New tools for the investigation of muscle fiber-type spatial distributions across histological sections.

BACKGROUND: The functional and metabolic properties of skeletal muscles are partly a function of the spatial arrangement of fibers across the muscle belly. Many muscles feature a non-uniform spatial pattern of fiber types, and alterations to the arrangement can reflect age or disease and correlate with changes in muscle mass and strength. Despite the significance of this event, descriptions of spatial fiber-type distributions across a muscle section are mainly provided qualitatively, by eye. Whilst several quantitative methods have been proposed, difficulties in implementation have meant that robust statistical analysis of fiber type distributions has not yielded new insight into the biological processes that drive the age- or disease-related changes in fiber type distributions. METHODS: We review currently available approaches for analysis of data reporting fast/slow fiber type distributions on muscle sections before proposing a new method based on a generalized additive model. We compare current approaches with our new method by analysis of sections of three mouse soleus muscles that exhibit visibly different spatial fiber patterns, and we also apply our model to a dataset representing the fiber type proportions and distributions of the mouse tibialis anterior. RESULTS: We highlight how current methods can lead to differing interpretations when applied to the same dataset and demonstrate how our new method is the first to permit location-based estimation of fiber-type probabilities, in turn enabling useful graphical representation. CONCLUSIONS: We present an open-access online application that implements current methods as well as our new method and which aids the interpretation of a variety of statistical tools for the spatial analysis of muscle fiber distributions.

Towards equitable scheduling of global health teleconferences: a spatial exploration of the world's population and health by time zone.

OBJECTIVES: To examine the world's population, development, and health by condensed Coordinated Universal Time (UTC) offset to support a normative position on how to most defensibly schedule global health teleconferences with the primary goal of advancing equitable regard for participants by health condition. DESIGN: Spatial exploration examined through the lens of equitable regard for participants. SETTING: The Earth. PARTICIPANTS: The global population. MAIN OUTCOME MEASURES: Global population, countries, Human Development Index (HDI), and health measured in total and disease-specific disability-adjusted life years (DALYs) per 100 000 per year by UTC offset. Strengths and weaknesses of scheduling teleconferences accordingly to alternative approaches. RESULTS: The UTC offset with the largest population of approximately 1 724 million persons occurred in UTC+5, largest country count of approximately 40 countries in UTC+1, and the lowest median HDI of 0.527 occurred in UTC0. The highest median total DALYs per 100 000 per year of 41 873 occurred in UTC+11, highest median HIV/AIDS DALYs per 100 000 per year of 941 in UTC0, and highest median typhoid and paratyphoid fevers DALYs per 100 000 per year of 279 occurred in UTC+5. Hypothetical teleconference scheduling scenarios generated temporal distances of up to 11 hours to UTC offsets representing the most countries and greatest number of DALYs per 100 000 per year. Teleconference scheduling based on egoism was considered to be problematic, and contractualism as unrealistically demanding. Utilitarianism resulted in the risk of systematically disadvantaging small, temporally remote groups. Egalitarianism offered equality, but prioritarianism offered the possibility of addressing health inequities. CONCLUSIONS: Global health teleconferences may generate great temporal distances between participants compromising representative participation, as well as the well-being of attendees. Our spatial exploration of the world's population and health by UTC offset may be used to support a normative position on scheduling global health teleconferences that enhance progress towards health equity.

The spatio-temporal distribution of COVID-19 infection in England between January and June 2020.

The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.A common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.Using test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first 6 months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on 23 March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.In terms of controlling transmission, the most important practical application of our results is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.

Application of kernel smoothing to estimate the spatio-temporal variation in risk of STEC O157 in England.

Identifying geographical areas with significantly higher or lower rates of infectious diseases can provide important aetiological clues to inform the development of public health policy and interventions designed to reduce morbidity. We applied kernel smoothing to estimate the spatial and spatio-temporal variation in risk of STEC O157 infection in England between 2009 and 2015, and to explore differences between the residential locations of cases reporting travel and those not reporting travel. We provide evidence that the distribution of STEC O157 infection in England is non-uniform with respect to the distribution of the at-risk population; that the spatial distribution of the three main genetic lineages infecting humans (I, II and I/II) differs significantly and that the spatio-temporal risk is highly dynamic. Our results also indicate that cases of STEC O157 reporting travel within or outside the UK are more likely to live in the south/south-east of the country, meaning that their residential location may not reflect the location of exposure that led to their infection. We suggest that the observed variation in risk reflects exposure to sources of STEC O157 that are geographically prescribed. These differences may be related to a combination of changes in the strains circulating in the ruminant reservoir, animal movements (livestock, birds or wildlife) or the behavior of individuals prior to infection. Further work to identify the importance of behaviours and exposures reported by cases relative to residential location is needed.

Tutorial on kernel estimation of continuous spatial and spatiotemporal relative risk.

Kernel smoothing is a highly flexible and popular approach for estimation of probability density and intensity functions of continuous spatial data. In this role, it also forms an integral part of estimation of functionals such as the density-ratio or "relative risk" surface. Originally developed with the epidemiological motivation of examining fluctuations in disease risk based on samples of cases and controls collected over a given geographical region, such functions have also been successfully used across a diverse range of disciplines where a relative comparison of spatial density functions has been of interest. This versatility has demanded ongoing developments and improvements to the relevant methodology, including use spatially adaptive smoothers; tests of significantly elevated risk based on asymptotic theory; extension to the spatiotemporal domain; and novel computational methods for their evaluation. In this tutorial paper, we review the current methodology, including the most recent developments in estimation, computation, and inference. All techniques are implemented in the new software package sparr, publicly available for the R language, and we illustrate its use with a pair of epidemiological examples.

CT morphometry of adult thoracic intervertebral discs.

PURPOSE: Despite being commonly affected by degenerative disorders, there are few data on normal thoracic intervertebral disc dimensions. A morphometric analysis of adult thoracic intervertebral discs was, therefore, undertaken. METHODS: Archival computed tomography scans of 128 recently deceased individuals (70 males, 58 females, 20-79 years) with no known spinal pathology were analysed to determine thoracic disc morphometry and variations with disc level, sex and age. Reliability was assessed by intraclass correlation coefficients (ICCs). RESULTS: Anterior and posterior intervertebral disc heights and axial dimensions were significantly greater in men (anterior disc height 4.0±1.4 vs 3.6±1.3 mm; posterior disc height 3.6±0.90 vs 3.4±0.93 mm; p<0.01). Disc heights and axial dimensions at T4-5 were similar or smaller than at T2-3, but thereafter increased caudally (mean anterior disc height T4-5 and T10-11, 2.7±0.7 and 5.4±1.2 mm, respectively, in men; 2.6±0.8 and 5.1±1.3 mm, respectively, in women; p<0.05). Except at T2-3, anterior disc height decreased with advancing age and anteroposterior and transverse disc dimensions increased; posterior and middle disc heights and indices of disc shape showed no consistent statistically significant changes. Most parameters showed substantial to almost perfect agreement for intra- and inter-rater reliability. CONCLUSIONS: Thoracic disc morphometry varies significantly and consistently with disc level, sex and age. This study provides unique reference data on adult thoracic intervertebral disc morphometry, which may be useful when interpreting pathological changes and for future biomechanical and functional studies.

Use of Clinical Anatomy Resources by Musculoskeletal Outpatient Physiotherapists in Australian Public Hospitals: A Cross-Sectional Study.

PURPOSE: To investigate how musculoskeletal outpatient physiotherapists in public hospitals interact with and perceive clinical anatomy resources in the workplace. METHOD: This cross-sectional study used a postal survey sent to musculoskeletal outpatient physiotherapists in 64 Australian public hospitals. Survey questions examined demographics, qualifications, experience, types of resources used, whether resources meet requirements, and what improvements could be made to current resources. RESULTS: A total of 193 physiotherapists responded (75% response rate; 60% female), of whom 49% were age 35 years or younger; 67% had only an undergraduate qualification, and 37% had practised for 5 years or less. More experienced physiotherapists used resources significantly less frequently ([odds ratio]=1.35; 95% CI, 1.17-1.57), and we found no significant associations between preference for online versus printed resources and age, sex, qualifications, or experience. Trends included less experienced physiotherapists identifying the absence of online access as a barrier to resource use and provision of improved online facilities as necessary to improve access to clinical anatomy resources. CONCLUSION: RESULTS indicate distinct trends in physiotherapists' use of clinical anatomy resources, including a desire for improved online resource access on the part of less experienced physiotherapists. The findings are relevant to hospital outpatient clinics, particularly those that employ less experienced physiotherapists.

Objet : Enquêter sur la façon dont les physiothérapeutes externes spécialistes de l'appareil locomoteur dans les hôpitaux publics interagissent avec les ressources en matière d'anatomie clinique et les perçoivent. Méthode : Cette étude transversale a été menée au moyen d'une enquête postée aux physiothérapeutes externes spécialistes de l'appareil locomoteur de 64 hôpitaux publics de l'Australie. Les questions de l'enquête portaient sur les données démographiques, les qualifications, l'expérience, les types de ressources utilisées, la pertinence des ressources par rapport aux besoins et les améliorations qui pourraient être apportées aux ressources actuelles. Résultats : Au total, 193 physiothérapeutes ont pris part à l'enquête (taux de réponse de 75 %; 60 % des répondants étaient des femmes). De ce nombre, 49 % étaient âgés de 35 ans et moins, 67 % possédaient seulement des qualifications de premier cycle d'étude universitaire, et 37 % comptaient 5 ans et moins de pratique. Les physiothérapeutes expérimentés ont dit utiliser les ressources beaucoup moins fréquemment (RC 1,35; 95 % CI, 1,17 à 1,57), et aucune association importante n'est ressortie concernant la préférence entre les ressources en ligne et les ressources imprimées selon l'âge, le sexe, les qualifications ou l'expérience. En matière de tendances, les physiothérapeutes moins expérimentés ont désigné l'absence d'un accès en ligne comme un obstacle à l'utilisation de ressources et ont décrit l'amélioration des installations en ligne comme étant nécessaire à un meilleur accès aux ressources en matière d'anatomie clinique. Conclusion : Les résultats démontrent des tendances distinctes concernant l'utilisation des ressources en matière d'anatomie clinique chez les physiothérapeutes, y compris le désir d'un accès amélioré aux ressources en ligne chez les physiothérapeutes moins expérimentés. Les conclusions sont pertinentes pour les cliniques externes des hôpitaux, particulièrement celles qui emploient des physiothérapeutes moins expérimentés.

Jointly optimal bandwidth selection for the planar kernel-smoothed density-ratio.

The kernel-smoothed density-ratio or 'relative risk' function for planar point data is a useful tool for examining disease rates over a certain geographical region. Instrumental to the quality of the resulting risk surface estimate is the choice of bandwidth for computation of the required numerator and denominator densities. The challenge associated with finding some 'optimal' smoothing parameter for standalone implementation of the kernel estimator given observed data is compounded when we deal with the density-ratio per se. To date, only one method specifically designed for calculation of density-ratio optimal bandwidths has received any notable attention in the applied literature. However, this method exhibits significant variability in the estimated smoothing parameters. In this work, the first practical comparison of this selector with a little-known alternative technique is provided. The possibility of exploiting an asymptotic MISE formulation in an effort to control excess variability is also examined, and numerical results seem promising.

Modelling dichotomously marked muscle fibre configurations.

Human skeletal muscle consists of contractile elements (fibres) that may be differentiated according to their physiological and biochemical properties. The different types of fibre are distributed throughout each muscle, with the pattern (when viewed as a cross-section) of cell distribution being an important determinant of the functional properties of each muscle. It is well known that the proportions and distributions of muscle fibre types change with advancing age or disease, but few studies have quantitatively investigated these changes. A better knowledge of the nature of changes in muscle fibre distributions is an essential requirement for future development of therapies and interventions directed at maintaining or restoring good muscle function. In this work, we examine several statistical methods designed to gauge the departure of a dichotomously labelled muscle fibre distribution from that of a random fibre-type dispersal. These methods are also applicable to a wide range of biological investigations in which the spatial distribution of cells or specimens underpins an important biological principle. This work includes the proposal of a novel technique, based on weighted kernel-smoothed density ratios, which can account for the variable areas of the individual fibres. We illustrated the methodology by using a number of real-data examples, and we employed a comprehensive set of simulations to assess the empirical power and false-positive rates of these tests.

Identification of high-risk regions for schistosomiasis in the Guichi region of China: an adaptive kernel density estimation-based approach.

Identification of high-risk regions of schistosomiasis is important for rational resource allocation and effective control strategies. We conducted the first study to apply the newly developed method of adaptive kernel density estimation (KDE)-based spatial relative risk function (sRRF) to detect the high-risk regions of schistosomiasis in the Guichi region of China and compared it with the fixed KDE-based sRRF. We found that the adaptive KDE-based sRRF had a better ability to depict the heterogeneity of risk regions, but was more sensitive to altering the user-defined smoothing parameters. Specifically, the impact of bandwidths on the estimated risk value and risk significance (P value) was higher for the adaptive KDE-based sRRF, but lower on the estimated risk variation standard error (s.e.) compared with the fixed KDE-based sRRF. Based on this application the adaptive and fixed KDE-based sRRF have their respective advantages and disadvantages and the joint application of the two approaches can warrant the best possible identification of high-risk subregions of diseases.

Student injuries in the dissecting room.

Cadaver dissection is the first opportunity for many students to practice handling human tissue and is their first exposure to the occupational hazards involved with this task. Few studies examine dissection room injuries to ascertain the dangers associated with dissecting. We performed a retrospective cohort analysis of dissection room injuries from four student cohorts over an eleven-year period (2001-2011), including second-year medical students, third-year medical students, second-year dental students, and third-year science students. Injury data included activity causing injury, object responsible, and injury site. A total of 163 injuries during 70,039 hours of dissection were recorded, with 66 in third-year medical students, 42 in second-year medical students, 36 in third-year science students, and 16 in second-year dental students. The overall rate was 2.87 injuries per 1,000 dissection hours, with second-year medical students most frequently injured (5.5 injuries per 1,000 hours); third-year medical students were least frequently injured (1.3 injuries per 1,000 hours). A significant difference in injury rates between student groups indicated a higher than expected injury rate to second-year medical students and lower than expected rates to third-year medical students. Injury rates increased for most groups between 2001-2006 and 2007-2011 periods. Most injuries (79%) were from scalpel cuts to the finger or thumb. This study provides injury rates for dissection room injuries to students, indicating differences in injury frequency between cohorts and an increase in injury rate over time. As scalpel cuts were the most likely injury mechanism, targeting scalpel handling with preventative strategies may reduce future injury risk.

Risk signals of an influenza pandemic caused by highly pathogenic avian influenza subtype H5N1: spatio-temporal perspectives.

Highly pathogenic avian influenza (HPAI) subtype H5N1 is a trans-boundary animal disease that has crossed the animal-human species barrier and over the past decade has had a considerable impact on the poultry industry, wild bird populations and on human health. Understanding the spatio-temporal patterns of H5N1 outbreaks can provide visual clues to the dynamics of disease spread and of areas at risk, and thus improve the cost-effectiveness of disease control and prevention. This study describes the characteristics and investigates the temporal, spatial and space-time dynamics of H5N1 outbreaks in domestic poultry between December 2003 and December 2009 using a global database. The study found that the start date of the epidemic wave was postponed, the duration of the epidemic was prolonged and its magnitude reduced over time, but the disease transmission cycle was not efficiently interrupted. Two 'hot-spot' regions of H5N1 outbreaks were identified: well-documented locations in East and Southeast Asia, as well as a novel location at the boundaries of Europe and Africa, where enhanced surveillance should be conducted. The risk of a pandemic due to H5N1 remains high.

Adaptive kernel estimation of spatial relative risk.

Kernel smoothing is routinely used for the estimation of relative risk based on point locations of disease cases and sampled controls over a geographical region. Typically, fixed-bandwidth kernel estimation has been employed, despite the widely recognized problems experienced with this methodology when the underlying densities exhibit the type of spatial inhomogeneity frequently seen in geographical epidemiology. A more intuitive approach is to utilize a spatially adaptive, variable smoothing parameter. In this paper, we examine the properties of the adaptive kernel estimator by both asymptotic analysis and a simulation study, finding advantages over the fixed kernel approach in both the cases. We also look at practical issues with implementation of the adaptive relative risk estimator (including bandwidth choice and boundary correction), and develop a computationally inexpensive method for generating tolerance contours to highlight areas of significantly elevated risk.

Inference based on kernel estimates of the relative risk function in geographical epidemiology.

Kernel smoothing is a popular approach to estimating relative risk surfaces from data on the locations of cases and controls in geographical epidemiology. The interpretation of such surfaces is facilitated by plotting of tolerance contours which highlight areas where the risk is sufficiently high to reject the null hypothesis of unit relative risk. Previously it has been recommended that these tolerance intervals be calculated using Monte Carlo randomization tests. We examine a computationally cheap alternative whereby the tolerance intervals are derived from asymptotic theory. We also examine the performance of global tests of hetereogeneous risk employing statistics based on kernel risk surfaces, paying particular attention to the choice of smoothing parameters on test power.