Firing rate models for gamma oscillations in I-I and E-I networks.

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.

A Cost-Effective Approach to Creating Large Silicone Rubber Molds Using Advanced Rigid Polyurethane Foam.

In practical applications, polyurethane (PU) foam must be rigid to meet the demands of various industries and provide comfort and protection in everyday life. PU foam components are extensively used in structural foam, thermal insulation, decorative panels, packaging, imitation wood, and floral foam, as well as in models and prototypes. Conventional technology for producing PU foam parts often leads to defects such as deformation, short shots, entrapped air, warpage, flash, micro-bubbles, weld lines, and voids. Therefore, the development of rigid PU foam parts has become a crucial research focus in the industry. This study proposes an innovative manufacturing process for producing rigid PU foam parts using silicone rubber molds (SRMs). The deformation of the silicone rubber mold can be predicted based on its wall thickness, following a trend equation with a correlation coefficient of 0.9951. The volume of the PU foam part can also be predicted by the weight of the PU foaming agent, as indicated by a trend equation with a correlation coefficient of 0.9824. The optimal weight ratio of the foaming agent to water, yielding the highest surface hardness, was found to be 5:1. The surface hardness of the PU foam part can also be predicted based on the weight of the water used, according to a proposed prediction equation with a correlation coefficient of 0.7517. The average surface hardness of the fabricated PU foam part has a Shore O hardness value of approximately 75. Foam parts made with 1.5 g of water added to 15 g of a foaming agent have the fewest internal pores, resulting in the densest interior. PU foam parts exhibit excellent mechanical properties when 3 g of water is added to the PU foaming agent, as evidenced by their surface hardness and compressive strength. Using rigid PU foam parts as a backing material in the proposed method can reduce rapid tool production costs by about 62%. Finally, an innovative manufacturing process for creating large SRMs using rigid PU foam parts as backing material is demonstrated.

Selenium spatial distribution and bioavailability of soil-plant systems in China: a comprehensive review.

Selenium (Se) has a dual nature, with beneficial and harmful effects on plants, essential for both humans and animals, playing a crucial role in ecosystem regulation. Insufficient Se in specific terrestrial environments raises concerns due to its potential to cause diseases, while excess Se can lead to severe toxicity. Thus, maintaining an optimal Se level is essential for living organisms. This review focuses first on Se transformation, speciation, and geochemical properties in soil, and then provides a concise overview of Se distribution in Chinese soil and crops, with a focus on the relationship between soil Se levels and parent materials. Additionally, this paper explores Se bioavailability, considering parent materials and soil physicochemical properties, using partial least squares path modeling for analysis. This paper aimed to be a valuable resource for effectively managing Se-enriched soil resources, contributing to a better understanding of Se role in ecosystems.

Unraveling the complexity of rapid eye movement microstates: insights from nonlinear EEG analysis.

Although rapid eye movement (REM) sleep is conventionally treated as a unified state, it comprises two distinct microstates: phasic and tonic REM. Recent research emphasizes the importance of understanding the interplay between these microstates, hypothesizing their role in transient shifts between sensory detachment and external awareness. Previous studies primarily employed linear metrics to probe cognitive states, such as oscillatory power, while in this study, we adopt Lempel-Ziv Complexity (LZC), to examine the nonlinear features of electroencephalographic (EEG) data from the REM microstates and to gain complementary insights into neural dynamics during REM sleep. Our findings demonstrate a noteworthy reduction in LZC during phasic REM compared to tonic REM states, signifying diminished EEG complexity in the former. Additionally, we noted a negative correlation between decreased LZC and delta band power, along with a positive correlation with alpha band power. This study highlights the potential of nonlinear EEG metrics, particularly LZC, in elucidating the distinct features of REM microstates. Overall, this research contributes to advancing our understanding of the complex dynamics within REM sleep and opens new avenues for exploring its implications in both clinical and nonclinical contexts.

Targeting macrophages with multifunctional nanoparticles to detect and prevent atherosclerotic cardiovascular disease.

Despite the emergence of novel diagnostic, pharmacological, interventional, and prevention strategies, atherosclerotic cardiovascular disease remains a significant cause of morbidity and mortality. Nanoparticle (NP)-based platforms encompass diverse imaging, delivery, and pharmacological properties that provide novel opportunities for refining diagnostic and therapeutic interventions for atherosclerosis at the cellular and molecular levels. Macrophages play a critical role in atherosclerosis and therefore represent an important disease-related diagnostic and therapeutic target, especially given their inherent ability for passive and active NP uptake. In this review, we discuss an array of inorganic, carbon-based, and lipid-based NPs that provide magnetic, radiographic, and fluorescent imaging capabilities for a range of highly promising research and clinical applications in atherosclerosis. We discuss the design of NPs that target a range of macrophage-related functions such as lipoprotein oxidation, cholesterol efflux, vascular inflammation, and defective efferocytosis. We also provide examples of NP systems that were developed for other pathologies such as cancer and highlight their potential for repurposing in cardiovascular disease. Finally, we discuss the current state of play and the future of theranostic NPs. Whilst this is not without its challenges, the array of multifunctional capabilities that are possible in NP design ensures they will be part of the next frontier of exciting new therapies that simultaneously improve the accuracy of plaque diagnosis and more effectively reduce atherosclerosis with limited side effects.

Genome-wide CRISPR screens identify novel regulators of wild-type and mutant p53 stability.

Tumor suppressor p53 (TP53) is frequently mutated in cancer, often resulting not only in loss of its tumor-suppressive function but also acquisition of dominant-negative and even oncogenic gain-of-function traits. While wild-type p53 levels are tightly regulated, mutants are typically stabilized in tumors, which is crucial for their oncogenic properties. Here, we systematically profiled the factors that regulate protein stability of wild-type and mutant p53 using marker-based genome-wide CRISPR screens. Most regulators of wild-type p53 also regulate p53 mutants, except for p53 R337H regulators, which are largely private to this mutant. Mechanistically, FBXO42 emerged as a positive regulator for a subset of p53 mutants, working with CCDC6 to control USP28-mediated mutant p53 stabilization. Additionally, C16orf72/HAPSTR1 negatively regulates both wild-type p53 and all tested mutants. C16orf72/HAPSTR1 is commonly amplified in breast cancer, and its overexpression reduces p53 levels in mouse mammary epithelium leading to accelerated breast cancer. This study offers a network perspective on p53 stability regulation, potentially guiding strategies to reinforce wild-type p53 or target mutant p53 in cancer.

Enhancing Oxygen Reduction on Fe Single-Atom Catalysts by Tuning Noncovalent Interactions in Electrode/Electrolyte Interfaces.

Highly efficient electrochemical interfaces are significant for the oxygen reduction reaction (ORR). However, previous efforts have been mainly paid to design catalytic sites with high intrinsic activity and neglect the electrode/electrolyte interfaces, especially the noncovalent interactions in the outer Helmholtz plane (OHP). Herein, an Fe-N-C single-atom catalyst is synthesized and acts as the model catalyst to demonstrate the effect of noncovalent interactions on the ORR performance. Two specific molecules of THA+ and TEA+ with different structures and functional groups have been selected to tune the OHP through noncovalent interactions. TEA+ can adjust the OHP, improve the oxygen diffusion coefficient, and increase the double-layer capacitance. Therefore, TEA+ enhances the activity, selectivity, and stability of Fe-N-C single-atom catalysts toward the ORR. This provides a new approach to finding new directions in designing electrochemical interfaces beyond the intrinsic catalytic sites in acidic electrolytes.

Research Progress of Selenium-Enriched Foods.

Selenium is an essential micronutrient that plays a crucial role in maintaining human health. Selenium deficiency is seriously associated with various diseases such as Keshan disease, Kashin-Beck disease, cataracts, and others. Conversely, selenium supplementation has been found to have multiple effects, including antioxidant, anti-inflammatory, and anticancer functions. Compared with inorganic selenium, organic selenium exhibits higher bioactivities and a wider range of safe concentrations. Consequently, there has been a significant development of selenium-enriched foods which contain large amounts of organic selenium in order to improve human health. This review summarizes the physiological role and metabolism of selenium, the development of selenium-enriched foods, the physiological functions of selenium-enriched foods, and provides an analysis of total selenium and its species in selenium-enriched foods, with a view to laying the foundation for selenium-enriched food development.

Highly Durable PtNi Alloy on Sb-Doped SnO2 for Oxygen Reduction Reaction with Strong Metal-Support Interaction.

Carbon-supported Pt is currently used as catalyst for oxygen reduction reaction (ORR) in fuel cells but is handicapped by carbon corrosion at high potential. Herein, a stable PtNi/SnO2 interface structure has been designed and achieved by a two-step solvothermal method. The robust and conductive Sb-doped SnO2 supports provide sufficient surfaces to confine PtNi alloy. Moreover, PtNi/Sb0.11 SnO2 presents a more strongly coupled Pt-SnO2 interface with lattice overlap of Pt (111) and SnO2 (110), together with enhanced electron transfer from SnO2 to Pt. Therefore, PtNi/Sb0.11 SnO2 exhibits a high catalytic activity for ORR with a half-wave potential of 0.860 V versus reversible hydrogen electrode (RHE) and a mass activity of 166.2 mA mgPt -1 @0.9 V in 0.1 M HClO4 electrolyte. Importantly, accelerated degradation testing (ADT) further identify the inhibition of support corrosion and agglomeration of Pt-based active nanoparticles in PtNi/Sb0.11 SnO2 . This work highlights the significant importance of modulating metal-support interactions for improving the catalytic activity and durability of electrocatalysts.

Dynamic signatures of the Eureka effect: an EEG study.

The Eureka effect refers to the common experience of suddenly solving a problem. Here, we study this effect in a pattern recognition paradigm that requires the segmentation of complex scenes and recognition of objects on the basis of Gestalt rules and prior knowledge. In the experiments, both sensory evidence and prior knowledge were manipulated in order to obtain trials that do or do not converge toward a perceptual solution. Subjects had to detect objects in blurred scenes and indicate recognition with manual responses. Neural dynamics were assessed with high-density Electroencephalography (EEG) recordings. The results show significant changes of neural dynamics with respect to spectral distribution, coherence, phase locking, and fractal dimensionality. The Eureka effect was associated with increased coherence of oscillations in the alpha and theta bands over widely distributed regions of the cortical mantle predominantly in the right hemisphere. This increase in coherence was associated with decreased beta power over parietal and central regions and with decreased alpha power over frontal and occipital areas. In addition, there was a right hemisphere-lateralized reduction of fractal dimensionality. We propose that the Eureka effect requires cooperation of cortical regions involved in working memory, creative thinking, and the control of attention.

In vivo CRISPR screens reveal Serpinb9 and Adam2 as regulators of immune therapy response in lung cancer.

How the genetic landscape governs a tumor's response to immunotherapy remains poorly understood. To assess the immune-modulatory capabilities of 573 genes associated with altered cytotoxicity in human cancers, here we perform CRISPR/Cas9 screens directly in mouse lung cancer models. We recover the known immune evasion factors Stat1 and Serpinb9 and identify the cancer testis antigen Adam2 as an immune modulator, whose expression is induced by KrasG12D and further elevated by immunotherapy. Using loss- and gain-of-function experiments, we show that ADAM2 functions as an oncogene by restraining interferon and TNF cytokine signaling causing reduced presentation of tumor-associated antigens. ADAM2 also restricts expression of the immune checkpoint inhibitors PDL1, LAG3, TIGIT and TIM3 in the tumor microenvironment, which might explain why ex vivo expanded and adoptively transferred cytotoxic T-cells show enhanced cytotoxic efficacy in ADAM2 overexpressing tumors. Together, direct in vivo CRISPR/Cas9 screens can uncover genetic alterations that control responses to immunotherapies.

Corrigendum: NudC L279P mutation destabilizes filamin a by inhibiting the Hsp90 chaperoning pathway and suppresses cell migration.

[This corrects the article DOI: 10.3389/fcell.2021.671233.].

Bistability at the onset of neuronal oscillations.

The Hodgkin-Huxley (HH) model and squid axon (bathed in reduced Ca2+) fire repetitively for steady current injection. Moreover, for a current-range just suprathreshold, repetitive firing coexists with a stable steady state. Neuronal excitability, as such, shows bistability and hysteresis providing the opportunity for the system to perform as switchable between firing and non-firing states with transient input and providing the backbone as a dynamical mechanism for bursting oscillations. Some conditions for bistability can be derived by intricate analysis (bifurcation theory) and characterized by simulation, but conditions for emergence and robustness of such bistability do not typically follow from intuition. Here, we demonstrate with a semi-quantitative two-variable, V-w, reduction of the HH model features that promote/reduce bistability. Visualization of flow and trajectories in the V-w phase plane provides an intuitive grasp for bistability. The geometry of action potential recovery involves a late phase during which the dynamic negative feedback of [Formula: see text] inactivation and [Formula: see text] activation over/undershoot, respectively, their resting values, thereby leading to hyperexcitabilty and an intrinsically generated opportunity to by-pass the spiral-like stable rest state and initiate the next spike upstroke. We illustrate control of bistability and dependence of the degree of hysteresis on recovery timescales and gating properties. Our dynamical dissection reveals the strongly attracting depolarized phase of the spike, enabling approximations like the resetting feature of adapting integrate-and-fire models. We extend our insights and show that the Morris-Lecar model can also exhibit robust bistability.

Effect of nitrite on hydrolysis-acidification, biogas production and microbial community in semi-continuous two-phase anaerobic digestion of sewage sludge.

Previous study found that the pre-treatment of sewage sludge with nitrite improves the biogas production during the mono/two-phase anaerobic digestion (AD) using batch biochemical methane potential tests. In this study, the effects of nitrite on hydrolysis-acidification, biogas production, volatile solids destruction and microbial composition in semi-continuous two-phase AD of sewage sludge were investigated. The addition of nitrite promotes sludge organic matter solubilization (+484%) and VFAs production (+98.9%), and causes an increase in the VS degradation rate during the AD process (+8.7%). The comparison of biogas production from the acidogenic and methanogenic reactors with or without the addition of nitrite implies that the nitrite has no significant effect on the overall biogas production of two-phase sludge AD process. High-throughput sequencing analysis shows that the microbial communities of bacteria and archaea in two-phase AD reactors significantly changes after the addition of nitrite. Vulcanibacillus (bacteria) and Candidatus Methanofastidiosum (archaea) become the dominant genera in the acidogenic and methanogenic reactors with the nitrite respectively. These findings provide new insights about using nitrite to promote the organic matter degradation of sewage sludge in a semi-continuous two-phase AD system.

Nonlinear EEG signatures of mind wandering during breath focus meditation.

In meditation practices that involve focused attention to a specific object, novice practitioners often experience moments of distraction (i.e., mind wandering). Previous studies have investigated the neural correlates of mind wandering during meditation practice through Electroencephalography (EEG) using linear metrics (e.g., oscillatory power). However, their results are not fully consistent. Since the brain is known to be a chaotic/nonlinear system, it is possible that linear metrics cannot fully capture complex dynamics present in the EEG signal. In this study, we assess whether nonlinear EEG signatures can be used to characterize mind wandering during breath focus meditation in novice practitioners. For that purpose, we adopted an experience sampling paradigm in which 25 participants were iteratively interrupted during meditation practice to report whether they were focusing on the breath or thinking about something else. We compared the complexity of EEG signals during mind wandering and breath focus states using three different algorithms: Higuchi's fractal dimension (HFD), Lempel-Ziv complexity (LZC), and Sample entropy (SampEn). Our results showed that EEG complexity was generally reduced during mind wandering relative to breath focus states. We conclude that EEG complexity metrics are appropriate to disentangle mind wandering from breath focus states in novice meditation practitioners, and therefore, they could be used in future EEG neurofeedback protocols to facilitate meditation practice.

Detection of rare prostate cancer cells in human urine offers prospect of non-invasive diagnosis.

Two molecular cytology approaches, (i) time-gated immunoluminescence assay (TGiA) and (ii) Raman-active immunolabeling assay (RiA), have been developed to detect prostate cancer (PCa) cells in urine from five prostate cancer patients. For TGiA, PCa cells stained by a biocompatible europium chelate antibody-conjugated probe were quantitated by automated time-gated microscopy (OSAM). For RiA, PCa cells labeled by antibody-conjugated Raman probe were detected by Raman spectrometer. TGiA and RiA were first optimized by the detection of PCa cultured cells (DU145) spiked into control urine, with TGiA-OSAM showing single-cell PCa detection sensitivity, while RiA had a limit of detection of 4-10 cells/mL. Blinded analysis of each patient urine sample, using MIL-38 antibody specific for PCa cells, was performed using both assays in parallel with control urine. Both assays detected very low abundance PCa cells in patient urine (3-20 PCa cells per mL by TGiA, 4-13 cells/mL by RiA). The normalized mean of the detected PCa cells per 1 ml of urine was plotted against the clinical data including prostate specific antigen (PSA) level and Clinical Risk Assessment for each patient. Both cell detection assays showed correlation with PSA in the high risk patients but aligned with the Clinical Assessment rather than with PSA levels of the low/intermediate risk patients. Despite the limited available urine samples of PCa patients, the data presented in this proof-of-principle work is promising for the development of highly sensitive diagnostic urine tests for PCa.