An approximate threshold condition for a non-autonomous system: an application to a vector-borne infection

A non-autonomous system is proposed to model the seasonal pattern of dengue fever. We found that an approximate threshold condition for infection persistence describes all possible behavior of the system. As far as we know, the kind of analysis here proposed is entirely new. No precise mathematical theorems are demonstrated but we give enough numerical evidence to support the conclusions.Comment: 11 pages and 6 figure

Estimation of Tidal Volume during Exercise Stress Test from Wearable-Device Measures of Heart Rate and Breathing Rate

Tidal volume (TV), defined as the amount of air that moves in or out of the lungs with each respiratory cycle, is important in evaluating the respiratory function. Although TV can be reliably measured in laboratory settings, this information is hardly obtainable under everyday living conditions. Under such conditions, wearable devices could provide valuable support to monitor vital signs, such as heart rate (HR) and breathing rate (BR). The aim of this study was to develop a model to estimate TV from wearable-device measures of HR and BR during exercise. HR and BR were acquired through the Zephyr Bioharness 3.0 wearable device in nine subjects performing incremental cycling tests. For each subject, TV during exercise was obtained with a metabolic cart (Cosmed). A stepwise regression algorithm was used to create the model using as possible predictors HR, BR, age, and body mass index; the model was then validated using a leave-one-subject-out cross-validation procedure. The performance of the model was evaluated using the explained variance (R-2), obtaining values ranging from 0.65 to 0.72. The proposed model is a valid method for TV estimation with wearable devices and can be considered not subject-specific and not instrumentation-specific

Developing an algorithm to assess the UV erythemal dose for outdoor workers Validation through direct measures

An algorithm has been developed to determine the annual dose of UV solar radiation for outdoor workers. The dose is indirectly assessed basing on satellite data, mean global irradiance values, workers' data obtained by means of a questionnaire and corrective coefficients provided by a mathematical model. The values obtained by the use of the algorithm are compared with those obtained by measurement records in different environments. Results demonstrated that the algorithm estimates the mean daily erythemal dose with good approximation

Effectiveness and acceptability of psycho-education group intervention for people hospitalized in psychiatric wards and nurses

Objective: To assess effectiveness and acceptability of a Psycho-education Group Intervention (PGI) on a sample of patients admitted to a Psychiatric Inpatient Unit (PIU) and on ward nurses. Methods: Case-control study. PGI was delivered according to the model of Vendittelli and colleagues (2008). Male and female patients aged 18-70 were eligible. Cases attended the PGI, while controls did not. A 5-item ad hoc Likert-scale was used to record ward atmosphere. The Italian version of the Simple Feedback Question Form for people attending Cognitive Behaviour Therapy Group (SFQF-CBTG) was administered to each patient before discharge. The primary outcome was readmission rate after 6 months from discharge, secondary outcomes were ratings of ward atmosphere by nurses and feed-back from people hospitalized. All Statistics were performed with STATA 13.1. Results: Fifty-two patients were enrolled, 17 cases and 35 controls. No significant differences emerged in the primary outcome, though compulsory readmissions were noticeable only among controls. Ratings of ward atmosphere in relation to group activities did not differ. Seventeen SFQF-CBTG were filled in. Most cases reported at discharge to have found the group "helpful", stating that "they would attend it in the future again", and "group topics were not difficult". Conclusions: No evidence emerged in favour or against effectiveness of the PGI for patients and ward nurses, though the intervention was rated as acceptable and feasible

Magnitude and frequency variations of vector-borne infection outbreaks using the Ross–Macdonald model : explaining and predicting outbreaks of dengue fever

The classical Ross–Macdonald model is often utilized to model vector-borne infections; however, this model fails on several fronts. First, using measured (or estimated) parameters, which values are accepted from the literature, the model predicts a much greater number of cases than what is usually observed. Second, the model predicts a single large outbreak that is followed by decades of much smaller outbreaks, which is not consistent with what is observed. Usually towns or cities report a number of recurrences for many years, even when environmental changes cannot explain the disappearance of the infection between the peaks. In this paper, we continue to examine the pitfalls in modelling this class of infections, and explain that, if properly used, the Ross–Macdonald model works and can be used to understand the patterns of epidemics and even, to some extent, be used to make predictions.We model several outbreaks of dengue fever and show that the variable pattern of yearly recurrence (or its absence) can be understood and explained by a simple Ross–Macdonald model modified to take into account human movement across a range of neighbourhoods within a city. In addition, we analyse the effect of seasonal variations in the parameters that determine the number, longevity and biting behaviour of mosquitoes. Based on the size of the first outbreak, we show that it is possible to estimate the proportion of the remaining susceptible individuals and to predict the likelihood and magnitude of the eventual subsequent outbreaks. This approach is described based on actual dengue outbreaks with different recurrence patterns from some Brazilian regions

Emerging role of tumor-associated macrophages as therapeutic targets in patients with metastatic renal cell carcinoma.

Tumor-associated macrophages (TAMs) derived from peripheral blood monocytes recruited into the renal cell carcinoma (RCC) microenvironment. In response to inflammatory stimuli, macrophages undergo M1 (classical) or M2 (alternative) activation. M1 cells produce high levels of inflammatory cytokines, such as tumor necrosis factor-α, interleukin (IL)-12, IL-23 and IL-6, while M2 cells produce anti-inflammatory cytokines, such as IL-10, thus contributing to RCC-related immune dysfunction. The presence of extensive TAM infiltration in RCC microenvironment contributes to cancer progression and metastasis by stimulating angiogenesis, tumor growth, and cellular migration and invasion. Moreover, TAMs are involved in epithelial-mesenchymal transition of RCC cancer cells and in the development of tumor resistance to targeted agents. Interestingly, macrophage autophagy seems to play an important role in RCC. Based on this scenario, TAMs represent a promising and effective target for cancer therapy in RCC. Several strategies have been proposed to suppress TAM recruitment, to deplete their number, to switch M2 TAMs into antitumor M1 phenotype and to inhibit TAM-associated molecules. In this review, we summarize current data on the essential role of TAMs in RCC angiogenesis, invasion, impaired anti-tumor immune response and development of drug resistance, thus describing the emerging TAM-centered therapies for RCC patients

On-cloud decision-support system for non-small cell lung cancer histology characterization from thorax computed tomography scans

Non-Small Cell Lung Cancer (NSCLC) accounts for about 85% of all lung cancers. Developing non-invasive techniques for NSCLC histology characterization may not only help clinicians to make targeted therapeutic treatments but also prevent subjects from undergoing lung biopsy, which is challenging and could lead to clinical implications. The motivation behind the study presented here is to develop an advanced on-cloud decision-support system, named LUCY, for non-small cell LUng Cancer histologY characterization directly from thorax Computed Tomography (CT) scans. This aim was pursued by selecting thorax CT scans of 182 LUng ADenocarcinoma (LUAD) and 186 LUng Squamous Cell carcinoma (LUSC) subjects from four openly accessible data collections (NSCLC-Radiomics, NSCLC-Radiogenomics, NSCLC-Radiomics-Genomics and TCGA-LUAD), in addition to the implementation and comparison of two end-to-end neural networks (the core layer of whom is a convolutional long short-term memory layer), the performance evaluation on test dataset (NSCLC-Radiomics-Genomics) from a subject-level perspective in relation to NSCLC histological subtype location and grade, and the dynamic visual interpretation of the achieved results by producing and analyzing one heatmap video for each scan. LUCY reached test Area Under the receiver operating characteristic Curve (AUC) values above 77% in all NSCLC histological subtype location and grade groups, and a best AUC value of 97% on the entire dataset reserved for testing, proving high generalizability to heterogeneous data and robustness. Thus, LUCY is a clinically-useful decision-support system able to timely, non-invasively and reliably provide visually-understandable predictions on LUAD and LUSC subjects in relation to clinically-relevant information

Paradigm Shift in Gastric Cancer Prevention: Harnessing the Potential of Aristolochia olivieri Extract

Gastric cancer, particularly adenocarcinoma, is a significant global health concern. Environmental risk factors, such as Helicobacter pylori infection and diet, play a role in its development. This study aimed to characterize the chemical composition and evaluate the in vitro antibacterial and antitumor activities of an Aristolochia olivieri Colleg. ex Boiss. Leaves’ methanolic extract (AOME). Additionally, morphological changes in gastric cancer cell lines were analyzed. AOME was analyzed using HPLC-MS/MS, and its antibacterial activity against H. pylori was assessed using the broth microdilution method. MIC and MBC values were determined, and positive and negative controls were included in the evaluation. Anticancer effects were assessed through in vitro experiments using AGS, KATO-III, and SNU-1 cancer cell lines. The morphological changes were examined through SEM and TEM analyses. AOME contained several compounds, including caffeic acid, rutin, and hyperoside. The extract displayed significant antimicrobial effects against H. pylori, with consistent MIC and MBC values of 3.70 ± 0.09 mg/mL. AOME reduced cell viability in all gastric cancer cells in a dose- and time-dependent manner. Morphological analyses revealed significant ultrastructural changes in all tumor cell lines, suggesting the occurrence of cellular apoptosis. This study demonstrated that AOME possesses antimicrobial activity against H. pylori and potent antineoplastic properties in gastric cancer cell lines. AOME holds promise as a natural resource for innovative nutraceutical approaches in gastric cancer management. Further research and in vivo studies are warranted to validate its potential clinical applications