Reliability of the Clinical Application of a Mechanical Inclinometer in Measuring Glenohumeral Motion

Objective: Establish intra- and inter-examiner reliability of glenohumeral range of motion (ROM) measures taken by a single-clinician using a mechanical inclinometer. Design: A single-session, repeated-measure, randomized, counterbalanced design. Setting: Athletic Training laboratory. Participants: Ten college-aged volunteers (9 right-hand dominant; 4 males, 6 females; age=23.2±2.4y, mass=73±16kg, height=170±8cm) without shoulder or neck injuries within one year. Interventions: Two Certified Athletic Trainers separately assessed passive glenohumeral (GH) internal (IR) and external (ER) rotation bilaterally. Each clinician secured the inclinometer to each subject’s distal forearm using elastic straps. Clinicians followed standard procedures for assessing ROM, with the participants supine on a standard treatment table with 90° of elbow flexion. A second investigator recorded the angle. Clinicians measured all shoulders once to assess inter-clinician reliability and eight shoulders twice to assess intra-clinician reliability. We used SPSS 14.0 (SPSS Inc., Chicago, IL) to calculate standard error of measure (SEM) and Intraclass Correlation Coefficients (ICC) to evaluate intra- and inter-clinician reliability. Main Outcome Measures: Dependent variables were degrees of IR, ER, glenohumeral internal rotation deficit (GIRD) and total arc of rotation. We calculated GIRD as the bilateral difference in IR (nondominant–dominant) and total arc for each shoulder (IR+ER). Results: Intra-clinician reliability for each examiner was excellent (ICC[1,1] range=0.90-0.96; SEM=2.2°-2.5°) for all measures. Examiners displayed excellent inter-clinician reliability (ICC[2,1] range=0.79-0.97; SEM=1.7°-3.0°) for all measures except nondominant IR which had good reliability(0.72). Conclusions: Results suggest that clinicians can achieve reliable measures of GH rotation and GIRD using a single-clinician technique and an inexpensive, readily available mechanical inclinometer.

Anticancer activity of 4-N gemcitabine analogues

Gemcitabine (2', 2'-difluoro-2'-deoxycytidine or dFdC) has become a standard chemotherapeutic agent in the treatment of several cellular and solid tumor- related malignancies. Gemcitabine's anti-cancer activity has been attributed to its inhibitory effects on the cell's DNA synthetic machinery resulting in the induction of cell arrest and apoptosis. Despite its broad application, treatment capacity with this drug is limited due to complicated administration schedules stemming from low bioavailability and tumor resistance associated with its rampant intracellular enzymatic inactivation. The aim of this study is to characterize the anti-cancer activity of novel designed and synthesized gemcitabine analogues, that were modified with long alkyl chains at the 4-amino group of the cytosine ring. This study proposes the use of these alternative derivatives of gemcitabine that not only uphold current drug standards for potency, but additionally confer chemical stability against enzymatic inactivation. During screening conducted to identifY prospective gem-analogue candidates, I observed the potent anticancer properties ofthree 4-N modified compounds on MCF-7 breast adenocarcinoma cells. Experiments described here with these compounds referred to as LCO, LCAO, and Gvaldo, evaluate their cytotoxicity on MCF-7 cells at the concentrations of 25flM and 2.5flM, and assess their inhibitory effects on DNA synthesis and cell cycle progression using sulphorhodamine B and bromodeoxyuridine assays as well as flow cytometric analyses, respectively. Among the compounds tested, LCO was shown to be most active inhibitor of DNA synthesis (a=.05; p<.OOl) as reflected as a distinct GO/Gl versus S-phase arrest in the 25flM and 2.5flM treatments, respectively. Together, these experiments provide preliminary evidence for the clinical application of LCO-like gemcitabine derivatives as a novel treatment for breast cancer.

A novel signal processing method for intraoperative neurophysiological monitoring in spinal surgeries

Intraoperative neurophysiologic monitoring is an integral part of spinal surgeries and involves the recording of somatosensory evoked potentials (SSEP). However, clinical application of IONM still requires anywhere between 200 to 2000 trials to obtain an SSEP signal, which is excessive and introduces a significant delay during surgery to detect a possible neurological damage. The aim of this study is to develop a means to obtain the SSEP using a much less, twelve number of recordings. The preliminary step involved was to distinguish the SSEP with the ongoing brain activity. We first establish that the brain activity is indeed quasi-stationary whereas an SSEP is expected to be identical every time a trial is recorded. An algorithm was developed using Chebychev time windowing for preconditioning of SSEP trials to retain the morphological characteristics of somatosensory evoked potentials (SSEP). This preconditioning was followed by the application of a principal component analysis (PCA)-based algorithm utilizing quasi-stationarity of EEG on 12 preconditioned trials. A unique Walsh transform operation was then used to identify the position of the SSEP event. An alarm is raised when there is a 10% time in latency deviation and/or 50% peak-to-peak amplitude deviation, as per the clinical requirements. The algorithm shows consistency in the results in monitoring SSEP in up to 6-hour surgical procedures even under this significantly reduced number of trials. In this study, the analysis was performed on the data recorded in 29 patients undergoing surgery during which the posterior tibial nerve was stimulated and SSEP response was recorded from scalp. This method is shown empirically to be more clinically viable than present day approaches. In all 29 cases, the algorithm takes 4sec to extract an SSEP signal, as compared to conventional methods, which take several minutes. The monitoring process using the algorithm was successful and proved conclusive under the clinical constraints throughout the different surgical procedures with an accuracy of 91.5%. Higher accuracy and faster execution time, observed in the present study, in determining the SSEP signals provide a much improved and effective neurophysiological monitoring process.