Bridging agro-science and human nutrition: zinc nanoparticles and biochar as catalysts for enhanced crop productivity and biofortification.

The integration of zinc nanoparticles (Zn NPs) with biochar offers a transformative approach to sustainable agriculture by enhancing plant productivity and human nutrition. This combination improves soil health, optimizes nutrient uptake, and increases resilience to environmental stressors, leading to superior crop performance. Our literature review shows that combining Zn NPs with biochar significantly boosts the crop nutrient composition, including proteins, vitamins, sugars, and secondary metabolites. This enhancement improves the plant tolerance to environmental challenges, crop quality, and shelf life. This technique addresses the global issue of Zn deficiency by biofortifying food crops with increased Zn levels, such as mung beans, lettuce, tomatoes, wheat, maize, rice, citrus, apples, and microgreens. Additionally, Zn NPs and biochar improve soil properties by enhancing water retention, cation exchange capacity (CEC), and microbial activity, making soils more fertile and productive. The porous structure of biochar facilitates the slow and sustained release of Zn, ensuring its bioavailability over extended periods and reducing the need for frequent fertilizer applications. This synergy promotes sustainable agricultural practices and reduces the environmental footprint of the traditional farming methods. However, potential ecological risks such as biomagnification, nanoparticle accumulation, and toxicity require careful consideration. Comprehensive risk assessments and management strategies are essential to ensure that agricultural benefits do not compromise the environmental or human health. Future research should focus on sustainable practices for deploying Zn NPs in agriculture, balancing food security and ecological integrity and positioning this approach as a viable solution for nutrient-efficient and sustainable agriculture.

Preparation of Al@FTCS/P(VDF-HFP) Composite Energetic Materials and Their Reaction Properties.

Strengthening the interfacial contact between the reactive components effectively boosts the energy release of energetic materials. In this study, we aimed to create a close-knit interfacial contact condition between aluminum nanoparticles (Al NPs) and Polyvinylidene fluoride-hexafluoropropylene (P(VDF-HFP)) through hydrolytic adsorption and assembling 1H, 1H, 2H, 2H-Perfluorododecyltrichlorosilane (FTCS) on the surface of Al NPs. Leveraging hydrogen bonding between -CF and -CH and the interaction between C-F⋯F-C groups, the adsorbed FTCS directly leads to the growth of the P(VDF-HFP) coating layer around the treated Al NPs, yielding Al@FTCS/P(VDF-HFP) energetic composites. In comparison with the ultrasonically processed Al/P(VDF-HFP) mixture, thermal analysis reveals that Al@FTCS/P(VDF-HFP) exhibits a 57 °C lower reaction onset temperature and a 1646 J/g increase in heat release. Associated combustion tests demonstrate a 52% shorter ignition delay, 62% shorter combustion time, and a 288% faster pressurization rate. These improvements in energetic characteristics stem from the reactivity activation of FTCS towards Al NPs by the etching effect to the surface Al2O3. Moreover, enhanced interfacial contact facilitated by the FTCS-directed growth of P(VDF-HFP) around Al NPs further accelerates the whole reaction process.

Cadmium Exposure was Associated with Sex-Specific Thyroid Dysfunction: Consistent Evidence from Two Independent Cross-Sectional Studies Based on Urinary and Blood Cadmium Measurements.

Population-based studies on the association between cadmium (Cd) exposure and thyroid function are limited and have shown conflicting results. Two independent cross-sectional studies using different Cd biomarkers were carried out in six rural areas with different soil Cd levels in China. Thyroid dysfunction was defined based on levels of thyroid stimulating hormone (TSH) and free thyroxine (FT4). Multivariable linear regression, multiple logistic regression, and restrictive cubic splines models were used to estimate the association between Cd and thyroid dysfunction. For both of the two independent studies, higher Cd levels were observed to be associated with lower TSH levels and higher risk of thyroid dysfunction. The negative relationship between urinary Cd and TSH was found in both total participants (ß = - 0.072, p = 0.008) and males (ß = - 0.119, p = 0.020) but not in females; however, the negative relationship between blood Cd and TSH was only found in females (ß = - 0.104, p = 0.024). Higher urinary Cd was associated with higher risk of thyroid dysfunction (OR = 1.77, p = 0.031), while higher blood Cd was associated with higher risk of thyroid dysfunction (OR = 1.95, p = 0.011). Results from the two independent cross-sectional studies consistently suggested that higher Cd levels were associated with sex-specific thyroid dysfunction.

Effect of Modified Biochar Prepared by Co-pyrolysis of MgO on Phosphate Adsorption Performance and Seed Germination.

Biochar is currently used as a phosphate adsorbent in water and subsequently as a soil amendment. In this study, modified biochar was prepared directly by co-pyrolysis of MgO and rice straw, and a preliminary ecotoxicological assessment was performed before the application of modified biochar to soil. The effects of single factors, such as pyrolysis temperature, dosage, pH, and coexisting ions, on phosphate adsorption performance were investigated. In addition, after phosphate adsorption, the effects of modified biochar leachate on the germination of corn and rice seeds were examined. The results showed that phosphate adsorption by the modified biochar first increased and then decreased as the pyrolysis temperature increased, with modified biochar prepared at 800 °C showing the greatest adsorption. In addition, a comprehensive cost analysis showed that the best phosphate adsorption effect of modified biochar was achieved at a dosage of 0.10 g and a solution pH of 3. In contrast, the presence of competitive coexisting ions, Cl- , NO3 - , CO3 2- , and SO4 2- , reduced the phosphate adsorption capacity of the modified biochar. The adsorption kinetics results revealed that the process of phosphate adsorption by the modified biochar was more in line with the pseudo-second-order model and dominated by chemisorption. Moreover, the adsorption isotherm results indicated that the process was more in line with the Langmuir model and dominated by monomolecular layer adsorption, with a maximum adsorption of 217.54 mg/g. Subsequent seed germination tests showed that phosphate-adsorbed modified biochar leachate had no significant effect on the germination rate of corn seeds, whereas it improved the germination rate of rice seeds. Together, these results provide guidance for the application of modified biochar firstly as an adsorbent of phosphate and subsequently as a soil remediator.

Higher cadmium exposure was associated with sex-specific thyroid dysfunction: Consistent evidence from two independent cross-sectional studies based on urinary and blood cadmium measurements.

Population-based studies on the association between cadmium (Cd) exposure and thyroid function are limited and have shown conflicting results. Two independent cross-sectional studies using different Cd biomarkers were carried out in six rural areas with different soil Cd levels in China. Thyroid dysfunction was defined based on levels of thyroid stimulating hormone (TSH) and free thyroxine (FT4). Both multivariable linear regression, multiple logistic regression and restrictive cubic splines models were used to estimate the association between Cd and thyroid dysfunction. For both of the two independent studies, higher Cd levels were observed to be associated with lower TSH levels and higher risk of thyroid dysfunction. The negative relationship between urinary Cd and TSH was found in both total participants (ß = -0.072, p = 0.008) and males (ß = -0.119, p = 0.020) but not in females, however, the negative relationship between blood Cd and TSH was only found in females (ß = -0.104, p = 0.024). Higher urinary Cd (> 2.52 µg/g creatinine) was associated with higher risk of thyroid dysfunction, while higher blood Cd was associated with higher risk of hyperthyroidism status. The adjusted Odds Ratio (OR) for the risk of hyperthyroidism status was 3.48 (95%CI:1.36-8.92) and 6.94 (95%CI:1.23-39.31) times higher with every natural log unit higher in blood Cd in total participants and males, respectively. Results from the two independent cross-sectional studies consistently suggested that higher Cd levels were associated with sex-specific thyroid dysfunction.

Which method is more powerful in testing the relationship of theoretical constructs? A meta comparison of structural equation modeling and path analysis with weighted composites.

Structural equation modeling (SEM) has been deemed as a proper method when variables contain measurement errors. In contrast, path analysis with composite scores is preferred for prediction and diagnosis of individuals. While path analysis with composite scores has been criticized for yielding biased parameter estimates, recent literature pointed out that the population values of parameters in a latent-variable model depend on artificially assigned scales. Consequently, bias in parameter estimates is not a well-grounded concept for models involving latent constructs. This article compares path analysis with composite scores against SEM with respect to effect size and statistical power in testing the significance of the path coefficients, via the z- or t-statistics. The data come from many sources with various models that are substantively determined. Results show that SEM is not as powerful as path analysis even with equally weighted composites. However, path analysis with Bartlett-factor scores and the partial least-squares approach to SEM perform the best with respect to effect size and power.

Influence of health literacy of rural junior middle school students on knowledge, attitudes and practices of COVID-19 protection in Jiangxi Province / 中国学校卫生

Objective@#To understand the influence of junior middle school students health literacy on knowledge, belief and behavior of COVID-19 in rural areas of Jiangxi Province, and to enhance junior middle school students ability to deal with public health emergencies.@*Methods@#Stratified cluster random sampling was used to investigate the health literacy, knowledge level and behavior of COVID-19 protection of 4 311 grade 7 to grade 8 students in rural areas of Jiangxi Province; Chi square test and Logistic regression analysis were used to analyze the correlation between junior high school students health literacy and COVID-19 protection knowledge, belief and behavior.@*Results@#The rate of health literacy of junior middle school students in rural areas was 18.21 %( n =785), the reported rate of intermediate level was high ( n =2 454, 56.92%), and the reported rate of junior high school students at a low level of health literacy was 24.87%( n =1 072). The rate of junior middle school students in rural areas with good COVID-19 protection knowledge was 63.49%, the rate of positive protection attitude was 74.25%, and the rate of good protection behavior was 85.36%; Rate of COVID-19 protection knowledge ( OR=4.85, 95%CI =3.80-6.18) and positive rate of protection attitude of high level health literacy ( OR=44.07, 95%CI =24.57-79.05), protective behavior possession rate ( OR=25.99, 95%CI = 19.67-34.35) were higher than those with low level of health literacy( P <0.01).@*Conclusion@#Health literacy is associated with COVID-19 protection knowledge, belief and behavior in rural junior high school students of Jiangxi Province, the findings provide direction for junior middle school students to improve their ability to deal with public health emergencies.

Enhanced phosphate adsorption and desorption characteristics of MgO-modified biochars prepared via direct co-pyrolysis of MgO and raw materials.

Biochar modified by metal ions-particularly Mg-is typically used for the effective recovery of phosphorous. In this study, MgO-modified biochars were synthesized via the direct co-pyrolysis of MgO and raw materials such as rice straw, corn straw, Camellia oleifera shells, and branches from garden waste, which were labeled as MRS, MCS, MOT, and MGW, respectively. The resulting phosphate (PO) adsorption capacities and potential adsorption mechanisms were analyzed. The PO adsorption capacities of the biochars were significantly improved after the modification with MgO: MRS (24.71 ± 0.32 mg/g) > MGW (23.55 ± 0.46 mg/g) > MOT (15.23 ± 0.19 mg/g) > MCS (14.12 ± 0.21 mg/g). PO adsorption on the modified biochars was controlled by physical adsorption, precipitation, and surface inner-sphere complexation processes, although no electrostatic attraction was observed. Furthermore, PO adsorbed on modified biochars could be released under acidic, alkaline, and neutral conditions. The desorption efficiency of MRS was modest, indicating its suitability as a slow-release fertilizer.

Global research trends of artificial intelligence applied in esophageal carcinoma: A bibliometric analysis (2000-2022) via CiteSpace and VOSviewer.

Objective: Using visual bibliometric analysis, the application and development of artificial intelligence in clinical esophageal cancer are summarized, and the research progress, hotspots, and emerging trends of artificial intelligence are elucidated. Methods: On April 7th, 2022, articles and reviews regarding the application of AI in esophageal cancer, published between 2000 and 2022 were chosen from the Web of Science Core Collection. To conduct co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references, and keywords in this field, VOSviewer (version 1.6.18), CiteSpace (version 5.8.R3), Microsoft Excel 2019, R 4.2, an online bibliometric platform (http://bibliometric.com/) and an online browser plugin (https://www.altmetric.com/) were used. Results: A total of 918 papers were included, with 23,490 citations. 5,979 authors, 39,962 co-cited authors, and 42,992 co-cited papers were identified in the study. Most publications were from China (317). In terms of the H-index (45) and citations (9925), the United States topped the list. The journal "New England Journal of Medicine" of Medicine, General & Internal (IF = 91.25) published the most studies on this topic. The University of Amsterdam had the largest number of publications among all institutions. The past 22 years of research can be broadly divided into two periods. The 2000 to 2016 research period focused on the classification, identification and comparison of esophageal cancer. Recently (2017-2022), the application of artificial intelligence lies in endoscopy, diagnosis, and precision therapy, which have become the frontiers of this field. It is expected that closely esophageal cancer clinical measures based on big data analysis and related to precision will become the research hotspot in the future. Conclusions: An increasing number of scholars are devoted to artificial intelligence-related esophageal cancer research. The research field of artificial intelligence in esophageal cancer has entered a new stage. In the future, there is a need to continue to strengthen cooperation between countries and institutions. Improving the diagnostic accuracy of esophageal imaging, big data-based treatment and prognosis prediction through deep learning technology will be the continuing focus of research. The application of AI in esophageal cancer still has many challenges to overcome before it can be utilized.

Relationship between health literacy and unhealthy eating behavior of junior middle school students in rural areas of Jiangxi Province / 中国学校卫生

Objective@#To understand the relationship between health literacy and unhealthy eating behavior of junior middle school students in rural areas of Jiangxi Province, and to provide a reference for specific strategies for healthy eating behavior.@*Methods@#Stratified cluster random sampling was used to investigate the health literacy and unhealthy eating behavior of 4 311 students in grades 7 to 8 from 50 middle schools in rural areas of Jiangxi Province, the relationship between health literacy and unhealthy eating behavior was analyzed by Chi square test and Logistic regression.@*Results@#Health literacy of junior middle school students in rural areas (≥58 points) was 18.21%. Prevalence of unhealthy eating behavior was relatively high, among which irregular three meal time was the highest (62.33%), followed by high consumption of sugar sweetened beverage, insufficient dairy products consumption, breakfast skipping ever day and insufficient consumption of fruits and vegetables, accounting for 54.60%, 50.38 %, 36.23% and 19.53%, respectively. The risk of irregular meal time ( OR =1.35, 95% CI =1.11-1.65), breakfast skipping every day ( OR = 1.23 , 95% CI =1.01-1.49), insufficient dairy products consumption ( OR =1.29, 95% CI =1.07-1.55), insufficient consumption of fruits and vegetables ( OR =1.45, 95% CI =1.10-1.92) and high consumption of sugar sweetened beverage ( OR =1.39, 95% CI = 1.15 -1.68) was higher than students with high health literacy ( P <0.05).@*Conclusion@#There is a correlation between health literacy and unhealthy eating behavior of junior middle school students in rural areas of Jiangxi Province, schools, families, governments and relevant departments can improve the health literacy level of junior high school students to improve their unhealthy eating behavior, so as to improve the health status of junior high school students.

Influence of pyrolysis temperature on the physicochemical properties of biochars obtained from herbaceous and woody plants.

This work aimed to investigate the effect of pyrolysis temperature on the yield and properties of biochars synthesized from herbaceous and woody plants. Four typical materials, including two herbaceous plants (rice straw, corn straw) and two woody plants (camellia oleifera shells, garden waste), were used in the experiments under five operating temperatures (from 300 °C to 700 °C, with an interval of 100 °C). The results showed biochar derived from herbaceous plants had a significantly higher pH (from 7.68 to 11.29 for RS), electrical conductivity (EC, from 6.5 Ms cm-1 to 13.2 mS cm-1 for RS), cation exchange conductivity (CEC, from 27.81 cmol kg-1 to 21.69 cmol kg-1 for RS), and ash content (from 21.79% to 32.71% for RS) than the biochar from woody plants, but the volatile matter (VM, from 42.23% to 11.77% for OT) and specific surface area (BET, from 2.88 m2 g-1 to 301.67 m2 g-1 for OT) in the woody plant-derived biochar were higher. Except for CEC and VM, all the previously referred physicochemical characteristics in the as-prepared biochars increased with the increasing pyrolysis temperature, the H/C and O/C values of herbaceous and woody plant-derived biochar were lower than 0.9 and 0.3, respectively, confirming their potential as the material for carbon sequestration. The results revealed that biochar made from herbaceous plants was more suitable for acidic soil amendments. In contrast, woody plant-derived biochar were recommended to remove heavy metals in environmental remediation and water treatment.

Carbon dioxide reduction to multicarbon hydrocarbons and oxygenates on plant moss-derived, metal-free, in situ nitrogen-doped biochar.

Electrochemical reduction of carbon dioxide (CO2) is considered a promising renewable energy conversion technology, but it remains challenging to find active, stable, low-cost, and highly efficient electrocatalysts for the CO2 conversion. Here, we develop an in situ nitrogen-doped, metal-free, porous biochar from plant moss to catalyze the electrochemical reduction of CO2 into methane (CH4), methanol (CH3OH) and ethanol (C2H5OH) at high current densities and low overpotentials. Using this metal-free biochar electrocatalyst, production rates of approximately 36.1, 32.1, and 18.1 µg h-1 cm-2 towards CH4, C2H5OH, and CH3OH are obtained with Faradaic efficiencies of 56.0%, 26.0% and 10.5%, respectively. In addition, the total faradaic efficiency reaches 92.6% at -1.2 V (vs. Ag/AgCl) with good stability. A favorable pathway for the electrochemical reduction of CO2 over the metal-free biochar is also provided. This study presents a new approach to produce cost-effective, in situ nitrogen-doped porous biochars with excellent efficiency and durability for the electrochemical reduction of CO2.

Significant enhancement of electron transfer from Shewanella oneidensis using a porous N-doped carbon cloth in a bioelectrochemical system.

Modifying the surface of an anode can improve electron transfer, thus enhancing the performance of the associated bioelectrochemical system. In this study, a porous N-doped carbon cloth electrode was obtained via a simple thermal reduction and etching treatment, and then used as the anode in a bioelectrochemical system. The electrode has a high nitrogen-to­carbon (N/C) ratio (~3.9%) and a large electrochemically active surface area (145.4 cm2, about 4.4 times higher than that of the original carbon cloth), which increases the bacterial attachment and provides more active sites for extracellular electron transfer. Electrochemical characterization reveals that the peak anodic current (0.71 mA) of the porous N-doped carbon cloth electrode in riboflavin is 18 times higher than that of the original carbon cloth electrode (0.04 mA), confirming the presence of more electroactive sites for the redox reaction. We also obtained a maximum current density of 0.29 mA/cm2 during operation of a bioelectrochemical system featuring the porous N-doped carbon cloth electrode, which is 14.5 times higher than that of the original carbon cloth electrode. This result demonstrates that the adoption of our new electrode is a viable strategy for boosting the performance of bioelectrochemical systems.

Fit indices for mean structures with growth curve models.

Motivated by the need to effectively evaluate the quality of the mean structure in growth curve modeling (GCM), this article proposes to separately evaluate the goodness of fit of the mean structure from that of the covariance structure. Several fit indices are defined, and rationales are discussed. Particular considerations are given for polynomial and piecewise polynomial models because fit indices for them are valid regardless of the underlying population distribution of the data. Examples indicate that the newly defined fit indices remove the confounding issues with indices jointly evaluating mean and covariance structure models and provide much more reliable evaluation of the mean structure in GCM. Examples also show that pseudo R-squares and concordance correlations are unable to reflect the goodness of mean structures in GCM. Proper use of the fit indices for the purpose of model diagnostics is discussed. A window-based program, WebSEM, is also introduced for easily computing these fit indices by applied researchers. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Enhanced Rhodococcus pyridinivorans HR-1 anode performance by adding trehalose lipid in microbial fuel cell.

In this study, a trehalose lipid was added to a Rhodococcus pyridinivorans-inoculated MFC to improve the power output by enhancing electron transfer. Upon trehalose lipid additions of different concentrate from 0 to 20 mg/L, the maximum power density increased from 54.7 mW/m2 to 324.4 mW/m2 (5.93 times) while the corresponding current density was 3.66 times increased from 0.35 A/m2 to 1.28 A/m2. Cyclic voltammetry analysis revealed that the addition of trehalose lipid increased the electron transfer performance, while electrochemical impedance spectroscopy results proved a decrease in internal resistance. It was demonstrated that adding bio-surfactant in MFC was a novel way to enhance power output performance.

Steamed cake-derived 3D carbon foam with surface anchored carbon nanoparticles as freestanding anodes for high-performance microbial fuel cells.

Anode design is highly significant for microbial fuel cells, since it simultaneously serves as the scaffold for electroactive microorganisms and as a medium for electron migration. In this study, a stiff 3D carbon foam with surface anchored nitrogen-containing carbon nanoparticles was facilely constructed via in-situ polyaniline coating of carbonized steamed cake prior to the carbonization process. The resultant product was determined to be an excellent freestanding anode that enabled the microbial fuel cell to deliver a maximum power density of up to 1307 mW/m2, which significantly outperformed its non-coated counterpart, the widely used commercial carbon felt. Further investigations revealed that the overall performance enhancement was associated with the open porosity, enlarged electroactive surface, increased biocompatibility, and decreased electric resistance of the anode scaffold. This promising anode material would offer a green and economical option for fabricating high-performance microbial fuel cell-based devices towards various ends.

Structural Equation Modeling With Many Variables: A Systematic Review of Issues and Developments.

Survey data in social, behavioral, and health sciences often contain many variables (p). Structural equation modeling (SEM) is commonly used to analyze such data. With a sufficient number of participants (N), SEM enables researchers to easily set up and reliably test hypothetical relationships among theoretical constructs as well as those between the constructs and their observed indicators. However, SEM analyses with small N or large p have been shown to be problematic. This article reviews issues and solutions for SEM with small N, especially when p is large. The topics addressed include methods for parameter estimation, test statistics for overall model evaluation, and reliable standard errors for evaluating the significance of parameter estimates. Previous recommendations on required sample size N are also examined together with more recent developments. In particular, the requirement for N with conventional methods can be a lot more than expected, whereas new advances and developments can reduce the requirement for N substantially. The issues and developments for SEM with many variables described in this article not only let applied researchers be aware of the cutting edge methodology for SEM with big data as characterized by a large p but also highlight the challenges that methodologists need to face in further investigation.

Testing the Difference Between Reliability Coefficients Alpha and Omega.

Reliable measurements are key to social science research. Multiple measures of reliability of the total score have been developed, including coefficient alpha, coefficient omega, the greatest lower bound reliability, and others. Among these, the coefficient alpha has been most widely used, and it is reported in nearly every study involving the measure of a construct through multiple items in social and behavioral research. However, it is known that coefficient alpha underestimates the true reliability unless the items are tau-equivalent, and coefficient omega is deemed as a practical alternative to coefficient alpha in estimating measurement reliability of the total score. However, many researchers noticed that the difference between alpha and omega is minor in applications. Since the observed differences in alpha and omega can be due to sampling errors, the purpose of the present study, therefore, is to propose a method to evaluate the difference of coefficient alpha ([Formula: see text]) and omega ([Formula: see text]) statistically. In particular, the current article develops a procedure to estimate the SE of ([Formula: see text]) and consequently the confidence interval (CI) for ([Formula: see text]). This procedure allows us to test whether the observed difference ([Formula: see text]) is due to sample error or [Formula: see text] is significantly greater than [Formula: see text]. The developed procedure is then applied to multiple real data sets from well-known scales to empirically verify the values of ([Formula: see text]) in practice. Results showed that in most of the comparisons the differences are significantly above zero but cases also exist where the CIs contain zero. An R program for calculating [Formula: see text], [Formula: see text], and the SE of ([Formula: see text]) is also included in the present study so that the developed procedure is easily accessible to applied researchers.

Comparing Latent Means Without Mean Structure Models: A Projection-Based Approach.

The conventional setup for multi-group structural equation modeling requires a stringent condition of cross-group equality of intercepts before mean comparison with latent variables can be conducted. This article proposes a new setup that allows mean comparison without the need to estimate any mean structural model. By projecting the observed sample means onto the space of the common scores and the space orthogonal to that of the common scores, the new setup allows identifying and estimating the means of the common and specific factors, although, without replicate measures, variances of specific factors cannot be distinguished from those of measurement errors. Under the new setup, testing cross-group mean differences of the common scores is done independently from that of the specific factors. Such independent testing eliminates the requirement for cross-group equality of intercepts by the conventional setup in order to test cross-group equality of means of latent variables using chi-square-difference statistics. The most appealing piece of the new setup is a validity index for mean differences, defined as the percentage of the sum of the squared observed mean differences that is due to that of the mean differences of the common scores. By analyzing real data with two groups, the new setup is shown to offer more information than what is obtained under the conventional setup.