Identification and characterization of chemotherapy resistant high-risk neuroblastoma persister cells.

Relapse rates in high-risk neuroblastoma remain exceedingly high. The malignant cells that are responsible for relapse have not been identified, and mechanisms of therapy resistance remain poorly understood. Here, we used single nucleus RNA sequencing and bulk whole genome sequencing to identify and characterize the residual malignant persister cells that survive chemotherapy from a cohort of 20 matched diagnosis and definitive surgery tumor samples from patients treated with high-risk neuroblastoma induction chemotherapy. We show that persister cells share common mechanisms of chemotherapy escape including suppression of MYCN activity and activation of NF-κB signaling, the latter is further enhanced by cell-cell communication between the malignant cells and the tumor microenvironment. Overall, our work dissects the transcriptional landscape of cellular persistence in high-risk neuroblastoma and paves the way to the development of new therapeutic strategies to prevent disease relapse.

Pro-cycling team cyclist assignment for an upcoming race.

Professional bicycle racing is a popular sport that has attracted significant attention in recent years. The evolution and ubiquitous use of sensors allow cyclists to measure many metrics including power, heart rate, speed, cadence, and more in training and racing. In this paper we explore for the first time assignment of a subset of a team's cyclists to an upcoming race. We introduce RaceFit, a model that recommends, based on recent workouts and past assignments, cyclists for participation in an upcoming race. RaceFit consists of binary classifiers that are trained on pairs of a cyclist and a race, described by their relevant properties (features) such as the cyclist's demographic properties, as well as features extracted from his workout data from recent weeks; as well additional properties of the race, such as its distance, elevation gain, and more. Two main approaches are introduced in recommending on each stage in a race and aggregate from it to the race, or on the entire race. The model training is based on binary label which represent participation of cyclist in a race (or in a stage) in past events. We evaluated RaceFit rigorously on a large dataset of three pro-cycling teams' cyclists and race data achieving up to 80% precision@i. The first experiment had shown that using TP or STRAVA data performs the same. Then the best-performing parameters of the framework are using 5 weeks time window, imputation was effective, and the CatBoost classifier performed best. However, the model with any of the parameters performed always better than the baselines, in which the cyclists are assigned based on their popularity in historical data. Additionally, we present the top-ranked predictive features.

Epithelial cell-expressed type II IL-4 receptor mediates eosinophilic esophagitis.

BACKGROUND: Eosinophilic esophagitis (EoE) is a chronic, food-driven allergic disease, characterized by eosinophil-rich inflammation in the esophagus. The histopathological and clinical features of EoE have been attributed to overproduction of the type 2 cytokines IL-4 and IL-13, which mediate profound alterations in the esophageal epithelium and neutralizing of their shared receptor component (IL-4Rα) with a human antibody drug (dupilumab) demonstrates clinical efficacy. Yet, the relative contribution of IL-4 and IL-13 and whether the type II IL-4 receptor (comprised of the IL-4Rα chain in association with IL-13Rα1) mediates this effect has not been determined. METHODS: Experimental EoE was induced in WT, Il13ra1-/- , and Krt14Cre /Il13ra1fl/fl mice by skin-sensitized using 4-ethoxymethylene-2-phenyl-2-oxazolin (OXA) followed by intraesophageal challenges. Esophageal histopathology was determined histologically. RNA was extracted and sequenced for transcriptome analysis and compared with human EoE RNAseq data. RESULTS: Induction of experimental EoE in mice lacking Il13ra1 and in vivo IL-13 antibody-based neutralization experiments blocked antigen-induced esophageal epithelial and lamina propria thickening, basal cell proliferation, eosinophilia, and tissue remodeling. In vivo targeted deletion of Il13ra1 in esophageal epithelial cells rendered mice protected from experimental EoE. Single-cell RNA sequencing analysis of human EoE biopsies revealed predominant expression of IL-13Rα1 in epithelial cells and that EoE signature genes correlated with IL-13 expression compared with IL-4. CONCLUSIONS: We demonstrate a definitive role for IL-13 signaling via IL-13Rα1 in EoE. These data provide mechanistic insights into the mode of action of current therapies in EoE and highlight the type II IL-4R as a future therapeutic target.

Characteristics of step responses following varying magnitudes of unexpected lateral perturbations during standing among older people - a cross-sectional laboratory-based study.

INTRODUCTION: The inability to recover from unexpected lateral loss of balance may be particularly relevant to the problem of falling. AIM: We aimed to explore whether different kinematic patterns and strategies occur in the first recovery step in single-step trials in which a single step was required to recover from a fall, and in multiple-step trials in which more than one step was required to recover from a fall. In addition, in the multiple-step trials, we examined kinematic patterns of balance recovery where extra steps were needed to recover balance. METHODS: Eighty-four older adults (79.3 ± 5.2 years) were exposed to unannounced right/left perturbations in standing that were gradually increased to trigger a recovery stepping response. We performed a kinematic analysis of the first recovery step of all single-step and multiple-step trials for each participant and of total balance recovery in the multiple-step trial. RESULTS: Kinematic patterns and strategies of the first recovery step in the single-step trials were significantly dependent on the perturbation magnitude. It took a small, yet significantly longer time to initiate a recovery step and a significantly longer time to complete the recovery step as the magnitude increased. However, the first recovery step in the multiple-step trials showed no significant differences between different perturbation magnitudes; while, in total balance recovery of these trials, we observed a small, yet significant difference as the magnitude increased. CONCLUSIONS: At relatively low perturbation magnitudes, i.e., single-step trials, older adults selected different first stepping strategies and kinematics as perturbation magnitudes increased, suggesting that this population activated pre-planned programs based on the perturbation magnitude. However, in the first recovery step of the multiple-step trials, i.e., high perturbation magnitudes, similar kinematic movement patterns were used at different magnitudes, suggesting a more rigid, automatic behavior, while the extra-steps were scaled to the perturbation magnitude. This suggest that older adults activate pre-planned programs based on the magnitude of the perturbation, even before the first step is completed..

Fucosylated Human Milk Oligosaccharide Foraging within the Species Bifidobacterium pseudocatenulatum Is Driven by Glycosyl Hydrolase Content and Specificity.

Human milk enriches members of the genus Bifidobacterium in the infant gut. One species, Bifidobacterium pseudocatenulatum, is found in the gastrointestinal tracts of adults and breastfed infants. In this study, B. pseudocatenulatum strains were isolated and characterized to identify genetic adaptations to the breastfed infant gut. During growth on pooled human milk oligosaccharides (HMOs), we observed two distinct groups of B. pseudocatenulatum, isolates that readily consumed HMOs and those that did not, a difference driven by variable catabolism of fucosylated HMOs. A conserved gene cluster for fucosylated HMO utilization was identified in several sequenced B. pseudocatenulatum strains. One isolate, B. pseudocatenulatum MP80, which uniquely possessed GH95 and GH29 α-fucosidases, consumed the majority of fucosylated HMOs tested. Furthermore, B. pseudocatenulatum SC585, which possesses only a single GH95 α-fucosidase, lacked the ability to consume the complete repertoire of linkages within the fucosylated HMO pool. Analysis of the purified GH29 and GH95 fucosidase activities directly on HMOs revealed complementing enzyme specificities with the GH95 enzyme preferring 1-2 fucosyl linkages and the GH29 enzyme favoring 1-3 and 1-4 linkages. The HMO-binding specificities of the family 1 solute-binding protein component linked to the fucosylated HMO gene cluster in both SC585 and MP80 are similar, suggesting differential transport of fucosylated HMO is not a driving factor in each strain's distinct HMO consumption pattern. Taken together, these data indicate the presence or absence of specific α-fucosidases directs the strain-specific fucosylated HMO utilization pattern among bifidobacteria and likely influences competitive behavior for HMO foraging in situ. IMPORTANCE Often isolated from the human gut, microbes from the bacterial family Bifidobacteriaceae commonly possess genes enabling carbohydrate utilization. Isolates from breastfed infants often grow on and possess genes for the catabolism of human milk oligosaccharides (HMOs), glycans found in human breast milk. However, catabolism of structurally diverse HMOs differs between bifidobacterial strains. This study identifies key gene differences between Bifidobacterium pseudocatenulatum isolates that may impact whether a microbe successfully colonizes an infant gut. In this case, the presence of complementary α-fucosidases may provide an advantage to microbes seeking residence in the infant gut. Such knowledge furthers our understanding of how diet drives bacterial colonization of the infant gut.

DoChaP: the domain change presenter.

Alternative splicing results in multiple transcripts of the same gene, possibly encoding for different protein isoforms with different domains. Whereas it is possible to manually determine the effect of alternative splicing on the domain composition for a single event, the process requires the tedious integration of several data sources; it is error prone and not feasible for genome-wide characterization of domains affected by differential splicing. To fulfill the need for an automated solution, we developed the Domain Change Presenter (DoChaP, https://dochap.bgu.ac.il/), a web server for the visualization of exon-domain associations. DoChaP visualizes all transcripts of a given gene, the encoded proteins and their domains, and enables a comparison between the transcripts and between their protein products. The colors and organization make the structural effect of alternative splicing events on protein structures easily identified. To enable the study of the conservation of exons structure, alternative splicing, and the effect of alternative splicing on protein domains, DoChaP also provides a two-species comparison of exon-domain associations. DoChaP thus provides a unique and easy-to-use visualization of the exon-domain association and conservation, and will facilitate the study of the structural effects of alternative splicing in health and disease.

Supervisor-Worker Problems with an Application in Education.

In many e-learning settings, allowing students to choose which skills to practice encourages their motivation and contributes to learning. However, when given choice, students may prefer to practice skills that they already master, rather than practice skills they need to master. On the other hand, requiring students only to practice their required skills may reduce their motivation and lead to dropout. In this paper, we model this tradeoff as a multi-agent planning task, which we call SWOPP (Supervisor- Worker Problem with Partially Overlapping goals), involving two agents-a supervisor (teacher) and a worker (student)-each with different, yet non-conflicting, goals. The supervisor and worker share joint goals (mastering skills). The worker plans to achieve his/her own goals (completing an e-learning session) at a minimal cost (effort required to solve problems). The supervisor guides the worker towards achieving the joint goals by controlling the problems in the choice set for the worker. We provide a formal model for the SWOPP task and two sound and complete algorithms for the supervisor to guide the worker's plan to achieve their joint goals. We deploy SWOPP for the first time in a real-world study to personalize math questions for K5 students using an e-learning software in schools. We show that SWOPP was able to guide students' interactions with the software to practice necessary skills without deterring their motivation.

Development and piloting of a perturbation stationary bicycle robotic system that provides unexpected lateral perturbations during bicycling (the PerStBiRo system).

BACKGROUND: Balance control, and specifically balance reactive responses that contribute to maintaining balance when balance is lost unexpectedly, is impaired in older people. This leads to an increased fall risk and injurious falls. Improving balance reactive responses is one of the goals in fall-prevention training programs. Perturbation training during standing or treadmill walking that specifically challenges the balance reactive responses has shown very promising results; however, only older people who are able to perform treadmill walking can participate in these training regimes. Thus, we aimed to develop, build, and pilot a mechatronic Perturbation Stationary Bicycle Robotic system (i.e., PerStBiRo) that can challenge balance while sitting on a stationary bicycle, with the aim of improving balance proactive and reactive control. METHODS: This paper describes the development, and building of the PerStBiRo using stationary bicycles. In addition, we conducted a pilot randomized control trial (RCT) with 13 older people who were allocated to PerStBiRo training (N = 7) versus a control group, riding stationary bicycles (N = 6). The Postural Sway Test, Berg Balance Test (BBS), and 6-min Walk Test were measured before and after 3 months i.e., 20 training sessions. RESULTS: The PerStBiRo System provides programmed controlled unannounced lateral balance perturbations during stationary bicycling. Its software is able to identify a trainee's proactive and reactive balance responses using the Microsoft Kinect™ system. After a perturbation, when identifying a trainee's trunk and arm reactive balance response, the software controls the motor of the PerStBiRo system to stop the perturbation. The pilot RCT shows that, older people who participated in the PerStBiRo training significantly improved the BBS (54 to 56, p = 0.026) and Postural Sway velocity (20.3 m/s to 18.3 m/s, p = 0.018), while control group subject did not (51.0 vs. 50.5, p = 0.581 and 15 m/s vs. 13.8 m/s, p = 0.893, respectively), 6MWT tended to improve in both groups. CONCLUSIONS: Our participants were able to perform correct balance proactive and reactive responses, indicating that older people are able to learn balance trunk and arm reactive responses during stationary bicycling. The pilot study shows that these improvements in balance proactive and reactive responses are generalized to performance-based measures of balance (BBS and Postural Sway measures).

Characteristics of upper-extremity reactions to sudden lateral loss of balance in persons with stroke.

BACKGROUND: Upper-extremity reactions are part of a whole-body response to counterweight the falling center of mass after unexpected balance loss. Impairments in upper-extremity reactions due to unilateral hemiparesis may contribute to stroke survivors propensity for falling. We aimed to characterize upper-extremity (paretic and non-paretic sides) reactive movements in response to lateral balance perturbations in Persons with Stroke vs. healthy controls. METHODS: Twenty-six subacute persons with stroke and 15 healthy controls were exposed to multidirectional sudden unannounced surface translations in stance. Spatiotemporal parameters of upper- and lower-extremity balance responses to lateral perturbations were analyzed. FINDINGS: In both groups reactive upper-extremity movement initiation preceded reactive step initiation. In response to a loss of balance toward the paretic side, persons with stroke demonstrated delayed movement initiation of both upper- and lower-extremity compared with healthy controls (In persons with stroke: 234.7 ± 60.0 msec and 227.1 ± 39.6 msec for upper extremities vs. 272.1 ± 59.1 msec for lower-extremity; and in controls: 180.1 ± 39.9 msec and 197.8 ± 61.3 msec for upper-extremities vs. 219.3 ± 40.8 msec for lower-extremity; p = 0.001, Cohen's d's: 0.59-1.03) and a greater abduction excursion in the ipsilateral upper-extremity compared with the contralateral upper-extremity (In persons with stroke: 39.3 ± 23.6 cm vs. 24.9 ± 10.1 cm, respectively; In Controls: 42.6 ± 21.8 cm vs. 29.3 ± 17.3 cm, respectively). INTERPRETATION: The faster upper-extremity reactive movement reactions compared to reactive step initiation in both persons with stroke and healthy controls suggests that balance recovery is an automatic "reflex-like" response. Delayed upper-extremity reactive reactions in conditions of surface translation toward the non-paretic side in persons with stroke may increase the risk of falls in the direction of the paretic side.

The kinematics and strategies of recovery steps during lateral losses of balance in standing at different perturbation magnitudes in older adults with varying history of falls.

BACKGROUND: Step-recovery responses are critical in preventing falls when balance is lost unexpectedly. We investigated the kinematics and strategies of balance recovery in older adults with a varying history of falls. METHODS: In a laboratory study, 51 non-fallers (NFs), 20 one-time fallers (OFs), and 12 recurrent-fallers (RFs) were exposed to random right/left unannounced underfoot perturbations in standing of increasing magnitude. The stepping strategies and kinematics across an increasing magnitude of perturbations and the single- and multiple-step threshold trials, i.e., the lowest perturbation magnitude to evoke single step and multiple steps, respectively, were analyzed. Fall efficacy (FES) and self-reported lower-extremity function were also assessed. RESULTS: OFs had significantly lower single- and multiple-step threshold levels than NFs; the recovery-step kinematics were similar. Surprisingly, RFs did not differ from NFs in either threshold. The kinematics in the single-step threshold trial in RFs, however, showed a significant delay in step initiation duration, longer step duration, and larger center of mass (CoM) displacement compared with NFs and OFs. In the multiple-step threshold trial, the RFs exhibited larger CoM displacements and longer time to fully recover from balance loss. Interestingly, in the single-stepping trials, 45% of the step-recovery strategies used by RFs were the loaded-leg strategy, about two times more than OFs and NFs (22.5 and 24.2%, respectively). During the multiple-stepping trials, 27.3% of the first-step recovery strategies used by RFs were the loaded-leg strategy about two times more than OFs and NFs (11.9 and 16.4%, respectively), the crossover stepping strategy was the dominated response in all 3 groups (about 50%). In addition, RFs reported a lower low-extremity function compared with NFs, and higher FES in the OFs. CONCLUSIONS: RFs had impaired kinematics during both single-step and multiple-step recovery responses which was associated with greater leg dysfunction. OFs and NFs had similar recovery-step kinematics, but OFs were more likely to step at lower perturbation magnitudes suggesting a more "responsive" over-reactive step response related from their higher fear of falling and not due to impaired balance abilities. These data provide insight into how a varying history of falls might affect balance recovery to a lateral postural perturbation. TRIAL REGISTRATION: This study was registered prospectively on November 9th, 2011 at clinicaltrials.gov ( NCT01439451 ).

Characteristics of First Recovery Step Response following Unexpected Loss of Balance during Walking: A Dynamic Approach.

INTRODUCTION: Many falls in older adults occur during walking and result in lateral falls. The ability to perform a recovery step after balance perturbation determines whether a fall will occur. AIM: To investigate age-related changes in first recovery step kinematics and kinematic adaptations over a wide range of lateral perturbation magnitudes while walking. METHODS: Thirty-five old (78.5 ± 5 years) and 19 young adults (26.0 ± 0.8 years) walked at their preferred walking speed on a treadmill. While walking, the subjects were exposed to announced right/left perturbations in different phases of the gait cycle that were gradually increased in order to trigger a recovery stepping response. The subjects were instructed to react naturally and try to avoid falling. Kinematic analysis was performed to analyze the first recovery step parameters (e.g., step initiation, swing duration, step length, and the estimated distance of the center of mass from the base of support [dBoS]). RESULTS: Compared with younger adults, older adults displayed a significantly lower step threshold and at lower perturbation magnitudes during the experiment. Also, they showed slower compensatory step initiation, shorter step length, and dBoS with similar step recovery times. As the perturbation magnitudes increased, older adults showed very small, yet significant, decreases in the timing of the step response, and increased their step length. Younger adults did not show changes in the timing of stepping, with a tendency toward a significant increase in step length. CONCLUSIONS: First compensatory step performance is impaired in older adults. In terms of the dynamic approach, older adults were more flexible, i.e., less automatic, while younger adults displayed more automatic behavior.

Insufficient Balance Recovery Following Unannounced External Perturbations in Persons With Stroke.

Background. Persons with stroke (PwS) are at increased risk of falls, especially toward the paretic side, increasing the probability of a hip fracture. The ability to recover from unexpected loss of balance is a critical factor in fall prevention. Objectives. We aimed to compare reactive balance capacity and step kinematics between PwS and healthy controls. Methods. Thirty subacute PwS and 15 healthy controls were exposed to forward, backward, right, and left unannounced surface translations in 6 increasing intensities while standing. Single step threshold, multiple step threshold, and fall threshold (ie, perturbation intensity leading to a fall into harness system) were recorded as well as reactive step initiation time, step length, and step velocity. Results. Twenty-five PwS fell into harness system during the experiment while healthy controls did not fall. Fourteen out of 31 falls occurred in response to surface translations toward the nonparetic side, that is, falling toward the paretic side. Compared with healthy controls, PwS demonstrated significantly lower fall threshold and multiple step threshold in response to forward, backward, and lateral surface translations. Impairments were more pronounced in response to forward surface translation and toward the nonparetic side (ie, loss of balance toward the paretic side). A trend toward significant shorter step length in response to lateral surface translations was found in PwS compared with healthy controls. Conclusions. Findings highlight the importance of assessing reactive balance capacity in response to perturbations in different directions and intensities in addition to the routine assessment in PwS.

Effects of Perturbation-Based Balance Training in Subacute Persons With Stroke: A Randomized Controlled Trial.

BACKGROUND: Reactive balance responses are critical for fall prevention. Perturbation-based balance training (PBBT) has shown a positive effect in reducing the risk of falls among older adults and persons with Parkinson's disease. OBJECTIVE: To explore the effect of a short-term PBBT on reactive balance responses, performance-based measures of balance and gait and balance confidence. METHODS: Thirty-four moderate-high functioning, subacute persons with stroke (PwS) (lower extremity Fugl-Meyer score 29.2 ± 4.3; Berg Balance Scale [BBS] score 43.8 ± 9.5, 42.0 ± 18.7 days after stroke onset) hospitalized in a rehabilitation setting were randomly allocated to PBBT (n = 18) and weight shifting and gait training (WS>) (n = 16). Both groups received 12 training sessions, 30 minutes each, for a period of 2.5 weeks. PBBT included unexpected balance perturbations during standing and treadmill walking, WS> included weight shifting in standing and treadmill walking without perturbations. The main outcome measures, that is, multiple step-threshold and fall-threshold were examined at baseline, immediately postintervention, and about 5 weeks postintervention. The secondary outcome measures, that is, BBS, 6-minute walk test (6MWT), 10-meter walk test (10MWT), and Activity-specific Balance Confidence (ABC) scale were examined at baseline and immediately postintervention. RESULTS: Compared with the WS> group, immediately postintervention participants in the PBBT group showed higher multiple-step thresholds in response to forward and backward surface translations (effect size [ES] = 1.07 and ES = 1.10, respectively) and moderate ES in the ABC scale (ES = 0.74). No significant differences were found in fall-threshold, BBS, 6MWT, and 10MWT between the groups. CONCLUSIONS: Inclusion of perturbation training during rehabilitation of PwS improved reactive balance and balance confidence.

Using Deep Learning for Image-Based Potato Tuber Disease Detection.

Many plant diseases have distinct visual symptoms, which can be used to identify and classify them correctly. This article presents a potato disease classification algorithm that leverages these distinct appearances and advances in computer vision made possible by deep learning. The algorithm uses a deep convolutional neural network, training it to classify the tubers into five classes: namely, four disease classes and a healthy potato class. The database of images used in this study, containing potato tubers of different cultivars, sizes, and diseases, was acquired, classified, and labeled manually by experts. The models were trained over different train-test splits to better understand the amount of image data needed to apply deep learning for such classification tasks. The models were tested over a data set of images taken using standard low-cost RGB (red, green, and blue) sensors and were tagged by experts, demonstrating high classification accuracy. This is the first article to report the successful implementation of deep convolutional networks, popular in object identification, to the task of disease identification in potato tubers, showing the potential of deep learning techniques in agricultural tasks.

Comparing RGB-D Sensors for Close Range Outdoor Agricultural Phenotyping.

Phenotyping is the task of measuring plant attributes for analyzing the current state of the plant. In agriculture, phenotyping can be used to make decisions concerning the management of crops, such as the watering policy, or whether to spray for a certain pest. Currently, large scale phenotyping in fields is typically done using manual labor, which is a costly, low throughput process. Researchers often advocate the use of automated systems for phenotyping, relying on the use of sensors for making measurements. The recent rise of low cost, yet reasonably accurate, RGB-D sensors has opened the way for using these sensors in field phenotyping applications. In this paper, we investigate the applicability of four different RGB-D sensors for this task. We conduct an outdoor experiment, measuring plant attribute in various distances and light conditions. Our results show that modern RGB-D sensors, in particular, the Intel D435 sensor, provides a viable tool for close range phenotyping tasks in fields.

The inter-observer reliability and agreement of lateral balance recovery responses in older and younger adults.

The purpose of this study was to evaluate the inter-observer reliability and agreement of balance recovery responses, step and multiple-steps thresholds, and kinematic parameters of stepping responses. Older and younger adults were exposed to 36 progressively challenging right and left unannounced surface translations during quiet standing. Subjects were instructed to "react naturally". Step threshold and multiple-step threshold were defined as the minimum disturbance magnitude that consistently elicited one and more than one recovery step, respectively. Fall threshold is defined as the minimum disturbance magnitude from which a fall resulted (i.e., fall into harness system or grasped one of the anchor straps of the harness, or grasped the research assistant to maintain balance). The inter-observer reliability of balance recovery responses for older adults were excellent, especially for step and multiple-step thresholds (ICC2,1 = 0.978 and ICC2,1 = 0.971, respectively; p < 0.001). Also kinematic parameters of stepping responses such as step recovery duration and step length were excellent (ICC2,1 > 0.975 and ICC2,1 = 0.978, respectively; p < 0.001), substantial reliability was found for swing phase duration (ICC2,1 = 0.693, p < 0.001). Younger adults showed similar ICCs. The Bland-Altman plots demonstrated excellent limits of agreement (LOA > 90%) for most kinematic step parameters and stepping thresholds. These results suggest that balance recovery responses and kinematic parameters of stepping including step threshold and multiple-step threshold are extremely reliable parameters. The measure of balance recovery responses from unexpected loss of balance is feasible and can be used in clinical setting and research-related assessments of fall risk.

Validity of the microsoft kinect system in assessment of compensatory stepping behavior during standing and treadmill walking.

BACKGROUND: Rapid compensatory stepping plays an important role in preventing falls when balance is lost; however, these responses cannot be accurately quantified in the clinic. The Microsoft Kinect™ system provides real-time anatomical landmark position data in three dimensions (3D), which may bridge this gap. METHODS: Compensatory stepping reactions were evoked in 8 young adults by a sudden platform horizontal motion on which the subject stood or walked on a treadmill. The movements were recorded with both a 3D-APAS motion capture and Microsoft Kinect™ systems. The outcome measures consisted of compensatory step times (milliseconds) and length (centimeters). The average values of two standing and walking trials for Microsoft Kinect™ and the 3D-APAS systems were compared using t-test, Pearson's correlation, Altman-bland plots, and the average difference of root mean square error (RMSE) of joint position. RESULTS: The Microsoft Kinect™ had high correlations for the compensatory step times (r = 0.75-0.78, p = 0.04) during standing and moderate correlations for walking (r = 0.53-0.63, p = 0.05). The step length, however had a very high correlations for both standing and walking (r > 0.97, p = 0.01). The RMSE showed acceptable differences during the perturbation trials with smallest relative error in anterior-posterior direction (2-3%) and the highest in the vertical direction (11-13%). No systematic bias were evident in the Bland and Altman graphs. CONCLUSIONS: The Microsoft Kinect™ system provides comparable data to a video-based 3D motion analysis system when assessing step length and less accurate but still clinically acceptable for step times during balance recovery when balance is lost and fall is initiated.

Validating bifidobacterial species and subspecies identity in commercial probiotic products.

BACKGROUND: The ingestion of probiotics to attempt to improve health is increasingly common; however, quality control of some commercial products can be limited. Clinical practice is shifting toward the routine use of probiotics to aid in prevention of necrotizing enterocolitis in premature infants, and probiotic administration to term infants is increasingly common to treat colic and/or prevent atopic disease. Since bifidobacteria dominate the feces of healthy breast-fed infants, they are often included in infant-targeted probiotics. METHODS: We evaluated 16 probiotic products to determine how well their label claims describe the species of detectable bifidobacteria in the product. Recently developed DNA-based methods were used as a primary means of identification, and were confirmed using culture-based techniques. RESULTS: We found that the contents of many bifidobacterial probiotic products differ from the ingredient list, sometimes at a subspecies level. Only 1 of the 16 probiotics perfectly matched its bifidobacterial label claims in all samples tested, and both pill-to-pill and lot-to-lot variation were observed. CONCLUSION: Given the known differences between various bifidobacterial species and subspecies in metabolic capacity and colonization abilities, the prevalence of misidentified bifidobacteria in these products is cause for concern for those involved in clinical trials and consumers of probiotic products.

Task-based decomposition of factored POMDPs.

Recently, partially observable Markov decision processes (POMDP) solvers have shown the ability to scale up significantly using domain structure, such as factored representations. In many domains, the agent is required to complete a set of independent tasks. We propose to decompose a factored POMDP into a set of restricted POMDPs over subsets of task relevant state variables. We solve each such model independently, acquiring a value function. The combination of the value functions of the restricted POMDPs is then used to form a policy for the complete POMDP. We explain the process of identifying variables that correspond to tasks, and how to create a model restricted to a single task, or to a subset of tasks. We demonstrate our approach on a number of benchmarks from the factored POMDP literature, showing that our methods are applicable to models with more than 100 state variables.

Evaluating point-based POMDP solvers on multicore machines.

Recent scaling up of partially observable Markov decision process solvers toward realistic applications is largely due to point-based methods which quickly provide approximate solutions for midsized problems. New multicore machines offer an opportunity to scale up to larger domains. These machines support parallel execution and can speed up existing algorithms considerably. In this paper, we evaluate several ways in which point-based algorithms can be adapted to parallel computing. We overview the challenges and opportunities and present experimental results, providing evidence to the usability of our suggestions.