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BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks.
Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study. We propose a suite of Batch Effect Removal Neural Networks (BERNN) to remove batch effects in large LC-MS experiments, with the goal of maximizing sample classification performance between conditions. More importantly, these models must efficiently generalize in batches not seen during training. A comparison of batch effect correction methods across five diverse datasets demonstrated that BERNN models consistently showed the strongest sample classification performance. However, the model producing the greatest classification improvements did not always perform best in terms of batch effect removal. Finally, we show that the overcorrection of batch effects resulted in the loss of some essential biological variability. These findings highlight the importance of balancing batch effect removal while preserving valuable biological diversity in large-scale LC-MS experiments.
Fillable Magnetic Microrobots for Drug Delivery to Cardiac Tissues in Vitro.
Many cardiac diseases, such as arrhythmia or cardiogenic shock, cause irregular beating patterns that must be regulated to prevent disease progression towards heart failure. Treatments can include invasive surgery or high systemic drug dosages, which lack precision, localization, and control. Drug delivery systems (DDSs) that can deliver cargo to the cardiac injury site could address these unmet clinical challenges. Here, we present a microrobotic DDS that can be mobilized to specific sites via magnetic control. Our DDS incorporates an internal chamber that can protect drug cargo. Furthermore, the DDS contains a tunable thermosensitive sealing layer that gradually degrades upon exposure to body temperature, enabling prolonged drug release. Once loaded with the small molecule drug norepinephrine, our microrobotic DDS modulated beating frequency in induced pluripotent stem-cell derived cardiomyocytes (iPSC-CMs) in a dose-dependent manner, thus simulating drug delivery to cardiac cells in vitro. The DDS also navigated several maze-like structures seeded with cardiomyocytes to demonstrate precise locomotion under a rotating low-intensity magnetic field and on-site drug delivery. This work demonstrates the utility of a magnetically actuating DDS for precise, localized, and controlled drug delivery which is of interest for a myriad of future opportunities such as in treating cardiac diseases. This article is protected by copyright. All rights reserved.
RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis.
Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.
Ultrasonic vocalisation rate tracks the diurnal pattern of activity in winter phenotype Djungarian hamsters (Phodopus sungorus)
AbstractVocalisations are increasingly being recognised as an important aspect of normal rodent behaviour yet little is known of how they interact with other spontaneous behaviours such as sleep and torpor, particularly in a social setting. We obtained chronic recordings of the vocal behaviour of adult male and female Djungarian hamsters (Phodopus sungorus) housed under short photoperiod (8 h light, 16 h dark, square wave transitions), in different social contexts. The animals were kept in isolation or in same-sex sibling pairs, separated by a grid which allowed non-physical social interaction. On approximately 20% of days hamsters spontaneously entered torpor, a state of metabolic depression that coincides with the rest phase of many small mammal species in response to actual or predicted energy shortages. Animals produced ultrasonic vocalisations (USVs) with a peak frequency of 57 kHz in both social and asocial conditions and there was a high degree of variability in vocalisation rate between subjects. Vocalisation rate was correlated with locomotor activity across the 24-h light cycle, occurring more frequently during the dark period when the hamsters were more active and peaking around light transitions. Solitary-housed animals did not vocalise whilst torpid and animals remained in torpor despite overlapping with vocalisations in social-housing. Besides a minor decrease in peak USV frequency when isolated hamsters were re-paired with their siblings, changing social contexts did not influence vocalisation behaviour or structure. In rare instances, temporally overlapping USVs occurred when animals were socially-housed and were grouped in such a way that could indicate coordination. We did not observe broadband calls (BBCs) contemporaneous with USVs in this paradigm, corroborating their correlation with physical aggression which was absent from our experiment. Overall, we find little evidence to suggest a direct social function of hamster USVs. We conclude that understanding the effects of vocalisations on spontaneous behaviours, such as sleep and torpor, will inform experimental design of future studies, especially where the role of social interactions is investigated.
Online cognitive monitoring technology for people with Parkinson's disease and REM sleep behavioural disorder.
Automated online cognitive assessments are set to revolutionise clinical research and healthcare. However, their applicability for Parkinson's Disease (PD) and REM Sleep Behavioural Disorder (RBD), a strong PD precursor, is underexplored. Here, we developed an online battery to measure early cognitive changes in PD and RBD. Evaluating 19 candidate tasks showed significant global accuracy deficits in PD (0.65 SD, p = 0.003) and RBD (0.45 SD, p = 0.027), driven by memory, language, attention and executive underperformance, and global reaction time deficits in PD (0.61 SD, p = 0.001). We identified a brief 20-min battery that had sensitivity to deficits across these cognitive domains while being robust to the device used. This battery was more sensitive to early-stage and prodromal deficits than the supervised neuropsychological scales. It also diverged from those scales, capturing additional cognitive factors sensitive to PD and RBD. This technology offers an economical and scalable method for assessing these populations that can complement standard supervised practices.
A Parasite Odyssey: An RNA virus concealed in Toxoplasma gondii
Abstract We are entering a “Platinum Age of Virus Discovery”, an era marked by exponential growth in the discovery of virus biodiversity, and driven by advances in metagenomics and computational analysis. In the ecosystem of a human (or any animal) there are more species of viruses than simply those directly infecting the animal cells. Viruses can infect all organisms constituting the microbiome, including bacteria, fungi, and unicellular parasites. Thus the complexity of possible interactions between host, microbe, and viruses is unfathomable. To understand this interaction network we must employ computationally-assisted virology as a means of analyzing and interpreting the millions of available samples to make inferences about the ways in which viruses may intersect human health. From a computational viral screen of human neuronal datasets, we identified a novel narnavirus Apocryptovirus odysseus (Ao) which likely infects the neurotropic parasite Toxoplasma gondii. Previously, several parasitic protozoan viruses (PPVs) have been mechanistically established as triggers of host innate responses, and here we present in silico evidence that Ao is a plausible pro-inflammatory factor in human and mouse cells infected by T. gondii. T. gondii infects billions of people worldwide, yet the prognosis of toxoplasmosis disease is highly variable, and PPVs like Ao could function as a hitherto undescribed hypervirulence factor. In a broader screen of over 7.6 million samples, we explored phylogenetically-proximal viruses to Ao and discovered 19 Apocryptovirus species, all found in libraries annotated as vertebrate transcriptome or metatranscriptomes. While samples containing this genus of narnaviruses are derived from sheep, goat, bat, rabbit, chicken, and pigeon samples, the presence of virus is strongly predictive of parasitic Apicomplexa nucleic acid co-occurrence, supporting that Apocryptovirus is a genus of parasite-infecting viruses. This is a computational proof-of-concept study in which we rapidly analyze millions of datasets from which we distilled a mechanistically, ecologically, and phylogenetically refined hypothesis. We predict this highly diverged Ao RNA virus is biologically a T. gondii infection, and that Ao, and other viruses like it, will modulate this disease which afflicts billions worldwide.
Endolysosomal TPCs regulate social behavior by controlling oxytocin secretion.
Oxytocin (OT) is a prominent regulator of many aspects of mammalian social behavior and stored in large dense-cored vesicles (LDCVs) in hypothalamic neurons. It is released in response to activity-dependent Ca2+ influx, but is also dependent on Ca2+ release from intracellular stores, which primes LDCVs for exocytosis. Despite its importance, critical aspects of the Ca2+-dependent mechanisms of its secretion remain to be identified. Here we show that lysosomes surround dendritic LDCVs, and that the direct activation of endolysosomal two-pore channels (TPCs) provides the critical Ca2+ signals to prime OT release by increasing the releasable LDCV pool without directly stimulating exocytosis. We observed a dramatic reduction in plasma OT levels in TPC knockout mice, and impaired secretion of OT from the hypothalamus demonstrating the importance of priming of neuropeptide vesicles for activity-dependent release. Furthermore, we show that activation of type 1 metabotropic glutamate receptors sustains somatodendritic OT release by recruiting TPCs. The priming effect could be mimicked by a direct application of nicotinic acid adenine dinucleotide phosphate, the endogenous messenger regulating TPCs, or a selective TPC2 agonist, TPC2-A1-N, or blocked by the antagonist Ned-19. Mice lacking TPCs exhibit impaired maternal and social behavior, which is restored by direct OT administration. This study demonstrates an unexpected role for lysosomes and TPCs in controlling neuropeptide secretion, and in regulating social behavior.
Assessment of Tissue Viability by Functional Imaging of Membrane Potential.
Electrical activity plays a key role in physiology, in particular for signaling and coordination. Cellular electrophysiology is often studied with micropipette-based techniques such as patch clamp and sharp electrodes, but for measurements at the tissue or organ scale, more integrated approaches are needed. Epifluorescence imaging of voltage-sensitive dyes ("optical mapping") is a tissue non-destructive approach to obtain insight into electrophysiology with high spatiotemporal resolution. Optical mapping has primarily been applied to excitable organs, especially the heart and brain. Action potential durations, conduction patterns, and conduction velocities can be determined from the recordings, providing information about electrophysiological mechanisms, including factors such as effects of pharmacological interventions, ion channel mutations, or tissue remodeling. Here, we describe the process for optical mapping of Langendorff-perfused mouse hearts, highlighting potential issues and key considerations.
Evaluation of cervical lymph nodes using multispectral optoacoustic tomography: a proof-of-concept study.
OBJECTIVES: Examination of lymph nodes is one of the most common indications for imaging in the head and neck region. The purpose of this study is to evaluate whether multispectral optoacoustic tomography can be used to observe chromophore differences between benign and malignant neck lymph nodes. MATERIALS AND METHODS: Proof-of-concept ex vivo study of resected cervical lymph nodes from 11 patients. The examination of lymph nodes included imaging with hybrid ultrasound and multispectral tomography system followed by spectral unmixing to separate signals from the endogenous chromophores water, lipid, hemoglobin and oxygenated hemoglobin; calculation of semi-quantitative parameters (total hemoglobin and relative oxygenation of hemoglobin). Comparison of the results from the hybrid measurement with the histopathological results. RESULTS: Most patients suffered from squamous cell carcinoma (n = 7), also metastasis from salivary gland adenocarcinoma and papillary thyroid carcinoma, were included. The comparison between benign cervical lymph nodes and metastases showed significant differences for the absorbers water, lipid, hemoglobin and oxygenated hemoglobin and total hemoglobin. CONCLUSIONS: Our ex vivo study suggests that multispectral optoacoustic tomography can be used to detect differences between reactive lymph nodes and metastases. The measurement of endogenous chromophores can be used for this purpose. The examinations are non-invasively and thus potentially improve diagnostic prediction. However, potential influences from the ex vivo setting must be considered.
Benchmarking of Cph1 Mutants and DrBphP for Light-Responsive Phytochrome-Based Hydrogels with Reversibly Adjustable Mechanical Properties.
In the rapidly expanding field of molecular optogenetics, the performance of the engineered systems relies on the switching properties of the underlying genetically encoded photoreceptors. In this study, the bacterial phytochromes Cph1 and DrBphP are engineered, recombinantly produced in Escherichia coli, and characterized regarding their switching properties in order to synthesize biohybrid hydrogels with increased light-responsive stiffness modulations. The R472A mutant of the cyanobacterial phytochrome 1 (Cph1) is identified to confer the phytochrome-based hydrogels with an increased dynamic range for the storage modulus but a different light-response for the loss modulus compared to the original Cph1-based hydrogel. Stiffness measurements of human atrial fibroblasts grown on these hydrogels suggest that differences in the loss modulus at comparable changes in the storage modulus affect cell stiffness and thus underline the importance of matrix viscoelasticity on cellular mechanotransduction. The hydrogels presented here are of interest for analyzing how mammalian cells respond to dynamic viscoelastic cues. Moreover, the Cph1-R472A mutant, as well as the benchmarking of the other phytochrome variants, are expected to foster the development and performance of future optogenetic systems.