Liver histology and histomorphometry in hybrid sorubim (Pseudoplatystoma reticulatum × Pseudoplatystoma corruscans) reared on intensive fish farming

This study aimed to characterize the liver histology and histomorphometry in sorubim hybrid of different categories (nursery, growth and grow‐out) reared on fish farming. The categories were defined considering body weight (BW): nursery category (n = 5): BW = 37.06 ± 6.00 g (31.6–45.3 g); growth category (n = 5): BW = 310.40 ± 53.80 g (242.1–376.4 g) and grow‐out category (n = 5): BW = 874.28 ± 27.59 g (846.2–913.1 g). Liver fragments were processed to paraffin inclusion, and sections were stained by haematoxylin and eosin (H&E), PAS (Periodic Acid Schiff) and Perl's staining to histology, histomorphometry and density volumetric of liver structures; glycogen analysis and to detect ferric irons (Fe³⁺) respectively. The hepatosomatic index decreased between the categories (P < 0.01). The percentage of PAS‐positive hepatocytes in the nursery category was higher (P < 0.05) in relation to the growth and grow‐out categories. The hepatocytes from all fish were positive to Perl's staining. The density volumetric of liver structures did not differ among categories except to blood vessels were higher (P < 0.01) in the nursery and growth. The area (μm²) and perimeter (μm) of hepatocytes, and the area (μm²), perimeter (μm) and volume (μm³) of the nuclei from grow‐out fish were lower (P < 0.01) than those from the nursery and growth categories. Changes in morphometric characteristics of hepatocytes may result from metabolic changes associated with body growth surubins; therefore, these morphometric characteristics of liver tissue can be used as functional biomarkers for the assessment of fish health and nutrition status.     

Artificial neural network modeling of microbial community structures in the Atlantic Forest of Brazil

Microbial communities vary across the landscape in forest soils, but prediction of their biomass and composition is a difficult challenge due to the large numbers of variables that influence their community structures. Here we examine the use of artificial neural network (ANN) models for extraction of patterns among soil chemical variables and microbial community structures in forest soils from three regions of the Atlantic Forest of Brazil. At each location, variations in soil chemical properties and FAME profiles of microbial community structures were mapped at 20 × 20 m intervals within 10 ha parcels. Geostatistical analyses showed that spatial variability in soil physical and chemical variables could be mapped at scale distances of 20 m, but that FAME profiles representing the microbial communities were highly variable and had no spatial dependence at the same scale in most cases. RDA analysis showed that FAME signatures representing different microbial groups were positively associated with soil pH, OM, P and base cations concentrations, whereas microbial biomass was negatively associated with the same environmental factors. In contrast, ANN models revealed clear relationships between microbial community structures at each parcel location, and generated verifiable predictions of variations in FAME profiles in relation to soil pH, texture, and the relative abundances of base cations. The results suggest that ANN modeling provides a useful approach for describing the relationships between microbial community structures and soil properties in tropical forest soils that were not able to be captured using geostatistical and RDA analyses.     

Comparative functional responses of native and high‐impacting invasive fishes: impact predictions for native prey populations

Comparative functional responses (FRs) can predict impacts of invasive species, including piscivorous fishes, via quantifying their depletion of native food resources as a function of prey density. The utility of FRs for predicting impacts on prey populations by invasive fishes of different trophic guilds was tested here by comparing the FRs of the invaders Cyprinus carpio and Carassius auratus, with three native, trophically analogous fishes, Barbus barbus, Squalius cephalus and Tinca tinca. Chironomid larvae and Gammarus pulex were used as prey items. Predictions, developed from studies on the foraging of C. carpio and C. auratus in the literature, were that the invaders would have significantly higher consumption rates for chironomids than the native fishes, but not for G. pulex. Mean consumption rates for chironomids were significantly lower for both invaders than B. barbus and S. cephalus, but were similar to T. tinca. Barbus barbus had a significantly lower consumption rate of G. pulex than both invaders, but there were no significant differences between S. cephalus, T. tinca and the invaders. All FRs were type II, with FR curves for the invaders preying upon chironomids never being significantly higher than the native fishes, contrary to predictions. For G. pulex, some significant differences were apparent between the invaders and native fishes, but again were contrary to predictions. These results indicated that when predation impacts of invasive fishes could also be a function of their population density and body sizes, these parameters should be incorporated into FR models to improve impact predictions.     

大连市中心区声环境功能区划调整研究

在分析了大连市中心区声环境功能区划调整必要性的基础上,全面评估了现有区划实施效果,以问题为导向提出了区划调整的方法体系,并阐述了区划调整结果的可行性,为城市环境噪声管理和防治提供科学依据。     

基于WT-CNN-LSTM的溶解氧含量预测模型

溶解氧（Dissolved oxygen, DO）含量是影响水产养殖产量的重要因素之一，具有时序性、不稳定性和非线性等特点，且其影响因子过多、存在复杂的耦合关系，难以实现精准预测。针对传统长短时记忆神经网络（Long short term memory, LSTM）预测模型易引入冗余数据，且在训练过长序列时会出现梯度消失现象，从而不能捕捉因子间长期的依赖性问题，提出了基于小波变换（Wavelet transform, WT）、卷积神经网络（Convolutional neural network, CNN）和LSTM的溶解氧含量预测模型。首先，使用WT降低数据噪声；然后，使用CNN深度挖掘各变量之间的潜在关系；最后，利用LSTM的时序性预测2h后的水产养殖溶解氧含量。结果表明，本文提出的WT-CNN-LSTM模型预测效果良好，其平均绝对误差、均方根误差和决定系数分别为0.138、0.229和0.954，比传统LSTM模型分别优化了28.87%、21.03%和4.61%。     

Evaluation of Intestinal Absorption of Dietary Halocynthiaxanthin,a Carotenoid from the Sea Squirt Halocynthia roretzi

Halocynthiaxanthin is an acetylenic carotenoid mainly found in Halocynthia roretzi. To date, several bioactivities of halocynthiaxanthin have been reported, but its mechanism of digestion and absorption in mammals has not been studied yet. In this study, we evaluated the intestinal absorption of halocynthiaxanthin in mice. The halocynthiaxanthin-rich fraction was prepared from the tunicate Halocynthia roretzi. Mice were orally administered the fraction at a dose of 5 mg/kg body weight. The halocynthiaxanthin levels in the plasma, liver, and small intestine, were quantified using HPLC-PDA, 1, 3, 6, and 9 h after ingestion. The halocynthiaxanthin-rich fraction mainly consisted of the all-trans form and a small amount of cis forms. These three isomers were detected in the plasma of mice 3 h after ingestion. Time-course changes after the ingestion of this fraction were found, with cis isomers being more abundant than the all-trans isomer in the mouse plasma and liver. In the small intestine, however, the all-trans isomer was primarily detected. The possibility that cis isomers might be absorbed rapidly from the small intestine cannot be denied, but our results suggest that dietary all-trans-halocynthiaxanthin might be isomerized to the cis isomer after intestinal absorption.     

黑木耳功能性成分及其干燥技术研究进展

本文综述了黑木耳功能性成分以及干燥技术的研究进展，以期为黑木耳干燥技术的选取、应用和黑木耳产品开发的方向提供更多的参考。     

稻瘟病菌F-box蛋白MoFbr7生物学功能分析

F-box蛋白在泛素-蛋白酶体途径(ubiquitin-proteasome pathway,UPP)中参与调控胞内蛋白降解、受体识别、信号传导等生物学过程。本研究从稻瘟病菌中克隆了F-box基因MoFbr7,序列分析表明,该基因编码产物具有1个F-box结构域(N-端)和8个连续的WD40重复序列(C-端),在丝状真菌中高度保守。利用基因敲除方法,获得4个MoFbr7基因敲除突变体,同时构建了回补菌株。表型分析结果显示,MoFbr7基因缺失突变体在产孢量、附着胞形态、原生质体释放、致病性等方面均无异常。突变体在MM、RDC培养基上生长速率下降;对细胞壁胁迫因子CFW(Calcofluor white)、刚果红敏感。以上结果表明MoFbr7参与稻瘟病菌的营养生长与细胞壁完整性,为进一步揭示其生物学功能奠定基础。     

Allometric Estimates of Aboveground Biomass Using Cover and Height Are Improved by Increasing Specificity of Plant Functional Groups in Eastern Australian Rangelands

Plant aboveground biomass (AGB) is a useful metric to assess ecosystem functioning, and its sensitivity to changing environmental conditions provides insight into potential global change impacts. Allometric estimates of AGB using vegetation characteristics such as plant cover or height provide nondestructive biomass proxies for repeated measurements but can introduce uncertainty to estimates. We estimated the relationship between both plant cover and a cover·height index and AGB for 15 plant species from six sites to identify the most reliable approach to estimate biomass nondestructively in semiarid eastern Australian rangelands. Estimates were made by grouping species at four different levels of specificity, to test whether generic estimates were more robust than grouping species based on life history and morphological characteristics. Estimates were then tested on a 1.5-m² plot at each site for validation. In all cases, models were highly significant (P < 0.001) with adjusted R² values ranging from 0.42 to 0.96 for cover models and 0.38 to 0.98 for cover·height index models. We found the addition of height improved model fits in four groups while reducing model fits in two groups. The error around AGB estimates for cover·height index−based models ranged from −66.8 to 4% (absolute mean 35%). Cover-based models had errors between −13.4% and 53% (absolute mean 14.2%). For cover-based estimates of AGB in validation plots, grouping plants by plant functional types (PFTs) increased accuracy (absolute mean error 17.3%) compared with estimates using data from all 15 species (absolute mean of 65.2%). Overall cover was a useful surrogate to estimate AGB (with the exception of one site, accuracy ranged from −2.3% to 11.5%), while height (thought to be a surrogate for canopy characteristics) provided benefit in a few circumstances. We suggest that future research should test additional nondestructive proxies and group species based on PFTs to improve AGB estimates using allometry.