Non visual effects of light: an overview and an Italian experience

Since the discovery of non-visual effect of light, consequences on human psychology and physiology have been investigated; however, effects on cognition of exposure to different spectral composition have been partially explored. Aim of this paper is an overview on researches developed in this field to compare general approaches and measurements protocols: the scarce knowledge of the physiological mechanisms, as well as the lack of shared methods, techniques, tools and procedures represent the weak point of this research. The impact of different procedures and experimental settings on results is shown, evidencing the need for scientifically consistent and internationally agreed procedures

T-wave morphology restitution in chronic heart failure patient with atrial fibrillation

Chronic heart failure (CHF) represents one of the major public health problems that often end in sudden cardiac death (SCD). Atrial fibrillation (AF) is associated withan increased risk of SCD but nowadays there is no non-invasive method that accurately predicts that risk. The recently developed T-wave morphology restitution (TMR) index showed its specific association with SCD risk prediction in sinus rhythm subjects with CHF. The aim of this work was to investigate the SCD predictive value of this index in individuals with AF. TMR was computed from 171 24-hour ECG Holter recordings from CHF patients enrolled in the “MUerte Súbita en Insuficiencia Cardiaca”study with AF. There were 19 SCD victims after the 4 years’follow-up. The Mann–Whitney U test showed that TMR was not significantly different in SCD victims as compared to survivors (p=0.617). However, this might be due to the huge gap in sample size betweenbothpopulations. Assuming a balanced case-control scenario, the TMR value distribution mayapproach to a normal distribution. Under this hypothesis, the t-test was performed under the condition of unequal variances between both populations, showinga significant difference in TMR between bothgroups (p=0.023). In conclusion, the predictive power of TMR index in AF rhythm should not be excluded, but it needs a more in-depth studyPeer ReviewedPostprint (published version

Lung nodule diagnosis and cancer histology classification from computed tomography data by convolutional neural networks: A survey

Lung cancer is among the deadliest cancers. Besides lung nodule classification and diagnosis, developing non-invasive systems to classify lung cancer histological types/subtypes may help clinicians to make targeted treatment decisions timely, having a positive impact on patients' comfort and survival rate. As convolutional neural networks have proven to be responsible for the significant improvement of the accuracy in lung cancer diagnosis, with this survey we intend to: show the contribution of convolutional neural networks not only in identifying malignant lung nodules but also in classifying lung cancer histological types/subtypes directly from computed tomography data; point out the strengths and weaknesses of slice-based and scan-based approaches employing convolutional neural networks; and highlight the challenges and prospective solutions to successfully apply convolutional neural networks for such classification tasks. To this aim, we conducted a comprehensive analysis of relevant Scopus-indexed studies involved in lung nodule diagnosis and cancer histology classification up to January 2022, dividing the investigation in convolutional neural network-based approaches fed with planar or volumetric computed tomography data. Despite the application of convolutional neural networks in lung nodule diagnosis and cancer histology classification is a valid strategy, some challenges raised, mainly including the lack of publicly-accessible annotated data, together with the lack of reproducibility and clinical interpretability. We believe that this survey will be helpful for future studies involved in lung nodule diagnosis and cancer histology classification prior to lung biopsy by means of convolutional neural networks

Mathematical Model of Glucagon Kinetics for the Assessment of Insulin-Mediated Glucagon Inhibition During an Oral Glucose Tolerance Test

none6siGlucagon is secreted from the pancreatic alpha cells and plays an important role in the maintenance of glucose homeostasis, by interacting with insulin. The plasma glucose levels determine whether glucagon secretion or insulin secretion is activated or inhibited. Despite its relevance, some aspects of glucagon secretion and kinetics remain unclear. To gain insight into this, we aimed to develop a mathematical model of the glucagon kinetics during an oral glucose tolerance test, which is sufficiently simple to be used in the clinical practice. The proposed model included two first-order differential equations -one describing glucagon and the other describing C-peptide in a compartment remote from plasma - and yielded a parameter of possible clinical relevance (i.e., SGLUCA(t), glucagon-inhibition sensitivity to glucose-induced insulin secretion). Model was validated on mean glucagon data derived from the scientific literature, yielding values for SGLUCA(t) ranging from -15.03 to 2.75 (ng of glucagon·nmol of C-peptide-1). A further validation on a total of 100 virtual subjects provided reliable results (mean residuals between -1.5 and 1.5 ng·L-1) and a negative significant linear correlation (r = -0.74, p < 0.0001, 95% CI: -0.82 - -0.64) between SGLUCA(t) and the ratio between the areas under the curve of suprabasal remote C-peptide and glucagon. Model reliability was also proven by the ability to capture different patterns in glucagon kinetics. In conclusion, the proposed model reliably reproduces glucagon kinetics and is characterized by sufficient simplicity to be possibly used in the clinical practice, for the estimation in the single individual of some glucagon-related parameters.openMorettini, Micaela; Burattini, Laura; Göbl, Christian; Pacini, Giovanni; Ahrén, Bo; Tura, AndreaMorettini, Micaela; Burattini, Laura; Göbl, Christian; Pacini, Giovanni; Ahrén, Bo; Tura, Andre

Exercise-Induced Repolarization Alternans Heterogeneity in Patients with an Implanted Cardiac Defibrillator

Abstract Repolarization alternans (RA

solution of linear and non linear boundary value problems using population distributed parallel differential evolution

Abstract Cases where the derivative of a boundary value problem does not exist or is constantly changing, traditional derivative can easily get stuck in the local optima or does not factually represent a constantly changing solution. Hence the need for evolutionary algorithms becomes evident. However, evolutionary algorithms are compute-intensive since they scan the entire solution space for an optimal solution. Larger populations and smaller step sizes allow for improved quality solution but results in an increase in the complexity of the optimization process. In this research a population-distributed implementation for differential evolution algorithm is presented for solving systems of 2nd-order, 2-point boundary value problems (BVPs). In this technique, the system is formulated as an optimization problem by the direct minimization of the overall individual residual error subject to the given constraint boundary conditions and is then solved using differential evolution in the sense that each of the derivatives is replaced by an appropriate difference quotient approximation. Four benchmark BVPs are solved using the proposed parallel framework for differential evolution to observe the speedup in the execution time. Meanwhile, the statistical analysis is provided to discover the effect of parametric changes such as an increase in population individuals and nodes representing features on the quality and behavior of the solutions found by differential evolution. The numerical results demonstrate that the algorithm is quite accurate and efficient for solving 2nd-order, 2-point BVPs

Surface electromyography low-frequency content: Assessment in isometric conditions after electrocardiogram cancellation by the Segmented-Beat Modulation Method

Background: Surface electromyography (SEMG) is widely used in clinics for assessing muscle functionality. All procedures proposed for noise reduction alter SEMG spectrum, especially in the low-frequency band (below 30 Hz). Indeed, low-frequency band is generally addressed to motion artifacts and electrocardiogram (ECG) interference without any further investigation on the possibility of SEMG having significant spectral content. The aim of the present study was evaluating SEMG frequency content to understand if low-frequency spectral content is negligible or, on the contrary, represents a significant SEMG portion potentially providing relevant clinical information. Method: Isometric recordings of five muscles (sternocleidomastoideus, erectores spinae at L4, rectus abdominis, rectus femoris and tibialis anterior) were acquired in 10 young healthy voluntary subjects. These recordings were not affected by motion artifacts by construction and were pre-processed by the Segmented-Beat Modulation Method for ECG deletion before performing spectral analysis. Results: Results indicated that SEMG frequency content is muscle and subject dependent. Overall, the 50th[25th;75th] percentiles spectrum median frequency and spectral power below 30 Hz were 74[54; 87] Hz and 18[10; 31] % of total (0–450 Hz) spectral power. Conclusions: Low-frequency spectral content represents a significant SEMG portion and should not be neglected. Keywords: Surface electromyographic signal, Electromyographic spectrum, Segmented-Beat Modulation Method, Non-linear filtering, Spectral analysi

Mathematical model of insulin kinetics accounting for the amino acids effect during a mixed meal tolerance test

Amino acids (AAs) are well known to be involved in the regulation of glucose metabolism and, in particular, of insulin secretion. However, the effects of different AAs on insulin release and kinetics have not been completely elucidated. The aim of this study was to propose a mathematical model that includes the effect of AAs on insulin kinetics during a mixed meal tolerance test. To this aim, five different models were proposed and compared. Validation was performed using average data, derived from the scientific literature, regarding subjects with normal glucose tolerance (CNT) and with type 2 diabetes (T2D). From the average data of the CNT and T2D people, data for two virtual populations (100 for each group) were generated for further model validation. Among the five proposed models, a simple model including one first-order differential equation showed the best results in terms of model performance (best compromise between model structure parsimony, estimated parameters plausibility, and data fit accuracy). With regard to the contribution of AAs to insulin appearance/disappearance (kAA model parameter), model analysis of the average data from the literature yielded 0.0247 (confidence interval, CI: 0.0168 - 0.0325) and -0.0048 (CI: -0.0281 - 0.0185) μU·ml-1/(μmol·l-1·min), for CNT and T2D, respectively. This suggests a positive effect of AAs on insulin secretion in CNT, and negligible effect in T2D. In conclusion, a simple model, including single first-order differential equation, may help to describe the possible AAs effects on insulin kinetics during a physiological metabolic test, and provide parameters that can be assessed in the single individuals

The Power of Exercise-Induced T-wave Alternans to Predict Ventricular Arrhythmias in Patients with Implanted Cardiac Defibrillator

ABSTRACT The power of exercise-induced T-wave alternans (TWA) to predict the occurrence of ventricular arrhythmias was evaluated in 67 patients with an implanted cardiac defibrillator (ICD). During the 4-year follow-up, electrocardiographic (ECG) tracings were recorded in a bicycle ergometer test with increasing workload ranging from zero (NoWL) to the patient&apos;s maximal capacity (MaxWL). After the follow-up, patients were classified as either ICD_Cases (n = 29), if developed ventricular tachycardia/fibrillation, or ICD_Controls (n = 38). TWA was quantified using our heart-rate adaptive match filter. Compared to NoWL, MaxWL was characterized by faster heart rates and higher TWA in both ICD_Cases (12−18 µ V vs. 20−39 µ V; P &lt; 0.05) and ICD_Controls (9-15 µ V vs. 20−32 µ V; P &lt; 0.05 ). Still, TWA was able to discriminate the two ICD groups during NoWL (sensitivity = 59−83%, specificity = 53−84%) but not MaxWL (sensitivity = 55−69%, specificity = 39−74%). Thus, this retrospective observational case-control study suggests that TWA&apos;s predictive power for the occurrence of ventricular arrhythmias could increase at low heart rates