The application of nanotechnology in the food industry enables prioritization of consumers’ needs. Nanotechnology has the ability to provide new forms of control on food structure; therefore, this technology has higher industrial value. This paper briefly introduces the main concepts of nanotechnology and its correlation with size reduction performance. This paper also introduces the main nanobjects and their potential applications in food, and summarizes various studies and their applications in food industry.

Multiple myeloma (MM) is a hematologic cancer characterized by clonal proliferation of plasma cells within the bone marrow. It is the most serious form of plasma cell dyscrasias, whose complications—hypercalcemia, renal failure, anemia, and lytic bone lesions—are severe and justify the therapeutic management. Imaging of bone lesions is a cardinal element in the diagnosis, staging, study of response to therapy, and prognostic evaluation of patients with MM. Historically, the skeletal radiographic workup (SRW), covering the entire axial skeleton, has been used to detect bone lesions. Over time, new imaging techniques that are more powerful than SRW have been evaluated. Low-dose and whole-body computed tomography (CT) supplants SRW for the detection of bone involvement, but is of limited value in assessing therapeutic response. Bone marrow MRI, initially studying the axial pelvic-spinal skeleton and more recently the whole body, is an attractive alternative. Beyond its non-irradiating character, its sensitivity for the detection of marrow damage, its capacity to evaluate the therapeutic response and its prognostic value has been demonstrated. This well-established technique has been incorporated into disease staging systems by many health systems and scientific authorities. Along with positron emission tomography (PET)-18 fluorodeoxyglucose CT, it constitutes the current imaging of choice for MM. This article illustrates the progress of the MRI technique over the past three decades and situates its role in the management of patients with MM.

Background: Multiple sclerosis is often a longitudinal disease continuum with an initial relapsing-remitting phase (RRMS) and later secondary progression (SPMS). Most currently approved therapies are not sufficiently effective in SPMS. Early detection of SPMS conversion is therefore critical for therapy selection. Important decision-making tools may include testing of partial cognitive performance and magnetic resonance imaging (MRI). Aim of the work: To demonstrate the importance of cognitive testing and MRI for the prediction and detection of SPMS conversion. Elaboration of strategies for follow-up and therapy management in practice, especially in outpatient care. Material and methods: Review based on an unsystematic literature search. Results: Standardized cognitive testing can be helpful for early SPMS diagnosis and facilitate progression assessment. Annual use of sensitive screening tests such as Symbol Digit Modalities Test (SDMT) and Brief Visual Memory Test-Revised (BVMT-R) or the Brief International Cognitive Assessment for MS (BICAMS) test battery is recommended. Persistent inflammatory activity on MRI in the first three years of disease and the presence of cortical lesions are predictive of SPMS conversion. Standardized MRI monitoring for features of progressive MS can support clinically and neurocognitively based suspicion of SPMS. Discussion: Interdisciplinary care of MS patients by clinically skilled neurologists, supported by neuropsychological testing and MRI, has a high value for SPMS prediction and diagnosis. The latter allows early conversion to appropriate therapies, as SPMS requires different interventions than RRMS. After drug switching, clinical, neuropsychological, and imaging vigilance allows stringent monitoring for neuroinflammatory and degenerative activity as well as treatment complications.

The present work shows an application of the Chan-Vese algorithm for the semi-automatic segmentation of anatomical structures of interest (lungs and lung tumor) in 4DCT images of the thorax, as well as their three-dimensional reconstruction. The segmentation and reconstruction were performed on 10 CT images, which make up an inspiration-expiration cycle. The maximum displacement was calculated for the case of the lung tumor using the reconstructions of the onset of inspiration, the onset of expiration, and the voxel information. The proposed method achieves appropriate segmentation of the studied structures regardless of their size and shape. The three-dimensional reconstruction allows us to visualize the dynamics of the structures of interest throughout the respiratory cycle. In the future, it is expected to have more evidence of the good performance of the proposed method and to have the feedback of the clinical expert, since the knowledge of the characteristics of anatomical structures, such as their dimension and spatial position, helps in the planning of Radiotherapy (RT) treatments, optimizing the radiation dose to cancer cells and minimizing it in healthy organs. Therefore, the information found in this work may be of interest for the planning of RT treatments.