Application of nanoparticles entrapped orange essential oil to inhibit the incidence of phytopathogenic fungi during storage of agroecological maize seeds.

The demand for sustainable, healthy, and pesticide-free food has grown in recent years. Agroecological seeds cannot receive chemical treatment, as pesticides present toxicological and environmental risks, requiring the development of alternative methods for disease control, such as the use of essential oils. In this study, orange essential oil was extracted and encapsulated in zein nanoparticles by the nanoprecipitation method.

Multiproxy bioarchaeological data reveals interplay between growth, diet and population dynamics across the transition to farming in the central Mediterranean.

The transition to farming brought on a series of important changes in human society, lifestyle, diet and health. The human bioarchaeology of the agricultural transition has received much attention, however, relatively few studies have directly tested the interrelationship between individual lifestyle factors and their implications for understanding life history changes among the first farmers. We investigate the interplay between skeletal growth, diet, physical activity and population size across 30,000 years in the central Mediterranean through a 'big data' cross-analysis of osteological data related to stature (n = 361), body mass (n = 334) and long bone biomechanics (n = 481), carbon (δC) and nitrogen (δN) stable isotopes (n = 1986 human, n = 475 animal) and radiocarbon dates (n = 5263).

The added value of lung perfusion scintigraphy semiquantitative measures in post-COVID patients with persistent dyspnea without pulmonary embolism.

Background: Persistent dyspnea is frequent in post-COVID patients, even in the absence of pulmonary embolism (PE). In this scenario, the role of lung perfusion scintigraphy is unclear. The present study correlated scintigraphy-based semiquantitative perfusion parameters with chest high-resolution computed tomography (hrCT) volumetric indexes and clinical data in post-COVID patients with persistent dyspnea.

Data-driven clustering of combined Functional Motor Disorders based on the Italian registry.

Introduction: Functional Motor Disorders (FMDs) represent nosological entities with no clear phenotypic characterization, especially in patients with multiple (combined FMDs) motor manifestations. A data-driven approach using cluster analysis of clinical data has been proposed as an analytic method to obtain non-hierarchical unbiased classifications. The study aimed to identify clinical subtypes of combined FMDs using a data-driven approach to overcome possible limits related to "a priori" classifications and clinical overlapping.