Baseline Neurocognitive Performance and Symptoms in Those With Attention Deficit Hyperactivity Disorders and History of Concussion With Previous Loss of Consciousness

Previous consensus statements on sports concussion have highlighted the importance of Attention Deficit Hyperactivity Disorder (ADHD) and loss of consciousness (LOC) as risk factors related to concussion management. The present study investigated how self-reported history of either ADHD diagnosis or history of previous concussion resulting in LOC influence baseline neurocognitive performance and self-reported symptoms. This analysis was performed retrospectively on data collected primarily from student-athletes, both Division 1 and club sports athletes. The dataset (n = 1460) is comprised of college students (age = 19.1 ± 1.4 years). Significant differences were found for composite scores on the ImPACT for both history of concussion (p = 0.016) and ADHD (p = 0.014). For concussion history, those with a previous concussion, non-LOC, performed better on the visual motor speed (p = 0.004). Those with diagnosis of ADHD performed worse on verbal memory (p = 0.001) and visual motor speed (p = 0.033). For total symptoms, concussion history (p < 0.001) and ADHD (p = 0.001) had an influence on total symptoms. Those with ADHD reported more symptoms for concussion history; those with previous LOC concussion reported more symptoms than those with non-LOC concussion (p = 0.003) and no history (p < 0.001). These results highlight the importance of baseline measures of neurocognitive function and symptoms in concussion management in order to account for pre-existing conditions such as ADHD and LOC from previous concussion that could influence these measures

Characterization of a new metallo-β-lactamase gene, blaNDM-1, and a novel erythromycin esterase gene carried on a unique genetic structure in klebsiella pneumoniae sequence Type 14 from India

A Swedish patient of Indian origin traveled to New Delhi, India, and acquired a urinary tract infection caused by a carbapenem-resistant Klebsiella pneumoniae strain that typed to the sequence type 14 complex. The isolate, Klebsiella pneumoniae 05-506, was shown to possess a metallo-β-lactamase (MBL) but was negative for previously known MBL genes. Gene libraries and amplification of class 1 integrons revealed three resistance-conferring regions; the first contained blaCMY-4 flanked by ISEcP1 and blc. The second region of 4.8 kb contained a complex class 1 integron with the gene cassettes arr-2, a new erythromycin esterase gene; ereC; aadA1; and cmlA7. An intact ISCR1 element was shown to be downstream from the qac/sul genes. The third region consisted of a new MBL gene, designated blaNDM-1, flanked on one side by K. pneumoniae DNA and a truncated IS26 element on its other side. The last two regions lie adjacent to one another, and all three regions are found on a 180-kb region that is easily transferable to recipient strains and that confers resistance to all antibiotics except fluoroquinolones and colistin. NDM-1 shares very little identity with other MBLs, with the most similar MBLs being VIM-1/VIM-2, with which it has only 32.4% identity. As well as possessing unique residues near the active site, NDM-1 also has an additional insert between positions 162 and 166 not present in other MBLs. NDM-1 has a molecular mass of 28 kDa, is monomeric, and can hydrolyze all β-lactams except aztreonam. Compared to VIM-2, NDM-1 displays tighter binding to most cephalosporins, in particular, cefuroxime, cefotaxime, and cephalothin (cefalotin), and also to the penicillins. NDM-1 does not bind to the carbapenems as tightly as IMP-1 or VIM-2 and turns over the carbapenems at a rate similar to that of VIM-2. In addition to K. pneumoniae 05-506, blaNDM-1 was found on a 140-kb plasmid in an Escherichia coli strain isolated from the patient's feces, inferring the possibility of in vivo conjugation. The broad resistance carried on these plasmids is a further worrying development for India, which already has high levels of antibiotic resistance

Characterizing the Neurophysiological Correlates of Age-Related Cognitive Decline with Corticomotor Transcranial Magnetic Stimulation

The field of Alzheimer's Disease and Related Dementia (ADRD) is currently in a state of flux, with a push to disarticulate the pathobiological and clinico-behavioral facets of the disease. Concurrently, the same tailwinds propelling this reconceptualization have provoked increased attention on the preclinical stages of the disease continuum. These changes are, in part, driven by necessity. Repeated clinical failures underscore that 1) care must be taken to disambiguate the relatively imprecise clinical phenotype of amnestic dementia by focusing on more specific pathobiological entities, and 2) the manifestation of clinico-behavioral impairment represents the late stages of the ADRD continuum that are likely medically refractory conditions necessitating earlier intervention. As the field continues to shift focus toward the nascent, preclinical stages of the disease, there is an urgent unmet need to better characterize risk profiles for cognitive deterioration. Beyond the hallmark proteinopathies of AD, complementary neurophysiological features of cortical excitability and neural plasticity may add depth and precision to forecasting an individual's clinical trajectory along this continuum. Corticomotor Transcranial Magnetic Stimulation (TMS) may have utility in this regard as a tool capable of generating an array of relevant proxy measures in this domain. The following dissertation explores this potential utility by characterizing TMS-derived neurophysiological correlates of cognitive aging. Chapter 1 provides in-depth discussions introducing the capabilities of corticomotor TMS and describing the current landscape of ADRD research. Chapter 2 details the first cross-sectional study I completed in this area of investigation, where we generated novel findings suggestive of diminished homeostatic metaplasticity in this population of interest. Chapter 3 entails a systematic review and meta-analysis I co-authored, where we quantitively assessed the extant literature reporting on corticomotor TMS proxy measures in Mild Cognitive Impairment and AD. Chapter 4 details the final study in this series of works, where we took lessons learned from the preceding meta-analysis and attempted to fill in the gaps that we identified in the literature. In Chapter 5, I tie these works together in a discussion that also addresses limitations and looks ahead to future directions

The bidirectional gut-brain-microbiota axis as a potential nexus between traumatic brain injury, inflammation, and disease

As head injuries and their sequelae have become an increasingly salient matter of public health, experts in the field have made great progress elucidating the biological processes occurring within the brain at the moment of injury and throughout the recovery thereafter. Given the extraordinary rate at which our collective knowledge of neurotrauma has grown, new insights may be revealed by examining the existing literature across disciplines with a new perspective. This article will aim to expand the scope of this rapidly evolving field of research beyond the confines of the central nervous system (CNS). Specifically, we will examine the extent to which the bidirectional influence of the gut-brain axis modulates the complex biological processes occurring at the time of traumatic brain injury (TBI) and over the days, months, and years that follow. In addition to local enteric signals originating in the gut, it is well accepted that gastrointestinal (GI) physiology is highly regulated by innervation from the CNS. Conversely, emerging data suggests that the function and health of the CNS is modulated by the interaction between 1) neurotransmitters, immune signaling, hormones, and neuropeptides produced in the gut, 2) the composition of the gut microbiota, and 3) integrity of the intestinal wall serving as a barrier to the external environment. Specific to TBI, existing pre-clinical data indicates that head injuries can cause structural and functional damage to the GI tract, but research directly investigating the neuronal consequences of this intestinal damage is lacking. Despite this void, the proposed mechanisms emanating from a damaged gut are closely implicated in the inflammatory processes known to promote neuropathology in the brain following TBI, which suggests the gut-brain axis may be a therapeutic target to reduce the risk of Chronic Traumatic Encephalopathy and other neurodegenerative diseases following TBI. To better appreciate how various peripheral influences are implicated in the health of the CNS following TBI, this paper will also review the secondary biological injury mechanisms and the dynamic pathophysiological response to neurotrauma. Together, this review article will attempt to connect the dots to reveal novel insights into the bidirectional influence of the gut-brain axis and propose a conceptual model relevant to the recovery from TBI and subsequent risk for future neurological conditions.12 month embargo; Available online 17 May 2017.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Bioluminescence in a Complex Coastal Environment: 2. Prediction of Bioluminescent Source Depth From Spectral Water-leaving Radiance

Many bioluminescence observations are made from the ocean\u27s surface. However, the depth of the bioluminescent source is difficult to estimate on the basis of surface observations alone, given the variable light attenuation of unknown concentrations of water column constituents such as phytoplankton, colored dissolved organic matter, and detritus. Part 1 of this paper showed that bioluminescent water-leaving radiance signals are detectable, even in extremely turbid and dynamic coastal waters. Here, in part 2 of this paper, we analyze the water-leaving radiance patterns of bioluminescence modeled by HydroLight 4.2 to determine if the depth of the bioluminescent source can be estimated from its spectral signature. We find that the depth of the bioluminescent source is contained within the spectral signal and can be elucidated by simple neural networks. These networks can predict the depth of a bioluminescent layer with great accuracy, solely on the basis of the spectral shape of bioluminescent water-leaving radiance in a variety of water column and bottom type conditions. In addition, we found that as little as three wavelengths from the spectrum of water-leaving radiance are sufficient for an accurate determination of the depth of the bioluminescent source

Human brain diffusion tensor imaging at submillimeter isotropic resolution on a 3Tesla clinical MRI scanner

International audienceThe advantages of high-resolution diffusion tensor imaging (DTI) have been demonstrated in a recent post-mortem human brain study (Miller et al., NeuroImage 2011;57(1):167-181), showing that white matter fiber tracts can be much more accurately detected in data at a submillimeter isotropic resolution. To our knowledge, in vivo human brain DTI at a submillimeter isotropic resolution has not been routinely achieved yet because of the difficulty in simultaneously achieving high resolution and high signal-to-noise ratio (SNR) in DTI scans. Here we report a 3D multi-slab interleaved EPI acquisition integrated with multiplexed sensitivity encoded (MUSE) reconstruction, to achieve high-quality, high-SNR and submillimeter isotropic resolution (0.85×0.85×0.85mm(3)) in vivo human brain DTI on a 3Tesla clinical MRI scanner. In agreement with the previously reported post-mortem human brain DTI study, our in vivo data show that the structural connectivity networks of human brains can be mapped more accurately and completely with high-resolution DTI as compared with conventional DTI (e.g., 2×2×2mm(3))

Exploring the potential of combining transcranial magnetic stimulation and electroencephalography to investigate mild cognitive impairment and Alzheimer’s disease: a systematic review

Transcranial magnetic stimulation (TMS) and electroencephalography (EEG) are non-invasive techniques used for neuromodulation and recording brain electrical activity, respectively. The integration of TMS-EEG has emerged as a valuable tool for investigating the complex mechanisms involved in age-related disorders, such as mild cognitive impairment (MCI) and Alzheimer’s disease (AD). By systematically synthesizing TMS-EEG studies, this review aims to shed light on the neurophysiological mechanisms underlying MCI and AD, while also exploring the practical applications of TMS-EEG in clinical settings. PubMed, ScienceDirect, and PsychInfo were selected as the databases for this review. The 22 eligible studies included a total of 592 individuals with MCI or AD as well as 301 cognitively normal adults. TMS-EEG assessments unveiled specific patterns of corticospinal excitability, plasticity, and brain connectivity that distinguished individuals on the AD spectrum from cognitively normal older adults. Moreover, the TMS-induced EEG features were observed to be correlated with cognitive performance and the presence of AD pathological biomarkers. The comprehensive examination of the existing studies demonstrates that the combination of TMS and EEG has yielded valuable insights into the neurophysiology of MCI and AD. This integration shows great potential for early detection, monitoring disease progression, and anticipating response to treatment. Future research is of paramount importance to delve into the potential utilization of TMS-EEG for treatment optimization in individuals with MCI and AD.National Institute on Aging12 month embargo; first published 15 February 2024This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Comparison of train-of-four ratios measured with Datex-Ohmeda's M-NMT MechanoSensor (TM) and M-NMT ElectroSensor (TM)

Neuromuscular blockade is usually monitored using train-of-four (TOF) stimulation pattern. A TOF ratio of higher than 90 % is recommended to reduce the risk of adverse effects after anaesthesia. TOF ratio 90 % is used in clinical practice with all different neuromuscular monitors. Kinemyography (KMG) is one commercialized method to obtain numerical TOF values. We compared the KMG data obtained with Datex M-NMT MechanoSensor (TM) module, to the EMG data collected with Datex ElectroSensor (TM), during clinical anaesthesia. Ipsilateral comparisons of the sensors were performed in 20 female patients during clinical procedures in propofol-remifentanil anaesthesia. After initial bolus dose of rocuronium (0.6 mg/kg), the spontaneous recovery of TOF ratio and T1 % were monitored. KMG gave higher TOF values than EMG. The difference was significant at KMG TOF values of 40 % or higher. After anaesthetic induction, but before administration of rocuronium, both TOF sensor values drifted from the TOF value of 1.0, showing either significant spontaneous fade (T1 > T4) or tendency of reverse fade (T1 <T4). KMG overestimates the recovery from neuromuscular blockade when compared with EMG. KMG and EMG cannot be used interchangeably, and TOF ratio 90 % cannot be considered as adequate level of recovery with all monitoring devices.Peer reviewe

Maintenance and Representation of Mind Wandering during Resting-State fMRI

International audienceMajor advances in resting-state functional magnetic resonance imaging (fMRI) techniques in the last two decades have provided a tool to better understand the functional organization of the brain both in health and illness. Despite such developments, characterizing regulation and cerebral representation of mind wandering, which occurs unavoidably during resting-state fMRI scans and may induce variability of the acquired data, remains a work in progress. Here, we demonstrate that a decrease or decoupling in functional connectivity involving the caudate nucleus, insula, medial prefrontal cortex and other domain-specific regions was associated with more sustained mind wandering in particular thought domains during resting-state fMRI. Importantly, our findings suggest that temporal and between-subject variations in functional connectivity of above-mentioned regions might be linked with the continuity of mind wandering. Our study not only provides a preliminary framework for characterizing the maintenance and cerebral representation of different types of mind wandering, but also highlights the importance of taking mind wandering into consideration when studying brain organization with resting-state fMRI in the future. Over the past two decades, resting-state functional connectivity measured by functional magnetic resonance imaging (fMRI) has played an essential role in understanding brain functional networks in healthy and patient populations 1–5. Resting-state functional connectivity is measured by the temporal co-activation level of spontaneous fMRI signals between spatially distinct brain regions in the absence of a perceptual or behavioral task 6. Although the participants are not engaged in any particular task, there is increasing evidence that spontaneous thoughts (known as mind wandering, daydreaming, self-generated mental activity or task-unrelated thought) that are minimally constrained by external perception emerge during fMRI scans and may potentially affect resting-state fMRI data 7,8. Mind wandering during resting-state fMRI has been assessed using different approaches. Questionnaires can be administered, following the resting-state fMRI scan, in which participants are asked to report the presence and frequency of spontaneous thoughts across various domains. Resting-state fMRI studies have employed several types of retrospective measures to assess spontaneous thoughts: Amsterdam Resting-State Questionnaire (ARSQ) 9 , New York Cognition Questionnaire (NYC-Q) 10–12 , and Resting-State Questionnaire (ReSQ) 13,14. Alternatively, mind-wandering has been assessed using experience or thought sampling in conjunction with resting-state fMRI scanning 15–20. While regions within the default mode networ