Virtual Reality-Based Parallel Coordinates Plots Enhanced with Explainable AI and Data-Science Analytics for Decision-Making Processes

We present a refinement of the Immersive Parallel Coordinates Plots (IPCP) system for Virtual Reality (VR). The evolved system provides data-science analytics built around a well-known method for visualization of multidimensional datasets in VR. The data-science analytics enhancements consist of importance analysis and a number of clustering algorithms including a novel SuMC (Subspace Memory Clustering) solution. These analytical methods were applied to both the main visualizations and supporting cross-dimensional scatter plots. They automate part of the analytical work that in the previous version of IPCP had to be done by an expert. We test the refined system with two sample datasets that represent the optimum solutions of two different multi-objective optimization studies in turbomachinery. The first one describes 54 data items with 29 dimensions (DS1), and the second 166 data items with 39 dimensions (DS2). We include the details of these methods as well as the reasoning behind selecting some methods over others.

The importance of body composition assessment in the rehabilitation process

Introduction. This personal study provides several aspects of the importance of body composition assessment in rehabilitation process in order to manage fat mass (FM), fat-free mas imbalances (FFM), pre-sarcopenia status, sarcopenia and risks association and to improve global functionality. Health outcomes and risk estimations regarding fat mass and skeletal muscle mass (SMM) plays a major role and should be integrated into the rehabilitation process routine in order to avoid functional impairment and physical disability by applying specific kinetic programs. Material and method. A number of 14 subjects classified as outpatients who have received physical therapy at home- kinesiotherapy for post-fracture / dislocation status of the lower limbs in accordance with the medical recommendations and legislation in force. At the end of the rehabilitation phase, the body composition was measured using bio impedance in order to adjust the next step of the active rehabilitation. The measurements were obtained with a completely bioelectrical impedance analyzer (BIA). Single frequency BIA (SF-BIA) was used. For each subject major body compartments determined as FFM (including bone mineral tissue, total body water-TBW and visceral protein), SMM and FM were measured as a tissue-system by means of linear empirical equations stored in the system memory together with personal physical data. IBM SPSS software version 25 was used for statistical analysis. Results and discussions. Four age groups determined as follows: 21.43% for 18-39 years, 50-69 years, >70 years each and 35.71% for 40-49 years, based on the rate of muscle loss, because its integrity is essential for rehabilitation program. From the 14 subjects there are 57.14 % men and 42.86% women, from urban environment 78.57% and rural 21.43%. Mean Age is 48.79 years ± 18.792 Std. Deviation. Fat mass from BIA recorded 21.43% cases low and normal each, and high/very high 57.14% of total cases. Consequently, of BMI (body mass index) association, 57.14% are at normal weight, 35.71% overweight and with obesity and 7.14% underweight. One Sample Chi-Square test applied to BMI Type Associate with FM reveals the statistical significance, < .05(.014). Fat-free mass index (FFMI), fat mass index (FMI), skeletal mass index (SMI) were computed by adjusted with height square. FMI somatotype components results are 64.3% adipose cases, 21.4% intermediate and 14.3% lean. One Sample Chi-Square test applied to FMI Types reveals the statistical significance < .05(.046). Regression equation of standard BMI and FMI with scatter plots for 77.8% of cases was computed in the present study. FFMI somatotype components recorded 57.1% intermediate cases, 21.4% slender and solid each. Regression equation of standard BMI and FFMI with scatter plots for 57.4% of cases was computed. Three patients exceeded 15 seconds at the chair stand test so probable sarcopenia was identified. From BIA were extracted the value for the skeletal mass and SMI was calculated by height adjusted: 13 (92.86%) cases have normal values and one (7.14%) case have optimal value. Regression equation of standard BMI and SMI with scatter plots for 66.4% of cases was computed. Pearson correlation (CI =99%) denotes strong statistical relationship between BMI and FMI (r=0.882), FFMI (r=0.815), Age (r=0.659), Water (r=-0.693). FMI also correlates strongly with Age (r= 0.707), Water (r=-0.925) and Proteins values (r=-0.819). FFMI also correlates strongly with SMI (r=0.984). Water correlates with Protein (r=0.848, CI = 99%). Beta regression analysis strongly correlates SMI prediction with FFMI (ß=0.731), Water (ß=0.138) and Protein (ß=-0.370) for p<0.05. Anova significance of .000 (CI=99%) with applicability of 99.8% of the cases (R2 =0.998) proved that constant predictors: Water (%), FFMI, Proteins (%), FMI, BMI interact to influence SMM variability. 64.25% of subjects recorded an insufficient water level and 71.43% of subjects recorded an insufficient proteins level. Body composition evaluation should be integrated into routine clinical practice for the initial assessment and sequential follow-up and the strongest point of BIA is the possibility to replace invasive laboratory analysis with a quick, noninvasive test that can be carried out in a medical office. Body composition evaluation should be performed at the different stages of the disease, during the course of treatments and the rehabilitation phase. Conclusions. For each patient specific kinetic program will be developed. FMI increase (64.3% adipose cases) denotes the risk of metabolic syndrome and insulin resistance. Consequently, resistive and concentric exercises will be applied. For FFMI loss (57.1% intermediate cases, 21.4% slender) and SMI increasing (92.86% cases have normal values but not optimal ones, 21.43% pre-sarcopenia detected by positive chair test) resistance, eccentric/concentric exercises should be applied. All kinetic programs will be preceded by warm-up and followed by stretching taking into account cardiac reserve for each patient. Maximal/sub-maximal force exercises will be used age-related. Additional water (64.25% of subjects recorded an insufficient water level) and proteins levels (71.43% of subjects recorded an insufficient proteins level) must be balanced by nutritional support in accordance with rehabilitation consult and current physician approval in the interdisciplinary team. BIA may be an important supporting tool for health professionals in order to customize the rehabilitation programs for each patient. Keywords: body composition, rehabilitation, bioelectrical impedance, fat-free mass index, fat mass index, skeletal muscle index,

Analysis of lncRNAs and mRNA Expression in the ZBTB1 Knockout Monoclonal EL4 Cell Line and Combined Analysis With miRNAs and circRNAs

In previous experiments, we identified the effect of deletion of the Zbtb1 gene on circRNAs and microRNAs. In this study, we examined the expression profiles of lncRNAs and mRNAs using the RNA-seq method for Zbtb1-deficient EL4 cells and performed a clustering analysis of differentially expressed lncRNAs and mRNAs. GO term histograms and KEGG scatter plots were drawn. For the experimental results, a joint analysis was performed, which predicted the regulatory relationships among lncRNAs, mRNAs, microRNAs and circRNAs. For the regulatory relationship between lncRNAs and target genes, the chromatin structure and the degree of openness were verified for the possible target gene locations regulated by lncRNA using experimental methods such as Hi-C and ATAC-seq. Ultimately, the possible differential regulation of the Brcal and Dennd5d genes by lncRNAs and the differential changes in transcription factor binding sites in the promoter region were identified. For neRNA-regulated target genes with significantly differentially expressed mRNAs, a combined screen was performed, and the final obtained candidate target genes were subjected to GO and KEGG term enrichment analyses. Our results illustrate that the Zbtb1 gene can not only function as a regulatory factor but also regulate EL4 cells from multiple perspectives based on ceRNA theory.

A machine learning approach to predict the stress results of quadratic tetrahedral elements

Industries are always looking for an effective and efficient way to reduce the computation time of simulation because of the huge expenditure involved. From basics of Finite Element Method (FEM), it is known that, linear order finite elements consume less computation time and are less accurate compared to higher order finite elements say quadratic elements. An approach to get the benefit of less computation cost of linear elements and the good accuracy of quadratic elements can be of a good thought. The methodology to get the accurate results of quadratic elements with the advantage of less simulation run time of linear elements is presented here. Machine Learning (ML) algorithms are found to be effective in making predictions based on some known data set. The present paper discusses a methodology to implement ML model to predict the results equivalent to that of quadratic elements based on the solutions obtained from the linear elements. Here, a ML model is developed using python code, the stress results from Finite Element (FE) model of linear tetrahedral elements is given as the input to it to predict the stress results of quadratic tetrahedral elements. Abaqus is used as the FEM tool to develop the FE models. A python script is used to extract the stresses and the corresponding node numbers. The results showed that the developed ML model is successful in prediction of the accurate stress results for the set of test data. The scatter plots showed that the Z-score method was effective in removing the singularities. The proposed methodology is effective to reduce the computation time for simulation.

U-CIE [/juː ’siː/]: Color encoding of high-dimensional data

U-CIE is a visualization method that encodes arbitrary high-dimensional data as colors using a combination of dimensionality reduction and the CIELAB color space to retain the original structure to the extent possible. We illustrate its broad applicability by visualizing single-cell data on a protein network and metagenomic data on a world map and on scatter plots. U-CIE is available as a web resource at https://u-cie.jensenlab.org/ and as an R package.

Bedside determination of microcirculatory oxygen delivery and uptake: a prospective observational clinical study for proof of principle

Assessment of microcirculatory functional capacity is considered to be of prime importance for therapy guidance and outcome prediction in critically ill intensive care patients. Here, we show determination of skin microcirculatory oxygen delivery and consumption rates to be a feasible approach at the patient’s bedside. Real time laser-doppler flowmetry (LDF) and white light spectrophotometry (WLS) were used for assessment of thenar skin microperfusion, regional Hb and postcapillary venous oxygen saturation before and after forearm ischemia. Adapted Fick’s principle equations allowed for calculation of microcirculatory oxygen delivery and uptake. Patient groups with expected different microcirculatory status were compared [control (n = 20), sepsis-1/2 definition criteria identified SIRS (n = 10) and septic shock patients (n = 20), and the latter group further classified according to sepsis-3 definition criteria in sepsis (n = 10) and septic shock (n = 10)], respectively. In otherwise healthy controls, microcirculatory oxygen delivery and uptake approximately doubled after ischemia with maximum values (mDO2max and mVO2max) significantly lower in SIRS or septic patient groups, respectively. Scatter plots of mVO2max and mDO2max values defined a region of unphysiological low values not observed in control but in critically ill patients with the percentage of dots within this region being highest in septic shock patients. LDF and WLS combined with vasoocclusive testing reveals significant differences in microcirculatory oxygen delivery and uptake capacity between control and critically ill patients. As a clinically feasible technique for bedside determination of microcirculatory oxygen delivery and uptake, LDF and WLS combined with vasoocclusive testing holds promise for monitoring of disease progression and/or guidance of therapy at the microcirculatory level to be tested in further clinical trials.ClinicalTrials.gov: NCT01530932.

Non-linear behavior of root and stem diameter changes in monopodial orchid

Precision agriculture aims to maximize yield with optimum resources. Vast majority of natural systems are acknowledged as complex and non-linear. However, prior to formulation of precise models, linearity tests are performed to validate plant behavior. This study has presented proof that the water uptake system in monopodial orchid is indeed non-linear. The change in physical growth of root and stem due to temperature and relative humidity factors are observed. The work focused on Ascocenda Fuchs Harvest Moon x (V. Chaophraya x Boots) orchid hybrid. Three complementary methods are presented: linearity tests through 1) regression fitting; 2) scatter plots; and 3) cross-correlation function tests. Root diameter, stem diameter, temperature, and relative humidity are logged at 15 minutes interval for a duration of 71 days. The polynomial equations derived for root diameter and stem diameter changes attained strong regression coefficients. The non-linear behavior is further confirmed by the scatter plots where no linear associations are present between the independent and dependent variables. Subsequently, the cross-correlation function tests conducted on temperature-root diameter, temperature-stem diameter, relative humidity-root diameter, and relative humidity-stem diameter combinations also revealed weak correlation. Despite using different techniques, the behavior of physical changes has been consistently proven to be non-linear.

No Diagnostic Utility of Zero Heparin Control Buffer in Serotonin Release Assay: Findings from a Validation Study

Background: Heparin induced thrombocytopenia (HIT) is a rare immune mediated complication that is triggered in a subset of patients temporal to therapeutic heparin exposure. Laboratory testing is based on screening for the presence of serum anti-PF4 antibodies using sensitive solid-phase immunoassays. If antibodies are detected, functional testing to demonstrate the platelet activating properties and heparin dependence of these immune complexes is then performed. Previous studies have reported possible clinical utility in identifying non heparin dependent platelet activating antibodies using a buffer control with zero heparin in the serotonin release functional assay (SRA). These reports suggested a correlation between reactivity in the zero heparin buffer control and pathogenicity of HIT antibodies which may define a subtype of HIT, referred to as autoimmune HIT. We aimed to investigate the utility of zero heparin buffer control as a part of an inhouse validation study of a mass spectrometry-coupled SRA (Mayo-SRA). Methods: Three hundred archived serum samples were tested using anti-PF4 IgG antibody enzyme-linked immunosorbent assay (ELISA; Immucor Diagnostics, GA, USA). SRA was preformed on all samples using Mayo-SRA and reference 14C SRA methods. Zero heparin control buffer was included in the Mayo-SRA assay. Serotonin release &gt;20% in the low dose heparin (0.1U/mL, LDH) and ELISA optical density (OD) &gt;0.4 were considered positive. Drug interference studies were performed by spiking known SRA-positive samples with increasing concentrations of unfractionated heparin (UFH), low molecular weight heparin (LMWH) or fondaparinux in the LDH and zero heparin SRA. The clinical 4T score was calculated retrospectively calculated for all patients. Results: Of the 300 tested samples, 57 were anti-PF4 ELISA positive. 33 of the 57 samples were positive using the reference 14C SRA method. Whereas 43 samples were positive by Mayo-SRA assay. Three additional samples were positive by Mayo-SRA, but negative by both screening anti-PF4 ELISA and the reference SRA method (Fig- 1A). Lastly, 13 samples were anti-PF4 ELISA positive, but SRA negative by both methods in comparison. Interestingly, 44 of 46 (95%) samples interpreted positive by LDH were also interpreted positive (serotonin release &gt;20%) under zero heparin conditions. These included the 3 samples that were positive by Mayo-SRA but negative by both screening anti-PF4 ELISA and the reference SRA. The overall % serotonin release using zero heparin control was significantly lower (P= 0.003, paired Student T-test) compared to LDH (Fig-1B). In addition, zero heparin followed a similar pattern as LDH, with highest levels at ELISA OD units &gt;2 (Fig-1C). Strikingly, drug interference studies showed artifactual serotonin release in the zero heparin reaction, which was not detected in the absence of spiked drugs. For UFH, serotonin release in zero heparin control occurred at very low spiked concentrations, ≥0.063 U/mL. LMWH and fondaparinux spiking experiments also displayed similar zero heparin serotonin release patterns (Fig-1D). Of note, none of these interferences were detected in UFH spiked SRA-negative samples (data not shown). Conclusion: Contrary to prior results suggesting that less than 50% of LDH SRA positive samples are also positive in the zero heparin SRA, our results show high zero heparin SRA positivity rate of &gt;95%. Zero heparin SRA showed a pattern with highest levels at ELISA OD units &gt;2 suggesting that reactivity in this condition is a function of antibody strength rather than a qualitative difference (i.e. "autoimmune" HIT antibodies vs "non-autoimmune" HIT antibodies). In addition, contamination of patient sera with small amounts of remnant heparin can significantly impact platelet activation in the zero heparin SRA test. Thus, zero heparin SRA positive results may be artifactual and represent residual heparin contained in the patient sample. Figure legend: Fig-1A. Scatter plots of SRA positive samples grouped by 4T scores. Red dots are Mayo-SRA only positive samples. Fig-1B and Fig-1C. Scatter plots of % serotonin release of Mayo-SRA positive samples at LDH (circles) vs. zero heparin buffers (squares), and grouped by ELISA OD values, respectively. Fig-1D. % Serotonin release of known SRA-positive samples spiked with increasing concentrations of UFH, LMWH, or fondaparinux at LDH (white) or zero heparin buffers (red). Figure 1 Figure 1. Disclosures Pruthi: CSL Behring: Honoraria; Genentech: Honoraria; Bayer Healthcare AG: Honoraria; HEMA Biologics: Honoraria; Instrumentation Laboratory: Honoraria; Merck: Honoraria. Padmanabhan: Veralox Therapeutics: Membership on an entity's Board of Directors or advisory committees.