Microspheres of essential oil in polylactic acid and poly(methyl methacrylate) matrices and their blends

This study is focussed on micro-encapsulation of essential oils in polylactic acid (PLA) and a poly(methyl methacrylate) (PMMA) matrix as well as blends of the same. Microspheres were prepared by the solvent evaporation technique and characterised by scanning electron microscopy (SEM), differential scanning calorimetry (DSC) and Fourier transform infra-red spectroscopy (FTIR). The encapsulation efficiencies and release profiles of the essential oils were studied by gas chromatography mass spectrometry (GC-MS) and head-space solid-phase microextraction GC-MS, respectively. Furthermore, the microspheres were tested for antibacterial activity against both Gram-negative and Gram-positive bacterial strains.

The results showed that the microspheres compositions (PLA/PMMA ratio) have significant effect on their characteristics. The process adopted for preparing the microspheres promoted formation of spherical particles at the sizes of 1.5–9.5?µm. The highest encapsulation efficiency of the prepared microspheres was observed in systems consisting of linalool (81.10?±?10.0?wt. % for PLA system and 76.0?±?3.3?wt. % for PMMA system). Confirmation was also made that the release rate of the microspheres was affected by the size of the same.     

Depression embodied: an ambiguous striving against fading

Although depression is associated to physical discomfort, meanings of the body in depression are rarely addressed in clinical research. Drawing on the concept of the lived body, this study explores depression as an embodied phenomenon. Using a hermeneutic phenomenological approach, the analysis of narrative‐based interviews with 11 depressed adults discloses a thematic structure of an embodied process of an ambiguous striving against fading. Five subthemes elicit different dimensions of this process, interpreted as disabling or enabling: feeling estranged, feeling confined, feeling burdensome, sensing life and seeking belongingness. In relation to clinical practice, we suggest that the interdisciplinary team can focus on enhancing the enabling dimensions, for example through guided physical activities to support the patient to feel more alive, capable and connected. Moreover, we suggest that the treatment process benefits from an increased awareness of the ambiguity in the patient's struggle, acknowledging both destructive and recharging elements of the withdrawing, and the perceived conflict in‐between.     

Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma(HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate.AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy.METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses.RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure(area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure(area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model(integrated discrimination improvement = 0.117, P =0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic(P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone.CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.