The Role of Sarcopenic Obesity in Cancer and Cardiovascular Disease: A Synthesis of the Evidence on Pathophysiological Aspects and Clinical Implications

Obesity is globally a serious public health concern and is associated with a high risk of cardiovascular disease (CVD) and various types of cancers. It is important to evaluate various types of obesity, such as visceral and sarcopenic obesity. The evidence on the associated risk of CVD, cancer and sarcopenic obesity, including pathophysiological aspects, occurrence, clinical implications and survival, needs further investigation. Sarcopenic obesity is a relatively new term. It is a clinical condition that primarily affects older adults. There are several endocrine-hormonal, metabolic and lifestyle aspects involved in the occurrence of sarcopenic obesity that affect pathophysiological aspects that, in turn, contribute to CVD and neoplasms. However, there is no available evidence on the role of sarcopenic obesity in the occurrence of CVD and cancer and its pathophysiological interplay. Therefore, this review aims to describe the pathophysiological aspects and the clinical and epidemiological evidence on the role of sarcopenic obesity related to the occurrence and mortality risk of various types of cancer and cardiovascular disease. This literature review highlights the need for further research on sarcopenic obesity to demonstrate the interrelation of these various associations

Process Monitoring of Moisture Content and Mass Transfer Rate in a Fluidised Bed with a Low Cost Inline MEMS NIR Sensor

Purpose The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry–Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control. Methods Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules. A PLS moisture model was constructed resulting in a high resolution moisture signal, used to demonstrate (i) endpoint determination and (ii) evaluation of mass transfer performance. Results The sensors appear robust with respect to vibration and ambient temperature changes, and the accuracy of water content predictions (±13 % ) is similar to those reported for high specification NIR sensors. Fusion of temperature and moisture content signal allowed monitoring of water transport rates in the fluidised bed and highlighted the importance water transport within the solid phase at low moisture levels. The NIR data was also successfully used with PCA-based MSPC models for endpoint detection. Conclusions The spectral quality of the small form factor NIR sensor and its robustness is clearly sufficient for the construction and application of PLS models as well as PCA-based MSPC moisture models. The resulting high resolution moisture content signal was successfully used for endpoint detection and monitoring the mass transfer rate

Data fusion strategies to combine sensor and multivariate model outputs for multivariate statistical process control

Process analytical technologies (PAT) applied to process monitoring and control generally provide multiple outputs that can come from different sensors or from different model outputs generated from a single multivariate sensor. This paper provides a contribution to current data fusion strategies for the combination of sensor and/or model outputs in the development of multivariate statistical process control (MSPC) models. Data fusion is explored through three real process examples combining output from multivariate models coming from the same sensor uniquely (in the near-infrared (NIR)-based end point detection of a two-stage polyester production process) or the combination of these outputs with other process variable sensors (using NIR-based model outputs and temperature values in the end point detection of a fluidized bed drying process and in the on-line control of a distillation process). The three examples studied show clearly the flexibility in the choice of model outputs (e.g. key properties prediction by multivariate calibration, process profiles issued from a multivariate resolution method) and the benefit of using MSPC models based on fused information including model outputs towards those based on raw single sensor outputs for both process control and diagnostic and interpretation of abnormal process situations. The data fusion strategy proposed is of general applicability for any analytical or bioanalytical process that produces several sensor and/or model outputs

Steps to build a DIY low-cost fixed-wing drone for biodiversity conservation

Despite the proved usefulness of drones in biodiversity studies, acquisition costs and difficulties in operating, maintaining and repairing these systems constrain their integration in conservation projects, particularly for low-income countries. Here we present the steps necessary to build a low-cost fixed-wing drone for environmental applications in large areas, along with instructions to increase the reliability of the system and testing its performance. Inspired by DIY (Do It Yourself) and open source models, this work prioritizes simplicity and accounts for cost-benefit for the researcher. The DIY fixed-wing drone developed has electric propulsion, can perform pre-programmed flight, can carry up to 500 g payload capacity with 65 minutes flight duration and flies at a maximum distance of 20 km. It is equipped with a RGB (Red, Green and Blue) sensor capable of obtaining 2.8 cm per pixel Ground Sample Distance (GSD) resolution at a constant altitude of 100 m above ground level (AGL). The total cost was $995 which is substantially less than the average value of similar commercial drones used in biodiversity studies. We performed 12 flight tests in auto mode using the developed model in protected areas in Brazil, obtaining RGB images that allowed us to identify deforestation spots smaller than 5 m2 and medium-sized animals. Building DIY drones requires some technical knowledge and demands more time than buying a commercial ready-to-fly system, but as proved here, it can be less expensive, which is often crucial in conservation projects

Correlation between the heterosis of maize hybrids and genetic divergence among lines

The objective of this work was to evaluate grain yield of maize single cross hybrids obtained from diallel crosses among contrasting lines, to estimate the combining ability of the lines, and finally to confirm if the genetic diversity among those lines assessed by molecular markers is correlated with single cross hybrids heterosis. The 36 single cross hybrids resulting from partial diallel and 12 parental lines were evaluated in Campinas in randomized block design, with three replicates and two control lines checks. General combining ability of the lines was estimated according to Griffing model 4. Correlations among matrices were estimated through Mantel statistics, considering heterosis, yield and specific combining ability with genetic divergence assessed by AFLP and SSR. The hybrids PM518 x L111 exhibited an outstanding yield and the lines PM518, IP4035 and L111 showed positive general combining ability. The estimate heterosis ranged from 927 to 6,698 kg ha(-1). A positive and significant correlation was observed in parental lines between heterosis and genetic diversity assessed by AFLP and SSR. The genetic divergence, however, was not enough to determine the specific combining ability and the hybrids yield.42681181

Regionalização para o cultivo do feijão no Rio Grande do Sul com base na interação genótipo x ambiente¹.

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