Investigating the diet of Mesolithic groups in the Southern Alps: An attempt using stable carbon and nitrogen isotope analyses

Stable isotopic data (δ13C; δ15N) were obtained from Mesolithic human and faunal remains from north- eastern Italy in order to document the human diet and provide information on the relationship between landscape use and subsistence strategies. The bone samples were from an adult female individual (Early Mesolithic, Late Sauveterrian) buried at Vatte di Zambana (Trento), an adult male (Late Mesolithic, Castelnovian) buried at Mondeval de Sora (Belluno), and an adult female from Mezzocorona Borgonuovo (Trento). For the latter, the stratigraphic position of the burial pit and evidence of the associated ritual suggest a Mesolithic attribution. Carbon (13C/12C) and nitrogen (15N/14N) stable isotope compositions of human bone collagen were compared with those of animal remains from different taxa found in stratigraphic association with the burial. The isotopic data and the Bayesian model developed from the latter and from data in the literature indicate a very significant proportion of terrestrial resources in the protein fraction of the human diet, particularly from red deer compared to other ungulates and potentially from freshwater fish and small mammals. These results add to the information provided by zooarchaeological studies and reopen the debate on the role of secondary resources such as chamois, ibex, small mammals and fish, such as pike, in the diet of these mobile human societies. However, as this is a preliminary study based on a very small sample size, interpretations should be considered with caution.Les compositions isotopiques en carbone et en azote (δ13C ; δ15N) ont été mesurées sur des restes osseux humains et animaux du Mésolithique dans le nord-est de l’Italie afin de documenter l’alimentation de ces dernières communautés de chasseurs-cueilleurs et les liens entre l’environnement et les stratégies de subsistance. Les restes osseux analysés proviennent d’une femme adulte (Mésolithique ancien, Sauveterrien récent) inhumée à Vatte di Zambana (Trento), d’un homme adulte (Mésolithique récent, Castelnovien) inhumé à Mondeval de Sora (Belluno) et d’une femme adulte du site de Mezzocorona-Borgonuovo (Trento). La position stratigraphique de la sépulture à Mezzocorona-Borgonuovo ainsi que les pratiques funéraires suggèrent une attribution au Mésolithique. Les ratios isotopiques du carbone et de l’azote du collagène osseux des sujets humains ont été comparés avec ceux d’animaux de différentes espèces associés stratigraphiquement aux sépultures. Les résultats isotopiques ainsi qu’un modèle bayésien, réalisé à partir de ces données et celles de la littérature, indiquent une contribution très significative des protéines animales du milieu terrestre, et surtout la consommation importante de cerfs par rapport aux autres ongulés, ainsi qu’un rôle potentiel des poissons d’eau douce et de petits mammifères. Ces données complètent les informations apportées par les études archéozoologiques et relancent la discussion sur le rôle secondaire que peuvent avoir le chamois, l’ibex, les petits mammifères et les ressources aquatiques, comme le brochet, dans la subsistance de ces nomades. Cette étude reste toutefois préliminaire et le faible corpus d’échantillons analysés nous amène à considérer ces interprétations avec prudence

Predicting hourly ozone concentrations using wavelets and ARIMA models

In recent years, air pollution has been a major concern for its implications on human health. Specifically, ozone ( O3 ) pollution is causing common respiratory diseases. In this paper, we illustrate the process of modeling and prediction hourly O3 pollution measurements using wavelet transforms. We split the time series of O3 in daily intervals and estimate scale and wavelet coefficients for each interval by the discrete wavelet transform (DWT) with Haar filter. Subsequently we apply cumulated autoregressive integrated moving average (ARIMA) to estimate the coefficients and forecast their evolution in future intervals. Then the inverse discrete wavelet transform is implemented for the reconstruction of the time series and the forecast in the near future. In order to assess the performance of the proposed methodology, we compare the predictions obtained by the DWTARIMA with those obtained by the ARIMA model. Several theoretical results are shown through a simulation study.(VLID)341257

Outlier Vehicle Trajectory Detection Using Deep Autoencoders in Santiago, Chile

In the last decade, a large amount of data from vehicle location sensors has been generated due to the massification of GPS systems to track them. This is because these sensors usually include multiple variables such as position, speed, angular position of the vehicle, etc., and, furthermore, they are also usually recorded in very short time intervals. On the other hand, routes are often generated so that they do not correspond to reality, due to artifacts such as buildings, bridges, or sensor failures and where, due to the large amount of data, visual analysis of human expert is unable to detect genuinely anomalous routes. The presence of such abnormalities can lead to faulty sensors being detected which may allow sensor replacement to reliably track the vehicle. However, given the reliability of the available sensors, there are very few examples of such anomalies, which can make it difficult to apply supervised learning techniques. In this work we propose the use of unsupervised deep neural network models based on stacked autoencoders to detect anomalous routes in vehicles within Santiago de Chile. The results show that the proposed model is capable of effectively detecting anomalous paths in real data considering validation given by an expert user, reaching a performance of 82.1% on average. As future work, we propose to incorporate the use of Long Short-Term Memory (LSTM) and attention-based networks in order to improve the detection of anomalous trajectories

Wavelet-based 3-D Multifractal Spectrum with Applications in Breast MRI Images

Breast cancer is the second leading cause of death in women in the United States. Breast Magnetic Resonance Imaging (BMRI) is an emerging tool in breast cancer diagnostics and research, and it is becoming routine in clinical practice. Recently, the American Cancer Society (ACS) recommended that women at very high risk of developing breast cancer have annual BMRI exams, in addition to annual mammograms, to increase the likelihood of early detection. (Saslow et al. [20]). Many medical images demonstrate a certain degree of self-similarity over a range of scales. The multifractal spectrum (MFS) summarizes possibly variable degrees of scaling in one dimensional signals and has been widely used in fractal analysis. In this work, we develop a generalization of MFS to three dimensions and use dynamics of the scaling as discriminatory descriptors for the classification of BMRI images to benign and malignant. Methodology we propose was tested using breast MRI images for four anonymous subjects (two cancer, and two cancer-free cases). The dataset consists of BMRI scans obtained on a 1.5T GE Signa MR (with VIBRANT) scanner at Emory University. We demonstrate that meaningful descriptors show potential for classifying inference

Follow-up of breast cancer: why is it necessary to start a Consensus in 2024?

In Italy, breast cancer is the most frequently diagnosed cancer in women, with 55,900 new cases in 2023 (over 90% in the early stages). Due to the screening, early diagnosis and adjuvant treatment, these patients have a 5-years survival rate of 87% after the diagnosis. There are 834,154 women in Italy with a previous diagnosis of breast cancer: most of these women require a follow-up. The AIOM, ESMO and ASCO Guidelines recommend for early breast cancer (EBC) a clinical follow-up with only physical examination (and eliciting of symptoms) and an annual X-ray mammography, on the basis of the results of two randomized trials published in 1994 that showed no benefit in overall survival with intensive follow-up. However, an Italian survey reported the application by 80% of oncologists of an intensive follow-up based on the individual patient’s risk of recurrence. In fact, the oncologists believe that an early diagnosis of locoregional or distant recurrence may allow an early start of very effective therapies. In this lack of up-to-date scientific data, many questions about follow-up remain unanswered and the few ongoing studies will provide results in several years. Non-compliance with guideline recommendations leads to increased costs for the healthcare system. Furthermore, management varies widely from centre to centre with regard to guideline recommendations, resulting in inequalities between patients. For these reasons, the follow-up of breast cancer should be reconsidered. In the absence of recent scientific evidence, a multidisciplinary group of breast cancer experts has initiated a Consensus on the follow-up of EBC according to the mini-Delphi methodology. The project will be completed by the end of 2024

“OPERATION PHALCO”—Adapted Physical Activity for Breast Cancer Survivors: Is It Time for a Multidisciplinary Approach?

The international literature emphasizes the importance of physical activity (PA) in the first steps after cancer surgery. The regular practice of physical exercise causes positive adaptations on several functional capacities, with positive consequences on patients’ quality of life. This project aims to evaluate the effect of a post-operative training protocol, structured by taking into account both cancer-related issues and the presence of comorbidities, on functional capacities and quality of life of breast cancer survivors. Therefore, it was necessary to create a synergy between oncologists (referring physicians), sport medicine physicians (risk stratification and exercise prescription) and kinesiologists (trainers). Thirty-five post-surgery BC patients decided on a voluntary basis to attend an online Adapted PA (APA) protocol for 4 months, twice a week (APA Group) or Usual Care Group (UC Group). Functional capacity of the APA Group significantly increased, by 13.1% (p = 0.000), whereas perceived exertion decreased by 19.7% (p = 0.020). In the same group, the general health evaluated through the questionnaire EORTC-QLQ-C30 increased (p = 0.050). No differences were found in the UC Group. Operation Phalco, creating a network between oncologists, sports medicine physicians and kinesiologists, confirms the importance of structuring a post-operative path where APA should be included as early as possible in the cancer patient care

“OPERATION PHALCO”—Adapted Physical Activity for Breast Cancer Survivors: Is It Time for a Multidisciplinary Approach?

The international literature emphasizes the importance of physical activity (PA) in the first steps after cancer surgery. The regular practice of physical exercise causes positive adaptations on several functional capacities, with positive consequences on patients’ quality of life. This project aims to evaluate the effect of a post-operative training protocol, structured by taking into account both cancer-related issues and the presence of comorbidities, on functional capacities and quality of life of breast cancer survivors. Therefore, it was necessary to create a synergy between oncologists (referring physicians), sport medicine physicians (risk stratification and exercise prescription) and kinesiologists (trainers). Thirty-five post-surgery BC patients decided on a voluntary basis to attend an online Adapted PA (APA) protocol for 4 months, twice a week (APA Group) or Usual Care Group (UC Group). Functional capacity of the APA Group significantly increased, by 13.1% (p = 0.000), whereas perceived exertion decreased by 19.7% (p = 0.020). In the same group, the general health evaluated through the questionnaire EORTC-QLQ-C30 increased (p = 0.050). No differences were found in the UC Group. Operation Phalco, creating a network between oncologists, sports medicine physicians and kinesiologists, confirms the importance of structuring a post-operative path where APA should be included as early as possible in the cancer patient care

The Impact of NUTRItional Status at First Medical Oncology Visit on Clinical Outcomes: The NUTRIONCO Study

Malnutrition affects up to 75% of cancer patients and results from a combination of anorexia and metabolic dysregulation. Metabolic and nutritional abnormalities in cancer patients can lead to cachexia, a multifactorial syndrome characterized by involuntary loss of skeletal muscle mass, systemic inflammation and increased protein catabolism. Cancer cachexia negatively affects patients’ outcomes, response to anticancer treatments, quality of life, and survival. However, risk of malnutrition, and cachexia are still under-recognized in cancer patients. The Prevalence of Malnutrition in Oncology (PreMiO) study revealed that 51% of patients already had nutritional deficiencies at their first medical oncology visit. Here, we report the results of the subsequent retrospective, observational NUTRItional status at first medical oncology visit ON Clinical Outcomes (NUTRIONCO) study, aimed at assessing the impact of baseline nutritional and non-nutritional variables collected in the PreMiO study on the clinical outcomes of the same patients followed up from August 2019 to October 2021. We have highlighted a statistically significant association between baseline variables and patient death, rehospitalization, treatment toxicity, and disease progression at follow-up. We found a higher overall survival probability in the well-nourished general study population vs. malnourished patients (p p p = 0.004) and VAS score for appetite loss (p = 0.0104), in addition to albumin p 3 (p = 0.0007), were independently associated with the death of non-metastatic patients at follow-up. These findings highlight the importance of proactive, early management of malnutrition and cachexia in cancer patients, and in particular, in non-metastatic patients, from the perspective of a substantial improvement of their clinical outcomes