Mathematical modeling of the Drosophila neuromuscular junction

Poster presentation: An important challenge in neuroscience is understanding how networks of neurons go about processing information. Synapses are thought to play an essential role in cellular information processing however quantitative and mathematical models of the underlying physiologic processes that occur at synaptic active zones are lacking. We are generating mathematical models of synaptic vesicle dynamics at a well-characterized model synapse, the Drosophila larval neuromuscular junction. This synapse's simplicity, accessibility to various electrophysiological recording and imaging techniques, and the genetic malleability intrinsic to Drosophila system make it ideal for computational and mathematical studies. We have employed a reductionist approach and started by modeling single presynaptic boutons. Synaptic vesicles can be divided into different pools; however, a quantitative understanding of their dynamics at the Drosophila neuromuscular junction is lacking [4]. We performed biologically realistic simulations of high and low release probability boutons [3] using partial differential equations (PDE) taking into account not only the evolution in time but also the spatial structure in two dimensions (the extension to three dimensions will be implemented soon). PDEs are solved using UG, a program library for the calculation of multi-dimensional PDEs solved using a finite volume approach and implicit time stepping methods leading to extended linear equation systems be solvedwith multi-grid methods [3,4]. Numerical calculations are done on multi-processor computers for fast calculations using different parameters in order to asses the biological feasibility of different models. In preliminary simulations, we modeled vesicle dynamics as a diffusion process describing exocytosis as Neumann streams at synaptic active zones. The initial results obtained with these models are consistent with experimental data. However, this should be regarded as a work in progress. Further refinements will be implemented, including simulations using morphologically realistic geometries which were generated from confocal scans of the neuromuscular junction using NeuRA (a Neuron Reconstruction Algorithm). Other parameters such as glutamate diffusion and reuptake dynamics, as well as postsynaptic receptor kinetics will be incorporated as well

Synaptic boutons sizes are tuned to best fit their physiological performances

To truly appreciate the myriad of events which relate synaptic function and vesicle dynamics, simulations should be done in a spatially realistic environment. This holds true in particular in order to explain as well the rather astonishing motor patterns which we observed within in vivo recordings which underlie peristaltic contractionsas well as the shape of the EPSPs at different forms of long-term stimulation, presented both here, at a well characterized synapse, the neuromuscular junction (NMJ) of the Drosophila larva (c.f. Figure 1). To this end, we have employed a reductionist approach and generated three dimensional models of single presynaptic boutons at the Drosophila larval NMJ. Vesicle dynamics are described by diffusion-like partial differential equations which are solved numerically on unstructured grids using the uG platform. In our model we varied parameters such as bouton-size, vesicle output probability (Po), stimulation frequency and number of synapses, to observe how altering these parameters effected bouton function. Hence we demonstrate that the morphologic and physiologic specialization maybe a convergent evolutionary adaptation to regulate the trade off between sustained, low output, and short term, high output, synaptic signals. There seems to be a biologically meaningful explanation for the co-existence of the two different bouton types as previously observed at the NMJ (characterized especially by the relation between size and Po), the assigning of two different tasks with respect to short- and long-time behaviour could allow for an optimized interplay of different synapse types. We can present astonishing similar results of experimental and simulation data which could be gained in particular without any data fitting, however based only on biophysical values which could be taken from different experimental results. As a side product, we demonstrate how advanced methods from numerical mathematics could help in future to resolve also other difficult experimental neurobiological issues

Synaptic bouton sizes are tuned to best fit their physiological performances : poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011, Stockholm, Sweden, 23 - 28 July 2011

Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. To truly appreciate the myriad of events which relate synaptic function and vesicle dynamics, simulations should be done in a spatially realistic environment. This holds true in particular in order to explain the rather astonishing motor patterns presented here which we observed within in vivo recordings which underlie peristaltic contractions at a well characterized synapse, the neuromuscular junction (NMJ) of the Drosophila larva. To this end, we have employed a reductionist approach and generated three dimensional models of single presynaptic boutons at the Drosophila larval NMJ. Vesicle dynamics are described by diffusion-like partial differential equations which are solved numerically on unstructured grids using the uG platform. In our model we varied parameters such as bouton-size, vesicle output probability (Po), stimulation frequency and number of synapses, to observe how altering these parameters effected bouton function. Hence we demonstrate that the morphologic and physiologic specialization maybe a convergent evolutionary adaptation to regulate the trade off between sustained, low output, and short term, high output, synaptic signals. There seems to be a biologically meaningful explanation for the co-existence of the two different bouton types as previously observed at the NMJ (characterized especially by the relation between size and Po),the assigning of two different tasks with respect to short- and long-time behaviour could allow for an optimized interplay of different synapse types. As a side product, we demonstrate how advanced methods from numerical mathematics could help in future to resolve also other difficult experimental neurobiological issues

Absence of Brca2 causes genome instability by chromosome breakage and loss associated with centrosome amplification

AbstractWomen heterozygous for mutations in the breast-cancer susceptibility genes BRCA1 and BRCA2 have a highly elevated risk of developing breast cancer [1]. BRCA1 and BRCA2 encode large proteins with no sequence similarity to one another. Although involvement in DNA repair and transcription has been suggested, it is still not understood how loss of function of these genes leads to breast cancer [2]. Embryonic fibroblasts (MEFs) derived from mice homozygous for a hypomorphic mutation (Brca2Tr2014) within the 3′ region of exon 11 in Brca2[3], or a similar mutation (Brca2Tr) [4], proliferate poorly in culture and overexpress the tumour suppressor p53 and the cyclin-dependent kinase inhibitor p21Waf1/Cip1. These MEFs have intact p53-dependent DNA damage G1–S [3,4] and G2–M checkpoints [4], but are impaired in DNA double-strand break repair [3] and develop chromosome aberrations [4]. Here, we report that Brca2Tr2014/Tr2014 MEFs frequently develop micronuclei. These abnormal DNA-containing bodies were formed through both loss of acentric chromosome fragments and by chromosome missegregation, which resulted in aneuploidy. Absence of Brca2 also led to centrosome amplification, which we found associated with the formation of micronuclei. These data suggest a potential mechanism whereby loss of BRCA2 may, within subclones, drive the loss of cell-cycle regulation genes, enabling proliferation and tumourigenesis

A High-Resolution Atlas of Uranium-Neon in the H Band

We present a high-resolution (R ~ 50 000) atlas of a uranium-neon (U/Ne) hollow-cathode spectrum in the H-band (1454 nm to 1638 nm) for the calibration of near-infrared spectrographs. We obtained this U/Ne spectrum simultaneously with a laser-frequency comb spectrum, which we used to provide a first-order calibration to the U/Ne spectrum. We then calibrated the U/Ne spectrum using the recently-published uranium line list of Redman et al. (2011), which is derived from high-resolution Fourier transform spectrometer measurements. These two independent calibrations allowed us to easily identify emission lines in the hollow cathode lamp that do not correspond to known (classified) lines of either uranium or neon, and to compare the achievable precision of each source. Our frequency comb precision was limited by modal noise and detector effects, while the U/Ne precision was limited primarily by the signal-to-noise ratio (S/N) of the observed emission lines and our ability to model blended lines. The standard deviation in the dispersion solution residuals from the S/N-limited U/Ne hollow cathode lamp were 50% larger than the standard deviation of the dispersion solution residuals from the modal-noise-limited laser frequency comb. We advocate the use of U/Ne lamps for precision calibration of near-infrared spectrographs, and this H-band atlas makes these lamps significantly easier to use for wavelength calibration.Comment: 23 pages, 7 figures, submitted and accepted in ApJSS. Online-only material to be published online by ApJS

Ant Community Structure in Secondary Logged Forest of Malua Forest Reserve, Sabah, Borneo

Ants are ecologically dominant and important in the functioning of an ecosystem. Thus, understanding their community structure has become fundamental in ecological studies. This study aims to examine the ant richness, abundance, and composition in the secondary logged forests of Sabah, Malaysia. Ground-based fogging was employed to collect canopy ants (n=38) and Winkler extraction method for leaf litter ants (n=63). A total of 12,810 ant individuals were collected, representing 389 morphospecies, 65 genera, and 11 subfamilies. The most species-rich subfamily for canopy and leaf litter ants were Formicinae (112 morphospecies, 49.34%) and Myrmicinae (116 morphospecies, 58.00%) respectively. Polyrhachis (56 morphospecies, 24.67%) was the most diverse genera in the canopy, while Pheidole (23 morphospecies, 11.50%) was the most speciose genera on the leaf litter. The most abundant species for canopy and leaf litter ants were Dolichoderus 1 (876 individuals) and Carebara 2 (1,215 individuals) respectively. The randomized species accumulation curves and species richness estimators reveal that additional sampling is required. We suggest that incorporating a variety of ant sampling methods and high sampling efforts are important to thoroughly sample the ant assemblage in an area

Synaptic bouton sizes are tuned to best fit their physiological performances

Poster presentation from Twentieth Annual Computational Neuroscience Meeting: CNS*2011 Stockholm, Sweden. 23-28 July 2011. To truly appreciate the myriad of events which relate synaptic function and vesicle dynamics, simulations should be done in a spatially realistic environment. This holds true in particular in order to explain the rather astonishing motor patterns presented here which we observed within in vivo recordings which underlie peristaltic contractions at a well characterized synapse, the neuromuscular junction (NMJ) of the Drosophila larva. To this end, we have employed a reductionist approach and generated three dimensional models of single presynaptic boutons at the Drosophila larval NMJ. Vesicle dynamics are described by diffusion-like partial differential equations which are solved numerically on unstructured grids using the uG platform. In our model we varied parameters such as bouton-size, vesicle output probability (Po), stimulation frequency and number of synapses, to observe how altering these parameters effected bouton function. Hence we demonstrate that the morphologic and physiologic specialization maybe a convergent evolutionary adaptation to regulate the trade off between sustained, low output, and short term, high output, synaptic signals. There seems to be a biologically meaningful explanation for the co-existence of the two different bouton types as previously observed at the NMJ (characterized especially by the relation between size and Po),the assigning of two different tasks with respect to short- and long-time behaviour could allow for an optimized interplay of different synapse types. As a side product, we demonstrate how advanced methods from numerical mathematics could help in future to resolve also other difficult experimental neurobiological issues

High-resolution age modelling of peat bogs from northern Alberta, Canada, using pre- and post-bomb 14 C, 210 Pb and historical cryptotephra

High-resolution studies of peat profiles are frequently undertaken to investigate natural and anthropogenic disturbances over time. However, overlapping profiles of the most commonly applied age-dating techniques, including 14C and 210Pb, often show significant offsets (>decadal) and biases that can be difficult to resolve. Here we investigate variations in the chronometers and individual site histories from six ombrotrophic peat bogs in central and northern Alberta. Dates produced using pre- and post-bomb 14C, 210Pb (corroborated with 137Cs and 241Am), and cryptotephra peaks, are compared and then integrated using OxCal's P_Sequence function to produce a single Bayesian age model. Environmental histories for each site obtained using physical and chemical characteristics of the peat cores, e.g. plant macrofossils, humification, ash content and dry density, provide important constraints for the models by highlighting periods with significant changes in accumulation rate, e.g. fire events, permafrost development, and prolonged surficial drying. Despite variable environmental histories, it is possible to produce high-resolution age-depth models for each core sequence. Consistent offsets between 14C and 210Pb dates pre-1960s are seen at five of the six sites, but tephra-corrected 210Pb data can be used to produce more coherent models at three of these sites. Processes such as permafrost development and thaw, surficial drying and local fires can disrupt the normal processes by which chronological markers and environmental records are incorporated in the peat record. In consequence, applying standard dating methodologies to these records will result in even greater uncertainties and discrepancies between the different dating tools. These results show that using any single method to accurately date peat profiles where accumulation has not been uniform over time may be unreliable, but a comprehensive multi-method investigation paired with the application of Bayesian statistics can produce more robust chronologies. New cryptotephra data for the Alberta region are also reported here, including the historical Novarupta-Katmai 1912 eruption, White River Ash (East), and glass from Mt. St. Helens, Mt. Churchill, and probable Aleutian sources

A pilot study for a non-invasive system for detection of malignancy in canine subcutaneous and cutaneous masses using machine learning

IntroductionEarly diagnosis of cancer enhances treatment planning and improves prognosis. Many masses presenting to veterinary clinics are difficult to diagnose without using invasive, time-consuming, and costly tests. Our objective was to perform a preliminary proof-of-concept for the HT Vista device, a novel artificial intelligence-based thermal imaging system, developed and designed to differentiate benign from malignant, cutaneous and subcutaneous masses in dogs.MethodsForty-five dogs with a total of 69 masses were recruited. Each mass was clipped and heated by the HT Vista device. The heat emitted by the mass and its adjacent healthy tissue was automatically recorded using a built-in thermal camera. The thermal data from both areas were subsequently analyzed using an Artificial Intelligence algorithm. Cytology and/or biopsy results were later compared to the results obtained from the HT Vista system and used to train the algorithm. Validation was done using a “Leave One Out” cross-validation to determine the algorithm's performance.ResultsThe accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the system were 90%, 93%, 88%, 83%, and 95%, respectively for all masses.ConclusionWe propose that this novel system, with further development, could be used to provide a decision-support tool enabling clinicians to differentiate between benign lesions and those requiring additional diagnostics. Our study also provides a proof-of-concept for ongoing prospective trials for cancer diagnosis using advanced thermodynamics and machine learning procedures in companion dogs

FAN1 controls mismatch repair complex assembly via MLH1 retention to stabilize CAG repeat expansion in Huntington's disease.

CAG repeat expansion in the HTT gene drives Huntington's disease (HD) pathogenesis and is modulated by DNA damage repair pathways. In this context, the interaction between FAN1, a DNA-structure-specific nuclease, and MLH1, member of the DNA mismatch repair pathway (MMR), is not defined. Here, we identify a highly conserved SPYF motif at the N terminus of FAN1 that binds to MLH1. Our data support a model where FAN1 has two distinct functions to stabilize CAG repeats. On one hand, it binds MLH1 to restrict its recruitment by MSH3, thus inhibiting the assembly of a functional MMR complex that would otherwise promote CAG repeat expansion. On the other hand, it promotes accurate repair via its nuclease activity. These data highlight a potential avenue for HD therapeutics in attenuating somatic expansion