844 research outputs found
An importance sampling algorithm for generating exact eigenstates of the nuclear Hamiltonian
We endow a recently devised algorithm for generating exact eigensolutions of
large matrices with an importance sampling, which is in control of the extent
and accuracy of the truncation of their dimensions. We made several tests on
typical nuclei using a correlated basis obtained from partitioning the shell
model space. The sampling so implemented allows not only for a substantial
reduction of the shell model space but also for an extrapolation to exact
eigenvalues and E2 strengths.Comment: A compressed file composed of a text in latex of 19 pages and 9
figures in p
Plasma kisspeptin levels are associated with insulin secretion in nondiabetic individuals
To evaluate if plasma kisspeptin concentrations are associated with insulin secretion, as suggested by recent in vitro studies, independently of confounders. 261 nondiabetic subjects were stratified into tertiles according to kisspeptin values. Insulin secretion was assessed using indexes derived from oral glucose tolerance test (OGTT). After adjusting for age, gender, and BMI, subjects in the highest (tertile 3) kisspeptin group exhibited significantly lower values of insulinogenic index, corrected insulin response (CIR30), and Stumvoll indexes for first-phase and second-phase insulin release as compared with low (tertile 1) or intermediate (tertile 2) kisspeptin groups. Univariate correlations between kisspeptin concentration and metabolic variables showed that kisspeptin concentration was significantly and positively correlated with age, blood pressure, and 2-h post-load glucose, and inversely correlated with BMI, and waist circumference. There was an inverse relationship between kisspeptin levels and OGTT-derived indexes of glucose-stimulated insulin secretion. A multivariable regression analysis in a model including all the variables significantly correlated with kisspeptin concentration showed thar age (β = -0.338, P<0.0001), BMI (β = 0.272, P<0.0001), 2-h post-load glucose (β = -0.229, P<0.0001), and kisspeptin (β = -0.105, P = 0.03) remained associated with insulinogenic index. These factors explained 34.6% of the variance of the insulinogenic index. In conclusion, kisspeptin concentrations are associated with insulin secretion independently of important determinants of glucose homeostasis such as gender, age, adiposity, 2-h post-load glucose, and insulin sensitivity
Elevated hemoglobin glycation index identify non-diabetic individuals at increased risk of kidney dysfunction
Hemoglobin glycation index (HGI), calculated as the difference between the observed value of HbA1 and the predicted HbA1c based on plasma glucose concentration, is a measure of the individual tendency toward non-enzymatic hemoglobin glycation which has been found to be positively associated with nephropathy in subjects with diabetes. In this cross-sectional study we aimed to evaluate whether higher HGI levels are associated with impaired kidney function also among nondiabetic individuals. The study group comprised 1505 White nondiabetic individuals stratified in quartiles according to HGI levels. Estimated glomerular filtration rate (eGFR) was calculated by using the MDRD equation. Individuals in the intermediate and high HGI groups exhibited a worse metabolic phenotype with increased levels of visceral obesity, total cholesterol, triglycerides, inflammatory biomarkers such as hsCRP and white blood cells count and lower values of HDL and insulin sensitivity assessed by Matsuda index in comparison to the lowest quartile of HGI. Subjects in the intermediate and high HGI groups displayed a graded decrease of eGFR levels in comparison with the lowest quartile of HGI. In a logistic regression analysis individuals in the highest quartile of HGI exhibited a significantly 3.6-fold increased risk of having chronic kidney disease (95% CI: 1.13-11.24, P = 0.03) and a significantly 1.6-fold increased risk of having a mildly reduced kidney function (95% CI: 1.19-2.28, P = 0.003) in comparison to individuals in the lowest HGI group. In conclusion HGI may be a useful tool to identify nondiabetic individuals with an increased risk of having kidney dysfunction
Insulin-like growth factor-1 is a negative modulator of glucagon secretion
Glucagon secretion involves a combination of paracrine, autocrine, hormonal, and autonomic neural mechanisms. Type 2 diabetes often presents impaired glucagon suppression by insulin and glucose. Insulin-like growth factor-I (IGF-1) has elevated homology with insulin, and regulates pancreatic β-cells insulin secretion. Insulin and IGF-1 receptors share considerable structure homology and function. We hypothesized the existence of a mechanism linking the inhibition of α-cells glucagon secretion to IGF-1. Herein, we evaluated the association between plasma IGF-1 and glucagon levels in 116 nondiabetic adults. After adjusting for age gender and BMI, fasting glucagon levels were positively correlated with 2-h post-load glycaemia, HOMA index and fasting insulin, and were negatively correlated with IGF-1 levels. In a multivariable regression, the variables independently associated to fasting glucagon were circulating IGF-1 levels, HOMA index and BMI, explaining 20.7% variation. To unravel the molecular mechanisms beneath IGF-1 and glucagon association, we investigated whether IGF-1 directly modulates glucagon expression and secretion in an in vitro model of α-cells. Our data showed that IGF-1 inhibits the ability of low glucose concentration to stimulate glucagon expression and secretion via activation of the phosphatidylinositol-3-kinase/Akt/FoxO1 pathway. Collectively, our results suggest a new regulatory role of IGF-1 on α-cells biological function
Reciprocal Association of Plasma IGF-1 and Interleukin-6 Levels With Cardiometabolic Risk Factors in Nondiabetic Subjects
OBJECTIVE—To examine the relationship between plasma IGF-1 and interleukin-6 (IL-6) levels in Caucasian nondiabetic subjects and evaluate the association of IGF-1 and IL-6 with the cardiometabolic risk factors characterizing metabolic syndrome (MetS)
Solution of large scale nuclear structure problems by wave function factorization
Low-lying shell model states may be approximated accurately by a sum over
products of proton and neutron states. The optimal factors are determined by a
variational principle and result from the solution of rather low-dimensional
eigenvalue problems. Application of this method to sd-shell nuclei, pf-shell
nuclei, and to no-core shell model problems shows that very accurate
approximations to the exact solutions may be obtained. Their energies, quantum
numbers and overlaps with exact eigenstates converge exponentially fast as the
number of retained factors is increased.Comment: 12 pages, 12 figures (from 15 eps files) include
A Novel Broadband Forcecardiography Sensor for Simultaneous Monitoring of Respiration, Infrasonic Cardiac Vibrations and Heart Sounds
The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High-Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients
Association between serum Mg2+ concentrations and cardiovascular organ damage in a cohort of adult subjects
Magnesium (Mg2+) levels are associated with insulin resistance, hypertension, atherosclerosis, and type 2 diabetes (T2DM). We evaluated the clinical utility of physiological Mg2+ in assessing subclinical cardiovascular organ damage including increased carotid artery intima-media thickness (c-IMT) and left ventricular mass index (LVMI) in a cohort of well-characterized adult non-diabetic individuals. Age-and gender-adjusted correlations between Mg2+ and metabolic parameters showed that Mg2+ circulating levels were correlated negatively with body mass index (BMI), fasting glucose, and 2h-oral glucose tolerance test (OGTT) glucose. Similarly, Mg2+ levels were significantly and negatively related to c-IMT and LVMI. A multivariate regression analysis revealed that age (β = 0.440; p < 0.0001), BMI (β = 0.225; p < 0.0001), and Mg2+ concentration (β = −0.122; p < 0.01) were independently associated with c-IMT. Age (β = 0.244; p = 0.012), Mg2+ (β = −0.177; p = 0.019), and diastolic blood pressure (β = 0.184; p = 0.038) were significantly associated with LVMI in women, while age (β = 0.211; p = 0.019), Mg2+ (β = −0.171; p = 0.038) and the homeostasis model assessment index of insulin resistance (HOMA-IR) (β = −0.211; p = 0.041) were the sole variables associated with LVMI in men. In conclusion, our data support the hypothesis that the assessment of Mg2+ as part of the initial work-up might help unravel the presence of subclinical organ damage in subjects at increased risk of cardiovascular complications
Serum IgG2 levels are specifically associated with whole-body insulin-mediated glucose disposal in non-diabetic offspring of type 2 diabetic individuals. a cross-sectional study
.Preclinical studies suggested that IgG2c isotype may specifically impair skeletal muscle insulin
sensitivity in mice. In this study we investigated the association between serum levels of the four IgG
subclasses and insulin sensitivity in non-diabetic individuals. Total IgG, IgG1, IgG2, IgG3 and IgG4
levels were measured in 262 subjects. Whole-body insulin sensitivity was assessed by euglycemic
hyperinsulinemic clamp. IgG2 levels were positively correlated with BMI, waist circumference, 2-h postload
glucose levels and complement C3. Serum IgG2, but not IgG1, IgG3 and IgG4 levels were negatively
correlated with whole-body insulin sensitivity (r = −0.17; P = 0.003) and muscle insulin sensitivity index
(r = −0.16; P = 0.03) after adjustment for age and gender. No significant correlation was found between
IgG2 levels and hepatic insulin resistance assessed by HOMA-IR and liver IR index. In a multivariable
regression analysis including variables known to affect insulin sensitivity such as age, gender, BMI,
smoking, lipids, inflammatory markers, fasting and 2-h post-load glucose levels, IgG2 levels were
independently associated with insulin-stimulated glucose disposal (β = −0.115, 95% CI: −0.541 to
−0.024; P = 0.03). These data demonstrate the independent association between higher levels of IgG2
and decreased whole-body insulin sensitivity, thus confirming in humans the animal-based evidence
indicating the pathogenic role of IgG2 in insulin resistance
Complete breakdown of the Debye model of rotational relaxation near the isotropic-nematic phase boundary: Effects of intermolecular correlations in orientational dynamics
The Debye-Stokes-Einstein (DSE) model of rotational diffusion predicts that
the rotational correlation times vary as , where
is the rank of the orientational correlation function (given in terms of the
Legendre polynomial of rank ). One often finds significant deviation from
this prediction, in either direction. In supercooled molecular liquids where
the ratio falls considerably below three (the Debye limit),
one usually invokes a jump diffusion model to explain the approach of the ratio
to unity. Here we show in a computer simulation study of a
standard model system for thermotropic liquid crystals that this ratio becomes
much less than unity as the isotropic-nematic phase boundary is approached from
the isotropic side. Simultaneously, the ratio (where is
the shear viscosity of the liquid) becomes {\it much larger} than hydrodynamic
value near the I-N transition. We have also analyzed the break down of the
Debye model of rotational diffusion in ratios of higher order rotational
correlation times. We show that the break down of the DSE model is due to the
growth of orientational pair correlation and provide a mode coupling theory
analysis to explain the results.Comment: Submitted to Physical Review
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