Photic and circadian regulation of self-feeding activity in ayu

ABSTRACT:   The self-feeding rhythms of ayu Plecoglossus altivelis altivelis were examined. Individual ayu (mean body weight 40 g) were held in 60-L glass tanks equipped with self-feeders. Six of 14 fish learned self-feeding during the experiment. Under two different light–dark (LD) conditions (16 h:8 h and 8 h:16 h LD), self-feeding was synchronized to the LD cycle, and feeding occurred almost exclusively during the light phase. During exposure to constant light (LL), circadian feeding rhythms were observed. These results indicate self-feeding rhythms in ayu are restricted to the light phase under LD conditions and are controlled by the circadian clock under LL conditions.     

Using automated monitoring systems to uncover pest population dynamics in agricultural fields

Understanding pest population dynamics is an essential part of pest management programs, but the examination of field pest populations faces many logistical difficulties. Consequently, potentially useful characteristics of pest ecology that can be utilized in the development of pest control strategies are yet to be discovered. In this study, we used an automated pest monitoring system to study a population of the oriental fruit fly and revealed its intriguing population dynamics in the field. The system automatically counts the number of flies captured by traps, and the real-time data are accessible anywhere using the Internet. Data from two time periods (May–June and July–August) were analyzed. Autocorrelation analysis indicated that there was a statistically significant population cycle in May and June, but the population was stationary in July and August. Partial rate correlation analysis and an associated functional analysis revealed the existence of delayed density-dependence that differed between the two periods. These results suggest that the mechanism of population dynamics may change possibly within a short time frame. These patterns were revealed because of the detailed data that were made available by the monitoring system and were unknown prior to the study. The automated monitoring system will be highly valuable for the advancement of pest monitoring and pest management programs.     

Can stumps tell what people want: Pattern and preference of informal wood extraction in an urban forest of Nairobi, Kenya

Detailed patterns and preferences of informal wood extraction were investigated in an urban forest used by slum inhabitants of Nairobi, Kenya, as such information determines the sustainability of resource use. Instead of asking the people what they had secretly cut, a survey was conducted of the stumps and trees left in the forest to (i) evaluate how accessibility and patrolling affected spatial patterns of resource use, and to (ii) estimate a broad spectrum of species and species-specific size preferences. Both probability and size of cutting increased with better accessibility (represented by distance from the slum), and stump size exceeded that of living stem size around 1.7 km from the slum, which suggested magnified impact of tree cutting near the slum. Patrolling (represented by distance from ranger stations) had little effect in reducing the probability of cutting but was effective in reducing cut size. With the use of random effect models, a broad species preference spectrum (including less abundant and non-preferred species) was estimated, which indicated trends in vegetation change. Smaller stems were preferred for most species presumably used for domestic fuelwood, but major exploitation of large Brachylaena huillensis stems traded in the woodcarving industry was also revealed. Such detailed information on informal wood use can help forest managers to understand threats to the forests as well as the needs of local communities. This is a first step to redefining ‘acceptable’ resource use by the local community for their increased role and responsibility in sustainable forest management, especially when conventional controls of informal activities (i.e. exclusion and penalty) are not functioning well.     

Evaluation of serum and urine 1,5-anhydro-D-glucitol and myo-inositol concentrations in healthy dogs

1,5-anhydro-D-glucitol (1,5AG) is a pyranoid polyol compound found in human circulating blood. Myo-inositol (MI) is a stereoisomer of inositol and serves as a precursor of inositol phospholipids. 1,5AG and MI are filtered by the glomerulus and almost completely reabsorbed through the renal tubules. However, under hyperglycemic conditions, reabsorption through the renal tubules is competitively inhibited because the structures of 1,5AG and MI resemble that of glucose. In this study, we investigated the kinetics of serum and urine 1,5AG and MI levels in healthy dogs. We demonstrated that 1,5AG and MI exist in canine serum and urine by gas chromatography-mass spectrometry. Under continuous hyperglycemic conditions, the serum 1,5AG concentration in healthy dogs decreased while the serum MI concentration remained unchanged. Urinary excretion of 1,5AG and MI increased significantly after blood glucose concentrations reached 200 to 220 mg/dl. A significant negative correlation was observed between serum 1,5AG and glucose concentrations during hyperglycemia. However, no significant correlation was observed between serum MI and glucose concentrations. In this study, we demonstrated that serum and urine 1,5AG and MI levels were changed by blood glucose concentrations. The serum 1,5AG concentration was decreased by continuous hyperglycemia. However, the serum MI concentration does not reflect hyperglycemia.     

Applicability of a progesterone-based timed artificilal insemination protocol after follicular fluid aspiration using the ovum pick-up technique in suckled beef cows

We conducted a progesterone-based timed AI protocol after follicular fluid aspiration using the ovum pick-up (OPU) technique to examine its applicability to the suckled beef cow. A total of 19 beef cows were randomly allocated to one of the following three groups based on the number of days postpartum: 13 to 60 days (Group A: suckled; early postpartum period, n=9), 61 to 150 days (Group B: suckled; mid postpartum period, n=6), or 151 to 281 days (Group C: non-suckled; prolonged open period, n=4) postpartum. These cows were treated with follicular fluid aspiration and insertion of a progesterone-releasing intravaginal device (PRID) on day 0. The PRID was removed and 500 microg of cloprostenol was intramuscularly administered on day 7. A dose (100 microg) of fertirelin acetate was injected intramuscularly 48 hours later, and this was followed by a timed AI (TAI) after another 18 hours (day 10). Serum samples were taken on days 0, 7, 9, 10, 12, 17, 24 and 31 for determination of the estradiol-17beta (E(2)) and progesterone concentrations. Pregnancy diagnosis was made by rectal palpation approximately 60 days after TAI. There was no significant difference in the peripheral E(2) concentrations among the three groups during the period of the hormonal treatment. The average progesterone concentrations in Group A on day 17 were significantly higher than those in Group B and exceeded 1.0 ng/ml on day 17 and thereafter. There was no significant difference in the numbers of collected immature oocytes among the three groups. The pregnancy rates in Groups A, B, and C were 77.8% (7/9), 83.3% (5/6) and 50.0% (2/4), respectively. In conclusion, this timed AI protocol is applicable to suckled beef cows within the period of 60 days postpartum.     

Histopathological evaluation of the ocular-irritation potential of shampoos,make-up removers and cleansing foams in the bovine corneal opacity and permeability assay

The bovine corneal opacity and permeability (BCOP) assay is an alternative method to the in vivo Draize eye test in rabbits for evaluating eye irritation in vitro. Here, we compared the numerical results of the BCOP assay with the corresponding histopathology for three different corneas for each test substance, including commercially available shampoos, make-up removers and cleansing foams that contained surfactants and other ingredients. The histopathological score was defined based on the severity of lesions in the corneal epithelium. The histopathological findings and scores of the three sections for each test substance were comparable. The in vitro irritancy score (IVIS) generally corresponds to the corneal irritant potential of the test substances assigned on the basis of the histopathological findings in this study. In the present study, we characterized the histopathology of the corneal epithelium and stroma and especially showed that the corneal epithelial injury caused by test substances might be important in assessment of test substances that are mild eye irritants (category 2B) as classified by the United Nations (UN) Globally Harmonized System of Classification and Labelling of Chemicals (GHS), as corneal lesions suggestive of classification into category 2B were localized on the border between the corneal epithelium and stroma, which contained cell elements related to assessment of prognosis of an in vivo eye injury. Histopathological assessment might be useful in predicting in vivo ocular irritation, particularly for test substances with an IVIS >3.1 but ≤25 that are classified as mild irritants (category 2B) according to the UN GHS.     

Three-layered Feedforward artificial neural network with dropout for short-term prediction of class-differentiated Chl-a based on weekly water-quality observations in a eutrophic agricultural reservoir

To effectively manage a eutrophic reservoir, short-term predictions of algae class-differentiated chlorophyll a (Chl-a) were conducted. The study adopted a three-layered feedforward artificial neural network using discrete water environment datasets collected through weekly observations from May to November over seven years (2012–2018). This network was constructed using supervised learning, and the available datasets of a certain observation day were set as the input variables to determine the total Chl-a, Chlorophyceae Chl-a, and cyanobacteria Chl-a that would exist after one week. From the viewpoint of the simplification of the network’s complexity to suppress overfitting, input variables were carefully selected by identifying the important variables related to the seasonal changes in Chlorophyceae and cyanobacteria and eliminating the duplicated expressions of water-quality parameters. However, network downsizing was found insufficient to suppress overfitting. To improve prediction accuracy, dropout was introduced, which stochastically deactivated some nodes in the input and hidden layers in the learning process. The analysis results showed that sufficient short-term predictions of total Chl-a and Chlorophyceae Chl-a may be achieved. The insufficient prediction accuracy of cyanobacteria Chl-a may be overcome using meteorological data as close as possible to the desired prediction day. Consequently, this model may serve as a useful tool for the management of eutrophic reservoirs because short-term predictions of the dominant phytoplankton can be achieved, and the necessary mitigation measures may be accordingly planned.