Nevin Manimala

Environ Int. 2021 Oct 15;158:106933. doi: 10.1016/j.envint.2021.106933. Online ahead of print.

ABSTRACT

BACKGROUND: The urban environment may influence neurodevelopment from conception onwards, but there is no evaluation of the impact of multiple groups of exposures simultaneously. We investigated the association between early-life urban environment and cognitive and motor function in children.

METHODS: We used data from 5403 mother-child pairs from four population-based birth-cohorts (UK, France, Spain, and Greece). We estimated thirteen urban home exposures during pregnancy and childhood, including: built environment, natural spaces, and air pollution. Verbal, non-verbal, gross motor, and fine motor functions were assessed using validated tests at five years old. We ran adjusted multi-exposure models using the Deletion-Substitution-Addition algorithm.

RESULTS: Higher greenness exposure within 300 m during pregnancy was associated with higher verbal abilities (1.5 points (95% confidence interval 0.4, 2.7) per 0.20 unit increase in greenness). Higher connectivity density within 100 m and land use diversity during pregnancy were related to lower verbal abilities. Childhood exposure to PM2.5 mediated 74% of the association between greenness during childhood and verbal abilities. Higher exposure to PM2.5 during pregnancy was related to lower fine motor function (-1.2 points (-2.1, -0.4) per 3.2 μg/m3 increase in PM2.5). No associations were found with non-verbal abilities and gross motor function.

DISCUSSION: This study suggests that built environment, greenness, and air pollution may impact child cognitive and motor function at five years old. This study adds evidence that well-designed urban planning may benefit children’s cognitive and motor development.

PMID:34662798 | DOI:10.1016/j.envint.2021.106933

Food Chem. 2021 Oct 9;370:131370. doi: 10.1016/j.foodchem.2021.131370. Online ahead of print.

ABSTRACT

In this study, stationary and time-resolvedfluorescence signatures, were statistically and chemometrically analyzed among three typologies of Chardonnay wines (A, B and C) with the objectives to evaluate their sensitivity to acidic and polyphenolic changes. For that purpose, a dataset was built using Excitation Emission Matrices of fluorescence (N = 103) decomposed by a Parallel Factor Analysis (PARAFAC), andfluorescence decays (N = 22), mathematically fitted, using the conventional exponential modeling and the phasor plot representation. Wine PARAFAC component C4 coupledwith its phasor plot g and s values enable the description of malolactic fermentation (MLF) occurrence in Chardonnay wines. Such proxies reflect wine concentration modifications in total acidity, malic/lactic and phenol acids.Lower g values among fresh MLF + wines compared to MLF- wines are explained by a quenching effect on wine fluorophores by both organic and phenolic acids.The combination of multispectral fluorescence parametersopens a novel routinely implementable methodology to diagnose fermentative processes.

PMID:34662797 | DOI:10.1016/j.foodchem.2021.131370

Neuroimage Clin. 2021 Oct 13;32:102857. doi: 10.1016/j.nicl.2021.102857. Online ahead of print.

ABSTRACT

OBJECTIVE: Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson’s disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia.

METHODS: Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1-3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13-20 Hz) and high (21-30 Hz) beta frequency bands and low (31-60 Hz) and high (61-100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures.

RESULTS: Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side.

DISCUSSION: Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes.

PMID:34662779 | DOI:10.1016/j.nicl.2021.102857

Pulm Pharmacol Ther. 2021 Oct 15:102084. doi: 10.1016/j.pupt.2021.102084. Online ahead of print.

ABSTRACT

Leukotriene inhibition, in vitro and in vivo, is found to suppress tumor growth across a variety of cancer cells. A mouse model of lung cancer revealed that the leukotriene inhibitor montelukast induced lung cancer cell death. Based on the preclinical data we hypothesize that exposure to a leukotriene inhibitor is associated with a lower risk of lung cancer. We conducted a national retrospective cohort study among U.S. Veterans with asthma to explore the relationship between leukotriene inhibition and incident lung cancer. We utilize a variety of statistical techniques, including cox proportional hazards models, propensity score matching and falsification testing to examine the association. A total of 558,466 patients met study criteria consisting of 23,730 patients with leukotriene exposure and 534,736 patients with no leukotriene medication use. Leukotriene inhibitor exposure reduced the risk of lung cancer by 17% (HR=0.830; 95% CI= (0.757-0.911)) in the unmatched and 22.2% in the matched analysis (HR=0.778 95% CI=(0.688-0.88)). Falsification testing with appendicitis and rotator cuff injury end points, suggest no evidence of selection bias. However, because treatment was not randomized, residual confounding cannot be ruled out. The pre-clinical data on leukotriene inhibition and lung cancer combined with our database analysis provide intriguing evidence warranting further research into the relationship between leukotrienes and lung cancer.

PMID:34662740 | DOI:10.1016/j.pupt.2021.102084

J Acad Nutr Diet. 2021 Oct 15:S2212-2672(21)01382-4. doi: 10.1016/j.jand.2021.10.015. Online ahead of print.

ABSTRACT

BACKGROUND: Commercial nutrition apps are increasingly used to evaluate diet. Evaluating the comparative validity of nutrient data from commercial nutrition app databases is important to determine the merits of using these apps for dietary assessment.

OBJECTIVE: Nutrient data from four commercial nutrition apps were compared with a research-based food database, Nutrition Data System for Research (NDSR) (2017).

DESIGN: Comparative Validation Study PARTICIPANTS: /Setting: An investigator identified the fifty most frequently consumed foods (22% of total reported foods) from a weight-loss study at Chicago, Illinois (2017). Nutrient data were compared between four commercial databases with NDSR.

MAIN OUTCOME MEASURES: Comparative validity of energy, macronutrients, and other nutrient data (total sugars, fiber, saturated fat, cholesterol, calcium, sodium).

STATISTICAL ANALYSES PERFORMED: Intraclass correlation coefficients (ICCs) evaluated agreement between commercial databases with the NDSR for foods that were primarily un- and minimally processed and by the three most frequently consumed food groups. Bland-Altman plots determined degree of bias for calories between commercial databases and NDSR.

RESULTS: This study observed excellent agreement between NDSR and CalorieKing® (ICC range=0.90-1.00). Compared with NDSR, agreement for Lose It! and MyFitnessPal ranged from good to excellent (ICC range=0.89-1.00), with the exception of fiber in MyFitnessPal (ICC=0.67). Fitbit showed the widest variability with NDSR (ICC range=0.52-0.98). When evaluating by food group, Fitbit had poor agreement for all food groups, with the lowest agreement observed for fiber within the Vegetable group (ICC=0.16). Bland-Altman plots confirmed ICC energy results but also found that MyFitnessPal had the poorest agreement to NDSR (8.35 [133.31] kcal) for all food items.

CONCLUSIONS: Degree of agreement varied by commercial nutrition app. CalorieKing® and Lose It! had mostly excellent agreement with NDSR for all investigated nutrients. Fitbit showed the widest variability in agreement with NDSR for most nutrients, which may reflect how well the app can accurately capture diet.

PMID:34662722 | DOI:10.1016/j.jand.2021.10.015

Eur J Pharm Biopharm. 2021 Oct 15:S0939-6411(21)00260-5. doi: 10.1016/j.ejpb.2021.10.005. Online ahead of print.

ABSTRACT

Pharmaceutical nanotechnology research is focused on smart nano-vehicles, which can deliver active pharmaceutical ingredients to enhance their efficacy through any route of administration and in the most varied therapeutical application. The design and development of new nanopharmaceuticals can be very laborious. In recent years, the application of mathematics, statistics and computational tools is emerging as a convenient strategy for this purpose. The application of Quality by Design (QbD) tools has been introduced to guarantee quality for pharmaceutical products and improve translational research from the laboratory bench into applicable therapeutics. In this review, a collection of basic-concept, historical overview and application of QbD in nanomedicine are discussed. A specific focus has been put on Response Surface Methodology and Artificial Neural Network approaches in general terms and their application in the development of nanomedicine to monitor the process parameters obtaining optimized system ensuring its quality profile.

PMID:34662719 | DOI:10.1016/j.ejpb.2021.10.005

Heart Rhythm. 2021 Oct 15:S1547-5271(21)02235-9. doi: 10.1016/j.hrthm.2021.10.008. Online ahead of print.

ABSTRACT

BACKGROUND: Ventricular fibrillation (VF) is characterised by multiple wavelets and rotors. No equation to predict the number of rotors and wavelets observed during fibrillation has been validated in human VF.

OBJECTIVE: We hypothesized a single equation derived from a Markov M/M/∞ birth-death process, could predict the number of rotors and wavelets occurring in human clinical VF.

METHODS: Epicardial induced VF (256-electrodes) recordings obtained from patients undergoing cardiac surgery were studied (n=12 patients, n=62 epochs). Rate constants for phase singularity (PS, which occur at the pivot points of rotors) and wavefront (WF) formation and destruction were derived by fitting distributions to PS and WF inter-formation and lifetimes. These rate-constants were combined in an M/M/∞ governing equation to predict the number of PS and WF in VF episodes. Observed distributions were compared to those predicted by the M/M/∞ equation.

RESULTS: The M/M/∞ equation accurately predicted average PS and WF number and population distribution, demonstrated in all epochs. Self-terminating episodes of VF were distinguished from VF episodes requiring termination by a trend towards slower PS destruction, and slower rates of PS formation, and a slower mixing rate of the VF process, indicated by larger values of the second-largest eigenvalue modulus (SLEM) of the M/M/∞ birth-death matrix. The longest-lasting PS (associated with rotors) had shorter inter-activation time intervals compared to shorter lasting PS lasting <150 ms (∼1 PS rotation in human VF).

CONCLUSIONS: The M/M/∞ equation explains the number of wavelets and rotors observed, supporting a paradigm of VF based on statistical fibrillatory dynamics.

PMID:34662707 | DOI:10.1016/j.hrthm.2021.10.008

Magn Reson Imaging. 2021 Oct 15:S0730-725X(21)00185-5. doi: 10.1016/j.mri.2021.10.018. Online ahead of print.

ABSTRACT

OBJECTIVES: In this study; we aimed to evaluate the efficacy of the 3D-Dixon-Caipirinha-Vibe fat images in detecting intramural fat accumulation (IFA) and contributions of 3D-Dixon-Caipirinha-Vibe in the management of patients with Chron’s disease.

METHODS: Eighty-five patients who had a 3-tesla MR enterography (MRE) with the 3D-Dixon-Caipirinha-Vibe technique were included. Wall thickness, ADC-value, intramural edema, presence/extension of IFA, and contrast-material enhancement of the affected segments were examined. Findings of MRE were compared statistically with clinical, laboratory, endoscopy, and pathological exams.

RESULTS: The presence of IFA was more common in patients with chronic active and chronic inflammation than only active inflammation and normal cases. Patients with IFA had a longer disease duration than patients without IFA. IFA-containing segment lengths of patients with chronic active inflammation and chronic inflammation were found to be longer than those with active inflammation. It was found that patients whose pathology results were reported as active inflammation contained less IFA than patients with chronic inflammation.

CONCLUSIONS: The presence of IFA is strongly related to chronicity. 3D-Dixon-Caipirinha-Vibe is a fast, easy, and useful method for detecting IFA and evaluating Chron’s disease.

PMID:34662701 | DOI:10.1016/j.mri.2021.10.018

Biosystems. 2021 Oct 15:104562. doi: 10.1016/j.biosystems.2021.104562. Online ahead of print.

ABSTRACT

Quantitative modelling of biological systems using Petri net technologies has experienced renaissance in the past couple of decades. The overwhelming majority of these models is deterministic though underlying biological systems are usually at the mesoscopic level and small, rather than large, and employ sparse molecular structure. Sparse biological systems are accompanied by randomness due to low molecular density, intrinsic random nature of phenomena and noise in an experiment. On the other hand, biochemical reactions are inherently uncertain due to imprecision and vagueness of kinetic parameters. Stochastic methods are used to cope with randomness while fuzzy methods are developed to deal with uncertainty of biological systems, but there is lack of common voice among researchers regarding the best choice of modelling approach for a particular biological system. The main issues addressed in this paper are the choice between deterministic, stochastic and fuzzy parameters and aspects; that is, which modelling approach to follow to reach the realistic approximation of an underlying biological system, and how to measure parallels and discrepancies between different quantitative paradigms. To this end, we use Petri nets with hybrid, stochastic and fuzzy parameters to create quantitative model of p16-mediated signalling pathway in higher eukaryotes, perform deterministic, pure stochastic and fuzzy stochastic simulations to predict the behaviour of major molecular regulators of p16-mediated pathway. In the meanwhile, we show how uncertain kinetic parameters can be precisely approximated in terms of α cuts. Then we perform statistical analysis of simulation results to measure similarity between the three modelling approaches. The statistical analysis reveals significant deviations between deterministic, pure stochastic and fuzzy stochastic approaches for most of the biological components. Due to rather small size of underlying biological system, it turns out that fuzzy stochastic approach is the most appropriate for modelling of p16-mediated signalling pathway because it successfully deals with both randomness and uncertainty and produces quantitative results with biological relevance.

PMID:34662677 | DOI:10.1016/j.biosystems.2021.104562

J Ethnopharmacol. 2021 Oct 15:114754. doi: 10.1016/j.jep.2021.114754. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Erigeron canadensis has been used in traditional medicine to treat a variety of respiratory diseases, including acute upper and lower respiratory tract infections and cough-related asthma. There is as yet no relevant experimental or clinical study in the scientific literature evaluating the efficacy of plants in these disorders.

AIM OF THE STUDY: To investigate the active ingredients in Erigeron canadensis, a complex isolated from flowering parts of a plant was tested for airway defense reflexes, in particular for cough reflexes and airway reactivity. Both were experimentally induced by a chemical irritant that simulated the inflammatory conditions of their formation.

MATERIAL AND METHODS: The polyphenolic polysaccharide-protein (PPP) complex was isolated from the flowering parts of Erigeron canadensis by hot alkaline extraction and a multi-stage purification process. The antitussive activity was confirmed as a decrease in the number of citric acid-induced coughs and the bronchodilator effect was verified as a decrease in specific airway resistance (sRaw) in conscious guinea pigs.

RESULTS: The dark brown Erigeron complex with a molecular weight of 38,000 g/mol contained phenolics (13.2% wt%), proteins (16.3% wt%), and uronic acids (6.3% wt%). The neutral carbohydrate part of Erigeron consisted mainly of xylose (12.1 wt%), glucose (13.3 wt%), arabinose (24.1 wt%), and galactose (41.0 wt%) residues. Arabinogalactan and 4-OMe-glucuronoxylan have been found to be the major polysaccharides in the Erigeron complex. Using a method of chemically-induced cough reflex and guinea pigs test system the Erigeron complex exhibited statistically significant, the dose-dependent antitussive activity, which was similar to that of the centrally-acting opioid agonist codeine.

CONCLUSION: Pharmacological tests have revealed a new pharmacodynamic effect of the Erigeron complex, namely an antitussive effect. Its activity was most pronounced in comparison with all previously tested compounds from other medicinal plants and approached the effect of codeine, the most potent antitussive used in clinical practice. The results provide the scientific basis for the application of this herb in traditional medicine.

PMID:34662663 | DOI:10.1016/j.jep.2021.114754