Altered CXCR4 dynamics at the cell membrane impairs directed cell migration in WHIM syndrome patients.

Chemokine receptor nanoscale organization at the cell membrane is orchestrated by the actin cytoskeleton and influences cell responses. Using single-particle tracking analysis we show that CXCR4R334X, a truncated mutant chemokine receptor linked to WHIM syndrome (warts, hypogammaglobulinemia, infections, myelokathexis), fails to nanoclusterize after CXCL12 stimulation, and alters the lateral mobility and spatial organization of CXCR4 when coexpressed. These findings correlate with multiple phalloidin-positive protrusions in cells expressing CXCR4R334X, and their inability to correctly sense chemokine gradients. The underlying mechanisms involve inappropriate actin cytoskeleton remodeling due to the inadequate ß-arrestin1 activation by CXCR4R334X, which disrupts the equilibrium between activated and deactivated cofilin. Overall, we provide insights into the molecular mechanisms governing CXCR4 nanoclustering, signaling and cell function, and highlight the essential scaffold role of ß-arrestin1 to support CXCL12-mediated actin reorganization and receptor clustering. These defects associated with CXCR4R334X expression might contribute to the severe immunological symptoms associated with WHIM syndrome.

Mechanical stress confers nuclear and functional changes in derived leukemia cells from persistent confined migration.

Nuclear deformability plays a critical role in cell migration. During this process, the remodeling of internal components of the nucleus has a direct impact on DNA damage and cell behavior; however, how persistent migration promotes nuclear changes leading to phenotypical and functional consequences remains poorly understood. Here, we described that the persistent migration through physical barriers was sufficient to promote permanent modifications in migratory-altered cells. We found that derived cells from confined migration showed changes in lamin B1 localization, cell morphology and transcription. Further analysis confirmed that migratory-altered cells showed functional differences in DNA repair, cell response to chemotherapy and cell migration in vivo homing experiments. Experimental modulation of actin polymerization affected the redistribution of lamin B1, and the basal levels of DNA damage in migratory-altered cells. Finally, since major nuclear changes were present in migratory-altered cells, we applied a multidisciplinary biochemical and biophysical approach to identify that confined conditions promoted a different biomechanical response of the nucleus in migratory-altered cells. Our observations suggest that mechanical compression during persistent cell migration has a role in stable nuclear and genomic alterations that might handle the genetic instability and cellular heterogeneity in aging diseases and cancer.

A Thematic Survey on the Reporting Quality of Randomized Controlled Trials in Rehabilitation: The Case of Multiple Sclerosis.

BACKGROUND AND PURPOSE: Optimal reporting is a critical element of scholarly communications. Several initiatives, such as the EQUATOR checklists, have raised authors' awareness about the importance of adequate research reports. On these premises, we aimed at appraising the reporting quality of published randomized controlled trials (RCTs) dealing with rehabilitation interventions. Given the breadth of such literature, we focused on rehabilitation for multiple sclerosis (MS), which was taken as a model of a challenging condition for all the rehabilitation professionals.A thematic methodological survey was performed to critically examine rehabilitative RCTs published in the last 2 decades in MS populations according to 3 main reporting themes: (1) basic methodological and statistical aspects; (2) reproducibility and responsiveness of measurements; and (3) clinical meaningfulness of the change. SUMMARY OF KEY POINTS: Of the initial 526 RCTs retrieved, 370 satisfied the inclusion criteria and were included in the analysis. The survey revealed several sources of weakness affecting all the predefined themes: among these, 25.7% of the studies complemented the P values with the confidence interval of the change; 46.8% reported the effect size of the observed differences; 40.0% conducted power analyses to establish the sample size; 4.3% performed retest procedures to determine the outcomes' reproducibility and responsiveness; and 5.9% appraised the observed differences against thresholds for clinically meaningful change, for example, the minimal important change. RECOMMENDATIONS FOR CLINICAL PRACTICE: The RCTs dealing with MS rehabilitation still suffer from incomplete reporting. Adherence to evidence-based checklists and attention to measurement issues and their impact on data interpretation can improve study design and reporting in order to truly advance the field of rehabilitation in people with MS.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A424 ).

Autonomous Vehicle Dataset with Real Multi-Driver Scenes and Biometric Data.

The development of autonomous vehicles is becoming increasingly popular and gathering real-world data is considered a valuable task. Many datasets have been published recently in the autonomous vehicle sector, with synthetic datasets gaining particular interest due to availability and cost. For a real implementation and correct evaluation of vehicles at higher levels of autonomy, it is also necessary to consider human interaction, which is precisely something that lacks in existing datasets. In this article the UPCT dataset is presented, a public dataset containing high quality, multimodal data obtained using state-of-the-art sensors and equipment installed onboard the UPCT's CICar autonomous vehicle. The dataset includes data from a variety of perception sensors including 3D LiDAR, cameras, IMU, GPS, encoders, as well as driver biometric data and driver behaviour questionnaires. In addition to the dataset, the software developed for data synchronisation and processing has been made available. The quality of the dataset was validated using an end-to-end neural network model with multiple inputs to obtain the speed and steering wheel angle and it obtained very promising results.

Effects of playing 1 vs 3 matches in a one-week period on physical performance in young soccer players.

The aim of this study was to analyse the effects of playing 1 vs 3 matches in a one-week period on physical performance in young soccer players. Twelve youth soccer players completed a battery of physical tests (countermovement jump [CMJ], 25 m sprint, 5-0-5 agility test, ankle dorsiflexion range of motion [AD ROM]) 72 h after a match. These tests were performed on two different occasions: during a week with 1 competitive match, and during a week in which 3 matches were played. Three matches in a week caused from most likely to very likely impairments in CMJ (ES = 0.81), the 5-0-5 agility test (ES = 1.03), and in AD ROM (ES = 0.46-0.63) compared with the 1 match in a week. For the 25 m sprint test, performance impairments were found in the split times for 10-15 m (ES = 0.72), 15-20 m (ES = 0.52) and 20-25 m (ES = 0.90) compared with 1 match in a week. Jumping, sprinting, change of direction (COD) performance and AD ROM are significantly affected during congested calendars in young soccer players. The monitoring of these variables is a useful tool to assess players' recovery and may help in determining players' readiness for the next matches.

Caffeine Health Claims on Sports Supplement Labeling. Analytical Assessment According to EFSA Scientific Opinion and International Evidence and Criteria.

Caffeine is a food supplement widely consumed by athletes, but it has not been established. So far, the veracity of their labeling in terms of the dosage and cause/effect relationship aimed at the consumer. The aim is to analyze the health claims and the dosage presented on the labeling of caffeine supplements and to evaluate if they follow the European Food Safety Authority (EFSA) and international criteria. A descriptive cross-sectional study of a sample of caffeine supplements was carried out. The search was done through the Amazon and Google Shopping web portals. In order to assess the adequacy of the health claims, the guidelines of reference established by European Food Safety Authority were compared to the Academy of Nutrition and Dietetics, International Olympic Committee, and Australian Institute of Sport guidelines; in addition, recent systematic reviews were addressed. A review of labels of 42 caffeine supplements showed that, in less than 3% of the products were the health claims supported by the recommendations and by the labeled quantity of caffeine. The claims that fully complied the recommendations were, "improves or increases endurance performance", "improves strength performance", or "improves short-term performance". In most cases, the recommended dosage was 200 mg/day for these products, which is the minimum for the caffeine effects to be declared. The rest of the health claims were not adequate or need to be modified. Most of the health claims identified indicated an unproven cause and effect, which constitutes consumer fraud, and so must be modified or eliminated.

Effect of Pharmacological Inhibition of the Catalytic Activity of Phosphatases of Regenerating Liver in Early T Cell Receptor Signaling Dynamics and IL-2 Production.

We have previously shown the delivery of phosphatase of regenerating liver-1 (PRL-1) to the immunological synapse (IS) and proposed a regulatory role of the catalytic activity of PRLs (PRL-1, PRL-2 and PRL-3) in antigen-induced IL-2 production. Nonetheless, the expression in T cells and delivery to the IS of the highly homologous PRL-3, as well as the role of the catalytic activity of PRLs in antigen-induced early signaling, has not been investigated. Here, the expression of PRL-3 protein was detected in primary CD4 T cells and in the CD4 T cell line Jurkat (JK), in which an overexpressed GFP-PRL-3 fluorescent fusion protein trafficked through the endosomal recycling compartment and co-localized with PLCγ1 signaling sites at the IS. Pharmacological inhibition was used to compare the role of the catalytic activity of PRLs in antigen-induced early signaling and late IL-2 production. Although the phosphatase activity of PRLs was not critical for early signaling triggered by antigen, it seemed to regulate signaling dynamics and was necessary for proper IL-2 production. We propose that enzymatic activity of PRLs has a higher significance for cytokine production than for early signaling at the IS. However, further research will be necessary to deeply understand the regulatory role of PRLs during lymphocyte activation and effector function.

An Origin of Citations: Darwin's Collaborators and Their Contributions to the Origin of Species.

In the first edition of the Origin of Species (1859), Charles Darwin apologized for not correctly referencing all the works cited in his magnum opus. More than 150 years later we have catalogued these citations and analyzed the resultant data. Looking for a complete selection of collaborators, a flexible interpretation of the term citation was necessary; we define it as any reference made to a third party, independently of its form or function. Following the same idea, the sixth edition of the Origin, originally published in 1872 and reprinted with minor additions and corrections in 1876, was chosen for the research because it represents the end of a long debate between Darwin and his peers. It naturally is the edition with the greatest number of citations and collaborators. Through a diverse theoretical analysis, we aim to present a new perspective for the study of the Origin of Species: a bibliographic approach that provides the tools needed to understand the history of the book as a physical and cultural object. Bibliometrics provides a theory of citations as well as a quantitative analysis; science studies highlights the profound social aspects of science in the making. The analysis resulted in 639 citations to 298 collaborators and provided a new perspective of the rhetorical structure of the Origin, even though these results are only the tip of the iceberg of the potential of all the data gathered in this study.

Effects of Maximal Strength Training on Perceived-Fatigue and Functional Mobility in Persons with Relapsing-Remitting Multiple Sclerosis.

Background and objectives: Fatigue is one of the most disabling symptoms that limit daily life activities in persons with multiple sclerosis (pwMS). This study aimed to evaluate the effects of maximal strength training (MST) on perceived-fatigue and functional mobility in pwMS. Materials and Methods: 26 participants with MS were balanced according to their pre-intervention fatigue scores and distributed into an MST group (n = 13) and a control group (CG; n = 13). The MST group completed eight weeks using high loads, evaluating detraining after ten weeks. Quadriceps and hamstring isokinetic (QPTIK; HPTIK) and isometric (QPTIM; HPTIM) peak torques were assessed using an isokinetic dynamometer. Effect size differences were estimated with the Hedges' g index (dg ). Fatigue was evaluated through the Fatigue Severity Scale (FSS), while functional mobility was assessed via the Timed Up and Go Test (TUG). Results: The MST significantly improved all the strength measurements after the intervention (Δ6.43-29.55%; p < 0.05) compared to the control group. FSS showed a significant reduction (59.97%, dg = 5.41, large). The MST group also reduced the TUG time (19.69%; dg = 0.93, large) compared to the control group. Improvements caused by the intervention did not remain after a 10-week follow-up, with decreases in strength performance from 4.40% to 13.86% (dg = 0.24-0.56, small to moderate), 112.08% in the FSS (dg = -3.88, large), and 16.93% in TUG (dg = -1.07, large). Conclusions: MST (up to 90% 1RM) seems to be a feasible and useful way to obtain clinically relevant improvements in the perceived-fatigue symptoms and functional mobility. Still, symptom improvements decrease after a 10-week detraining period.

TRIC: an automated alignment strategy for reproducible protein quantification in targeted proteomics.

Next-generation mass spectrometric (MS) techniques such as SWATH-MS have substantially increased the throughput and reproducibility of proteomic analysis, but ensuring consistent quantification of thousands of peptide analytes across multiple liquid chromatography-tandem MS (LC-MS/MS) runs remains a challenging and laborious manual process. To produce highly consistent and quantitatively accurate proteomics data matrices in an automated fashion, we developed TRIC (http://proteomics.ethz.ch/tric/), a software tool that utilizes fragment-ion data to perform cross-run alignment, consistent peak-picking and quantification for high-throughput targeted proteomics. TRIC reduced the identification error compared to a state-of-the-art SWATH-MS analysis without alignment by more than threefold at constant recall while correcting for highly nonlinear chromatographic effects. On a pulsed-SILAC experiment performed on human induced pluripotent stem cells, TRIC was able to automatically align and quantify thousands of light and heavy isotopic peak groups. Thus, TRIC fills a gap in the pipeline for automated analysis of massively parallel targeted proteomics data sets.

A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research.

This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.

Distinct Trafficking of Cell Surface and Endosomal TIM-1 to the Immune Synapse.

The T cell costimulatory molecule TIM-1 (T cell/transmembrane, mucin and immunoglobulin domain protein 1) sorts mainly to endosomes in lymphoid cells. At difference from the cell surface protein, endosomal TIM-1 translocates to the immune synapse (IS), where it can contribute to antigen-dependent T cell costimulation. TIM-1 ligands increase the amount of cell surface protein, preventing its traffic to the IS. The bipolar sorting of TIM-1 observed during IS formation is determined by differences in its subcellular location, and probably modulates antigen-driven immune responses.

Drift time-specific collision energies enable deep-coverage data-independent acquisition proteomics.

We present a data-independent acquisition mass spectrometry method, ultradefinition (UD) MS(E). This approach utilizes ion mobility drift time-specific collision-energy profiles to enhance precursor fragmentation efficiency over current MS(E) and high-definition (HD) MS(E) data-independent acquisition techniques. UDMS(E) provided high reproducibility and substantially improved proteome coverage of the HeLa cell proteome compared to previous implementations of MS(E), and it also outperformed a state-of-the-art data-dependent acquisition workflow. Additionally, we report a software tool, ISOQuant, for processing label-free quantitative UDMS(E) data.

Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry.

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.

Intersystem crossing rates of single perylene molecules in ortho-dichlorobenzene.

Triplet states can be interesting for optical switching of molecular fluorescence as well as quantum experiments relying on the manipulation of spin states. However, the ground state of molecules is usually a singlet state. It is therefore interesting to study the intersystem crossing (ISC) rates between singlet and triplet states. We have measured the autocorrelation function of the fluorescence from single perylene molecules in an ortho-dichlorobenzene host matrix at cryogenic temperatures (1.3 K). We observed two time scales in the autocorrelation function corresponding to intersystem crossing to two indistinguishable triplet states (TX and TY) and a third triplet state (TZ). By studying the power dependence of the correlation times and contrasts in the autocorrelation functions of single molecules, we determine the ISC rates of perylene for the first time.

Automatic detection of microaneurysms in diabetic retinopathy fundus images using the L*a*b color space.

We develop an automated image processing system for detecting microaneurysm (MA) in diabetic patients. Diabetic retinopathy is one of the main causes of preventable blindness in working age diabetic people with the presence of an MA being one of the first signs. We transform the eye fundus images to the L*a*b* color space in order to separately process the L* and a* channels, looking for MAs in each of them. We then fuse the results, and last send the MA candidates to a k-nearest neighbors classifier for final assessment. The performance of the method, measured against 50 images with an ophthalmologist's hand-drawn ground-truth, shows high sensitivity (100%) and accuracy (84%), and running times around 10 s. This kind of automatic image processing application is important in order to reduce the burden on the public health system associated with the diagnosis of diabetic retinopathy given the high number of potential patients that need periodic screening.

Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics.

Quantifying the similarity of spectra is an important task in various areas of spectroscopy, for example, to identify a compound by comparing sample spectra to those of reference standards. In mass spectrometry based discovery proteomics, spectral comparisons are used to infer the amino acid sequence of peptides. In targeted proteomics by selected reaction monitoring (SRM) or SWATH MS, predetermined sets of fragment ion signals integrated over chromatographic time are used to identify target peptides in complex samples. In both cases, confidence in peptide identification is directly related to the quality of spectral matches. In this study, we used sets of simulated spectra of well-controlled dissimilarity to benchmark different spectral comparison measures and to develop a robust scoring scheme that quantifies the similarity of fragment ion spectra. We applied the normalized spectral contrast angle score to quantify the similarity of spectra to objectively assess fragment ion variability of tandem mass spectrometric datasets, to evaluate portability of peptide fragment ion spectra for targeted mass spectrometry across different types of mass spectrometers and to discriminate target assays from decoys in targeted proteomics. Altogether, this study validates the use of the normalized spectral contrast angle as a sensitive spectral similarity measure for targeted proteomics, and more generally provides a methodology to assess the performance of spectral comparisons and to support the rational selection of the most appropriate similarity measure. The algorithms used in this study are made publicly available as an open source toolset with a graphical user interface.

A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data.

This article describes an automated sensor-based system to detect pedestrians in an autonomous vehicle application. Although the vehicle is equipped with a broad set of sensors, the article focuses on the processing of the information generated by a Velodyne HDL-64E LIDAR sensor. The cloud of points generated by the sensor (more than 1 million points per revolution) is processed to detect pedestrians, by selecting cubic shapes and applying machine vision and machine learning algorithms to the XY, XZ, and YZ projections of the points contained in the cube. The work relates an exhaustive analysis of the performance of three different machine learning algorithms: k-Nearest Neighbours (kNN), Naïve Bayes classifier (NBC), and Support Vector Machine (SVM). These algorithms have been trained with 1931 samples. The final performance of the method, measured a real traffic scenery, which contained 16 pedestrians and 469 samples of non-pedestrians, shows sensitivity (81.2%), accuracy (96.2%) and specificity (96.8%).

Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants.

Phenomics is a technology-driven approach with promising future to obtain unbiased data of biological systems. Image acquisition is relatively simple. However data handling and analysis are not as developed compared to the sampling capacities. We present a system based on machine learning (ML) algorithms and computer vision intended to solve the automatic phenotype data analysis in plant material. We developed a growth-chamber able to accommodate species of various sizes. Night image acquisition requires near infrared lightning. For the ML process, we tested three different algorithms: k-nearest neighbour (kNN), Naive Bayes Classifier (NBC), and Support Vector Machine. Each ML algorithm was executed with different kernel functions and they were trained with raw data and two types of data normalisation. Different metrics were computed to determine the optimal configuration of the machine learning algorithms. We obtained a performance of 99.31% in kNN for RGB images and a 99.34% in SVM for NIR. Our results show that ML techniques can speed up phenomic data analysis. Furthermore, both RGB and NIR images can be segmented successfully but may require different ML algorithms for segmentation.