Nevin Manimala

Epilepsy Behav. 2021 Dec 14;126:108473. doi: 10.1016/j.yebeh.2021.108473. Online ahead of print.

ABSTRACT

OBJECTIVE: The purpose of this study was to better understand the role of social determinants of health (SDoH) in both treatment delays and treatment gaps for individuals with epilepsy (IWE) enrolled in Arizona’s Medicaid program using predictive models at the population and individual levels.

METHODS: In this retrospective cohort study, two statistical regression models were developed using Arizona Medicaid medical and pharmacy claims records from 2015-2019 and selected census tract-level SDoH data. Three treatment outcomes were defined: timely treatment (treated within thirty days); delayed treatment (treated after thirty days); and untreated. For the first model, least squares regression was used to regress the epilepsy treatment delays on selected SDoH factors at the population-level. For the second model, multinomial logistic regression was used to estimate associations between epilepsy treatment delays and individual-level sociodemographic factors.

RESULTS: Of the 5965 IWE identified with a new epilepsy diagnosis during the study period, 43.1% were treated with a mean delay of 180 days. Among the treated population, 42% received timely treatment. A treatment gap of at least 40.6% and potentially up to 56.9% was calculated. Individuals with epilepsy diagnosed in an inpatient setting or in emergency departments were more likely to be treated and receive timely treatment than those diagnosed in an office or clinic setting. Individuals with epilepsy diagnosed in “other” settings were more likely to go untreated or receive delayed treatment than a patient diagnosed in an office or clinic. Compared to IWE aged 31-50 years, IWE aged 0-30 years were more likely to receive timely treatment, IWE aged 51-64 years were more likely to receive delayed treatment, and IWE aged 65 years or older were more likely to go untreated. Widowed IWE were more likely to go untreated relative to single patients. Individuals with epilepsy experiencing homelessness were also more likely to go untreated. Unemployed IWE were more likely to go untreated or receive delayed treatment. Native American IWE were more likely to go untreated compared to White patients.

CONCLUSIONS: Treatment gaps and treatment delays are experienced by IWE in the Arizona Medicaid population. The SDoH factors predicted to impact treatment delays include care setting, age, race, marital status, homelessness, and employment.

PMID:34920347 | DOI:10.1016/j.yebeh.2021.108473

Prev Vet Med. 2021 Nov 23;198:105548. doi: 10.1016/j.prevetmed.2021.105548. Online ahead of print.

ABSTRACT

Live animal movements generate direct contacts (via the exchange of live animals) and indirect contacts (via the transit of transport vehicles) between farms, which can contribute to the spread of pathogens. However, most analyses focus solely on direct contacts and can therefore underestimate the contribution of live animal movements in the spread of infectious diseases. Here, we used French live duck movement data (2016-2018) from one of the largest transport companies to compare direct and indirect contact patterns between duck farms and evaluate how these patterns were associated with the French 2016-2017 epidemic of highly pathogenic avian influenza H5N8. A total number of 614 farms were included in the study, and two directed networks were generated: the animal introduction network (exchange of live ducks) and the transit network (transit of transport vehicles). Following descriptive analyses, these two networks were scrutinized in relation to farm infection status during the epidemic. Results showed that farms were substantially more connected in the transit network than in the animal introduction network and that the transit of transport vehicles generated more opportunities for transmission than the exchange of live animals. We also showed that animal introduction and transit networks’ statistics decreased substantially during the epidemic (January-March 2017) compared to non-epidemic periods (January-March 2016 and January-March 2018). We estimated a probability of 33.3 % that a farm exposed to the infection through either of the two live duck movement networks (i.e. that was in direct or indirect contact with a farm that was reported as infected in the following seven days) becomes infected within seven days after the contact. However, we also demonstrated that the level of exposure of farms by these two contact patterns was low, leading only to a handful of transmission events through these routes. As a consequence, we showed that live animal movement patterns are efficient transmission routes for HPAI but have been efficiently reduced to limit the spread during the French 2020-2021 epidemic. These results underpin the relevance of studying indirect contacts resulting from the movement of animals to understand their transmission potential and the importance of accounting for both routes when designing disease control strategies.

PMID:34920326 | DOI:10.1016/j.prevetmed.2021.105548

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

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

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

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

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