Biology subjects

Mehrotra, D.

Publications and source records attributed to Mehrotra, D..

5 recordsLinked to original sources

bioRxiv2022

Pynapple: a toolbox for data analysis in neuroscience.

Datasets collected in neuroscientific studies are of ever-growing complexity, often combining high dimensional time series data from multiple data acquisition modalities. Handling and manipulating these various data streams in an adequate programming environment is crucial to ensure reliable analysis, and to facilitate sharing of reproducible analysis pipelines. Here, we present Pynapple, the PYthon Neural Analysis Package, a lightweight python package designed to process a broad range of time-resolved data in systems neuroscience. The core feature of this package is a small number of versatile objects that support the manipulation of any data streams and task parameters. The package includes a set of methods to read common data formats and allows users to easily write their own. The resulting code is easy to read and write, avoids low-level data processing and other error-prone steps, and is open source. Libraries for higher-level analyses are developed within the Pynapple framework but are contained within in a collaborative repository of specialized and continuously updated analysis routines. This provides flexibility while ensuring long-term stability of the core package. In conclusion, Pynapple provides a common framework for data analysis in neuroscience. HighlightsO_LIAn open-source framework for data analysis in systems neuroscience. C_LIO_LIEasy-to-use object-oriented programming for data manipulation. C_LIO_LIA lightweight and standalone package ensuring long-term backward compatibility. C_LI

neuroscience↗

bioRxiv2022

Supraorbital whiskers act as wind-antennae in rat anemotaxis

We know little about mammalian anemotaxis, wind-sensing. Recently, however, Hartmann and colleagues showed whisker-based anemotaxis in rats. To investigate how whiskers sense airflow, we tracked whisker tips in anesthetized or cadaver rats under no airflow, low airflow and high (fan-blowing) airflow. Whisker tips showed little movement under no airflow conditions and all whisker tips moved during high airflow. Low airflow conditions - most similar to naturally occurring wind stimuli - engaged whisker tips differentially. Most whiskers moved little, the long supraorbital whisker showed maximal displacement and , A1, {beta}, and {gamma} whiskers also showed movements. The long supraorbital whisker differs from other whiskers in its exposed dorsal position, upward bending, length and thin diameter. Ex vivo extracted long supraorbital whiskers also showed exceptional airflow displacement, suggesting whisker-intrinsic biomechanics mediate the unique airflow-sensitivity. Micro computed tomography revealed that the ring-wulst - the follicle structure receiving the most sensitive afferents - was more complete/ closed in supraorbital and other wind-sensitive whiskers than in non-wind-sensitive whiskers, suggesting specialization of the supraorbital for omni-directional sensing. We localized and targeted the cortical supraorbital whisker representation in simultaneous Neuropixels recordings with D/E-row whisker barrels. Responses to wind-stimuli were stronger in the supraorbital whisker representation than in D/E-row barrel cortex. We assessed the behavioral significance of whiskers in an airflow-sensing paradigm. We observed that rats spontaneously turn towards airflow stimuli in complete darkness. Selective trimming of wind-responsive whiskers diminished airflow turning responses more than trimming of non-wind-responsive whiskers. Lidocaine injections targeted to supraorbital whisker follicles also diminished airflow turning responses compared to control injections. We conclude that supraorbital whiskers act as wind antennae. New and NoteworthyAnimals rely on sensory processing of airflow (anemotaxis) to guide navigation and survival. We examined mechanisms of rat anemotaxis by combining whisker tracking, biomechanical analysis, micro computed tomography of follicle structure, Neuropixels recordings in the barrel field, behavior of airflow turning and whisker interference by trimming and lidocaine injections. This diversity of methods led to a coherent pattern of results. Whiskers greatly differ in their airflow sensitivity and strongly wind-responsive whiskers - in particular long supraorbital whiskers - determine behavioral responses to airflow stimuli in rats.

neuroscience↗

bioRxiv2022

Large-scale systematic feasibility study on the pan-cancer predictability of multi-omic biomarkers from whole slide images with deep learning

We assessed the pan-cancer predictability of multi-omic biomarkers from haematoxylin and eosin (H&E)-stained whole slide images (WSI) using deep learning (DL) throughout a systematic study. A total of 13,443 DL models predicting 4,481 multi-omic biomarkers across 32 cancer types were trained and validated. The investigated biomarkers included a broad range of genetic, transcriptomic, proteomic, and metabolic alterations, as well as established markers relevant for prognosis, molecular subtypes and clinical outcomes. Overall, we found that DL can predict multi-omic biomarkers directly from routine histology images across solid cancer types, with 50% of the models performing at an area under the curve (AUC) of more than 0.633 (with 25% of the models having an AUC larger than 0.711). A wide range of biomarkers were detectable from routine histology images across all investigated cancer types, with a mean AUC of at least 0.62 in almost all malignancies. Strikingly, we observed that biomarker predictability was mostly consistent and not dependent on sample size and class ratio, suggesting a degree of true predictability inherent in histomorphology. Together, the results of our study show the potential of DL to predict a multitude of biomarkers across the omics spectrum using only routine slides. This paves the way for accelerating diagnosis and developing more precise treatments for cancer patients.

cancer biology↗

bioRxiv2022

Evaluation of a predictive method for the H&E-based molecular profiling of breast cancer with deep learning

We present a public validation of PANProfiler (ER, PR, HER2), an in-vitro medical device (IVD) that predicts the qualitative status of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) by analysing the hematoxylin and eosin (H&E)-stained tissue scan. In public validation on 648 (ER), 648 (PR) and 560 (HER2) unseen cases with known biomarker status, the device achieves an accuracy of 87% (ER), 83% (PR) and 87% (HER2). The validation offers early evidence of the ability to predict clinically relevant breast biomarkers from an H&E slide in a relevant clinical setting.

cancer biology↗

bioRxiv2021

Novel measures of Morris water maze performance that use vector field maps to assess accuracy, uncertainty, and intention of navigational searches

Most commonly used behavioural measures for testing learning and memory in the Morris water maze (MWM) involve comparisons of an animals residence time in different quadrants of the pool. Such measures are limited in their ability to test different aspects of the animals performance. Here, we describe novel measures of performance in the MWM that use vector fields to capture the motion of mice as well as their search pattern in the maze. Using these vector fields, we develop quantitative measures of performance that are intuitive and more sensitive than classical measures. First, we describe search patterns in terms of vector field properties and use these properties to define three metrics of spatial memory namely Spatial Accuracy, Uncertainty and, Intensity of Search. We demonstrate the usefulness of these measures using four different data sets including comparisons between different strains of mice, an analysis of two mouse models of Noonan syndrome (Ptpn11 D61G and Ptpn11 N308D/+), and a study of goal reversal training. Importantly, besides highlighting novel aspects of performance in this widely used spatial task, our measures were able to uncover previously undetected differences, including in an animal model of Noonan syndrome, which we rescued with the mitogen activated protein kinase kinase (MEK) inhibitor SL327. Thus, our results show that our approach breaks down performance in the Morris water maze into sensitive measurable independent components that highlight differences in spatial learning and memory in the MWM that were undetected by conventional measures.

animal behavior and cognition↗