Predict the prevalence and incidence of Parkinson's disease using fractal interpolation-LSTM model.

The investigation of the prediction of disease population is a noticeable exploration topic in the field of sciences. As a type of neurological disease, the incidence and prevalence of Parkinson's disease are still difficult to accurately study. In this paper, a method is proposed to forecast the number of incident cases (NumIn), incidence rate (InRa), the number of prevalent cases (NumPr), and prevalence rate (PrRa) of Parkinson's disease in ten countries selected. Using past data on the incidence rate, the number of prevalent cases, and the prevalence rate from 1990 to 2019, three types of fractal interpolations with different fractal dimensions are constructed for reconstructing the past data, where the vertical scaling factors are determined by the method proposed in this article. Then, the Long Short-Term Memory (LSTM) model is employed to forecast the values of NumIn, InRa, NumPr, and PrRa with Parkinson's disease in 2020. Meanwhile, the autoregressive integrated moving average model is used to predict the values compared with the LSTM model. The evaluation metrics employed for error calculation include the root mean square error and the coefficient of determination (R2). According to the proposed optimal criteria, the best predicted results are the average of three types of prediction values based on the LSTM model by analyzing and comparing eight predicted results.

Transcriptome Analysis of Maize Ear Leaves Treated with Long-Term Straw Return plus Nitrogen Fertilizer under the Wheat-Maize Rotation System.

Straw return (SR) plus nitrogen (N) fertilizer has become a practical field management mode to improve soil fertility and crop yield in North China. This study aims to explore the relationship among organic waste, mineral nutrient utilization, and crop yield under SRN mode. The fertilizer treatments included unfertilized (CK), SR (straws from wheat and corn), N fertilizer (N), and SR plus N fertilizer (SRN). SRN treatment not only significantly increased the grain yield, net photosynthetic rate, and transpiration rate but also enhanced the contents of chlorophyll, soluble sugar, and soluble protein and increased the activities of antioxidant enzymes but reduced intercellular CO2 concentration and malondialdehyde (MDA) content when compared to other treatments. There were 2572, 1258, and 3395 differentially expressed genes (DEGs) identified from the paired comparisons of SRvsCK, NvsCK, and SRNvsCK, respectively. The transcript levels of many promising genes involved in the transport and assimilation of potassium, phosphate, and nitrogen, as well as the metabolisms of sugar, lipid, and protein, were down-regulated by straw returning under N treatment. SRN treatment maintained the maximum maize grain yield by regulating a series of genes' expressions to reduce nutrient shortage stress and to enhance the photosynthesis of ear leaves at the maize grain filling stage. This study would deepen the understanding of complex molecular mechanisms among organic waste, mineral nutrient utilization, crop yield, and quality.

Paclitaxel combined with platinum (PTX) versus fluorouracil combined with cisplatin (PF) in the treatment of unresectable esophageal cancer: a systematic review and meta-analysis of the efficacy and toxicity of two different regimens.

Background: Chemotherapy plays an important role in definitive chemoradiotherapy strategies. However, the most optimal concurrent chemotherapy scheme is still controversial. This study aimed to systematically evaluate the efficacy and toxicity of paclitaxel/docetaxel combined with platinum (PTX) and fluorouracil combined with cisplatin (PF) in the concurrent chemoradiotherapy (CCRT) of unresectable esophageal cancer. Methods: The PubMed, China National Knowledge Infrastructure (CNKI), Google Scholar and Embase databases were searched by combining subject words and free words through December 31, 2021. The inclusion criteria were pathologically confirmed esophageal cancer studies using CCRT, where the chemotherapy regimen only compared PTX and PF. Quality evaluation and data extraction of studies that met the inclusion criteria were carried out independently. Stata 11.1 software was used to perform the meta-analysis. The begger analysis and egger analysis were used to assess publication bias, and the robustness of the pooled results further assessed by the Trim and Fill analysis. Results: After screening, 13 randomized controlled trials (RCTs) were included. A total of 962 cases were enrolled, including 480 (49.9%) in the PTX group and 482 (50.1%) in the PF group. The gastrointestinal reaction to the PF regimen was the most serious [relative risk (RR) =0.54, 95% confidence interval (CI): 0.36-0.80, P=0.003]. The complete remission (CR) rate, objective response rate (ORR), and disease control rate (DCR) of the PTX group were higher than those of the PF group (RR =1.35, 95% CI: 1.03-1.76, P=0.030; RR =1.12, 95% CI: 1.03-1.22, P=0.006; RR =1.05, 95% CI: 1.01-1.09, P=0.022). In terms of the overall survival (OS) rate, the 2-year survival rates of the PTX group were higher than those of the PF group (P=0.005). There was no significant difference in the 1-, 3-, and 5-year survival rates between the two regimens (P=0.064, 0.144, and 0.341, respectively). There may be publication bias for ORR and DCR, and the results are reversed after applying the Trim and Fill method, so the combined results are not robust. Conclusions: PTX may be the preferred regimen for CCRT of esophageal squamous cell carcinoma, with better short-term therapeutic effect and 2-year OS rate and lower gastrointestinal toxicity.

Within-leaf chloroplasts and nitrogen allocation to thylakoids in relation to photosynthesis during grain filling in maize.

Nitrogen (N) is an important contributor to photosynthetic rate (Pn). However, during grain-filling stage in maize, some leaf N is remobilized to meet demands for grain protein accumulation rather than photosynthetic demands. Therefore, plants that can maintain a relatively high Pn during the N remobilization process would have the key to achieving both high grain yields (HGY) and high grain protein concentrations (HGPC). In this study, we investigated two high-yielding maize hybrids in photosynthetic apparatus and N allocation in a two-year field experiment. During grain filling, XY335 had a higher Pn and photosynthetic N-use efficiency than ZD958 had in the upper leaf, but not in the middle or lower leaves. In the upper leaf, the diameter and area of the bundle sheath (BS) were larger and the distance between bundle sheaths was greater in XY335 than in ZD958. XY335 had more bundle sheath cells (BSCs) and a larger BSC area, as well as a larger chloroplast area in the BSC, resulting in a higher total number and total area of chloroplasts in the BS. XY335 also had higher stomatal conductance (gs), intercellular CO2 concentration, and N allocation to the thylakoids. No genotypic differences were found in mesophyll cell ultrastructure, N content and starch content in the three types of leaves. Therefore, a trifecta of higher gs, greater N allocation to thylakoids for photo-phosphorylation and electron transport, and more and larger chloroplasts promoting CO2 assimilation in the BS confers a high Pn to simultaneously achieve HGY and high HGPC in maize.

Pinning synchronization of stochastic neutral memristive neural networks with reaction-diffusion terms.

This paper investigates the pinning synchronization of stochastic neutral memristive neural networks with reaction-diffusion terms. Firstly, two novel pinning controllers, which contain both current state and past state, are designed. Subsequently, in terms of Green's theorem, inequality technology, stochastic analysis theory and pinning control technology, two easy-to-test sufficient conditions based on algebraic inequalities are obtained to ensure the mean-square asymptotic synchronization of stochastic memristive neural networks with neutral delays and reaction-diffusion terms by providing a new Lyapunov-Krasovskii functional. In addition, some existing results can be regarded as special cases of our work. Finally, illustrative examples further verify the correctness and validity of the derived results.

Stability and pinning synchronization of delayed memristive neural networks with fractional-order and reaction-diffusion terms.

Global asymptotic stability and synchronization are explored in this paper for fractional delayed memristive neural networks with reaction-diffusion terms (FDRDMNNs) in sense of Riemann-Liouville. First, we introduce diffusion into the existing model of fractional delayed memristive neural networks. Next, in terms of Green's theorem and inequality technique, a less conservative criterion for the asymptotic stability of FDRDMNNs is given by endowing Lyapunov direct method. Then, the appropriate pinning feedback controllers and adaptive controllers are designed to achieve the synchronization of the FDRDMNNs, and two sufficient conditions for global asymptotic synchronization are acquired. In addition, the results based on algebraic inequalities enhance some existing ones. The numerical simulations finally verify the validity of the derived results.

Prediction Model of VCA Formed by the Packing of Hybrid Lithological Coarse Aggregates Used in SMA.

The voids in coarse aggregate (VCA) is an important volumetric index in the mineral aggregate gradation design of stone matrix asphalt (SMA) mixtures. To explore the law of variation for VCA formed by the packing of basalt and lime coarse aggregates, a uniform design method and vibrating compaction tests were used to establish the prediction model. Based on the test results and stepwise regression analysis, a reliable prediction model of VCA was obtained. There is a multiple nonlinear relationship between the VCA and the proportion of each coarse aggregate in the mixture. Regardless of the type of coarse aggregates used, the rule of VCA with different forms of aggregate gradation curves has universal significance. This conclusion can help to determine the aggregate gradation in the design of SMA mixtures.

Impacts of Aggregate Gradation on the Volumetric Parameters and Rutting Performance of Asphalt Concrete Mixtures.

The main objective of this study was to determine the effect of aggregate gradation (AG) on the volumetric parameters (VPs) and rutting performance (RP) of asphalt concrete (AC) mixtures. The boundary sieve (BS) between fine and coarse aggregates was 2.36 mm size, and 15 gradation curves of three nominal maximum aggregate sizes (13.2, 19.0, and 26.5 mm) were designed based on the percentage passing of the BS. A vibrating compaction test of coarse aggregates, Marshall compaction and wheel-tracking tests of AC mixtures with various gradations were conducted. It was found that AG had crucial effects on the VPs and RP of AC mixtures. The AC mixture can be designed as a skeletal dense structure provided that the percentage passing of the BS is appropriate. More notably, AC mixtures with a skeletal dense structure showed the best rutting resistance performance. Therefore, it is important to optimize AG for enhancing the high-temperature RP of AC mixtures.

Interaction Effects of Nitrogen Rates and Forms Combined With and Without Zinc Supply on Plant Growth and Nutrient Uptake in Maize Seedlings.

Previous studies have shown that zinc (Zn) accumulation in shoot and grain increased as applied nitrogen (N) rate increased only when Zn supply was not limiting, suggesting a synergistic effect of N on plant Zn accumulation. However, little information is available about the effects of different mineral N sources combined with the presence or absence of Zn on the growth of both shoot and root and nutrient uptake. Maize plants were grown under sand-cultured conditions at three N forms as follows: NO3 - nutrition alone, mixture of NO3 -/NH4 + with molar ratio of 1:1 (recorded as mixed-N), and NH4 + nutrition alone including zero N supply as the control. These treatments were applied together without or with Zn supply. Results showed that N forms, Zn supply, and their interactions exerted a significant effect on the growth of maize seedlings. Under Zn-sufficient conditions, the dry weight (DW) of shoot, root, and whole plant tended to increase in the order of NH4 + < NO3 - < mixed-N nutrition. Compared with NH4 + nutrition alone, mixed-N supply resulted in a 27.4 and 28.1% increase in leaf photosynthetic rate and stomatal conductance, which further resulted in 35.7 and 33.5% of increase in shoot carbon (C) accumulation and shoot DW, respectively. Furthermore, mixed-N supply resulted in a 19.7% of higher shoot C/N ratio vs. NH4 + nutrition alone, which means a higher shoot biomass accumulation, because of a significant positive correlation between shoot C/N ratio and shoot DW (R 2 = 0.682***). Additionally, mixed-N supply promoted the greatest root DW, total root length, and total root surface area and synchronously improved the root absorption capacity of N, iron, copper, manganese, magnesium, and calcium. However, the above nutrient uptake and the growth of maize seedlings supplied with NH4 + were superior to either NO3 - or mixed-N nutrition under Zn-deficient conditions. These results suggested that combined applications of mixed-N nutrition and Zn fertilizer can maximize plant growth. This information may be useful for enabling integrated N management of Zn-deficient and Zn-sufficient soils and increasing plant and grain production in the future.

Constitutive expression of aldose reductase 1 from Zea mays exacerbates salt and drought sensitivity of transgenic Escherichia coli and Arabidopsis.

Aldose reductases (ARs) have been considered to play important roles in sorbitol biosynthesis, cellular detoxification and stress response in some plants. ARs from maize are capable of catalyzing the oxidation of sorbitol to glucose. However, little is known how maize ARs response to abiotic stresses. In this work, we cloned one isoform of maize ARs (ZmAR1), and furthermore we analyzed the roles of ZmAR1 in response to salt and drought stresses at both prokaryotic and eukaryotic levels. ZmAR1 encodes a putative 35 kDa protein that contains 310 amino acids. Under normal growth conditions, ZmAR1 was expressed in maize seedlings, and the highest expression level was found in leaves. But when seedlings were subjected to drought or salt treatment, the expression levels of ZmAR1 were significantly reduced. The constitutive expression of ZmAR1 increased the sensitivity of recombinant E. coli cells to drought and salt stresses compared with the control. Under salt and drought stresses, transgenic Arabidopsis lines displayed lower seed germination rate, shorter seedling root length, lower chlorophyll content, lower survival rate and lower antioxidant enzyme activity than wild type (WT) plants, but transgenic Arabidopsis had higher relative conductivity, higher water loss rate, and more MDA content than WT. Meanwhile, the introduction of ZmAR1 into Arabidopsis changed the expression levels of some stress-related genes. Taken together, our results suggested that ZmAR1 might act as a negative regulator in response to salt and drought stresses in Arabidopsis by reducing the sorbitol content and modulating the expression levels of some stress-related genes.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces.

BACKGROUND: Many critical biological processes are strongly related to protein-RNA interactions. Revealing the protein structure motifs for RNA-binding will provide valuable information for deciphering protein-RNA recognition mechanisms and benefit complementary structural design in bioengineering. RNA-binding events often take place at pockets on protein surfaces. The structural classification of local binding pockets determines the major patterns of RNA recognition. RESULTS: In this work, we provide a novel framework for systematically identifying the structure motifs of protein-RNA binding sites in the form of pockets on regional protein surfaces via a structure alignment-based method. We first construct a similarity network of RNA-binding pockets based on a non-sequential-order structure alignment method for local structure alignment. By using network community decomposition, the RNA-binding pockets on protein surfaces are clustered into groups with structural similarity. With a multiple structure alignment strategy, the consensus RNA-binding pockets in each group are identified. The crucial recognition patterns, as well as the protein-RNA binding motifs, are then identified and analyzed. CONCLUSIONS: Large-scale RNA-binding pockets on protein surfaces are grouped by measuring their structural similarities. This similarity network-based framework provides a convenient method for modeling the structural relationships of functional pockets. The local structural patterns identified serve as structure motifs for the recognition with RNA on protein surfaces.

The diffusion-weighted magnetic resonance imaging (DWI) predicts the early response of esophageal squamous cell carcinoma to concurrent chemoradiotherapy.

PURPOSE: To investigate the predictive value of serial diffusion-weighted MRI (DWI) on tumor response of the concurrent chemoradiotherapy (CCRT) for esophageal squamous cell carcinoma (ESCC) and to determine the optimal time point of DWI measurements. METHODS AND MATERIALS: From June 2010 to October 2011, 38 ESCC patients were consecutively enrolled into this prospective cohort study. During their treatment, the longitudinal DWIs were acquired at beginning and every week during the course of CCRT. ADC maps were generated from there DWIs. The tumor responses were evaluated according to the RECIST. RESULTS: (1) At completion of CCRT, 20 (52.6%) and 18 (47.4%) patients were evaluated as CR and PR, respectively. Over the time points of measures, the series of ADC values (10-3mm2/s) in whole GTV were consistently characterized with higher (all p<0.05) for these CR patients as their means (std) were 2.24 (0.49), 2.23 (0.51), 2.44 (0.57), 2.54 (0.52), 2.70 (0.46), 2.80 (0.55), 2.92 (0.62), compared with these PR patients as 1.83 (0.31), 1.79 (0.21), 1.87 (0.30), 1.97 (0.37), 2.15 (0.44), 2.26 (0.46), 2.32 (0.51), respectively. However, the ADC change rates (ΔADC) of two groups were found to be similar. These results were also supported by the multivariate ANOVA analyses. The same analysis results of DWI based GTV volumes were also found. (2) The comparisons of logistic regression analysis indicated that only the ADC values at Week 3 (15 fractions) were an independent prognostic factor of tumor response (OR=0.303, p=0.003). ROC curve analysis showed that Area Under Curve for ADC values of the end of 2nd and 3rd weeks were biggest (0.822) and the prediction efficacy was comparatively optimized. The corresponding cut-off values were 2.11 and 2.14 (10-3mm2/s), respectively. (3) Additional analyses on those eight patients with tumor local recurrence within 1year demonstrated the level-off after the continuously increased ADC values till Week 4. CONCLUSIONS: DWI can be used as a biomarker to predict TE of esophageal cancers in early time during CCRT. The treatment-induced change in ADC of whole GTV during the first 2-3weeks can be highly predictive to TE. The unchanged ADC value in late period may indicate the high tendency of tumor recurrence after 1year.

Analysis of heart rate variability using fuzzy measure entropy.

This paper proposed a new entropy measure, Fuzzy Measure Entropy (FuzzyMEn), for the analysis of heart rate variability (HRV) signals. FuzzyMEn was calculated based on the fuzzy set theory and improved the poor statistical stability in the approximate entropy (ApEn) and sample entropy (SampEn). The simulation results also demonstrated that the FuzzyMEn had better algorithm discrimination ability when compared with the recently published fuzzy entropy (FuzzyEn), The validity of FuzzyMEn was tested for clinical HRV analysis on 120 subjects (60 heart failure and 60 healthy control subjects). It is concluded that FuzzyMEn could be considered as a valid and reliable method for a clinical HRV application.