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.

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.

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.

Psychometric Properties of Measures of Team Diversity With Likert Data.

Certain diversity among team members is beneficial to the growth of an organization. Multiple measures have been proposed to quantify diversity, although little is known about their psychometric properties. This article proposes several methods to evaluate the unidimensionality and reliability of three measures of diversity. To approximate the interval scale required by the measures of diversity, a transformation on the Likert-item scores is proposed. Ridge maximum likelihood is used to deal with the issue of small sample size, and methods for evaluating the significance of the difference of two reliability estimates with correlated samples are also developed. Results with a real data set on entrepreneurial teams indicate that different measures of diversity may correspond to significantly different estimates of reliability. Results also indicate that diversity measures obtained with the transformed data tend to be more unidimensional than their counterparts obtained from Likert data. However, diversity measures obtained from Likert data tend to yield greater reliability estimates. Among the three examined measures of diversity, the standard deviation is found to yield greater and more efficient reliability estimates than the others and is thus recommended.

Nonactivated and activated biochar derived from bananas as alternative cathode catalyst in microbial fuel cells.

Nonactivated and activated biochars have been successfully prepared by bananas at different thermotreatment temperatures. The activated biochar generated at 900°C (Biochar-act900) exhibited improved oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) performances in alkaline media, in terms of the onset potential and generated current density. Rotating disk electron result shows that the average of 2.65 electrons per oxygen molecule was transferred during ORR of Biochar-act900. The highest power density of 528.2 mW/m(2) and the maximum stable voltage of 0.47 V were obtained by employing Biochar-act900 as cathode catalyst, which is comparable to the Pt/C cathode. Owning to these advantages, it is expected that the banana-derived biochar cathode can find application in microbial fuel cell systems.

[Sustainable electricity generation in microbial fuel cells using Fe(III)-EDTA as cathodic electron shuttle].

The rate of oxygen reduction reaction (ORR) at the cathode is a major factor affecting the performance of the microbial fuel cells (MFC). Results showed that when using Fe(III)-EDTA solution as catholyte, the ORR rate was significantly increased and the internal resistance was reduced, consequently leading to an increase in power output. With a concentration of Fe(III )-EDTA at 20.0 mmol/L in the catholyte, the MFC produced the voltage and power density at approximate 200.1 mV and 16.0 mW/m2, respectively, which was increased by 73.2% and 70.1% contrary to the MFC without the presence of Fe(III)-EDTA. The further experiment suggested that Fe(III)-EDTA functioned as electron shuttle to accelerate electron transfer. Fe(III)-EDTA received electron and got reduced to Fe(III)-EDTA, which further provided electrons to oxygen and got reoxidized at the same time. Therefore Fe(III)-EDTA can act as recyclable electron shuttles between cathode electrode and oxygen. The optimum condition in the case of using Fe(III)-EDTA as cathode electron shuttles was tested to be Fe(III)-EDTA concentration at 20.0 mmol/L and pH at 5.0, which allowed MFC produced the maximum power density of 100.9 mW/m2.

[Mechanisms of bioelectricity generation in Enterobacter aerogenes-based microbial fuel cells].

Microbial fuel cells (MFCs) using hydrogen-producing bacteria (HPB) could utilize a large number of substrates to generate power. However, the coulombic efficiency is limited by the fact that only suspended cells are used as biocatalyst in anodic medium. MFCs using Fe (III)-reducing bacteria have high energy recovery efficiency, but can only utilize some simple organic matters. In this study, Enterobacter aerogenes XM02, a hydrogen-producing strain with Fe(III)-reducing activity, was selected as biocatalyst for MFCs, which could produce electricity by digesting lots of carbohydrates even starch. Graphite felt, a material with high specific surface area and hydrogen catalysis, instead of carbon paper supported platinum, was used as anode material. The coulombic efficiency had been substantially improved from 1.68% to 42.49%, higher than other HPB-based MFCs previously reported. The SEM image proved the ability of XM02 strain to colonize on the anode surface. Power generation of MFCs could restore quickly when anodic medium was completely replaced with non-growth medium containing glucose. This suggested that the attached cells contributed to electricity production because planktonic cells had been removed during the medium replacement. This study proposed the mechanism of power generated from in situ oxidation of hydrogen produced by the XM02 strain biofilm.