MV-mimicking micelles loaded with PEG-serine-ACP nanoparticles to achieve biomimetic intra/extra fibrillar mineralization of collagen in vitro

Since their discovery, matrix vesicles (MVs) containing minerals have received considerable attention for their role in the mineralization of bone, dentin and calcified cartilage. Additionally, MVs' association with collagen fibrils, which serve as the scaffold for calcification in the organic matrix, has been repeatedly highlighted. The primary purpose of the present study was to establish a MVs–mimicking model (PEG-S-ACP/micelle) in vitro for studying the exact mechanism of MVs-mediated extra/intra fibrillar mineralization of collagen in vivo. In this study, high-concentration serine was used to stabilize the amorphous calcium phosphate (S-ACP), which was subsequently mixed with polyethylene glycol (PEG) to form PEG-S-ACP nanoparticles. The nanoparticles were loaded in the polysorbate 80 micelle through a micelle self-assembly process in an aqueous environment. This MVs–mimicking model is referred to as the PEG-S-ACP/micelle model. By adjusting the pH and surface tension of the PEG-S-ACP/micelle, two forms of minerals (crystalline mineral nodules and ACP nanoparticles) were released to achieve the extrafibrillar and intrafibrillar mineralization, respectively. This in vitro mineralization process reproduced the mineral nodules mediating in vivo extrafibrillar mineralization and provided key insights into a possible mechanism of biomineralization by which in vivo intrafibrillar mineralization could be induced by ACP nanoparticles released from MVs. Also, the PEG-S-ACP/micelle model provides a promising methodology to prepare mineralized collagen scaffolds for repairing bone defects in bone tissue engineering.     

Response of three lotic assemblages to riparian and catchment‐scale land use: implications for designing catchment monitoring programmes

1. Although many studies have focussed on the effects of catchment land use on lotic systems, the importance of broad (catchment) and fine (segment/reach) scale effects on stream assemblages remain poorly understood. 2. Nine biological metrics for macrophytes (498 sites), benthic macroinvertebrates (491) and fish (478) of lowland and mountain streams in four ecoregions of France and Germany were related to catchment and riparian buffer land use using partial Redundancy Analysis and Boosted Regression Trees (BRTs). 3. Lotic fauna was better correlated (mean max., r = 0.450) than flora (r = 0.277) to both scales of land use: the strongest correlations were noted for mountain streams. BRTs revealed strong non‐linear relationships between mountain assemblage metrics and land use. Correlations increased with increasing buffer lengths, suggesting the importance of near‐stream land use on biotic assemblages. 4. Several metrics changed markedly between 10–20% (mountain ecoregions) and 40–45% (lowland) of arable land use, irrespective of the buffer size. At mountain sites with >10% catchment arable land use, metric values differed between sites with <30% and sites with >30% forest in the near‐stream riparian area. 5. These findings support the role of riparian land use in catchment management; however, differences between mountain and lowland ecoregions support the need for ecoregion‐specific management.     

How do elevated CO2 and O3 affect the interception and utilization of radiation by a soybean canopy?

Net productivity of vegetation is determined by the product of the efficiencies with which it intercepts light (?_i) and converts that intercepted energy into biomass (?_c). Elevated carbon dioxide (CO₂) increases photosynthesis and leaf area index (LAI) of soybeans and thus may increase ?_i and ?_c; elevated O₃ may have the opposite effect. Knowing if elevated CO₂ and O₃ differentially affect physiological more than structural components of the ecosystem may reveal how these elements of global change will ultimately alter productivity. The effects of elevated CO₂ and O₃ on an intact soybean ecosystem were examined with Soybean Free Air Concentration Enrichment (SoyFACE) technology where large field plots (20‐m diameter) were exposed to elevated CO₂ (～550 μmol mol^?1) and elevated O₃ (1.2 × ambient) in a factorial design. Aboveground biomass, LAI and light interception were measured during the growing seasons of 2002, 2003 and 2004 to calculate ?_i and ?_c. A 15% increase in yield (averaged over 3 years) under elevated CO₂ was caused primarily by a 12% stimulation in ?_c , as ?_i increased by only 3%. Though accelerated canopy senescence under elevated O₃ caused a 3% decrease in ?_i, the primary effect of O₃ on biomass was through an 11% reduction in ?_c. When CO₂ and O₃ were elevated in combination, CO₂ partially reduced the negative effects of elevated O₃. Knowing that changes in productivity in elevated CO₂ and O₃ were influenced strongly by the efficiency of conversion of light energy into energy in plant biomass will aid in optimizing soybean yields in the future. Future modeling efforts that rely on ?_c for calculating regional and global plant productivity will need to accommodate the effects of global change on this important ecosystem attribute.     

Leaf micromorphology inAgathis and its taxonomic implications

This study surveys the micromorphological surface structure of the leaves of the conifer genusAgathis (Araucariaceae) from throughout the range of the genus (Malaysia to New Zealand and Fiji) as seen with the scanning electron microscope. These data confirm that the vegetative parts ofAgathis are taxonomically highly conservative, but suggest the Melanesian and New Zealand elements to be distinctive from those of the rest of the genus, and from one another. Conclusions are compared with those that have been derived from studies based on other characters.     

Sampling for Explosives-Residues at Fort Greely,Alaska

Fort Greely, Alaska has an extensive complex of weapon training and testing areas located on lands withdrawn from the public domain under the Military Lands Withdrawal Act (PL106-65). The Army has pledged to implement a program to identify possible munitions contamination. Because of the large size (344,165,000 m²) of the high hazard impact areas, characterization of these constituents will be difficult. We used an authoritative sampling design to find locations most likely to contain explosives-residues on three impact areas. We focused our sampling on surface soils and collected multi-increment and discrete samples at locations of known firing events and from areas on the range that had craters, pieces of munitions, targets, or a designation as a firing point. In the two impact areas used primarily by the Army, RDX was the most frequently detected explosive. In the impact area that was also used by the Air Force, TNT was the most frequently detected explosive. Where detected, the explosives concentrations generally were low (<0.05 mg/kg) except in soils near low-order detonations, where the explosive-filler was in contact with the soil surface. These low-order detonations potentially can serve as localized sources for groundwater contamination if positioned in recharge areas.     

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.     

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.