A nonoscillatory, millisecond-scale embedding of brain state provides insight into behavior.

The most robust and reliable signatures of brain states are enriched in rhythms between 0.1 and 20 Hz. Here we address the possibility that the fundamental unit of brain state could be at the scale of milliseconds and micrometers. By analyzing high-resolution neural activity recorded in ten mouse brain regions over 24 h, we reveal that brain states are reliably identifiable (embedded) in fast, nonoscillatory activity. Sleep and wake states could be classified from 100 to 101 ms of neuronal activity sampled from 100 µm of brain tissue. In contrast to canonical rhythms, this embedding persists above 1,000 Hz. This high-frequency embedding is robust to substates, sharp-wave ripples and cortical on/off states. Individual regions intermittently switched states independently of the rest of the brain, and such brief state discontinuities coincided with brief behavioral discontinuities. Our results suggest that the fundamental unit of state in the brain is consistent with the spatial and temporal scale of neuronal computation.

Evaluation of PVC and PTFE filters for direct-on-filter crystalline silica quantification by FTIR.

Direct-on-Filter (DoF) analysis of respirable crystalline silica (RCS) by Fourier Transform Infrared (FTIR) spectroscopy is a useful tool for assessing exposure risks. With the RCS exposure limits becoming lower, it is important to characterize and reduce measurement uncertainties. This study systematically evaluated two filter types (i.e., polyvinyl chloride [PVC] and polytetrafluoroethylene [PTFE]) for RCS measurements by DoF FTIR spectroscopy, including the filter-to-filter and day-to-day variability of blank filter FTIR reference spectra, particle deposition patterns, filtration efficiencies, and pressure drops. For PVC filters sampled at a flow rate of 2.5 L/min for 8 h, the RCS limit of detection (LOD) was 7.4 µg/m3 when a designated laboratory reference filter was used to correct the absorption by the filter media. When the spectrum of the pre-sample filter (blank filter before dust sampling) was used for correction, the LOD could be up to 5.9 µg/m3. The PVC absorption increased linearly with reference filter mass, providing a means to correct the absorption differences between the pre-sample and reference filters. For PTFE, the LODs were 12 and 1.2 µg/m3 when a designated laboratory blank or the pre-sample filter spectrum was used for blank correction, respectively, indicating that using the pre-sample blank spectrum will reduce RCS quantification uncertainty. Both filter types exhibited a consistent radially symmetric deposition pattern when particles were collected using 3-piece cassettes, indicating that RCS can be quantified from a single measurement at the filter center. The most penetrating aerodynamic diameters were around 0.1 µm with filtration efficiencies ≥ 98.8% across the measured particle size range with low-pressure drops (0.2-0.3 kPa) at a flow rate of 2.5 L/min. This study concludes that either the PVC or the PTFE filters are suitable for RCS analysis by DoF FTIR, but proper methods are needed to account for the variability of blank absorption among different filters.

Evaluation of a non-dispersive infrared spectrometer for quantifying organic and elemental carbon in diesel particulate matter.

Diesel particulate matter (DPM) is a common and well-known health hazard in the mining environment. The regulatory method for monitoring both the organic and elemental carbon (OC, EC) portions of DPM is a laboratory-based thermal-optical method with a typical turnaround time of one week. In order to evaluate exposure levels and take corrective action prior to overexposure, a portable real-time device capable of quantifying both OC and EC is needed. To that end, researchers from the National Institute for Occupational Safety and Health (NIOSH) designed and tested the feasibility of a device based on bandpass optical filters that target key infrared wavelengths associated with DPM and its spectroscopic baseline. The resulting device, referred to here as a non-dispersive infrared (NDIR) spectrometer could serve as the basis of a cost-effective, field-portable alternative to the laboratory thermal-optical method. The limits of quantification (LOD) indicate that the NDIR spectrometer can quantify EC, OC, and TC provided they are present at 20, 37, and 46 µg/m3 or more, respectively. In the event that the NDIR spectrometer is integrated with a sampler and filter tape the LOD is estimated to be reduced to 13, 7, and 10 µg/m3 for EC, OC, and TC, respectively. These LOD estimates assume a face velocity of 59 cm/s and a sampling time of 30 min.

A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies.

The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings.

A non-oscillatory, millisecond-scale embedding of brain state provides insight into behavior.

Sleep and wake are understood to be slow, long-lasting processes that span the entire brain. Brain states correlate with many neurophysiological changes, yet the most robust and reliable signature of state is enriched in rhythms between 0.1 and 20 Hz. The possibility that the fundamental unit of brain state could be a reliable structure at the scale of milliseconds and microns has not been addressed due to the physical limits associated with oscillation-based definitions. Here, by analyzing high resolution neural activity recorded in 10 anatomically and functionally diverse regions of the murine brain over 24 h, we reveal a mechanistically distinct embedding of state in the brain. Sleep and wake states can be accurately classified from on the order of 100 to 101 ms of neuronal activity sampled from 100 µm of brain tissue. In contrast to canonical rhythms, this embedding persists above 1,000 Hz. This high frequency embedding is robust to substates and rapid events such as sharp wave ripples and cortical ON/OFF states. To ascertain whether such fast and local structure is meaningful, we leveraged our observation that individual circuits intermittently switch states independently of the rest of the brain. Brief state discontinuities in subsets of circuits correspond with brief behavioral discontinuities during both sleep and wake. Our results suggest that the fundamental unit of state in the brain is consistent with the spatial and temporal scale of neuronal computation, and that this resolution can contribute to an understanding of cognition and behavior.

Transcriptomic cell type structures in vivo neuronal activity across multiple timescales.

Cell type is hypothesized to be a key determinant of a neuron's role within a circuit. Here, we examine whether a neuron's transcriptomic type influences the timing of its activity. We develop a deep-learning architecture that learns features of interevent intervals across timescales (ms to >30 min). We show that transcriptomic cell-class information is embedded in the timing of single neuron activity in the intact brain of behaving animals (calcium imaging and extracellular electrophysiology) as well as in a bio-realistic model of the visual cortex. Further, a subset of excitatory cell types are distinguishable but can be classified with higher accuracy when considering cortical layer and projection class. Finally, we show that computational fingerprints of cell types may be universalizable across structured stimuli and naturalistic movies. Our results indicate that transcriptomic class and type may be imprinted in the timing of single neuron activity across diverse stimuli.

Cloud-controlled microscopy enables remote project-based biology education in underserved Latinx communities.

Project-based learning (PBL) has long been recognized as an effective way to teach complex biology concepts. However, not all institutions have the resources to facilitate effective project-based coursework for students. We have developed a framework for facilitating PBL using remote-controlled internet-connected microscopes. Through this approach, one lab facility can host an experiment for many students around the world simultaneously. Experiments on this platform can be run on long timescales and with materials that are typically unavailable to high school classrooms. This allows students to perform novel research projects rather than just repeating standard classroom experiments. To investigate the impact of this program, we designed and ran six user studies with students worldwide. All experiments were hosted in Santa Cruz and San Francisco, California, with observations and decisions made remotely by the students using their personal computers and cellphones. In surveys gathered after the experiments, students reported increased excitement for science and a greater desire to pursue a career in STEM. This framework represents a novel, scalable, and effective PBL approach that has the potential to democratize biology and STEM education around the world.

Review of Filters for Air Sampling and Chemical Analysis in Mining Workplaces.

This review considers the use of filters to sample air in mining workplace environments for dust concentration measurement and subsequent analysis of hazardous contaminants, especially respirable crystalline silica (RCS) on filters compatible with wearable personal dust monitors (PDM). The review summarizes filter vendors, sizes, costs, chemical and physical properties, and information available on filter modeling, laboratory testing, and field performance. Filter media testing and selection should consider the characteristics required for mass by gravimetry in addition to RCS quantification by Fourier-transform infrared (FTIR) or Raman spectroscopic analysis. For mass determination, the filters need to have high filtration efficiency (≥99% for the most penetrable particle sizes) and a reasonable pressure drop (up to 16.7 kPa) to accommodate high dust loading. Additional requirements include: negligible uptake of water vapor and gaseous volatile compounds; adequate particle adhesion as a function of particle loading; sufficient particle loading capacity to form a stable particle deposit layer during sampling in wet and dusty environments; mechanical strength to withstand vibrations and pressure drops across the filter; and appropriate filter mass compatible with the tapered element oscillating microbalance. FTIR and Raman measurements require filters to be free of spectral interference. Furthermore, because the irradiated area does not completely cover the sample deposit, particles should be uniformly deposited on the filter.

IoT cloud laboratory: Internet of Things architecture for cellular biology.

The Internet of Things (IoT) provides a simple framework to control online devices easily. IoT is now a commonplace tool used by technology companies but is rarely used in biology experiments. IoT can benefit cloud biology research through alarm notifications, automation, and the real-time monitoring of experiments. We developed an IoT architecture to control biological devices and implemented it in lab experiments. Lab devices for electrophysiology, microscopy, and microfluidics were created from the ground up to be part of a unified IoT architecture. The system allows each device to be monitored and controlled from an online web tool. We present our IoT architecture so other labs can replicate it for their own experiments.

Quantifying elemental and organic carbon in diesel particulate matter by mid-infrared spectrometry.

A method for the quantification of airborne organic carbon (OC) and elemental carbon (EC) within aerosolized diesel particulate matter (DPM) is described in this article. DPM is a known carcinogen encountered in many industrial workplaces (notably mining) and in the ambient atmosphere. The method described here collects DPM particles onto a quartz fiber filter, after which reflection-mode infrared spectra are measured on a mid-infrared Fourier transform (FT-IR) spectrometer. Several infrared absorption bands are investigated for their efficacy in quantifying OC and EC. The thermo-optical (T-O) method is used to calibrate a linear regression model to predict OC and EC from the infrared spectra. The calibrated model, generated from laboratory DPM samples, is then utilized to quantify OC and EC in mine samples obtained from two metal mine locations under a variety of operating conditions. The feasibility of further improving these results by partial least squares (PLS) regression was investigated. A single calibration that is broadly applicable would be considered an improvement over currently available portable instruments, which require aerosol-specific calibration.

Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments.

Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.

ISAC Probe Tag Dictionary: Standardized Nomenclature for Detection and Visualization Labels Used in Cytometry and Microscopy Imaging.

Since the advent of microscopy imaging and flow cytometry, there has been an explosion in the number of probes, consisting of a component binding to an analyte and a detectable tag, to mark areas of interest in or on cells and tissue. Probe tags have been created to detect and/or visualize probes. Over time, these probe tags have increased in number. The expansion has resulted in arbitrarily created synonyms of probe tags used in publications and software. The synonyms are problematic for readability of publications, accuracy of text/data mining, and bridging data from multiple platforms, protocols, and databases for Big Data analysis. Development and implementation of a universal language for probe tags will ensure equivalent quality and level of data being reported or extracted for clinical/scientific evaluation as well as help connect data from many platforms. The International Society for Advancement of Cytometry Data Standards Task Force composed of academic scientists and industry hardware/software/reagent manufactures have developed recommendations for a standardized nomenclature for probe tags used in cytometry and microscopy imaging. These recommendations are shared in this technical note in the form of a Probe Tag Dictionary. © 2020 International Society for Advancement of Cytometry.

Data File Standard for Flow Cytometry, Version FCS 3.2.

FCS 3.2 is a revision of the flow cytometry data standard based on a decade of suggested improvements from the community as well as industry needs to capture instrument conditions and measurement features more precisely. The unchanged goal of the standard is to provide a uniform file format that allows files created by one type of acquisition hardware and software to be analyzed by any other type. The standard retains the overall FCS file structure and most features of previous versions, but also contains a few changes that were required to support new types of data and use cases efficiently. These changes are incompatible with existing FCS file readers. Notably, FCS 3.2 supports mixed data types to, for example, allow FCS measurements that are intrinsically integers (e.g., indices or class assignments) or measurements that are commonly captured as integers (e.g., time ticks) to be more represented as integer values, while capturing other measurements as floating-point values in the same FCS data set. In addition, keywords explicitly specifying dyes, detectors, and analytes were added to avoid having to extract those heuristically and unreliably from measurement names. Types of measurements were formalized, several keywords added, others removed, or deprecated, and various aspects of the specification were clarified. A reference implementation of the cyclic redundancy check (CRC) calculation is provided in two programming languages since a correct CRC implementation was problematic for many vendors. © 2020 International Society for Advancement of Cytometry.

Brief Report: Durable Suppression and Low Rate of Virologic Failure 3 Years After Switch to Dolutegravir + Rilpivirine 2-Drug Regimen: 148-Week Results From the SWORD-1 and SWORD-2 Randomized Clinical Trials.

BACKGROUND: The SWORD trials showed that in participants who achieved virologic suppression taking 3-drug or 4-drug regimens, switching to the 2-drug regimen dolutegravir plus rilpivirine was noninferior in maintaining HIV-1 RNA <50 copies/mL at the week 48 primary endpoint. We present pooled week 148 analysis results from both studies. SETTING: SWORD-1: 65 centers, 13 countries; SWORD-2: 60 centers, 11 countries. METHODS: SWORD-1 and SWORD-2 are identical, open-label, phase III studies. Participants with screening HIV-1 RNA <50 copies/mL for ≥6 months; no prior virologic failure; and no documented resistance-associated major protease inhibitor, integrase inhibitor, nucleoside reverse transcriptase inhibitor (NRTI), or non-NRTI mutations or integrase resistance-associated substitution R263K were randomly assigned 1:1 to switch to once-daily dolutegravir 50 mg plus rilpivirine 25 mg on day 1 (early-switch group) or to continue their current antiretroviral regimen and, if virologically suppressed at week 48, switch to dolutegravir plus rilpivirine at week 52 (late-switch group) until week 148. RESULTS: Using snapshot algorithm at week 148, 432 of 513 (84%) early-switch participants (148 weeks of exposure) and 428 of 477 (90%) late-switch participants (96 weeks of exposure) maintained HIV-1 RNA <50 copies/mL. Eleven participants (1%) on dolutegravir plus rilpivirine met the confirmed virologic withdrawal criterion through week 148 (early-switch group, n = 8; late-switch group, n = 3) with no integrase resistance identified. Non-NRTI resistance-associated mutations were identified in 6 participants (<1%). Drug-related adverse events (grades 2-4) were observed in 31 (6%) early-switch and 16 (3%) late-switch participants. Significant improvements in bone biomarkers were observed. Significant improvements were observed in renal biomarkers in participants taking tenofovir disoproxil fumarate pre-switch. CONCLUSION: Switching to the 2-drug regimen dolutegravir plus rilpivirine maintained virologic suppression for a high proportion of participants through 3 years, with low rates of virologic failure and a well-tolerated safety profile.

Efficacy and safety of dolutegravir-rilpivirine for maintenance of virological suppression in adults with HIV-1: 100-week data from the randomised, open-label, phase 3 SWORD-1 and SWORD-2 studies.

BACKGROUND: Primary analyses of the SWORD-1 and SWORD-2 trials at 48 weeks showed that switching to a two-drug regimen of dolutegravir plus rilpivirine was non-inferior to continuing a standard three-drug or four-drug antiretroviral regimen for maintenance of virological suppression in people with HIV-1. Here, we present efficacy and safety data from the 100-week analysis of the trials. METHODS: SWORD-1 and SWORD-2 are identically designed, randomised, open-label phase 3 studies at 65 centres in 13 countries and 60 centres in 11 countries, respectively. Adults aged 18 years or older who were on a standard three-drug or four-drug antiretroviral therapy (ART) and had had fewer than 50 HIV-1 RNA copies per mL of plasma for at least 6 months were randomly assigned (1:1) to 50 mg dolutegravir plus 25 mg rilpivirine orally once daily (early-switch group) or to continue their standard regimen for 52 weeks before switching to the dolutegravir plus rilpivirine combination (ie, the late-switch group). In this analysis of week 100 data, the efficacy endpoint of interest was the proportion of participants with fewer than 50 copies of HIV-1 RNA per mL of plasma (per the US Food and Drug Administration snapshot algorithm). This outcome was assessed in all randomly assigned participants who received at least one dose of the study drug. Data were analysed after the last participant completed week 100 (Sept 15, 2017) and verified through the data cutoff (Nov 21, 2017). SWORD-1 and SWORD-2 are registered with ClinicalTrials.gov, numbers NCT02429791 and NCT02422797, respectively. FINDINGS: 513 participants were randomly assigned to dolutegravir plus rilpivirine (ie, the early-switch group) and 511 to continue their standard ART regimen, 477 of whom then switched to dolutegravir plus rilpivirine at week 52 (ie, the late-switch group). At week 100, 456 (89% [95% CI 86-92]) of 513 participants in the early-switch group and 444 (93% [91-95]) of 477 in the late-switch group had fewer than 50 HIV-1 RNA copies per mL. Drug-related adverse events occurred in 103 (20%) participants in the early-switch group and 58 (12%) in the late-switch group. The most common drug-related adverse events were headache (11 participants in the early-switch group [2%] vs eight [2%] in the late-switch group) and nausea (eight [2%] vs five [1%]). INTERPRETATION: The combination of dolutegravir plus rilpivirine sustained virological suppression of HIV-1, was associated with a low frequency of virological failure, and had a favourable safety profile, which support its use as a nucleoside reverse transcriptase inhibitor-sparing and protease inhibitor-sparing alternative to three-drug regimens that reduces overall exposure to ART. FUNDING: ViiV Healthcare and Janssen Pharmaceutica.

High-fidelity detection and sorting of nanoscale vesicles in viral disease and cancer.

Biological nanoparticles, including viruses and extracellular vesicles (EVs), are of interest to many fields of medicine as biomarkers and mediators of or treatments for disease. However, exosomes and small viruses fall below the detection limits of conventional flow cytometers due to the overlap of particle-associated scattered light signals with the detection of background instrument noise from diffusely scattered light. To identify, sort, and study distinct subsets of EVs and other nanoparticles, as individual particles, we developed nanoscale Fluorescence Analysis and Cytometric Sorting (nanoFACS) methods to maximise information and material that can be obtained with high speed, high resolution flow cytometers. This nanoFACS method requires analysis of the instrument background noise (herein defined as the "reference noise"). With these methods, we demonstrate detection of tumour cell-derived EVs with specific tumour antigens using both fluorescence and scattered light parameters. We further validated the performance of nanoFACS by sorting two distinct HIV strains to >95% purity and confirmed the viability (infectivity) and molecular specificity (specific cell tropism) of biological nanomaterials sorted with nanoFACS. This nanoFACS method provides a unique way to analyse and sort functional EV- and viral-subsets with preservation of vesicular structure, surface protein specificity and RNA cargo activity.

Automated subset identification and characterization pipeline for multidimensional flow and mass cytometry data clustering and visualization.

When examining datasets of any dimensionality, researchers frequently aim to identify individual subsets (clusters) of objects within the dataset. The ubiquity of multidimensional data has motivated the replacement of user-guided clustering with fully automated clustering. The fully automated methods are designed to make clustering more accurate, standardized and faster. However, the adoption of these methods is still limited by the lack of intuitive visualization and cluster matching methods that would allow users to readily interpret fully automatically generated clusters. To address these issues, we developed a fully automated subset identification and characterization (SIC) pipeline providing robust cluster matching and data visualization tools for high-dimensional flow/mass cytometry (and other) data. This pipeline automatically (and intuitively) generates two-dimensional representations of high-dimensional datasets that are safe from the curse of dimensionality. This new approach allows more robust and reproducible data analysis,+ facilitating the development of new gold standard practices across laboratories and institutions.

Methodology for evaluating and comparing flow cytometers: A multisite study of 23 instruments.

We demonstrate improved methods for making valid and accurate comparisons of fluorescence measurement capabilities among instruments tested at different sites and times. We designed a suite of measurements and automated data processing methods to obtain consistent objective results and applied them to a selection of 23 instruments at nine sites to provide a range of instruments as well as multiple instances of similar instruments. As far as we know, this study represents the most accurate methods and results so far demonstrated for this purpose. The first component of the study reporting improved methods for photoelectron scale (Spe) evaluations, which was published previously (Parks, El Khettabi, Chase, Hoffman, Perfetto, Spidlen, Wood, Moore, and Brinkman: Cytometry A 91 (2017) 232-249). Those results which were within themselves are not sufficient for instrument comparisons, so here, we use the Spe scale results for the 23 cytometers and combine them with additional information from the analysis suite to obtain the metrics actually needed for instrument evaluations and comparisons. We adopted what we call the 2+2SD limit of resolution as a maximally informative metric, for evaluating and comparing dye measurement sensitivity among different instruments and measurement channels. Our results demonstrate substantial differences among different classes of instruments in both dye response and detection sensitivity and some surprisingly large differences among similar instruments, even among instruments with nominally identical configurations. On some instruments, we detected defective measurement channels needing service. The system can be applied in shared resource laboratories and other facilities as an aspect of quality assurance, and accurate instrument comparisons can be valuable for selecting instruments for particular purposes and for making informed instrument acquisition decisions. An institutionally supported program could serve the cytometry community by facilitating access to materials, and analysis and maintaining an archive of results. © 2018 International Society for Advancement of Cytometry.

QFMatch: multidimensional flow and mass cytometry samples alignment.

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples.