Surface multi-walled carbon nanotube modified quaternary amine-functionalized polymers for purification and determination of glyphosate and its four metabolites in plasma samples.

The present study focused on the pretreatment and detection of GLY and its four metabolites AMPA, N-acetyl AMPA, N-methyl GLY and N-acetyl GLY in plasma samples. Multi-walled carbon nanotube-modified quaternary amine-functionalized polymers (QA-PDNV@MWCNTs) were synthesized in a controlled manner by self-assembly, and its morphology and composition were extensively characterized. The QA-PDNV@MWCNTs microspheres were then used as an SPE adsorbent for the preparation and rapid determination of GLY and its four metabolites in plasma samples combined with ultra-performance liquid chromatography-high resolution mass spectrometry (UPLCHRMS). The SPE conditions based on QA-PDNV@MWCNTs were optimized for GLY and its metabolites to obtain the best purification efficiency. The experimental results show that when the adsorbent contains 8% MWCNTs, it can balance the adsorption of target analytes and the purification performance of the adsorbent for impurities. In addition, this study compared the QA-PDNV@MWCNTs based SPE method with the commercial Waters Oasis MAX SPE cartridge and the results showed that the developed method in this study has better resistance to matrix interference. Under optimal conditions, the recoveries of GLY and its metabolites spiked in plasma were 82.6-99.4 % with relative standard deviations (RSDs) of 1.0-7.8 %. The limits of detection (LODs, S/N ≥ 3) and limits of quantification (LOQs, S/N ≥ 9) of the method were 0.05-0.33 µg/L and 0.15-1.00 µg/L, respectively. Finally, the developed QA-PDNV@MWCNTs based SPE-UPLCHRMS method was used to confirm GLY poisoning not only on the basis of the detection of the GLY prototype, but also on the basis of its four metabolites.

Amplitude- and frequency-dependent activation of layer II/III neurons by intracortical microstimulation.

Intracortical microstimulation (ICMS) has been used for the development of brain machine interfaces. However, further understanding about the spatiotemporal responses of neurons to different electrical stimulation parameters is necessary to inform the design of optimal therapies. In this study, we employed in vivo electrophysiological recording, two-photon calcium imaging, and electric field simulation to evaluate the acute effect of ICMS on layer II/III neurons. Our results show that stimulation frequency non-linearly modulates neuronal responses, whereas the magnitude of responses is linearly correlated to the electric field strength and stimulation amplitude before reaching a steady state. Temporal dynamics of neurons' responses depends more on stimulation frequency and their distance to the stimulation electrode. In addition, amplitude-dependent post-stimulation suppression was observed within ∼500 µm of the stimulation electrode, as evidenced by both calcium imaging and local field potentials. These findings provide insights for selecting stimulation parameters to achieve desirable spatiotemporal specificity of ICMS.

Development, characterization and in vivo zinc absorption capacity of a novel soy meal hydrolysate-zinc complexes.

Background: Zinc is an essential trace element for the human body. Recently, a novel Zn-binding peptide, Lys-Tyr-Lys-Arg-Gln-Arg-Trp (PP), was purified and identified from soy protein hydrolysates with high Zn-binding capacity (83.21 ± 2.65%) by our previous study. The preparation of soy meal hydrolysates (SMHs)-Zn complexes is convenient and low-cost, while PP (Lys-Tyr-Lys-Arg-Gln-Arg-Trp)-Zn complexes have a higher coordination rate but a relatively high cost. The aim of this study was to investigate the effect of soy meal hydrolysates (SMHs)-Zn complexes on zinc absorption in mice model, and synthetic soy peptide (PP)-Zn complexes with high Zn-binding capacity were used as control. Firstly, SMHs were prepared by enzymolysis, and the PP (Lys-Tyr-Lys-Arg-Gln-Arg-Trp) were synthesized based on previous studies. The binding mechanism of soy hydrolysates and zinc was analyzed by spectral analysis. Furthermore, the cytotoxicity of the SMHs-Zn complexes was also studied using the CCK-8 method. The effect of zinc absorption was evaluated based on Zn content, total protein and albumin content, relevant enzyme system, and the PeT1 and ZnT1 mRNA expression levels. Result: The result showed that zinc was bound with carboxyl oxygen and amino nitrogen atoms on SMHs, with hydrophobic and electrostatic interactions as auxiliary stabilizing forces. SMHs-Zn were proved to have great solubility and a small particle size at different pH values, and it showed a beneficial effect on Caco-2 cells growth. Moreover, it was proved that SMHs-Zn and PP-Zn could increase the levels of zinc and the activity of Zn-related enzymes in mice. SMHs-Zn possessed higher PepT1 and ZnT1 mRNA expression levels than PP-Zn in the small intestine. Conclusion: SMHs-Zn with a lower Zn-binding capacity had similar effects on zinc absorption in mice as PP-Zn, suggesting that the bioavailability of peptide-zinc complexes in mice was not completely dependent on their Zn-binding capacity, but may also be related to the amino acid composition.

EEG classification of traumatic brain injury and stroke from a nonspecific population using neural networks.

Traumatic Brain Injury (TBI) and stroke are devastating neurological conditions that affect hundreds of people daily. Unfortunately, detecting TBI and stroke without specific imaging techniques or access to a hospital often proves difficult. Our prior research used machine learning on electroencephalograms (EEGs) to select important features and to classify between normal, TBI, and stroke on an independent dataset from a public repository with an accuracy of 0.71. In this study, we expanded to explore whether featureless and deep learning models can provide better performance in distinguishing between TBI, stroke and normal EEGs by including more comprehensive data extraction tools to drastically increase the size of the training dataset. We compared the performance of models built upon selected features with Linear Discriminative Analysis and ReliefF with several featureless deep learning models. We achieved 0.85 area under the curve (AUC) of the receiver operating characteristic curve (ROC) using feature-based models, and 0.84 AUC with featureless models. In addition, we demonstrated that Gradient-weighted Class Activation Mapping (Grad-CAM) can provide insight into patient-specific EEG classification by highlighting problematic EEG segments during clinical review. Overall, our study suggests that machine learning and deep learning of EEG or its precomputed features can be a useful tool for TBI and stroke detection and classification. Although not surpassing the performance of feature-based models, featureless models reached similar levels without prior computation of a large feature set allowing for faster and cost-efficient deployment, analysis, and classification.

RNADisease v4.0: an updated resource of RNA-associated diseases, providing RNA-disease analysis, enrichment and prediction.

Numerous studies have shown that RNA plays an important role in the occurrence and development of diseases, and RNA-disease associations are not limited to noncoding RNAs in mammals but also exist for protein-coding RNAs. Furthermore, RNA-associated diseases are found across species including plants and nonmammals. To better analyze diseases at the RNA level and facilitate researchers in exploring the pathogenic mechanism of diseases, we decided to update and change MNDR v3.0 to RNADisease v4.0, a repository for RNA-disease association (http://www.rnadisease.org/ or http://www.rna-society.org/mndr/). Compared to the previous version, new features include: (i) expanded data sources and categories of species, RNA types, and diseases; (ii) the addition of a comprehensive analysis of RNAs from thousands of high-throughput sequencing data of cancer samples and normal samples; (iii) the addition of an RNA-disease enrichment tool and (iv) the addition of four RNA-disease prediction tools. In summary, RNADisease v4.0 provides a comprehensive and concise data resource of RNA-disease associations which contains a total of 3 428 058 RNA-disease entries covering 18 RNA types, 117 species and 4090 diseases to meet the needs of biological research and lay the foundation for future therapeutic applications of diseases.

Synthesis, characterization of tuna polypeptide selenium nanoparticle, and its immunomodulatory and antioxidant effects in vivo.

The tuna polypeptide (TP) was used as the reducing agent and the stabilizing agent to synthesize a tuna polypeptide selenium nanoparticle (TP-SeNP) via a green method. An animal experiment was conducted to investigate its immunomodulatory and antioxidant effects in vivo. The results indicated that the TP regulated the accumulation and stabilization of the TP-SeNP. And the conversion of selenium was tested to be 20.44%. The TP-SeNP was about 22 nm in diameter, a mix of spherical and quasi-spherical, and amorphous. The reaction between the TP and Na2SeO3 was entropy-driven spontaneous, and the binding force was mainly hydrophobic. Intake of the TP-SeNP could greatly increase the phagocytic activity of the mononuclear phagocytic system, and the contents of immunological molecules. The antioxidant capacity of the liver was also improved.

Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification.

OBJECTIVES: Big data analytics can potentially benefit the assessment and management of complex neurological conditions by extracting information that is difficult to identify manually. In this study, we evaluated the performance of commonly used supervised machine learning algorithms in the classification of patients with traumatic brain injury (TBI) history from those with stroke history and/or normal EEG. METHODS: Support vector machine (SVM) and K-nearest neighbors (KNN) models were generated with a diverse feature set from Temple EEG Corpus for both two-class classification of patients with TBI history from normal subjects and three-class classification of TBI, stroke and normal subjects. RESULTS: For two-class classification, an accuracy of 0.94 was achieved in 10-fold cross validation (CV), and 0.76 in independent validation (IV). For three-class classification, 0.85 and 0.71 accuracy were reached in CV and IV respectively. Overall, linear discriminant analysis (LDA) feature selection and SVM models consistently performed well in both CV and IV and for both two-class and three-class classification. Compared to normal control, both TBI and stroke patients showed an overall reduction in coherence and relative PSD in delta frequency, and an increase in higher frequency (alpha, mu, beta and gamma) power. But stroke patients showed a greater degree of change and had additional global decrease in theta power. CONCLUSIONS: Our study suggests that EEG data-driven machine learning can be a useful tool for TBI classification. SIGNIFICANCE: Our study provides preliminary evidence that EEG ML algorithm can potentially provide specificity to separate different neurological conditions.

Label-free X-ray estimation of brain amyloid burden.

Amyloid plaque deposits in the brain are indicative of Alzheimer's and other diseases. Measurements of brain amyloid burden in small animals require laborious post-mortem histological analysis or resource-intensive, contrast-enhanced imaging techniques. We describe a label-free method based on spectral small-angle X-ray scattering with a polychromatic beam for in vivo estimation of brain amyloid burden. Our findings comparing 5XFAD versus wild-type mice correlate well with histology, showing promise for a fast and practical in vivo technique.

Longitudinal multimodal assessment of neurodegeneration and vascular remodeling correlated with signal degradation in chronic cortical silicon microelectrodes.

Significance: Cortically implanted microelectrode arrays provide a direct interface with neuronal populations and are used to restore movement capabilities and provide sensory feedback to patients with paralysis or amputation. Penetrating electrodes experience high rates of signal degradation within the first year that limit effectiveness and lead to eventual device failure. Aim: To assess vascular and neuronal changes over time in mice with implanted electrodes and examine the contribution of the brain tissue response to electrode performance. Approach: We used a multimodal approach combining in vivo electrophysiology and subcellular-level optical imaging. Results: At acute timescales, we observed structural damage from the mechanical trauma of electrode insertion, evidenced by severed dendrites in the electrode path and local hypofluorescence. Superficial vessel growth and remodeling occurred within the first few weeks in both electrode-implanted and window-only animals, but the deeper capillary growth evident in window-only animals was suppressed in electrode-implanted animals. After longer implantation periods, there was evidence of degeneration of transected dendrites superficial to the electrode path and localized neuronal cell body loss, along with deep vascular velocity changes near the electrode. Total spike rate (SR) across all animals reached a peak between 3 and 9 months postimplantation, then decreased. The local field potential signal remained relatively constant for up to 6 months, particularly in the high-gamma band, indicating long-term electrode viability and neuronal functioning at further distances from the electrode, but it showed a reduction in some animals at later time points. Most importantly, we found that progressive high-gamma and SR reductions both correlate positively with localized cell loss and decreasing capillary density within 100 µ m of the electrode. Conclusions: This multifaceted approach provided a more comprehensive picture of the ongoing biological response at the brain-electrode interface than can be achieved with postmortem histology alone and established a real-time relationship between electrophysiology and tissue damage.

Longitudinal neural and vascular structural dynamics produced by chronic microelectrode implantation.

Implanted microelectrode arrays sense local neuronal activity, signals which are used as control commands for brain computer interface (BCI) technology. Patients with tetraplegia have used BCI technology to achieve an extraordinary degree of interaction with their local environment. However, current microelectrode arrays for BCIs lose the ability to record high-quality neural signals in the months-to-years following implantation. Very little is known regarding the dynamic response of neurons and vasculature in the months following electrode array implantation, but loss of structural integrity near the electrode may contribute to the degradation of recording signals. Here, we use in-vivo dual-modality imaging to characterize neuronal and vasculature structures in the same animal for 3 months following electrode insertion. We find ongoing neuronal atrophy, but relative vascular stability, in close proximity to the electrode, along with evidence suggesting links between rare, abrupt hypoxic events and neuronal process atrophy.

Longitudinal Functional Assessment of Brain Injury Induced by High-Intensity Ultrasound Pulse Sequences.

Exposure of the brain to high-intensity stress waves creates the potential for long-term functional deficits not related to thermal or cavitational damage. Possible sources of such exposure include overpressure from blast explosions or high-intensity focused ultrasound (HIFU). While current ultrasound clinical protocols do not normally produce long-term neurological deficits, the rapid expansion of potential therapeutic applications and ultrasound pulse-train protocols highlights the importance of establishing a safety envelope beyond which therapeutic ultrasound can cause neurological deficits not detectable by standard histological assessment for thermal and cavitational damage. In this study, we assessed the neuroinflammatory response, behavioral effects, and brain micro-electrocorticographic (µECoG) signals in mice following exposure to a train of transcranial pulses above normal clinical parameters. We found that the HIFU exposure induced a mild regional neuroinflammation not localized to the primary focal site, and impaired locomotor and exploratory behavior for up to 1 month post-exposure. In addition, low frequency (δ) and high frequency (ß, γ) oscillations recorded by ECoG were altered at acute and chronic time points following HIFU application. ECoG signal changes on the hemisphere ipsilateral to HIFU exposure are of greater magnitude than the contralateral hemisphere, and persist for up to three months. These results are useful for describing the upper limit of transcranial ultrasound protocols, and the neurological sequelae of injury induced by high-intensity stress waves.

[Detection of free amino acids in tea using ultra-high performance liquid chromatography-tandem mass spectrometry].

To efficiently and quickly detect free amino acid components in tea, a method using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was developed. With the optimization of mass spectrometry, chromatographic conditions, and amino-acid extraction conditions, a total of 20 free amino acids were identified using 5 mmol/L ammonium acetate aqueous solution containing 0.2% (v/v) formic acid and methanol as mobile phases for gradient elution and detected by electrospray ionization (ESI) and positive-ion scanning. The results showed that all calibration curves expressed good linearities. Theanine (Thea), Arg, Asn, and Asp were in the range of 50-500 µg/L. The other amino acids were in the range of 10-250 µg/L with all correlation coefficients ≥ 0.99. The average recoveries were between 92.3% and 109.2%. The relative standard deviation (RSDs) were between 2.00% and 9.88%. The limits of detection (LODs) were 0.001-0.011 mg/L, and the limits of quantification (LOQs) were 0.010-0.053 mg/L. The method is sensitive, accurate, and has good repeatability and stability. The method can effectively detect 20 types of amino acids and amino components in tea leaves from the samples of green tea, white tea, and black tea.

Comparative proteomic analysis provides novel insights into the regulation mechanism underlying papaya (Carica papaya L.) exocarp during fruit ripening process.

BACKGROUND: Papaya (Carica papaya L.) is a popular climacteric fruit, undergoing various physico-chemical changes during ripening. Although papaya is widely cultivated and consumed, few studies on the changes in metabolism during its ripening process at the proteasome level have been performed. Using a newly developed TMT-LCMS analysis, proteomes of papaya fruit at different ripening stages were investigated. RESULTS: In total, 3220 proteins were identified, of which 2818 proteins were quantified. The differential accumulated proteins (DAPs) exhibited various biological functions and diverse subcellular localizations. The KEGG enrichment analysis showed that various metabolic pathways were significantly altered, particularly in flavonoid and fatty acid metabolisms. The up-regulation of several flavonoid biosynthesis-related proteins may provide more raw materials for pigment biosynthesis, accelerating the color variation of papaya fruit. Variations in the fatty acid metabolism- and cell wall degradation-related proteins were investigated during the ripening process. Furthermore, the contents of several important fatty acids were determined, and increased unsaturated fatty acids may be associated with papaya fruit volatile formation. CONCLUSIONS: Our data may give an intrinsic explanation of the variations in metabolism during the ripening process of papaya fruit.

[Determination of residual glyphosate and aminomethylphosphonic acid in wheat flour and oats samples by non-derivatization method based on ultra-performance liquid chromatography-high resolution mass spectrometry].

A rapid and accurate analysis method based on ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was developed for the determination of residual glyphosate (GLY) and aminomethylphosphonic acid (AMPA) in wheat flour and oats samples. The wheat flour and oats samples were firstly subjected to vortex and ultrasound extraction; then, the extract solution was purified by MCX solid-phase extraction (SPE) cartridges as well as protein precipitation using acetonitrile. The chromatographic separation was carried out on a Dikma Polyamino HILIC column (150 mm×2.0 mm, 5 µm) by linear gradient elution procedure using 5 mmol/L ammonium acetate in water (pH=10.5) and acetonitrile as the elution solvent. An electrospray ion source in negative mode and parallel reaction monitor (PRM) mode was used for quantification by the internal standard method. The instrument conditions for liquid chromatography (LC) and HRMS, and the sample pretreatment conditions for GLY and its metabolite AMPA were systematically optimized. In addition, the matrix effect and injection system residue were investigated, and a comparison of different analytical methods was carried out. The results indicated that GLY and AMPA showed good linearities in the range of 5.0-100.0 µg/L with coefficients (R2) higher than 0.999. The limits of detection (LODs) were found to be 0.005 and 0.05 mg/kg for GLY and AMPA, respectively. The recoveries of GLY and AMPA in the wheat flour and oats samples were in the range of 93.8%-115% and 89.8%-110% at the spiked levels of 0.1, 0.5, and 2.0 mg/kg, respectively, while the relative standard deviations (RSDs) were all less than 10%. The results of the matrix effect test revealed that the matrix inhibition effect could be reduced by using an isotopic internal standard with the matrix effect parameter |η|<3%. Moreover, the injection system residue was effectively controlled with a residual level of less than 1.0%. A comparison of the developed method with the reported derivatization method indicated little difference, with RSDs of 2.19% and 3.07% to the assigned value, respectively. The established analytical method was used for the Food Analysis Performance Assessment Scheme (FAPAS) proficiency test (No. 09122, GLY in oats), and the results were satisfactory with a z value of 0.2. Moreover, the result obtained using this method was very closed to the assigned value of the FAPAS QC sample, with a recovery of 102.2% (No. T09119QC, GLY in wheat flour). The proposed method is fast, simple, sensitive, and accurate, and it can be applied for the daily monitoring of GLY and its metabolite AMPA in wheat flour and oats samples.

[Simultaneous determination of insecticide in tea samples using QuEChERS-based clean up and ultra-fast liquid chromatography-tandem mass spectrometry].

OBJECTIVE: To develop a method for determination of imidacloprid, acetamiprid, chlorobenzamide and indoxacarb in tea samples using Qu ECh ERS-based pretreatment method and ultra-fast liquid chromatography-tandem mass spectrometry( UFLC-MS/MS). METHODS: Tea samples were firstly extracted by acetonitrile-water solution( 4∶ 1, V/V) by vortex and ultrasound, and then 1 g Na Cl and 4 g Mg SO4 were added into the mixture, following by vortex and centrifugation at 8500 r/min for 5 min. Finally the supernatant was purified by Mg SO4 and PSA power, and then the chromatographic separation process was performed on a Waters ACQUITY UPLC BEH C18 column( 2. 1 mm × 100 mm, 1. 7 µm) with a linear gradient elution procedure ofacetonitrile and 0. 1%( V/V) formic acid-5 mmol/L ammonium acetate in water as elution solvent. The multiple reaction monitoring( MRM) in positive mode was used for quantification by internal standard method. RESULTS: The four insecticides including imidacloprid, acetamiprid, chlorobenzamide, and indoxacarb showed good linearity in the range of 0. 20-50. 0 µg/L with coefficients( r) higher than 0. 9998. The limits of detection( LODs) varied from 0. 1 µg/kg to 0. 3 µg/kg. The recoveries of spiked tea samples in the range of 88. 4%-98. 8% at the three concentrations of 1. 0 µg/kg, 40. 0µg/kg and 80. 0 µg/kg, while the relative standard deviations( RSD) were all less than10%. CONCLUSION: The proposed method is simple, fast, sensitive and accuracy, and can be used for qualitative and quantitative analysis of imidacloprid, acetamiprid, chlorobenzamide, andindoxacarb in tea samples.

[Determination of glyphosate, glufosinate, and main metabolite aminomethylphosphonic acid residues in dry tea using ultra-high performance liquid chromatography-tandem mass spectrometry].

A method has been developed for the determination of glyphosate (GLY), glufosinate (GLUF), and the main metabolite aminomethylphosphonic acid (AMPA) residues in dry tea based on ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) coupled with pre-column derivatization. A systematic study of the effects of pretreatment methods including extraction and purification procedures was designed and carried out for the determination of GLY, GLUF, and AMPA. The results indicated that the optimal pretreatment method was as follows:the tea sample was first extracted by water in vortex, and then purified by a cation exchange solid-phase extraction column with the elution of 0.5% (v/v) formic acid aqueous solution. Finally, the eluant was derivatized by 9-fluorenylmethyl chloroformate, and the target compounds were separated on a C18 chromatographic column and analysed by UPLC-MS/MS (ESI+). GLY, GLUF, and AMPA showed good linearity in the range of 1-100 µ g/L, with correlation coefficients above 0.991. The limits of detection and limits of quantification were found to be 0.0160-0.0300 mg/kg and 0.0530-0.100 mg/kg, respectively. The average spiked recoveries of GLY, GLUF, and AMPA varied from 78.3% to 108% at three spiked levels (0.0500, 0.400, and 1.20 mg/kg), while the relative standard deviations ranged from 5.46% to 9.63%. The proposed method was utilized to detect 837 batches of tea samples. The detection ratios of GLY, GLUF, and AMPA were 3.46%, 0.24%, and 4.42%, respectively, while 0.24% of the investigated tea samples had values above maximum residue limits. The developed method is simple, rapid, sensitive, and accurate for the determination of GLY, GLUF, and AMPA in dry tea and may be used for routine analysis.

Epidermal Electrode Technology for Detecting Ultrasonic Perturbation of Sensory Brain Activity.

OBJECTIVE: We aim to demonstrate the in vivo capability of a wearable sensor technology to detect localized perturbations of sensory-evoked brain activity. METHODS: Cortical somatosensory evoked potentials (SSEPs) were recorded in mice via wearable, flexible epidermal electrode arrays. We then utilized the sensors to explore the effects of transcranial focused ultrasound, which noninvasively induced neural perturbation. SSEPs recorded with flexible epidermal sensors were quantified and benchmarked against those recorded with invasive epidural electrodes. RESULTS: We found that cortical SSEPs recorded by flexible epidermal sensors were stimulus frequency dependent. Immediately following controlled, focal ultrasound perturbation, the sensors detected significant SSEP modulation, which consisted of dynamic amplitude decreases and altered stimulus-frequency dependence. These modifications were also dependent on the ultrasound perturbation dosage. The effects were consistent with those recorded with invasive electrodes, albeit with roughly one order of magnitude lower signal-to-noise ratio. CONCLUSION: We found that flexible epidermal sensors reported multiple SSEP parameters that were sensitive to focused ultrasound. This work therefore 1) establishes that epidermal electrodes are appropriate for monitoring the integrity of major CNS functionalities through SSEP; and 2) leveraged this technology to explore ultrasound-induced neuromodulation. The sensor technology is well suited for this application because the sensor electrical properties are uninfluenced by direct exposure to ultrasound irradiation. SIGNIFICANCE: The sensors and experimental paradigm we present involve standard, safe clinical neurological assessment methods and are thus applicable to a wide range of future translational studies in humans with any manner of health condition.

Alterations in neurovascular coupling following acute traumatic brain injury.

Following acute traumatic brain injury (TBI), timely transport to a hospital can significantly improve the prognosis for recovery. There is, however, a dearth of quantitative biomarkers for brain injury that can be rapidly acquired and interpreted in active, field environments in which TBIs are frequently incurred. We explored potential functional indicators for TBI that can be noninvasively obtained through portable detection modalities, namely optical and electrophysiological approaches. By combining diffuse correlation spectroscopy with colocalized electrophysiological measurements in a mouse model of TBI, we observed concomitant alterations in sensory-evoked cerebral blood flow (CBF) and electrical potentials following controlled cortical impact. Injury acutely reduced the peak amplitude of both electrophysiological and CBF responses, which mostly recovered to baseline values within 30 min, and intertrial variability for these parameters was also acutely altered. Notably, the postinjury dynamics of the CBF overshoot and undershoot amplitudes differed significantly; whereas the amplitude of the initial peak of stimulus-evoked CBF recovered relatively rapidly, the ensuing undershoot did not appear to recover within 30 min of injury. Additionally, acute injury induced apparent low-frequency oscillatory behavior in CBF ([Formula: see text]). Histological assessment indicated that these physiological alterations were not associated with any major, persisting anatomical changes. Several time-domain features of the blood flow and electrophysiological responses showed strong correlations in recovery kinetics. Overall, our results reveal an array of stereotyped, injury-induced alterations in electrophysiological and hemodynamic responses that can be rapidly obtained using a combination of portable detection techniques.

Retinal Wave Patterns Are Governed by Mutual Excitation among Starburst Amacrine Cells and Drive the Refinement and Maintenance of Visual Circuits.

Retinal waves are correlated bursts of spontaneous activity whose spatiotemporal patterns are critical for early activity-dependent circuit elaboration and refinement in the mammalian visual system. Three separate developmental wave epochs or stages have been described, but the mechanism(s) of pattern generation of each and their distinct roles in visual circuit development remain incompletely understood. We used neuroanatomical,in vitroandin vivoelectrophysiological, and optical imaging techniques in genetically manipulated mice to examine the mechanisms of wave initiation and propagation and the role of wave patterns in visual circuit development. Through deletion of ß2 subunits of nicotinic acetylcholine receptors (ß2-nAChRs) selectively from starburst amacrine cells (SACs), we show that mutual excitation among SACs is critical for Stage II (cholinergic) retinal wave propagation, supporting models of wave initiation and pattern generation from within a single retinal cell type. We also demonstrate that ß2-nAChRs in SACs, and normal wave patterns, are necessary for eye-specific segregation. Finally, we show that Stage III (glutamatergic) retinal waves are not themselves necessary for normal eye-specific segregation, but elimination of both Stage II and Stage III retinal waves dramatically disrupts eye-specific segregation. This suggests that persistent Stage II retinal waves can adequately compensate for Stage III retinal wave loss during the development and refinement of eye-specific segregation. These experiments confirm key features of the "recurrent network" model for retinal wave propagation and clarify the roles of Stage II and Stage III retinal wave patterns in visual circuit development. SIGNIFICANCE STATEMENT: Spontaneous activity drives early mammalian circuit development, but the initiation and patterning of activity vary across development and among modalities. Cholinergic "retinal waves" are initiated in starburst amacrine cells and propagate to retinal ganglion cells and higher-order visual areas, but the mechanism responsible for creating their unique and critical activity pattern is incompletely understood. We demonstrate that cholinergic wave patterns are dictated by recurrent connectivity within starburst amacrine cells, and retinal ganglion cells act as "readouts" of patterned activity. We also show that eye-specific segregation occurs normally without glutamatergic waves, but elimination of both cholinergic and glutamatergic waves completely disrupts visual circuit development. These results suggest that each retinal wave pattern during development is optimized for concurrently refining multiple visual circuits.