11 research outputs found

    Characterization of Dye-Loaded Poly(lactic-<i>co</i>-glycolic acid) Nanoparticles by Comprehensive Two-Dimensional Liquid Chromatography Combining Hydrodynamic and Reversed-Phase Liquid Chromatography

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    Analytical methods for the assessment of drug-delivery systems (DDSs) are commonly suitable for characterizing individual DDS properties, but do not allow determination of several properties simultaneously. A comprehensive online two-dimensional liquid chromatography (LC × LC) system was developed that is aimed to be capable of characterizing both nanoparticle size and encapsulated cargo over the particle size distribution of a DDS by using one integrated method. Polymeric nanoparticles (NPs) with encapsulated hydrophobic dyes were used as model DDSs. Hydrodynamic chromatography (HDC) was used in the first dimension to separate the intact NPs and to determine the particle size distribution. Fractions from the first dimension were taken comprehensively and disassembled online by the addition of an organic solvent, thereby releasing the encapsulated cargo. Reversed-phase liquid chromatography (RPLC) was used as a second dimension to separate the released dyes. Conditions were optimized to ensure the complete disassembly of the NPs and the dissolution of the dyes during the solvent modulation step. Subsequently, stationary-phase-assisted modulation (SPAM) was applied for trapping and preconcentration of the analytes, thereby minimizing the risk of analyte precipitation or breakthrough. The developed HDC × RPLC method allows for the characterization of encapsulated cargo as a function of intact nanoparticle size and shows potential for the analysis of API stability.</p

    Het verhaal van Lucas als sleutel tot de identiteit

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    Bad splits in bilateral sagittal split osteotomy:systematic review and meta-analysis of reported risk factors

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    An unfavourable and unanticipated pattern of the bilateral sagittal split osteotomy (BSSO) is generally referred to as a ‘bad split’. Patient factors predictive of a bad split reported in the literature are controversial. Suggested risk factors are reviewed in this article. A systematic review was undertaken, yielding a total of 30 studies published between 1971 and 2015 reporting the incidence of bad split and patient age, and/or surgical technique employed, and/or the presence of third molars. These included 22 retrospective cohort studies, six prospective cohort studies, one matched-pair analysis, and one case series. Spearman's rank correlation showed a statistically significant but weak correlation between increasing average age and increasing occurrence of bad splits in 18 studies (ρ = 0.229; P < 0.01). No comparative studies were found that assessed the incidence of bad split among the different splitting techniques. A meta-analysis pooling the effect sizes of seven cohort studies showed no significant difference in the incidence of bad split between cohorts of patients with third molars present and concomitantly removed during surgery, and patients in whom third molars were removed at least 6 months preoperatively (odds ratio 1.16, 95% confidence interval 0.73–1.85, Z = 0.64, P = 0.52). In summary, there is no robust evidence to date to show that any risk factor influences the incidence of bad split

    The use of cranial resection templates with 3D virtual planning and PEEK patient-specific implants: A 3 year follow-up

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    Purpose: The aim of this study was to evaluate the accuracy of resection templates in cranioplasties in order to facilitate a one-stage resection and cranial reconstruction. Patients and methods: In three cases, cranial resections were combined with direct reconstructions using the principles of computer-aided design, manufacturing, and surgery. The precision of the resection template was evaluated through a distance map, comparing the planned and final result. Results: The mean absolute difference between the planned and actual reconstructed contour was less than 1.0 mm. After 3 years, no clinical signs of infection or rejection of the implants were present. The computed tomography scans showed no irregularities, and the aesthetic results remained satisfactory. Conclusion: One-stage resection and cranial reconstruction using a resection template, control template, and a prefabricated patient-specific implant of poly(ether-ether-ketone) (PEEK) proved to be a viable and safe method

    Factors related to failure of autologous cranial reconstructions after decompressive craniectomy

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    Purpose: Cranioplasty is customary after decompressive craniectomy. Many different materials have been developed and used for this procedure. The ideal material does not yet exist, while complication rates in cranioplasties remain high. This study aimed to determine factors related to autologous bone flap failure. Materials and methods: In this two-center retrospective cohort study, 276 patients underwent autologous bone cranioplasty after initial decompressive craniectomy between 2004 and 2014. Medical records were reviewed regarding patient characteristics and factors potentially related to bone flap failure. Data were analyzed using univariable and multivariable regression analysis. Results: Independent factors related to overall bone flap failure were: duration of hospitalization after decompressive craniectomy [OR: 1.012 (95%CI: 1.003–1.022); p = 0.012], time interval between decompressive craniectomy and cranioplasty [OR: 1.018 (95%CI: 1.004–1.032); p = 0.013], and follow-up duration [OR: 1.034 (95%CI: 1.020–1.047); p < 0.001]. In patients with bone flap infection, neoplasm as initial diagnosis occurred significantly more often (29.2% vs. 7.8%; RD 21.3%; 95%CI 8.4 –38.3%; NNH 5; 95%CI 3 –12) and duration of hospitalization after decompressive craniectomy tended to be longer (means 54 vs. 28 days, MD 26.2 days, 95%CI −8.6 to 60.9 days). Patients with bone flap resorption were significantly younger (35 vs. 43 years, MD 7.7 years, 95%CI 0.8–14.6 years) and their cranial defect size tended to be wider than in patients without bone flap resorption (mean circumference 39 vs. 37 cm; MD 2.4 cm, 95% CI -0.43–5.2 cm) and follow-up duration was significantly longer (44 vs. 14 months, MD 29 months, 95%CI 17–42 months). Conclusion: A neoplasm as initial diagnosis, longer hospitalization after decompressive craniectomy, larger time interval between decompressive craniectomy and cranioplasty, and longer follow-up duration are associated with a higher risk of failure of autologous bone flaps for cranioplasty. Patients with these risk factors may be better served with an early recovery program after decompressive surgery or an alloplastic material for cranioplasty

    Bad splits in bilateral sagittal split osteotomy: systematic review and meta-analysis of reported risk factors

    No full text
    An unfavourable and unanticipated pattern of the bilateral sagittal split osteotomy (BSSO) is generally referred to as a ‘bad split’. Patient factors predictive of a bad split reported in the literature are controversial. Suggested risk factors are reviewed in this article. A systematic review was undertaken, yielding a total of 30 studies published between 1971 and 2015 reporting the incidence of bad split and patient age, and/or surgical technique employed, and/or the presence of third molars. These included 22 retrospective cohort studies, six prospective cohort studies, one matched-pair analysis, and one case series. Spearman's rank correlation showed a statistically significant but weak correlation between increasing average age and increasing occurrence of bad splits in 18 studies (ρ = 0.229; P < 0.01). No comparative studies were found that assessed the incidence of bad split among the different splitting techniques. A meta-analysis pooling the effect sizes of seven cohort studies showed no significant difference in the incidence of bad split between cohorts of patients with third molars present and concomitantly removed during surgery, and patients in whom third molars were removed at least 6 months preoperatively (odds ratio 1.16, 95% confidence interval 0.73–1.85, Z = 0.64, P = 0.52). In summary, there is no robust evidence to date to show that any risk factor influences the incidence of bad split
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