Adaptive sequence divergence forged new neurodevelopmental enhancers in humans.

Searches for the genetic underpinnings of uniquely human traits have focused on human-specific divergence in conserved genomic regions, which reflects adaptive modifications of existing functional elements. However, the study of conserved regions excludes functional elements that descended from previously neutral regions. Here, we demonstrate that the fastest-evolved regions of the human genome, which we term "human ancestor quickly evolved regions" (HAQERs), rapidly diverged in an episodic burst of directional positive selection prior to the human-Neanderthal split, before transitioning to constraint within hominins. HAQERs are enriched for bivalent chromatin states, particularly in gastrointestinal and neurodevelopmental tissues, and genetic variants linked to neurodevelopmental disease. We developed a multiplex, single-cell in vivo enhancer assay to discover that rapid sequence divergence in HAQERs generated hominin-unique enhancers in the developing cerebral cortex. We propose that a lack of pleiotropic constraints and elevated mutation rates poised HAQERs for rapid adaptation and subsequent susceptibility to disease.

A guide to the visual analysis and communication of biomolecular structural data.

Biologists regularly face an increasingly difficult task - to effectively communicate bigger and more complex structural data using an ever-expanding suite of visualization tools. Whether presenting results to peers or educating an outreach audience, a scientist can achieve maximal impact with minimal production time by systematically identifying an audience's needs, planning solutions from a variety of visual communication techniques and then applying the most appropriate software tools. A guide to available resources that range from software tools to professional illustrators can help researchers to generate better figures and presentations tailored to any audience's needs, and enable artistically inclined scientists to create captivating outreach imagery.

The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy.

Successful surgical treatment of drug-resistant epilepsy traditionally relies on the identification of seizure onset zones (SOZs). Connectome-based analyses of electrographic data from stereo electroencephalography (SEEG) may empower improved detection of SOZs. Specifically, connectome-based analyses based on the Interictal Suppression Hypothesis (ISH) posit that when the patient is not having a seizure, SOZs are inhibited by non-SOZs through high inward connectivity and low outward connectivity. However, it is not clear whether there are other motifs that can better identify potential SOZs. Thus, we sought to use unsupervised machine learning to identify network motifs that elucidate SOZs and investigate if there is another motif that outperforms the ISH. Resting-state SEEG data from 81 patients with drug-resistant epilepsy undergoing a pre-surgical evaluation at Vanderbilt University Medical Center were collected. Directed connectivity matrices were computed using the alpha band (8-12Hz). Principal component analysis (PCA) was performed on each patient's connectivity matrix. Each patient's components were analyzed qualitatively to identify common patterns across patients. A quantitative definition was then used to identify the component that most closely matched the observed pattern in each patient. A motif characteristic of the Interictal Suppression Hypothesis (high-inward and low-outward connectivity) was present in all individuals and found to be the most robust motif for identification of SOZs in 64/81 (79%) patients. This principal component demonstrated significant differences in SOZs compared to non-SOZs. While other motifs for identifying SOZs were present in other patients, they differed for each patient, suggesting that seizure networks are patient specific, but the ISH is present in nearly all networks. We discovered that a potentially suppressive motif based on the Interictal Suppression Hypothesis was present in all patients, and it was the most robust motif for SOZs in 79% of patients. Each patient had additional motifs that further characterized SOZs, but these motifs were not common across all patients. This work has the potential to augment clinical identification of SOZs to improve epilepsy treatment.

Correcting signal biases and detecting regulatory elements in STARR-seq data.

High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal.

Indirect structural changes and reduced controllability after temporal lobe epilepsy resection.

OBJECTIVE: To understand the potential behavioral and cognitive effects of mesial temporal resection for temporal lobe epilepsy (TLE) a method is required to characterize network-wide functional alterations caused by a discrete structural disconnection. The objective of this study was to investigate network-wide alterations in brain dynamics of patients with TLE before and after surgical resection of the seizure focus using average regional controllability (ARC), a measure of the ability of a node to influence network dynamics. METHODS: Diffusion-weighted imaging (DWI) data were acquired in 27 patients with drug-resistant unilateral mesial TLE who underwent selective amygdalohippocampectomy. Imaging data were acquired before and after surgery and a presurgical and postsurgical structural connectome was generated from whole-brain tractography. Edge-wise strength, node strength, and node ARC were compared before and after surgery. Direct and indirect edge-wise strength changes were identified using patient-specific simulated resections. Direct edges were defined as primary edges disconnected by the resection zone itself. Indirect edges were secondary measured edge strength changes. Changes in node strength and ARC were then related to both direct and indirect edge changes. RESULTS: We found nodes with significant postsurgical changes in both node strength and ARC surrounding the resection zone (paired t tests, p < .05, Bonferroni corrected). ARC identified additional postsurgical changes in nodes outside of the resection zone within the ipsilateral occipital lobe, which were associated with indirect edge-wise strength changes of the postsurgical network (Fisher's exact test, p < .001). These indirect edge-wise changes were facilitated through the "hub" nodes including the thalamus, putamen, insula, and precuneus. SIGNIFICANCE: Discrete network disconnection from TLE resection results in widespread structural and functional changes not predicted by disconnection alone. These can be well characterized by dynamic controllability measures such as ARC and may be useful for investigating changes in brain function that may contribute to seizure recurrence and behavioral or cognitive changes after surgery.

Structural disconnection relates to functional changes after temporal lobe epilepsy surgery.

Epilepsy surgery consists of surgical resection of the epileptic focus and is recommended for patients with drug-resistant focal epilepsy. However, focal brain lesions can lead to effects in distant brain regions. Similarly, the focal resection in temporal lobe epilepsy surgery has been shown to lead to functional changes distant from the resection. Here we hypothesize that there are changes in brain function caused by temporal lobe epilepsy surgery in regions distant from the resection that are due to their structural disconnection from the resected epileptic focus. Therefore, the goal of this study was to localize changes in brain function caused by temporal lobe epilepsy surgery and relate them to the disconnection from the resected epileptic focus. This study takes advantage of the unique opportunity that epilepsy surgery provides to investigate the effects of focal disconnections on brain function in humans, which has implications in epilepsy and broader neuroscience. Changes in brain function from pre- to post-epilepsy surgery were quantified in a group of temporal lobe epilepsy patients (n = 36) using a measure of resting state functional MRI activity fluctuations. We identified regions with significant functional MRI changes that had high structural connectivity to the resected region in healthy controls (n = 96) and patients based on diffusion MRI. The structural disconnection from the resected epileptic focus was then estimated using presurgical diffusion MRI and related to the functional MRI changes from pre- to post-surgery in these regions. Functional MRI activity fluctuations increased from pre- to post-surgery in temporal lobe epilepsy in the two regions most highly structurally connected to the resected epileptic focus in healthy controls and patients-the thalamus and the fusiform gyrus ipsilateral to the side of surgery (PFWE < 0.05). Broader surgeries led to larger functional MRI changes in the thalamus than more selective surgeries (P < 0.05), but no other clinical variables were related to functional MRI changes in either the thalamus or fusiform. The magnitude of the functional MRI changes in both the thalamus and fusiform increased with a higher estimated structural disconnection from the resected epileptic focus when controlling for the type of surgery (P < 0.05). These results suggest that the structural disconnection from the resected epileptic focus may contribute to the functional changes seen after epilepsy surgery. Broadly, this study provides a novel link between focal disconnections in the structural brain network and downstream effects on function in distant brain regions.

Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease.

Cognitive impairment is the most frequent non-motor symptom in Parkinson's disease and is associated with deficits in a number of cognitive functions including working memory. However, the pathophysiology of Parkinson's disease cognitive impairment is poorly understood. Beta oscillations have previously been shown to play an important role in cognitive functions including working memory encoding. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits increases the spectral power of beta oscillations and results in Parkinson's disease motor symptoms. Analogous changes in parallel cognitive CSTC circuits involving the caudate and dorsolateral prefrontal cortex (DLPFC) may contribute to Parkinson's disease cognitive impairment. The objective of our study is to evaluate whether changes in beta oscillations in the caudate and DLPFC contribute to cognitive impairment in Parkinson's disease patients. To investigate this, we used local field potential recordings during deep brain stimulation surgery in 15 patients with Parkinson's disease. Local field potentials were recorded from DLPFC and caudate at rest and during a working memory task. We examined changes in beta oscillatory power during the working memory task as well as the relationship of beta oscillatory activity to preoperative cognitive status, as determined from neuropsychological testing results. We additionally conducted exploratory analyses on the relationship between cognitive impairment and task-based changes in spectral power in additional frequency bands. Spectral power of beta oscillations decreased in both DLPFC and caudate during working memory encoding and increased in these structures during feedback. Subjects with cognitive impairment had smaller decreases in caudate and DLPFC beta oscillatory power during encoding. In our exploratory analysis, we found that similar differences occurred in alpha frequencies in caudate and theta and alpha in DLPFC. Our findings suggest that oscillatory power changes in cognitive CSTC circuits may contribute to cognitive symptoms in patients with Parkinson's disease. These findings may inform the future development of novel neuromodulatory treatments for cognitive impairment in Parkinson's disease.

The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence.

Why are people with focal epilepsy not continuously having seizures? Previous neuronal signalling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure-onset zones have increased inward connectivity that could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure-onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug-resistant focal epilepsy undergoing presurgical evaluation. We used intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation and non-involved zones. We then used diffusion imaging to acquire estimates of white-matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure-onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inwards connectivity and decreased outwards connectivity using both resting-state (one-way ANOVA, P-value = 3.13 × 10-13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, P-value = 2.5 × 10-3). When controlling for the distance between regions, the difference between inwards and outwards connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect P-value of 2.6 × 10-12). Structure-function coupling analyses revealed that seizure-onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect P-value of 9.76 × 10-21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0 ± 2.2% to classify early propagation and seizure-onset zones. These results suggest that seizure-onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure-onset zones. These findings have implications for the identification of seizure-onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug-resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative and neuromodulation approaches to improve surgical success rates in those suffering from drug-resistant focal epilepsy.

Building the next generation of virtual cells to understand cellular biology.

Cell science has made significant progress by focusing on understanding individual cellular processes through reductionist approaches. However, the sheer volume of knowledge collected presents challenges in integrating this information across different scales of space and time to comprehend cellular behaviors, as well as making the data and methods more accessible for the community to tackle complex biological questions. This perspective proposes the creation of next-generation virtual cells, which are dynamic 3D models that integrate information from diverse sources, including simulations, biophysical models, image-based models, and evidence-based knowledge graphs. These virtual cells would provide statistically accurate and holistic views of real cells, bridging the gap between theoretical concepts and experimental data, and facilitating productive new collaborations among researchers across related fields.

Intraoperative physiology augments atlas-based data in awake deep brain stimulation.

BACKGROUND: Deep brain stimulation (DBS) is commonly performed with patients awake to perform intraoperative microelectrode recordings and/or macrostimulation testing to guide final electrode placement. Supplemental information from atlas-based databases derived from prior patient data and visualised as efficacy heat maps transformed and overlaid onto preoperative MRIs can be used to guide preoperative target planning and intraoperative final positioning. Our quantitative analysis of intraoperative testing and corresponding changes made to final electrode positioning aims to highlight the value of intraoperative neurophysiological testing paired with image-based data to optimise final electrode positioning in a large patient cohort. METHODS: Data from 451 patients with movement disorders treated with 822 individual DBS leads at a single institution from 2011 to 2021 were included. Atlas-based data was used to guide surgical targeting. Intraoperative testing data and coordinate data were retrospectively obtained from a large patient database. Medical records were reviewed to obtain active contact usage and neurologist-defined outcomes at 1 year. RESULTS: Microelectrode recording firing profiles differ per track, per target and inform the locations where macrostimulation testing is performed. Macrostimulation performance correlates with the final electrode track chosen. Centroids of atlas-based efficacy heat maps per target were close in proximity to and may predict active contact usage at 1 year. Overall, patient outcomes at 1 year were improved for patients with better macrostimulation response. CONCLUSIONS: Atlas-based imaging data is beneficial for target planning and intraoperative guidance, and in conjunction with intraoperative neurophysiological testing during awake DBS can be used to individualize and optimise final electrode positioning, resulting in favourable outcomes.

Characterization of resting functional MRI activity alterations across epileptic foci and networks.

Brain network alterations have been studied extensively in patients with mesial temporal lobe epilepsy (mTLE) and other focal epilepsies using resting-state functional magnetic resonance imaging (fMRI). However, little has been done to characterize the basic fMRI signal alterations caused by focal epilepsy. Here, we characterize how mTLE affects the fMRI signal in epileptic foci and networks. Resting-state fMRI and diffusion MRI were collected from 47 unilateral mTLE patients and 96 healthy controls. FMRI activity, quantified by amplitude of low-frequency fluctuations, was increased in the epileptic focus and connected regions in mTLE. Evidence for spread of this epileptic fMRI activity was found through linear relationships of regional activity across subjects, the association of these relationships with functional connectivity, and increased activity along white matter tracts. These fMRI activity increases were found to be dependent on the epileptic focus, where the activity was related to disease severity, suggesting the focus to be the origin of these pathological alterations. Furthermore, we found fMRI activity decreases in the default mode network of right mTLE patients with different properties than the activity increases found in the epileptic focus. This work provides insights into basic fMRI signal alterations and their potential spread across networks in focal epilepsy.

Network dysfunction in pre and postsurgical epilepsy: connectomics as a tool and not a destination.

PURPOSE OF REVIEW: Patients with focal drug-resistant epilepsy (DRE) sometimes continue to have seizures after surgery. Recently, there is increasing interest in using advanced network analyses (connectomics) to better understand this problem. Connectomics has changed the way researchers and clinicians view DRE, but it must be applied carefully in a hypothesis-driven manner to avoid spurious results. This review will focus on studies published in the last 18 months that have thoughtfully used connectomics to advance our fundamental understanding of network dysfunction in DRE - hopefully for the eventual direct benefit to patient care. RECENT FINDINGS: Impactful recent findings have centered on using patient-specific differences in network dysfunction to predict surgical outcome. These works span functional and structural connectivity and include the modalities of functional and diffusion magnetic resonance imaging (MRI) and electrophysiology. Using functional MRI, many groups have described an increased functional segregation outside of the surgical resection zone in patients who fail surgery. Using electrophysiology, groups have reported network characteristics of resected tissue that suggest whether a patient will respond favorably to surgery. SUMMARY: If we can develop accurate models to outline functional and structural network characteristics that predict failure of standard surgical approaches, then we can not only improve current clinical decision-making; we can also begin developing alternative treatments including network approaches to improve surgical success rates.

Temporal lobe epilepsy lateralisation and surgical outcome prediction using diffusion imaging.

OBJECTIVE: We sought to augment the presurgical workup of medically refractory temporal lobe epilepsy by creating a supervised machine learning technique that uses diffusion-weighted imaging to classify patient-specific seizure onset laterality and surgical outcome. METHODS: 151 subjects were included in this analysis: 62 patients (aged 18-68 years, 36 women) and 89 healthy controls (aged 18-71 years, 47 women). We created a supervised machine learning technique that uses diffusion-weighted metrics to classify subject groups. Specifically, we sought to classify patients versus healthy controls, unilateral versus bilateral temporal lobe epilepsy, left versus right temporal lobe epilepsy and seizure-free versus not seizure-free surgical outcome. We then reduced the dimensionality of derived features with community detection for ease of interpretation. RESULTS: We classified the subject groups in withheld testing data sets with a cross-fold average testing areas under the receiver operating characteristic curve of 0.745 for patients versus healthy controls, 1.000 for unilateral versus bilateral seizure onset, 0.662 for left versus right seizure onset, 0.800 for left-sided seizure-free vsersu not seizure-free surgical outcome and 0.775 for right-sided seizure-free versus not seizure-free surgical outcome. CONCLUSIONS: This technique classifies important clinical decisions in the presurgical workup of temporal lobe epilepsy by generating discerning white-matter features. We believe that this work augments existing network connectivity findings in the field by further elucidating important white-matter pathology in temporal lobe epilepsy. We hope that this work contributes to recent efforts aimed at using diffusion imaging as an augmentation to the presurgical workup of this devastating neurological disorder.

Nanomechanics and Morphology of Simulated Respiratory Particles.

The impact of respiratory particle composition on the equilibrium morphology and phase is not well understood. Furthermore, the effects of these different phases and morphologies on the viability of viruses embedded within these particles are equally unknown. Physiologically relevant respiratory fluid analogues were constructed, and their hygroscopic behavior was measured using an ensemble technique. A relationship between hygroscopicity and protein concentration was determined, providing additional validation to the high protein content of respiratory aerosol measured in prior works (>90%). It was found that the salt component of the respiratory particles could crystallize as a single crystal, multiple crystals, or would not crystallize at all. It was found that dried protein particles at indoor-relevant climatic conditions could exist separately in a glassy (∼77% of particles) or viscoelastic state (∼23% of particles). The phase state and morphology of respiratory particles may influence the viability of embedded pathogens. We recommend that pathogen research aiming to mimic the native composition of respiratory fluid should use a protein concentration of at least 90% by solute volume to improve the representativity of the pathogen's microenvironment.

Bayesian estimation of genetic regulatory effects in high-throughput reporter assays.

MOTIVATION: High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA. RESULTS: We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters. AVAILABILITY AND IMPLEMENTATION: The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images.

PURPOSE: Diffusion weighted MRI imaging (DWI) is often subject to low signal-to-noise ratios (SNRs) and artifacts. Recent work has produced software tools that can correct individual problems, but these tools have not been combined with each other and with quality assurance (QA). A single integrated pipeline is proposed to perform DWI preprocessing with a spectrum of tools and produce an intuitive QA document. METHODS: The proposed pipeline, built around the FSL, MRTrix3, and ANTs software packages, performs DWI denoising; inter-scan intensity normalization; susceptibility-, eddy current-, and motion-induced artifact correction; and slice-wise signal drop-out imputation. To perform QA on the raw and preprocessed data and each preprocessing operation, the pipeline documents qualitative visualizations, quantitative plots, gradient verifications, and tensor goodness-of-fit and fractional anisotropy analyses. RESULTS: Raw DWI data were preprocessed and quality checked with the proposed pipeline and demonstrated improved SNRs; physiologic intensity ratios; corrected susceptibility-, eddy current-, and motion-induced artifacts; imputed signal-lost slices; and improved tensor fits. The pipeline identified incorrect gradient configurations and file-type conversion errors and was shown to be effective on externally available datasets. CONCLUSIONS: The proposed pipeline is a single integrated pipeline that combines established diffusion preprocessing tools from major MRI-focused software packages with intuitive QA.

Utility of Three Nebulizers in Investigating the Infectivity of Airborne Viruses.

Laboratory-generated bioaerosols are widely used in aerobiology studies of viruses; however, few comparisons of alternative nebulizers exist. We compared aerosol production and virus survival for a Collison nebulizer, vibrating mesh nebulizer (VMN), and hydraulic spray atomizer (HSA). We also measured the dry size distribution of the aerosols produced and calculated the droplet sizes before evaporation and the dry size distribution from normal saline solution. Dry count median diameters of 0.11, 0.22, and 0.30 µm were found for normal saline from the Collison nebulizer, VMN, and HSA, respectively. The volume median diameters were 0.323, 1.70, and 1.30 µm, respectively. The effect of nebulization on the viability of two influenza A viruses (IAVs) (H1N1 and H3N2) and human rhinovirus 16 (HRV-16) was assessed by nebulization into an SKC BioSampler. The HSA had the least impact on surviving fractions (SFs) of H1N1 and H3N2 (89% ± 3% and 94% ± 2%, respectively), followed by the Collison nebulizer (83% ± 1% and 82% ± 2%, respectively). The VMN yielded SFs of 78% ± 2% and 76% ± 2%, respectively. Conversely, for HRV-16, the VMN produced higher SFs (87% ± 8%). Our findings indicate that there were no statistical differences between SFs of the viruses nebulized by these nebulizers. However, VMN produced higher aerosol concentrations within the airborne size range, making it more suitable where high aerosol mass production is required. IMPORTANCE Viral respiratory tract infections cause millions of lost days of work and physician visits globally, accounting for significant morbidity and mortality. Respiratory droplets and droplet nuclei from infected hosts are the potential carriers of such viruses within indoor environments. Laboratory-generated bioaerosols are applied in understanding the transmission and infection of viruses, modeling the physiological aspects of bioaerosol generation in a controlled environment. However, little comparative characterization exists for nebulizers used in infectious disease aerobiology, including Collison nebulizer, vibrating mesh nebulizer, and hydraulic spray atomizer. This study characterized the physical features of aerosols generated by laboratory nebulizers and their performance in producing aerosols at a size relevant to airborne transmission used in infectious disease aerobiology. We also determined the impact of nebulization mechanisms of these nebulizers on the viability of human respiratory viruses, including IAV H1N1, IAV H3N2, and HRV-16.

Susceptibility of an Airborne Common Cold Virus to Relative Humidity.

The viability of airborne respiratory viruses varies with ambient relative humidity (RH). Numerous contrasting reports spanning several viruses have failed to identify the mechanism underlying this dependence. We hypothesized that an "efflorescence/deliquescence divergent infectivity" (EDDI) model accurately predicts the RH-dependent survival of airborne human rhinovirus-16 (HRV-16). We measured the efflorescence and deliquescence RH (RHE and RHD, respectively) of aerosols nebulized from a protein-enriched saline carrier fluid simulating the human respiratory fluid and found the RH range of the aerosols' hygroscopic hysteresis zone (RHE-D) to be 38-68%, which encompasses the preferred RH for indoor air (40-60%). The carrier fluid containing HRV-16 was nebulized into the sub-hysteresis zone (RHD) air, to set the aerosols to the effloresced/solid or deliquesced/liquid state before transitioning the RH into the intermediate hysteresis zone. The surviving fractions (SFs) of the virus were then measured 15 min post nebulization. SFs were also measured for aerosols introduced directly into the RHD zones without transition. SFs for transitioned aerosols in the hysteresis zone were higher for effloresced (0.17 ± 0.02) than for deliquesced (0.005 ± 0.005) aerosols. SFs for nontransitioned aerosols in the RHD zones were 0.18 ± 0.06, 0.05 ± 0.02, and 0.20 ± 0.05, respectively, revealing a V-shaped SF/RH dependence. The EDDI model's prediction of enhanced survival in the hysteresis zone for effloresced carrier aerosols was confirmed.

People with mesial temporal lobe epilepsy have altered thalamo-occipital brain networks.

While temporal lobe epilepsy (TLE) is a focal epilepsy, previous work demonstrates that TLE causes widespread brain-network disruptions. Impaired visuospatial attention and learning in TLE may be related to thalamic arousal nuclei connectivity. Our prior preliminary work in a smaller patient cohort suggests that patients with TLE demonstrate abnormal functional connectivity between central lateral (CL) thalamic nucleus and medial occipital lobe. Others have shown pulvinar connectivity disturbances in TLE, but it is incompletely understood how TLE affects pulvinar subnuclei. Also, the effects of epilepsy surgery on thalamic functional connectivity remains poorly understood. In this study, we examine the effects of TLE on functional connectivity of two key thalamic arousal-nuclei: lateral pulvinar (PuL) and CL. We evaluate resting-state functional connectivity of the PuL and CL in 40 patients with TLE and 40 controls using fMRI. In 25 patients, postoperative images (>1 year) were also compared with preoperative images. Compared to controls, patients with TLE exhibit loss of normal positive connectivity between PuL and lateral occipital lobe (p < 0.05), and a loss of normal negative connectivity between CL and medial occipital lobe (p < 0.01, paired t-tests). FMRI amplitude of low-frequency fluctuation (ALFF) in TLE trended higher in ipsilateral PuL (p = 0.06), but was lower in the lateral occipital (p < 0.01) and medial occipital lobe in patients versus controls (p < 0.05, paired t-tests). More abnormal ALFF in the ipsilateral lateral occipital lobe is associated with worse preoperative performance on Rey Complex Figure Test Immediate (p < 0.05, r = 0.381) and Delayed scores (p < 0.05, r = 0.413, Pearson's Correlations). After surgery, connectivity between PuL and lateral occipital lobe remains abnormal in patients (p < 0.01), but connectivity between CL and medial occipital lobe improves and is no longer different from control values (p > 0.05, ANOVA, post hoc Fischer's LSD). In conclusion, thalamic arousal nuclei exhibit abnormal connectivity with occipital lobe in TLE, and some connections may improve after surgery. Studying thalamic arousal centers may help explain distal network disturbances in TLE.

Can an ECG performed during emergency department triage and interpreted as normal by computer analysis safely wait for clinician review until the time of patient assessment? A pilot study.

INTRODUCTION: Electrocardiograms (ECGs) are frequently performed during patient triage in Emergency Departments (EDs). Emergency Physicians (EPs) are interrupted during other tasks to review ECGs. Critics believe this practice could lead to distraction with consequent medical error and decision fatigue. ECGs can be interpreted by computer software at the time of capture; some evidence exists to suggest that an ECG performed during ED triage with an immediate computer interpretation (ICI) of 'normal' will seldom contain information necessitating a change to triage management. MATERIAL AND METHODS: All ED triage ECGs performed in the Royal Derby Hospital between 13th July 2017 and 12th July 2018 in patients without chest pain and with an ICI of 'normal' were identified through a database search. Forty were randomly selected and reviewed by two EPs (blinded to patient details, ICI and outcome) who were asked to identify those that required a change to triage management. RESULTS: The study processes were feasible. At least one of the two EP reviewers felt that a change to triage management was required in 48% of cases (e.g. "review patient", "obtain blood gas", "review old ECGs"); they agreed on the need for change of management in 13% of cases. An ICI of normal had a NPV of 53% (95% CI 37-67%) for the need for a change to triage management based upon ECG findings. Inter-observer agreement was poor (kappa = 0.17). CONCLUSIONS: Based on these results, ED triage ECGs should still be presented to EPs for immediate review regardless of the ICI. Inter-observer agreement between EPs was poor. Further research is required to link triage ECG interpretation, need for intervention and patient outcome.