The authors would like to thank Ivan Hanigan for his support in extracting and interpreting the ultraviolet radiation satellite data. The work was supported by the NHMRC Career Development Award (Clinical) to HB [ID628856], NHMRC Project Grant [1032484], NHMRC Center for Research Excellence [Grant ID 1001216] and the MSBase Foundation. The MSBase Foundation is a not-for-profit organization that receives support from Merck Serono, Biogen Idec, Novartis Pharma, Bayer-Schering, Sanofi-Aventis and BioCSL. RL is supported by a NHMRC Career Development Award [ID 1004898].

NOTE: Each step described corresponds to a section of Stata code with the same number in the code file provided. Stata command names have been italicised in the following protocol.
1. Prepare and Plot the Observed Relapse Onset Data
<ol>
	<li>Open a do file by clicking on the &#34;New Do-file Editor&#34; button and use the generate command to calculate the number of relapse onsets dated to each of the twelve calendar months for each of the three geographic levels to be modelled: location, hemisphere and global. Action command by clicking the &#34;Execute (do)&#34; do-file action button in the do-file.</li>
	<li>Use the swilk orsktest command to test the underlying distribution of relapse counts for normality using a Shapiro-Wilk or modified Jarque-Bera test for location aggregate relapse data or disaggregate patient level relapse data respectively. Select code and click &#34;Execute (do)&#34;. 
	NOTE: In the presence of significant skew, apply a natural log transformation and subsequently test the log-transformed relapse count variable for approximate normality by reapplying the Shapiro-Wilk or modified Jarque-Bera test as appropriate.38,39</li>
	<li>Use the generate command to create a new variable &#34;north_month&#34; for southern hemisphere calendar months offset by +6 to allow plotting of both northern and southern hemisphere relapses by season along the same horizontal axis. Select code and click &#34;Execute (do)&#34;.
	<ol>
		<li>Graph a scatterplot of observed monthly relapse onsets with relapse frequency on the y-axis and calendar month on the x-axis for each hemisphere using the twoway scatter command. Repeat for each location. Observe pattern of peaks and troughs in relapse onset over the calendar year by viewing each plot in the graph viewer the automatically opens to screen.</li>
	</ol>
	</li>
	<li>Use the radar command to draw radar plots of the distribution of relapse frequency by calendar month with each radar axis capturing a single month ordered in a clockwise manner. Select code and click &#34;Execute (do)&#34;.
	<ol>
		<li>Repeat for all sites. Observe pattern of peaks and troughs in relapse onset over the calendar year by viewing each plot in the graph viewer the automatically opens to screen.</li>
	</ol>
	</li>
	<li>Run the seast command to apply an Edward&#39;s test of seasonality across the observed relapse data.40-42 Repeat for all geographic levels.</li>
</ol>
2. Model Building and Selection
<ol>
	<li>Use the generate command to specify the annual cycle sine and cosine trigonometric functions to be used in the regression. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Use the regress command specify the form of the base model with relapse count as the dependent outcome variable and the sine and cosine terms calculated in step 2.1 as the primary explanatory variables.
	<ol>
		<li>Add location-specific UVR37 to the base model as an additional adjusting covariate and use the analytic weight aweight option to weight the model for the number of patients contributed by each location. Select code and click &#34;Execute (do)&#34;. 
		NOTE: Record the model coefficient of determination (R2) and the residual error in the results window that automatically opens to screen. Ultraviolet radiation: Daily average erythemally-weighted ambient UVR for each month from 1979 to 2004 inclusive was sourced from the National Aeronautics and Space Administration Earth Probe Total Ozone Mapping Spectrometer for all individual locations included in the analysis. 37</li>
	</ol>
	</li>
	<li>Store the model predicted monthly log(relapse) using the predict command. Convert log relapses back to integer relapse counts by exponentiating the log(relapse) term using the generate command. Select code and click &#34;Execute (do)&#34;. Repeat for all sites.</li>
	<li>Overlay the exponentiated predicted monthly relapse estimates from 2.3 over the observed monthly relapse data using the twoway scatter command. Select code and click &#34;Execute (do)&#34;.
	<ol>
		<li>Repeat for all sites. View each plot in the graph viewer.</li>
	</ol>
	</li>
	<li>Use the regress command to expand the model specified in 2.2 by adding an additional harmonic sine/cosine pair. Select code and click &#34;Execute (do)&#34;. 
	NOTE: Record the residual error and the coefficient of determination. Save and transform model estimates as per 2.3 and plot model estimates over observed data as per 2.4. Repeat for all sites.</li>
	<li>Use the regress command to further expand the model specified in 2.2 by adding two additional harmonic sine/cosine pairs. Select code and click &#34;Execute (do)&#34;. 
	NOTE: Record the residuals and the coefficient of determination. Compare this model directly with the base model using a likelihood ratio test. Use the estat ic post-estimation command to generate Akaike and Bayesian Information Criteria. Save and transform model estimates as per 2.3 and plot model estimates over observed data as per 2.4. Repeat for all geographic levels.</li>
</ol>
3. Estimating Peak Relapse Probability
<ol>
	<li>Use the non-linear combination of estimators function (nlcom) to calculate the point estimate and 95% confidence interval for the phase-shift, using the best-fitting model identified from steps 2.1 through 2.6. Select code and click &#34;Execute (do)&#34;.
	<ol>
		<li>Convert these point estimates and associated confidence intervals to numbers representing calendar dates of peak relapse frequency (Tmax) and trough relapse frequency (Tmin) , where 1=1st January and 365=31st December and Tmax = phase-shift + (365/4) and Tmin = phase-shift + ((365/4)*3). Repeat for all geographic levels. Match Tmax and Tmin to a calendar date via the Excel look-up file.</li>
	</ol>
	</li>
	<li>Use the generate command to calculate peak-to-trough difference (Tmax minus Tmin) for each location, standardized for every 100 patients per site. Use a Wilcoxon rank-sum test to compare standardized peak-to-trough difference by latitude range. Select code and click &#34;Execute (do)&#34;.</li>
</ol>
4. Modelling Ultraviolet Radiation Data
<ol>
	<li>Run use command to load the UVR data. Calculate median monthly UVR for each location using the egen command. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Graph a scatterplot of monthly UVR (y-axis) by calendar month (x-axis) for each location using the twoway scatter function. View each plot in the graph viewer the automatically opens to screen.</li>
	<li>Repeat step 1.2 for the UVR data and use the regress command to specify a base model of location-level annual UVR trend where monthly UVR is specified as the dependent outcome variables and the sine and cosine trigonometric functions specified in step 2.1 are incorporated into the model as the explanatory variables.</li>
	<li>Repeat steps 2.4 through 2.6 for the UVR model and limited to the location-specific models only. This involves rerunning the twoway scatter command to overlay predicted estimates on observed data and using the regress command to run the expanded harmonic model alternatives.</li>
	<li>Using the best-fitting model of location-specific monthly UVR identified in steps 4.2 through 4.4 use the generate command to calculate the phase-shift point estimate and associated 95% confidence interval for UVR by again applying the double-angle formulae specified in step 3.1. Calculate Tmin (date of trough UVR) for each location using the formula described in step 3.1. Select code and click &#34;Execute (do)&#34;.</li>
</ol>
5. Modelling UVR-trough-to-relapse-peak Lag
<ol>
	<li>Append the model-estimated dates of seasonal UVR trough from step 4.5 and relapse peak dates from step 3.1 for each location using the merge command. Use the generate command to calculate the time lapsed in months between UVR trough date and subsequent relapse peak date. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Use the sktest command to test the UVR-trough-to-relapse-peak lag variable for significant departures from normality using a Shapiro-Wilk test Select code and click &#34;Execute (do)&#34;.</li>
	<li>Append location-level latitude data to dataset using the merge command. Convert relative latitude to absolute latitude using the abs(x) function. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Using the regress command, test the linearity of the relationship between lag and absolute latitude by running both linear and quadratic regressions and comparing residuals. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Using regress, specify a linear mean regression model with UVR-trough-to-relapse-peak lag as the dependent outcome variable and absolute latitude in units of 10 degrees as the predictor variable. Weight the model for the number of patients contributed by each location using the aweights regress option. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Use the twoway scatter command to plot absolute latitude on the y-axis against UVR-trough-to-relapse-lag in months on the x-axis. Overlay a line of best fit using lfit graph option. Visualise the relative patient weights of each location using the aweight analytical weights option. Select code and click &#34;Execute (do)&#34;.</li>
</ol>
6. Sensitivity Analyses of Patient-level Relapse Propensities
<ol>
	<li>Use the mepossion command to specify a mixed-effects Poisson regression where monthly relapse count is the dependent outcome variable, the sine and cosine trigonometric functions specified in step 2.1 are again incorporated into the model as the fixed variables, baseline EDSS, age at MS onset and prior exposure to MS specific disease-modifying treatment are included as potential confounders and unique patient identifier is specified as a random effect. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Repeat steps 2.4 through 2.6 to identify the best-fitting Poisson model. This involves rerunning the twoway scatter command to overlay predicted estimates on observed data and using the regress command to run the expanded harmonic model alternatives.</li>
	<li>Use the non-linear combination of estimators function (nlcom) to calculate the point estimate and 95% confidence interval for the phase-shift and calculate the date of peak relapse frequency. Compare results with the primary analysis.</li>
	<li>Use the generate command to recalculate UVR-trough-to-relapse-peak lag in months for each location as described in step 5.1, using the patient-level Poisson model estimates of peak relapse date derived in step 6.3. Select code and click &#34;Execute (do)&#34;.</li>
	<li>Use the regress command to remodel absolute latitude as a predictor of lag as described in step 5.5 and compare results with the primary analysis. Select code and click &#34;Execute (do)&#34;.</li>
</ol>

Tim Spelman received honoraria for consultancy and funding for travel from Biogen Idec Inc; Orla Gray received travel support from Biogen Idec, Merck Serono and Novartis; compensation for serving on scientific advisory boards from Biogen Idec, Genzyme, Novartis and Merck Serono; Robyn Lucas did not disclose any competing interests and Helmut Butzkueven received compensation for serving on scientific advisory boards and as a consultant for Biogen Idec and Novartis; speaker honoraria from Biogen Idec Australia, Merck Serono Australia, and Novartis Australia; travel support from Biogen Idec Australia and Merck Serono Australia; research support from CASS Foundation (Australia), Merck Serono Australia, the Royal Melbourne Hospital Friends of the Neurosciences Foundation, and the University of Melbourne.

The protocol described herein details a systematic regression based technique, guided by visual plot analysis, of global MS relapse onset data. It takes as a starting point a relatively simple descriptive analysis of relapse data from 20 countries across both hemispheres, allowing the user to explore theories regarding the temporality of relapse onset timing in MS and testing these theories formally through the use of trigonometric models. Through a step-wise process of first plotting global relapse onset data and then s...

The most common form of multiple sclerosis (MS) is Relapsing Remitting Multiple Sclerosis (RRMS). RRMS is characterized by episodic deteriorations in neurological function, followed by partial or complete recovery. Globally, the incidence and prevalence of MS increase with increasing distance away from the equator in both hemispheres.1-3 Whether the frequency of relapse events that occur specifically in RRMS also vary with latitude, and whether there is any underlying seasonal variation in any such association, remains unclear. To date studies exploring seasonality in relapse timing have been limited to single clinical centers, limiting any inferences regarding seasonal trends in relapse timing to solitary geographical locations and thus unable to explore broader latitudinal influences. 4-14 These studies have been further limited by small sample sizes and sparse relapse data. A 2000 meta-analysis of ten studies from clinical centres in Europe, the United States and Canada, where each study included a minimum of thirty cases reporting the season-of-onset of relapses, described a clear seasonal trend in the timing of relapse onset, with relapses peaking in spring and with a winter trough4. Similar cyclical annual trends in onset have been observed in subsequent, albeit smaller, studies in both Japan15 and Spain16. However, a comparable United States study failed to corroborate this pattern17. To date, these studies and observations have been limited to the northern hemisphere. The MSBase study group recently analyzed a large global dataset of MS relapses across both northern and southern hemispheres to explore seasonal trends in the timing of relapse onset in addition to latitudinal influences on the relationship between peak relapse probability and seasonal ultraviolet radiation (UVR) trough18. Central to these methods was the application of trigonometric regression to visualize and evaluate trends in the timing of relapse onset and UVR distributions.
The overall goal of this study was to test the hypothesis that temporal variation in the timing of relapse onset in MS varied predictably with season in both the northern and southern hemispheres and this seasonality was influenced by latitude. The rationale for the use of trigonometric modelling to investigate these questions was its flexibility for characterizing two- or three-dimensional phenomena that are known or suspected to describe discrete, predictable and consistent shapes or patterns, such as the annual cycle of peaks and troughs commonly observed in biological or epidemiological phenomena possessing seasonality.19-22 A disadvantage of conventional time-series analyses, including Fourier analysis, is the presumption that time series are often characterized by stochastic processes.21,23,24 By contrast, incorporating trigonometric functions into a regression type model has the advantage of both facilitating exploration of regular and systematic structures in periodic data whilst exploiting the regression model structure to explore other correlates or adjust for confounders of seasonality.
Trigonometric regression has previously been used widely in the medical epidemiological literature to explore temporality in topics as diverse infectious disease outbreak detection, the role of circadian rhythms in everything from autonomic nervous system dysfunction to preterm placental abruption through to seasonal correlates of congenital malformations and the timing of presentations of accident and emergency.25-32 Such modelling typically demands larger sample sizes than more conventional time-series analyses and as such this is the first time it has been applied to a global dataset of MS relapse onset. Trigonometric regression as described here is suitable tool for investigators exploring any phenomena which is known to or suspected of cycling systematically over time. Not only can such modelling help characterise and visualize these patterns, it further permits the user to explore potential drivers and correlates of these trends.
Regarding the specific example of MS relapse onset presented here, the use of scatter and residual plots to visualize and assess how closely a hypothesized trigonometric model form fits the data constitutes the critical step in determining: 1) whether the observed data provide sufficient evidence to support a hypothesis of seasonality or other temporal trends in the timing of relapse onset; and 2) whether the frequency and arrangement of sine and cosine functions which define a particular trigonometric model is adequate to permit use of this model for subsequent inference and prediction. Regression modelling also permits control for important confounders of any observed seasonal or latitudinal effect such as patient-level propensities for relapse, particularly factors which in themselves are time-varying such as the duration of pre-relapse exposure to disease-modifying drug (DMD) treatment. Isolating independent geographic and temporal predictors and correlates of relapse onset timing in MS has the potential to guide biological investigation into the mechanisms of relapse events which in turn may inform the development of future treatment interventions aimed at preventing or delaying disease exacerbation.
The MSBase Registry
MS patients contributing relapse data to this analysis were sourced from the international MSBase registry. Established in 2004, the registry longitudinally collates demographic, disease activity, clinical examination and investigation characteristics and metrics from consenting patients attending MS clinic using an internet-based, physician-owned and operated system.33 Member centers follow a common protocol that defines the minimum dataset required to be uploaded at agreed regular intervals to ensure outcome data such as relapse events are consistently and prospectively compiled. The date of relapse onset is included as a mandatory minimum dataset variable. In addition relevant clinical data associated with these relapse events is commonly collected including corticosteroid treatment and functional system affected. The use of the common iMed data entry system further ensures a unified approach across centers to data collection and reporting. This project holds Human Research Ethics Committee approval or exemption at each contributing center. Informed consent according to local laws from all patients included in the analysis is mandatory.
Inclusion criteria
A total of 9811 patients contributing 32,762 relapse events were included in the analysis. Clinical MS centres with a minimum of 20 registered patients consented, uploaded and tracked in the registry as of the 1st December 2013 (date of data compilation) were eligible for inclusion in the analysis. To ensure all relapse events included in the analysis were prospectively observed, only relapse onsets dated subsequent to the first recorded patient disability assessment (using the Kurtzke Expanded Disability Status Score (EDSS)) were included in the analysis. All patients contributing relapse data to the analysis satisfied formal diagnostic criteria for MS.34,35
Outcome measures
This study considered two primary outcomes: 1) whether there was temporal variation in the probability of relapse onset at the level of the geographic location, the hemisphere and/or globally; and 2) whether there was a relationship between latitude and the lag, in months, between the timing of seasonal UVR trough and the subsequent peak relapse probability date. The MSBase Study group hypothesized that as absolute vitamin D levels are lower in regions further away from the equator and location-specific seasonal population level vitamin D nadirs are likely reached earlier following the winter solstice in such distal locations, then the effect of low vitamin D levels on increased MS relapse probability would similarly describe such temporal and latitudinal patterns.
Relapse definition and dates
A relapse was defined as occurrence of new symptoms or exacerbation of existing symptoms persisting for at least 24 hours, in the absence of concurrent illness or fever, and occurring at least 30 days after a previous attack. This definition has previously been applied in an MSBase relapse phenotype analysis. 36 The follow-up period for each eligible patient across which relapse events could be observed was defined as the period spanning the date of first EDSS assessment through to the date of the most recent EDSS assessment recorded in the registry prior to the data of data extract and compilation. In instances where the exact day of relapse onset was unavailable or unable to be determined for a particular month, clinics used either the 1st or 15th day of the month as default dates. Of the 32,762 relapses analysed in this report, 7913 (24.2%) and 4594 (14.0%) were recorded on the 1st and 15th day of the month respectively, significantly higher than the proportions recorded on any other day of the month which ranged from 0.8% through 5.6%. To correct for this, relapses recorded on either the 1st of 15th day of the month were randomized to a day within a 15 day interval either side of both these default dates. The internal validity of this approach was confirmed via sensitivity analyses which demonstrated that the modelled estimate of peak relapse date under default date randomization was not significantly different from a model using either the original reported dates or excluding default dates entirely.

<table border="0" cellpadding="0" cellspacing="0" width="816">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Stata SE Version 13</td>
			<td style="width:136px;">StataCorp, College Station, Texas</td>
			<td style="width:119px;">Version 13</td>
			<td style="width:345px;">Statistical analysis software used for analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Microsoft Excel 2010</td>
			<td style="width:136px;">Microsoft</td>
			<td style="width:119px;">2010</td>
			<td>Spreadsheet program for calendar date look-up</td>
		</tr>
	</tbody>
</table>

a method of trigonometric modelling of seasonal variation demonstrated with multiple sclerosis relapse data

This report describes a novel Stata-based application of trigonometric regression modelling to 55 years of multiple sclerosis relapse data from 46 clinical centers across 20 countries located in both hemispheres. Central to the success of this method was the strategic use of plot analysis to guide and corroborate the statistical regression modelling. Initial plot analysis was necessary for establishing realistic hypotheses regarding the presence and structural form of seasonal and latitudinal influences on relapse probability and then testing the performance of the resultant models. Trigonometric regression was then necessary to quantify these relationships, adjust for important confounders and provide a measure of certainty as to how plausible these associations were. Synchronization of graphing techniques with regression modelling permitted a systematic refinement of models until best-fit convergence was achieved, enabling novel inferences to be made regarding the independent influence of both season and latitude in predicting relapse onset timing in MS. These methods have the potential for application across other complex disease and epidemiological phenomena suspected or known to vary systematically with season and/or geographic location.

The application of trigonometric regression to 32,762 relapse events sourced from 46 clinical centers across 20 countries was the basis for providing a defensible statistical argument for the observation that the timing of relapse onset in MS is cyclic and seasonal across both hemispheres and that the duration between seasonal UVR trough and subsequent relapse peak correlates with latitude. Critical to this was the reliance upon plot analysis to guide the necessarily iterative process of model development, evaluation and...

Watch this Scientific Journal Video about A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data at JoVE.com

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Combining plot analysis with trigonometric regression is a robust method for exploring complex, cyclical phenomena such as relapse onset timing in multiple sclerosis (MS). This method enabled unbiased characterisation of seasonal trends in relapse onset permitting novel inferences around the influence of seasonal variation, ultraviolet radiation (UVR) and latitude.

This report describes a novel Stata-based application of trigonometric regression modelling to  55 years of multiple sclerosis relapse data from 46 ...

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10.6K Views.  Royal Melbourne Hospital. Combining plot analysis with trigonometric regression is a robust method for exploring complex, cyclical phenomena such as relapse onset timing in multiple sclerosis (MS). This method enabled unbiased characterisation of seasonal trends in relapse onset permitting novel inferences around the influence of seasonal variation, ultraviolet radiation (UVR) and latitude. 

Video: A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Protocol for Comprehensive Assessment of Bulbar Dysfunction in Amyotrophic Lateral Sclerosis (ALS)

Improved methods for assessing bulbar impairment are necessary for expediting diagnosis of bulbar dysfunction in ALS, for predicting disease progression across speech subsystems, and for addressing the critical need for sensitive outcome measures for ongoing experimental treatment trials. To address this need, we are obtaining longitudinal profiles of bulbar impairment in 100 individuals based on a comprehensive instrumentation-based assessment that yield objective measures. Using instrumental approaches to quantify speech-related behaviors is very important in a field that has primarily relied on subjective, auditory-perceptual forms of speech assessment1. Our assessment protocol measures performance across all of the speech subsystems, which include respiratory, phonatory (laryngeal), resonatory (velopharyngeal), and articulatory. The articulatory subsystem is divided into the facial components (jaw and lip), and the tongue. Prior research has suggested that each speech subsystem responds differently to neurological diseases such as ALS. The current protocol is designed to test the performance of each speech subsystem as independently from other subsystems as possible. The speech subsystems are evaluated in the context of more global changes to speech performance. These speech system level variables include speaking rate and intelligibility of speech.
The protocol requires specialized instrumentation, and commercial and custom software. The respiratory, phonatory, and resonatory subsystems are evaluated using pressure-flow (aerodynamic) and acoustic methods. The articulatory subsystem is assessed using 3D motion tracking techniques. The objective measures that are used to quantify bulbar impairment have been well established in the speech literature and show sensitivity to changes in bulbar function with disease progression. The result of the assessment is a comprehensive, across-subsystem performance profile for each participant. The profile, when compared to the same measures obtained from healthy controls, is used for diagnostic purposes. Currently, we are testing the sensitivity and specificity of these measures for diagnosis of ALS and for predicting the rate of disease progression. In the long term, the more refined endophenotype of bulbar ALS derived from this work is expected to strengthen future efforts to identify the genetic loci of ALS and improve diagnostic and treatment specificity of the disease as a whole. The objective assessment that is demonstrated in this video may be used to assess a broad range of speech motor impairments, including those related to stroke, traumatic brain injury, multiple sclerosis, and Parkinson disease.

A Protocol for Comprehensive Assessment of Bulbar Dysfunction in Amyotrophic Lateral Sclerosis ALS

Objective assessments of the physiological mechanisms that support speech are needed to monitor disease onset and progression in persons with ALS and to quantify treatment effects in clinical trials. In this video, we present a comprehensive, instrumentation-based protocol for quantifying speech motor performance in clinical populations.

Improved methods for assessing bulbar impairment are necessary for expediting diagnosis of bulbar dysfunction in ALS, for predicting disease progression ...

Clinical Testing and Spinal Cord Removal in a Mouse Model for Amyotrophic Lateral Sclerosis (ALS)

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder resulting in progressive degeneration of motoneurons. Peak of onset is around 60 years for the sporadic disease and around 50 years for the familial disease. Due to its progressive course, 50% of the patients die within 30 months of symptom onset. In order to evaluate novel treatment options for this disease, genetic mouse models of ALS have been generated based on human familial mutations in the SOD gene, such as the SOD1 (G93A) mutation. Most important aspects that have to be evaluated in the model are overall survival, clinical course and motor function. Here, we demonstrate the clinical evaluation, show the conduction of two behavioural motor tests and provide quantitative scoring systems for all parameters. Because an in depth analysis of the ALS mouse model usually requires an immunohistochemical examination of the spinal cord, we demonstrate its preparation in detail applying the dorsal laminectomy method. Exemplary histological findings are demonstrated. The comprehensive application of the depicted examination methods in studies on the mouse model of ALS will enable the researcher to reliably test future therapeutic options which can provide a basis for later human clinical trials.

Clinical Testing and Spinal Cord Removal in a Mouse Model for Amyotrophic Lateral Sclerosis ALS

A mouse model for amyotrophic lateral sclerosis (ALS) is examined clinically and behaviorally. As a prerequisite for an accompanying immunohistological analysis the preparation of the spinal cord is depicted in detail.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder resulting in progressive degeneration of motoneurons. Peak of onset is around 60 ...

Utility of Dissociated Intrinsic Hand Muscle Atrophy in the Diagnosis of Amyotrophic Lateral Sclerosis

The split hand phenomenon refers to predominant wasting of thenar muscles and is an early and specific feature of amyotrophic lateral sclerosis (ALS). A novel split hand index (SI) was developed to quantify the split hand phenomenon, and its diagnostic utility was assessed in ALS patients. The split hand index was derived by dividing the product of the compound muscle action potential (CMAP) amplitude recorded over the abductor pollicis brevis and first dorsal interosseous muscles by the CMAP amplitude recorded over the abductor digiti minimi muscle. In order to assess the diagnostic utility of the split hand index, ALS patients were prospectively assessed and their results were compared to neuromuscular disorder patients. The split hand index was significantly reduced in ALS when compared to neuromuscular disorder patients (P&#60;0.0001). Limb-onset ALS patients exhibited the greatest reduction in the split&#160;hand index, and a value of 5.2 or less reliably differentiated ALS from other neuromuscular disorders. Consequently, the split&#160;hand index appears to be a novel diagnostic biomarker for ALS, perhaps facilitating an earlier diagnosis.

Dissociated atrophy of intrinsic hand muscles, termed the split hand, appears to be a specific feature of amyotrophic lateral sclerosis (ALS).&#160;Consequently, a novel neurodiagnostic test, termed the split hand&#160;index, was developed to quantify the clinical phenomenon of the split hand, which differentiated ALS from mimic disorders.

The split hand phenomenon refers to predominant wasting of thenar muscles and is an early and specific feature of amyotrophic lateral sclerosis (ALS). A ...

The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool

Precise measurement of neurological and neuropsychological impairment and disability in multiple sclerosis is challenging. We report a new test, the Multiple Sclerosis Performance Test (MSPT), which represents a new approach to quantifying MS related disability. The MSPT takes advantage of advances in computer technology, information technology, biomechanics, and clinical measurement science. The resulting MSPT represents a computer-based platform for precise, valid measurement of MS severity. Based on, but extending the Multiple Sclerosis Functional Composite (MSFC), the MSPT provides precise, quantitative data on walking speed, balance, manual dexterity, visual function, and cognitive processing speed. The MSPT was tested by 51 MS patients and 49 healthy controls (HC). MSPT scores were highly reproducible, correlated strongly with technician-administered test scores, discriminated MS from HC and severe from mild MS, and correlated with patient reported outcomes. Measures of reliability, sensitivity, and clinical meaning for MSPT scores were favorable compared with technician-based testing. The MSPT is a potentially transformative approach for collecting MS disability outcome data for patient care and research. Because the testing is computer-based, test performance can be analyzed in traditional or novel ways and data can be directly entered into research or clinical databases. The MSPT could be widely disseminated to clinicians in practice settings who are not connected to clinical trial performance sites or who are practicing in rural settings, drastically improving access to clinical trials for clinicians and patients. The MSPT could be adapted to out of clinic settings, like the patient&#8217;s home, thereby providing more meaningful real world data. The MSPT represents a new paradigm for neuroperformance testing. This method could have the same transformative effect on clinical care and research in MS as standardized computer-adapted testing has had in the education field, with clear potential to accelerate progress in clinical care and research.

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Precise measurement of neurological and neuropsychological impairment and disability in multiple sclerosis is challenging. We report methodologic details on a new test, the Multiple Sclerosis Performance Test (MSPT). This new approach to the objective of quantification of MS related disability provides a computer-based platform for precise, valid measurement of MS severity.

Precise measurement of neurological and neuropsychological impairment and disability in multiple sclerosis is challenging. We report a new test, the ...

Adapted Resistance Training Improves Strength in Eight Weeks in Individuals with Multiple Sclerosis

Hip weakness is a common symptom affecting walking ability in people with multiple sclerosis (MS). It is known that resistance strength training (RST) can improve strength in individuals with MS, however; it remains unclear the duration of RST that is needed to make strength gains and how to adapt hip strengthening exercises for individuals of varying strength using only resistance bands. This paper describes the methodology to set up and implement an adapted resistance strength training program, using resistance bands, for individuals with MS. Directions for pre- and post-strength tests to evaluate efficacy of the strength-training program are included. Safety features and detailed instructions outline the weekly program content and progression. Current evidence is presented showing that significant strength gains can be made within 8 weeks of starting a RST program. Evidence is also presented showing that resistance strength training can be successfully adapted for individuals with MS of varying strength with little equipment.

Hip weakness is a common symptom affecting walking ability in people with multiple sclerosis. Isolated muscle strengthening is a useful method to target specific weaknesses. This protocol describes a progressive resistance-training program using exercise bands to increase hip muscle strength.

Hip weakness is a common symptom affecting walking ability in people with multiple sclerosis (MS). It is known that resistance strength training (RST) can ...

A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation (tDCS) in Multiple Sclerosis (MS)

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that uses low amplitude direct currents to alter cortical excitability. With well-established safety and tolerability, tDCS has been found to have the potential to ameliorate symptoms such as depression and pain in a range of conditions as well as to enhance outcomes of cognitive and physical training. However, effects are cumulative, requiring treatments that can span weeks or months and frequent, repeated visits to the clinic. The cost in terms of time and travel is often prohibitive for many participants, and ultimately limits real-world access. 
Following guidelines for remote tDCS application, we propose a protocol that would allow remote (in-home) participation that uses specially-designed devices for supervised use with materials modified for patient use, and real-time monitoring through a telemedicine video conferencing platform. We have developed structured training procedures and clear, detailed instructional materials to allow for self- or proxy-administration while supervised remotely in real-time. The protocol is designed to have a series of checkpoints, addressing attendance and tolerability of the session, to be met in order to continue to the next step. The feasibility of this protocol was then piloted for clinical use in an open label study of remotely-supervised tDCS in multiple sclerosis (MS). This protocol can be widely used for clinical study of tDCS.

A Protocol for the Use of Remotely-Supervised Transcranial Direct Current Stimulation tDCS in Multiple Sclerosis MS

The goal of this pilot study is to describe a protocol for the remotely-supervised delivery of transcranial direct current stimulation (tDCS) so that the procedure maintains standards of in-clinic practice, including safety, reproducibility, and tolerability. The feasibility of this protocol was tested in participants with multiple sclerosis (MS).

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that uses low amplitude direct currents to alter cortical ...

Bioluminescence and Near-infrared Imaging of Optic Neuritis and Brain Inflammation in the EAE Model of Multiple Sclerosis in Mice

Experimental autoimmune encephalomyelitis (EAE) in SJL/J mice is a model for relapsing-remitting multiple sclerosis (RRMS). Clinical EAE scores describing motor function deficits are basic readouts of the immune-mediated inflammation of the spinal cord. However, scores and body weight do not allow for an in vivo assessment of brain inflammation and optic neuritis. The latter is an early and frequent manifestation in about 2/3 of MS patients. Here, we show methods for bioluminescence and near-infrared live imaging to assess EAE evoked optic neuritis, brain inflammation, and blood-brain barrier (BBB) disruption in living mice using an in vivo imaging system. A bioluminescent substrate activated by oxidases primarily showed optic neuritis. The signal was specific and allowed the visualization of medication effects and disease time courses, which paralleled the clinical scores. Pegylated fluorescent nanoparticles that remained within the vasculature for extended periods of time were used to assess the BBB integrity. Near-infrared imaging revealed a BBB leak at the peak of the disease. The signal was the strongest around the eyes. A near-infrared substrate for matrix metalloproteinases was used to assess EAE-evoked inflammation. Auto-fluorescence interfered with the signal, requiring spectral unmixing for quantification. Overall, bioluminescence imaging was a reliable method to assess EAE-associated optic neuritis and medication effects and was superior to the near-infrared techniques in terms of signal specificity, robustness, ease of quantification, and cost.

We show a technique for in vivo live bioluminescence and near-infrared imaging of optic neuritis and encephalitis in the experimental autoimmune encephalomyelitis (EAE) model for multiple sclerosis in SJL/J mice.

Experimental autoimmune encephalomyelitis (EAE) in SJL/J mice is a model for relapsing-remitting multiple sclerosis (RRMS). Clinical EAE scores describing ...

Precision Implementation of Minimal Erythema Dose (MED) Testing to Assess Individual Variation in Human Inflammatory Response

Minimal erythema dose (MED) testing is frequently used in clinical settings for determining the smallest amount of ultraviolet (UV) irradiation necessary to produce erythema (inflammatory reddening) on the surface of the skin. In this context, the MED is regarded as a key factor in determining starting doses for UV phototherapy for common skin conditions such as psoriasis and eczema. In research settings, MED testing also has potential to be a powerful tool for assessing within- and between-persons variation in inflammatory responses. However, MED testing has not been widely adopted for use in research settings, likely owing to a lack of published guidelines, which is a barrier to obtaining reproducible results from this assay. Also, protocols and equipment for establishing MED vary widely, making it difficult to compare results across laboratories. Here, we describe a precise and reproducible method to induce and measure superficial erythema using newly designed protocols and methods that can easily be adapted to other equipment and laboratory environments. The method described here includes detail on procedures that will allow extrapolation of a standardized dosage schedule to other equipment so that this protocol can be adapted to any UV radiation source.

Precision Implementation of Minimal Erythema Dose MED Testing to Assess Individual Variation in Human Inflammatory Response

Minimal erythema dose (MED) testing is used to establish dosage schedules for ultraviolet radiation phototherapy. It can assess individual variation in inflammatory response but lacks methodology for achieving reproducible results. Here, we present a precision implementation of MED and demonstrate its ability to capture individual variation in inflammatory response.

Minimal erythema dose (MED) testing is frequently used in clinical settings for determining the smallest amount of ultraviolet (UV) irradiation necessary ...

A Pre-clinical Rat Model for the Study of Ischemia-reperfusion Injury in Reconstructive Microsurgery

Ischemia-reperfusion injury is the main cause of flap failure in reconstructive microsurgery. The rat is the preferred preclinical animal model in many areas of biomedical research due to its cost-effectiveness and its translation to humans. This protocol describes a method to create a preclinical free skin flap model in rats with ischemia-reperfusion injury. The described 3 cm x 6 cm rat free skin flap model is easily obtained after the placement of several vascular ligatures and the section of the vascular pedicle. Then, 8 h after the ischemic insult and completion of the microsurgical anastomosis, the free skin flap develops the tissue damage. These ischemia-reperfusion injury-related damages can be studied in this model, making it a suitable model for evaluating therapeutic agents to address this pathophysiological process. Furthermore, two main monitoring techniques are described in the protocol for the assessment of this animal model: transit-time ultrasound technology and laser speckle contrast analysis.

Here, we describe a pre-clinical animal model for studying the pathophysiology of ischemia-reperfusion injury in reconstructive microsurgery. This free skin flap model based on the superficial caudal epigastric vessels in the rat may also allow for the evaluation of different therapies and compounds to counteract ischemia-reperfusion injury-related damage.

Ischemia-reperfusion injury is the main cause of flap failure in reconstructive microsurgery. The rat is the preferred preclinical animal model in many ...

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease

Early diagnosis of systemic sclerosis-related interstitial lung disease (SSc-ILD) is important to enable treatment to be administered with minimal delay. However, diagnosing SSc-ILD is challenging because key symptoms are non-specific. High-resolution computed tomography (HRCT) of the chest is recognized as a sensitive imaging method for diagnosing and assessing SSc-ILD. Exposure of patients to ionizing radiation may be considered as a limitation, although methodological steps may be taken to moderate this. We present practical recommendations for performing HRCT scans and interpreting the results. Key features of SSc-ILD on HRCT include a non-specific interstitial pneumonia (NSIP) pattern with peripheral ground-glass opacities and extensive traction bronchiectasis. Despite similarities between SSc-ILD and idiopathic pulmonary fibrosis (IPF), HRCT can be used to differentiate between these conditions: in SSc-ILD compared with IPF, there is a greater proportion of ground-glass opacity and fibrosis is less coarse. A dilated, air-filled esophagus with diameter &#62;10 mm, suggestive of esophageal dysmotility is commonly seen in SSc-ILD. Pulmonary artery size greater than the adjacent ascending aorta suggests coexistent pulmonary hypertension. Nodules must be monitored due to the increased risk of lung cancer. A large extent of disease on HRCT (&#8805;20%) or a high fibrosis score suggests an increased risk of mortality. HRCT is central to diagnosing SSc-ILD, and serial assessments can be helpful in monitoring disease progression or treatment response.

Here, we present practical recommendations for performing thoracic high-resolution computed tomography for diagnosing and assessing systemic sclerosis-related interstitial lung disease.

Early diagnosis of systemic sclerosis-related interstitial lung disease (SSc-ILD) is important to enable treatment to be administered with minimal delay. ...