Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma

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Diversity of endophytic bacteria and fungi in seeds of Elymus nutans growing in four locations of Qinghai Tibet Plateau,China

Plant and Soil - Seeds are involved in the transmission of microorganisms from one plant generation to the next, acting as initial inoculum for the plant microbiome, therefore provide a key source...     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Comparative Analysis of Endogenous Hormones and Metabolite Profiles in Early-Spring Flowering Plants and Unflowered Plants Revealing the Strategy of Blossom

Journal of Plant Growth Regulation - Early-spring plants are a special type of plant that complete their life cycle promptly in cold, early spring. Very little effort has been made into researching...     

A neural network study on the dynamic identification of a fermentation system

The objective of this paper is to propose neural networks for the study of dynamic identification and prediction of a fermentation system which produces mainly 2,3-butanediol (2,3-BDL). The metabolic products of the fermentation, acetic acid, acetoin, ethanol, and 2,3-BDL were measured on-line via a mass spectrometer modified by the insertion of a dimethylvinylsilicone membrane probe. The measured data at different sampling times were included as the input and output nodes, at different learning batches, of the network. A fermentation system is usually nonlinear and dynamic in nature. Measured fermentation data obtained from the complex metabolic pathways are often difficult to be entirely included in a static process model, therefore, a dynamic model was suggested instead. In this work, neural networks were provided by a dynamic learning and prediction process that moved along the time sequence batchwise. In other words, a scheme of two-dimensional moving window (number of input nodes by the number of training data) was proposed for reading in new data while forgetting part of the old data. Proper size of the network including proper number of input/output nodes were determined by trained with the real-time fermentation data. Different number of hidden nodes under the consideration of both learning performance and computation efficiency were tested. The data size for each learning batch was determined. The performance of the learning factors such as the learning coefficient η and the momentum term coefficient α were also discussed. The effect of different dynamic learning intervals, with different starting points and the same ending point, both on the learning and prediction performance were studied. On the other hand, the effect of different dynamic learning intervals, with the same starting point and different ending points, was also investigated. The size of data sampling interval was also discussed. The performance from four different types of transfer functions, x/(1+|x|), sgn(x)·x ²/(1+x ²), 2/(1+e ^{? x} )?1, and 1/(1+e ^{? x} ) was compared. A scaling factor b was added to the transfer function and the effect of this factor on the learning was also evaluated. The prediction results from the time-delayed neural networks were also studied.     

Functional analysis of a miRNA‐like small RNA derived from Bombyx mori cytoplasmic polyhedrosis virus

Bombyx mori cytoplasmic polyhedrosis virus (BmCPV) is a major pathogen of the economic insect silkworm, Bombyx mori. Virus‐encoded microRNAs (miRNAs) have been proven to play important roles in host–pathogen interactions. In this study we identified a BmCPV‐derived miRNA‐like 21 nt small RNA, BmCPV‐miR‐1, from the small RNA deep sequencing of BmCPV‐infected silkworm larvae by stem‐loop quantitative real‐time PCR (qPCR) and investigated its functions with qPCR and lentiviral expression systems. Bombyx mori inhibitor of apoptosis protein (BmIAP) gene was predicted by both target prediction software miRanda and Targetscan to be one of its target genes with a binding site for BmCPV‐miR‐1 at the 5′ untranslated region. It was found that the expression of BmCPV‐miR‐1 and its target gene BmIAP were both up‐regulated in BmCPV‐infected larvae. At the same time, it was confirmed that BmCPV‐miR‐1 could up‐regulate the expression of BmIAP gene in HEK293T cells with lentiviral expression systems and in BmN cells by transfecting mimics. Furthermore, BmCPV‐miR‐1 mimics could up‐regulate the expression level of BmIAP gene in midgut and fat body in the silkworm. In the midgut of BmCPV‐infected larvae, BmCPV‐miR‐1 mimics could be further up‐regulated and inhibitors could lower the virus‐mediated expression of BmIAP gene. With the viral genomic RNA segments S1 and S10 as indicators, BmCPV‐miR‐1 mimics could up‐regulate and inhibitors down‐regulate their replication in the infected silkworm. These results implied that BmCPV‐miR‐1 could inhibit cell apoptosis in the infected silkworm through up‐regulating BmIAP expression, providing the virus with a better cell circumstance for its replication.     

Prenatal diagnosis of Pallister-Killian syndrome and literature review

Pallister-Killian syndrome (PKS) is a rare sporadic genetic disorder usually caused by mosaicism of an extra isochromosome of 12p (i(12p)). This retrospective study analysed the prenatal ultrasound manifestations and molecular and cytogenetic results of five PKS foetuses. Samples of amniotic fluid and/or cord blood, skin biopsy and placenta were collected. Conventional karyotyping and single nucleotide polymorphism array (SNP array) were performed on all the amniotic fluid or cord blood samples. Copy number variants sequencing (CNV-seq) and fluorescence in situ hybridization (FISH) were also used for the validation for one foetus. All the five foetuses were from pregnancies with advanced parental age. Two foetuses involved structural abnormalities and one foetus had only soft markers, all of which included increased nuchal translucency. The rest two foetuses had normal ultrasounds in the second trimester, which has rarely been reported before. The karyotype revealed typical i(12p) in four cases and a small supernumerary marker chromosome consisting of 12p and 20p in the remaining one case. The proportion of cells with i(12p) ranged from 0 to 100% in cultural cells, while SNP array results suggested 2−4 copies of 12p. For one foetus, metaphase FISH showed normal results, but the interphase FISH suggested cell lines with two, three and four copies of 12p in the amniotic fluid. Advanced parental age may be an important risk factor for PKS, and there were no typical ultrasound manifestations related to PKS. A combination of karyotype analysis and molecular diagnosis is an effective method for the diagnosis of PKS.