Tommy Löfstedt

OnPLS—a novel multiblock method for the modelling of predictive and orthogonal variation

This paper presents a new multiblock analysis method called OnPLS, a general extension of O2PLS to the multiblock case. The proposed method is equivalent to O2PLS in cases involving only two matrices, but generalises to cases involving more than two matrices without giving preference to any particular matrix: the method is fully symmetric. OnPLS extracts a minimal number of globally predictive components that exhibit maximal covariance and correlation. Furthermore, the method can be used to study orthogonal variation, i.e. local phenomena captured in the data that are specific to individual combinations of matrices or to individual matrices. The methods utility was demonstrated by its application to three synthetic data sets. It was shown that OnPLS affords a reduced number of globally predictive components and increased intercorrelations of scores, and that it greatly facilitates interpretation of the predictive model. Copyright

OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants

BackgroundReactive oxygen species (ROS) are involved in the regulation of diverse physiological processes in plants, including various biotic and abiotic stress responses. Thus, oxidative stress tolerance mechanisms in plants are complex, and diverse responses at multiple levels need to be characterized in order to understand them. Here we present system responses to oxidative stress in Populus by integrating data from analyses of the cambial region of wild-type controls and plants expressing high-isoelectric-point superoxide dismutase (hipI-SOD) transcripts in antisense orientation showing a higher production of superoxide. The cambium, a thin cell layer, generates cells that differentiate to form either phloem or xylem and is hypothesized to be a major reason for phenotypic perturbations in the transgenic plants. Data from multiple platforms including transcriptomics (microarray analysis), proteomics (UPLC/QTOF-MS), and metabolomics (GC-TOF/MS, UPLC/MS, and UHPLC-LTQ/MS) were integrated using the most recent development of orthogonal projections to latent structures called OnPLS. OnPLS is a symmetrical multi-block method that does not depend on the order of analysis when more than two blocks are analysed. Significantly affected genes, proteins and metabolites were then visualized in painted pathway diagrams.ResultsThe main categories that appear to be significantly influenced in the transgenic plants were pathways related to redox regulation, carbon metabolism and protein degradation, e.g. the glycolysis and pentose phosphate pathways (PPP). The results provide system-level information on ROS metabolism and responses to oxidative stress, and indicate that some initial responses to oxidative stress may share common pathways.ConclusionThe proposed data evaluation strategy shows an efficient way of compiling complex, multi-platform datasets to obtain significant biological information.

Modelling human musculoskeletal functional movements using ultrasound imaging

BackgroundA widespread and fundamental assumption in the health sciences is that muscle functions are related to a wide variety of conditions, for example pain, ischemic and neurological disorder, exercise and injury. It is therefore highly desirable to study musculoskeletal contributions in clinical applications such as the treatment of muscle injuries, post-surgery evaluations, monitoring of progressive degeneration in neuromuscular disorders, and so on.The spatial image resolution in ultrasound systems has improved tremendously in the last few years and nowadays provides detailed information about tissue characteristics. It is now possible to study skeletal muscles in real-time during activity.MethodsThe ultrasound images are transformed to be congruent and are effectively compressed and stacked in order to be analysed with multivariate techniques. The method is applied to a relevant clinical orthopaedic research field, namely to describe the dynamics in the Achilles tendon and the calf during real-time movements.ResultsThis study introduces a novel method to medical applications that can be used to examine ultrasound image sequences and to detect, visualise and quantify skeletal muscle dynamics and functions.ConclusionsThis new objective method is a powerful tool to use when visualising tissue activity and dynamics of musculoskeletal ultrasound registrations.

Global, local and unique decompositions in OnPLS for multiblock data analysis

OnPLS is an extension of O2PLS that decomposes a set of matrices, in either multiblock or path model analysis, such that each matrix consists of two parts: a globally joint part containing variation shared with all other connected matrices, and a part that contains locally joint and unique variation, i.e. variation that is shared with some, but not all, other connected matrices or that is unique in a single matrix. A further extension of OnPLS suggested here decomposes the part that is not globally joint into locally joint and unique parts. To achieve this it uses the OnPLS method to first find and extract a globally joint model, and then applies OnPLS recursively to subsets of matrices that contain the locally joint and unique variation remaining after the globally joint variation has been extracted. This results in a set of locally joint models. The variation that is left after the globally joint and locally joint variation has been extracted is (by construction) not related to the other matrices and thus represents the strictly unique variation in each matrix. The methods utility is demonstrated by its application to both a simulated data set and a real data set acquired from metabolomic, proteomic and transcriptomic profiling of three genotypes of hybrid aspen. The results show that OnPLS can successfully decompose each matrix into global, local and unique models, resulting in lower numbers of globally joint components and higher intercorrelations of scores. OnPLS also increases the interpretability of models of connected matrices, because of the locally joint and unique models it generates.

Ultrasound imaging with speckle tracking of cervical muscle deformation and deformation rate: isometric contraction of patients after anterior cervical decompression and fusion for cervical disc disease and controls.

There is currently a lack of information regarding neck muscle activity during specific exercises. The purpose of the present study was to investigate deformation and deformation rate in different layers of dorsal and ventral neck muscles during isometric neck muscle contraction in individuals after anterior cervical decompression and fusion and in healthy controls. This study included 10 individuals (mean age 60 years; SD 7.1) with a verified, long-standing neck disorder and 10 healthy, age- and sex-matched controls. Ultrasonography and post-process speckle tracking analysis was used to investigate the degree and the rate of neck muscles motions at the C4 segmental level during sub-maximal, isometric resistance of the head in a seated position. None of the analyses performed showed significant differences between groups (p > 0.05). In the dorsal muscles, both groups exhibited a higher deformation rate in the multifidus than in the trapezius, splenius, and semispinalis capitis (p ≤ 0.01). In the neck disorder group, the multifidus also showed a higher deformation rate compared to the semispinalis cervicis (p = 0.02). In the ventral muscles of patients with neck disorders, the longus colli had a higher deformation rate than the sternocleidomastoid (p = 0.02). Among the healthy controls, the multifidus showed a higher degree of deformation (p = 0.02) than the trapezius. In conclusion, our results showed no significant differences between the two groups in mechanical neck muscle activation. Larger studies with different exercises, preferably with a standardized measure of resistance, are needed to investigate whether patients and controls show differences in deformation and deformation rates in neck muscles.

Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI

The use of machine-learning in neuroimaging offers new perspectives in early diagnosis and prognosis of brain diseases. Although such multivariate methods can capture complex relationships in the data, traditional approaches provide irregular (ℓ2 penalty) or scattered (ℓ1 penalty) predictive pattern with a very limited relevance. A penalty like Total Variation (TV) that exploits the natural 3D structure of the images can increase the spatial coherence of the weight map. However, TV penalization leads to non-smooth optimization problems that are hard to minimize. We propose an optimization framework that minimizes any combination of ℓ1, ℓ2, and TV penalties while preserving the exact ℓ1 penalty. This algorithm uses Nesterovs smoothing technique to approximate the TV penalty with a smooth function such that the loss and the penalties are minimized with an exact accelerated proximal gradient algorithm. We propose an original continuation algorithm that uses successively smaller values of the smoothing parameter to reach a prescribed precision while achieving the best possible convergence rate. This algorithm can be used with other losses or penalties. The algorithm is applied on a classification problem on the ADNI dataset. We observe that the TV penalty does not necessarily improve the prediction but provides a major breakthrough in terms of support recovery of the predictive brain regions.

Bi-modal OnPLS

This paper presents an extension to the recently published OnPLS data analysis method. Bi‐modal OnPLS allows for arbitrary block relationships in both columns and rows and is able to extract orthogonal variation in both columns and rows without bias towards any particular direction or matrix: the method is fully symmetric with regard to both rows and columns.

Dynamic ultrasound imaging—A multivariate approach for the analysis and comparison of time-dependent musculoskeletal movements

BackgroundMuscle functions are generally assumed to affect a wide variety of conditions and activities, including pain, ischemic and neurological disorders, exercise and injury. It is therefore very desirable to obtain more information on musculoskeletal contributions to and activity during clinical processes such as the treatment of muscle injuries, post-surgery evaluations, and the monitoring of progressive degeneration in neuromuscular disorders.The spatial image resolution achievable with ultrasound systems has improved tremendously in the last few years and it is nowadays possible to study skeletal muscles in real-time during activity. However, ultrasound imaging has an inherent problem that makes it difficult to compare different measurement series or image sequences from two or more subjects. Due to physiological differences between different subjects, the ultrasound sequences will be visually different – partly because of variation in probe placement and partly because of the difficulty of perfectly reproducing any given movement.MethodsUltrasound images of the biceps and calf of a single subject were transformed to achieve congruence and then efficiently compressed and stacked to facilitate analysis using a multivariate method known as O2PLS. O2PLS identifies related and unrelated variation in and between two sets of data such that different phases of the studied movements can be analysed. The methodology was used to study the dynamics of the Achilles tendon and the calf and also the Biceps brachii and upper arm. The movements of these parts of the body are both of interest in clinical orthopaedic research.ResultsThis study extends the novel method of multivariate analysis of congruent images (MACI) to facilitate comparisons between two series of ultrasound images. This increases its potential range of medical applications and its utility for detecting, visualising and quantifying the dynamics and functions of skeletal muscle.ConclusionsThe most important results of this study are that MACI with O2PLS is able to consistently extract meaningful variability from pairs of ultrasound sequences. The MACI method with O2PLS is a powerful tool with great potential for visualising and comparing dynamics between movements. It has many potential clinical applications in the study of muscle injuries, post-surgery evaluations and evaluations of rehabilitation, and the assessment of athletic training interventions.

Preliminary evaluation of dorsal muscle activity during resisted cervical extension in patients with longstanding pain and disability following anterior cervical decompression and fusion surgery

OBJECTIVES To compare mechanical activity (deformation and deformation rate) of the dorsal neck muscles between individuals with longstanding symptoms after anterior cervical decompression and fusion (ACDF) surgery and healthy controls. DESIGN Preliminary cross-sectional study. SETTING Neurosurgery clinic. PARTICIPANTS Ten individuals {mean age 60 [standard deviation (SD) 7.1]} who had undergone ACDF surgery 10 to 13 years previously and 10 healthy age- and sex-matched controls. MAIN OUTCOMES Mechanical activity of the different layers of dorsal neck muscles, measured at the C4 segment using ultrasonography (speckle tracking analysis) during a standardised, resisted cervical extension task. RESULTS A significant group×muscle interaction was found for muscle deformation (P<0.03) but not for deformation rate (P>0.79). The ACDF group showed significantly less deformation of the semispinalis capitis muscle during the extension task compared with the control group [mean 3.12 (SD 2.06) and 6.64 (SD 4.17), respectively; mean difference 3.34 (95% confidence interval -0.54 to 7.21)]. CONCLUSIONS As the semispinalis capitis muscle is a powerful neck extensor, the finding of altered activation following ACDF surgery lends support to the inclusion of exercise to train neck muscle performance in the management of these patients.

Near infrared and skin impedance spectroscopy – a possible support in the diagnostic process of skin tumours in primary health care

The global incidence of skin cancer has increased drastically in recent decades, especially in Australia and Northern Europe. Early detection is crucial for good prognosis and high survival rates. In general, primary care physicians have considerably lower sensitivity and specificity rates for detection of skin cancer, compared to dermatologists. A probable main reason for this is that current diagnostic tools are subjective in nature, and therefore diagnostic skills highly depend on experience. Illustratively, in Sweden, approximately 155 500 benign skin lesions are excised unnecessarily every year. An objective instrument, added to the clinical examination, might improve the diagnostic accuracy, and thus promote earlier detection of malignant skin tumours, as well as reduce medical costs associated with unnecessary biopsies and excisions. The general aim of this study was to investigate the usefulness of the combination of near infrared (NIR) and skin impedance spectroscopy as a supportive tool in the diagnosis and evaluation of skin tumours in primary health care.