PolyMatch: Novel Libraries, Algorithms, and Visualizations for Discovering Polymers and Chemical Series.

Polymers are integral components of everyday products, ranging from plastics and emulsifiers to lubricants and detergents. Characterization of these materials at the molecular level is essential to understanding their physicochemical properties and potential health impacts, considering factors such as the number of repeating units, chemical moieties, functional groups, and degree of unsaturation. This study introduces a free open-source vendor neutral software, PolyMatch, designed to annotate polysorbates, polysorbides, polyethylene glycols (PEGs), fatty acid esterified species, and related chemical species based on mass spectral and chromatographic patterns inherent in the repeating nature of chemical moieties. PolyMatch facilitates the generation of MS/MS libraries for polymeric chemical species characterization (with over 800 000 structures with associated fragment masses already built in) and covers the entire liquid chromatography-high-resolution mass spectrometry (LC-HRMS/MS) data-processing workflow. PolyMatch covers peak picking, blank filtering, annotation, data visualization, and sharing of interactive data sets via an HTML link to the community. The software was applied to a Tween 80 mixture, using LC-HRMS/MS on an Agilent 6546 Q-TOF instrument with iterative exclusion for comprehensive fragmentation coverage. PolyMatch automatically assigned 86 features with high confidence at the species level, 362 based on PEG containing fragments and accurate mass matching to a simulated polymer database, and over 10 000 based on being a member of a homologous series (three or more) with CH2CH2O repeating units. The ease of use of PolyMatch and comprehensive coverage with species level assignment is expected to contribute to the advancement of materials science, health research, and product development.

Expanding Per- and Polyfluoroalkyl Substances Coverage in Nontargeted Analysis Using Data-Independent Analysis and IonDecon.

Per- and polyfluoroalkyl substances (PFAS) are widespread, persistent environmental contaminants that have been linked to various health issues. Comprehensive PFAS analysis often relies on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC HRMS) and molecular fragmentation (MS/MS). However, the selection and fragmentation of ions for MS/MS analysis using data-dependent analysis results in only the topmost abundant ions being selected. To overcome these limitations, All Ions fragmentation (AIF) can be used alongside data-dependent analysis. In AIF, ions across the entire m/z range are simultaneously fragmented; hence, precursor-fragment relationships are lost, leading to a high false positive rate. We introduce IonDecon, which filters All Ions data to only those fragments correlating with precursor ions. This software can be used to deconvolute any All Ions files and generates an open source DDA formatted file, which can be used in any downstream nontargeted analysis workflow. In a neat solution, annotation of PFAS standards using IonDecon and All Ions had the exact same false positive rate as when using DDA; this suggests accurate annotation using All Ions and IonDecon. Furthermore, deconvoluted All Ions spectra retained the most abundant peaks also observed in DDA, while filtering out much of the artifact peaks. In complex samples, incorporating AIF and IonDecon into workflows can enhance the MS/MS coverage of PFAS (more than tripling the number of annotations in domestic sewage). Deconvolution in complex samples of All Ions data using IonDecon did retain some false fragments (fragments not observed when using ion selection, which were not isotopes or multimers), and therefore DDA and intelligent acquisition methods should still be acquired when possible alongside All Ions to decrease the false positive rate. Increased coverage of PFAS can inform on the development of regulations to address the entire PFAS problem, including both legacy and newly discovered PFAS.

Applying machine learning to predict viral assembly for adeno-associated virus capsid libraries.

Machine learning (ML) can aid in novel discoveries in the field of viral gene therapy. Specifically, big data gathered through next-generation sequencing (NGS) of complex capsid libraries is an especially prominent source of lost potential in data analysis and prediction. Furthermore, adeno-associated virus (AAV)-based capsid libraries are becoming increasingly popular as a tool to select candidates for gene therapy vectors. These higher complexity AAV capsid libraries have previously been created and selected in vivo; however, in silico analysis using ML computer algorithms may augment smarter and more robust libraries for selection. In this study, data of AAV capsid libraries gathered before and after viral assembly are used to train ML algorithms. We found that two ML computer algorithms, artificial neural networks (ANNs), and support vector machines (SVMs), can be trained to predict whether unknown capsid variants may assemble into viable virus-like structures. Using the most accurate models constructed, hypothetical mutation patterns in library construction were simulated to suggest the importance of N495, G546, and I554 in AAV2-derived capsids. Finally, two comparative libraries were generated using ML-derived data to biologically validate these findings and demonstrate the predictive power of ML in vector design.

Column-like Ca(2+) clusters in the mouse neonatal neocortex revealed by three-dimensional two-photon Ca(2+) imaging in vivo.

Neuronal network activity in the developing brain is generated in a discontinuous manner. In the visual cortex during the period of physiological blindness of immaturity, this activity mainly comprises retinally triggered spindle bursts or Ca(2+) clusters thought to contribute to the activity-dependent construction of cortical circuits. In spite of potentially important developmental functions, the spatial structure of these activity patterns remains largely unclear. In order to address this issue, we here used three-dimensional two-photon Ca(2+) imaging in the visual cortex of neonatal mice at postnatal days (P) 3-4 in vivo. Large-scale voxel imaging covering a cortical depth of 200µm revealed that Ca(2+) clusters, identified as spindle bursts in simultaneous extracellular recordings, recruit cortical glutamatergic neurons of the upper cortical plate (CP) in a column-like manner. Specifically, the majority of Ca(2+) clusters exhibit prominent horizontal confinement and high intra-cluster density of activation involving the entire depth of the upper CP. Moreover, using simultaneous Ca(2+) imaging from hundreds of neurons at single-cellular resolution, we demonstrate that the degree of neuronal co-activation within Ca(2+) clusters displays substantial heterogeneity. We further provide evidence that co-activated cells within Ca(2+) clusters are spatially distributed in a non-stochastic manner. In summary, our data support the conclusion that dense coding in the form of column-like Ca(2+) clusters is a characteristic property of network activity in the developing visual neocortex. Such knowledge is expected to be relevant for a refined understanding of how specific spatiotemporal characteristics of early network activity instruct the development of cortical circuits.

Method to quantify accuracy of position feedback signals of a three-dimensional two-photon laser-scanning microscope.

Two-photon laser-scanning microscopy enables to record neuronal network activity in three-dimensional space while maintaining single-cellular resolution. One of the proposed approaches combines galvanometric x-y scanning with piezo-driven objective movements and employs hardware feedback signals for position monitoring. However, readily applicable methods to quantify the accuracy of those feedback signals are currently lacking. Here we provide techniques based on contact-free laser reflection and laser triangulation for the quantification of positioning accuracy of each spatial axis. We found that the lateral feedback signals are sufficiently accurate (defined as <2.5 µm) for a wide range of scan trajectories and frequencies. We further show that axial positioning accuracy does not only depend on objective acceleration and mass but also its geometry. We conclude that the introduced methods allow a reliable quantification of position feedback signals in a cost-efficient, easy-to-install manner and should be applicable for a wide range of two-photon laser scanning microscopes.

GABA depolarizes immature neurons and inhibits network activity in the neonatal neocortex in vivo.

A large body of evidence from in vitro studies suggests that GABA is depolarizing during early postnatal development. However, the mode of GABA action in the intact developing brain is unknown. Here we examine the in vivo effects of GABA in cells of the upper cortical plate using a combination of electrophysiological and Ca(2+)-imaging techniques. We report that at postnatal days (P) 3-4, GABA depolarizes the majority of immature neurons in the occipital cortex of anaesthetized mice. At the same time, GABA does not efficiently activate voltage-gated Ca(2+) channels and fails to induce action potential firing. Blocking GABA(A) receptors disinhibits spontaneous network activity, whereas allosteric activation of GABA(A) receptors has the opposite effect. In summary, our data provide evidence that in vivo GABA acts as a depolarizing neurotransmitter imposing an inhibitory control on network activity in the neonatal (P3-4) neocortex.

Reliable in vivo identification of both GABAergic and glutamatergic neurons using Emx1-Cre driven fluorescent reporter expression.

The development of genetically modified mice in which subpopulations of cortical neurons are labelled by fluorescent proteins has greatly facilitated single-cellular imaging and electrophysiology studies in vitro and in vivo. However, the parallel visualization of both inhibitory and excitatory neocortical neurons remains problematic. We here provide an alternative approach to identify GABAergic neurons in the context of in vivo calcium imaging. The method relies on the Emx1(IREScre) recombinase driven expression of a red fluorescent protein in excitatory neurons and glia. We quantitatively examined the upper layers of the visual neocortex in vivo and found that due to pronounced neuropil staining Emx1(IREScre)-negative and Emx1(IREScre)-positive neurons can be reliably differentiated based on negative and positive contrast, respectively. Immunohistochemical analyses confirmed that the entire population of GABAergic interneurons is represented by Emx1(IREScre)-negative cells. The potential usefulness of the method is exemplified by calcium imaging of sensory-evoked responses in the primary visual cortex. We conclude that the proposed method extends the repertoire of strategies aimed at discriminating two major neocortical neuron populations in situ.

Steerable intravitreal inserts for drug delivery: in vitro and ex vivo mobility experiments.

The progress of wet age-related macular degeneration can now be controlled by intravitreal drug injection. This approach requires repeated injections, which could be avoided by delivering the drug to the retina. Intraocular implants are a promising solution for drug delivery near the retina. Currently, their accurate placement is challenging, and they can only be removed after a vitrectomy. In this paper, we introduce an approach for minimally invasive retinal drug delivery using magnetic intraocular inserts. We briefly discuss the electromagnetic-control system for magnetic implants and then focus on evaluating their ability to move in the vitreous humor. The mobility of magnetic intraocular implants is estimated in vitro with synthesized vitreous humors, and ex vivo with experiments on cadaver porcine eyes. Preliminary results show that with such magnetic implants a vitrectomy can be avoided.

Artificial vitreous humor for in vitro experiments.

In this paper we present a protocol to create artificial vitreous humor phantom tissue to be used as a test bed for in vitro experiments. The artificial vitreous consists of water, agar, and hyaluronic acid. Unlike existing vitreous replacement substances, this dummy tissue exhibits viscoelastic characteristics of in vivo natural vitreous humor. We are able to prepare artificial vitreous with a range of viscoelastic properties, which will allow us to account for the variation seen in human vitreous that comes with aging. The artificial vitreous will primarily serve as an experimental test bed for wireless magnetic control and vision-based tracking of assembled-MEMS microrobots. These microrobots will someday enable minimally invasive surgical and diagnostic intraocular procedures.

Pharmacokinetics of pipamperone from three different tablet formulations.

Twenty-four (24) Caucasian male subjects completed a single-blind, randomised, three-treatment, three-period, cross-over study. In each treatment phase, subjects received a single dose of 144 mg pipamperone dihydrochloride (CAS 2448-68-2) (equivalent to 120 mg pipamperone; CAS 1893-33-0) as either the reference product (3 x 40 mg tablets), test product A (3 x 40 mg tablets) or test product B (1 x 120 mg tablet). Each consecutive dosing was separated by a washout period of 14 days. Following each dosing, venous blood samples were collected over a period of 120 h for the determination of plasma pipamperone concentrations by high-performance liquid chromatography. The most common drug related adverse events, ranging from mild to moderate in intensity, were bloodshot eyes, nasal congestion, dry mouth, hypotension and dizziness. The geometric mean Cmax of pipamperone for both the reference product and test product A was 266 ng/ml and for test product B 263 ng/ml. The geometric mean AUC0-infinity was 3107 ng.h/ml for the reference product, 3229 ng.h/ml for test product A and 3108 ng.h/ml for test product B. The two test products were shown to be bioequivalent to the reference product with respect to all pharmacokinetic variables investigated.