Structural Insight into Chromatin Recognition by Multiple Domains of the Tumor Suppressor RBBP1

Retinoblastoma-binding protein 1 (RBBP1) is involved in gene regulation, epigenetic regulation, and disease processes. RBBP1 contains five domains with DNA-binding or histone-binding activities, but how RBBP1 specifically recognizes chromatin is still unknown. An AT-rich interaction domain (ARID) in RBBP1 was proposed to be the key region for DNA-binding and gene suppression. Here, we first determined the solution structure of a tandem PWWP-ARID domain mutant of RBBP1 after deletion of a long flexible acidic loop L12 in the ARID domain. NMR titration results indicated that the ARID domain interacts with DNA with no GC- or AT-rich preference. Surprisingly, we found that the loop L12 binds to the DNA-binding region of the ARID domain as a DNA mimic and inhibits DNA binding. The loop L12 can also bind weakly to the Tudor and chromobarrel domains of RBBP1, but binds more strongly to the DNA-binding region of the histone H2A-H2B heterodimer. Furthermore, both the loop L12 and DNA can enhance the binding of the chromobarrel domain to H3K4me3 and H4K20me3. Based on these results, we propose a model of chromatin recognition by RBBP1, which highlights the unexpected multiple key roles of the disordered acidic loop L12 in the specific binding of RBBP1 to chromatin.     

Mechanistic studies on carboxypeptidase a from goat pancreas — part II: Evidence for carboxyl group

Studies with substrate analogues and the pH optimum indicated the involvement of carboxyl group in the active site of goat carboxypeptidase A. Chemical modification of the enzyme with 1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide methoI -p-toluene sulphonate, a carboxyl specific reagent, led to loss of both esterase and peptidase activities. Protection studies showed that this carboxyl group was in the active site and was protected by Βp-phenylpropionic acid and glycyl-L-tyrosine. Kinetic studies also confirmed the involvement of carboxylic group because the enzyme modification with water soluble carbodiimide was a two step reaction which excluded the possibility of tyrosine or lysine which are known to give a one step reaction with this reagent     

Diet of the Indochinese silvered langur (Trachypithecus germaini) in Kien Luong Karst area,Kien Giang Province

The Indochinese silvered langur (Trachypithecus germaini) is distributed to the west of Mekong River in Cambodia, Lao PDR, Thailand and Vietnam. During a two‐year study, from May 2014 to May 2016, we collected 320.44 hr of behavior, with 17,040 feeding bouts recorded (142 hr) for T. germaini on Chua Hang Karst Mountain, Kien Luong District, Kien Giang Province, Vietnam. Feeding accounted for 45% of the Indochinese silvered langurs’ activity budget. The plant diet of the Indochinese silvered langurs was principally composed of young leaves (58%), followed by mature leaves (9.5%), fruits (22.7%), flowers (4.7%), buds (3.3%), petioles (1.2%), and other (0.5%). A total of 58 plant species were fed on by the silvered langurs, and leaves of eight species (Phyllathus reticulatus, Ficus rumphii, Ficus tinctoria, Ficus microcarpa, Cayratia trifolia, Streblus ilicifolia, Combretum latifolium, and Streblus asper) were fed on throughout the year. P. reticulatus was most frequently eaten (13.9% feeding time, n = 1,733). Food selection differed significantly between months and seasons. The Indochinese silvered langurs ate 27 plant species in the wet season compared with 23 plant species in the dry season. Leaf chemical composition of two food categories, 16 eaten species (with 10 most frequently consumed species and six least consumed species), and four noneaten species, were analyzed. Feeding samples from eaten species in the Indochinese silvered langurs's diet contained lower amounts of condensed tannin, lignin, protein, ash, and lipids, but a higher amount of total sugar compared with samples from noneaten species. Furthermore, the most frequently consumed species contained lower amounts of lignin compared with the less frequently consumed species. Using a generalized linear model with five variables, including neutral detergent fiber (NDF), total sugar, lignin, lipid, and calcium (Ca) indicated that NDF positively correlated and lignin content negatively correlated with feeding records in the diet of these langur.     

Population Changes of Heterodera glycines and Soybean Yields Resulting from Soil Treatment with Alachlor,Fenamiphos, and Ethoprop

The population dynamics of Heterodera glycines as influenced by alachlor, fenamiphos, and ethoprop alone and in herbicide-nematicide combinations were studied in the field. Numbers of H. glycines juveniles and eggs were higher at midseason and harvest where nematicides were applied. Fenamiphos alone or in combination with alachlor provided better control of H. glycines and greater seed yields than treatments with ethoprop. Numbers of H. glycines eggs at harvest in 1980 were positively correlated with numbers of juveniles at planting in 1981 and negatively related to seed yield in 1981.     

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.

     

Parameter estimation for the distribution of single cell lag times

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level.We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.     

Relative growth rate correlates negatively with pathogen resistance in radish: the role of plant chemistry

Plant growth rate has frequently been associated with herbivore defence: a large investment in quantitative defence compounds occurs at the expense of growth. We tested whether such a relationship also holds for growth rate and pathogen resistance. For 15 radish (Raphanus sativus L.) cultivars, we determined the potential growth rate and the resistance to fungal wilt disease caused by Fusarium oxysporum. We subsequently aimed to explain a putative negative relationship between growth rate and resistance based on plant chemical composition. Both growth rate and resistance level varied greatly among cultivars. Moreover, there was a strong negative correlation between growth rate and resistance, i.e. there are costs associated with a high resistance level. Roots of slow-growing, resistant cultivars have a higher biomass density. Using pyrolysis mass spectrometry. we part1y explained variation in both growth rate and resistance in terms of the same change in chemical composition. Leaves of slow-growing, resistant cultivars contained more cell wall material. Surprisingly, roots of slow-growing, highly resistant cultivars contained significantly less cell wall material, and more cytoplasmic elements (proteins). We speculate that this higher protein concentration is related to high construction and turn-over costs and high metabolic activity. The latter in turn is thought to be responsible for a rapid and adequate resistance reaction, in which phenols may be involved.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling

Three simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F-test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.