Multivitamin consumption and childhood asthma: a cross-sectional study of the NHANES database

Abstract Background Dietary intakes of vitamins are associated with asthma. However, previous studies mainly explored the association between a single vitamin intake and asthma, which did not take the multivitamins into consideration. Herein, this study aims to explore the overall effect of dietary multivitamins consumption on childhood asthma. Methods Data of children and adolescents (aged 2-17 years old) were extracted from the National Health and Nutrition Examination Survey (NHANES) database in 2015-2018 in this cross-sectional study. Weighted univariate logistic regression analysis was used to screen covariates. The association between multivitamins (including vitamin A, C, D, E, B1, B2, B6, B12, K, niacin, folic acid, and choline) and childhood asthma was explored using univariate and multivariate logistic regression analyses. The evaluation indexes were odds ratio (OR) and 95% confidence interval (CI). We further introduced the Bayesian kernel machine regression (BKMR) to assess the joint effect of the twelve vitamins on childhood asthma, the impact of an individual vitamin as part of a vitamin mixture, and the potential interactions among different vitamins. Results Among 4,715 eligible children and adolescents, 487 (10.3%) had asthma. After adjusting for covariates including race, family history of asthma, pregnant smoking, BMI Z-score, energy intake, breast feeding, and low birth weight, we found that for each 1-unit increase in vitamin K consumption, the odds of childhood asthma decreased 0.99 (P=0.028). The overall effect analysis reported a trend of negative relationship between the multivitamins and childhood asthma, especially at the 75th percentile and over. According to the BKMR models, when other vitamins are fixed at the median level, the odds of childhood asthma increased along with the elevated vitamin D (VD) and vitamin B2 (VB2), whereas along with the depressed vitamin C (VC). In addition, no potential interaction has been found between every two vitamins of multivitamins on childhood asthma. Conclusion Among children and adolescents who have high-risk of asthma, it may be beneficial to increase dietary consumption of multivitamins. Our findings recommended that children and adolescents should increase the intake of VC-rich foods, whereas control the dietary consumption of VD and VB2 in daily life

Early acquired resistance to EGFR-TKIs in lung adenocarcinomas before radiographic advanced identified by CT radiomic delta model based on two central studies

Abstract Early acquired resistance (EAR) to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) in lung adenocarcinomas before radiographic advance cannot be perceived by the naked eye. This study aimed to discover and validate a CT radiomic model to precisely identify the EAR. Training cohort (n = 67) and internal test cohort (n = 29) were from the First Affiliated Hospital of Fujian Medical University, and external test cohort (n = 29) was from the Second Affiliated Hospital of Xiamen Medical College. Follow-up CT images at three different times of each patient were collected: (1) baseline images before EGFR-TKIs therapy; (2) first follow-up images after EGFR-TKIs therapy (FFT); (3) EAR images, which were the last follow-up images before radiographic advance. The features extracted from FFT and EAR were used to construct the classic radiomic model. The delta features which were calculated by subtracting the baseline from either FFT or EAR were used to construct the delta radiomic model. The classic radiomic model achieved AUC 0.682 and 0.641 in training and internal test cohorts, respectively. The delta radiomic model achieved AUC 0.730 and 0.704 in training and internal test cohorts, respectively. Over the external test cohort, the delta radiomic model achieved AUC 0.661. The decision curve analysis showed that when threshold of the probability of the EAR to the EGFR-TKIs was between 0.3 and 0.82, the proposed model was more benefit than treating all patients. Based on two central studies, the delta radiomic model derived from the follow-up non-enhanced CT images can help clinicians to identify the EAR to EGFR-TKIs in lung adenocarcinomas before radiographic advance and optimize clinical outcomes

Maize yield estimation in intercropped smallholder fields using satellite data in southern Malawi

Satellite data provide high potential for estimating crop yield, which is crucial to understanding determinants of yield gaps and therefore improving food production, particularly in sub-Saharan Africa (SSA) regions. However, accurate assessment of crop yield and its spatial variation is challenging in SSA because of small field sizes, widespread intercropping practices, and inadequate field observations. This study aimed to firstly evaluate the potential of satellite data in estimating maize yield in intercropped smallholder fields and secondly assess how factors such as satellite data spatial and temporal resolution, within-field variability, field size, harvest index and intercropping practices affect model performance. Having collected in situ data (field size, yield, intercrops occurrence, harvest index, and leaf area index), statistical models were developed to predict yield from multisource satellite data (i.e., Sentinel-2 and PlanetScope). Model accuracy and residuals were assessed against the above factors. Among 150 investigated fields, our study found that nearly half were intercropped with legumes, with an average plot size of 0.17 ha. Despite mixed pixels resulting from intercrops, the model based on the Sentinel-2 red-edge vegetation index (VI) could estimate maize yield with moderate accuracy (R 2 = 0.51, nRMSE = 19.95%), while higher spatial resolution satellite data (e.g., PlanetScope 3 m) only showed a marginal improvement in performance (R 2 = 0.52, nRMSE = 19.95%). Seasonal peak VI values provided better accuracy than seasonal mean/median VI, suggesting peak VI values may capture the signal of the dominant upper maize foliage layer and may be less impacted by understory intercrop effects. Still, intercropping practice reduces model accuracy, as the model residuals are lower in fields with pure maize (1 t/ha) compared to intercropped fields (1.3 t/ha). This study provides a reference for operational maize yield estimation in intercropped smallholder fields, using free satellite data in Southern Malawi. It also highlights the difficulties of estimating yield in intercropped fields using satellite imagery, and stresses the importance of sufficient satellite observations for monitoring intercropping practices in SSA. </p

Wide-Range Linear Iontronic Pressure Sensor with Two-Scale Random Microstructured Film for Underwater Detection

A broad linear range of ionic flexible sensors (IFSs) with high sensitivity is vital to guarantee accurate pressure acquisition and simplify back-end circuits. However, the issue that sensitivity gradually decreases as the applied pressure increases hinders the linearity over the whole working range and limits its wide-ranging application. Herein, we design a two-scale random microstructure ionic gel film with rich porosity and a rough surface. It increases the buffer space during compression, enabling the stress deformation to be more uniform, which makes sure that the sensitivity maintains steady as the pressure loading. In addition, we develop electrodes with multilayer graphene produced by a roll-to-roll process, utilizing its large interlayer spacing and ion-accessible surface area. It benefits the migration and diffusion of ions inside the electrolyte, which increases the unit area capacitance and sensitivity, respectively. The IFS shows ultra-high linearity and a linear range (correlation coefficient ∼ 0.9931) over 0–1 MPa, an excellent sensitivity (∼12.8 kPa–1), a fast response and relaxation time (∼20 and ∼30 ms, respectively), a low detection limit (∼2.5 Pa), and outstanding mechanical stability. This work offers an available path to achieve wide-range linear response, which has potential applications for attaching to soft robots, followed with sensing slight disturbances induced by ships or submersibles

Wide-Range Linear Iontronic Pressure Sensor with Two-Scale Random Microstructured Film for Underwater Detection

A broad linear range of ionic flexible sensors (IFSs) with high sensitivity is vital to guarantee accurate pressure acquisition and simplify back-end circuits. However, the issue that sensitivity gradually decreases as the applied pressure increases hinders the linearity over the whole working range and limits its wide-ranging application. Herein, we design a two-scale random microstructure ionic gel film with rich porosity and a rough surface. It increases the buffer space during compression, enabling the stress deformation to be more uniform, which makes sure that the sensitivity maintains steady as the pressure loading. In addition, we develop electrodes with multilayer graphene produced by a roll-to-roll process, utilizing its large interlayer spacing and ion-accessible surface area. It benefits the migration and diffusion of ions inside the electrolyte, which increases the unit area capacitance and sensitivity, respectively. The IFS shows ultra-high linearity and a linear range (correlation coefficient ∼ 0.9931) over 0–1 MPa, an excellent sensitivity (∼12.8 kPa–1), a fast response and relaxation time (∼20 and ∼30 ms, respectively), a low detection limit (∼2.5 Pa), and outstanding mechanical stability. This work offers an available path to achieve wide-range linear response, which has potential applications for attaching to soft robots, followed with sensing slight disturbances induced by ships or submersibles

Wide-Range Linear Iontronic Pressure Sensor with Two-Scale Random Microstructured Film for Underwater Detection

A broad linear range of ionic flexible sensors (IFSs) with high sensitivity is vital to guarantee accurate pressure acquisition and simplify back-end circuits. However, the issue that sensitivity gradually decreases as the applied pressure increases hinders the linearity over the whole working range and limits its wide-ranging application. Herein, we design a two-scale random microstructure ionic gel film with rich porosity and a rough surface. It increases the buffer space during compression, enabling the stress deformation to be more uniform, which makes sure that the sensitivity maintains steady as the pressure loading. In addition, we develop electrodes with multilayer graphene produced by a roll-to-roll process, utilizing its large interlayer spacing and ion-accessible surface area. It benefits the migration and diffusion of ions inside the electrolyte, which increases the unit area capacitance and sensitivity, respectively. The IFS shows ultra-high linearity and a linear range (correlation coefficient ∼ 0.9931) over 0–1 MPa, an excellent sensitivity (∼12.8 kPa–1), a fast response and relaxation time (∼20 and ∼30 ms, respectively), a low detection limit (∼2.5 Pa), and outstanding mechanical stability. This work offers an available path to achieve wide-range linear response, which has potential applications for attaching to soft robots, followed with sensing slight disturbances induced by ships or submersibles

Understanding the maize yield gap in Southern Malawi by integrating ground and remote-sensing data, models, and household surveys

Context: improving the productivity of smallholder farmers in sub-Saharan Africa is a key component in reducing poverty and increasing food security as crop production is a significant source of livelihood for the majority of the population. Still, crop yields show a huge variability in smallholder farming systems whose productivity is poorly measured and understood. Objective: in this work, we estimate maize (Zea Mays) yield gap in Southern Malawi (Phalombe district) and assess drivers of productivity gap under different socio-economic and biophysical contexts. Methods: we use a mixed-method approach which integrates multi-source datasets (including primary ground-truth data we collected in the maize growing season 2019–2020 and secondary remote-sensing data), empirical and process-based crop-growth models (AquaCrop) to calculate the water-limited yield gap. In addition, we analyse the relationship between the relative yield (defined as the actual yield observed at the farmers' plots normalised by the AquaCrop simulated water-limited potential yield) and possible socio-economic drivers which we collected through surveys administered to households iin the same season 2019–2020. Results and Conclusions: we obtained a water-limited potential yield for the maize hybrid SC649 of 9.5 t/ha during the season 2019–2020 in the Malawian trial site. The observed actual yield at the households in the season 2019–2020 varied from 0.8 to 10.9 t/ha. The estimate of the yield gap ranged between 15% and 85% thus showing a large variability due to the high resolution, but low accuracy of the empirical model. Results suggest that with higher income and increased fertiliser application there is potential to increase the relative yield and that the marginal increase is spatially differentiated. SIGNIFICANCE: Our spatially-explicit approach to yield-gap analysis is valuable in identifying high-productive areas and differentiated policy interventions aimed at closing the yield and income gaps for smallholder farmers.</p