Process engineering approach to large-volume methacrylate monolith synthesis for plasmid purification

The construction of large?volume methacrylate monolithic columns for preparative-scale plasmid purification is obstructed by the enormous release of exotherms, thus introducing structural heterogeneity in the monolith pore system. A remarkable radial temperature gradient develops along the monolith thickness, reaching a terminal temperature that supersedes the maximum temperature required for the preparation of a structurally homogeneous monolith. A novel heat expulsion technique is employed to overcome the heat build-up during the synthesis process. The enormous heat build-up is perceived to encompass the heat associated with initiator decomposition and the heat released from free radical-monomer and monomer-monomer interactions. The heat resulting from the initiator decomposition was expelled along with some gaseous fumes before commencing polymerisation in a gradual addition fashion. Characteristics of a 50 mL monolith synthesized using this technique showed an improved uniformity in the pore structure radially along the length on the monolith. Chromatographic characterization of this adsorbent displayed a persistent binding capacity of 14.5 mg pDNA/mL of the adsorbent. The adsorbent was able to fractionate a clarified bacteria lysate in only 3 min (after loading) into RNA, protein and pDNA respectively. The pDNA fraction obtained was analyzed to be a homogeneous supercoiled pDNA.

Effect of cell wall properties on porosity and shrinkage of dried apple

Water removal during drying depends on the pathway of water migration from food materials. Moreover, the water removal rate also depends on the characteristics of the cell wall of plant tissue. In this study, the influence of cell wall properties (such as moisture distribution, stiffness, thickness and cell dimension) on porosity and shrinkage of dried product was investigated. Cell wall stiffness depends on a complex combination of plant cell microstructure, composition of food materials and the water-holding capacity of the cell. In this work, a preliminary investigation of the cell wall properties of apple was conducted in order to predict changes of porosity and shrinkage during drying. Cell wall characteristics of two types of apple (Granny Smith and Red Delicious) were investigated under convective drying to correlate with porosity and shrinkage. A scanning electron microscope (SEM), 2kN Intron, pycnometer and ImageJ software were used in order to measure and analyse cell characteristics, water holding capacity of cell walls, porosity and shrinkage. The cell firmness of the Red Delicious apple was found to be higher than for Granny Smith apples. A remarkable relationship was observed between cell wall characteristics when compare with heat and mass transfer characteristics. It was also found that the evolution of porosity and shrinkage are noticeably influenced by the nature of the cell wall during convective drying. This study has revealed a better understanding of porosity and the shrinkage of dried food at microscopy (cell) level, and will provide better insights to attain energy-effective drying processes and improved quality of dried foods.

Latent class analysis reveals distinct subgroups of patients based on symptom occurrence and demographic and clinical characteristics

Context Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report ten unrelieved and co-occurring symptoms. Objectives To determine if subgroups of oncology outpatients receiving active treatment (n=582) could be identified based on their distinct experience with thirteen commonly occurring symptoms; to determine whether these subgroups differed on select demographic, and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. Methods Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis (LCA) was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale (MSAS). Results Four distinct latent classes were identified (i.e., All Low (28.0%), Moderate Physical and Lower Psych (26.3%), Moderate Physical and Higher Psych (25.4%), All High (20.3%)). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the All High class had the worst QOL scores. Conclusion Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients are risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions.