Exploring the Therapeutic Potential of Coumarin-thiazolotriazole Pharmacophores for SARS-CoV-2 Spike Protein through In-vitro and In-silico Evaluation.

INTRODUCTION: The pandemic caused by SARS-CoV-2 significantly impacted human life around the globe. Numerous unexpected modifications of the SARS-CoV-2 genome have resulted in the emergence of new types and have caused great concern globally. METHOD: Inhibitory effects of bioactive phytochemicals derived from natural and synthetic sources are promising for pathogenic viruses. in vitro and in silico techniques were used in the current study to identify novel inhibitors of coumarin clubbed thiazolo[3,2-b][1,2,4]triazoles against the SARS-CoV-2 spike protein. RESULT: Interestingly, all the tested molecules demonstrated substantial inhibition of spike protein with 91.81-57.90% inhibition. The spike protein was remarkably inhibited by compounds 6k (91.83%), 6j (89.75%), 6m (87.69%),6i (86.60%), 6l (85.40%), 6h (84.70%), 6l (84.70%), 6g (83.40%), 6b (82.60%), 6f (81.90%), while compounds 6d 6a, 6c, and 6e exhibited significant activity against spike protein with 79.60%, 77.10%, 75.30%, and 57.90% inhibition, respectively. The binding mechanism of these novel inhibitors with spike protein was deduced in silico, which reflects that the active molecules firmly bind with the receptor binding domain (RBD) of spike protein, thereby inhibiting its function. CONCLUSION: The combined in vitro and in silico investigations unfold the therapeutic potential of coumarin-thiazolotriazole scaffolds in the treatment of SARS-CoV-2 infection.

Architectural organization and in situ fusion protein structure of lymphocytic choriomeningitis virus.

Arenaviruses exist globally and can cause hemorrhagic fever and neurological diseases, exemplified by the zoonotic pathogen lymphocytic choriomeningitis virus (LCMV). The structures of individual LCMV proteins or their fragments have been reported, but the architectural organization and the nucleocapsid assembly mechanism remain elusive. Importantly, the in situ structure of the arenavirus fusion protein complex (glycoprotein complex, GPC) as present on the virion prior to fusion, particularly with its integral stable signal peptide (SSP), has not been shown, hindering efforts such as structure-based vaccine design. Here, we have determined the in situ structure of LCMV proteins and their architectural organization in the virion by cryogenic electron tomography. The tomograms reveal the global distribution of GPC, matrix protein Z, and the contact points between the viral envelope and nucleocapsid. Subtomogram averaging yielded the in situ structure of the mature GPC with its transmembrane domain intact, revealing the GP2-SSP interface and the endodomain of GP2. The number of RNA-dependent RNA polymerase L molecules packaged within each virion varies, adding new perspectives to the infection mechanism. Together, these results delineate the structural organization of LCMV and offer new insights into its mechanism of LCMV maturation, egress, and cell entry. IMPORTANCE: The impact of COVID-19 on public health has highlighted the importance of understanding zoonotic pathogens. Lymphocytic choriomeningitis virus (LCMV) is a rodent-borne human pathogen that causes hemorrhagic fever. Herein, we describe the in situ structure of LCMV proteins and their architectural organization on the viral envelope and around the nucleocapsid. The virion structure reveals the distribution of the surface glycoprotein complex (GPC) and the contact points between the viral envelope and the underlying matrix protein, as well as the association with the nucleocapsid. The morphology and sizes of virions, as well as the number of RNA polymerase L inside each virion vary greatly, highlighting the fast-changing nature of LCMV. A comparison between the in situ GPC trimeric structure and prior ectodomain structures identifies the transmembrane and endo domains of GPC and key interactions among its subunits. The work provides new insights into LCMV assembly and informs future structure-guided vaccine design.

AlphaFold2 Modeling and Molecular Dynamics Simulations of the Conformational Ensembles for the SARS-CoV-2 Spike Omicron JN.1, KP.2 and KP.3 Variants: Mutational Profiling of Binding Energetics Reveals Epistatic Drivers of the ACE2 Affinity and Escape Hotspots of Antibody Resistance.

The most recent wave of SARS-CoV-2 Omicron variants descending from BA.2 and BA.2.86 exhibited improved viral growth and fitness due to convergent evolution of functional hotspots. These hotspots operate in tandem to optimize both receptor binding for effective infection and immune evasion efficiency, thereby maintaining overall viral fitness. The lack of molecular details on structure, dynamics and binding energetics of the latest FLiRT and FLuQE variants with the ACE2 receptor and antibodies provides a considerable challenge that is explored in this study. We combined AlphaFold2-based atomistic predictions of structures and conformational ensembles of the SARS-CoV-2 spike complexes with the host receptor ACE2 for the most dominant Omicron variants JN.1, KP.1, KP.2 and KP.3 to examine the mechanisms underlying the role of convergent evolution hotspots in balancing ACE2 binding and antibody evasion. Using the ensemble-based mutational scanning of the spike protein residues and computations of binding affinities, we identified binding energy hotspots and characterized the molecular basis underlying epistatic couplings between convergent mutational hotspots. The results suggested the existence of epistatic interactions between convergent mutational sites at L455, F456, Q493 positions that protect and restore ACE2-binding affinity while conferring beneficial immune escape. To examine immune escape mechanisms, we performed structure-based mutational profiling of the spike protein binding with several classes of antibodies that displayed impaired neutralization against BA.2.86, JN.1, KP.2 and KP.3. The results confirmed the experimental data that JN.1, KP.2 and KP.3 harboring the L455S and F456L mutations can significantly impair the neutralizing activity of class 1 monoclonal antibodies, while the epistatic effects mediated by F456L can facilitate the subsequent convergence of Q493E changes to rescue ACE2 binding. Structural and energetic analysis provided a rationale to the experimental results showing that BD55-5840 and BD55-5514 antibodies that bind to different binding epitopes can retain neutralizing efficacy against all examined variants BA.2.86, JN.1, KP.2 and KP.3. The results support the notion that evolution of Omicron variants may favor emergence of lineages with beneficial combinations of mutations involving mediators of epistatic couplings that control balance of high ACE2 affinity and immune evasion.

Development of feline infectious peritonitis diagnosis system by using CatBoost algorithm.

This study employed machine learning techniques to predict the rate of feline infectious peritonitis (FIP) diagnoses, with a specific focus on mutations in the spike protein gene of the feline coronavirus (FCoV). FIP is a fatal viral disease affecting the peritoneum of cats and is primarily caused by mutations in FCoV. Its diagnosis largely relies on evaluations of various biomarkers and clinical symptoms. The current analysis of FCoV spike protein gene mutations exhibits certain limitations. To address this problem, the present study employed a large dataset-comprising information on FCoV copy numbers, spike protein mutation outcomes, and related clinical data-and used machine learning models to analyze the association between spike protein gene mutations and FIP diagnosis. Various algorithms were used to establish highly accurate predictive models, namely logistic regression, random forest, decision tree, neural network, support vector machine, gradient boosting tree, and categorical boosting (CatBoost) algorithms. The model obtained using the CatBoost algorithm was discovered to have accuracy of 0.9541. Accordingly, a highly accurate predictive model was developed to enable early diagnosis of FIP and improve the rate of survival in cats. The application of machine learning technology in this study yielded research findings that provide veterinarians with effective tools for managing and preventing FIP, a painful and deadly disease for cats. This study is a pioneering work in the systematic application of multiple machine learning models to the prediction of FIP and comparison of performance results to improve diagnostic accuracy and efficiency. This study is the first of its kind in the field of FIP.

SARS-CoV-2 Genotyping Highlights the Challenges in Spike Protein Drift Independent of Other Essential Proteins.

As of 2024, SARS-CoV-2 continues to propagate and drift as an endemic virus, impacting healthcare for years. The largest sequencing initiative for any species was initiated to combat the virus, tracking changes over time at a full virus base-pair resolution. The SARS-CoV-2 sequencing represents a unique opportunity to understand selective pressures and viral evolution but requires cross-disciplinary approaches from epidemiology to functional protein biology. Within this work, we integrate a two-year genotyping window with structural biology to explore the selective pressures of SARS-CoV-2 on protein insights. Although genotype and the Spike (Surface Glycoprotein) protein continue to drift, most SARS-CoV-2 proteins have had few amino acid alterations. Within Spike, the high drift rate of amino acids involved in antibody evasion also corresponds to changes within the ACE2 binding pocket that have undergone multiple changes that maintain functional binding. The genotyping suggests selective pressure for receptor specificity that could also confer changes in viral risk. Mapping of amino acid changes to the structures of the SARS-CoV-2 co-transcriptional complex (nsp7-nsp14), nsp3 (papain-like protease), and nsp5 (cysteine protease) proteins suggest they remain critical factors for drug development that will be sustainable, unlike those strategies targeting Spike.

Electromagnetic waves destabilize the SARS-CoV-2 Spike protein and reduce SARS-CoV-2 Virus-Like Particle (SC2-VLP) infectivity.

Infection and transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to pose a global public health concern. Using electromagnetic waves represents an alternative strategy to inactivate pathogenic viruses such as SARS-CoV-2 and reduce overall transmission. However, whether electromagnetic waves reduce SARS-CoV-2 infectivity is unclear. Here, we adapted a coplanar waveguide (CPW) to identify electromagnetic waves that could neutralize SARS-CoV-2 virus-like particles (SC2-VLPs). Treatment of SC2-VLPs, particularly at frequencies between 2.5-3.5 GHz at an electric field of 400 V/m for 2 minutes, reduced infectivity. Exposure to a frequency of 3.1 GHz decreased the binding of SC2-VLPs to antibodies directed against the Spike S1 subunit receptor binding domain (RBD). These results suggest that electromagnetic waves alter the conformation of Spike, thereby reducing viral attachment to host cell receptors. Overall, this data provides proof-of-concept in using electromagnetic waves for sanitation and prevention efforts to curb the transmission of SARS-CoV-2 and potentially other pathogenic enveloped viruses.

Exploring the Potential Long-term Impact of SARS-CoV-2 on Protein Misfolding and Amyloid-related Conditions.

The long-term impact of the COVID-19 pandemic concerns risk to human health, particularly its potential association with protein misfolding and amyloidosis. This review article explores the causality relationship between SARS-CoV-2 infection, and protein misfolding, leading to amyloid-related conditions. It delves into the mechanisms by which viral proteins may accelerate amyloid formation, exacerbating post-infection complications, including neurological sequelae. Drawing from interdisciplinary research and clinical observations, the potential links between COVID-19, vaccination, and amyloidosis, emphasize the importance of understanding the longterm effect of post-COVID symptoms. This review examines the potential role of COVID-19-related proteins in the formation of amyloid in other related proteins of amyloidosis.

[Current progress on characteristics of intracranial electrophysiology related to prolonged disorders of consciousness].

Prolonged disorders of consciousness (pDOC) are pathological conditions of alterations in consciousness caused by various severe brain injuries, profoundly affecting patients' life ability and leading to a huge burden for both the family and society. Exploring the mechanisms underlying pDOC and accurately assessing the level of consciousness in the patients with pDOC provide the basis of developing therapeutic strategies. Research of non-invasive functional neuroimaging technologies, such as functional magnetic resonance (fMRI) and scalp electroencephalography (EEG), have demonstrated that the generation, maintenance and disorders of consciousness involve functions of multiple cortical and subcortical brain regions, and their networks. Invasive intracranial neuroelectrophysiological technique can directly record the electrical activity of subcortical or cortical neurons with high signal-to-noise ratio and spatial resolution, which has unique advantages and important significance for further revealing the brain function and disease mechanism of pDOC. Here we reviewed the current progress of pDOC research based on two intracranial electrophysiological signals, spikes reflecting single-unit activity and field potential reflecting multi-unit activities, and then discussed the current challenges and gave an outlook on future development, hoping to promote the study of pathophysiological mechanisms related to pDOC and provide guides for the future clinical diagnosis and therapy of pDOC.

Convergence of SARS-CoV-2 spike antibody levels to a population immune setpoint.

BACKGROUND: Individual immune responses to SARS-CoV-2 are well-studied, while the combined effect of these responses on population-level immune dynamics remains poorly understood. Given the key role of population immunity on pathogen transmission, delineation of the factors that drive population immune evolution has critical public health implications. METHODS: We enrolled individuals 5 years and older selected using a multistage cluster survey approach in the Northwest and Southeast of the Dominican Republic. Paired blood samples were collected mid-pandemic (Aug 2021) and late pandemic (Nov 2022). We measured serum pan-immunoglobulin antibodies against the SARS-CoV-2 spike protein. Generalized Additive Models (GAMs) and random forest models were used to analyze the relationship between changes in antibody levels and various predictor variables. Principal component analysis and partial dependence plots further explored the relationships between predictors and antibody changes. FINDINGS: We found a transformation in the distribution of antibody levels from an irregular to a normalized single peak Gaussian distribution that was driven by titre-dependent boosting. This led to the convergence of antibody levels around a common immune setpoint, irrespective of baseline titres and vaccination profile. INTERPRETATION: Our results suggest that titre-dependent kinetics driven by widespread transmission direct the evolution of population immunity in a consistent manner. These findings have implications for targeted vaccination strategies and improved modeling of future transmission, providing a preliminary blueprint for understanding population immune dynamics that could guide public health and vaccine policy for SARS-CoV-2 and potentially other pathogens. FUNDING: The study was primarily funded by the Centers for Disease Control and Prevention grant U01GH002238 (EN). Salary support was provided by Wellcome Trust grant 206250/Z/17/Z (AK) and the Australian National Health and Medical Research Council Investigator grant APP1158469 (CLL).

Temporal and Potential Predictive Relationships between Sleep Spindle Density and Spike-and-Wave Discharges.

Spike-and-wave discharges (SWDs) and sleep spindles are characteristic electroencephalographic (EEG) hallmarks of absence seizures and nonrapid eye movement sleep, respectively. They are commonly generated by the cortico-thalamo-cortical network including the thalamic reticular nucleus (TRN). It has been reported that SWD development is accompanied by a decrease in sleep spindle density in absence seizure patients and animal models. However, whether the decrease in sleep spindle density precedes, coincides with, or follows, the SWD development remains unknown. To clarify this, we exploited Pvalb-tetracycline transactivator (tTA)::tetO-ArchT (PV-ArchT) double-transgenic mouse, which can induce an absence seizure phenotype in a time-controllable manner by expressing ArchT in PV neurons of the TRN. In these mice, EEG recordings demonstrated that a decrease in sleep spindle density occurred 1 week before the onset of typical SWDs, with the expression of ArchT. To confirm such temporal relationship observed in these genetic model mice, we used a gamma-butyrolactone (GBL) pharmacological model of SWDs. Prior to GBL administration, we administered caffeine to wild-type mice for 3 consecutive days to induce a decrease in sleep spindle density. We then administered low-dose GBL, which cannot induce SWDs in normally conditioned mice but led to the occurrence of SWDs in caffeine-conditioned mice. These findings indicate a temporal relationship in which the decrease in sleep spindle density consistently precedes SWD development. Furthermore, the decrease in sleep spindle activity may have a role in facilitating the development of SWDs. Our findings suggest that sleep spindle reductions could serve as early indicators of seizure susceptibility.

Formation and retrieval of cell assemblies in a biologically realistic spiking neural network model of area CA3 in the mouse hippocampus.

The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of cell assemblies enable these functions. Yet, how cell assemblies are formed and retrieved in a full-scale spiking neural network (SNN) of CA3 that incorporates the observed diversity of neurons and connections within this circuit is not well understood. Here, we demonstrate that a data-driven SNN model quantitatively reflecting the neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, and long-term plasticity of the mouse CA3 is capable of robust auto-association and pattern completion via cell assemblies. Our results show that a broad range of assembly sizes could successfully and systematically retrieve patterns from heavily incomplete or corrupted cues after a limited number of presentations. Furthermore, performance was robust with respect to partial overlap of assemblies through shared cells, substantially enhancing memory capacity. These novel findings provide computational evidence that the specific biological properties of the CA3 circuit produce an effective neural substrate for associative learning in the mammalian brain.

The Inhibiting Effect of GB-2, (+)-Catechin, Theaflavin, and Theaflavin 3-Gallate on Interaction between ACE2 and SARS-CoV-2 EG.5.1 and HV.1 Variants.

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, continues to pose significant global health challenges. The results demonstrated that GB-2 at 200 µg/mL effectively increased the population of 293T-ACE2 cells with low RBD binding for both SARS-CoV-2 Omicron EG.5.1 and HV.1 variants by dual-color flow cytometry, indicating its ability to inhibit virus attachment. Further investigation revealed that (+)-catechin at 25 and 50 µg/mL did not significantly alter the ACE2-RBD interaction for the EG.5.1 variant. In contrast, theaflavin showed inhibitory effects at both 25 and 50 µg/mL for EG.5.1, while only the higher concentration was effective for HV.1. Notably, theaflavin 3-gallate exhibited a potent inhibition of ACE2-RBD binding for both variants at both concentrations tested. Molecular docking studies provided insight into the binding mechanisms of theaflavin and theaflavin 3-gallate with the RBD of EG.5.1 and HV.1 variants. Both compounds showed favorable docking scores, with theaflavin 3-gallate demonstrating slightly lower scores (-8 kcal/mol) compared to theaflavin (-7 kcal/mol) for both variants. These results suggest stable interactions between the compounds and key residues in the RBD, potentially explaining their inhibitory effects on virus attachment. In conclusion, GB-2, theaflavin, and theaflavin 3-gallate demonstrate significant potential as inhibitors of the ACE2-RBD interaction in Omicron variants, highlighting their therapeutic promise against COVID-19. However, these findings are primarily based on computational and in vitro studies, necessitating further in vivo research and clinical trials to confirm their efficacy and safety in humans.

Effects of Paclobutrazol on Reproductive and Vegetative Traits of Phalaenopsis Join Grace 'TH288-4'.

Phalaenopsis is the most popular potted plant worldwide. However, its typically long stalks often lead to increased shipping costs and risks. This study investigates the effectiveness of varying the concentration, timing, and frequency of paclobutrazol (PP333) applications on shortening the stalk of Phalaenopsis Join Grace 'TH288-4'. Concurrently, it also examines the potential for producing visually appealing and single-flower potted phalaenopsis products by means of truncation. Mature phalaenopsis plants were moved to a cool room in the seventh week to induce flowering. Four experimental groups were established based on different PP333 application schedules: the control (CK) group, with reverse osmosis water application in the second week; the T2 group, with a single application in the second week; the T2T3 group, with applications in both the second and third weeks; and the T7T8 group, with applications in the seventh and eighth weeks. The PP333 concentrations used were 250, 500, 750, and 1000 mg·L-1, applied as foliar sprays. The results showed that the shortest stalks, measured from the base to the first flower, were observed in the T2 group treated with PP333 at 750 mg·L-1 and in the T2T3 group with PP333 at 500, 750, and 1000 mg·L-1. These treatments resulted in stalk lengths of 19.18-22.17 cm, which are 67.2-71.6% shorter than the controls. PP333 application had minimal effect on the stalk diameter, pedicel length, flower width, length, and length/width ratio. However, root diameter was thicker in plants treated with PP333 compared with the control plants. For producing single-flower phalaenopsis, a foliar spray of 750 mg·L-1 PP333 is recommended approximately a month before moving the plants to cooler conditions, followed by truncation, retaining only the first flower. As a result, this study establishes a PP333 treatment protocol for phalaenopsis, offering a strategy to effectively shorten the stalks.

Discovery and characterization of a pan-betacoronavirus S2-binding antibody.

The continued emergence of deadly human coronaviruses from animal reservoirs highlights the need for pan-coronavirus interventions for effective pandemic preparedness. Here, using linking B cell receptor to antigen specificity through sequencing (LIBRA-seq), we report a panel of 50 coronavirus antibodies isolated from human B cells. Of these, 54043-5 was shown to bind the S2 subunit of spike proteins from alpha-, beta-, and deltacoronaviruses. A cryoelectron microscopy (cryo-EM) structure of 54043-5 bound to the prefusion S2 subunit of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike defined an epitope at the apex of S2 that is highly conserved among betacoronaviruses. Although non-neutralizing, 54043-5 induced Fc-dependent antiviral responses in vitro, including antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP). In murine SARS-CoV-2 challenge studies, protection against disease was observed after introduction of Leu234Ala, Leu235Ala, and Pro329Gly (LALA-PG) substitutions in the Fc region of 54043-5. Together, these data provide new insights into the protective mechanisms of non-neutralizing antibodies and define a broadly conserved epitope within the S2 subunit.

Technical survey of end-to-end signal processing in BCIs using invasive MEAs.

Modern brain-computer interfaces and neural implants allow interaction between the tissue, the user and the environment, where people suffer from neurodegenerative diseases or injuries. This interaction can be achieved by using penetrating/invasive microelectrodes for extracellular recordings and stimulation, such as Utah or Michigan arrays. The application-specific signal processing of the extracellular recording enables the detection of interactions and enables user interaction. For example, it allows to read out movement intentions from recordings of brain signals for controlling a prosthesis or an exoskeleton. To enable this, computationally complex algorithms are used in research that cannot be executed onchip or on embedded systems. Therefore, an optimization of the end-to-end processing pipeline, from the signal condition on the electrode array over the analog pre-processing to spike-sorting and finally the neural decoding process, is necessary for hardware inference in order to enable a local signal processing in real-time and to enable a compact system for achieving a high comfort level. is This paper presents a survey of system architectures and algorithms for end-to-end signal processing pipelines of neural activity on the hardware of such neural devices, including (i) on-chip signal pre-processing, (ii) spike-sorting on-chip or on embedded hardware and (iii) neural decoding on workstations. A particular focus for the hardware implementation is on low-power electronic design and artifact-robust algorithms with low computational effort and very short latency. For this, current challenges and possible solutions with support of novel machine learning techniques are presented in brief. In addition, we describe our future vision for next-generation BCIs.

The Assessment of Anti-SARS-CoV-2 Antibodies in Different Vaccine Platforms: A Systematic Review and Meta-Analysis of COVID-19 Vaccine Clinical Trial Studies.

BACKGROUND AND OBJECTIVE: The COVID-19 pandemic spread rapidly throughout the world and caused millions of deaths globally. Several vaccines have been developed to control the COVID-19 pandemic and reduce the burden it placed on public health. This study aimed to assess the efficacy of different vaccine platforms in inducing potent antibody responses. Moreover, the seroconversion rate and common side effects of vaccine platforms were evaluated. METHODS: This meta-analysis included clinical trials of COVID-19 vaccines that met the eligibility criteria. Electronic databases (including PubMed, Scopus, and Web of Science) and Google Scholar search engine were searched for eligible studies. Regarding the methodological heterogeneity between the included studies, we selected a random-effects model. The geometric mean ratio (GMR) was chosen as the effect size for this meta-analysis. RESULTS: Of the 1838 records identified through screening and after removing duplicate records, the full texts of 1076 records were assessed for eligibility. After the full-text assessment, 56 records were eligible and included in the study. Overall, vaccinated participants had a 150.8-fold increased rate of anti-spike IgG titres compared with the placebo group (GMR = 150.8; 95% CI, 95.9-237.1; I2 = 100%). Moreover, vaccinated participants had a 37.3-fold increased rate of neutralising antibody titres compared with the placebo group (GMR = 37.3; 95% CI, 28.5-48.7; I2 = 99%). The mRNA platform showed a higher rate of anti-spike IgG (GMR = 1263.5; 95% CI, 431.1-3702.8; I2 = 99%), while neutralising antibody titres were higher in the subunit platform (GMR = 53.4; 95% CI, 32.8-87.1; I2 = 99%) than in other platforms. Different vaccine platforms showed different rates of both anti-spike IgG and neutralising antibody titres with interesting results. The seroconversion rate of anti-spike IgG and neutralising antibody titres was more than 98% in the vaccinated participants. CONCLUSION: Inactivated and subunit vaccines produced a high percentage of neutralising antibodies and had a low common adverse reaction rate compared to other platforms. In this regard, subunit and inactivated vaccines can still be used as the main vaccine platforms for effectively controlling infections with high transmission rates.

DENOISING: Dynamic enhancement and noise overcoming in multimodal neural observations via high-density CMOS-based biosensors.

Large-scale multimodal neural recordings on high-density biosensing microelectrode arrays (HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity across various brain networks. However, the fidelity of these recordings is frequently compromised by pervasive noise, which obscures meaningful neural information and complicates data analysis. To address this challenge, we introduce DENOISING, a versatile data-derived computational engine engineered to adjust thresholds adaptively based on large-scale extracellular signal characteristics and noise levels. This facilitates the separation of signal and noise components without reliance on specific data transformations. Uniquely capable of handling a diverse array of noise types (electrical, mechanical, and environmental) and multidimensional neural signals, including stationary and non-stationary oscillatory local field potential (LFP) and spiking activity, DENOISING presents an adaptable solution applicable across different recording modalities and brain networks. Applying DENOISING to large-scale neural recordings from mice hippocampal and olfactory bulb networks yielded enhanced signal-to-noise ratio (SNR) of LFP and spike firing patterns compared to those computed from raw data. Comparative analysis with existing state-of-the-art denoising methods, employing SNR and root mean square noise (RMS), underscores DENOISING's performance in improving data quality and reliability. Through experimental and computational approaches, we validate that DENOISING improves signal clarity and data interpretation by effectively mitigating independent noise in spatiotemporally structured multimodal datasets, thus unlocking new dimensions in understanding neural connectivity and functional dynamics.

Control of action potential afterdepolarizations in the inferior olive by inactivating A-type currents through KV4 channels.

Neurons of the inferior olive (IO) fire action potentials with large, long-lasting afterdepolarizations (ADPs). Broader ADPs support more spikes in climbing fibre axons and evoke longer bursts of complex spikes in Purkinje cells, which affect the magnitude and sign of cerebellar synaptic plasticity. In the present study, we investigated the ionic mechanisms that regulate IO action potential waveforms by making whole-cell recordings in brainstem slices from C57BL6/J mice. IO spikes evoked from rest had ADPs of ∼30 ms. After 500-ms hyperpolarizations, however, evoked action potentials were brief (1-2 ms), lacking ADPs altogether. Because such preconditioning should maximally recruit depolarizing Ih and T-type currents and minimize repolarizing Ca-dependent currents known to shape the ADP, the rapid action potential downstroke suggested additional, dominant recovery of voltage-gated K currents at negative voltages. Under voltage clamp, outward currents evoked from -98 mV included large, voltage-gated, rapidly inactivating 'A-type' K currents. These currents had a steep availability curve with half-inactivation at -85 mV, suitable for recruitment by small hyperpolarizations. The fast decay time constant increased with depolarization, as is typical of KV4 channels. The KV4 channel blocker AmmTx3 almost eliminated inactivating currents and broadened action potentials evoked from strongly negative potentials by ∼8-fold. Optogenetic stimulation of inhibitory cerebellar nucleo-olivary terminals hyperpolarized IO cells sufficiently to abolish the ADP. The data support the idea that currents through KV4 channels control action potential waveforms in IO cells, shortening ADPs during synaptic inhibition or troughs of membrane potential oscillations, thereby controlling the number of climbing fibre action potentials that propagate to the cerebellum. KEY POINTS: Neurons in the mouse inferior olive (IO) express a large, inactivating, voltage-gated A-type K current carried by KV4 channels. IO action potentials evoked from rest have large, long afterdepolarizations that disappear with pre-spike hyperpolarizations of 5-15 mV. The steep voltage-sensitivity and rapid recovery of KV4 channels regulates the duration of the afterdepolarization over more than one order of magnitude. Factors such as synaptic inhibition are sufficient to recruit KV4 channels and eliminate afterdepolarization (ADP). By controlling the ADP, KV4 channels can set the number of climbing fibre action potentials relayed to the cerebellum and regulate plasticity implicated in motor learning.

Isotopic spike 190Os as internal standard and empirical coefficient LA-ICP-MS combined with Sb fire assay for the determination of ultra-trace platinum group elements in geochemical samples.

In this work, a novel method of antimony fire assay (Sb-FA) enrichment combined with laser ablation ICP-MS (LA-ICP-MS) for the determination of ultra-trace platinum group elements (PGEs) in geological samples was established. The purification and recycling technology of ultra-clean and high-purity fire assay collector Sb2O3 was proposed, in addition, high-purity quartz crucible was developed to replace the usual clay crucible, then the blank values of PGEs were as low as 0.0007-0.0028 ng g-1 (for 20 g sample). 190Os isotopic diluent was used as internal standard (IS) and quantitatively added into the fire assay ingredients, and fully mixed and balanced with the PGEs in the real samples by means of high temperature melting, cupellation and horizontal rotation of crucible and dish. Both 190Os and PGEs in the real sample were pre-concentrated in microgram level Sb granules (100 mg) through Sb-remaining cupellation. After grinding and polishing, 195Pt, 105Pd, 101Ru, 103Rh, 193Ir, total 189Os and 190Os enriched in Sb slices were determined by LA-ICP-MS, 190Os in the internal standard was calculated by isotope dilution equations. The Certified Reference Materials (CRMs) for PGEs were treated by the same procedure to obtain completely matrix matched Sb slices to solve the problem of no internationally recognized uniform PGEs standard materials for LA-ICP-MS determination. Due to the similar distribution trends of different PGEs in Sb slices by LA-ICP-MS imaging, then matrix-matched internal standard calibration strategy was used to reduce the element fractionation effect and improve the determination precision and accuracy of LA-ICP-MS. The laser frequency, energy density, denudation diameter and dwell times were optimized. Under the optimal conditions, empirical coefficient method was used to fit the standard curve and excellent curve fitting of PGEs were obtained with the correlation coefficient between 0.9990 and 0.9999. The method detection limits (LODs) for PGEs ranged from 0.00042 to 0.010 ng g-1. The established method was successfully applied to analyze real geochemical samples and various matrix Certified Reference Materials (CRMs) domestic and international, the determined values were in good agreement with the results of Sb-FA ICP-MS and the certified values.

Unsupervised spike sorting for multielectrode arrays based on spike shape features and location methods.

Microelectrode arrays (MEAs) enable simultaneous measurement of spike trains from numerous neurons, owing to advancements in microfabrication technology. These probes are highly valuable for comprehending the intricate dynamics of neuronal networks. Spike sorting is a pivotal step in comprehensively analyzing the activity of neuronal networks from extracellular recordings. However, the accuracy of spike sorting is relatively low due to the dense sampling of spikes in MEAs. Here, we propose an unsupervised pipeline named UMAP-COM method, which utilizes combined features to address this problem. These combined features comprise dominant spike shape features extracted by the uniform manifold approximation and projection (UMAP), as well as spike locations estimated by the center of mass (COM). We validate the UMAP-COM method on publicly available datasets from different kinds of probes, demonstrating that it is more accurate than other spike sorting methods. Furthermore, we conduct separate evaluations of spike shape feature extraction methods and spike localization methods. In this comparison, UMAP emerges as the superior feature extraction method, demonstrating its effectiveness in accurately representing spike shapes. Additionally, we find that the COM method outperforms other spike localization methods, highlighting its ability to enhance the accuracy of spike sorting.