Epilepsy afflicts 1-2% of the world’s population and often goes untreated; nearly 70% of those with a form of epilepsy fail to receive proper treatment. Therefore, there is great demand for the design of novel, effective anticonvulsants to combat epilepsy in its numerous forms. Previously, alpha-hydroxy-alpha-phenylcaprolactam was found to have rather potent antiepileptic activity [anti-maximal electroshock (MES) ED(50)=63 mg/kg and anti-subcutaneous Metrazol (scMet) ED(50)=74 mg/kg] when administered intraperitoneally in mice. We focused our attention on the development of this compound through traditional medicinal chemistry techniques-including the Topliss approach, isosteric replacement, methylene insertion, and rigid analogue approach-in the hopes of determining the effect of caprolactam alpha-substitution and other structural modifications on anticonvulsant activity. A number of the desired targets were successfully synthesized and submitted to the Anticonvulsant Screening Program of the National Institute of Neurological Disorders and Stroke (NINDS). Phase I results were quite promising for at least three of the compounds: alpha-ethynyl-alpha-hydroxycaprolactam (10), alpha-benzyl-alpha-hydroxycaprolactam (11), and alpha-hydroxy-alpha-(phenylethynyl)caprolactam (13). Phase II results for 11 strongly suggested it as a new structural class for further development, as it exhibited an anti-MES T.I. in excess of 4.0. Further, the potent activity of 13 in all models also pointed to the substituted alkynylcaprolactams as a new anticonvulsant structural class.

Cells form networks in animal tissues through synaptic, chemical, and adhesive links. Invertebrate muscle cells often connect to other cells through desmosomes, adhesive junctions anchored by intermediate filaments. To study desmosomal networks, we skeletonised 853 muscle cells and their desmosomal partners in volume electron microscopy data covering an entire larva of the annelid . Muscle cells adhere to each other, to epithelial, glial, ciliated, and bristle-producing cells and to the basal lamina, forming a desmosomal connectome of over 2000 cells. The aciculae - chitin rods that form an endoskeleton in the segmental appendages - are highly connected hubs in this network. This agrees with the many degrees of freedom of their movement, as revealed by video microscopy. Mapping motoneuron synapses to the desmosomal connectome allowed us to infer the extent of tissue influenced by motoneurons. Our work shows how cellular-level maps of synaptic and adherent force networks can elucidate body mechanics.

We describe new detachable floating glass micropipette electrode devices that provide targeted action potential recordings in active moving organs without requiring constant mechanical constraint or pharmacological inhibition of tissue motion. The technology is based on the concept of a glass micropipette electrode that is held firmly during cell targeting and intracellular insertion, after which a 100µg glass microelectrode, a "microdevice", is gently released to remain within the moving organ. The microdevices provide long-term recordings of action potentials, even during millimeter-scale movement of tissue in which the device is embedded. We demonstrate two different glass micropipette electrode holding and detachment designs appropriate for the heart (sharp glass microdevices for cardiac myocytes in rats, guinea pigs and humans) and the brain (patch glass microdevices for neurons in rats). We explain how microdevices enable measurements of multiple cells within a moving organ that are typically difficult with other technologies. Using sharp microdevices, action potential duration (APD) was monitored continuously for 15 minutes in unconstrained perfused hearts during global ischemia-reperfusion, providing beat-to-beat measurements of changes in APD. Action potentials from neurons in the hippocampus of anaesthetized rats were measured with patch microdevices, which provided stable base potentials during long-term recordings. Our results demonstrate that detachable microdevices are an elegant and robust tool to record electrical activity with high temporal resolution and cellular level localization without disturbing the physiological working conditions of the organ.

The prediction of pathological changes on single cell behaviour is a challenging task for deep learning models. Indeed, in self-supervised learning methods, no prior labels are used for the training and all of the information for event predictions are extracted from the data themselves. We present here a novel self-supervised learning model for the detection of anomalies in a given cell population, StArDusTS. Cells are monitored over time, and analysed to extract time-series of dry mass values. We assessed its performances on different cell lines, showing a precision of 96% in the automatic detection of anomalies. Additionally, anomaly detection was also associated with cell measurement errors inherent to the acquisition or analysis pipelines, leading to an improvement of the upstream methods for feature extraction. Our results pave the way to novel architectures for the continuous monitoring of cell cultures in applied research or bioproduction applications, and for the prediction of pathological cellular changes.

Population recordings of calcium activity are a major source of insight into neural function. Large dataset sizes often require automated methods, but automation can introduce errors that are difficult to detect. Here we show that automatic time course estimation can sometimes lead to significant misattribution errors, in which fluorescence is ascribed to the wrong cell. Misattribution arises when the shapes of overlapping cells are imperfectly defined, or when entire cells or processes are not identified, and misattribution can even be produced by methods specifically designed to handle overlap. To diagnose this problem, we develop a transient-by-transient metric and a visualization tool that allow users to quickly assess the degree of misattribution in large populations. To filter out misattribution, we also design a robust estimator that explicitly accounts for contaminating signals in a generative model. Our methods can be combined with essentially any cell finding technique, empowering users to diagnose and correct at large scale a problem that has the potential to significantly alter scientific conclusions.

In this work, we address the problem of precisely localizing key frames of an action, for example, the precise time that a pitcher releases a baseball, or the precise time that a crowd begins to applaud. Key frame localization is a largely overlooked and important action-recognition problem, for example in the field of neuroscience, in which we would like to understand the neural activity that produces the start of a bout of an action. To address this problem, we introduce a novel structured loss function that properly weights the types of errors that matter in such applications: it more heavily penalizes extra and missed action start detections over small misalignments. Our structured loss is based on the best matching between predicted and labeled action starts. We train recurrent neural networks (RNNs) to minimize differentiable approximations of this loss. To evaluate these methods, we introduce the Mouse Reach Dataset, a large, annotated video dataset of mice performing a sequence of actions. The dataset was collected and labeled by experts for the purpose of neuroscience research. On this dataset, we demonstrate that our method outperforms related approaches and baseline methods using an unstructured loss.

The interaural time difference (ITD) is a major cue to sound localization along the horizontal plane. The maximum natural ITD occurs when a sound source is positioned opposite to one ear. We examined the ability of owls and humans to detect large ITDs in sounds presented through headphones. Stimuli consisted of either broad or narrow bands of Gaussian noise, 100 ms in duration. Using headphones allowed presentation of ITDs that are greater than the maximum natural ITD. Owls were able to discriminate a sound leading to the left ear from one leading to the right ear, for ITDs that are 5 times the maximum natural delay. Neural recordings from optic-tectum neurons, however, show that best ITDs are usually well within the natural range and are never as large as ITDs that are behaviorally discriminable. A model of binaural crosscorrelation with short delay lines is shown to explain behavioral detection of large ITDs. The model uses curved trajectories of a cross-correlation pattern as the basis for detection. These trajectories represent side peaks of neural ITD-tuning curves and successfully predict localization reversals by both owls and human subjects.

How effectively synaptic and regenerative potentials propagate within neurons depends critically on the membrane properties and intracellular resistivity of the dendritic tree. These properties therefore are important determinants of neuronal function. Here we use simultaneous whole-cell patch-pipette recordings from the soma and apical dendrite of neocortical layer 5 pyramidal neurons to directly measure voltage attenuation in cortical neurons. When combined with morphologically realistic compartmental models of the same cells, the data suggest that the intracellular resistivity of neocortical pyramidal neurons is relatively low ( approximately 70 to 100 Omegacm), but that voltage attenuation is substantial because of nonuniformly distributed resting conductances present at a higher density in the distal apical dendrites. These conductances, which were largely blocked by bath application of CsCl (5 mM), significantly increased steady-state voltage attenuation and decreased EPSP integral and peak in a manner that depended on the location of the synapse. Together these findings suggest that nonuniformly distributed Cs-sensitive and -insensitive resting conductances generate a "leaky" apical dendrite, which differentially influences the integration of spatially segregated synaptic inputs.

Aphid taxonomy is often frustrated by the host alternation and extensive polyphenism displayed by many species. Here we examine the utility of using molecular data to assist in life cycle and taxonomic determination. We found that a relatively small amount of DNA sequence data can greatly assist in these tasks. Molecular data have identified the synonymy of five species: Tuberaphis plicator (Noordam) is a junior synonym of T.takenouchii (Takahashi), T.taiwana (Takahashi) is a junior synonym of T.coreana Takahashi, Hamiltonaphis styraci (Matsumura) is transferred to Tuberaphis Takahashi, Astegopteryx roepkei Hille Ris Lambers is transferred to Ceratoglyphina van der Goot, and A.vandermeermohri Hille Ris Lambers is transferred to Cerataphis Lichtenstein. We have elucidated the complete life cycles of five species: A.basalis (van der Goot) alternates between Styrax benzoin and bamboos, Ceratoglyphina bambusae van der Goot alternates between S.benzoin and bamboos, Pseudoregma sundanica (van der Goot) alternates between S.paralleloneura and Zingiberaceae, T.coreana alternates between S.formosana and Loranthaceae, and T.takenouchii alternates between S.japonica and Loranthaceae. In all cases the molecular data agreed with available morphological data. This analysis demonstrates the utility of DNA sequence comparisons for elucidating complex life cycles and the taxonomy of difficult insect groups.

Correct localization and topology are crucial for a protein's cellular function. To determine topologies of membrane proteins, a new technique, called fluorescence protease protection (FPP) assay, has recently been established. The sole requirements for FPP are the expression of fluorescent-protein fusion proteins and the selective permeabilization of the plasma membrane, permitting a wide range of cell types and organelles to be investigated. Proteins topologies in organelles like endoplasmic reticulum, Golgi apparatus, mitochondria, peroxisomes, and autophagosomes have already been determined by FPP. Here, two different step-by-step protocols of the FPP assay are provided. First, we describe the FPP assay using fluorescence microscopy for single adherent cells, and second, we outline the FPP assay for high-throughput screening applications.