A Light Weight Smartphone Based Human Activity Recognition System with High Accuracy

With the pervasive use of smartphones, which contain numerous sensors, data for modeling human activity is readily available. Human activity recognition is an important area of research because it can be used in context-aware applications. It has significant influence in many other research areas and applications including healthcare, assisted living, personal fitness, and entertainment. There has been a widespread use of machine learning techniques in wearable and smartphone based human activity recognition. Despite being an active area of research for more than a decade, most of the existing approaches require extensive computation to extract feature, train model, and recognize activities. This study presents a computationally efficient smartphone based human activity recognizer, based on dynamical systems and chaos theory. A reconstructed phase space is formed from the accelerometer sensor data using time-delay embedding. A single accelerometer axis is used to reduce memory and computational complexity. A Gaussian mixture model is learned on the reconstructed phase space. A maximum likelihood classifier uses the Gaussian mixture model to classify ten different human activities and a baseline. One public and one collected dataset were used to validate the proposed approach. Data was collected from ten subjects. The public dataset contains data from 30 subjects. Out-of-sample experimental results show that the proposed approach is able to recognize human activities from smartphones’ one-axis raw accelerometer sensor data. The proposed approach achieved 100% accuracy for individual models across all activities and datasets. The proposed research requires 3 to 7 times less amount of data than the existing approaches to classify activities. It also requires 3 to 4 times less amount of time to build reconstructed phase space compare to time and frequency domain features. A comparative evaluation is also presented to compare proposed approach with the state-of-the-art works

Comparison of different bronchial closure techniques following pneumonectomy in dogs

The comparison of the histologic healing and bronchopleural fistula (BPF) complications encountered with three different BS closure techniques (manual suture, stapler and manual suture plus tissue flab) after pneumonectomy in dogs was investigated for a one-month period. The dogs were separated into two groups: group I (GI) (n = 9) and group II (GII) (n = 9). Right and left pneumonectomies were performed on the animals in GI and GII, respectively. Each group was further divided into three subgroups according to BS closure technique: subgroup I (SGI) (n = 3), manual suture; subgroup II (SGII) (n = 3), stapler; and subgroup III (SGIII) (n = 3), manual suture plus tissue flab. The dogs were sacrificed after one month of observation, and the bronchial stumps were removed for histological examination. The complications observed during a one-month period following pneumonectomy in nine dogs (n = 9) were: BPF (n = 5), peri-operative cardiac arrest (n = 1), post-operative respiratory arrest (n = 1), post-operative cardiac failure (n = 1) and cardio-pulmonary failure (n = 1). Histological healing was classified as complete or incomplete healing. Histological healing and BPF complications in the subgroups were analyzed statistically. There was no significant difference in histological healing between SGI and SGIII (p = 1.00; p > 0.05), nor between SGII and SGIII (p = 1.00; p > 0.05). Similarly, no significant difference was observed between the subgroups in terms of BPF (p = 0.945; p > 0.05). The results of the statistical analysis indicated that manual suture, stapler or manual suture plus tissue flab could be alternative methods for BS closure following pneumonectomy in dogs

Longitudinal data reveal strong genetic and weak non-genetic components of ethnicity-dependent blood DNA methylation levels

Epigenetic architecture is influenced by genetic and environmental factors, but little is known about their relative contributions or longitudinal dynamics. Here, we studied DNA methylation (DNAm) at over 750,000 CpG sites in mononuclear blood cells collected at birth and age 7 from 196 children of primarily self-reported Black and Hispanic ethnicities to study race-associated DNAm patterns. We developed a novel Bayesian method for high-dimensional longitudinal data and showed that race-associated DNAm patterns at birth and age 7 are nearly identical. Additionally, we estimated that up to 51% of all self-reported race-associated CpGs had race-dependent DNAm levels that were mediated through local genotype and, quite surprisingly, found that genetic factors explained an overwhelming majority of the variation in DNAm levels at other, previously identified, environmentally-associated CpGs. These results indicate that race-associated blood DNAm patterns in particular, and blood DNAm levels in general, are primarily driven by genetic factors, and are not as sensitive to environmental exposures as previously suggested, at least during the first 7 years of life

Epithelial-Associated Inflammatory Pathways Underlie Residual Asthma Exacerbations in Urban Children Treated with Mepolizumab Therapy

Rationale: Identification of airway inflammatory pathways in asthma has proven essential to understanding mechanisms of disease and has led to effective personalized treatment with biologic therapies. However, relatively little is known about patterns of airway inflammation at the time of respiratory illnesses and how such patterns relate to responsiveness to biologic therapies. Methods: The MUPPITS-1 (n=106) and MUPPITS-2 (n=290) studies investigated asthma exacerbations in urban children with exacerbation-prone asthma and ≥150/microliter blood eosinophils. Children in both studies received guidelines-based asthma care; in MUPPITS-2, participants were additionally randomized (1:1) to placebo or mepolizumab. Nasal lavage samples were collected during respiratory illnesses for RNA-sequencing and analyzed by modular analysis to assess genome-wide expression patterns associated with exacerbation illnesses. Results: Among 284 illnesses, exacerbations that occurred in the absence of mepolizumab therapy showed significantly higher upregulation of eosinophil associated inflammatory pathways (fold change values [FC]=1.27-1.43, p-values\u3c0.05), including a Type-2 inflammation module composed of eosinophil, mast cell, and IL-13 response genes. In contrast, exacerbations that occurred while on mepolizumab therapy showed significantly higher upregulation of several epithelial inflammatory pathways (FC=1.36-1.64, p-values\u3c0.05) including TGF-β/Smad3 signaling, extracellular matrix production, and epidermal growth factor receptor signaling. Conclusions: These results indicate that novel inflammatory pathways, likely originating from the airway epithelium and distinct from Type-2 or eosinophilic inflammation, drive residual exacerbations that occur in children treated with mepolizumab therapy added to guideline-based care. These findings identify likely mechanisms of persistent disease expression in these children despite significant depletion of eosinophils and can identify novel treatment targets for future studies

Mepolizumab Alters Regulation of Airway Type-2 Inflammation in Urban Children with Asthma by Disrupting Eosinophil Gene Expression but Enhancing Mast Cell and Epithelial Pathways

Rationale: Mepolizumab (anti-IL5) reduces asthma exacerbations in urban children. We previously utilized nasal transcriptomics to identify inflammatory pathways (gene co-expression modules) associated with exacerbations despite this therapy. To understand mepolizumab’s precise impact on these pathways, we assess gene co-expression and loss of correlation, “decoherence,” using differential co-expression network analyses. Methods: 290 urban children (6-17 years) with exacerbation-prone asthma and blood eosinophils ≥150/microliter were randomized (1:1) to q4 week placebo or mepolizumab injections added to guideline-based care for 52 weeks. Nasal lavage samples were collected before and during treatment for RNA-sequencing. Differential co-expression of gene networks was evaluated to assess interactions and regulatory aspects of type-2 and eosinophilic airway inflammation. Results: Mepolizumab, but not placebo, significantly reduced the overall expression of an established type-2 inflammation gene co-expression module (fold change=0.77, p=0.002) enriched for eosinophil, mast cell, and epithelial IL-13 response genes (242 genes). Mepolizumab uncoupled co-expression of genes in this pathway. During mepolizumab, but not placebo treatment, there was significant loss of correlation among eosinophil-specific genes including RNASE2 (EDN), RNASE3 (ECP), CLC, SIGLEC8, and IL5RA contrasting a reciprocal increase in correlation among mast cell-specific genes (TPSAB1, CPA3, FCER1A), T2 cytokines (IL4, IL5, and IL13), and POSTN. Conclusions: These results suggest mepolizumab disrupts the regulatory interactions of gene co-expression among airway eosinophils, mast cells and epithelium by interrupting transcription regulation in eosinophils with enhancement in mast cell and epithelial inflammation. This paradoxical effect may contribute to an incomplete reduction of asthma exacerbations and demonstrates how differential co-expression network analyses can identify targets for more precise therapies

An Individualized Risk Calculator for Research in Prodromal Psychosis

About 20–35% of individuals aged 12–30 years who meet criteria for a prodromal risk syndrome convert to psychosis within two years. However, this estimate ignores the fact that clinical high-risk (CHR) cases vary considerably in risk. Here we sought to create a risk calculator that can ascertain the probability of conversion to psychosis in individual patients based on profiles of risk indicators. The high risk category predicted by this calculator can inform research criteria going forward

Down-Modulation of Cockroach (CR) Allergen-specific Th2 Cell Responses Following Subcutaneous German Cockroach Allergen Immunotherapy (SCIT)

Rationale: The responses of T cells to subcutaneous allergen immunotherapy (SCIT) are not fully elucidated. We conducted a functional immunological evaluation of cockroach (CR) allergen-specific CD4+ T cell reactivity in the double-blinded, placebo-controlled, multi-center CRITICAL study. Methods: Participants (8-17 years of age) with mild to moderate, well-controlled asthma received 12 months of maintenance dosing of CR SCIT (n=20) or placebo (n=26). Peripheral blood mononuclear cells (PBMC) were isolated prior to, and after 12 months of therapy. CD4+ T cell responses at baseline and after treatment were assessed using overlapping peptide pools derived from 11 well-defined CR allergens and intracellular cytokine staining for IL-4, IFNg, and IL-10 production. T cell responses were further evaluated in terms of magnitude, cytokine polarization, and allergen immunodominance. Results: Significant down-modulation of the total magnitude of CD4+ T cell responses was observed with SCIT but not placebo, with a significant change between groups (-4.46±0.82 vs. −1.81±0.72, respectively, p = 0.020). Responses were driven by a decrease in IL-4 (-4.87±0.86 vs. −1.09±0.75, p = 0.002) with unaltered IFNg and IL-10 production, reflecting a shift towards a Th1 polarization profile (1.35±0.58 vs. −0.37±0.50, in SCIT and placebo respectively, p = 0.031). The largest effects were observed against the allergens Bla g 5 and Bla g 9, which are dominantly recognized, suggesting that dominant responses are susceptible to modulation. Conclusions: Our results demonstrate a significant down-regulation of CR-specific Th2 cell responses in urban children with asthma who received SCIT, compared with those who received placebo

A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology

Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients.We propose the interval coded scoring (ICS) system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems.The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the proposed methodology towards automated detection of interaction effects, multi-class decision support systems, prognosis and high-dimensional data

Distinct Airway Inflammatory Pathways Associated with Asthma Exacerbations are Modulated by Mepolizumab Therapy in Children

Rationale: Identification of specific airway inflammatory pathways can lead to effective personalized treatment with biologics in asthma and insights to mechanisms of action. Methods: 290 urban children with exacerbation-prone asthma and ≥150/mm3 blood eosinophils were randomized (1:1) to placebo or mepolizumab added to guideline-based care. Nasal lavage samples were collected at randomization and during treatment for RNA-sequencing, and analyzed by cell-deconvolution modular analysis to assess genome-wide expression patterns associated with exacerbation number and effect of treatment. Results: Mepolizumab significantly reduced the frequency of exacerbations compared to placebo. At randomization, there were no differences in expression between treatment groups; multiple modules were subsequently differentially expressed during mepolizumab but not placebo treatment. Furthermore, expression levels of multiple modules were associated with the exacerbation number during the study, with distinct relationships observed in the placebo and/or mepolizumab groups. Notably, higher expression at randomization of an eosinophil-associated module enriched for Type-2 genes including IL4, IL5, and IL13, was associated with increased exacerbations in placebo (β=0.19, p\u3c0.001), but not mepolizumab-treated children (interaction p\u3c0.01). Furthermore, mepolizumab treatment reduced expression of this module (Fold-change=0.62, p\u3c0.001). In contrast, higher expression at randomization of an eosinophil-associated module enriched for eosinophil activation (e.g. CD9) and mucus hypersecretion (e.g. MUC5AC) genes was associated with exacerbation number in both groups throughout the study (β=0.18, p\u3c0.01) and was unaltered by mepolizumab therapy. Conclusions: Multiple distinct airway inflammation patterns were identified associated with exacerbation frequency. These findings identify inflammatory endotypes and indicate likelihood and potential mechanisms of a beneficial clinical response to mepolizumab therapy to prevent exacerbations

The Effect of Subcutaneous German Cockroach Immunotherapy (SCIT) on Nasal Allergen Challenge (NAC) and Cockroach-specific Antibody Responses Among Urban Children and Adolescents

Rationale: Cockroach allergy contributes to asthma and rhinitis morbidity among many urban children. Treatment with cockroach SCIT could be beneficial. Methods: 8-17 year-old children with mild-moderate asthma from 11 urban sites participated in a randomized double-blind placebo-controlled SCIT trial using non-standardized, glycerinated German cockroach extract. Positive cockroach skin tests, cockroach-specific IgE, and nasal challenge response with total nasal symptom scores (TNSS) ≥6 or maximal sneeze scores of 3 during a graded NAC were required for enrollment. Following dose escalation, 0.4 ml of undiluted extract was targeted for maintenance dosing (∼7 mcg Bla g2/dose). The primary endpoint was change in NAC-induced mean TNSS from baseline to one year post randomization. Changes in cockroach-specific IgE (CRsIgE) and IgG4 (CRsIgG4) were also analyzed. Results: Mean TNSS did not significantly change from baseline in either group (placebo n=29, SCIT n=28). There was no significant difference in the change in mean TNSS between placebo and SCIT [−0.79±0.35 vs. −1.02±0.37, respectively, difference=0.2(−1.15, 0.70), p=0.63]. Baseline CRsIgE and CRsIgG4 didn’t differ between groups. Mean CRsIgE decreased in both groups following treatment: 3.6 to 2.3 kU/L (0.64 fold change), p=0.015 and 8.3 to 4.2 kU/L (0.51 fold change), p\u3c0.001 in placebo and SCIT respectively, but did not differ between groups [p=0.33]. Significant increases in CRsIgG4 post-treatment were observed among SCIT recipients only: 0.07 to 12.3 mg/L (176 fold change), p\u3c0.001. Conclusions: Cockroach SCIT increased CRsIgG4 levels but did not significantly alter NAC-induced TNSS responses. The extent to which NAC in these children may reflect clinical efficacy for rhinitis or asthma is uncertain