Influence of precursor chemistry on CVD grown TiO2 coatings: differential cell growth and biocompatibility

Nanocrystalline titanium oxide (TiO2) coatings with different phases and surface topographies were deposited using chemical vapor deposition (CVD) of different homo- and heteroleptic titanium precursors of general formula [XTi(OiPr)3] (X = Cl (1), -NEt2 (2), -N(SiMe3)2 (3), -C5H5 (4), -OiPr (5) and -OtBu (6)) to elucidate the influence of molecular configuration on resulting material properties. The interdependence of precursor chemistry and materials features of the CVD deposits was verified by performing film growth under similar conditions using different precursor molecules (1-6). Studies on composition (XPS), structure (SEM, XRD) and bio-functional properties (cell tests) revealed that the decomposition process is markedly influenced by the auxiliary ligands, which led to incorporation of heteroelements (Si, Cl, N) in the films. Cell tests performed to evaluate the biocompatibility of the coatings towards the growth of bone cells showed a pronounced correlation between cell adhesion and surface morphology as well as the chemical composition. Growth of osteoblast cells was strongly enhanced on films obtained using [Ti(OiPr)4] and [CpTi(OiPr)3], whereas TiO2 coatings produced by [ClTi(OiPr)3] significantly inhibited the cell growth and their proliferation due to Cl contamination. Also, the nanomorphological features of the films were found to stimulate the cell adhesion and growth

Validation, Categorizing, and Prediction of Upper Limb Outcomes after Stroke

The incidence and costs of stroke in the United States are projected to rise over the next decade because of the aging population. Declining stroke mortality over the past few decades means that more people survive stroke and live with physical, cognitive, and emotional disability. Stroke remains one of the leading causes of disability in the United States because very few survivors experience a full recovery of their upper limb. Upper limb recovery after stroke is critical to performing activities of daily living and physical and occupational therapies are one of the only treatment options to address these challenges. The World Health Organization’s (WHO) International Classification of Functioning, Disability, and Health Framework (ICF) informs our understanding of the importance of measuring upper limb changes across measurement levels, showing that improvements seen in one level (i.e. domain) do not directly transfer to another. Knowing this, it is important to evaluate existing prediction models of motor outcomes after stroke while simultaneously developing novel tools available to researchers and clinicians to facilitate measurement of the upper limb across the ICF domains. This dissertation work performs an external validation of an existing prediction model of upper limb capacity (UL; capability measured in the clinic) after stroke, identifies and defines categories of UL performance (actual UL use in daily life) in people with and without neurological UL deficits, and explores how early clinical measures and participant demographic information are associated with subsequent categories of UL performance after stroke.Recently, prediction algorithms of upper limb capacity after stroke have been developed to facilitate treatment selection, discharge planning, and goal setting for clinicians and their clients. Prediction models have tremendous clinical utility because they aid in the clinical decision making required to select the appropriate efficacious and emerging interventions that afford improvements in upper limb functional capacity, measured by standardized assessments in the therapy clinic. Prior to wide spread implementation of existing prediction algorithms into routine rehabilitation care, however, it is necessary to understand how small healthcare system differences and availability of neurophysiological assessments affect external validation of the models. In Chapter 2, we test how well an algorithm with clinical measures, developed for use in another country, applies to persons with stroke within the United States. Knowing the importance of measurement across ICF domains, it is necessary to develop tools that facilitate clinical decision making and implementation of upper limb performance data into routine rehabilitation care. The use of wearable sensor technology (e.g., accelerometers) for tracking human physical activity have allowed for measurement of actual activity performance of the upper limb in daily life. Data extracted from accelerometers can be used to quantify multiple variables measuring different aspects of UL activity in one or both limbs. A limitation is that several variables are needed to understand the complexity of UL performance in daily life. As a solution to the multi-variable problem, it would be helpful to form categories of UL performance in daily life. If natural groupings occur among multiple UL performance variables calculated from accelerometry data, then these groupings could facilitate clinical decision making and implementation of upper limb performance data into routine rehabilitation care. In Chapter 3 we identify and define categories of UL performance in daily life in adults with and without neurological deficits of the upper limb. Prediction of motor outcomes after stroke have tremendous clinical utility, however there have been limited efforts to develop prediction models of upper limb performance (i.e., actual upper limb activity) in daily life after stroke. With advances in computing power, it is possible to capitalize on machine learning techniques to predict upper limb performance after stroke. These techniques allow for predicting a multivariate categorical outcome. This is important because it provides more information about the expected upper limb outcome to people with stroke, their families, and clinicians than a single continuous variable or a binary category (e.g., good or poor). Chapter 4 of this dissertation explores how different machine learning approaches can be used to understand the association between early clinical measures and participant demographics to the UL performance categories from a later post stroke time point. Our findings provide strong support for the importance of measuring recovery of the UL across ICF domains, not just with impairment and capacity level measures. Collectively this work provides preliminary measurement tools that could eventually be available to rehabilitation clinicians following subsequent validation efforts. Additionally, this work provides a rich exploration into the strengths, weaknesses, and limitations of analytical methods and their impact on validation efforts

Relationships between accelerometry and general compensatory movements of the upper limb after stroke

BACKGROUND: Standardized assessments are used in rehabilitation clinics after stroke to measure restoration versus compensatory movements of the upper limb. Accelerometry is an emerging tool that can bridge the gap between in- and out-of-clinic assessments of the upper limb, but is limited in that it currently does not capture the quality of a person\u27s movement, an important concept to assess compensation versus restoration. The purpose of this analysis was to characterize how accelerometer variables may reflect upper limb compensatory movement patterns after stroke. METHODS: This study was a secondary analysis of an existing data set from a Phase II, single-blind, randomized, parallel dose-response trial (NCT0114369). Sources of data utilized were: (1) a compensatory movement score derived from video analysis of the Action Research Arm Test (ARAT), and (2) calculated accelerometer variables quantifying time, magnitude and variability of upper limb movement from the same time point during study participation for both in-clinic and out-of-clinic recording periods. RESULTS: Participants had chronic upper limb paresis of mild to moderate severity. Compensatory movement scores varied across the sample, with a mean of 73.7 ± 33.6 and range from 11.5 to 188. Moderate correlations were observed between the compensatory movement score and each accelerometer variable. Accelerometer variables measured out-of-clinic had stronger relationships with compensatory movements, compared with accelerometer variables in-clinic. Variables quantifying time, magnitude, and variability of upper limb movement out-of-clinic had relationships to the compensatory movement score. CONCLUSIONS: Accelerometry is a tool that, while measuring movement quantity, can also reflect the use of general compensatory movement patterns of the upper limb in persons with chronic stroke. Individuals who move their limbs more in daily life with respect to time and variability tend to move with less movement compensations and more typical movement patterns. Likewise, individuals who move their paretic limbs less and their non-paretic limb more in daily life tend to move with more movement compensations at all joints in the paretic limb and less typical movement patterns

Risk Factor Analysis for 30-Day Readmission Rates of Newly Tracheostomized Children

Objectives: Pediatric patients undergo tracheostomy for a variety of reasons; however, medical complexity is common among these patients. Although tracheostomy may help to facilitate discharge, these patients may be at increased risk for hospital readmission. The purpose of this study was to evaluate our institutional rate of 30-day readmission for patients discharged with new tracheostomies and to identify risk factors associated with readmission. Study Design: A retrospective cohort study was conducted for all pediatric patients ages 0-18 years with new tracheostomies at our institution over a 36-month period. Methods: A chart review was performed for all newly tracheostomizedchildren from 2013 to 2016. We investigated documented readmissions within 30 days of discharge, reasons for readmission, demographic variables including age and ethnicity, initial discharge disposition, co-morbidities, and socioeconomic status estimated by mean household income by parental zip code. Results: 45 patients were discharged during the study time period. A total of 13 (28.9%) required readmission within 30 days of discharge. Among these 13 patients, the majority (61.5%) were readmitted for lower airway concerns, many (30.8%) were admitted for reasons unrelated to tracheostomy or respiratory concerns, and only one patient (7.7%) was readmitted for a reason related to tracheostomy itself (tracheostomalbreakdown). Age, ethnicity, discharge disposition, co-morbidities, and socioeconomic status were not associated with differences in readmission rates. Patients readmitted within 30 days had a higher number of admissions within the first year. Conclusion: Pediatric patients with new tracheostomies are at high risk for readmission after discharge from initial hospitalization. The readmissions are most likely secondary to underlying medical complexity rather than issues related specifically to the tracheostomy procedure.https://jdc.jefferson.edu/patientsafetyposters/1046/thumbnail.jp

Predicting later categories of upper limb activity from earlier clinical assessments following stroke: An exploratory analysis

BACKGROUND: Accelerometers allow for direct measurement of upper limb (UL) activity. Recently, multi-dimensional categories of UL performance have been formed to provide a more complete measure of UL use in daily life. Prediction of motor outcomes after stroke have tremendous clinical utility and a next step is to explore what factors might predict someone\u27s subsequent UL performance category. PURPOSE: To explore how different machine learning techniques can be used to understand how clinical measures and participant demographics captured early after stroke are associated with the subsequent UL performance categories. METHODS: This study analyzed data from two time points from a previous cohort (n = 54). Data used was participant characteristics and clinical measures from early after stroke and a previously established category of UL performance at a later post stroke time point. Different machine learning techniques (a single decision tree, bagged trees, and random forests) were used to build predictive models with different input variables. Model performance was quantified with the explanatory power (in-sample accuracy), predictive power (out-of-bag estimate of error), and variable importance. RESULTS: A total of seven models were built, including one single decision tree, three bagged trees, and three random forests. Measures of UL impairment and capacity were the most important predictors of the subsequent UL performance category, regardless of the machine learning algorithm used. Other non-motor clinical measures emerged as key predictors, while participant demographics predictors (with the exception of age) were generally less important across the models. Models built with the bagging algorithms outperformed the single decision tree for in-sample accuracy (26-30% better classification) but had only modest cross-validation accuracy (48-55% out of bag classification). CONCLUSIONS: UL clinical measures were the most important predictors of the subsequent UL performance category in this exploratory analysis regardless of the machine learning algorithm used. Interestingly, cognitive and affective measures emerged as important predictors when the number of input variables was expanded. These results reinforce that UL performance, in vivo, is not a simple product of body functions nor the capacity for movement, instead being a complex phenomenon dependent on many physiological and psychological factors. Utilizing machine learning, this exploratory analysis is a productive step toward the prediction of UL performance. Trial registration NA

Phylogenetic diversity, antimicrobial susceptibility and virulence gene profiles of Brachyspira hyodysenteriae isolates from pigs in Germany

Swine dysentery (SD) is an economically important diarrheal disease in pigs caused by different strongly hemolytic Brachyspira (B.) species, such as B. hyodysenteriae, B. suanatina and B. hampsonii. Possible associations of epidemiologic data, such as multilocus sequence types (STs) to virulence gene profiles and antimicrobial susceptibility are rather scarce, particularly for B. hyodysenteriae isolates from Germany. In this study, B. hyodysenteriae (n = 116) isolated from diarrheic pigs between 1990 and 2016 in Germany were investigated for their STs, susceptibility to the major drugs used for treatment of SD (tiamulin and valnemulin) and genes that were previously linked with virulence and encode for hemolysins (tlyA, tlyB, tlyC, hlyA, BHWA1_RS02885, BHWA1_RS09085, BHWA1_RS04705, and BHWA1_RS02195), outer membrane proteins (OMPs) (bhlp16, bhlp17.6, bhlp29.7, bhmp39f, and bhmp39h) as well as iron acquisition factors (ftnA and bitC). Multilocus sequence typing (MLST) revealed that 79.4% of the isolates belonged to only three STs, namely ST52 (41.4%), ST8 (12.1%), and ST112 (25.9%) which have been observed in other European countries before. Another 24 isolates belonged to twelve new STs (ST113-118, ST120-123, ST131, and ST193). The temporal distribution of STs revealed the presence of new STs as well as the regular presence of ST52 over three decades (1990s–2000s). The proportion of strains that showed resistance to both tiamulin und valnemulin (39.1%) varied considerably among the most frequent STs ranging from 0% (0/14 isolates resistant) in ST8 isolates to 46.7% (14/30), 52.1% (25/48), and 85.7% (6/7) in isolates belonging to ST112, ST52, and ST114, respectively. All hemolysin genes as well as the iron-related gene ftnA and the OMP gene bhlp29.7 were regularly present in the isolates, while the OMP genes bhlp17.6 and bhmp39h could not be detected. Sequence analysis of hemolysin genes of selected isolates revealed co-evolution of tlyB, BHWA1_RS02885, BHWA1_RS09085, and BHWA1_RS02195 with the core genome and suggested independent evolution of tlyA, tlyC, and hlyA. Our data indicate that in Germany, swine dysentery might be caused by a limited number of B. hyodysenteriae clonal groups. Major STs (ST8, ST52, and ST112) are shared with other countries in Europe suggesting a possible role of the European intra-Community trade of pigs in the dissemination of certain clones. The identification of several novel STs, some of which are single or double locus variants of ST52, may on the other hand hint towards an ongoing diversification of the pathogen in the studied area. The linkage of pleuromutilin susceptibility and sequence type of an isolate might reflect a clonal expansion of the underlying resistance mechanism, namely mutations in the ribosomal RNA genes. A linkage between single virulence-associated genes (VAGs) or even VAG patterns and the phylogenetic background of the isolates could not be established, since almost all VAGs were regularly present in the isolates

Implementation of wearable sensing technology for movement: Pushing forward into the routine physical rehabilitation care field

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples\u27 homes and communities

Syzygies of the secant variety of a curve

We show that the secant variety of a linearly normal smooth curve of degree at least 2g+3 is arithmetically Cohen-Macaulay, and we use this information to study the graded Betti numbers of the secant variety.Comment: 24 pages; minor revision and reorganizatio