Comparison between touchscreen operant chambers and water maze to detect early prefrontal dysfunction in mice

The relative lack of sensitive and clinically valid tests of rodent behavior might be one of the reasons for the limited success of the clinical translation of preclinical Alzheimer's disease (AD) research findings. There is a general interest in innovative behavioral methodology, and protocols have been proposed for touchscreen operant chambers that might be superior to existing cognitive assessment methods. We assessed and analyzed touchscreen performance in several novel ways to examine the possible occurrence of early signs of prefrontal (PFC) functional decline in the APP/PS1 mouse model of AD. Touchscreen learning performance was compared between APP/PS1-21 mice and wildtype littermates on a C57BL/6J background at 3, 6 and 12 months of age in parallel to the assessment of spatial learning, memory and cognitive flexibility in the Morris water maze (MWM). We found that older mice generally needed more training sessions to complete the touchscreen protocol than younger ones. Older mice also displayed defects in MWM working memory performance, but touchscreen protocols detected functional changes beginning at 3 months of age. Histological changes in PFC of APP/PS1 mice indeed occurred as early as 3 months. Our results suggest that touchscreen operant protocols are more sensitive to PFC dysfunction, which is of relevance to the use of these tasks and devices in preclinical AD research and experimental pharmacology.     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.     

Home‐site fidelity and homing behavior of the big‐headed turtle Platysternon megacephalum

Site fidelity refers to the restriction of dispersal distance of an animal and its tendency to return to a stationary site. To our knowledge, the homing ability of freshwater turtles and their fidelity is reportedly very low in Asia. We examined mark–recapture data spanning a 4‐year period in Diaoluoshan National Nature Reserve, Hainan Province, China, to investigate the site fidelity and homing behavior of big‐headed turtles Platysternon megacephalum. A total of 11 big‐headed turtles were captured, and all individuals were used in this mark–recapture study. The site fidelity results showed that the adult big‐headed turtles (n = 4) had a 71.43% recapture rate in the original site after their release at the same site, whereas the juveniles (n = 1) showed lower recapture rates (0%). Moreover, the homing behavior results showed that the adults (n = 5) had an 83.33% homing rate after displacement. Adult big‐headed turtles were able to return to their initial capture sites (home) from 150 to 2,400 m away and precisely to their home sites from either upstream or downstream of their capture sites or even from other streams. However, none of the juveniles (n = 4) returned home, despite only being displaced 25–150 m away. These results indicated that the adult big‐headed turtles showed high fidelity to their home site and strong homing ability. In contrast, the juvenile turtles may show an opposite trend but further research is needed.     

The plant antifungal isoflavone genistein is metabolized by Armillaria mellea Vahl to give non-fungitoxic products

Abstract

Armillaria mellea, the causal agent of root rot, is a fungal pathogen which proved able to convert the leguminous plant antifungal compound 4′,5,7-trihydroxyisoflavone (genistein) into intermediate metabolites. After suitable periods of incubation, the metabolites were extracted and concentrated from liquid culture media, containing both the isoflavone and the fungus. After purification by column chromatography, the molecular structure of the metabolites was determined by means of mass spectrometry and nuclear magnetic resonance analyses. Five different compounds were identified: 1,3,5-trihydroxybenzene, 4-hydroxyphenylacetic acid, 2,5-dihydroxyphenylacetic acid (homogentisic acid), its lactone 5-hydroxy-2(3H)-benzofuranone, and 1,4-benzoquinone. In vitro experiments showed that while the starting compound, i.e. genistein, has some activity in inhibiting the growth of the fungal pathogen, the degradation products are devoid of any appreciable fungitoxic activity. Moreover, results show that the isoflavone metabolites can be, at least partially, utilized by A. mellea as a carbon source.     

Study of naïve and memory cells in a cohort of Egyptian chronic granulomatous disease patients

Abstract

Context: Chronic granulomatous disease (CGD) is a primary immunodeficiency disorder caused by inherited defects in the NADPH oxidase complex which may be involved in important pathways that connect innate and adaptive immunity. Objectives: Characterize the naive and memory compartment of B and T lymphocytes in patients with CGD. Methods: Twenty CGD patients and twenty healthy controls matched for age and sex were enrolled in this study. Flow cytometric assessment of the naïve and memory compartments of peripheral blood lymphocytes was done using cell surface markers CD45RO, CD45RA, CD27, CD3 and CD19. Results: There were 15 (79%) autosomal recessive CGD patients (8 females (53%) and 7 males (47%), 100% positive parental consanguinity) and four (21%) X-linked CGD patients. On comparing the 3 groups; AR CGD, X-linked CGD and controls, there was a positive statistical significant difference for the percentage and absolute count of CD19?+?CD27+ memory B cell (p?=?0.028 and p?=?0.047 respectively), CD45RA cells (with p values of p?=?0.000 and 0.033, respectively), the naïve compartment CD3?+?CD45RA+ cells percentage and absolute counts (p?=?0.005, 0.01respectively), CD3?+?CD27?+?cells percentage and absolute counts (p?=?0.001, 0.012 respectively), CD3?+?CD45RA?+?CD27+ cells percentage and absolute counts (p?=?0.015, 0.005, respectively). The significance was mainly attributed to the decrease in the X-linked group than control group. Conclusion: There was an altered naïve and memory B profile in CGD patients, this may increase susceptibility of the patients to opportunistic infections and autoimmune disorders. T-cell alterations have to be interpreted cautiously especially in the presence of infections.     

Sequencing of the Dutch Elm Disease Fungus Genome Using the Roche/454 GS-FLX Titanium System in a Comparison of Multiple Genomics Core Facilities

As part of the DNA Sequencing Research Group of the Association of Biomolecular Resource Facilities, we have tested the reproducibility of the Roche/454 GS-FLX Titanium System at five core facilities. Experience with the Roche/454 system ranged from <10 to >340 sequencing runs performed. All participating sites were supplied with an aliquot of a common DNA preparation and were requested to conduct sequencing at a common loading condition. The evaluation of sequencing yield and accuracy metrics was assessed at a single site. The study was conducted using a laboratory strain of the Dutch elm disease fungus Ophiostoma novo-ulmi strain H327, an ascomycete, vegetatively haploid fungus with an estimated genome size of 30–50 Mb. We show that the Titanium System is reproducible, with some variation detected in loading conditions, sequencing yield, and homopolymer length accuracy. We demonstrate that reads shorter than the theoretical minimum length are of lower overall quality and not simply truncated reads. The O. novo-ulmi H327 genome assembly is 31.8 Mb and is comprised of eight chromosome-length linear scaffolds, a circular mitochondrial conti of 66.4 kb, and a putative 4.2-kb linear plasmid. We estimate that the nuclear genome encodes 8613 protein coding genes, and the mitochondrion encodes 15 genes and 26 tRNAs.     

Impacts of 3 years of elevated atmospheric CO2 on rhizosphere carbon flow and microbial community dynamics

Carbon (C) uptake by terrestrial ecosystems represents an important option for partially mitigating anthropogenic CO₂ emissions. Short‐term atmospheric elevated CO₂ exposure has been shown to create major shifts in C flow routes and diversity of the active soil‐borne microbial community. Long‐term increases in CO₂ have been hypothesized to have subtle effects due to the potential adaptation of soil microorganism to the increased flow of organic C. Here, we studied the effects of prolonged elevated atmospheric CO₂ exposure on microbial C flow and microbial communities in the rhizosphere. Carex arenaria (a nonmycorrhizal plant species) and Festuca rubra (a mycorrhizal plant species) were grown at defined atmospheric conditions differing in CO₂ concentration (350 and 700 ppm) for 3 years. During this period, C flow was assessed repeatedly (after 6 months, 1, 2, and 3 years) by ¹³C pulse‐chase experiments, and label was tracked through the rhizosphere bacterial, general fungal, and arbuscular mycorrhizal fungal (AMF) communities. Fatty acid biomarker analyses and RNA‐stable isotope probing (RNA‐SIP), in combination with real‐time PCR and PCR‐DGGE, were used to examine microbial community dynamics and abundance. Throughout the experiment the influence of elevated CO₂ was highly plant dependent, with the mycorrhizal plant exerting a greater influence on both bacterial and fungal communities. Biomarker data confirmed that rhizodeposited C was first processed by AMF and subsequently transferred to bacterial and fungal communities in the rhizosphere soil. Over the course of 3 years, elevated CO₂ caused a continuous increase in the ¹³C enrichment retained in AMF and an increasing delay in the transfer of C to the bacterial community. These results show that, not only do elevated atmospheric CO₂ conditions induce changes in rhizosphere C flow and dynamics but also continue to develop over multiple seasons, thereby affecting terrestrial ecosystems C utilization processes.     

Variation in hippocampal glial cell numbers in food‐caching birds from different climates

Enhancements to memory are associated with enhanced neural structures that support those capabilities. A great deal of work has examined this relationship in the context of natural variation in spatial memory capability and hippocampal (Hp) structure. Most studies have focused on volumetric and neuron measures, but have seldom examined the role of glial cells. Once considered involved only in supportive functions associated with neurons, the importance of glial cells in cognitive processes, including memory, is gaining more attention. Building upon our previous study on the relationship between the brain, memory, and environmental severity in food‐caching birds, we compared the total number of Hp glial cells in wild‐sampled and in lab‐reared (common garden) black‐capped chickadees (Poecile atricapillus) originating from two different environmental extremes. We found that birds from more harsh climate tended to have significantly more Hp glial cells than those from more mild climate and that lab‐reared chickadees had significantly fewer Hp glial cells compared to the wild‐sampled birds. These results suggest that population differences in glial numbers may be controlled, at least in part, by heritable mechanisms, but glial numbers appear to be additionally regulated by an individual's environment. The pattern of Hp glial cell abundance among our treatment groups closely followed that of the Hp volume, suggesting that Hp glial cell number may be associated with the Hp volume. Unlike Hp neurons, however, the number of Hp glial cells may be, at least in part, affected by an individual's experiences and environment. © 2013 Wiley Periodicals, Inc. Develop Neurobiol 73: 480–485, 2013     

Automated analysis of courtship suppression learning and memory in Drosophila melanogaster

Study of the fruit fly, Drosophila melanogaster, has yielded important insights into the underlying molecular mechanisms of learning and memory. Courtship conditioning is a well-established behavioral assay used to study Drosophila learning and memory. Here, we describe the development of software to analyze courtship suppression assay data that correctly identifies normal or abnormal learning and memory traits of individual flies. Development of this automated analysis software will significantly enhance our ability to use this assay in large-scale genetic screens and disease modeling. The software increases the consistency, objectivity, and types of data generated.     

A Zebrafish Model of Diabetes Mellitus and Metabolic Memory

Diabetes mellitus currently affects 346 million individuals and this is projected to increase to 400 million by 2030. Evidence from both the laboratory and large scale clinical trials has revealed that diabetic complications progress unimpeded via the phenomenon of metabolic memory even when glycemic control is pharmaceutically achieved. Gene expression can be stably altered through epigenetic changes which not only allow cells and organisms to quickly respond to changing environmental stimuli but also confer the ability of the cell to "memorize" these encounters once the stimulus is removed. As such, the roles that these mechanisms play in the metabolic memory phenomenon are currently being examined.We have recently reported the development of a zebrafish model of type I diabetes mellitus and characterized this model to show that diabetic zebrafish not only display the known secondary complications including the changes associated with diabetic retinopathy, diabetic nephropathy and impaired wound healing but also exhibit impaired caudal fin regeneration. This model is unique in that the zebrafish is capable to regenerate its damaged pancreas and restore a euglycemic state similar to what would be expected in post-transplant human patients. Moreover, multiple rounds of caudal fin amputation allow for the separation and study of pure epigenetic effects in an in vivo system without potential complicating factors from the previous diabetic state. Although euglycemia is achieved following pancreatic regeneration, the diabetic secondary complication of fin regeneration and skin wound healing persists indefinitely. In the case of impaired fin regeneration, this pathology is retained even after multiple rounds of fin regeneration in the daughter fin tissues. These observations point to an underlying epigenetic process existing in the metabolic memory state. Here we present the methods needed to successfully generate the diabetic and metabolic memory groups of fish and discuss the advantages of this model.