peutic protocols that would avert such failure and maximize HIV-1 remission.The pattern of neural activity evoked by a stimulus can be substantially affected by ongoing spontaneous activity. Separating these two types of activity is particularly important for calcium imaging data given the slow temporal dynamics of calcium indicators. Here we present a statistical model that decouples stimulus-driven activity from low dimensional spontaneous activity in this case. The model identifies hidden factors giving rise to spontaneous activity while jointly estimating stimulus tuning properties that account for the confounding effects that these factors introduce. By applying our model to data from zebrafish optic tectum and mouse visual cortex, we obtain quantitative measurements of the extent that neurons in each case are driven by evoked activity, spontaneous activity, and their interaction. By not averaging away potentially important information encoded in spontaneous activity, this broadly applicable model brings new insight into population-level neural activity within single trials.We give an approximate solution to the difficult inverse problem of inferring the topology of an unknown network from given time-dependent signals at the nodes. For example, we measure signals from individual neurons in the brain, and infer how they are inter-connected. We use Maximum Caliber as an inference principle. The combinatorial challenge of high-dimensional data is handled using two different approximations to the pairwise couplings. We show two proofs of principle in a nonlinear genetic toggle switch circuit, and in a toy neural network.One of the hallmarks of cancer is the extremely high mutability and genetic instability of tumor cells. Inherent heterogeneity of intra-tumor populations manifests itself in high variability of clone instability rates. Analogously to fitness landscapes, the instability rates of clonal populations form their mutability landscapes. Here, we present MULAN (MUtability LANdscape inference), a maximum-likelihood computational framework for inference of mutation rates of individual cancer subclones using single-cell sequencing data. It utilizes the partial information about the orders of mutation events provided by cancer mutation trees and extends it by inferring full evolutionary history and mutability landscape of a tumor. Evaluation of mutation rates on the level of subclones rather than individual genes allows to capture the effects of genomic interactions and epistasis. We estimate the accuracy of our approach and demonstrate that it can be used to study the evolution of genetic instability and infer tumor evolutionary history from experimental data. MULAN is available at https//github.com/compbel/MULAN.We derive and validate a novel and analytic method for estimating the probability that an epidemic has been eliminated (i.e. that no future local cases will emerge) in real time. When this probability crosses 0.95 an outbreak can be declared over with 95% confidence. Our method is easy to compute, only requires knowledge of the incidence curve and the serial interval distribution, and evaluates the statistical lifetime of the outbreak of interest. Using this approach, we show how the time-varying under-reporting of infected cases will artificially inflate the inferred probability of elimination, leading to premature (false-positive) end-of-epidemic declarations. Contrastingly, we prove that incorrectly identifying imported cases as local will deceptively decrease this probability, resulting in delayed (false-negative) declarations. Failing to sustain intensive surveillance during the later phases of an epidemic can therefore substantially mislead policymakers on when it is safe to remove travel bans or relax quarantine and social distancing advisories. World Health Organisation guidelines recommend fixed (though disease-specific) waiting times for end-of-epidemic declarations that cannot accommodate these variations. Consequently, there is an unequivocal need for more active and specialised metrics for reliably identifying the conclusion of an epidemic.Anadromous alewives (Alosa pseudoharengus) are abundant in the Canadian Maritimes, where they support lucrative commercial fisheries. Little is known about their coastal movement, and their potential to interact with anthropogenic structures. Acoustic telemetry can provide detailed information on the spatiotemporal distribution and survival of fishes in coastal areas, using information transmitted from tagged fishes and recorded by moored receivers. However, few acoustic telemetry studies have been performed on clupeids as they are extremely sensitive to handling, and are often compromised by surgical tag implantation. This research assesses the feasibility of a surgical tagging protocol using novel High Residency acoustic tags in alewives, and establishes a baseline of short-term tagging effects.  https://www.selleckchem.com/products/GDC-0449.html  Alewives from the Gaspereau River population were tagged between 2018 (n = 29) and 2019 (n = 96) with non-transmitting models of Vemco/Innovasea V5 HR tags. Tagging effects were evaluated based on recovery rate, reflex impairment, and necropsy-based health assessments. Alewives responded well to tagging, with low mortality (3%) and no observed instances of tag shedding 72 hours post-surgery. The use of sutures to close the incision site had no effect on recovery times. Water temperature and spawning condition had the greatest effect on the behavioural response of fish to tagging. Our findings suggest that, with proper handling and smaller acoustic tags, telemetry studies on alewives are feasible.Spatiotemporally precise and robust cell fate transitions, which depend on specific signaling cues, are fundamental to the development of appropriately patterned tissues. The fidelity and precision with which photoreceptor fates are recruited in the Drosophila eye exemplifies these principles. The fly eye consists of a highly ordered array of ~750 ommatidia, each of which contains eight distinct photoreceptors, R1-R8, specified sequentially in a precise spatial pattern. Recruitment of R1-R7 fates requires reiterative receptor tyrosine kinase / mitogen activated protein kinase (MAPK) signaling mediated by the transcriptional effector Pointed (Pnt). However the overall signaling levels experienced by R2-R5 cells are distinct from those experienced by R1, R6 and R7. A relay mechanism between two Pnt isoforms initiated by MAPK activation directs the universal transcriptional response. Here we ask how the generic Pnt response is tailored to these two rounds of photoreceptor fate transitions. We find that during R2-R5 specification PntP2 is coexpressed with a closely related but previously uncharacterized isoform, PntP3.