Category: Statistics

J Mech Behav Biomed Mater. 2021 Dec 3;126:105013. doi: 10.1016/j.jmbbm.2021.105013. Online ahead of print.

ABSTRACT

It is well established that the soft connective tissues show a nonlinear elastic response that comes from their microstructural arrangement. Tissues’ microstructure alters with various physiological conditions and may affect their mechanical responses. Therefore, the accurate prediction of tissue’s mechanical response is crucial for clinical diagnosis and treatments. Thus, a physically motivated and mathematically simplified model is required for the accurate prediction of tissues’ mechanical and structural responses. This study explored the ‘Exp-Ln’ hyperelastic model (Khajehsaeid et al., 2013) to capture soft tissues’ mechanical and histological behaviour. In this work, uniaxial tensile test data for the belly and back pig skin were extracted from the experiments performed in our laboratory, whereas uniaxial test data for other soft tissues (human skin, tendon, ligament, and aorta) were extracted from the literature. The ‘Exp-Ln; and other hyperelastic models (e.g. Money Rivlin, Ogden, Yeoh, and Gent models) were fitted with these experimental data, and obtained results were compared between the models. These results show that the ‘Exp-Ln’ model could capture the mechanical behaviour of soft tissues more accurately than other hyperelastic models. This model was also found numerically stable for all modes and ranges of deformation. This study also investigated the link between ‘Exp-Ln’ material parameters and tissue’s histological parameters. The histological parameters such as collagen content, fibre free length, crosslink density, and collagen arrangement were measured using staining and ATR-FTIR techniques. The material parameters were found statistically correlated with the histological parameters. Further, ‘Exp-Ln’ model was implemented in ABAQUS through the VUMAT subroutine, where the mechanical behaviour of various soft tissues was simulated for different modes of deformation. The finite element analysis results obtained using the ‘Exp-Ln’ model agreed with the experiments and were more accurate than other hyperelastic models. Overall, these results demonstrate the capability of ‘Exp-Ln’ model to predict the mechanical and structural responses of the soft tissues.

PMID:34920323 | DOI:10.1016/j.jmbbm.2021.105013

Cognition. 2021 Dec 14;220:104960. doi: 10.1016/j.cognition.2021.104960. Online ahead of print.

ABSTRACT

How can infants detect where words or morphemes start and end in the continuous stream of speech? Previous computational studies have investigated this question mainly for English, where morpheme and word boundaries are often isomorphic. Yet in many languages, words are often multimorphemic, such that word and morpheme boundaries do not align. Our study employed corpora of two languages that differ in the complexity of inflectional morphology, Chintang (Sino-Tibetan) and Japanese (in Experiment 1), as well as corpora of artificial languages ranging in morphological complexity, as measured by the ratio and distribution of morphemes per word (in Experiments 2 and 3). We used two baselines and three conceptually diverse word segmentation algorithms, two of which rely purely on sublexical information using distributional cues, and one that builds a lexicon. The algorithms’ performance was evaluated on both word- and morpheme-level representations of the corpora. Segmentation results were better for the morphologically simpler languages than for the morphologically more complex languages, in line with the hypothesis that languages with greater inflectional complexity could be more difficult to segment into words. We further show that the effect of morphological complexity is relatively small, compared to that of algorithm and evaluation level. We therefore recommend that infant researchers look for signatures of the different segmentation algorithms and strategies, before looking for differences in infant segmentation landmarks across languages varying in complexity.

PMID:34920298 | DOI:10.1016/j.cognition.2021.104960

Pathol Res Pract. 2021 Dec 6;229:153718. doi: 10.1016/j.prp.2021.153718. Online ahead of print.

ABSTRACT

Histological grade is one of the most important prognosticators of breast cancer which is available for nearly all cases. It also makes part of several multivariable analysis derived combined prognostic profiles despite concerns about its reproducibility. The aims included a reproducibility study of grading in the light of a recently described statistical approach, ONEST (Observers Needed to Evaluate Subjective Tests) and review earlier reproducibility studies in the light of the ONEST analysis. Nine pathologists reviewed 50 core needle biopsies and 50 slides from different excision specimens and recorded the scores for gland (tubule) formation, nuclear pleomorphism and mitotic activity as well as histological grade. Overall percent agreement, Fleiss kappa and the intraclass correlation coefficient (ICC) were used for the analysis of reproducibility. ONEST data and curves were generated from 100 random permutations of the participants. ONEST suggested a minimum of 4 observers for the reliable evaluation of reproducibility for both the scored components and grade in either type of specimen. Our results suggested moderate or moderate to good reproducibility of grading (kappa values of 0.51 for excisions, and 0.54 for biopsies and ICCs of 0.70 and 0.69, respectively) with gland formation being the most and nuclear pleomorphism the worst consistently evaluated feature. In studies with sufficient participants (at least 4) and non-pairwise comparisons in the analysis, the reproducibility of histological grading is fair to moderate, whereas studies with fewer participants or pairwise kappa analysis suggest moderate to almost prefect agreement of the results. ONEST is a valuable complementation of reproducibility analyses.

PMID:34920295 | DOI:10.1016/j.prp.2021.153718

ESMO Open. 2021 Dec 14;7(1):100338. doi: 10.1016/j.esmoop.2021.100338. Online ahead of print.

ABSTRACT

BACKGROUND: Vascular endothelial growth factor receptor (VEGFR)-targeted tyrosine kinase inhibitors (TKIs) are widely used in cancer treatment and burdened by cardiovascular toxicity. The majority of data come from clinical trials, thus in selected populations. The aim of our study is to evaluate the cardiotoxicity profile of VEGFR-targeted TKIs and the impact of cardiovascular risk factors in a real-life population.

PATIENTS AND METHODS: In this cohort, population-based study, patients treated with VEGFR-targeted TKIs, bevacizumab and trastuzumab between 2009 and 2014 were analyzed. A multi-source strategy for data retrieval through hospital, pharmaceutical and administrative databases of the Lombardy region, Italy, has been adopted. The primary endpoint was to determine the incidence and type of major adverse cardiovascular events (MACEs) along with their temporal trend. The secondary endpoint was to define the impact of cardiovascular risk factors in the occurrence of MACEs.

RESULTS: A total of 829 patients were treated with VEGFR-targeted TKIs. Eighty-one MACEs occurred in the first year of follow-up [crude cumulative incidence (CCI): 9.79%] mainly consisting of arterial thrombotic events (ATEs, 31 events, CCI: 3.99%), followed by rhythm disorders (22 events, CCI: 2.66%), pulmonary embolisms and heart failures (13 events each, CCI: 1.57%). While the incidence of most MACEs showed a plateau after 6 months, ATEs kept increasing along the year of follow-up. Hypertension and dyslipidemia were associated with an increase in risk of ATEs [relative risk difference (RRD) +209.8% and +156.2%, respectively], while the presence of previous MACEs correlated with a higher risk of all MACEs in multivariate analysis (RRD 151.1%, 95% confidence interval 53.6% to 310.3%, P < 0.001).

CONCLUSIONS: MACEs occur in a clinically significant proportion of patients treated with VEGFR-targeted TKIs, with ATEs being predominant, mainly associated with hypertension and dyslipidemia. A clinical algorithm for effective proactive management of these patients is warranted.

PMID:34920290 | DOI:10.1016/j.esmoop.2021.100338

Environ Int. 2021 Dec 14;159:107046. doi: 10.1016/j.envint.2021.107046. Online ahead of print.

ABSTRACT

Single nucleotide polymorphisms (SNPs) of cytochrome P450 (CYPs) and UDP-glucuronosyltransferase (UGTs) genes have been proposed to influence phthalates and 1,2-cyclo-hexanedicarboxylic acid diisononyl ester (DINCH) biotransformation but have not been investigated on a populational level. We investigated the role of SNPs in CYP2C9, CYP2C19, CYP2D6, UGT2B15, and UGT1A7 genes in the biotransformation of phthalates (DEHP, DEP, DiBP, DnBP, BBzP, DiNP, DidP) and DINCH by determining their urine metabolites. From the Slovenian study population of 274 men and 289 lactating primiparous women we obtained data on phthalate and DINCH urine metabolite levels (MEHP, 5OH-MEHP, 5oxo-MEHP, 5cx-MEPP, MEP, MiBP, MnBP, MBzP, cx-MINP, OH-MiDP, MCHP, MnPeP, MnOP, 5OH-MINCH, 5oxo-MINCH), SNP genotypes (rs1057910 = CYP2C9*3, rs1799853 = CYP2C9*2, rs4244285 = CYP2C19*2, rs12248560 = CYP2C19*17, rs3892097 = CYP2D6*4, rs1902023 = UGT2B15*2, and rs11692021 = UGT1A7*3) and questionnaires. Associations of SNPs with levels of metabolites and their ratios were assessed by multiple linear regression and ordinary logistic regression analyses. Significant associations were observed for CYP2C9*2, CYP2C9*3, CYP2C19*17, and UGT1A7*3 SNPs. The most pronounced was the influence of CYP2C9*2 and *3 on the reduced DEHP biotransformation, with lower levels of metabolites and their ratios in men and women. In contrast, carriers of CYP2C19*17 showed higher urine levels of DEHP metabolites in both genders, and in women also in higher DiNP, DiDP, and DINCH metabolite levels. The presence of UGT1A7*3 was associated with increased metabolite levels of DINCH in men and of DiBP and DBzP in women. Statistical models explained up to 27% of variability in metabolite levels or their ratios. Our observations confirm the effect of CYP2C9*2 and *3 SNPs towards reduced DEHP biotransformation. We show that CYP2C9*2, CYP2C9*3, CYP2C19*17, and UGT1A7*3 SNPs might represent biomarkers of susceptibility or resilience in phthalates and DINCH exposure that have been so far unrecognised.

PMID:34920277 | DOI:10.1016/j.envint.2021.107046

J Environ Manage. 2021 Dec 14;304:114236. doi: 10.1016/j.jenvman.2021.114236. Online ahead of print.

ABSTRACT

In the present work, a suitable experimental setup was developed to successfully apply advanced oxidation processes (AOP) to real groundwater matrices. This setup combines an O₃-bubble column reactor with a carrier-bound TiO₂/UV-system. The degradation of various chlorinated ethene and methane derivatives commonly found of chlorinated volatile organic compound polluted regional groundwater samples was investigated. Because of known issues within water remediation using AOP such as toxification by transformation products, this study aimed at complete mineralization of the contained organic micropollutants. Moreover, the influences of variable process parameters such as flow rate, ozone concentration, and radiation dose on process performance were statistically evaluated and discussed. Parameter optimization using a Box-Behnken experimental design resulted in very promising degradation rates. It was thus possible to achieve a degradation rate of at least 98% for cis-dichloroethene, trichloroethene and tetrachloroethene and 85% for trichloromethane without formation of transformation products. The results of this work open up the possibility of developing innovative technologies based on AOP, which can be universally applied even to challenging matrices such as groundwater.

PMID:34920281 | DOI:10.1016/j.jenvman.2021.114236

Talanta. 2021 Dec 10;239:123140. doi: 10.1016/j.talanta.2021.123140. Online ahead of print.

ABSTRACT

In this study, a new approach for PLS modelling for low-correlated multiple responses, called Common-Subset-of-Independent-Variables Partial-Least-Squares, denoted as CSIV-PLS1, is proposed and evaluated. In CSIV-PLS1, for each response vector, individual PLS1 models with individual model complexities are developed, based on one common set of independent variables, obtained after variable selection by the Final Complexity Adapted Models method, using the absolute values of the PLS regression coefficients, denoted as FCAM-REG. CSIV-PLS1 combines a common variable set for all response vectors, which is a characteristic of PLS2, with the individual model complexity for each response, which is a characteristic of PLS1. These characteristics make CSIV-PLS1 more flexible than PLS2. The selective and predictive abilities of the proposed CSIV-PLS1 method are investigated using one simulated and four real data sets with low-correlated multiple responses from different sources. The simulated data set is used to test the general applicability of the CSIV-PLS1 method. The predictive abilities, measured by the RMSEP values, resulting from CSIV-PLS1 models, are statistically compared with those of the corresponding PLS1 and PLS2 models, using one-tailed paired t-tests. The selective ability of the CSIV-PLS1 method is good, because mostly variables with an informative meaning to the responses are selected. The RMSEP values resulting from the CSIV-PLS1 method are (i) significantly lower at the 95% confidence level than those of the corresponding PLS2 method, and (ii) borderline significantly lower at the 90-95% confidence level than those of the corresponding PLS1 methods. In case of low-correlated multiple responses, the predictive ability of the CSIV-PLS1 method is significantly better than that of the PLS2 method, and borderline significantly better than those of the corresponding PLS1 methods. Therefore, CSIV-PLS1 modelling may be an alternative for PLS1 or PLS2.

PMID:34920253 | DOI:10.1016/j.talanta.2021.123140

Talanta. 2021 Dec 8;239:123131. doi: 10.1016/j.talanta.2021.123131. Online ahead of print.

ABSTRACT

Developing a sensitive portable sensor for the screening of illicit drugs is always challenging. Due to the importance of pethidine (PTD) tracking in addiction diagnosis, many demands have recently increased for a selective and real-time sensor. Herein, a simple electrochemical sensor has been developed based on conductive carbon cloth (CC) modified with carbon selenide nanofilms (CSe₂NF) to provide a CSe₂NF/CC electrode as a novel PTD sensing tool. Profiting from the ingenious design of doping strategy during the synthesis process, Se was doped in the carbonaceous skeleton of the CC. Thus, the active surface area of the CSe₂NF (4.61 cm²) increased respect to the unmodified CC (0.094 cm²) to embed a suitable sensing interface in the fast PTD assay. By optimizing some effective experimental parameters such as pH, supporting electrolyte, Se powder amount, scan rate and accumulation time, the sensor catalyzed efficiently the oxidation reaction of PTD at 0.97 V. Based on peak current variations, the PTD was measured over a broad concentration range from 29 nM up to 181.8 μM with a limit of detection (LOD) as low as 19.3 nM compared to the other reported PTD sensors. The developed flexible sensor recognized the spiked PTD concentrations in some biofluids, including human blood, urine and saliva. The results of PTD analysis in the non-spiked and spiked blood, urine and saliva samples as the real samples by the developed sensor were validated by HPLC analysis as the reference method using t-test statistical method at confidence level of 5%. This sensing strategy based on the binder-free electrode could be promising for designing some sizable wearable sensors at a low cost. The high sensitivity of the sensor, which is a bonus for the rapid and on-site measurement of PTD, may open up a route for noninvasive routine analysis in clinical samples.

PMID:34920261 | DOI:10.1016/j.talanta.2021.123131

J Equine Vet Sci. 2021 Oct 29;109:103798. doi: 10.1016/j.jevs.2021.103798. Online ahead of print.

ABSTRACT

The study investigated between-rider differences in pelvic roll and pitch motion during horseback riding as the horse walked around circles without rein contact (walk on long reins), with rein contact, and with moderate collection. Ten horses were ridden by five riders on left and right 10 m circles, in a partly crossed design, yielding 14 trials. Each trial included each of the three walk variations in both directions. Riders wore an inertial measurement unit (IMU), logging at 100 Hz, dorsally on the pelvis. Pelvic roll and pitch data were split into strides based on data from IMU-sensors on the horse’s hind cannons. Data were analyzed using signal decomposition into the fundamental frequency (the stride frequency) and its first two harmonics. Mixed models accounting for the type of walk were used to analyze how riders differed in roll and pitch pelvic motion in two ways: comparing amplitudes of the frequency components and comparing whole stride mean data. Graphically pelvic pitch showed substantial timing and amplitude differences between riders, and this was confirmed statistically. Pelvic roll timing was similar, but amplitude varied between the riders, both graphically and statistically. Individual rider patterns tended to persist across different horses and all exercises. These results suggest that exercises at walk can be ridden with different pelvis pitch timing, a fact that has so far not been discussed in the equestrian literature. Whether pelvic pitch timing affects the horse’s performance remains to be investigated.

PMID:34920247 | DOI:10.1016/j.jevs.2021.103798

J Thromb Haemost. 2021 Dec 17. doi: 10.1111/jth.15623. Online ahead of print.

ABSTRACT

INTRODUCTION: Patients with lower-leg cast immobilization and patients undergoing knee arthroscopy have an increased risk of venous thrombosis (VT). Guidelines are ambiguous about thromboprophylaxis use and individual risk factors for developing VT are often ignored. To assist in VT risk stratification and guide thromboprophylaxis use, various prediction models have been developed. These models depend largely on clinical factors and provide reasonably good C-statistics of around 70%. We explored using protein levels in blood plasma measured by multiplexed quantitative targeted proteomics to predict VT. Our aim was to assess whether a VT risk prediction model based on absolute plasma protein quantification is possible.

METHODS: We used internal standards to quantify proteins in less than 10 μL plasma. We measured 270 proteins in samples from patients scheduled for knee arthroscopy or with lower-leg cast immobilization. The two prospective POT-(K)CAST trails allow complementary views of VT signature in blood, namely pre and post trauma, respectively. From approximately 3,000 patients, 31 patients developed VT who were included and matched with double the number of controls.

RESULTS: Top discriminating proteins between cases and controls included APOC3, APOC4, APOC2, ATRN, F13B, and F2 in knee arthroscopy patients and APOE, SERPINF2, B2M, F13B, AFM, and C1QC in patients with lower-leg cast. A logistic regression model with cross-validation resulted in C-statistics of 88.1% (95%CI: 85.7-90.6%) and 79.6% (95% CI: 77.2-82.0%) for knee arthroscopy and cast immobilization groups respectively.

CONCLUSIONS: Promising C-statistics merit further exploration of the value of proteomic tests for predicting VT risk upon additional validation.

PMID:34919779 | DOI:10.1111/jth.15623