR) ≥2.14 were randomly assigned (n = 114 per group) to receive true acupuncture plus placebo (true acupuncture), metformin plus sham acupuncture (metformin, 0.5 g three times daily) or sham acupuncture plus placebo (sham acupuncture) for 4 months, with an additional 3-month follow-up. True or sham acupuncture was given three times per week, and 0.5 g metformin or placebo was given three times daily. The primary outcome was change in HOMA-IR from baseline to 4 months after baseline visit. Secondary outcomes included changes in the glucose AUC during an oral glucose tolerance test, BMI and side effects at 4 months after baseline visit. MAIN RESULTS AND THE ROLE OF CHANCE: After 4 months of treatment, the changes of HOMA-IR were -0.5 (decreased 14.7%) in the true acupuncture group, -1.0 (decreased 25.0%) in the metformin group and -0.3 (decreased 8.6%) in the sham acupuncture group, when compared with baseline. True acupuncture is not as effective as metformin in improving HOMA-IR at 4 months after baseline visit (difference, 0.6; 95% CI, 0.1-1.1). No significant difference was found in change in HOMA-IR between true and sham acupuncture groups at 4 months after baseline visit (difference, -0.2; 95% CI, -0.7 to 0.3). During the 4 months of treatment, gastrointestinal side effects were more frequent in the metformin group, including diarrhea, nausea, loss of appetite, fatigue, vomiting and stomach discomfort (31.6%, 13.2%, 11.4%, 8.8%, 14.0% and 8.8%, respectively). Bruising was more common in the true acupuncture group (14.9%). LIMITATIONS, REASONS FOR CAUTION: This study might have underestimated the sample size in the true acupuncture group with 4 months of treatment to enable detection of statistically significant changes in HOMA-IR with fixed acupuncture (i.e. a non-personalized protocol). Participants who withdrew because of pregnancy did not have further blood tests and this can introduce bias. WIDER IMPLICATIONS OF THE FINDINGS: True acupuncture did not improve insulin sensitivity as effectively as metformin in women with PCOS and IR, but it is better than metformin in improving glucose metabolism (which might reduce the risk of type 2 diabetes) and has less side effects. Metformin had a higher incidence of gastrointestinal adverse effects than acupuncture groups, and thus acupuncture might be a non-pharmacological treatment with low risk for women with PCOS. Further studies are needed to evaluate the effect of acupuncture combined with metformin on insulin sensitivity in these women. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by grants 2017A020213004 and 2014A020221060 from the Science and Technology Planning Project of Guangdong Province. The authors have no conflicts of interest. TRIAL REGISTRATION NUMBER: Clinicaltrials.gov number: NCT02491333. TRIAL REGISTRATION DATE: 8 July 2015. DATE OF FIRST PATIENT'S ENROLLMENT: 11 November 2015.

Evaluating Triglyceride and Glucose Index as a Simple and Easy-to-Calculate Marker for All-Cause and Cardiovascular Mortality.

OBJECTIVE: The triglyceride and glucose (TyG) index is a useful marker of insulin resistance and is a predictor of several metabolic diseases. The aim of this study was to evaluate the association between the TyG index and all-cause or cardiovascular mortality using a large population-based cohort study database. METHODS: A total of 255,508 subjects in the Kangbuk Samsung Health Study cohort were enrolled. Cox proportional hazards models were used to analyze the risk of mortality. RESULTS: During a median 5.7-year follow-up, the cumulative all-cause and cardiovascular mortality was 0.47% and 0.07%. There was a nonlinear relationship between the TyG index and death, and moving from moderate to high, the TyG index levels were associated with an increase in the risk of death. The hazard ratio (HR) for all-cause and cardiovascular mortality of the TyG index was 1.21 [95% confidence interval (CI) 1.14-1.28] and 1.45 (95% CI 1.26-1.66) in the unadjusted model, respectively. After adjustment for covariates, the association between the TyG index and all-cause and cardiovascular mortality was attenuated. In the multivariable-adjusted model, the TyG index was associated with an elevated risk of all-cause mortality in women (HR 1.13, 95% CI 1.02-1.26) and a decreased risk in men (HR 0.92, 95% CI 0.85-0.99). The association between cardiovascular mortality and the TyG index was not statistically significant among either men or women in the multivariable-adjusted model. CONCLUSIONS: The TyG index in a young, relatively healthy, population is associated with an elevated risk of all-cause and cardiovascular mortality. This association between the TyG index and all-cause mortality persists in women after multivariable adjustment.

Bayesian criterion-based assessments of recurrent event models with applications to commercial truck driver behavior studies.

Multitype recurrent events are commonly observed in transportation studies, since commercial truck drivers may encounter different types of safety critical events (SCEs) and take different lengths of on-duty breaks in a driving shift. Bayesian nonhomogeneous Poisson process models are a flexible approach to jointly model the intensity functions of the multitype recurrent events. For evaluating and comparing these models, the deviance information criterion (DIC) and the logarithm of the pseudo-marginal likelihood (LPML) are studied and Monte Carlo methods are developed for computing these model assessment measures. We also propose a set of new concordance indices (C-indices) to evaluate various discrimination abilities of a Bayesian multitype recurrent event model. Specifically, the within-event C-index quantifies adequacy of a given model in fitting the recurrent event data for each type, the between-event C-index provides an assessment of the model fit between two types of recurrent events, and the overall C-index measures the model's discrimination ability among multiple types of recurrent events simultaneously. Moreover, we jointly model the incidence of SCEs and on-duty breaks with driving behaviors using a Bayesian Poisson process model with time-varying coefficients and time-dependent covariates. An in-depth analysis of a real dataset from the commercial truck driver naturalistic driving study is carried out to demonstrate the usefulness and applicability of the proposed methodology.