The little things that run: a general scaling of invertebrate exploratory speed with body mass.

Speed is a key trait of animal movement, and while much is already known about vertebrate speed and how it scales with body mass, studies on invertebrates are sparse, especially across diverse taxonomic groups. Here, we used automated image-based tracking to characterize the exploratory (voluntary) speed of 173 invertebrates comprising 57 species across six taxonomic groups (Arachnida, Chilopoda, Diplopoda, Entognatha, Insecta, Malacostraca) and four feeding types (carnivore, detritivore, herbivore, omnivore). Across all individuals, exploratory speed (mm/s) scaled with body mass (g) following a power-law relationship with a scaling exponent of 0.19 ± 0.04 (mean ± SE) and an intercept of 14.33 ± 1.2. These parameters varied substantially with taxonomic group and feeding type. For the first time, we provide general empirically derived allometric scaling relationships of exploratory speed across broad taxonomic groups of invertebrates. As exploratory speed drives key components of species interactions, such as encounter and attack rates, or competition, our study contributes to a deeper understanding of the role of individual movement in population and community level processes.

Overexpression of synphilin-1 promotes clearance of soluble and misfolded alpha-synuclein without restoring the motor phenotype in aged A30P transgenic mice.

Lewy bodies and neurites are the pathological hallmark of Parkinson's disease. These structures are composed of fibrillized and ubiquitinated alpha-synuclein suggesting that impaired protein clearance is an important event in aggregate formation. The A30P mutation is known for its fast oligomerization, but slow fibrillization rate. Despite its toxicity to neurons, mechanisms involved in either clearance or conversion of A30P alpha-synuclein from its soluble state into insoluble fibrils and their effects in vivo are poorly understood. Synphilin-1 is present in Lewy bodies, interacting with alpha-synuclein in vivo and in vitro and promotes its sequestration into aggresomes, which are thought to act as cytoprotective agents facilitating protein degradation. We therefore crossed animals overexpressing A30P alpha-synuclein with synphilin-1 transgenic mice to analyze its impact on aggregation, protein clearance and phenotype progression. We observed that co-expression of synphilin-1 mildly delayed the motor phenotype caused by A30P alpha-synuclein. Additionally, the presence of N- and C-terminal truncated alpha-synuclein species and fibrils were strongly reduced in double-transgenic mice when compared with single-transgenic A30P mice. Insolubility of mutant A30P and formation of aggresomes was still detectable in aged double-transgenic mice, paralleled by an increase of ubiquitinated proteins and high autophagic activity. Hence, this study supports the notion that co-expression of synphilin-1 promotes formation of autophagic-susceptible aggresomes and consecutively the degradation of human A30P alpha-synuclein. Notably, although synphilin-1 overexpression significantly reduced formation of fibrils and astrogliosis in aged animals, a similar phenotype is present in single- and double-transgenic mice suggesting additional neurotoxic processes in disease progression.

Disentangling rodent behaviors to improve automated behavior recognition.

Automated observation and analysis of behavior is important to facilitate progress in many fields of science. Recent developments in deep learning have enabled progress in object detection and tracking, but rodent behavior recognition struggles to exceed 75-80% accuracy for ethologically relevant behaviors. We investigate the main reasons why and distinguish three aspects of behavior dynamics that are difficult to automate. We isolate these aspects in an artificial dataset and reproduce effects with the state-of-the-art behavior recognition models. Having an endless amount of labeled training data with minimal input noise and representative dynamics will enable research to optimize behavior recognition architectures and get closer to human-like recognition performance for behaviors with challenging dynamics.

CatWalk XT gait parameters: a review of reported parameters in pre-clinical studies of multiple central nervous system and peripheral nervous system disease models.

Automated gait assessment tests are used in studies of disorders characterized by gait impairment. CatWalk XT is one of the first commercially available automated systems for analyzing the gait of rodents and is currently the most used system in peer-reviewed publications. This automated gait analysis system can generate a large number of gait parameters. However, this creates a new challenge in selecting relevant parameters that describe the changes within a particular disease model. Here, for the first time, we performed a multi-disorder review on published CatWalk XT data. We identify commonly reported CatWalk XT gait parameters derived from 91 peer-reviewed experimental studies in mice, covering six disorders of the central nervous system (CNS) and peripheral nervous system (PNS). The disorders modeled in mice were traumatic brain injury (TBI), stroke, sciatic nerve injury (SNI), spinal cord injury (SCI), Parkinson's disease (PD), and ataxia. Our review consisted of parameter selection, clustering, categorization, statistical evaluation, and data visualization. It suggests that certain gait parameters serve as potential indicators of gait dysfunction across multiple disease models, while others are specific to particular models. The findings also suggest that the more site-specific the injury is, the fewer parameters are reported to characterize its gait abnormalities. This study strives to present a clearly organized picture of gait parameters used in each one of the different mouse models, potentially helping novel CatWalk XT users to apply this information to similar or related mouse models they are working on.

Early postnatal exposure of rat pups to methylglyoxal induces oxidative stress, inflammation and dysmetabolism at adulthood.

This work aimed to investigate the effects of early progeny exposure to methylglyoxal (MG), programming for metabolic dysfunction and diabetes-like complications later in life. At delivery (PN1), the animals were separated into two groups: control group (CO), treated with saline, and MG group, treated with MG (20 mg/kg of BW; i.p.) during the first 2 weeks of the lactation period. In vivo experiments and tissue collection were done at PN90. Early MG exposure decreased body weight, adipose tissue, liver and kidney weight at adulthood. On the other hand, MG group showed increased relative food intake, blood fructosamine, blood insulin and HOMA-IR, which is correlated with insulin resistance. Besides, MG-treated animals presented dyslipidaemia, increased oxidative stress and inflammation. Likewise, MG group showed steatosis and perivascular fibrosis in the liver, pancreatic islet hypertrophy, increased glomerular area and pericapsular fibrosis, but reduced capsular space. This study shows that early postnatal exposure to MG induces oxidative stress, inflammation and fibrosis markers in pancreas, liver and kidney, which are related to metabolic dysfunction features. Thus, nutritional disruptors during lactation period may be an important risk factor for metabolic alterations at adulthood.

[The influence of a healthy lifestyle on body mass index in a sample of 12-14 year old individuals in Murcia (Spain)].

BACKGROUND: Excess weight and obesity in childhood is directly related to comorbidities that can have serious conse-quences for health. This study set out to identify the main modifiable lifestyles that influence the development of excess weight and obesity in childhood. METHODS: A cross-sectional study was carried out at seven secondary schools in Area V, Murcia, Spain. Questionnaires completed by parents were used to gather information about healthy habits in adolescents (ENHASA), The surveys con-sisted of four dimensions made up of modifiable lifestyle factors: nutrition, physical activity, new technologies and schoolmates. The adolescents' somatometric data was measured and classified according to the WHO categories for body mass index (BMI). ANOVA was used to compare the score differences among the BMI groups. RESULTS: The questionnaire was completed by the parents of 421 adolescents with an average age of 12 years. 21.1% pre-sented excess weight and 19.7% obesity. The score obtained by adolescents in the physical activity dimension decreased in the increased BMI group (score in normal weight 6.36 vs. 4.45 in obesity; p<0.001). The other three dimensions showed insignificant differences in scores between normal weight and obesity groups. CONCLUSION: Excess weight was present in 40.8% of the sample. Physical activity was the modifiable lifestyle to be most markedly linked to BMI. This outcome may help in planning specific strategies for sedentary lifestyles to reduce this dietary epidemic.

Early AGEing and metabolic diseases: is perinatal exposure to glycotoxins programming for adult-life metabolic syndrome?

Perinatal early nutritional disorders are critical for the developmental origins of health and disease. Glycotoxins, or advanced glycation end-products, and their precursors such as the methylglyoxal, which are formed endogenously and commonly found in processed foods and infant formulas, may be associated with acute and long-term metabolic disorders. Besides general aspects of glycotoxins, such as their endogenous production, exogenous sources, and their role in the development of metabolic syndrome, we discuss in this review the sources of perinatal exposure to glycotoxins and their involvement in metabolic programming mechanisms. The role of perinatal glycotoxin exposure in the onset of insulin resistance, central nervous system development, cardiovascular diseases, and early aging also are discussed, as are possible interventions that may prevent or reduce such effects.

Emerging Role of Translational Digital Biomarkers Within Home Cage Monitoring Technologies in Preclinical Drug Discovery and Development.

In drug discovery and development, traditional assessment of human patients and preclinical subjects occurs at limited time points in potentially stressful surroundings (i.e., the clinic or a test arena), which can impact data quality and welfare. However, recent advances in remote digital monitoring technologies enable the assessment of human patients and preclinical subjects across multiple time points in familiar surroundings. The ability to monitor a patient throughout disease progression provides an opportunity for more relevant and efficient diagnosis as well as improved assessment of drug efficacy and safety. In preclinical in vivo animal models, these digital technologies allow for continuous, longitudinal, and non-invasive monitoring in the home environment. This manuscript provides an overview of digital monitoring technologies for use in preclinical studies including their history and evolution, current engagement through use cases, and impact of digital biomarkers (DBs) on drug discovery and the 3Rs. We also discuss barriers to implementation and strategies to overcome them. Finally, we address data consistency and technology standards from the perspective of technology providers, end-users, and subject matter experts. Overall, this review establishes an improved understanding of the value and implementation of digital biomarker (DB) technologies in preclinical research.

Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives.

The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These systems enable prolonged and longitudinal recordings, and provide large continuous measures of spontaneous behavior that can be analyzed across multiple time scales. In this review, a diverse team of neuroscientists and product developers share their experiences using such an automated monitoring system that combines Noldus PhenoTyper® home-cages and the video-based tracking software, EthoVision® XT, to extract digital biomarkers of motor, emotional, social and cognitive behavior. After presenting our working definition of a "home-cage", we compare home-cage testing with more conventional out-of-cage tests (e.g., the open field) and outline the various advantages of the former, including opportunities for within-subject analyses and assessments of circadian and ultradian activity. Next, we address technical issues pertaining to the acquisition of behavioral data, such as the fine-tuning of the tracking software and the potential for integration with biotelemetry and optogenetics. Finally, we provide guidance on which behavioral measures to emphasize, how to filter, segment, and analyze behavior, and how to use analysis scripts. We summarize how the PhenoTyper has applications to study neuropharmacology as well as animal models of neurodegenerative and neuropsychiatric illness. Looking forward, we examine current challenges and the impact of new developments. Examples include the automated recognition of specific behaviors, unambiguous tracking of individuals in a social context, the development of more animal-centered measures of behavior and ways of dealing with large datasets. Together, we advocate that by embracing standardized home-cage monitoring platforms like the PhenoTyper, we are poised to directly assess issues pertaining to reproducibility, and more importantly, measure features of rodent behavior under more ethologically relevant scenarios.

Disruption of T cell homeostasis in mice expressing a T cell-specific dominant negative transforming growth factor beta II receptor.

The immune system, despite its complexity, is maintained at a relative steady state. Mechanisms involved in maintaining lymphocyte homeostasis are poorly understood; however, recent availability of transgenic (Tg) and knockout mouse models with altered balance of lymphocyte cell populations suggest that cytokines play a major role in maintaining lymphocyte homeostasis. We show here that transforming growth factor (TGF)-beta plays a critical role in maintaining CD8(+) T cell homeostasis in a Tg mouse model that specifically overexpresses a dominant negative TGF-beta II receptor (DNRII) on T cells. DNRII T cell Tg mice develop a CD8(+) T cell lymphoproliferative disorder resulting in the massive expansion of the lymphoid organs. These CD8(+) T cells are phenotypically "naive" except for the upregulation of the cell surface molecule CD44, a molecule usually associated with memory T cells. Despite their dominance in the peripheral lymphoid organs, CD8(+) T cells appear to develop normally in the thymus, suggesting that TGF-beta exerts its homeostatic control in the peripheral immune system.

Deep learning improves automated rodent behavior recognition within a specific experimental setup.

Automated observation and analysis of rodent behavior is important to facilitate research progress in neuroscience and pharmacology. Available automated systems lack adaptivity and can benefit from advances in AI. In this work we compare a state-of-the-art conventional rat behavior recognition (RBR) system to an advanced deep learning method and evaluate its performance within and across experimental setups. We show that using a multi-fiber network (MF-Net) in conjunction with data augmentation strategies within-setup dataset performance improves over the conventional RBR system. Two new methods for video augmentation were used: video cutout and dynamic illumination change. However, we also show that improvements do not transfer to videos in different experimental setups, for which we discuss possible causes and cures.

Disappearance of the lymphoid system in Bcl-2 homozygous mutant chimeric mice.

The bcl-2 proto-oncogene can prevent the death of many cell types. Mice were generated that were chimeric for the homozygous inactivation of bcl-2. Lymphocytes without Bcl-2 differentiated into phenotypically mature cells. However, in vitro, the mature T cells that lacked Bcl-2 had shorter life-spans and increased sensitivity to glucocorticoids and gamma-irradiation. In contrast, stimulation of CD3 inhibited the death of these cells. T and B cells with no Bcl-2 disappeared from the bone marrow, thymus, and periphery by 4 weeks of age. Thus, Bcl-2 was dispensable for lymphocyte maturation, but was required for a stable immune system after birth.

An Integrated System for the Automated Recording and Analysis of Insect Behavior in T-maze Arrays.

Host-plant resistance to insects like thrips and aphids is a complex trait that is difficult to phenotype quickly and reliably. Here, we introduce novel hardware and software to facilitate insect choice assays and automate the acquisition and analysis of movement tracks. The hardware consists of an array of individual T-mazes allowing simultaneous release of up to 90 insect individuals from their individual cage below each T-maze with choice of two leaf disks under a video camera. Insect movement tracks are acquired with computer vision software (EthoVision) and analyzed with EthoAnalysis, a novel software package that allows for automated reporting of highly detailed behavior parameters and statistical analysis. To validate the benefits of the system we contrasted two Arabidopsis accessions that were previously analyzed for differential resistance to western flower thrips. Results of two trials with 40 T-mazes are reported and we show how we arrived at optimized settings for the different filters and statistics. The statistics are reported in terms of frequency, duration, distance and speed of behavior events, both as sum totals and event averages, and both for the total trial period and in time bins of 1 h. Also included are higher level analyses with subcategories like short-medium-long events and slow-medium-fast events. The time bins showed how some behavior elements are more descriptive of differences between the genotypes during the first hours, whereas others are constant or become more relevant at the end of an 8 h recording. The three overarching behavior categories, i.e., choice, movement, and halting, were automatically corrected for the percentage of time thrips were detected and 24 out of 38 statistics of behavior parameters differed by a factor 2-6 between the accessions. The analysis resulted in much larger contrasts in behavior traits than reported previously. Compared to leaf damage assays on whole plants or detached leaves that take a week or more to complete, results were obtained in 8 h, with more detail, fewer individuals and higher significance. The potential value of the new integrated system, named EntoLab, for discovery of genetic traits in plants and insects by high throughput screening of large populations is discussed.

Reproducibility via coordinated standardization: a multi-center study in a Shank2 genetic rat model for Autism Spectrum Disorders.

Inconsistent findings between laboratories are hampering scientific progress and are of increasing public concern. Differences in laboratory environment is a known factor contributing to poor reproducibility of findings between research sites, and well-controlled multisite efforts are an important next step to identify the relevant factors needed to reduce variation in study outcome between laboratories. Through harmonization of apparatus, test protocol, and aligned and non-aligned environmental variables, the present study shows that behavioral pharmacological responses in Shank2 knockout (KO) rats, a model of synaptic dysfunction relevant to autism spectrum disorders, were highly replicable across three research centers. All three sites reliably observed a hyperactive and repetitive behavioral phenotype in KO rats compared to their wild-type littermates as well as a dose-dependent phenotype attenuation following acute injections of a selective mGluR1 antagonist. These results show that reproducibility in preclinical studies can be obtained and emphasizes the need for high quality and rigorous methodologies in scientific research. Considering the observed external validity, the present study also suggests mGluR1 as potential target for the treatment of autism spectrum disorders.

Financial benefits for child health and well-being in low income or socially disadvantaged families in developed world countries.

BACKGROUND: A strong and consistent relationship has been observed between relative poverty and poor child health and wellbeing even among rich nations. This review set out to examine evidence that additional monies provided to poor or disadvantaged families may benefit children by reducing relative poverty and thereby improving children's health, well-being and educational attainment. OBJECTIVES: To assess the effectiveness of direct provision of additional monies to socially or economically disadvantaged families in improving children's health, well-being and educational attainment SEARCH STRATEGY: In total 10 electronic databases were searched including the Cochrane library searched 2006 (Issue 1), Medline searched 1966 to May 2006 , Econlit searched 1969 to June 2006 and PsycINFO searched 1872 to June 2006, together with 3 libraries of working papers (MDRC, SSRN, SRDC). The general search strategy was [terms for income and financial benefits] and [paediatric terms] and [RCT filter] SELECTION CRITERIA: Studies selected provided money to relatively poor families (which included a child under the age of 18 or a pregnant woman), were randomised or quasi-randomised, measured outcomes related to child health or wellbeing and were conducted in a high income country. DATA COLLECTION AND ANALYSIS: Titles and abstracts identified in the search were independently assessed for eligibility by two reviewers. Data were extracted and entered into RevMan, synthesised and presented in both written and graphical form (forest plots). MAIN RESULTS: Nine trials including more than 25,000 participants were included in this review. No effect was observed on child health, measures of child mental health or emotional state. Non-significant effects favouring the intervention group were seen for child cognitive development and educational achievement, and a non-significant effect favouring controls in rates of teenage pregnancy. AUTHORS' CONCLUSIONS: The review set out to examine the potential of financial support to poor families to improve circumstances for children. However, on the basis of current evidence we can not state unequivocally whether financial benefits delivered as an intervention are effective at improving child health or wellbeing in the short term. Our conclusions are limited by the fact that most of the studies had small effects on total household income and that while no conditions were attached to how money was spent, all studies included strict conditions for receipt of payments. We note particular concerns by some authors that sanctions and conditions (such as working hours) placed on families may increase family stress.

Neighbourhood incidence rate of paediatric dental extractions under general anaesthetic in South West England.

Introduction Extraction of decayed teeth is the most common reason for UK children aged 5-9 years to receive a general anaesthetic. Inequalities in oral health are well recognised, but is under-explored in dental general anaesthesia (DGA).Methods Secondary analysis of routinely collected data from three local authorities in South West England was used to assess: 1) dental activities recorded for children <18 years attending NHS general dental practitioners (GDP); 2) the incidence rate of DGA and disease severity among <16-year-olds; and 3) individual and neighbourhood factors associated with higher rates of child DGA, and greater severity of disease.Results Among 208,533 GDP appointments, rates of preventive action were low where 1/7 included fluoride varnish but 1/5 included permanent fillings. The incidence rate of DGA was 6.6 admissions for every 1,000 children, rising to 12.4/1,000 among 5-9-year-olds. A total of 86 (7.6%) children had previously received a DGA at the same hospital. Area deprivation was strongly associated with higher rates of DGA, but rates of DGA remained high in less deprived areas. No associations were observed between number of teeth removed and socio-economic status.Conclusion Too many children are receiving DGA, and too few preventive actions are recorded by GDPs. Area-based inequalities in DGA were apparent, but wealthy areas also experienced substantial childhood dental decay.

Learning to recognize rat social behavior: Novel dataset and cross-dataset application.

BACKGROUND: Social behavior is an important aspect of rodent models. Automated measuring tools that make use of video analysis and machine learning are an increasingly attractive alternative to manual annotation. Because machine learning-based methods need to be trained, it is important that they are validated using data from different experiment settings. NEW METHOD: To develop and validate automated measuring tools, there is a need for annotated rodent interaction datasets. Currently, the availability of such datasets is limited to two mouse datasets. We introduce the first, publicly available rat social interaction dataset, RatSI. RESULTS: We demonstrate the practical value of the novel dataset by using it as the training set for a rat interaction recognition method. We show that behavior variations induced by the experiment setting can lead to reduced performance, which illustrates the importance of cross-dataset validation. Consequently, we add a simple adaptation step to our method and improve the recognition performance. COMPARISON WITH EXISTING METHODS: Most existing methods are trained and evaluated in one experimental setting, which limits the predictive power of the evaluation to that particular setting. We demonstrate that cross-dataset experiments provide more insight in the performance of classifiers. CONCLUSIONS: With our novel, public dataset we encourage the development and validation of automated recognition methods. We are convinced that cross-dataset validation enhances our understanding of rodent interactions and facilitates the development of more sophisticated recognition methods. Combining them with adaptation techniques may enable us to apply automated recognition methods to a variety of animals and experiment settings.

Automated video tracking of thrips behavior to assess host-plant resistance in multiple parallel two-choice setups.

BACKGROUND: Piercing-sucking insects cause severe damage in crops. Breeding for host-plant resistance can significantly reduce the yield losses caused by these insects, but host-plant resistance is a complex trait that is difficult to phenotype quickly and reliably. Current phenotyping methods mainly focus on labor-intensive and time-consuming end-point measurements of plant fitness. Characterizing insect behavior as a proxy for host-plant resistance could be a promising time-saving alternative to end-point measurements. RESULTS: We present a phenotyping platform that allows screening for host-plant resistance against Western flower thrips (WFT, Frankliniella occidentalis (Pergande)) in a parallel two-choice setup using automated video tracking of thrips behavior. The platform was used to establish host-plant preference of WFT with a large plant population of 345 wild Arabidopsis accessions and the method was optimized with two extreme accessions from this population that differed in resistance towards WFT. To this end, the behavior of 88 WFT individuals was simultaneously tracked in 88 parallel two-choice arenas during 8 h. Host-plant preference of WFT was established both by the time thrips spent on either accession and various behavioral parameters related to movement (searching) and non-movement (feeding) events. CONCLUSION: In comparison to 6-day end-point choice assays with whole plants or detached leaves, the automated video-tracking choice assay developed here delivered similar results, but with higher time- and resource efficiency. This method can therefore be a reliable and effective high throughput phenotyping tool to assess host-plant resistance to thrips in large plant populations.

Computer-assisted decision support for the diagnosis and treatment of infectious diseases in intensive care units.

Diagnosing nosocomial infections in critically ill patients admitted to intensive care units (ICUs) is a challenge because signs and symptoms are usually non-specific for a particular infection. In addition, the choice of treatment, or the decision not to treat, can be difficult. Models and computer-based decision-support systems have been developed to assist ICU physicians in the management of infectious diseases. We discuss the historical development, possibilities, and limitations of various computer-based decision-support models for infectious diseases, with special emphasis on Bayesian approaches. Although Bayesian decision-support systems are potentially useful for medical decision making in infectious disease management, clinical experience with them is limited and prospective evaluation is needed to determine whether their use can improve the quality of patient care.

A novel 3D method of locomotor analysis in adult zebrafish: Implications for automated detection of CNS drug-evoked phenotypes.

BACKGROUND: Expanding the spectrum of organisms to model human brain phenotypes is critical for our improved understanding of the pathobiology of neuropsychiatric disorders. Given the clear limitations of existing mammalian models, there is an urgent need for low-cost, high-throughput in-vivo technologies for drug and gene discovery. NEW METHOD: Here, we introduce a new automated method for generating 3D (X,Y,Z) swim trajectories in adult zebrafish (Danio rerio), to improve their neurophenotyping. RESULTS: Based on the Track3D module of EthoVision XT video tracking software (Noldus Information Technology), this tool enhances the efficient, high-throughput 3D analyses of zebrafish behavioral responses. Applied to adult zebrafish behavior, this 3D method is highly sensitive to various classes of psychotropic drugs, including selected psychostimulant and hallucinogenic agents. COMPARISON WITH EXISTING METHODS: Our present method offers a marked advance in the existing 2D and 3D methods of zebrafish behavioral phenotyping, minimizing research time and recording high-resolution, automatically synchronized videos with calculated, high-precision object positioning. CONCLUSIONS: Our novel approach brings practical simplicity and 'integrative' capacity to the often complex and error-prone quantification of zebrafish behavioral phenotypes. Illustrating the value of 3D swim path reconstructions for identifying experimentally-evoked phenotypic profiles, this method fosters innovative, ethologically relevant, and fully automated small molecule screens using adult zebrafish.