MicroRNAs (miRNAs) have been involved in regulation of diverse spectrum of plant development processes in many species. In cotton, few miRNAs have been well characterised in floral organ development. Floral organ, which should be finely tuned, is a crucial factor affecting the yield of cotton. Therefore, it is well worth revealing the function of miRNAs in regulation of floral organ development. Here, we report the role of miRNA156/157 in regulation of floral organ size in cotton. Over-expression of the GhmiRNA157 precursor in cotton (Gossypium hirsutum) resulted in smaller floral organs, fewer ovules and decreased seed production due to suppression of cell proliferation and cell elongation. Five SQUAMOSA promoter-binding protein-like (SPL) genes were identified as targets of GhmiRNA157 using a RNA ligase-mediated rapid amplification of cDNA end approach, and the expression level of miR157-targeted GhSPLs decreased in the miR157 over-expression lines, indicating the presence of the miR157/SPL axis in cotton. Two MADS-box genes, orthologs of AtAGL6 and SITDR8, which are associated with floral organ development and reproductive production, were repressed in the miR157 over-expression lines. In addition, auxin-inducible genes were also down-regulated, and auxin signal visualized by a DR5::GUS reporter was attenuated in the miR157 over-expression lines. Our results indicate that the miR157/SPL axis controls floral organ growth and ovule production by regulating MADS-box genes and auxin signal transduction. The work further elucidates the mechanism of floral organ development and provides helpful molecular basis for improvement of cotton yield.

Over the last three decades, accurate modeling and forecasting of electricity prices has become a key issue in competitive electricity markets. As electricity price series usually exhibit several complex features, such as high volatility, seasonality, calendar effect, non-stationarity, non-linearity and mean reversion, price forecasting is not a trivial task. However, participants of electricity market need price forecast to make decisions in their daily activity in the market, such as trading, risk management or future planning. In this study we consider linear and nonlinear models for one-day-ahead forecast of electricity prices using components estimation techniques. This approach requires to filter out the structural, deterministic components from the original time series and to model the residual component by means of some stochastic process. The final forecast is obtained by combining the predictions of both these components. In this work, linear and non-linear models are applied to both, deterministic and stochastic, components. In the case of stochastic component, AutoRegressive, Nonparametric AutoRegressive, Functional AutoRegressive, and Nonparametric Functional AutoRegressive have been considered. Furthermore, two naïve benchmarks are applied directly to the price time series and their results are compared with our proposed models. An application of the proposed methodology is presented for the Italian electricity market (IPEX). Our analysis suggests that, in terms of Mean Absolute Error, Mean Absolute Percentage Error, and Pearson correlation coefficient, best results are obtained when deterministic component is estimated by using parametric approach. Further, Functional AutoRegressive model performs relatively better than the rest while Nonparametric AutoRegressive is highly competitive.

Abiotic stress is an important factor affecting the normal growth and development of plants and crop yield. To reduce the impact of abiotic adversity on cotton growth and development, the material basis of cotton resistance and its physiological functions are analyzed at the molecular level. At the same time, the use of genetic engineering methods to recombine resistance genes has become a hot spot in cotton resistance research. This paper provides an overviews of the resistance mechanism of cotton against the threat of non-biological adversity, as well as the research progress of osmoregulation-related genes, protein-acting genes, and transcription regulatory factor genes in recent years, and outlines the explored gene resources in cotton resistance genetic engineering, with the aim to provide ideas and reference bases for future research on cotton resistance.

Cotton is considered as the main crop in the agricultural sector of Pakistan. Water deficiency in this region in recent years has reduced the chances of high yields of cotton. Selection and creation of high-yielding varieties of cotton, even in water deficit conditions, is one of urgent tasks of today. For this purpose, 40 diverse genotypes of upland cotton were screened in normal and water deficit conditions in triplicate arrangement under split plot in a randomized complete block design. All the genotypes showed significant difference under both water regimes. Ten upland cotton accessions were screened out as water deficit tolerant (VH-144, IUB-212, MNH-886, VH-295, IR-3701, AA-802, NIAB-111, NS-121, FH-113, and FH-142) and five as water deficit sensitive (IR-3, CIM-443, FH-1000, MNH-147, and S-12) based on seed cotton yield and stress susceptibility index. These tolerant and sensitive genotypes were crossed in line × tester mating design. For further evaluation of genetic material, the seed of 50 F₁ crosses and their 15 parents were field planted under normal and water deficit conditions during next cotton growing season. Traits related to yield under the study showed significant variations among the accessions and their half sibs. The results of the principal component analysis (PCA) exhibited that total variation exhibited by factors 1 and factor 2 were 55.55 and 41.95%, respectively. PCA transformed the variables into three factors, and only two factors (F1 and F2) had eigenvalue > 1. The degree of dominance revealed that all parameters were highly influenced by non-additive gene action under both water regimes. Furthermore, the line VH-295 and tester CIM-443 had better yield performance under water deficit stress. The cross-combinations, viz., VH-144 × S-12, NIAB-111 × IR-3, and VH-295 × MNH-147, were the best for yield contributing traits. These combinations may be helpful for germplasm enhancement on large scale under water scarcity. All the studied traits have non-additive types of gene action suggesting the usage of these genotypes in cotton hybrid development program against water deficit tolerance.

Introduction: Currently, there is still clinical overlap between dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) patients, which may affect the accuracy of the early diagnosis of DLB. For better diagnosis and prognosis, further exploration of local cortical atrophy patterns and white matter lesions is needed.Methods: We reviewed the outpatient medical records of 97 DLB patients and 173 AD patients from January 2018 to September 2020 along with 30 matched outpatient clinic normal elderly people. MRI visual rating scales, including medial temporal lobe atrophy (MTA), global cortical atrophy-frontal subscale (GCA-F), posterior atrophy (PA), Fazekas scale, Evans Index and cerebral microbleeds were evaluated and analyzed in DLB and AD patients with different severities and normal controls.Results: Overall, patients with DLB had higher scores on all visual rating scales than the normal controls. Meanwhile, compared with AD, DLB had lower MTA scores in the mild to moderate groups (both p ≤ 0.001), but the GCA-F and PA scores were similar (all p > 0.05). The Fazekas scores in the moderate to severe DLB group were lower than those in the AD group (p = 0.024 and p = 0.027, respectively). In addition, the diagnostic performance and sensitivity of multiple imaging indicators for DLB were better than that of MTA alone (the combination of MTA, GCA-F, PA, Fazekas visual rating scales, AUC = 0.756, 95%CI: 0.700–0.813, sensitivity = 0.647, specificity = 0.804 and MTA visual rating scale, AUC = 0.726, 95%CI: 0.667–0.785, sensitivity = 0.497, specificity = 0.876, respectively).Conclusion: The medial temporal lobe of DLB patients was relatively preserved, the frontal and parietal lobes were similarly atrophied to AD patients, and the white matter hyperintensity was lighter than that in AD patients. Combined multiple visual rating scales may provide a novel idea for the diagnosis of early DLB.

Intercropping has been widely adopted by farmers because it often enhances crop productivity and economic returns. However, to increase the comprehensive production benefits of agricultural cultivation and increase the economic benefits of cotton in Northwest Shandong Province, a set of green, ecological, and efficient intercropping mode suitable for Northwest Shandong Province was preliminarily formed. A 2-year intercropping experiment was conducted in Xiajin and Dongping counties in Shandong Province, with six alternative intercropping patterns proposed. After analyzing the experimental data, it was determined that the traditional cotton–peanut intercropping method is not mechanized and that a new intercropping mode has been proposed: four rows of cotton and six rows of peanut. We selected the appropriate intercropping mode for Xiajin and Dongping counties. The production efficiency of 4:4 cotton intercropping in Peanut Ridge was the best in Dongping and Xiajin counties, which was 28–123% higher than that of monoculture. This planting pattern is suitable for demonstration and promotion in the two counties, as well as in the traditional cotton area of the old Yellow River in Northwest Shandong.