Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Background: Fatigue is a process that results in a decreased ability to produce force, and which could eventually affect performance and increase the risk of injury. Force variability analysis has been proposed to describe the level of fatigue with the purpose of detecting the development of fatigue. Variability is credited to play a functional and adaptive role through which the components of a system self-organize to solve a motor problem. Non-linear tools have been applied to analyze the variability of physiological signals, revealing that the structure of motor fluctuations provides relevant information about the functional role of variability. It has been suggested that the presence of lower complexity in the variability structure could reveal a less functional and adaptative state (e.g., ageing or illness). In the last years, an increased number of studies have applied these techniques to force variability analysis in relation to fatigue. Objective: To provide an overview of the current knowledge on the use of non-linear tools on force variability as a fatigue index. Methods: Following PRISMA guidelines, a systematic search of SPORTDiscus, Scopus, Web of Science and PubMed was carried out. Studies included were: a) original studies that analyzed the effect of fatigue on humans during an action focused on force production; b) published studies with their title and abstract in English; c) studies that applied non-linear tools on a signal directly related to force production. Results: Twenty-five studies were included in this review. The relationship between fatigue and the complexity of force variability, the type of action and relative intensity, the nature of the signal and the non-linear tools used, and the methods of data acquisition and processing were identified. Conclusion: The articles reviewed suggest that fatigue leads to a decrease in complexity mostly in isometric contractions, but this is not as clear in dynamic contractions. This fatigue-induced loss of complexity seems to be a result of changes in the nervous system at the central level, albeit triggered by peripheral mechanisms. It should be noted that non-linear tools are affected by the relative intensity of contraction, non-stationarity, and the acquisition and treatment of the signal.

Oral antibiotics are posed as a possible risk factor for breast cancer. Evidence is insufficient to determine whether the choice of antibiotic class could effect this potential association, and non-linearity has not been studied. We aimed to fill these important knowledge gaps.
PubMed, Web of Science, Embase and a trial registry were searched from inception until January 2020, without any restrictions. Additionally, extensive manual searches were undertaken. Random-effects meta-analyses provided pooled risk estimates with 95 % confidence intervals (CI). Dose-response analyses modeling the relationship between number of antibiotic prescriptions and breast cancer risk were extended to non-linear models. Heterogeneity, publication bias and small-study effects were assessed.
Of 7805 identified publications ten were eligible, including 3,719,383 individuals and 84,485 breast cancer cases. The pooled breast cancer risk was modestly increased among individuals who ever used antibiotics (relative risk RR = 1.18, 95 %CI 1.08-1.29), also after excluding the last year prior diagnosis. This excess risk was seen among penicillin (RR = 1.09, 95 %CI 1.01-1.18), tetracycline (RR = 1.13, 95 %CI 1.04-1.24) and nitrofuran users (RR = 1.26, 95 %CI 1.05-1.52), whilst nitroimidazole and metronidazole use (RR = 1.05, 95 %CI 1.00-1.11) indicated for marginal association. No apparent association was found for other antibiotics. Data suggested for a non-linear dose-dependent relationship, with a seemingly protective effect after at least 35 prescriptions. However, these findings might partly be explained by limited power of dose-response analyses.
The association of antibiotics with breast cancer risk appears to differ between the various antibiotic classes. Whether this association is causal remains unclear, requiring further clarification and mechanistic studies.

This review is a summary of the Raman spectroscopy applications made over the last 10 years in the field of cellulose and lignocellulose materials. This paper functions as a status report on the kinds of information that can be generated by applying Raman spectroscopy. The information in the review is taken from the published papers and author\'s own research-most of which is in print. Although, at the molecular level, focus of the investigations has been on cellulose and lignin, hemicelluloses have also received some attention. The progress over the last decade in applying Raman spectroscopy is a direct consequence of the technical advances in the field of Raman spectroscopy, in particular, the application of new Raman techniques (e.g., Raman imaging and coherent anti-Stokes Raman or CARS), novel ways of spectral analysis, and quantum chemical calculations. On the basis of this analysis, it is clear that Raman spectroscopy continues to play an important role in the field of cellulose and lignocellulose research across a wide range of areas and applications, and thereby provides useful information at the molecular level.

Ultrasound contrast agent microbubbles have expanded the utility of biomedical ultrasound from anatomic imaging to the assessment of microvascular blood flow characteristics and ultrasound-assisted therapeutic applications. Central to their effectiveness in these applications is their resonant and non-linear oscillation behaviour. This article reviews the salient physics of an oscillating microbubble in an ultrasound field, with particular emphasis on phospholipid-coated agents. Both the theoretical underpinnings of bubble vibration and the experimental evidence of non-linear encapsulated bubble dynamics and scattering are discussed and placed within the context of current and emerging applications.

Nanomaterials (NMs) are used in an extremely diverse range of products and are increasingly entering the environment, driving a need to better understand their potential health effects in both humans and wildlife. A major challenge in nanoparticle (eco)toxicology is the ability to localise NMs post exposure, to enable more targeted biological effects analyses. A range of imaging techniques have been applied to do so, but they are limited, requiring either extensive processing of the material, staining or use of high intensity illumination that can lead to photo damage and/or have limited tissue penetration. Coherent anti-Stokes Raman scattering (CARS) microscopy is a label-free imaging technique, providing contrast based on the intrinsic molecular vibrations of a specimen, circumventing the need for chemical perturbation by exogenous labels. CARS uses near infra-red excitation wavelengths which allow microscopy at depths of several hundred microns in intact tissues and minimises photo-damage to live and delicate samples. Here we provide an overview of the CARS process and present a series of illustrative examples demonstrating its application for detecting NMs within biological tissues, ranging from isolated cells to whole organisms and including materials spanning metals to polymers. We highlight the advantages of this technique which include chemically selective live imaging and substantial depth penetration, but we also discuss its limitations when applied to nanotoxicology, which most notably include the lack of resolution for studies on single nanoparticles.