Major depressive disorder (MDD) is a mixed disorder with the highly irregular course, inconsistent response to treatment and has no well-known mechanism for the pathophysiology. Major causes of depression are genetic, neurobiological, and environmental. However, over the past few years, altered serum levels of macro-minerals (MM) and trace elements (TE) have been recognized as major causative factors to the pathogenesis of many mental disorders. The purpose of this study was to determine the serum levels of MM (calcium and magnesium) and TE (copper, iron, manganese, selenium, and zinc) in MDD patients and find out their associations with depression risk. This prospective case-control study recruited 247 patients and 248 healthy volunteers matched by age and sex. The serum levels of MM and TE were analyzed by atomic absorption spectroscopy (AAS). Statistical analysis was performed with independent sample t-tests and Pearson’s correlation test. We found significantly decreased concentrations of calcium and magnesium, iron, manganese, selenium, and zinc in MDD patients compared with control subjects (p < 0.05). But the concentration of copper was significantly increased in the patients than control subjects (p < 0.05). Data obtained from different inter-element relations in MDD patients and control subjects strongly suggest that there is a disturbance in the element homeostasis. Our study suggests that altered serum concentrations of MM and TE are major contributing factors for the pathogenesis of MDD. Alterations of these elements in serum levels of MDD patients arise independently and they may provide a prognostic tool for the assessment of depression risk.

In this study, four textural classes of soil (Clay, Clay Loam, Loam, and Loamy Sand) were used to investigate the dielectric properties of soils, using a vector network analyser with an open-ended coaxial probe kit at room temperature (25 ± 2°C) in the 700–7000 MHz microwave frequency range. Four levels of soil moisture content (oven dry, 33% field capacity, 66% field capacity and 100% field capacity) were maintained to perform the experiment with three replication and three observation each. The results showed that, with increasing soil moisture, from oven dry conditions to 100% field capacity, both the real (Dielectric Constant) and imaginary (Loss Factor) components of the dielectric properties increased; however, the responses were not linear. The dielectric properties of oven dry soils were very low compared with the soils with higher moisture content. Therefore, soil moisture was the major contributor to the dielectric behaviour of soil. The dielectric properties of sandy soil were much lower than the other soils; however, the dielectric loss factor of the Dookie clay soil was higher compare with the other soils. Models were developed to explain the dielectric properties of soils as a function of frequency and moisture content. The goodness of fit (r²) for these models varies between 0.952 for the Dookie Sandy Soil to 0.997 for the Dookie Loam Soil, suggesting that these models were adequate to describe the dielectric properties of these soils over the range of frequencies and moisture contents assessed in this study. Another model was developed to estimate the expected penetration depth of electromagnetic waves in these soils, based on the model of the dielectric properties. It was clear that penetration decreases with both frequency and moisture content. Low frequencies penetrate further into the soils than higher frequencies. Similarly, dry soils allow further penetration than moist soils.

Soil carbon (C) mineralization was studied in an incubation experiment comprised of two factors having six organic materials and three nitrogen (N) rates. Cow dung (CD), rice straw (RS), wood ash (WA), cow dung biochar (CB), rice straw biochar (RB) and wood biochar (WB) considering 2.5 g C kg⁻¹ soil along with three levels of N, i.e., 0, 0.05 and 0.10 g N kg⁻¹ soil were mixed with 400 g of soil used in each pot. The pots were placed for 0, 30, 60, 90, 120, 150 and 180 days of incubation, and soils were collected after each incubation and analyzed for C and N. Irrespective of treatment factors, C decreased in an irregular fashion until 180 days of incubation. From the initial level of 1.91%, C contents decreased to 1.08, 1.10, 1.06, 1.23, 1.17 and 1.12% in soil mixed with CD, RS, WA, CB, RB and WB, respectively, and to 1.28, 1.11 and 0.99% in 0, 0.05 and 0.10 g N kg⁻¹ soil, respectively, at 180 days of incubation. The mineralization followed the order of WA > CD > RS > WB > RB > CB. Biochars could supply stable C in soil, while N enhances mineralization; optimization of N is therefore essential to ensure soil C accretion.

This study aimed to evaluate the differences between the growth patterns of large- and normal-sized Japanese quail strains and their F1 progeny, by fitting their growth parameter values to five nonlinear regression growth models (Weibull, Logistic, Gompertz, Richards, and Brody). The Richards model presented the best fit for both sexes of the large-sized quail strain, whereas the Gompertz model presented the best fit for both sexes of the normal-sized quail strain, based on goodness-of-fit criteria (higher adjusted R2 and lower Akaike and Bayesian information criteria). Both sexes of F1 birds derived from the cross between normal-sized females and large-sized males were best fitted by the Richards model. In contrast, growth parameters of the F1 birds derived from the cross between large-sized females and normal-sized males were best fitted to the Gompertz model. The data could be fitted nearly as well to the Weibull and Logistic models as to the Richards and Gompertz models. The Brody model presented the poorest fit for the growth parameter values. The results indicated that the Richards and Gompertz models could best describe the growth characteristics of both large- and normal-sized quails. Moreover, the observed growth pattern of the F1 birds was likely inherited from the male parental strain. To the best of our knowledge, this is the first study comparing the growth curves of the reciprocal F1 generations with their parental strains in quails.