Towards an efficient one-class classifier for mobile devices and wearable sensors on the context of personal risk detection

In this work, we present a first step towards an efficient one-class classifier well suited for mobile devices to be implemented as part of a user application coupled with wearable sensors in the context of personal risk detection. We compared one-class Support Vector Machine (ocSVM) and OCKRA (One-Class K-means with Randomly-projected features Algorithm). Both classifiers were tested using four versions of the publicly available PRIDE (Personal RIsk DEtection) dataset. The first version is the original PRIDE dataset, which is based only on time-domain features. We created a second version that is simply an extension of the original dataset with new attributes in the frequency domain. The other two datasets are a subset of these two versions, after a feature selection procedure based on a correlation matrix analysis followed by a Principal Component Analysis. All experiments were focused on the performance of the classifiers as well as on the execution time during the training and classification processes. Therefore, our goal in this work is twofold: we aim at reducing execution time but at the same time maintaining a good classification performance. Our results show that OCKRA achieved on average, 89.1% of Area Under the Curve (AUC) using the full set of features and 83.7% when trained using a subset of them. Furthermore, regarding execution time, OCKRA reports in the best case a 33.1% gain when using a subset of the feature vector, instead of the full set of features. These results are better than those reported by ocSVM, in which case, even though the AUCs are very close to each other, execution times are significantly higher in all cases, for example, more than 20 h versus less than an hour in the worst-case scenario. Having in mind the trade-off between classification performance and efficiency, our results support the choice of OCKRA as our best candidate so far for a mobile implementation where less processing and memory resources are at hand. OCKRA reports a very encouraging speed-up without sacrificing the classifier performance when using the PRIDE dataset based only on time-domain attributes after a feature selection procedure

Production of codon optimized Polyomavirus small t antigen in Escherichia coli.

Background: Hauzen et al., went against the dogma that cancer only develops by genetic factors and postulated oncogenic human papillomavirus (HPV) as the etiological agent of cervical cancer (2008). The eleven new human polyomaviruses (HPyVs) identified have been shown to infect humans subclinically from an early age. The small t-antigen (tAg) proteins of polyomaviruses control cellular phosphorylation mechanisms leading to uncontrolled replication cycles and cancer. Mechanisms of transformation and progression to tumor cells, and cellular tropism of the new HPyVs, remain unknown. Availability of recombinant tAg (rtAg) can contribute to understanding them. Methods: tAg coding sequences derived from Merkel cell polyomavirus (MCPyV) genome were codon-optimized, synthesized, cloned in an expression vector (pGEX), and transformed into E. coli. Clones were fermented, induced for expression of the tAG cassette, and purified by IMAC (Immobilized metal affinity chromatography). Results: rtAg produced in bacteria from different expression strains demonstrated distinct expression levels. The rtAg of ~20KDa was produced at the level of 11.3 mg L-1 and folded correctly since antibody 5 anti-MCPyV recognized rtAg. Conclusions: MCPyV tAg was efficiently expressed in E. coli. The availability of rtAg from MCPyV will be useful in immunity diagnostics, structure studies, and investigation of metabolic pathways interference and cell tropism features of HPyVs infections. This especially until cell culture systems for new HPyVs are developed. Acknowledgements: Our sincere gratitude to the Dana-Farber Cancer Institute for gene and antibody samples as well as the National Council of Science and Technology (CONACYT) for the scholarship 304814 to LMRM

Comparison theorems for Lorentzian length spaces with lower timelike curvature bounds

In this article we introduce a notion of normalized angle for Lorentzian pre-length spaces. This concept allows us to prove some equivalences to the definition of timelike curvature bounds from below for Lorentzian pre-length spaces. Specifically, we establish some comparison theorems known as the local Lorentzian version of the Toponogov theorem and the Alexandrov convexity property. Finally, as an application we obtain a first variation Formula for non-negatively curved globally hyperbolic Lorentzian length spaces

Chromium picolinate, biotin, and sodium bicarbonate combination as a dietary supplement in the treatment of type 2 diabetes

Background: Type 2 diabetes mellitus (T2DM) is characterized by hyperglycemia due to insulin resistance, which can lead to micro and macrovascular complications. The importance of glycemic control for prevention demands the need to promote accessible and safe treatments among others in the form of scientifically proven nutritional supplements. Previous studies have suggested that the consumption of bicarbonate-rich mineral water altered blood metabolites and gut microbiome which has beneficial effects on patients with T2DM. Likewise, chromium picolinate and biotin have shown usefulness in glycemic control. The objective of our study was to evaluate the supplementation with chromium picolinate, biotin, and sodium bicarbonate in patients with T2DM. Methods: We planned and supervised the execution of a crossover, randomized, double-blind, placebo-controlled study of patients with the diagnosis of T2DM that was conducted in Diabetes Clinics of the Endocrinology Service of the University Hospital “Dr. José E. González” of the Autonomous University of Nuevo Leon in Monterrey, Mexico from June 2011 to July 2012. Patients’ follow-ups during the study included a day-0 baseline visit and six more visits over the next six months. Efficacy of treatment was assessed by expressing changes in hemoglobin A1c (HbA1c), body mass index (BMI), and blood pressure (BP). Results: Forty-seven (62.6%) of the original 75 patients completed the trial. Regarding the baseline characteristics, 25 (53.1%) of the participants were male and the mean age was 55.23 ± 9.88. The mean HbA1c was 8.38 ± 1.08%, the mean BMI was 29.34 ± 4.64, the mean systolic BP of 143.84 ± 23.6 mm Hg, and the mean diastolic BP of 84.5 ± 12.13 mm Hg. When comparing the changes that occurred after both interventions, we observed that the HbA1c in the active ingredient group decreased (-0.15%) and in the placebo increased (+0.12%) (p=0.148). When we subdivided both groups according to their HbA1c level before the intervention and compared the participants with HbA1c ≥9, the placebo group had an increase of 0.15 ± 1.32 % and the reduction in the active ingredients was -0.68 ± 1.58 % (p=0.158). Conclusions: In our study, we observed that the supplementation with chromium picolinate, biotin, and sodium bicarbonate decreased HbA1c in 3 months compared to the placebo group in which there was an increase, but with a tendency in the statistical analyses. We believe that this could be due to two reasons: the size of our sample, due to the large percentage of participants who dropped out of the study, or because the treatment period to observe a greater difference should have been longer

UniPROBE, update 2015: new tools and content for the online database of protein-binding microarray data on protein-DNA interactions

The Universal PBM Resource for Oligonucleotide Binding Evaluation (UniPROBE) serves as a convenient source of information on published data generated using universal protein-binding microarray (PBM) technology, which provides in vitro data about the relative DNA-binding preferences of transcription factors for all possible sequence variants of a length k (‘k-mers’). The database displays important information about the proteins and displays their DNA-binding specificity data in terms of k-mers, position weight matrices and graphical sequence logos. This update to the database documents the growth of UniPROBE since the last update 4 years ago, and introduces a variety of new features and tools, including a new streamlined pipeline that facilitates data deposition by universal PBM data generators in the research community, a tool that generates putative nonbinding (i.e. negative control) DNA sequences for one or more proteins and novel motifs obtained by analyzing the PBM data using the BEEML-PBM algorithm for motif inference. The UniPROBE database is available at http://uniprobe.org.National Institutes of Health (U.S.) (R01 HG003985)National Science Foundation (U.S.). Graduate Research Fellowship Progra

Correlation between Ct-values and symptoms of COVID-19 patients

Background: Currently available RT-PCR methods for the diagnosis of COVID-19 can give an estimate of the viral load. The cycle threshold value (Ct-value) of the PCR correlates inversely with the viral load; low Ct-values indicate high viral loads and vice versa. Higher viral loads have been seen to correlate with disease severity and infectivity. Therefore, we studied the correlation of the Ct-value of RT-PCR and the most common symptoms of COVID-19 individually. Methods: A prospective and descriptive study was carried out with the subjects that attended our laboratory for a COVID-19 test from September 14, 2020, to January 30, 2021. Subjects filled out a questionnaire with demographic and clinical information prior to taking the naso and oropharyngeal samples. The samples were processed by Vircell SARS-CoV-2 Real-time PCR Kit (Granada, Spain). Statistical analyses were performed using IBM SPSS software. Results: We included 657 positive subjects with complete information, with a median age of 36 (27-47) and a male predominance of 477 (72.6%). Of these, 395 (60.1%) were symptomatic and the median number of symptoms was 2 (0-5). The most predominant symptoms were headache 271 (68.6%), cough 229 (58%), and myalgias 180 (45.6%). The median Ct-value for gene N was 30 (23-36) and for gene E was 31 (23-35). In comparison between symptomatic and asymptomatic subjects, asymptomatic patients had a higher Ct-value (lower viral load) in both genes and a lower age (p Conclusions: The viral load correlates with symptoms within COVID-19, having found that higher viral loads were correlated with symptoms such as headache, cough, and fever, while lower viral loads were correlated with dyspnea, diarrhea, and alterations of smell or taste senses

TBW Assessment by Deuterium Dilution in Spanish Adolescents

Congreso para especialistas en Nutrición, Actividad Física y Composición CorporalINTRODUCTION: Total body water (TBW) assessment is a cornerstone in order to validate equations to estimate body composition components as fat mass and fat free mass. Deuterium dilution technique (D2DT) is considered the gold standard method to assess TBW, however in Spain there are not any reference data using D2DT. The knowledge of specific references for Spanish population must be a goal for the biological studies of Spanish people. OBJECTIVE: It was our aim to assess TBW using the D2DT in a sample of Spanish adolescents. METHODS: 224 specimens of urine from 150 adolescents (113 girls and 111 boys) were taken to analyze. A dose of 0.1 grams of 2D2O per Kg of body weight was administrated; afterwards it was followed by 4-hours stabilization period. The isotope (deuterium oxide (D2O)) dilution method was used to measure TBW with an isotope-ratio mass-spectrometer. Averages by sex and Tanner stages were calculated for %TBW and TBW. General lineal model were used to analyze differences and interactions between groups. RESULTS: %TBW was significantly different between boys and girls (58.98_5.59% vs 55.5_4.28%, P0.05). CONCLUSIONS: This study has been the first in Spain, which have measured TBW in vivo using D2DT. These data can be useful to validate new methods and equations from bioimpedance analysis to estimate TBW.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Coca-Col

Ensemble of one-class classifiers for personal risk detection based on wearable sensor data

This study introduces the One-Class K-means with Randomly-projected features Algorithm (OCKRA). OCKRA is an ensemble of one-class classifiers built over multiple projections of a dataset according to random feature subsets. Algorithms found in the literature spread over a wide range of applications where ensembles of one-class classifiers have been satisfactorily applied; however, none is oriented to the area under our study: personal risk detection. OCKRA has been designed with the aim of improving the detection performance in the problem posed by the Personal RIsk DEtection(PRIDE) dataset. PRIDE was built based on 23 test subjects, where the data for each user were captured using a set of sensors embedded in a wearable band. The performance of OCKRA was compared against support vector machine and three versions of the Parzen window classifier. On average, experimental results show that OCKRA outperformed the other classifiers for at least 0.53% of the area under the curve (AUC). In addition, OCKRA achieved an AUC above 90% for more than 57% of the users

Rational design for the recombinant expression of the Receptor Binding Domain of SARS-CoV-2 Spike Glycoprotein

Background: COVID-19 represents a significant threat to global human health. SARS-CoV-2, the etiologic viral agent, needs to be under-covered at the structural biology level to facilitate the rational design of diagnostic tests and vaccine candidates. SARS-CoV-2 Receptor Binding Domain of Spike protein (RBD-S) acts as the key to open the gate, to enter the cells during infection. Thus, it is a stronger candidate for designing effective antigens for vaccines and diagnostics. Here, we relied on the viral DNA codifying to RBD-S to use synthetic biology for optimizing the recombinant expression of this (rRBD-S) as a proof of concept of rational designs of bioprocess for vaccine candidates and immunogens to improved rapid diagnostic tests. Methods: rRBD-S coding sequences inspired on RBD-S ectodomain from SARS-CoV-2 were designed, codon-optimized, tagged, synthesized, cloned in an expression vector (pD444-MR), and transformed into C41(DE3)pLysS E. coli strain. Expression of recombinant RBD-S was resulting in a protein purified using Ni-IMAC (Nickel Immobilized metal affinity chromatography). Results: rRBD-S produced result in a ~30KDa protein with yields of 4.618 gr L-1. Protein was recovered from the bacterial soluble fraction without refolding process. Conclusions: rRBD-S is an important tool for immunity diagnostics as Lateral-Flow-Devices, structural biology studies, and even as vaccine candidate for combating SARS-CoV-2. Notably considering the advantages of rational subunit vaccines for immune response against other vaccines technologies whose effectiveness in the long-term process has not been demonstrated yet. Acknowledgements: We thank HIDALGO´s Council of Science, Technology and Innovation (CITNOVA) for the GRANT 20201122 to LMRM