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Influences of photosynthesis of leaf and silique on seeds yield and quality of oilseed rape (Brassica napus L.) were explored in this study. A field comparing experiment with several rapeseed varieties was conducted and the results showed, that the leaf area index (LAI), silique surface area index (SAI), siliques number per plant, and biological yield were statistically classified as the first principal factors which greatly influenced seeds yield, the leaf net photosynthetic rate (Pn) and silique Pn were the second principal factors; the stomatal conductance (Gs) and chlorophyll a (Chl a) content were the first principal factors which influenced leaf Pn and silique Pn. A shading experiment was conducted and the results showed that, under treatments of the ZH1, ZH2, and ZH3 (shading rapeseed plants during flowering stage, during time from initial flowering until seeds ripening, and during time from flowering ending until seeds ripening, respectively), respectively the seeds yield per plant was reduced by 34.6%, 84.3%, and 86.1%, the seed protein content was significantly increased. The treatment ZH1 Not, but the ZH2 and ZH3 caused significant decrease in both seed oil content and oleic acid (C18:1) content in seed oil, and the contents of linoleic acid (C18:2), linolenic acid (C18:3) in oil were significantly increased, gene expression of the ACCase (Acetyl-CoA carboxylase), FAD2 (fatty acid desaturase), and FAD3 (ω-3 fatty acid dehydrogenase) in green seeds was restrained/changed. Thus the LAI, SAI, siliques number per plant, biological yield per plant, leaf Pn, silique Pn, and the Gs, Chl a content of leaf and silique formed an indexes system to be used in screening rapeseed variety with higher light efficiency and seeds yield; the silique photosynthesis inhibition and the photosynthates deficiency in rapeseed plant after flowering stage predominately influenced seeds yield and quality.

Background and objective Sudden cardiac death (SCD) is one of the leading causes of death in cardiovascular diseases. Monitoring the state of the heart in real time and giving early warning of possible dangers by using ambulate electrocardiogram signals are the keys to prevent cardiovascular death. However, due to the diversity inducing factors of SCD and great individual differences, accurate prediction of SCD using electrocardiogram is a hard task, especially applied in portable electrocardiograph. Methods This paper proposed a multi-domain features fusion algorithm to predict SCD. Heart rate variability (HRV) signals was used to investigate the characters of SCD. A multiscale variation feature extracted from multiscale poincare plots was proposed to demonstrate the dynamic changes of HRV along different scales. A time-domain feature, Shannon entropy and this multiscale variation feature were combined by using SVM classifier to classify SCD. HRV signals from different time periods prior to SCD onset were used to test the effectiveness of the SCD prediction algorithm. And the dynamic variation characteristics of SCD prediction accuracy for each minute were also studied. Results In the prediction of SCD using the 70-min HRV signals before the onset of SCD, the average prediction accuracy only using the multiscale variation feature reached to 85.83%, which verified the effectiveness and high specificity of this multiscale variation feature. By combining time domain, Shannon entropy and the multiscale variation feature, the average prediction accuracy was improved to 91.22%. Through fusing multi-domain feature extracted in this paper, the advance prediction time was increased to 70 min before the onset of SCD. Conclusions A feature with high sensitivity and specificity is proposed to predict SCD. By fusing multi-domain features of HRV signals, a high prediction accuracy is achieved and the advance prediction ability is improved. The algorithm is low computational complexity and easy to integrate into cardiovascular intelligent monitoring equipment, making the intelligent monitoring and real-time early warning of SCD becomes possible.

Obesity is thought to significantly impact the quality of life. In this study, we sought to evaluate the health consequences of obesity on the risk of a broad spectrum of human diseases. The causal effects of exposing to obesity on health outcomes were inferred using Mendelian randomization (MR) analyses using a fixed effects inverse-variance weighted model. The instrumental variables were SNPs associated with obesity as measured by body mass index (BMI) reported by GIANT consortium. The spectrum of outcome consisted of the phenotypes from published GWAS and the UK Biobank. The MR-Egger intercept test was applied to estimate horizontal pleiotropic effects, along with Cochran’s Q test to assess heterogeneity among the causal effects of instrumental variables. Our MR results confirmed many putative disease risks due to obesity, such as diabetes, dyslipidemia, sleep disorder, gout, smoking behaviors, arthritis, myocardial infarction, and diabetes-related eye disease. The novel findings indicated that elevated red blood cell count was inferred as a mediator of BMI-induced type 2 diabetes in our bidirectional MR analysis. Intriguingly, the effects that higher BMI could decrease the risk of both skin and prostate cancers, reduce calorie intake, and increase the portion size warrant further studies. Our results shed light on a novel mechanism of the disease-causing roles of obesity.

Yunnan Province is the main planting area of the precious Chinese herbal medicines (CHM) Panax notoginseng; however, it locates the geological area with high soil heavy metals in China. The frequent land replacement due to continuous cropping obstacles and excessive application of chemicals makes P. notoginseng prone to be contaminated by heavy metals under the farmland P. notoginseng (FPn) planting. To overcome farmland shortage, understory P. notoginseng (UPn) was developed as a new ecological planting model featured by no chemicals input. However, this newly developed planting system requires urgently the soil-plant heavy metal characteristics and risk assessment. This study aimed to evaluate the pollution status of eight heavy metals in the tillage layer (0-20 cm), subsoil layer (20-40 cm) and the plants of UPn in Lancang County, Yunnan Province. Pollution index (P

One of the major causes of the coronary heart disease is vascular stenosis and thrombosis that is generally caused by development of fibrous plaques. Therefore, detection of a fibrous plaque in coronary arteries for the diagnosis and treatment of coronary heart disease is of clinical significance. Technical challenges are in reading the optical coherence tomography (OCT) images which is tedious and inaccurate. In response, we propose an automated coronary artery fibrous plaque detection method based on deep learning with Convolutional Neural Networks (CNN). We present our novel techniques of identifying a contracting path to capture the context and a symmetric expanding path that enables the precise localization. The algorithm utilizes the features of the contracting path and the expanding path, so that the merged features can present the context and accurate localization, and uses the multi-scale feature maps for detection. Experimental results show that the proposed method achieved a coincidence of 91.04%, accuracy of 94.12%, and recall of 94.12%. Compared with the previously published work the proposed method is advantageous in both accuracy and robustness.

Antipsychotic-induced metabolic disturbance (AIMD) is a common adverse effect of antipsychotics with genetics partly underpinning variation in susceptibility among schizophrenia patients. Melanocortin4 receptor (MC4R) gene, one of the candidate genes for AIMD, has been under-studied in the Chinese patients. We conducted a pharmacogenetic study in a large cohort of Chinese patients with schizophrenia. In this study, we investigated the genetic variation of MC4R in Chinese population by genotyping two SNPs (rs489693 and rs17782313) in 1,991 Chinese patients and examined association of these variants with the metabolic effects that were often observed to be related to AIMD. Metabolic measures, including body mass index (BMI), waist circumference (WC), glucose, triglyceride, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were assessed at baseline and after 6-week antipsychotic treatment. We found that interaction of SNP×medication status (drug-naïve/medicated) was significantly associated with BMI, WC, and HDL change %, respectively. Both SNPs were significantly associated with baseline BMI and WC in the medicated group. Moderate association of rs489693 with WC, Triglyceride, and HDL change % were observed in the whole sample. In the drug-naïve group, we found recessive effects of rs489693 on BMI gain more than 7%, WC and Triglyceride change %, with AA incurring more metabolic adverse effects. In conclusion, the association between rs489693 and the metabolic measures is ubiquitous but moderate. Rs17782313 is less involved in AIMD. Two SNPs confer risk of AIMD to patients treated with different antipsychotics in a similar way.

It has been recognized that drug addiction engages aberrant process of learning and memory, and substantial studies have focused on developing effective treatment to erase the enduring drug memories to reduce the propensity to relapse. Extinction, a behavioral intervention exposing the individuals to the drug-associated cues repeatedly, can weaken the craving and relapse induced by drug-associated cues, but its clinic efficacy is limited. A clear understanding of the neuronal circuitry and molecular mechanism underlying extinction of drug memory will facilitate the successful use of extinction therapy in clinic. As a key component of mesolimbic system, medial prefrontal cortex (mPFC) has received particular attention largely in that PFC stands at the core of neural circuits for memory extinction and manipulating mPFC influences extinction of drug memories and subsequent relapse. Here, we review the recent advances in both animal models of drug abuse and human addicted patients toward the understanding of the mechanistic link between mPFC and drug memory, with particular emphasis on how mPFC contributes to the extinction of drug memory at levels ranging from neuronal architecture, synaptic plasticity to molecular signaling and epigenetic regulation, and discuss the clinic relevance of manipulating the extinction process of drug memory to prevent craving and relapse through enhancing mPFC function.

Although it has been recognized that inhibition of calcineurin induced depressive-like behavior, the underlying neural mediators have not yet been identified. Mammalian target of rapamycin (mTOR), a serine/threonine protein kinase that regulates protein synthesis in synapses, has been demonstrated to be involved in the rapid antidepressant effects of ketamine.To investigate a potential role of mTOR signaling pathway which interferes with depressive-like behavior induced by calcineurin blockade and to determine the neurobiological mechanisms underlying mood-related disorders.Calcineurin inhibitor cyclosporine A (CsA) and tacrolimus (FK506) were microinjected into the medial prefrontal cortex (mPFC) in rats, and the depressive-like behavior was measured in sucrose preference test and forced swim test. Additionally, mTOR activity was tested by the levels of phosphorylation of p70s6 kinase (p70s6k) and 40S ribosomal protein S6 (rps6).Chronic microinjection of CsA or FK506 into mPFC increased depressive-like behaviors and decreased mTOR activity, but acute CsA or FK506 had no effects on both behavioral phenotype and mTOR activity. Furthermore, activation of mTOR by NMDA reversed the depressive-like behavior induced by chronic CsA or FK506 administration. Moreover, inhibition of mTOR by rapamycin reversed the antidepressant effects of ketamine. Finally, traditional antidepressant venlafaxine prevented the depressive-like performance induced by chronic CsA or FK506 treatment.These findings indicate that calcineurin-inhibition-induced depressive-like behavior is mediated by blockade of the mTOR signaling pathway and raise the possibility that stimulation of specific brain mTOR may be sufficient to decrease risk of affective disorders in patients treated with calcineurin inhibitor.

To identify susceptibility loci for schizophrenia, we performed a two-stage genome-wide association study (GWAS) of schizophrenia in the Han Chinese population (GWAS: 746 individuals with schizophrenia and 1,599 healthy controls; validation: 4,027 individuals with schizophrenia and 5,603 healthy controls). We identified two susceptibility loci for schizophrenia at 6p21-p22.1 (rs1233710 in an intron of ZKSCAN4, P(combined) = 4.76 × 10(-11), odds ratio (OR) = 0.79; rs1635 in an exon of NKAPL, P(combined) = 6.91 × 10(-12), OR = 0.78; rs2142731 in an intron of PGBD1, P(combined) = 5.14 × 10(-10), OR = 0.79) and 11p11.2 (rs11038167 near the 5' UTR of TSPAN18, P(combined) = 1.09 × 10(-11), OR = 1.29; rs11038172, P(combined) = 7.21 × 10(-10), OR = 1.25; rs835784, P(combined) = 2.73 × 10(-11), OR = 1.27). These results add to previous evidence of susceptibility loci for schizophrenia at 6p21-p22.1 in the Han Chinese population. We found that NKAPL and ZKSCAN4 were expressed in postnatal day 0 (P0) mouse brain. These findings may lead to new insights into the pathogenesis of schizophrenia.

Moso bamboo (Phyllostachys pubescens) has an extremely fast growth rate, however little information is available on the dynamics of carbon accumulation during the fast growth period. Bamboo trunk were sampled at three different stages (1: shoot emergence to first shell detachment; 2: first shell detachment to branch emergence; 3: branch emergence to detachment of all shells) and divided into three parts (upper, middle and lower). The average shoot elongation rate and biomass accumulation rate were 17 cm/d and 96 g/d, respectively. The carbon content increased progressively at the growth stage, and the fixed carbon was partitioned into cell wall hemicellulose and cellulose to meet the demand of rapid cell elongation. Different rates of N, P, K, Ca, and Mg content were found among different parts. These results indicated that the fast growth of the bamboo trunk is related to the extraordinary ability of bamboo to assimilate carbon, but not consistently related to mineral nutrients absorption.

The mercury release behavior during thermal decomposition of three Chinese coals with different types was studied under nitrogen, carbon dioxide and air at temperatures of 800, 900, 1,000 and 1,100 °C. The thermal treatment experiments were carried out in a quartz tube reactor. Results showed that the release ratio of total mercury during thermal decomposition of coals increases with the increasing temperature. The order of the amount of mercury released under the three atmospheres is nitrogen carbon dioxide>air for all three coals. The release behavior of the total mercury under air is independent of the coal type. Under the other two atmospheres the release behavior is distinguished by the coal type.