The first optic ganglion of the bee

Summary The arrangement of first and second order neurons in an optic cartridge and the topographical relationships of the second order neurons within a cartridge and to groups of surrounding cartridges have been analyzed in the visual system of the bee, Apis mellifera, from light and electron microscope studies on Golgi preparations. At the level of the monopolar cell body layer, the nine retinula cell fibres of each ommatidium, the six short visual fibres arranged in a circle surrounding the three long visual fibres, become cartridges as a consequence of the appearance of the second order neurons (L-fibres) which join the R-fibre bundles. Two of the four different L-fibre types, L-1 and L-2, remain together in the centre of the cartridge throughout the lamina. The axons of the L-3 and L-4 fibres, however, have their position integrated into the circle formed by the endings of the short visual fibres. On the basis of further examination of light and especially electron microscopical Golgi material, the different L-fibres can be classified into four types which appear in each cartridge. The clear stratification in the first synaptic region (A, B and C) seems to be the best criterion for a morphological classification since such a classification necessarily also includes a functional basis. According to a naming system based on the position of the lateral processes, L-fibres with side branches in strata A, B and C are called L-1 fibres. Fibres with lateral processes in strata A and B are L-2 fibres; monopolar cell fibres with branches only in the second stratum B are L-fibres of type 3; and all monopolar cells with branches only in stratum C are called L-4 fibres. In addition to the branching pattern covering only the parent cartridge, two of the four fibre types (L-2 and L-4) have long collaterals reaching neighbouring cartridges: L-2 in stratum A and L-4 in stratum C. These collaterals presumably form a substrate for lateral interactions.     

Predicting the unexpected: using a qualitative model of a New Zealand dryland ecosystem to anticipate pest management outcomes

Pest management is expensive and there is often uncertainty about the benefits for the resources being protected. There can also be unintended consequences for other parts of the ecosystem, especially in complex food webs. In making decisions managers generally have to rely on qualitative information collected in a piecemeal fashion. A method to assist decision making is a qualitative modelling approach using fuzzy cognitive maps, a directed graphical model related to neural networks that can take account of interactions between pests and conservation assets in complex food webs. Using all available information on relationships between native and exotic resources and consumers, we generated hypotheses about potential consequences of single‐species and multi‐species pest control on the long‐term equilibrium abundances of other biotic components of an ecosystem. We applied the model to a dryland ecosystem in New Zealand because we had good information on its trophic structure, but the information on the strength of species interactions was imprecise. Our model suggested that pest control is unlikely to significantly boost native invertebrates and lizards in this ecosystem, suggesting that other forms of management may be required for these groups. Most of the pest control regimes tested resulted in greater abundances of at least one other pest species, which could potentially lead to other management problems. Some of the predictions were unexpected, such as more birds resulting from possum and mouse control. We also modelled the effects of an increase in invasive rabbits, which led to unexpected declines of stoats, weasels, mice and possums. These unexpected outcomes resulted from complex indirect pathways in the food web. Fuzzy cognitive maps allow rapid construction of prototype models of complex food webs using a wide range of data and expert opinion. Their utility lies in providing direction for future monitoring efforts and generating hypotheses that can be tested with field experiments.     

最大等速离心运动诱发肌肉损伤程度与肌酸激酶水平的关系

为探讨人体进行最大等速离心运动(ECC)诱发血液肌酸激酶(CK)水平变化、血清肌酸激酶水平与肌肉损伤(EIMD)的关系,本研究筛选出150名"缺乏运动"的健康大学生为受试者,进行血样采集,进行前测包括血清肌酸激酶(CK)、最大等长肌力(MVC)、肘关节活动角度(ROM)、上臂围(CIR)、肌肉感受(VAS)。受试者进行5组×12次最大等速离心运动,运动后恢复期,将全部受试者血清肌酸激酶值进行排序:血清肌酸激酶值最高和最低20%样本,高肌酸激酶水平组(HCK组)和低肌酸激酶水平组(low LCK组),利用SPSS18.0统计学软件,以方差分析和多元回归分析进行统计分析。本研究发现全部受试者、高肌酸激酶水平组、低肌酸激酶水平组在最大等速离心运动后各评估指标均显著高于比前测结果,p<0.05。全部受试者、高肌酸激酶水平组受试者在最大等速离心运动后各指标变化皆明显大于低肌酸激酶水平组受试者,p<0.05。受试者血清肌酸激酶峰值与最大等长肌力、肘关节活动角度、上臂围、肌肉感受最大变化值有相关,p<0.05。本研究认为肌肉损伤程度与肌酸激酶水平具有显著相关,尤其高血清肌酸激酶水平者肌酸激酶水平较大程度反映肌肉损伤程度趋势。本研究表明,肘关节活动角度、上臂围具有预测肌酸激酶峰值的效果。     

玉米茎秆强度形成与木质素积累关系的研究

为探究玉米基部节间质量性状与茎秆强度形成的内在关系,该研究选用不同耐密性玉米品种为材料,采用随机区组设计,在田间条件下研究玉米基部节间形态特征、干物质积累的变化特点,分析茎秆内部木质素积累动态变化及其相关合成酶活性对茎秆强度形成的影响。结果表明：(1)耐密品种‘先玉335’基部节间单位长度干重(DWUL)和直径均较高,不同品种的茎秆强度快速形成时期有一定差异,与木质素的积累密切相关。(2)耐密品种茎秆穿刺强度(RPS)和木质素积累快速形成时期较不耐密品种‘新玉41’长5~7 d,穿刺强度高于不耐密品种24.9%~36.6%,其木质素积累量高于不耐密品种12.5%~47.0%,且RPS和木质素积累速率较不耐密品种快。(3)玉米抽雄期(VT)前是基部节间木质素快速积累的关键时期,玉米大喇叭口期(V12~V15)酶活性与抽雄期木质素积累量呈显著或极显著正相关,对茎秆强度形成至关重要。(4)在玉米12叶期耐密品种‘先玉335’的木质素合成相关酶均显著高于不耐密品种‘新玉41’,PAL、TAL、CAD和POD分别较‘新玉41’高1.85、0.30、0.11和0.42 U·mg^-1。研究认为,玉米大喇叭口期茎秆干物质积累量较高、木质素合成相关酶的活性较强,能有效促进木质素的快速积累,增加茎秆抗倒伏强度,进而提高玉米茎秆抗倒伏能力。     

Accuracy of specimen-specific nonlinear finite element analysis for evaluation of radial diaphysis strength in cadaver material

The feasibility of a user-specific finite element model for predicting the in situ strength of the radius after implantation of bone plates for open fracture reduction was established. The effect of metal artifact in CT imaging was characterized. The results were verified against biomechanical test data. Fourteen cadaveric radii were divided into two groups: (1) intact radii for evaluating the accuracy of radial diaphysis strength predictions with finite element analysis and (2) radii with a locking plate affixed for evaluating metal artifact. All bones were imaged with CT. In the plated group, radii were first imaged with the plates affixed (for simulating digital plate removal). They were then subsequently imaged with the locking plates and screws removed (actual plate removal). Fracture strength of the radius diaphysis under axial compression was predicted with a three-dimensional, specimen-specific, nonlinear finite element analysis for both the intact and plated bones (bones with and without the plate captured in the scan). Specimens were then loaded to failure using a universal testing machine to verify the actual fracture load. In the intact group, the physical and predicted fracture loads were strongly correlated. For radii with plates affixed, the physical and predicted (simulated plate removal and actual plate removal) fracture loads were strongly correlated. This study demonstrates that our specimen-specific finite element analysis can accurately predict the strength of the radial diaphysis. The metal artifact from CT imaging was shown to produce an overestimate of strength.     

Body masses,functional responses and predator–prey stability

The stability of ecological communities depends strongly on quantitative characteristics of population interactions (type‐II vs. type‐III functional responses) and the distribution of body masses across species. Until now, these two aspects have almost exclusively been treated separately leaving a substantial gap in our general understanding of food webs. We analysed a large data set of arthropod feeding rates and found that all functional‐response parameters depend on the body masses of predator and prey. Thus, we propose generalised functional responses which predict gradual shifts from type‐II predation of small predators on equally sized prey to type‐III functional‐responses of large predators on small prey. Models including these generalised functional responses predict population dynamics and persistence only depending on predator and prey body masses, and we show that these predictions are strongly supported by empirical data on forest soil food webs. These results help unravelling systematic relationships between quantitative population interactions and large‐scale community patterns.     

Differential label‐free quantitative proteomic analysis of avian eggshell matrix and uterine fluid proteins associated with eggshell mechanical property

Eggshell strength is a crucial economic trait for table egg production. During the process of eggshell formation, uncalcified eggs are bathed in uterine fluid that plays regulatory roles in eggshell calcification. In this study, a label‐free MS‐based protein quantification technology was used to detect differences in protein abundance between eggshell matrix from strong and weak eggs (shell matrix protein from strong eggshells and shell matrix protein from weak eggshells) and between the corresponding uterine fluids bathing strong and weak eggs (uterine fluid bathing strong eggs and uterine fluid bathing weak eggs) in a chicken population. Here, we reported the first global proteomic analysis of uterine fluid. A total of 577 and 466 proteins were identified in uterine fluid and eggshell matrix, respectively. Of 447 identified proteins in uterine fluid bathing strong eggs, up to 357 (80%) proteins were in common with proteins in uterine fluid bathing weak eggs. Similarly, up to 83% (328/396) of the proteins in shell matrix protein from strong eggshells were in common with the proteins in shell matrix protein from weak eggshells. The large amount of common proteins indicated that the difference in protein abundance should play essential roles in influencing eggshell strength. Ultimately, 15 proteins mainly relating to eggshell matrix specific proteins, calcium binding and transportation, protein folding and sorting, bone development or diseases, and thyroid hormone activity were considered to have closer association with the formation of strong eggshell.     

Microbes make the meal: oligolectic bees require microbes within their host pollen to thrive

1. For solitary bees that specialise on select pollen types (oligoleges), larval development depends on the availability of forage pollen from appropriate host plants and the naturally occurring microbiota present therein. While access to host pollen may be critical for the development of oligolectic bees, the extent to which pollen microbiota contribute to their brood success is unknown. 2. To investigate, we used a diet manipulation experiment to rear larvae of the oligolege, Osmia ribifloris, under in-vitro conditions. Larvae were reared either on host pollen provisioned by their mother or on non-host pollen collected by honey bees, in the presence or absence of the respective pollen-associated microbiota. We assessed impacts on components of larval fitness: developmental time, biomass, and survivorship. 3. Our results revealed a significant interaction between pollen type and pollen-associated microbes. The relative effect of microbes on larval performance was substantially greater than that of pollen type. Host pollen substrate produced the fittest larvae but only when combined with its full complement of naturally occurring microbiota. In contrast, host pollen without microbes resulted in a marked decline in fitness components. Larvae consuming non-host pollen showed intermediate fitness, regardless of whether microbes were present or not. 4. These findings imply that the microbiota associated with maternally provisioned host pollen perform critical functions in larval nutrition and survival. For oligoleges in particular, the ability to develop on poorer quality host pollen likely derives from this sustained symbiosis with their microbial exosymbionts, rather than the biochemical characteristics of pollen type alone.     

Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data

Accurate prognostic prediction using molecular information is a challenging area of research, which is essential to develop precision medicine. In this paper, we develop translational models to identify major actionable proteins that are associated with clinical outcomes, like the survival time of patients. There are considerable statistical and computational challenges due to the large dimension of the problems. Furthermore, data are available for different tumor types; hence data integration for various tumors is desirable. Having censored survival outcomes escalates one more level of complexity in the inferential procedure. We develop Bayesian hierarchical survival models, which accommodate all the challenges mentioned here. We use the hierarchical Bayesian accelerated failure time model for survival regression. Furthermore, we assume sparse horseshoe prior distribution for the regression coefficients to identify the major proteomic drivers. We borrow strength across tumor groups by introducing a correlation structure among the prior distributions. The proposed methods have been used to analyze data from the recently curated “The Cancer Proteome Atlas” (TCPA), which contains reverse-phase protein arrays–based high-quality protein expression data as well as detailed clinical annotation, including survival times. Our simulation and the TCPA data analysis illustrate the efficacy of the proposed integrative model, which links different tumors with the correlated prior structures.