Biocompatible chitosan nanofibers functionalized with silver nanoparticles for SERS based detection

Electrospun chitosan nanofibrous substrates are functionalized with silver nanoparticles by reduction of silver from Tollens reagent using glucose. Filling factor is estimated through developed protocol by using analysis of scanning electron microscopy images. Obtained nanocomposite silver-chitosan plasmonic films display reliable surface enhanced Raman scattering signal of rhodamine B with the concentration 10(-5) M adsorbed onto the surface of functionalized substrates

Low rank perturbations and the spectral statistics of pseudointegrable billiards

We present an efficient method to solve Schr\"odinger's equation for perturbations of low rank. In particular, the method allows to calculate the level counting function with very little numerical effort. To illustrate the power of the method, we calculate the number variance for two pseudointegrable quantum billiards: the barrier billiard and the right triangle billiard (smallest angle $\pi/5$). In this way, we obtain precise estimates for the level compressibility in the semiclassical (high energy) limit. In both cases, our results confirm recent theoretical predictions, based on periodic orbit summation.Comment: 4 page

Metaheuristic design of feedforward neural networks: a review of two decades of research

Over the past two decades, the feedforward neural network (FNN) optimization has been a key interest among the researchers and practitioners of multiple disciplines. The FNN optimization is often viewed from the various perspectives: the optimization of weights, network architecture, activation nodes, learning parameters, learning environment, etc. Researchers adopted such different viewpoints mainly to improve the FNN's generalization ability. The gradient-descent algorithm such as backpropagation has been widely applied to optimize the FNNs. Its success is evident from the FNN's application to numerous real-world problems. However, due to the limitations of the gradient-based optimization methods, the metaheuristic algorithms including the evolutionary algorithms, swarm intelligence, etc., are still being widely explored by the researchers aiming to obtain generalized FNN for a given problem. This article attempts to summarize a broad spectrum of FNN optimization methodologies including conventional and metaheuristic approaches. This article also tries to connect various research directions emerged out of the FNN optimization practices, such as evolving neural network (NN), cooperative coevolution NN, complex-valued NN, deep learning, extreme learning machine, quantum NN, etc. Additionally, it provides interesting research challenges for future research to cope-up with the present information processing era

Correlates of tobacco cessation counseling among Hispanic physicians in the US: a cross-sectional survey study.

BACKGROUND: Physician advice is an important motivator for attempting to stop smoking. However, physicians\u27 lack of intervention with smokers has only modestly improved in the last decade. Although the literature includes extensive research in the area of the smoking intervention practices of clinicians, few studies have focused on Hispanic physicians. The purpose of this study was to explore the correlates of tobacco cessation counseling practices among Hispanic physicians in the US. METHODS: Data were collected through a validated survey instrument among a cross-sectional sample of self-reported Hispanic physicians practicing in New Mexico, and who were members of the New Mexico Hispanic Medical Society in the year 2001. Domains of interest included counseling practices, self-efficacy, attitudes/responsibility, and knowledge/skills. Returned surveys were analyzed to obtain frequencies and descriptive statistics for each survey item. Other analyses included: bivariate Pearson\u27s correlation, factorial ANOVAs, and multiple linear regressions. RESULTS: Respondents (n = 45) reported a low level of compliance with tobacco control guidelines and recommendations. Results indicate that physicians\u27 familiarity with standard cessation protocols has a significant effect on their tobacco-related practices (r = .35, variance shared = 12%). Self-efficacy and gender were both significantly correlated to tobacco related practices (r = .42, variance shared = 17%). A significant correlation was also found between self-efficacy and knowledge/skills (r = .60, variance shared = 36%). Attitudes/responsibility was not significantly correlated with any of the other measures. CONCLUSION: More resources should be dedicated to training Hispanic physicians in tobacco intervention. Training may facilitate practice by increasing knowledge, developing skills and, ultimately, enhancing feelings of self-efficacy

Morphology alterations of skin and subcutaneous fat at NIR laser irradiation combined with delivery of encapsulated indocyanine green

The goal of this study is to quantify the impact of the in vivo photochemical treatment of rats with obesity using indocyanine green (ICG) dissolved in saline or dispersed in an encapsulated form at NIR laser irradiation, which was monitored by tissue sampling and histochemistry. The subcutaneous injection of the ICG solution or ICG encapsulated into polyelectrolyte microcapsules, followed by diode laser irradiation (808 nm, 8    W / cm 2 , 1 min), resulted in substantial differences in lipolysis of subcutaneous fat. Most of the morphology alterations occurred in response to the laser irradiation if a free-ICG solution had been injected. In such conditions, membrane disruption, stretching, and even delamination in some cases were observed for a number of cells. The encapsulated ICG aroused similar morphology changes but with weakly expressed adipocyte destruction under the laser irradiation. The Cochran Q test rendered the difference between the treatment alternatives statistically significant. By this means, laser treatment using the encapsulated form of ICG seems more promising and could be used for safe layerwise laser treatment of obesity and cellulit

A comparison study between electrospun polycaprolactone and piezoelectric poly(3-hydroxybutyrate-co-3-hydroxyvalerate) scaffolds for bone tissue engineering

This study was supported by the Federal Target Program #14.587.21.0013 (a unique application number 2015-14-588-0002-5599)

A Novel Machine Learning-based Predictive Model of Clinically Significant Prostate Cancer and Online Risk Calculator

OBJECTIVE To create a machine-learning predictive model combining prostate imaging-reporting and data system (PI-RADS) score, PSA density, and clinical variables to predict clinically significant prostate cancer (csPCa). METHODS We evaluated a cohort of patients who underwent prostate biopsy for suspected prostate cancer (PCa) in New Zealand, Australia, and Switzerland. We collected data on age, body mass index (BMI), PSA level, prostate volume, PSA density (PSAD), PI-RADS scores, previous biopsy, and corresponding histology results. The dataset was divided into derivation (training) and validation (test) sets using random splits. An independent dataset was obtained from the Harvard Dataverse for external validation. A cohort of 1272 patients was analyzed. We fitted a Lasso model, XGBoost, and LightGBM to the training set and assessed their accuracy. RESULTS All models demonstrated ROC-AUC values ranging from 0.830 to 0.851. LightGBM was considered the superior model, with an ROC of 0.851 (95%CI: 0.804-0.897) in the test set and 0.818 (95% CI: 0.798-0.831) in the external dataset. The most important variable was PI-RADS, followed by PSA density, history of previous biopsy, age, and BMI. CONCLUSION We developed a predictive model for detecting csPCa that exhibited a high ROC-AUC value for internal and external validations. This suggests that the integration of the clinical parameters outperformed each individual predictor. Additionally, the model demonstrated good calibration metrics, indicative of a more balanced model than the existing models

Expanding the clinical phenotype in patients with disease causing variants associated with atypical Usher syndrome

Atypical Usher syndrome (USH) is poorly defined with a broad clinical spectrum. Here, we characterize the clinical phenotype of disease caused by variants in CEP78, CEP250, ARSG, and ABHD12. Chart review evaluating demographic, clinical, imaging, and genetic findings of 19 patients from 18 families with a clinical diagnosis of retinal disease and confirmed disease-causing variants in CEP78, CEP250, ARSG, or ABHD12. CEP78-related disease included sensorineural hearing loss (SNHL) in 6/7 patients and demonstrated a broad phenotypic spectrum including: vascular attenuation, pallor of the optic disc, intraretinal pigment, retinal pigment epithelium mottling, areas of mid-peripheral hypo-autofluorescence, outer retinal atrophy, mild pigmentary changes in the macula, foveal hypo-autofluorescence, and granularity of the ellipsoid zone. Nonsense and frameshift variants in CEP250 showed mild retinal disease with progressive, non-congenital SNHL. ARSG variants resulted in a characteristic pericentral pattern of hypo-autofluorescence with one patient reporting non-congenital SNHL. ABHD12-related disease showed rod-cone dystrophy with macular involvement, early and severe decreased best corrected visual acuity, and non-congenital SNHL ranging from unreported to severe. This study serves to expand the clinical phenotypes of atypical USH. Given the variable findings, atypical USH should be considered in patients with peripheral and macular retinal disease even without the typical RP phenotype especially when SNHL is noted. Additionally, genetic screening may be useful in patients who have clinical symptoms and retinal findings even in the absence of known SNHL given the variability of atypical USH

In vivo optical monitoring of transcutaneous delivery of calcium carbonate microcontainers

The research was supported by the Government of the RF (grant 14.Z50.31.0004 to support scientific research projects implemented under the supervision of leading scientists)