Erratum: Resting state functional connectivity of the rat claustrum.

[This corrects the article DOI: 10.3389/fnana.2019.00022.].

Development of a top-down MS assay for specific identification of human periostin isoforms.

Periostin is a matricellular protein encoded by the POSTN gene that is alternatively spliced to produce ten different periostin isoforms with molecular weights ranging from 78 to 91 kDa. It is known to promote fibrillogenesis, organize the extracellular matrix, and bind integrin-receptors to induce cell signaling. As well as being a key component of the wound healing process, it is also known to participate in the pathogenesis of different diseases including atopic dermatitis, asthma, and cancer. In both health and disease, the functions of the different periostin isoforms are largely unknown. The ability to precisely determine the isoform profile of a given human sample is fundamental for characterizing their functional significance. Identification of periostin isoforms is most often carried out at the transcriptional level using RT-PCR based approaches, but due to high sequence homogeneity, identification on the protein level has always been challenging. Top-down proteomics, where whole proteins are measured by mass spectrometry, offers a fast and reliable method for isoform identification. Here we present a fully developed top-down mass spectrometry assay for the characterization of periostin splice isoforms at the protein level.

The modulation of task relevance on emotion-induced blindness depends on whether targets and distractors belong to the same category.

Previous research on emotion-induced blindness (EIB) argues emotional distractors capture attention in a bottom-up manner due to their physical and emotional salience. However, recent research has shown it is controversial whether EIB will be modulated by top-down factors. The present study further investigated whether the magnitude of EIB would be modulated by top-down factors, specifically the emotional relevance between tasks and distractors. Participants were divided into two groups having the same targets except for different task instructions. The orientation judgment group was asked to judge the orientation of the target (an emotionally irrelevant task), and the emotion judgment group was required to judge the emotional valence of the target (an emotionally relevant task). It was found the emotional relevance between tasks and distractors has no modulation on the magnitudes of EIB in two groups when targets and distractors are from different categories (Experiment 1), but a modulation when they are from the same category (Experiment 2). Consequently, we contend top-down task relevance modulates the EIB effect and distractors' priority is regulated by the emotional relevance between tasks and distractors. The current study holds attentional capture by stimulus-driven is unconditional in EIB, while attentional capture by goal-driven requires certain conditions.

Biogeographic and seasonal differences in consumer pressure underlie strong predation in the tropics.

Biotic interactions play a critical role in shaping patterns of global biodiversity. While several macroecological studies provide evidence for stronger predation in tropical regions compared with higher latitudes, results are variable even within the tropics, and the drivers of this variability are not well understood. We conducted two complementary standardized experiments on communities of sessile marine invertebrate prey and their associated predators to test for spatial and seasonal differences in predation across the tropical Atlantic and Pacific coastlines of Panama. We further tested the prediction that higher predator diversity contributes to stronger impacts of predation, using both direct observations of predators and data from extensive reef surveys. Our results revealed substantially higher predation rates and stronger effects of predators on prey in the Pacific than in the Atlantic, demonstrating striking variation within tropical regions. While regional predator diversity was high in the Atlantic, functional diversity at local scales was markedly low. Peak predation strength in the Pacific occurred during the wet, non-upwelling season when ocean temperatures were warmer and predator communities were more functionally diverse. Our results highlight the importance of regional biotic and abiotic drivers that shape interaction strength and the maintenance of tropical communities, which are experiencing rapid environmental change.

Combining SDS-PAGE to capillary zone electrophoresis-tandem mass spectrometry for high-resolution top-down proteomics analysis of intact histone proteoforms.

Mass spectrometry (MS)-based top-down proteomics (TDP) analysis of histone proteoforms provides critical information about combinatorial post-translational modifications (PTMs), which is vital for pursuing a better understanding of epigenetic regulation of gene expression. It requires high-resolution separations of histone proteoforms before MS and tandem MS (MS/MS) analysis. In this work, for the first time, we combined SDS-PAGE-based protein fractionation (passively eluting proteins from polyacrylamide gels as intact species for mass spectrometry, PEPPI-MS) with capillary zone electrophoresis (CZE)-MS/MS for high-resolution characterization of histone proteoforms. We systematically studied the histone proteoform extraction from SDS-PAGE gel and follow-up cleanup as well as CZE-MS/MS, to determine an optimal procedure. The optimal procedure showed reproducible and high-resolution separation and characterization of histone proteoforms. SDS-PAGE separated histone proteins (H1, H2, H3, and H4) based on their molecular weight and CZE provided additional separations of proteoforms of each histone protein based on their electrophoretic mobility, which was affected by PTMs, for example, acetylation and phosphorylation. Using the technique, we identified over 200 histone proteoforms from a commercial calf thymus histone sample with good reproducibility. The orthogonal and high-resolution separations of SDS-PAGE and CZE made our technique attractive for the delineation of histone proteoforms extracted from complex biological systems.

Associations of Cognitive Expectancies With Auditory Hallucinations and Hallucinatory-Like Experiences in Patients With Schizophrenia.

BACKGROUND: Various neurocognitive models explore perceptual distortions and hallucinations in schizophrenia and the general population. A variant of predictive coding account suggests that strong priors, like cognitive expectancy, may influence perception. This study examines if stronger cognitive expectancies result in more auditory false percepts in clinical and healthy control groups, investigates group differences, and explores the association between false percepts and hallucinations. STUDY DESIGN: Patients diagnosed with schizophrenia with current auditory hallucinations (n = 51) and without hallucinations (n = 66) and healthy controls (n = 51) underwent the False Perception Task under various expectancy conditions. All groups were examined for the presence and severity of hallucinations or hallucinatory-like experiences. STUDY RESULTS: We observed a main effect of condition across all groups, ie, the stronger the cognitive expectancy, the greater the ratio of auditory false percepts. However, there was no group effect for the ratio of auditory false percepts. Despite modest pairwise correlations in the hallucinating group, the ratio of auditory false percepts was not predicted by levels of hallucinations and hallucinatory-like experiences in a linear mixed model. CONCLUSIONS: The current study demonstrates that strong priors in the form of cognitive expectancies affect perception and play a role in perceptual disturbances. There is also a tentative possibility that overreliance on strong priors may be associated with hallucinations in currently hallucinating subjects. Possible, avoidable confounding factors are discussed in detail.

Combining Native Mass Spectrometry and Proteomics to Differentiate and Map the Metalloform Landscape in Metallothioneins.

Within the intricate landscape of the proteome, approximately 30% of all proteins bind metal ions. This repertoire is even larger when considering all the different forms of a protein, known as proteoforms. Here, we propose the term "metalloforms" to refer to different structural or functional variations of a protein resulting from the binding of various hetero- or homogeneous metal ions. Using human Cu(I)/Zn(II)-metallothionein-3 as a representative model, we developed a chemical proteomics strategy to simultaneously differentiate and map Zn(II) and Cu(I) metal binding sites. In the first labeling step, N-ethylmaleimide reacts with Cysteine (Cys), resulting in the dissociation of all Zn(II) ions while Cu(I) remains bound to the protein. In the second labeling step, iodoacetamide is utilized to label Cu(I)-bound Cys residues. Native mass spectrometry (MS) was used to determine the metal/labeling protein stoichiometries, while bottom-up/top-down MS was used to map the Cys-labeled residues. Next, we used a developed methodology to interrogate an isolated rabbit liver metallothionein fraction containing three metallothionein-2 isoforms and multiple Cd(II)/Zn(II) metalloforms. The approach detailed in this study thus holds the potential to decode the metalloproteoform diversity within other proteins.

Orbitofrontal cortex modulates auditory cortical sensitivity and sound perception in Mongolian gerbils.

Sensory perception is dynamic, quickly adapting to sudden shifts in environmental or behavioral context. Although decades of work have established that these dynamics are mediated by rapid fluctuations in sensory cortical activity, we have a limited understanding of the brain regions and pathways that orchestrate these changes. Neurons in the orbitofrontal cortex (OFC) encode contextual information, and recent data suggest that some of these signals are transmitted to sensory cortices. Whether and how these signals shape sensory encoding and perceptual sensitivity remain uncertain. Here, we asked whether the OFC mediates context-dependent changes in auditory cortical sensitivity and sound perception by monitoring and manipulating OFC activity in freely moving Mongolian gerbils of both sexes under two behavioral contexts: passive sound exposure and engagement in an amplitude modulation (AM) detection task. We found that the majority of OFC neurons, including the specific subset that innervates the auditory cortex, were strongly modulated by task engagement. Pharmacological inactivation of the OFC prevented rapid context-dependent changes in auditory cortical firing and significantly impaired behavioral AM detection. Our findings suggest that contextual information from the OFC mediates rapid plasticity in the auditory cortex and facilitates the perception of behaviorally relevant sounds.

Filling the gaps in peptide maps with a platform assay for top-down characterization of purified protein samples.

Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as truncation and oxidation, increase the difficulty of precise proteoform characterization owing to inherent limitations in peptide and intact protein analyses. Top-down MS (TDMS) can resolve this ambiguity via fragmentation of specific proteoforms. We leveraged the strengths of flow-programmed (fp) denaturing online buffer exchange (dOBE) chromatography, including robust automation, relatively high ESI sensitivity, and long MS/MS window time, to support a TDMS platform for industrial protein characterization. We tested data-dependent (DDA) and targeted strategies using 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large, focused dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based workflow provided objective identification of αLac truncation proteoforms with a two-termini clipping search. A targeted TDMS workflow facilitated the characterization of αLac oxidation positional isomers. This strategy relied on using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results amenable to fragment noise filtering, which is a fundamental enhancement relevant to TDMS applications generally.

Increases in Global and East Asian Nitrogen Trifluoride (NF3) Emissions Inferred from Atmospheric Observations.

Nitrogen trifluoride (NF3) is a potent and long-lived greenhouse gas that is widely used in the manufacture of semiconductors, photovoltaic cells, and flat panel displays. Using atmospheric observations from eight monitoring stations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and inverse modeling with a global 3-D atmospheric chemical transport model (GEOS-Chem), we quantify global and regional NF3 emission from 2015 to 2021. We find that global emissions have grown from 1.93 ± 0.58 Gg yr-1 (± one standard deviation) in 2015 to 3.38 ± 0.61 Gg yr-1 in 2021, with an average annual increase of 10% yr-1. The available observations allow us to attribute significant emissions to China (0.93 ± 0.15 Gg yr-1 in 2015 and 1.53 ± 0.20 Gg yr-1 in 2021) and South Korea (0.38 ± 0.07 Gg yr-1 to 0.65 ± 0.10 Gg yr-1). East Asia contributes around 73% of the global NF3 emission increase from 2015 to 2021: approximately 41% of the increase is from emissions from China (with Taiwan included), 19% from South Korea, and 13% from Japan. For Japan, which is the only one of these three countries to submit annual NF3 emissions to UNFCCC, our bottom-up and top-down estimates are higher than reported. With increasing demand for electronics, especially flat panel displays, emissions are expected to further increase in the future.

Enhanced Declustering Enables Native Top-Down Analysis of Membrane Protein Complexes using Ion-Mobility Time-Aligned Fragmentation.

Native mass spectrometry (MS) is proving to be a disruptive technique for studying the interactions of proteins, necessary for understanding the functional roles of these biomolecules. Recent research is expanding the application of native MS towards membrane proteins directly from isolated membrane preparations or from purified detergent micelles. The former results in complex spectra comprising several heterogeneous protein complexes; the latter enables therapeutic protein targets to be screened against multiplexed preparations of compound libraries. In both cases, the resulting spectra are increasingly complex to assign/interpret, and the key to these new directions of native MS research is the ability to perform native top-down analysis, which allows unambiguous peak assignment. To achieve this, detergent removal is necessary prior to MS analyzers, which allow selection of specific m/z values, representing the parent ion for downstream activation. Here, we describe a novel, enhanced declustering (ED) device installed into the first pumping region of a cyclic IMS-enabled mass spectrometry platform. The device enables declustering of ions prior to the quadrupole by imparting collisional activation through an oscillating electric field applied between two parallel plates. The positioning of the device enables liberation of membrane protein ions from detergent micelles. Quadrupole selection can now be utilized to isolate protein-ligand complexes, and downstream collision cells enable the dissociation and identification of binding partners. We demonstrate that ion mobility (IM) significantly aids in the assignment of top-down spectra, aligning fragments to their corresponding parent ions by means of IM drift time. Using this approach, we were able to confidently assign and identify a novel hit compound against PfMATE, obtained from multiplexed ligand libraries.

Activating Adsorption Sites of Waste Crayfish Shells via Chemical Decalcification for Efficient Capturing of Nanoplastics.

The property of being stubborn and degradation resistant makes nanoplastic (NP) pollution a long-standing remaining challenge. Here, we apply a designed top-down strategy to leverage the natural hierarchical structure of waste crayfish shells with exposed functional groups for efficient NP capture. The crayfish shell-based organic skeleton with improved flexibility, strength (14.37 to 60.13 MPa), and toughness (24.61 to 278.98 MJ m-3) was prepared by purposefully removing the inorganic components of crayfish shells through a simple two-step acid-alkali treatment. Due to the activated functional groups (e.g., -NH2, -CONH-, and -OH) and ordered architectures with macropores and nanofibers, this porous crayfish shell exhibited effective removal capability of NPs (72.92 mg g-1) by physical interception and hydrogen bond/electrostatic interactions. Moreover, the sustainability and stability of this porous crayfish shell were demonstrated by the maintained high-capture performance after five cycles. Finally, we provided a postprocessing approach that could convert both porous crayfish shell and NPs into a tough flat sheet. Thus, our feasible top-down engineering strategy combined with promising posttreatment is a powerful contender for a recycling approach with broad application scenarios and clear economic advantages for simultaneously addressing both waste biomass and NP pollutants.

Playing pin-the-tail-on-the-protein in extracellular vesicle (EV) proteomics.

Extracellular vesicles (EVs) are anucleate particles enclosed by a lipid bilayer that are released from cells via exocytosis or direct budding from the plasma membrane. They contain an array of important molecular cargo such as proteins, nucleic acids, and lipids, and can transfer these cargoes to recipient cells as a means of intercellular communication. One of the overarching paradigms in the field of EV research is that EV cargo should reflect the biological state of the cell of origin. The true relationship or extent of this correlation is confounded by many factors, including the numerous ways one can isolate or enrich EVs, overlap in the biophysical properties of different classes of EVs, and analytical limitations. This presents a challenge to research aimed at detecting low-abundant EV-encapsulated nucleic acids or proteins in biofluids for biomarker research and underpins technical obstacles in the confident assessment of the proteomic landscape of EVs that may be affected by sample-type specific or disease-associated proteoforms. Improving our understanding of EV biogenesis, cargo loading, and developments in top-down proteomics may guide us towards advanced approaches for selective EV and molecular cargo enrichment, which could aid EV diagnostics and therapeutics research.

Ocean warming undermines the recovery resilience of New England kelp forests following a fishery-induced trophic cascade.

Ecological theory predicts that kelp forests structured by trophic cascades should experience recovery and persistence of their foundation species when herbivores become rare. Yet, climate change may be altering the outcomes of top-down forcing in kelp forests, especially those located in regions that have rapidly warmed in recent decades, such as the Gulf of Maine. Here, using data collected annually from 30+ sites spanning >350 km of coastline, we explored the dynamics of Maine's kelp forests in the ~20 years after a fishery-induced elimination of sea urchin herbivores. Although forests (Saccharina latissima and Laminaria digitata) had broadly returned to Maine in the late 20th century, we found that forests in northeast Maine have since experienced slow but significant declines in kelp, and forest persistence in the northeast was juxtaposed by a rapid, widespread collapse in the southwest. Forests collapsed in the southwest apparently because ocean warming has-directly and indirectly-made this area inhospitable to kelp. Indeed, when modeling drivers of change using causal techniques from econometrics, we discovered that unusually high summer seawater temperatures the year prior, unusually high spring seawater temperatures, and high sea urchin densities each negatively impacted kelp abundance. Furthermore, the relative power and absolute impact of these drivers varied geographically. Our findings reveal that ocean warming is redefining the outcomes of top-down forcing in this system, whereby herbivore removal no longer predictably leads to a sustained dominance of foundational kelps but instead has led to a waning dominance (northeast) or the rise of a novel phase state defined by "turf" algae (southwest). Such findings indicate that limiting climate change and managing for low herbivore abundances will be essential for preventing further loss of the vast forests that still exist in northeast Maine. They also more broadly highlight that climate change is "rewriting the rules" of nature, and thus that ecological theory and practice must be revised to account for shifting species and processes.

Beyond the basics: A deep dive into parameter estimation for advanced PBPK and QSP models.

Physiologically-based pharmacokinetic (PBPK) models and quantitative systems pharmacology (QSP) models have contributed to drug development strategies. The parameters of these models are commonly estimated by capturing observed values using the nonlinear least-squares method. Software packages for PBPK and QSP modeling provide a range of parameter estimation algorithms. To choose the most appropriate method, modelers need to understand the basic concept of each approach. This review provides a general introduction to the key points of parameter estimation with a focus on the PBPK and QSP models, and the respective parameter estimation algorithms. The latter part assesses the performance of five parameter estimation algorithms - the quasi-Newton method, Nelder-Mead method, genetic algorithm, particle swarm optimization, and Cluster Gauss-Newton method - using three examples of PBPK and QSP modeling. The assessment revealed that some parameter estimation results were significantly influenced by the initial values. Moreover, the choice of algorithms demonstrating good estimation results heavily depends on factors such as model structure and the parameters to be estimated. To obtain credible parameter estimation results, it is advisable to conduct multiple rounds of parameter estimation under different conditions, employing various estimation algorithms.

Sensitivity to and Control of Distraction: Distractor-Entrained Oscillation and Frontoparietal EEG Gamma Synchronization.

While recent advancements have been made towards a better understanding of the involvement of the prefrontal cortex (PFC) in the context of cognitive control, the exact mechanism is still not fully understood. Successful behavior requires the correct detection of goal-relevant cues and resisting irrelevant distractions. Frontal parietal networks have been implicated as important for maintaining cognitive control in the face of distraction. The present study investigated the role of gamma-band power in distraction resistance and frontoparietal networks, as its increase is linked to cholinergic activity. We examined changes in gamma activity and their relationship to frontoparietal top-down modulation for distractor challenges and to bottom-up distractor processing. Healthy young adults were tested using a modified version of the distractor condition sustained attention task (dSAT) while wearing an EEG. The modified distractor was designed so that oscillatory activities could be entrained to it, and the strength of entrainment was used to assess the degree of distraction. Increased top-down control during the distractor challenge increased gamma power in the left parietal regions rather than the right prefrontal regions predicted from rodent studies. Specifically, left parietal gamma power increased in response to distraction where the amount of this increase was negatively correlated with the neural activity reflecting bottom-up distractor processing in the visual area. Variability in gamma power in right prefrontal regions was associated with increased response time variability during distraction. This may suggest that the right prefrontal region may contribute to the signaling needed for top-down control rather than its implementation.

Online Mixed-Bed Ion Exchange Chromatography for Native Top-Down Proteomics of Complex Mixtures.

Native top-down mass spectrometry (nTDMS) allows characterization of protein structure and noncovalent interactions with simultaneous sequence mapping and proteoform characterization. The majority of nTDMS studies utilize purified recombinant proteins, with significant challenges hindering application to endogenous systems. To perform native top-down proteomics (nTDP), where endogenous proteins from complex biological systems are analyzed by nTDMS, it is essential to separate proteins under nondenaturing conditions. However, it remains difficult to achieve high resolution with MS-compatible online chromatography while preserving protein tertiary structure and noncovalent interactions. Herein, we report the use of online mixed-bed ion exchange chromatography (IEC) to enable separation of endogenous proteins from complex mixtures under nondenaturing conditions, preserving noncovalent interactions for nTDP analysis. We have successfully detected large proteins (>146 kDa) and identified endogenous metal-binding and oligomeric protein complexes in human heart tissue lysate. The use of a mixed-bed stationary phase allowed retention and elution of proteins over a wide range of isoelectric points without altering the sample or mobile phase pH. Overall, our method provides a simple online IEC-MS platform that can effectively separate proteins from complex mixtures under nondenaturing conditions and preserve higher-order structure for nTDP applications.

A comprehensive review on preparation and functional application of the wood aerogel with natural cellulose framework.

As the traditional aerogel has defects such as poor mechanical properties, complicated preparation process, high energy consumption and non-renewable, wood aerogel as a new generation of aerogel shows unique advantages. With a natural cellulose framework, wood aerogel is a novel nano-porous material exhibiting exceptional properties such as light weight, high porosity, large specific surface area, and low thermal conductivity. Furthermore, its adaptability to further functionalization enables versatile applications across diverse fields. Driven by the imperative for sustainable development, wood aerogel as a renewable and eco-friendly material, has garnered significant attention from researchers. This review introduces preparation methods of wood aerogel based on the top-down strategy and analyzes the factors influencing their key properties intending to obtain wood aerogels with desirable properties. Avenues for realizing its functionality are also explored, and research progress across various domains are surveyed, including oil-water separation, conductivity and energy storage, as well as photothermal conversion. Finally, potential challenges associated with wood aerogel exploitation and utilization are addressed, alongside discussions on future prospects and research directions. The results emphasize the broad research value and future prospects of wood aerogels, which are poised to drive high-value utilization of wood and foster the development of green multifunctional aerogels.

MCP: Multi-Chicken Pose Estimation Based on Transfer Learning.

Poultry managers can better understand the state of poultry through poultry behavior analysis. As one of the key steps in behavior analysis, the accurate estimation of poultry posture is the focus of this research. This study mainly analyzes a top-down pose estimation method of multiple chickens. Therefore, we propose the "multi-chicken pose" (MCP), a pose estimation system for multiple chickens through deep learning. Firstly, we find the position of each chicken from the image via the chicken detector; then, an estimate of the pose of each chicken is made using a pose estimation network, which is based on transfer learning. On this basis, the pixel error (PE), root mean square error (RMSE), and image quantity distribution of key points are analyzed according to the improved chicken keypoint similarity (CKS). The experimental results show that the algorithm scores in different evaluation metrics are a mean average precision (mAP) of 0.652, a mean average recall (mAR) of 0.742, a percentage of correct keypoints (PCKs) of 0.789, and an RMSE of 17.30 pixels. To the best of our knowledge, this is the first time that transfer learning has been used for the pose estimation of multiple chickens as objects. The method can provide a new path for future poultry behavior analysis.

Prefrontal cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation.

Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical slow and spindle oscillations during non-REM sleep. Recent evidence suggests that high-frequency cortical ripples can also coordinate with hippocampal SWRs in support of consolidation; however, the contribution of cortical ripples to reactivation remains unclear. We used high-density, continuous recordings in the hippocampus (area CA1) and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples dissociated from SWRs are prevalent in NREM sleep and predominantly suppress hippocampal activity. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation rather than coordination, and this suppression is stronger for assemblies that are reactivated during coordinated CA1-PFC ripples for consolidation of recent experiences. Further, we show non-canonical, serial coordination of independent cortical ripples with slow and spindle oscillations, which are known signatures of memory consolidation. These results establish a role for prefrontal cortical ripples in top-down regulation of behaviorally relevant hippocampal representations during consolidation.