Impairment in recognition memory may be associated with near-term risk for suicide attempt in a high-risk sample.

INTRODUCTION: Prior work has implicated several neurocognitive domains, including memory, in patients with a history of prior suicide attempt. The current study evaluated whether a delayed recognition test could enhance prospective prediction of near-term suicide outcomes in a sample of patients at high-risk for suicide. METHODS: 132 Veterans at high-risk for suicide completed a computer-based recognition memory test including semantically-related and -unrelated words. Outcomes were coded as actual suicide attempt (ASA), other suicide-related event (OtherSE) such as aborted/interrupted attempt or preparatory behavior, or neither (noSE), within 90 days after testing. RESULTS: Reduced performance was a significant predictor of upcoming ASA, but not OtherSE, after controlling for standard clinical variables such as current suicidal ideation and history of prior suicide attempt. However, compared to the noSE reference group, the OtherSE group showed a reduction in the expected benefit of semantic relatedness in recognizing familiar words. A computational model, the drift diffusion model (DDM), to explore latent cognitive processes, revealed the OtherSE group had decreased decisional efficiency for semantically-related compared to semantically-unrelated familiar words. LIMITATIONS: This study was a secondary analysis of an existing dataset, involving participants in a treatment trial, and requires replication; ~10 % of the sample was excluded from analysis due to failure to master the practice tasks and/or apparent noncompliance. CONCLUSION: Impairments in recognition memory may be associated with near-term risk for suicide attempt, and may provide a tool to improve prediction of when at-risk individuals may be transitioning into a period of heightened risk for suicide attempt.

Reward and Punishment Learning as Predictors of Cognitive Behavioral Therapy Response in Parkinson's Disease Comorbid with Clinical Depression.

Depression is highly comorbid among individuals with Parkinson's Disease (PD), who often experience unique challenges to accessing and benefitting from empirically supported interventions like Cognitive Behavioral Therapy (CBT). Given the role of reward processing in both depression and PD, this study analyzed a subset (N = 25) of participants who participated in a pilot telemedicine intervention of PD-informed CBT, and also completed a Reward- and Punishment-Learning Task (RPLT) at baseline. At the conclusion of CBT, participants were categorized into treatment responders (n = 14) and non-responders (n = 11). Responders learned more optimally from negative rather than positive feedback on the RPLT, while this pattern was reversed in non-responders. Computational modeling suggested group differences in learning rate to negative feedback may drive the observed differences. Overall, the results suggest that a within-subject bias for punishment-based learning might help to predict response to CBT intervention for depression in those with PD.Plain Language Summary Performance on a Computerized Task may predict which Parkinson's Disease Patients benefit from Cognitive Behavioral Treatment of Clinical DepressionWhy was the study done? Clinical depression regularly arises in individuals with Parkinson's Disease (PD) due to the neurobiological changes with the onset and progression of the disease as well as the unique psychosocial difficulties associated with living with a chronic condition. Nonetheless, psychiatric disorders among individuals with PD are often underdiagnosed and likewise undertreated for a variety of reasons. The results of our study have implications about how to improve the accuracy and specificity of mental health treatment recommendations in the future to maximize benefits for individuals with PD, who often face additional barriers to accessing quality mental health treatment.What did the researchers do? We explored whether performance on a computerized task called the Reward- and Punishment-Learning Task (RPLT) helped to predict response to Cognitive Behavioral Therapy (CBT) for depression better than other predictors identified in previous studies. Twenty-five individuals with PD and clinical depression that completed a 10-week telehealth CBT program were assessed for: Demographics (Age, gender, etc.); Clinical information (PD duration, mental health diagnoses, levels of anxiety/depression, etc.); Neurocognitive performance (Memory, processing speed, impulse control, etc.); and RPLT performance.What did the researchers find? A total of 14 participants significantly benefitted from CBT treatment while 11 did not significantly benefit from treatment.There were no differences before treatment in the demographics, clinical information, and neurocognitive performance of those participants who ended up benefitting from the treatment versus those who did not.There were, however, differences before treatment in RPLT performance so that those individuals that benefitted from CBT seemed to learn better from negative feedback.What do the findings mean? Our results suggest that the CBT program benefitted those PD patients with clinical depression that seemed to overall learn best from avoiding punishment rather than obtaining reward which was targeted in CBT by focusing on increasing engagement in rewarding activities. The Reward- and Punishment-Learning Task hence may be a useful tool to help predict treatment response and provide more individualized recommendations on how to best maximize the benefits of psychotherapy for individuals with PD that may struggle to connect to mental health care. Caution is recommended about interpretating these results beyond this study as the overall number of participants was small and the data for this study were collected as part of a previous study so there was no opportunity to include additional measurements of interest.

A Complement to Traditional Treatments for Antibody-Mediated Rejection? Use of Eculizumab in Lung Transplantation: A Review and Early Center Experience.

OBJECTIVE: To review the efficacy and safety of eculizumab for prevention and treatment of antibody-mediated rejection (AMR) in lung transplant recipients (LTRs). DATA SOURCES: A literature search of PubMed and the Cochrane Controlled Trials Register (2007 to mid-October 2023) was performed using the following search terms: eculizumab, complement inhibitor, solid organ transplant, lung transplant, and AMR. STUDY SELECTION AND DATA EXTRACTION: All relevant English-language studies were reviewed and considered. DATA SYNTHESIS: Eculizumab, a monoclonal antibody that binds complement protein C5 to inhibit its cleavage and subsequent generation of the membrane attack complex, is currently approved to treat paroxysmal nocturnal hemoglobinuria, atypical hemolytic uremic syndrome, generalized myasthenia and neuromyelitis optica spectrum disorder. Given the role of antibodies directed against donor antigens that are produced by allospecific B-cells and plasma cells in AMR, eculizumab is being investigated for use within this indication. Three case reports have described the successful use of eculizumab for the prevention and treatment of AMR in LTRs. Given this lack of robust data, evidence for the use of eculizumab in other solid organ transplant recipients is of increased value. Early experiences from a single center's use of eculizumab in LTRs are also described. RELEVANCE TO PATIENT CARE AND CLINICAL PRACTICE: Lung transplant is a recognized treatment for end-stage lung disease, though complications posttransplant can be associated with significant morbidity and mortality. While prevention and management of AMR remains a substantial challenge without comprehensive guidance from societal guidelines, recently published literature may be helpful to guide clinical practice using alternative treatment options. However, this remains an area of great clinical importance, given the impact of AMR on long-term allograft function. CONCLUSIONS: Optimizing use of current therapies, as well as identifying and advancing novel therapeutic modalities such as eculizumab, are vital for the improvement of AMR prevention and treatment in LTRs to extend long-term allograft function and survival.

Altered learning and transfer abilities in Korsakoff's syndrome depending on task complexity.

Korsakoff's syndrome (KS) is characterized by episodic memory impairment due to damage to the medial diencephalic structures. Although commonly associated with chronic alcoholism, starvation due to the hunger strike is one of its nonalcoholic causes. Learning the stimulus-response associations and transferring the just-learned associations to novel combinations were previously tested by specific tasks in memory-impaired patients with hippocampal, basal forebrain, and basal ganglia damage. To add to this previous research, we aimed to use the same tasks in a group of patients with hunger strike-related KS presenting a stable isolated amnestic profile. Twelve patients with hunger strike-related KS and matched healthy controls were tested in two tasks varying in task complexity. Each task included two phases: the initial phase is feedback-based learning of (simple vs. complex) stimulus-response associations, and the following phase is transfer generalization (in the presence vs. absence of feedback). On a task involving simple associations, five patients with KS failed to learn the associations, while the other seven patients showed intact learning and transfer. On the other task involving more complex associations, seven patients showed slower learning and failed at transfer generalization, whereas the other five patients failed even at the acquisition phase. These findings of a task-complexity-related impairment on associative learning and transfer represent a distinct pattern from the spared learning but impaired transfer previously observed on these tasks in patients with medial temporal lobe amnesia.

Prefrontal transcranial magnetic stimulation boosts response vigour during reinforcement learning in healthy adults.

A 10-Hz repetitive transcranial magnetic stimulation to the left dorsal lateral prefrontal cortex has been shown to increase dopaminergic activity in the dorsal striatum, a region strongly implicated in reinforcement learning. However, the behavioural influence of this effect remains largely unknown. We tested the causal effects of 10-Hz stimulation on behavioural and computational characteristics of reinforcement learning. A total of 40 healthy individuals were randomized into active and sham (placebo) stimulation groups. Each participant underwent one stimulation session (1500 pulses) in which stimulation was applied over the left dorsal lateral prefrontal cortex using a robotic arm. Participants then completed a reinforcement learning task sensitive to striatal dopamine functioning. Participants' choices were modelled using a reinforcement learning model (Q-learning) that calculates separate learning rates associated with positive and negative reward prediction errors. Subjects receiving active stimulation exhibited increased reward rate (number of correct responses per second of task activity) compared with those in sham. Computationally, although no group differences were observed, the active group displayed a higher learning rate for correct trials (αG) compared with incorrect trials (αL). Finally, when tested with novel pairs of stimuli, the active group displayed extremely fast reaction times, and a trend towards a higher reward rate. This study provided specific behavioural and computational accounts of altered striatal-mediated behaviour, particularly response vigour, induced by a proposed increase of dopamine activity by 10-Hz stimulation to the left dorsal lateral prefrontal cortex. Together, these findings bolster the use of repetitive transcranial magnetic stimulation to target neurocognitive disturbances attributed to the dysregulation of dopaminergic-striatal circuits.

Improving the prospective prediction of a near-term suicide attempt in veterans at risk for suicide, using a go/no-go task.

BACKGROUND: Neurocognitive testing may advance the goal of predicting near-term suicide risk. The current study examined whether performance on a Go/No-go (GNG) task, and computational modeling to extract latent cognitive variables, could enhance prediction of suicide attempts within next 90 days, among individuals at high-risk for suicide. METHOD: 136 Veterans at high-risk for suicide previously completed a computer-based GNG task requiring rapid responding (Go) to target stimuli, while withholding responses (No-go) to infrequent foil stimuli; behavioral variables included false alarms to foils (failure to inhibit) and missed responses to targets. We conducted a secondary analysis of these data, with outcomes defined as actual suicide attempt (ASA), other suicide-related event (OtherSE) such as interrupted/aborted attempt or preparatory behavior, or neither (noSE), within 90-days after GNG testing, to examine whether GNG variables could improve ASA prediction over standard clinical variables. A computational model (linear ballistic accumulator, LBA) was also applied, to elucidate cognitive mechanisms underlying group differences. RESULTS: On GNG, increased miss rate selectively predicted ASA, while increased false alarm rate predicted OtherSE (without ASA) within the 90-day follow-up window. In LBA modeling, ASA (but not OtherSE) was associated with decreases in decisional efficiency to targets, suggesting differences in the evidence accumulation process were specifically associated with upcoming ASA. CONCLUSIONS: These findings suggest that GNG may improve prediction of near-term suicide risk, with distinct behavioral patterns in those who will attempt suicide within the next 90 days. Computational modeling suggests qualitative differences in cognition in individuals at near-term risk of suicide attempt.

Plasma Serotonin 2A Receptor Autoantibodies Predict Rapid, Substantial Decline in Neurocognitive Performance in Older Adult Veterans with TBI.

Aim: Traumatic brain injury (TBI) was associated with increased plasma serotonin 2A receptor (5-HT2AR) autoantibodies in adults who experienced neurodegenerative complications. We tested whether the baseline presence of plasma serotonin 2A receptor (5-HT2AR) autoantibodies was a significant predictor of the two-year rate of cognitive decline in middle-aged and older adult TBI. Methods: Plasma from thirty-five middle-aged and older adult veterans (mean 65 years old) who had suffered traumatic brain injury was subjected to protein-A affinity chromatography. One-fortieth dilution of the resulting immunoglobulin (Ig) G fraction was tested for binding (in ELISA) to a linear synthetic peptide corresponding to the second extracellular loop region of the human 5-HT2A receptor. All available patients completed baseline and two-year follow-up neurocognitive tests of memory (St Louis University Mental Status), processing speed (Digit Symbol Substitution Test) and executive function (Trails-making Test, Part B). Change in cognitive performance was computed as (two-year - baseline) raw test score. Results: Eighteen patients completed both baseline and two-year follow up neurocognitive tests. TBI patients harboring plasma 5-HT2AR autoantibodies at the baseline examination (n=13) did not differ significantly in their baseline clinical characteristics (age, education level) compared to TBI patients lacking baseline plasma autoantibodies (n=5). Plasma serotonin 2AR antibody-positive patients experienced a significantly greater post-baseline decline in performance on the St Louis University Mental Status test (P=0.0118) and in the Digit Symbol Substitution Test (P=0.011), but not in Trails-making Part B (P=0.129) compared to serotonin 2AR antibody-negative patients. In multivariable linear regression analyses that adjusted for age, baseline presence of plasma 5-HT2AR autoantibody was a significant predictor of the two-year rate of decline in memory, and processing speed. Binding of plasma autoantibody to the serotonin 2A receptor peptide in the enzyme linked immunosorbent assay was also significantly higher (at 1/160th titer of the protein-A eluate= 1 µg/mL IgG) in TBI patients harboring vs. those not harboring baseline plasma 5-HT2AR autoantibodies. Conclusion: These data suggest that plasma 5-hydroxytryptamine 2A receptor autoantibodies which were increased in approximately two-thirds of middle-aged and older adults following traumatic brain injury predicts rapid and substantial declines in cognitive function (memory and processing speed), independent of age.

A practical introduction to using the drift diffusion model of decision-making in cognitive psychology, neuroscience, and health sciences.

Recent years have seen a rapid increase in the number of studies using evidence-accumulation models (such as the drift diffusion model, DDM) in the fields of psychology and neuroscience. These models go beyond observed behavior to extract descriptions of latent cognitive processes that have been linked to different brain substrates. Accordingly, it is important for psychology and neuroscience researchers to be able to understand published findings based on these models. However, many articles using (and explaining) these models assume that the reader already has a fairly deep understanding of (and interest in) the computational and mathematical underpinnings, which may limit many readers' ability to understand the results and appreciate the implications. The goal of this article is therefore to provide a practical introduction to the DDM and its application to behavioral data - without requiring a deep background in mathematics or computational modeling. The article discusses the basic ideas underpinning the DDM, and explains the way that DDM results are normally presented and evaluated. It also provides a step-by-step example of how the DDM is implemented and used on an example dataset, and discusses methods for model validation and for presenting (and evaluating) model results. Supplementary material provides R code for all examples, along with the sample dataset described in the text, to allow interested readers to replicate the examples themselves. The article is primarily targeted at psychologists, neuroscientists, and health professionals with a background in experimental cognitive psychology and/or cognitive neuroscience, who are interested in understanding how DDMs are used in the literature, as well as some who may to go on to apply these approaches in their own work.

Distressed (Type D) personality is predicted by avoidance: evidence from a computer-based avatar task.

Background: One personality type associated with poor health outcomes is distressed (Type D) personality which involves high levels of both social inhibition (SI) and negative affectivity (NA). Type D is also linked to psychopathologies such as post-traumatic stress disorder (PTSD), anxiety disorders, and depression. One mechanism through which personality temperament may result in these psychopathologies is avoidance. Recently, a computer-based measure designed to assess avoidant behaviors, in which the participant guides the behavior of an avatar interacting with strangers in social situations, has been found to be related to various forms of avoidance. In the current study, we extended this work with the avatar avoidance task to determine its relationship to distressed (Type D) personality. We hypothesized that Type D personality, along with SI, but not NA, would be positively related to avatar avoidance scores. We also hypothesized that avatar avoidance scores would be higher in Type D individuals than non-Type D individuals. Methods: A total of 302 undergraduates completed the Distressed Type D Personality Scale (DS-14), and a computer-based avatar avoidance task. Results: Type D and SI, and NA to a lesser degree, were positively correlated with avoidance scores on the avatar task. Furthermore, regression analyses revealed that Type D and SI scores were best predicted by a model including avoidance scores and education level while NA scores were best predicted by a model including avoidance scores. Standard cut-off scores on the DS-14 scale resulted in four groups (i.e., low SI and NA, high SI, high NA, and Type D) which significantly differed in avoidance scores. Specifically, Type D individuals had higher avoidance scores than the other three groups. Taken together these findings support a role for avoidance in Type D personality. The computer-based avatar avoidance task may be particularly relevant as an ecologically valid measure to identify avoidance in a virtual setting for use with individuals expressing Type D personality who may be unwilling or unable to accurately self-report or describe their own avoidant tendencies.

Recipient selection, timing of referral, and listing for lung transplantation.

Recipient selection for lung transplantation is a balance between providing access to transplantation to maximum patients, while utilizing this limited resource in the most optimal way. This review summarizes the current literature and recommendations about referral, listing, and evaluation of lung transplant candidates, with a focus on patients considered to have high risk characteristics.

Clazakizumab for desensitization in highly sensitized patients awaiting transplantation.

Alloantibodies are a significant barrier to successful transplantation. While desensitization has emerged, efficacy is limited. Interleukin-6 (IL-6) is an important mediator of inflammation and immune cell activation. Persistent IL-6 production increases the risk for alloantibody production. Here we report our experience with clazakizumab (anti-IL-6) for desensitization of highly HLA-sensitized patients (HS). From March 2018 to September 2020, 20 HS patients were enrolled in an open label pilot study to assess safety and limited efficacy of clazakizumab desensitization. Patients received PLEX, IVIg, and clazakizumab 25 mg monthly X6. If transplanted, graft function, pathology, HLA antibodies and regulatory immune cells were monitored. Transplanted patients received standard immunosuppression and clazakizumab 25 mg monthly posttransplant. Clazakizumab was well tolerated and associated with significant reductions in class I and class II antibodies allowing 18 of 20 patients to receive transplants with no DSA rebound in most. Significant increases in Treg and Breg cells were seen posttransplant. Antibody-mediated rejection occurred in three patients. The mean estimated glomerular filtration rate at 12 months was 58 ± 29 ml/min/1.73 m2 . Clazakizumab was generally safe and associated with significant reductions in HLA alloantibodies and high transplant rates for highly-sensitized patients. However, confirmation of efficacy for desensitization requires assessment in randomized controlled trials.

Attentional control may be modifiable with Mindfulness-Based Cognitive Therapy to Prevent Suicide.

OBJECTIVE: To test whether Mindfulness-Based Cognitive Therapy to Prevent Suicide (MBCT-S) is associated with improvement in attentional control, an objective marker of suicide attempt. METHOD: In the context of a randomized clinical trial targeting suicide risk in Veterans, computerized Stroop and emotion Stroop (E-Stroop) tasks were administered 3 times over 6-months follow-up to 135 high suicide risk Veterans. Seventy were randomized to receive MBCT-S in addition to enhanced treatment as usual (eTAU), and 65 were randomized to eTAU only. E-Stroop word types included positively- and negatively-valenced emotion, suicide, and combat-related words. Interference scores and mixed effects linear regression analyses were used. RESULTS: Veterans receiving MBCT-S showed a more favorable trajectory of attentional control over time, as indicated by performance on two E-Stroop tasks. Combat-stress interference scores improved over time among Veterans in MBCT-S. Interference processing time for negative affective words deteriorated over time among Veterans receiving eTAU only. CONCLUSIONS: MBCT-S may effectively target attentional control, and in particular reduce processing time during affective interference, in high suicide risk Veterans. Future studies to replicate these findings are warranted.

Respiratory Care Student Readiness for the Clinical Phase of the Program.

BACKGROUND: In a baccalaureate degree program in respiratory care, the first 2 years of the program are spent completing liberal arts and elective requirements. The last 2 years are comprised of respiratory care core courses and the clinical phase of the program. The purpose of this investigation was two-fold: Did students truly understand what the major entailed during the first 2 years of the curriculum, and secondly, did the preclinical math and science courses prepare them to be successful in completing the clinical phase of the curriculum during the last 2 years? The primary goal of this project was to identify if these two factors, combined or separately, can be linked to attrition in the program. METHODS: Third- and fourth-year respiratory care students in the university answered a 10-question survey via SurveyMonkey. Fifty-seven students from 2018-2019 were surveyed with a return rate of 63% (n=36). RESULTS: Survey results revealed that 75% of students felt prepared entering the clinical phase of the program. Moreover, 78% felt, specifically, that the required math and science courses prepared them for the core courses involving a basic understanding of medical physics and computation of formulas. Only 36% admitted they knew exactly what the profession entailed as a freshman and sophomore. CONCLUSION: Results indicate the math and science courses required during the first 2 years do prepare students for the clinical phase of the program. However, students need more exposure to the major, and it is important to require an introduction course during the freshman and sophomore year to introduce the respiratory care profession and provide an overview of the major and the curriculum. Increased knowledge of the profession of respiratory care, during the early stages of having enrolled in this major, could reduce student attrition.

Pyridostigmine bromide, chlorpyrifos, and DEET combined Gulf War exposure insult depresses mitochondrial function in neuroblastoma cells.

Gulf War Illness (GWI) is defined by the Centers for Disease Control and Prevention (CDC) as a multi-symptom illness having at least one symptom from two of three factors, which include: fatigue, mood-cognition problems, and musculoskeletal disorders. The cluster of long-term symptoms is unique to military personnel from coalition countries including United States, Australia, and the United Kingdom that served in Operation Desert Storm from 1990 to 1991. Reporting of these symptoms is much lower among soldiers deployed in other parts of the world like Bosnia during the same time period. The exact cause of GWI is unknown, but combined exposure to N,N-diethyl-m-toluamide (DEET), organophosphates like chlorpyrifos (CPF), and pyridostigmine bromide (PB), has been hypothesized as a potential mechanism. Mitochondrial dysfunction is known to occur in most neurodegenerative diseases that share symptoms with GWI and has therefore been implicated in GWI. Although exposure to these and other toxicants continues to be investigated as potential causes of GWI, their combined impact on mitochondrial physiology remains unknown. In this study, the effects of combined GWI toxicant exposure on mitochondrial function were determined in a commonly used and readily available immortalized cell line (N2a), whose higher rate of oxygen consumption resembles that of highly metabolic neurons in vivo. We report that combined exposure containing pesticide CPF 71 µM, insect repellants DEET 78 µM, and antitoxins PB 19 µM, causes profound mitochondrial dysfunction after a 4-h incubation resulting in decreased mitochondrial respiratory states in the absence of proapoptotic signaling, proton leak, or significant increase in reactive oxygen species production.

Incidence of venous thromboembolism in coronavirus disease 2019: An experience from a single large academic center.

BACKGROUND: Infection with the novel severe acute respiratory syndrome coronavirus 2 has been associated with a hypercoagulable state. Emerging data from China and Europe have consistently shown an increased incidence of venous thromboembolism (VTE). We aimed to identify the VTE incidence and early predictors of VTE at our high-volume tertiary care center. METHODS: We performed a retrospective cohort study of 147 patients who had been admitted to Temple University Hospital with coronavirus disease 2019 (COVID-19) from April 1, 2020 to April 27, 2020. We first identified the VTE (pulmonary embolism [PE] and deep vein thrombosis [DVT]) incidence in our cohort. The VTE and no-VTE groups were compared by univariable analysis for demographics, comorbidities, laboratory data, and treatment outcomes. Subsequently, multivariable logistic regression analysis was performed to identify the early predictors of VTE. RESULTS: The 147 patients (20.9% of all admissions) admitted to a designated COVID-19 unit at Temple University Hospital with a high clinical suspicion of acute VTE had undergone testing for VTE using computed tomography pulmonary angiography and/or extremity venous duplex ultrasonography. The overall incidence of VTE was 17% (25 of 147). Of the 25 patients, 16 had had acute PE, 14 had had acute DVT, and 5 had had both PE and DVT. The need for invasive mechanical ventilation (adjusted odds ratio, 3.19; 95% confidence interval, 1.07-9.55) and the admission D-dimer level ≥1500 ng/mL (adjusted odds ratio, 3.55; 95% confidence interval, 1.29-9.78) were independent markers associated with VTE. The all-cause mortality in the VTE group was greater than that in the non-VTE group (48% vs 22%; P = .007). CONCLUSIONS: Our study represents one of the earliest reported from the United States on the incidence rate of VTE in patients with COVID-19. Patients with a high clinical suspicion and the identified risk factors (invasive mechanical ventilation, admission D-dimer level ≥1500 ng/mL) should be considered for early VTE testing. We did not screen all patients admitted for VTE; therefore, the true incidence of VTE could have been underestimated. Our findings require confirmation in future prospective studies.

Case series: Failure of imaging & biochemical markers to capture disease progression in COVID-19.

We report four individuals admitted for acute respiratory failure due to COVID-19 who demonstrated significant clinical improvement prior to discharge and subsequently were readmitted with worsening respiratory failure, elevated inflammatory markers and worsening chest imaging. We propose a multi-disciplinary discharge criterion to establish a safer discharge process including trending inflammatory markers, daily imaging and pursuing follow up CT chest, particularly in individuals with significant morbidities and health disparities.

Dataset of active avoidance in Wistar-Kyoto and Sprague Dawley rats: Experimental data and reinforcement learning model code and output.

Data were collected from 40 Wistar-Kyoto (WKY) and 40 Sprague Dawley (SD) rats during an active escape-avoidance experiment. Footshock could be avoided by pressing a lever during a danger period prior to onset of shock. If avoidance did not occur, a series of footshocks was administered, and the rat could press a lever to escape (terminate shocks). For each animal, data were simplified to the presence or absence of lever press and stimuli in each 12-second time frame. Using the pre-processed dataset, a reinforcement learning (RL) model, based on an actor-critic architecture, was utilized to estimate several different model parameters that best characterized each rat's behaviour during the experiment. Once individual model parameters were determined for all 80 rats, behavioural recovery simulations were run using the RL model with each animal's "best-fit" parameters; the simulated behaviour generated avoidance data (percent of trials avoided during a given experimental session) that could be compared across simulated rats, as is customarily done with empirical data. The datasets representing both the experimental data and the model-generated data can be interpreted in various ways to gain further insight into rat behaviour during avoidance and escape learning. Furthermore, the estimated parameters for each individual rat can be compared across groups. Thus, possible between-strain differences in model parameters can be detected, which might provide insights into strain differences in learning. The software implementing the RL model can also be applied to or serve as a template for other experiments involving acquisition learning. Reference for Co-Submission: K.M. Spiegler, J. Palmieri, K.C.H. Pang, C.E. Myers, A reinforcement-learning model of active avoidance behavior: Differences between Sprague-Dawley and Wistar-Kyoto rats. Behav. Brain Res. (2020 Jun 22[epub ahead of print])  doi: 10.1016/j.bbr.2020.112784.

Serotonin 2A Receptor Autoantibodies Increase in Adult Traumatic Brain Injury In Association with Neurodegeneration.

OBJECTIVE: Traumatic brain injury (TBI) is associated with an increased risk of late neurodegenerative complications via unknown mechanisms. Circulating neurotoxic 5-hydroxytryptamine 2A receptor (5-HT2AR) autoantibodies were reported to increase in subsets of obese type 2 diabetes having microvascular complications. We tested whether 5-HT2AR autoantibodies increase in adults following traumatic brain injury in association with neurodegenerative complications. METHODS: Plasma from thirty-five middle-aged and older adult veterans (mean 65 years old) who had suffered traumatic brain injury was subjected to protein-A affinity chromatography. The resulting immunoglobulin (Ig) G fraction was tested for neurotoxicity (acute neurite retraction, and accelerated cell death) in mouse N2A neuroblastoma cells or for binding to a linear synthetic peptide corresponding to the second extracellular loop region of the human 5-HT2A receptor. RESULTS: Nearly two-thirds of traumatic brain injured-patients harbored 5-HT2AR autoantibodies in their circulation. Active TBI autoantibodies caused neurite retraction in mouse N2A neuroblastoma cells and accelerated N2A cell loss which was substantially prevented by co-incubation with a two hundred and fifty nanomolar concentration of M100907, a highly selective 5-HT2AR antagonist. Antagonists of RhoA/Rho kinase and Gq11/phospholipase C/inositol triphosphate receptor signaling pathways blocked TBI autoantibody-induced neurite retraction. Following traumatic brain injury, autoantibody binding to a 5-HT2A receptor peptide was significantly increased in patients having co-morbid Parkinson's disease (n=3), dementia (n=5), and painful neuropathy (n=8) compared to TBI subsets without neurologic or microvascular complication (n=20). Autoantibody titer was significantly elevated in TBI subsets experiencing multiple neurotraumatic exposures vs. single TBI. Plasma white blood cell, a marker of systemic inflammation, correlated significantly (correlation coefficient r =0.52; P < 0.01) with, 5-HT2A receptor peptide binding of the TBI-autoantibody. CONCLUSION: These data suggest that circulating neurotoxic 5-hydroxytryptamine 2A receptor agonist autoantibodies increase in adults following traumatic brain injury in association with late neurodegenerative complications.

COVID-19 in lung transplant recipients.

Solid organ transplant recipients are considered at high risk for COVID-19 infection due to chronic immune suppression; little data currently exists on the manifestations and outcomes of COVID-19 infection in lung transplant recipients. Here we report 8 cases of COVID-19 identified in patients with a history of lung transplant. We describe the clinical course of disease as well as preexisting characteristics of these patients.