Distribution of autoantibodies to insulinoma-associated antigen-2 and zinc transporter 8 in type 1 diabetes and latent autoimmune diabetes: A nationwide, multicentre, cross-sectional study

AIMS

This study investigated insulinoma-associated-2 autoantibody (IA-2A) and zinc transporter 8 autoantibody (ZnT8A) distribution in patients with type 1 diabetes (T1D) and latent autoimmune diabetes (LAD) and the autoantibodies' association with clinical characteristics and HLA-DR-DQ genes.

MATERIALS AND METHODS

This cross-sectional study recruited 17,536 patients with diabetes from 46 hospitals across China. A total of 189 patients with T1D and 58 patients with LAD with IA-2A positivity, 126 patients with T1D and 86 patients with LAD with ZnT8A positivity, and 231 patients with type 2 diabetes (T2D) were selected to evaluate islet autoantibodies, clinical phenotypes, and HLA-DR-DQ gene frequency.

RESULTS

IA-2A was bimodally distributed in patients with T1D and LAD. Patients with low IA-2A titre LAD had lower fasting C-peptide (FCP) (p < 0.01), lower postprandial C-peptide (PCP) (p < 0.001), and higher haemoglobin A1c (HbA1c) levels (p < 0.05) than patients with T2D. Patients with high IA-2A titre LAD were younger than patients with low IA-2A titre LAD (p < 0.05). Patients with low IA-2A titre T1D had lower FCP (p < 0.01), lower PCP (p < 0.01), and higher HbA1c levels (p < 0.05) than patients with high IA-2A titre LAD. HLA-DR-DQ genetic analysis demonstrated that the frequency of susceptible HLA haplotypes was higher in IA-2A-positive patients (p < 0.001) than in patients with T2D. Patients with high ZnT8A titre LAD had lower FCP (p = 0.045), lower PCP (p = 0.023), and higher HbA1c levels (p = 0.009) and a higher frequency of total susceptible haplotypes (p < 0.001) than patients with low ZnT8A titre LAD.

CONCLUSIONS

IA-2A in patients with T1D and LAD was bimodally distributed, and the presence of IA-2A could demonstrate partial LAD clinical characteristics. ZnT8A titre had a certain predictive value for islet functions in patients with LAD.

Particle Size Inversion Constrained by L∞ Norm for Dynamic Light Scattering

Particle size inversion of dynamic light scattering (DLS) is a typically ill-posed problem. Regularization is an effective method to solve the problem. The regularization involves imposing constraints on the fitted autocorrelation function data by adding a norm. The classical regularization inversion for DLS data is constrained by the L₂ norm. In the optimization equation, the norm determines the smoothness and stability of the inversion result, affecting the inversion accuracy. In this paper, the L_p norm regularization model is constructed. When p is 1, 2, 10, 50, 100, 1000, and ∞, respectively, the influence of their norm models on the inversion results of data with different noise levels is studied. The results prove that overall, the inversion distribution errors show a downward trend with the increase of p. When p is larger than 10, there is no significant difference in distribution error. Compared with L₂, L_∞ can provide better performance for unimodal particles with strong noise, although this does not occur in weak noise cases. Meanwhile, L_∞ has lower sensitivity to noise and better peak resolution, and its inverse particle size distribution is closer to the true distribution for bimodal particles. Thus, L_∞ is more suitable for the inversion of DLS data.

Would foot arch development in children characterize a body maturation process? a prospective longitudinal study

BACKGROUND

Flatfoot (Pes Planus), often regarded as a physiological deviation in children, is of concern to parents because there is no test to predict the development of foot arch. This study aimed to use a new diagnostic flatfoot criterion to determine 1) how the footprint index changes during the development of foot arches, 2) what factors can predict a foot arch development, and 3) whether foot arch development could be a process of body growth.

MATERIALS AND METHODS

572 children were enrolled in a prospective longitudinal study of anthropometrical parameters and physical fitness twice at age of 6.7 and 8.2 years. The bimodal frequency distribution of the Chippaux-Smirak index (CSI) of the footprint was used to define flatfoot as CSI <0.58 and non-flatfoot as CSI >0.61. Body measurements and physical fitness tests were compared between children with flatfeet who developed foot arches and children who did not.

RESULTS

Of 263 children with flatfeet, the CSI significantly changed from 0.72 to 0.46 in 70 children who developed foot arches over 1.5 years and the others had minimal change in the index. Children with foot arch development had a lower initial CSI, improved boys' performance in one-leg balance, and less increase in girls' body height than children who remained flatfooted, whereas sex and weight were similar in both groups.

CONCLUSION

This longitudinal study with the bimodal distribution of the CSI investigated how the development of foot arch advances in children around age 7. A significant and unique pattern in change of the CSI suggests involvement of a maturational stage in foot arch development. Along with the improved performance in one-leg balance, the unidirectional transition from flatfoot to non-flatfoot is associated with improvement in motor control of the ankle.

Copula modeling of receiver operating characteristic and predictiveness curves

Receiver operating characteristic (ROC) and predictiveness curves are graphical tools to study the discriminative and predictive power of a continuous-valued marker in a binary outcome. In this paper, a copula-based construction of the joint density of the marker and the outcome is developed for plotting and analyzing both curves. The methodology only requires a copula function, the marginal distribution of the marker, and the prevalence rate for the model to be characterized. The adoption of the Gaussian copula and the customization of the margin for the marker are proposed for such characterization. The computation of both curves is numerically more feasible than methods that attempt to obtain one curve in terms of the other. Estimation is carried out using maximum likelihood and resampling-based methods. Randomized quantile residuals from each conditional distribution are employed for both assessing the adequacy of the model and identifying outliers. The performance of the estimators of both curves and their underlying quantities is evaluated in simulation studies that assume different dependence structures and sample sizes. The methods are illustrated with an analysis of the level of progesterone receptor gene expression for the diagnosis and prediction of estrogen receptor-positive breast cancer.

Conditions of the Presence of Bimodal Amplitude Distribution of Two-Process Surfaces

Two-process surfaces are functionally important. They contain plateau and valley parts. They are created by superimpositions of two one-process textures of Gaussian probability height distributions. It is expected that the resulting two-process surface would have bimodal height probability distribution. However, typically two-process textures have unimodal ordinate distribution. The present authors developed limiting conditions of presence of bimodal ordinate distribution. These conditions depend on the material ratio at the plateau-to-valley transition (the Smq parameter), and on the ratio of heights of the plateau and valley surface parts (Spq/Svq). Generated stratified textures and measured two-process surfaces of cylinder liners were taken into consideration.

Weighted Quantile Regression Forests for Bimodal Distribution Modeling: A Loss Given Default Case

Due to various regulations (e.g., the Basel III Accord), banks need to keep a specified amount of capital to reduce the impact of their insolvency. This equity can be calculated using, e.g., the Internal Rating Approach, enabling institutions to develop their own statistical models. In this regard, one of the most important parameters is the loss given default, whose correct estimation may lead to a healthier and riskless allocation of the capital. Unfortunately, since the loss given default distribution is a bimodal application of the modeling methods (e.g., ordinary least squares or regression trees), aiming at predicting the mean value is not enough. Bimodality means that a distribution has two modes and has a large proportion of observations with large distances from the middle of the distribution; therefore, to overcome this fact, more advanced methods are required. To this end, to model the entire loss given default distribution, in this article we present the weighted quantile Regression Forest algorithm, which is an ensemble technique. We evaluate our methodology over a dataset collected by one of the biggest Polish banks. Through our research, we show that weighted quantile Regression Forests outperform “single” state-of-the-art models in terms of their accuracy and the stability.

Stationary moments, distribution conjugation and phenotypic regions in stochastic gene transcription

Transcription is a pivotal step in gene expression yet a complex biochemical process. It occurs often in a bursty manner, leading to cell-to-cell variability important for the cells surviving in complex environments. Quantitative experiments of such stochastic transcription call for model analysis in a systematic rather than case-by-case fashion. Here we analyze two general yet biologically-reasonable classes of stochastic transcription models: the first class called promoter models considers that promoter structure is general, and the second class called queuing models considers that waiting-time distributions are general. For the former, we show that there are conjugate relationships between models with different transcription exits. This property well reveals the mechanic principle of stochastic transcription in complex cases of transcription factor regulation. For the latter, we establish an integral equation for the mRNA moment-generating function, through which stationary mRNA moments of any orders can be analytically derived. Finally, we analyze parametric regions for robust unimodality and bimodality. The overall analysis not only lays a foundation for quantitative analysis of stochastic transcription but also reveals how the upstream promoter kinetics impact the downstream expression dynamics.

Growth model interpretation of planet size distribution

The radii and orbital periods of 4,000+ confirmed/candidate exoplanets have been precisely measured by the Kepler mission. The radii show a bimodal distribution, with two peaks corresponding to smaller planets (likely rocky) and larger intermediate-size planets, respectively. While only the masses of the planets orbiting the brightest stars can be determined by ground-based spectroscopic observations, these observations allow calculation of their average densities placing constraints on the bulk compositions and internal structures. However, an important question about the composition of planets ranging from 2 to 4 Earth radii (R⊕) still remains. They may either have a rocky core enveloped in a H2-He gaseous envelope (gas dwarfs) or contain a significant amount of multicomponent, H2O-dominated ices/fluids (water worlds). Planets in the mass range of 10-15 M⊕, if half-ice and half-rock by mass, have radii of 2.5 R⊕, which exactly match the second peak of the exoplanet radius bimodal distribution. Any planet in the 2- to 4-R⊕ range requires a gas envelope of at most a few mass percentage points, regardless of the core composition. To resolve the ambiguity of internal compositions, we use a growth model and conduct Monte Carlo simulations to demonstrate that many intermediate-size planets are "water worlds."

pH Switchable Nanoassembly for Imaging a Broad Range of Malignant Tumors

Polymer-based fluorescent nanomaterials have proven to universally image various tumors based on their extremely sharp responsiveness to pH change. Such a property has never been realized in supramolecular systems. We herein design a small molecule (DPP-thiophene-4) that is composed of a diketopyrrolopyrrole (DPP) core and two alkyl chains terminated with quaternary ammonium. DPP-thiophene-4 can self-assemble into a nonfluorescent nanoassembly when the pH is >7.0 but reversibly disassembles back to fluorescent monomers when the pH is <6.8. Meanwhile, its fluorescence emission increases by 10-fold within a 0.2 pH unit change. Such a fluorogenic nanoassembly can precisely differentiate a number of malignant tumors among normal tissues in vivo due to the slight acidity within tumor microenvironments. Further the nanoassembly shows satisfactory biocompatibility and an effective clearance from the body. Overall, this supramolecular fluorogenic nanoassembly exhibits an immense potential for realizing broad range tumor diagnosis.

Impact of Prolonged Absence of Low Temperature on Adult Eclosion Patterns of Western Cherry Fruit Fly (Diptera: Tephritidae)

Western cherry fruit fly, Rhagoletis indifferens (Curran) (Diptera: Tephritidae), is a serious pest of cherries (Prunus spp.) in the Pacific Northwest of the United States. Previous research suggests that R. indifferens is unlikely to establish in commercial cherry production areas in California and in tropical export markets because cold temperatures, below 5 °C, in those regions appear insufficient to complete diapause. However, it is unclear how prolonged absence of cold exposure affects diapause termination in R. indifferens. Here, we examined this question by exposing R. indifferens pupae for 40 wk to simulated temperate and tropical conditions of 23 or 26 °C, 40 or 80% RH, and a photoperiod of 16:8 or 12:12 (L:D) h. Eclosion patterns among fly groups in the four conditions did not differ. For all groups, fly eclosion from pupae not exposed to cold exhibited a bimodal distribution. The first major peak, comprising 3.2% of the total fly emergence, occurred at 1-10 wk. The second major peak, comprising the remaining 96.8%, occurred at a mode of ∼30 wk. Based on responses to no cold and cold (3 ± 1.5 °C) exposures, there were three distinct pupal diapause groups: the first eclosion group was likely nondiapausing pupae; the second eclosion group was likely diapausing pupae; a third group that remained viable but did not produce adults after 40 wk may represent prolonged dormancy pupae. We suggest that eclosion of adults after prolonged absence of cold exposure needs to be incorporated into models for potential fly establishment in warm climates.