Search

Activation of dopamine (DA) neurons is essential for the transition from sleep to wakefulness and maintenance of awakening, and sufficient to accelerate the emergence from general anesthesia in animals. Dopamine receptors (DR) are involve in arousal mediation. In the present study, we showed that the olfactory tubercle (OT) was active during emergence from isoflurane anesthesia, local injection of dopamine D1 receptor (D1R) agonist chloro-APB (1 mg/mL) and D2 receptor (D2R) agonist quinpirole (1 mg/mL) into OT enhanced behavioural and cortical arousal from isoflurane anesthesia, while D1R antagonist SCH-23390 (1 mg/mL) and D2R antagonist raclopride (2.5 mg/mL) prolonged recovery time. Optogenetic activation of DAergic terminals in OT also promoted behavioural and cortical arousal from isoflurane anesthesia. However, neither D1R/D2R agonists nor D1R/D2R antagonists microinjection had influences on the induction of isoflurane anesthesia. Optogenetic stimulation on DAergic terminals in OT also had no impact on the anesthesia induction. Our results indicated that DA signals in OT accelerated emergence from isoflurane anesthesia. Furthermore, the induction of general anesthesia, different from the emergence process, was not mediated by the OT DAergic pathways.

Background:Substantial substance use disorders and related health conditions emerged during the mid-20th century and continue to represent a remarkable 21st century global burden of disease. This burden is largely driven by the substance-dependence process, which is a complex process and is influenced by both genetic and environmental factors. During the past few decades, a great deal of progress has been made in identifying genetic variants associated with Substance Use and Dependence (SUD) through linkage, candidate gene association, genome-wide association and sequencing studies.Methods:Various statistical methods and software have been employed in different types of SUD genetic studies, facilitating the identification of new SUD-related variants.Conclusion:In this article, we review statistical methods and software that are currently available for SUD genetic studies, and discuss their strengths and limitations.

Objective: To evaluate the efficacy and toxicity of VMP regimen applied to the patients with low-risk gestational trophoblastic neoplasia (LR-GTN) treated in Anhui provincial hospital. Materials and methods: Between 2005 and 2017, 87 patients with low-risk gestational trophoblastic neoplasia received VMP regimen, consisted of vincristine (VCR), methotrexate (MTX) and platinum (cisplatin, carboplatin or nedaplatin), 68 of whom received VMP as their first-line chemotherapy, and 19 methotrexate-failed patients received VMP regimen as their second-line chemotherapy. The staging and scoring system was based on International Federation of Gynecology and Obstetrics (FIGO 2000) criteria. We describe and analyze their baseline characteristics, remission/resistance/recurrence rates, adverse reactions and prognosis. Results: The first-line VMP protocol can achieve an 83.8% remission rate and it tended to develop resistance when the pretreatment β-hCG reaches 7503.5 IU/L, and can achieve complete remission with FAV and EMA-CO as the salvage regimen. Among the 19 methotrexate-failed patients, 2 of whom were yet resistant to VMP regimen, followed by several courses of salvage chemotherapy such as FAV and EMP, and achieved 89.5% remission rate in second-line VMP group. Resistance to this regimen was obviously related with higher pre-treatment HCG whether used as primary or salvage treatment. Severe myelosuppression (grade 3 or 4) was shown in 4 (5.9%) of 68 cases, of which none was grade 4. Conclusion: For patients diagnosed with LR-GTN VMP regimen was a safe and effective treatment with a high rate of remission. Keywords: Low-risk gestational trophoblastic neoplasia, Vincristine, Methotrexate, Platinum, Efficacy

Vegetation segmentation from images is an essential issue in the application of computer vision in agriculture. In this paper, we present a new vegetation segmentation method based on Particle Swarm Optimisation (PSO) clustering and morphology modelling in CIE L∗a∗b∗ colour space. At the off-line learning stage, a new method is put forward to determine the clustering number. Secondly, the tools of morphological dilation and erosion are employed to establish the vegetation colour model. At the online segmentation stage, the PSO-based k-means is used to cluster the vegetation image into vegetation classes and non-vegetation classes. Afterwards, the established colour model is used to distinguish the vegetation classes and give the segmentation result. In the experiments, the proposed method was applied to segment 200 smaller regions of the full camera images of rice and 100 smaller regions of the full camera images of cotton. The means of segmentation qualities reached 88.1% and 91.7% respectively. Moreover, the proposed method was compared with three well-known vegetation segmentation methods and two skin segmentation methods. Experiments demonstrate that the proposed method yielded the highest mean of segmentation qualities and lowest standard deviations of segmentation qualities. In addition, the vegetation colour models built with different structuring element types are analysed.

Crop segmentation from the images taken in the outdoor fields is a complex task. In this paper, a new morphology modeling method is utilized to establish the crop color model in the CIE L^*a^*b^* (or Lab for simplification) color space and to realize the crop image segmentation. In the supervised learning stage, morphology modeling is applied to deal with the color characteristics of the crop with respect to the pixel lightness component and establish the crop color model. To verify the performance of the proposed method, 56 test images which in size of 601x601 and taken from April 27, 2011 to May 21, 2011 are utilized to compare the proposed method with eight other famous approaches. Experiment shows that the segmentation quality of the proposed method is approximately 87.2% for the Automatic Target Recognition Working Group (ATRWG) evaluation method and 96.0% for another evaluation method. Moreover, the segmentation performance for images taken on cloudy, overcast and sunny days is analyzed. Experiment demonstrates that our method is robust to the variation of illumination in the field and performed better than eight other approaches. Furthermore, the impact of different structuring element types to the proposed method is compared. Overall, the proposed crop segmentation method can be used to crop segmentation in the field effectively.

This paper proposes an efficient joint implementation algorithm for computing color space conversion, quantization and discrete cosine transform (DCT) in an image coder/decoder. By combining the three stages, the proposed algorithm reduces the operation amount of computing color space conversion considerably. In the case of color sampling 4:4:4, the proposed algorithm reduces the multiplication amount by 40% and the addition amount by 42% for the conversion from RGB to YCbCr in an image coder, and reduces the multiplication amount by 60% and the addition amount by 42% for the conversion from YCbCr to RGB in an image decoder. In the cases of down-sampling 4:2:2 and 4:1:1, there are the similar results. The existing fast methods in the literatures can still be applied together with this proposed algorithm into the implementation of the international image coding standards which use the transform coding technology, such as JPEG, MPEG and H.26X, and raises the image coding/decoding speed efficiently.

Summary Epithelial ovarian cancer is composed of a diverse group of tumors that can be derived from the fallopian tube, endometrium, or ovary. In this study, we explored the expression levels of LATS family members in ovarian tumors using normal ovaries, fallopian tubes, and endometrium as controls. Immunohistochemistry studies of LATS1, LATS2, Pax8, and calretinin were performed on normal ovary, fallopian tube, normal endometrium, and ovarian tumor sections. Statistical analyses were conducted using the χ 2 test, Fisher exact test, or Kruskal-Wallis H test. Patient survival was analyzed using the Kaplan-Meier method. LATS1 was expressed in normal ovarian epithelia, endometrium, and fallopian tubes, whereas LATS2 expression was observed in the normal fallopian tubes and endometrium. High expressions of LATS1 and LATS2 in serous cystadenomas gradually decreased in borderline cystadenomas and carcinomas, respectively. However, an opposite expression pattern was observed in mucinous tumors. Low expressions of LATS1 and LATS2 were also detected in clear cell carcinoma. Both LATS1 and LATS2 expression levels significantly correlated with recurrence and stage; LATS1 levels were also related with tumor grades in serous carcinoma. However, univariate and multivariate Cox regression analyses revealed that high expression of LATS1 was associated with better prognosis in patients with serous carcinoma. Both LATS1 and LATS2 were not related with the clinical variables in mucinous and clear cell carcinoma. LATS1 expression levels might be a valuable survival indicator in ovarian serous carcinoma.

An energy-efficient distributed detection method for wireless sensor networks is considered in this paper. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. We assume that the links between the nodes and the fusion center are subject to Rayleigh fading wireless channels. At the fusion center, incorporating the effect of fading in the detection process, a decision fusion rule based on the linear minimum mean square error(LMMSE) is investigated. In this paper, two types of constraints are considered: 1) transmission power constraints at the nodes, and 2) the communication channel between the nodes and the decision center. we propose a optimal distributed estimation algorithm in energy-constrained wireless sensor networks. By numerical examples, we illustrate the performance of the proposed serial detection scheme.

We consider energy-efficient Distributed Detection in wireless sensor networks. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. Each node computes a local statistic and communicates it to a fusion center over Rayleigh fading wireless channels.At the fusion,the linear minimum mean square error(LMMSE) is used. In this paper Two types of constraints are considered: 1) transmission power constraints at the nodes, and 2) the communication channel between the nodes and the decision center. we propose a optimal distributed estimation algorithm in energy-constrained wireless sensor networks. Finally, we demonstrate the applicability of our results through numerical examples.

By means of a linear tendency estimation scheme and correlation analysis a study is undertaken of change in Zhengzhou climate and phonological response of woody plants thereto, together with relations between meteorological elements (rainfall, sunshine length and mean temperature) and phenological periods investigated. And later, using a least squares polynomial, a fit expression is constructed for the peak phase of flowering in relation to mean temperature over the previous 3 months. Results show that mean temperature is the critical climate factor to the phonological response of the trees except for leaf-falling phase in autumn; temperature inference of phenology has a clear ecological implication in exploring the relation between climate change and phonological response, with which to plan agricultural undertaking and monitor ecological environment on a scientific basis.

Climate yield potential is known to be under great effect of climate factors. Based on multi-yearly climate records and agrometeorological observations and by means of the scheme for calculating yield potential (YP) proposed by Huang Bingwei the authors investigate the distribution of mean climate YP for several representative stations in Henan and averaged availability of climate resources for staple crops in this province, and with Zhengzhou station as the typical station, calculated is made of annual YP of photosynthesis, light-temperature, and light - temperature- water and also YP of wheat and corn related to the above three factors. Wavelet analysis shows that on an annual basis, the photosynthesis YP has quasi-8 yearly periods, light-temperature YP gives quasi-8 and quasi-4 yearly periods, and light- temperature-water YP exhibits quasi-6 and quasi-10-yearly periods. Study is also undertaken of availability of climate resources by wheat and corn in the year and their growth season. Finally, analysis is done of effects of meteorological factors upon yields of the staple crops as well as their availability of the climate resources.