On Fog and Forgetting: Using Obfuscated Memory as a Choreographic Tool

My choreographic curiosities lie in the various points of blurry overlap in this photo. As a dance-maker, I utilize characteristics of dissociation, out of body experiences, and obfuscated memory as tools for choreographing. This research has most recently manifested as a duet titled, underneath fog, then something bright, which attempts to choreographically enact rhythms of dissociative experiences. This photo of the duet is visually emblematic of the kinesthetic sensation I hope to curate for audiences of the work: it blurs senses of time and body to a point where we become unable to track where one thing ends and another begins.Ope

Phenomenology as a resource for patients

Patient support tools have drawn on a variety of disciplines, including psychotherapy, social psychology, and social care. One discipline that has not so far been used to support patients is philosophy. This paper proposes that a particular philosophical approach, phenomenology, could prove useful for patients, giving them tools to reflect on and expand their understanding of their illness. I present a framework for a resource that could help patients to philosophically examine their illness, its impact on their life, and its meaning. I explain the need for such a resource, provide philosophical grounding for it, and outline the epistemic and existential gains philosophy offers. Illness often begins as an intrusion on one's life but with time becomes a way of being. I argue that this transition impacts on core human features such as the experience of space and time, human abilities, and adaptability. It therefore requires philosophical analysis and response. The paper uses ideas from Husserl and Merleau-Ponty to present such a response in the form of a phenomenological toolkit for patients. The toolkit includes viewing illness as a form of phenomenological reduction, thematizing illness, and examining illness as altering the ill person's being in the world. I suggest that this toolkit could be offered to patients as a workshop, using phenomenological concepts, texts, and film clips to reflect on illness. I conclude by arguing that examining illness as a limit case of embodied existence deepens our understanding of phenomenology.© The Author 2012. Published by Oxford University Press, on behalf of the Journal of Medicine and Philosophy Inc. All rights reserved

Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data

Background Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance, empirical research, and clinical intervention. We sought to improve existing OOD electronic phenotypes by incorporating new data types beyond diagnostic codes and by applying several statistical and machine learning methods. Materials and Methods We developed an EHR dataset of emergency department visits involving OOD cases or patients considered at risk for an OOD and ascertained true OOD status through manual chart reviews. We developed and validated prediction models using Random Forest, Extreme Gradient Boost, and Elastic Net models that incorporated 717 features involving primary and second diagnoses, chief complaints, medications prescribed, vital signs, laboratory results, and procedural codes. We also developed models limited to single data types. Results A total of 1718 records involving 1485 patients were manually reviewed; 541 (36.4%) patients had one or more OOD. Prediction performance was similar for all models; sensitivity varied from 94% to 97%; and area under the receiver operating characteristic curve (AUC) was 98% for all methods. The primary diagnosis and chief complaint were the most important contributors to AUC performance; primary diagnoses and medication class contributed most to sensitivity; chief complaint, primary diagnosis, and vital signs were most important for specificity. Models limited to decision support data types available in real time demonstrated robust prediction performance. Conclusions Substantial prediction performance improvements were demonstrated for identifying OODs in EHR data. Our e-phenotypes could be applied in surveillance, retrospective empirical applications, or clinical decision support systems

Honors Voice Recital

Welcome to our KSU School of Music Honors Voice Recital. We are in the third year of presenting our talented vocal artists in a gala evening of beautiful song, beloved duets, and memorable ensembles. We are proud of our singers and the work they have done. Our voice faculty is a stellar group of artists and educators who are dedicated to each and every one of our singers. Thank you for attending tonight’s GALA event - KSU School of Music HONORS VOICE RECITAL. KSU Voice Professors Dr. Nathan Munson, Professor Jana Young,Professor Eileen Moremen, Professor Todd Wedge, and Professor Heather Witt.https://digitalcommons.kennesaw.edu/musicprograms/2294/thumbnail.jp

Feasibility and Safety of Multicenter Tissue and Biofluid Sampling for α-Synuclein in Parkinson's Disease: The Systemic Synuclein Sampling Study (S4)

BACKGROUND: α-synuclein is a lead Parkinson's disease (PD) biomarker. There are conflicting reports regarding accuracy of α-synuclein in different tissues and biofluids as a PD biomarker, and the within-subject anatomical distribution of α-synuclein is not well described. The Systemic Synuclein Sampling Study (S4) aims to address these gaps in knowledge. The S4 is a multicenter, cross-sectional, observational study evaluating α-synuclein in multiple tissues and biofluids in PD and healthy controls (HC). OBJECTIVE: To describe the baseline characteristics of the S4 cohort and safety and feasibility of this study. METHODS: Participants underwent motor and non-motor clinical assessments, dopamine transporter SPECT, biofluid collection (cerebrospinal fluid, saliva, and blood), and tissue biopsies (skin, sigmoid colon, and submandibular gland). Biopsy adequacy was determined based on presence of adequate target tissue. Tissue sections were stained with the 5C12 monoclonal antibody against unmodified α-synuclein. All specimens were acquired and processed in a standardized manner. Adverse events were systematically recorded. RESULTS: The final cohort consists of 82 participants (61 PD, 21 HC). In 68 subjects (83%), all types of specimens were obtained but only 50 (61%) of subjects had all specimens both collected and evaluable for α-synuclein. Mild adverse events were common, especially for submandibular gland biopsy, but only 1 severe adverse event occurred. CONCLUSION: Multicenter tissue and biofluid sampling for α-synuclein is feasible and generally safe. S4 will inform understanding of the concurrent distribution of α-synuclein pathology and biomarkers in biofluids and peripheral nervous system in PD

Blueberry anthocyanin intake attenuates the postprandial cardiometabolic effect of an energy-dense food challenge: results from a double blind, randomized controlled trial in metabolic syndrome participants

Background & aims: Whilst the cardioprotective effects of blueberry intake have been shown in prospective studies and short-term randomized controlled trials (RCTs), it is unknown whether anthocyanin-rich blueberries can attenuate the postprandial, cardiometabolic dysfunction which follows energy-dense food intakes; especially in at-risk populations. We therefore examined whether adding blueberries to a high-fat/high-sugar meal affected the postprandial cardiometabolic response over 24 h. Methods: A parallel, double-blind RCT (n = 45; age 63.4 ± 7.4 years; 64% male; BMI 31.4 ± 3.1 kg/m 2) was conducted in participants with metabolic syndrome. After baseline assessments, an energy-dense drink (969 Kcals, 64.5 g fat, 84.5 g carbohydrate, 17.9 g protein) was consumed with either 26 g (freeze-dried) blueberries (equivalent to 1 cup/150 g fresh blueberries) or 26 g isocaloric matched placebo. Repeat blood samples (30, 60, 90, 120, 180, 360 min and 24 h), a 24 h urine collection and vascular measures (at 3, 6, and 24 h) were performed. Insulin and glucose, lipoprotein levels, endothelial function (flow mediated dilatation (FMD)), aortic and systemic arterial stiffness (pulse wave velocity (PWV), Augmentation Index (AIx) respectively), blood pressure (BP), and anthocyanin metabolism (serum and 24 h urine) were assessed. Results: Blueberries favorably affected postprandial (0–24 h) concentrations of glucose (p < 0.001), insulin (p < 0.01), total cholesterol (p = 0.04), HDL-C, large HDL particles (L-HDL-P) (both p < 0.01), extra-large HDL particles (XL-HDL-P; p = 0.04) and Apo-A1 (p = 0.01), but not LDL-C, TG, or Apo-B. After a transient higher peak glucose concentration at 1 h after blueberry intake ([8.2 mmol/L, 95%CI: 7.7, 8.8] vs placebo [6.9 mmol/L, 95%CI: 6.4, 7.4]; p = 0.001), blueberries significantly attenuated 3 h glucose ([4.3 mmol/L, 95%CI: 3.8, 4.8] vs placebo [5.1 mmol/L, 95%CI: 4.6, 5.6]; p = 0.03) and insulin concentrations (blueberry: [23.4 pmol/L, 95%CI: 15.4, 31.3] vs placebo [52.9 pmol/L, 95%CI: 41.0, 64.8]; p = 0.0001). Blueberries also improved HDL-C ([1.12 mmol/L, 95%CI: 1.06, 1.19] vs placebo [1.08 mmol/L, 95%CI: 1.02, 1.14]; p = 0.04) at 90 min and XL-HDLP levels ([0.38 × 10-6, 95%CI: 0.35, 0.42] vs placebo [0.35 × 10-6, 95%CI: 0.32, 0.39]; p = 0.02) at 3 h. Likewise, significant improvements were observed 6 h after blueberries for HDL-C ([1.17 mmol/L, 95%CI: 1.11, 1.24] vs placebo [1.10 mmol/L, 95%CI: 1.03, 1.16]; p < 0.001), Apo-A1 ([1.37 mmol/L, 95%CI: 1.32, 1.41] vs placebo [1.31 mmol/L, 95%CI: 1.27, 1.35]; p = 0.003), L-HDLP ([0.70 × 10-6, 95%CI: 0.60, 0.81] vs placebo [0.59 × 10-6, 95%CI: 0.50, 0.68]; p = 0.003) and XL-HDLP ([0.44 × 10-6, 95%CI: 0.40, 0.48] vs placebo [0.40 × 10-6, 95%CI: 0.36, 0.44]; p < 0.001). Similarly, total cholesterol levels were significantly lower 24 h after blueberries ([4.9 mmol/L, 95%CI: 4.6, 5.1] vs placebo [5.0 mmol/L, 95%CI: 4.8, 5.3]; p = 0.04). Conversely, no effects were observed for FMD, PWV, AIx and BP. As anticipated, total anthocyanin-derived phenolic acid metabolite concentrations significantly increased in the 24 h after blueberry intake; especially hippuric acid (6-7-fold serum increase, 10-fold urinary increase). In exploratory analysis, a range of serum/urine metabolites were associated with favorable changes in total cholesterol, HDL-C, XL-HDLP and Apo-A1 (R = 0.43 to 0.50). Conclusions: For the first time, in an at-risk population, we show that single-exposure to the equivalent of 1 cup blueberries (provided as freeze-dried powder) attenuates the deleterious postprandial effects of consuming an energy-dense high-fat/high-sugar meal over 24 h; reducing insulinaemia and glucose levels, lowering cholesterol, and improving HDL-C, fractions of HDL-P and Apo-A1. Consequently, intake of anthocyanin-rich blueberries may reduce the acute cardiometabolic burden of energy-dense meals. Clinical trial registry: NCT02035592 at www.clinicaltrials.gov

2020 Collage Concert

An exciting highlight each season, Collage is the signature production of the School of Music and a major fundraising event for supporting scholarships for music students. This special performance features over 200 student and faculty performers and includes jazz, orchestra, choir, band, percussion, and opera selections for soloists, chamber groups, and ensembles. Special lighting effects and stage design combine with the diverse and exciting program presented as rapid-fire, flowing vignettes to create a truly unique performance.https://digitalcommons.kennesaw.edu/musicprograms/2295/thumbnail.jp

Aptamer-based multiplexed proteomic technology for biomarker discovery

Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine