Prevalence and Risk Factors for Diabetic Peripheral Neuropathy in Type 2 Diabetic Patients From 14 Countries: Estimates of the INTERPRET-DD Study

Aim: Diabetic peripheral neuropathy (DPN) is a common, severe microvascular complication of diabetes. Our study was to assess prevalence and risk factors for DPN in subjects with type 2 diabetes from 14 different countries. Methods: A total of 2,733 subjects with type 2 diabetes aged 18–65 years (45.3% men, mean duration of diabetes = 8.8 years) were included to perform this International Prevalence and Treatment of Diabetes and Depression (INTERPRET-DD) study in 14 countries. After a structured questionnaire was used in face-to-face interviews to collect sociodemographic characteristics and medical records of the participating subjects, laboratory tests were carried out for clinical measurement. Depressive symptoms were diagnosed and measured using the Patient Health Questionnaire-9. The potential risk factors for DPN were determined by multilevel mixed-effects logistic regression, accounting for clustering of participants within the country. Robustness of the estimates was assessed by sensitivity analysis. Results: The overall prevalence of DPN across different countries was 26.71%, whereas country-specific prevalences showed considerable variation. Multivariate analysis revealed that duration of diabetes (OR: 1.08 per 1-year increase, 95% CI: 1.06–1.09), poor glycemic control (OR: 1.11 per 1% increase in HbA1c, 95% CI: 1.05–1.18), and history of hypertension (OR: 1.58, 95% CI: 1.18–2.12), cardiovascular disease (OR: 2.07, 95% CI: 1.55–2.78) and depressive symptoms (OR: 1.92, 95% CI: 1.43–2.58) were independently and positively associated with the risk of DPN. Sensitivity analyses including or excluding patients from countries with extreme low or high prevalence of DPN yielded similar estimates in terms of trend and magnitude. Conclusions: This international study illustrates that more than a quarter of individuals with type 2 diabetes developed DPN. The prevalence was positively associated with the duration of diabetes, poor glycemic control, and history of hypertension, cardiovascular disease and depressive symptoms

Feature Weight Driven Interactive Mutual Information Modeling for Heterogeneous Bio-Signal Fusion to Estimate Mental Workload

Many people suffer from high mental workload which may threaten human health and cause serious accidents. Mental workload estimation is especially important for particular people such as pilots, soldiers, crew and surgeons to guarantee the safety and security. Different physiological signals have been used to estimate mental workload based on the n-back task which is capable of inducing different mental workload levels. This paper explores a feature weight driven signal fusion method and proposes interactive mutual information modeling (IMIM) to increase the mental workload classification accuracy. We used EEG and ECG signals to validate the effectiveness of the proposed method for heterogeneous bio-signal fusion. The experiment of mental workload estimation consisted of signal recording, artifact removal, feature extraction, feature weight calculation, and classification. Ten subjects were invited to take part in easy, medium and hard tasks for the collection of EEG and ECG signals in different mental workload levels. Therefore, heterogeneous physiological signals of different mental workload states were available for classification. Experiments reveal that ECG can be utilized as a supplement of EEG to optimize the fusion model and improve mental workload estimation. Classification results show that the proposed bio-signal fusion method IMIM can increase the classification accuracy in both feature level and classifier level fusion. This study indicates that multi-modal signal fusion is promising to identify the mental workload levels and the fusion strategy has potential application of mental workload estimation in cognitive activities during daily life

Photon penetration depth in human brain for light stimulation and treatment: A realistic Monte Carlo simulation study

Light has been clinically utilized as a stimulation in medical treatment, such as Low-level laser therapy and photodynamic therapy, which has been more and more widely accepted in public. The penetration depth of the treatment light is important for precision treatment and safety control. The issue of light penetration has been highlighted in biomedical optics field for decades. However, quantitative research is sparse and even there are conflicts of view on the capability of near-infrared light penetration into brain tissue. This study attempts to quantitatively revisit this issue by innovative high-realistic 3D Monte Carlo modeling of stimulated light penetration within high-precision Visible Chinese human head. The properties of light, such as its wavelength, illumination profile and size are concern in this study. We made straightforward and quantitative comparisons among the effects by the light properties (i.e., wavelengths: 660, 810 and 980nm; beam types: Gaussian and flat beam; beam diameters: 0, 2, 4 and 6cm) which are in the range of light treatment. The findings include about 3% of light dosage within brain tissue; the combination of Gaussian beam and 810nm light make the maximum light penetration (>5cm), which allows light to cross through gray matter into white mater. This study offered us, the first time as we know, quantitative guide for light stimulation parameter optimization in medical treatment

The Detection of Early-Maturing Pear’s Effective Acidity Based on Hyperspectral Imaging Technology

International audienceThe hyperspectral imaging technology is used to detect early-maturing pear’s effective acidity nondestructively, and effective prediction model is established. 145 pears’ hyperspectral images are obtained in the wavelength range of 400nm-1000nm. Total 145 pears are separated into the calibration set (77 samples) and prediction set (68 samples). Early-maturing pear’s effective acidity partial least squares (PLS) prediction model is built in different range of spectrum band. By comparison, the range 498 nm - 971 nm was selected in using partial least squares (PLS) to build early-maturing pear’s effective acidity prediction model. The experimental results show that, PLS prediction model of early-maturing pear’s effective acidity has the best effect in this range of wavelength. The correlation coefficient R between early-maturing pear’s actual effective acidity and predicted effective acidity is 0.9944 and 0.9233 for calibration set and prediction set respectively, the root mean squared error of prediction samples (RMSEP) is 0.022 and 0.072 for calibration set and prediction set respectively

Fabrication of superamphiphobic surface with re-entrant structures via self-assembly colloidal template-assisted electrochemical deposition

From Elsevier via Jisc Publications RouterHistory: accepted 2023-06-06, epub 2023-06-16, issued 2023-08-31Article version: AMPublication status: PublishedFunder: National Natural Science Foundation of China; FundRef: https://doi.org/10.13039/501100001809; Grant(s): 52203140, 52175329Superamphiphobic surfaces with re-entrant structures have attracted widespread attention due to their superior water and oil resistance. However, current methods for fabricating superamphiphobic surfaces mostly rely on expensive equipment and cumbersome processes. This paper represents a facile and controlled preparation method for superamphiphobic surfaces with zinc oxide (ZnO) re-entrant structures using self-assembled polystyrene (PS) monolayer colloidal crystals (MCCs) as templates to assist electrochemical deposition of ZnO film. The prepared surface shows contact angles (CAs) larger than 150° and sliding angles smaller than 10° for water, glycerol, ethylene glycol (EG), and olive oil. The morphology and size of the re-entrant structures were modulated by the deposition potential and time, and the mechanism of the influence of the structures on the wetting properties was investigated. This superamphiphobic surface with re-entrant structures can be used as a surface-enhanced Raman spectroscopy (SERS) substrate for molecular detection with a detection limit of 10−10 M for rhodamine (R6G), benefiting from the enrichment effect of the superamphiphobic surface and the Schottky barrier at the Ag/ZnO contact interface. We hope that this preparation method for superamphiphobic surface has broad application prospects in the fields of self-cleaning, anti-icing, anti-fog, corrosion resistance, microfluidics, photocatalysis and fluid drag reduction

Genome-Wide Identification and Functional Investigation of 1-Aminocyclopropane-1-carboxylic Acid Oxidase (ACO) Genes in Cotton

ACO is one of the rate-limiting enzymes in the biosynthesis of ethylene, and it plays a critical role in the regulation of plant growth and development. However, the function of ACO genes in cotton is not well studied. In this study, a total of 332 GhACOs, 187 GaACOs, and 181 GrACOs were identified in G. hirsutum, G. arboretum, and G. raimondii, respectively. Gene duplication analysis showed that whole-genome duplication (WGD) and tandem duplication were the major forces driving the generation of cotton ACO genes. In the promoters of GhACOs, there were cis-acting elements responding to stress, phytohormones, light, and circadian factors, indicating the possible involvement of GhACOs in these processes. Expression and co-expression analyses illustrated that most GhACOs were not only widely expressed in various tissues but also coexpressed with other genes in response to salt and drought stress. GhACO106_At overexpression in Arabidopsis promoted flowering and increased salt tolerance. These results provide a comprehensive overview of the ACO genes of cotton and lay the foundation for subsequent functional studies of these genes

Preparation of Gelatin-Quaternary Ammonium Salt Coating on Titanium Surface for Antibacterial/Osteogenic Properties

Titanium (Ti) and its alloys are widely used in medical treatment, engineering, and other fields because of their excellent properties including biological activity, an elastic modulus similar to that of human bones, and corrosion resistance. However, there are still many defects in the surface properties of Ti in practical applications. For example, the biocompatibility of Ti with bone tissue can be greatly reduced in implants due to a lack of osseointegration as well as antibacterial properties, which may lead to osseointegration failure. To address these problems and to take advantage of the amphoteric polyelectrolyte properties of gelatin, a thin layer of gelatin was prepared by electrostatic self-assembly technology. Diepoxide quaternary ammonium salt (DEQAS) and maleopimaric acid quaternary ammonium salt (MPA−N+) were then synthesized and grafted onto the thin layer. The cell adhesion and migration experiments demonstrated that the coating has excellent biocompatibility, and those grafted with MPA−N+ promoted cell migration. The bacteriostatic experiment showed that the mixed grafting with two ammonium salts had excellent bacteriostatic performance against Escherichia coli and Staphylococcus aureus, with bacteriostasis rates of 98.1 ± 1.0% and 99.2 ± 0.5%, respectively

Theoretical Modeling of Multi-Channel Intracavity Spectroscopy Technology Based on Mode Competition in Er-Doped Fiber Ring Laser Cavity

An analytical model for analyzing multi-channel intracavity spectroscopy technology (ICST) is established based on rate equations of Er-doped fiber laser. With the consideration of the amplified spontaneous emission, how the mode competition influences the iterative process for a stable output is analyzed. From the perspective of iterative times, the sensitivity-enhanced mechanism of the ICST is explained. Moreover, the theoretical modeling is employed to analyze the role that the mode-competition effect plays in switching the sensing channel automatically. It is demonstrated that, owing to the mode-competition effect in the laser cavity, the modulation of the cavity loss can be used to tune the sensing channel automatically. Furthermore, our proposed theoretical modeling is verified using a multi-channel ICST sensing system. It is indicated that the calculated estimates agree well with those data from the experimental absorption spectra. The principle will play a significant role in realizing the multiplexing of ICST