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ABSTRACT Introduction Many patients report neuropsychiatric symptoms after SARS‐CoV‐2 infection. Data on prevalence of post‐COVID‐19 condition (PCC) vary due to the lack of specific diagnostic criteria, the report of unspecific symptoms, and reliable biomarkers. Methods PCC patients seen in a neurological outpatient department were followed for up to 18 months. Neurological examination, SARS‐CoV‐2 antibodies, Epstein–Barr virus antibodies, and cortisol levels as possible biomarkers, questionnaires to evaluate neuropsychiatric symptoms and somatization (Patient Health Questionnaires D [PHQ‐D]), cognition deficits (Montreal Cognitive Assessment [MoCA]), sleep disorders (ISS, Epworth Sleepiness Scale [ESS]), and fatigue (FSS) were included. Results A total of 175 consecutive patients (78% females, median age 42 years) were seen between May 2021 and February 2023. Fatigue, subjective stress intolerance, and subjective cognitive deficits were the most common symptoms. Specific scores were positive for fatigue, insomnia, and sleepiness and were present in 95%, 62.1%, and 44.0%, respectively. Cognitive deficits were found in 2.3%. Signs of somatization were identified in 61%, who also had an average of two symptoms more than patients without somatization. Overall, 28% had a psychiatric disorder, including depression and anxiety. At the second visit (n = 92), fatigue (67.3%) and insomnia (45.5%) had decreased. At visit three (n = 43), symptom load had decreased in 76.8%; overall, 51.2% of patients were symptom‐free. Biomarker testing did not confirm an anti‐EBV response. SARS‐CoV‐2‐specific immune reactions increased over time, and cortisol levels were within the physiological range. Conclusion Despite high initial symptom load, 76.8% improved over time. The prevalence of somatization and psychiatric disorders was high. Our data do not confirm the role of previously suggested biomarkers in PCC patients.

More than 90 % of opioid overdose deaths in North America are now caused by synthetic opioids, and while they are not as prevalent in the European illicit drug market, there are indications that they may become so in the near future. Multiple publications have argued that neither higher doses of naloxone nor more potent opioid receptor antagonists are needed to reverse a synthetic opioid overdose. However, the unique physicochemical properties of synthetic opioids result in a very rapid onset of respiratory depression compared to opium-based molecules, reducing the margin of opportunity to reverse an overdose. While intravenous administration rapidly delivers the high naloxone concentrations needed to reverse a synthetic opioid overdose, this option is often unavailable to first responders. A translational mechanistic model of opioid overdose developed by the FDA’s Division of Applied Regulatory Science provides an unbiased approach to evaluate the effectiveness of overdose reversal strategies. Reports using this model demonstrated the naloxone tools (2 mg intramuscular and 4 mg intranasal) used by many first responders can result in an unacceptable loss of life following a synthetic opioid (fentanyl, carfentanil) overdose. Moreover, sequential (2.5 minutes between doses) administration of up to four doses of intranasal naloxone was no more effective at reducing the incidence of cardiac arrest (a surrogate endpoint for lethality) than a single dose, suggesting that attempts at titration may not provide the rapid absorption required to reverse a synthetic opioid overdose. This model was also used to compare the effectiveness of intranasal naloxone to intranasal nalmefene, a recently FDA-approved opioid receptor antagonist with a more rapid absorption and a higher affinity at mu-opioid receptors compared to intranasal naloxone. Intranasal nalmefene resulted in large and clinically meaningful reductions in the incidence of cardiac arrest compared to intranasal naloxone. Furthermore, simultaneous administration of four doses of intranasal naloxone was needed to reduce the incidence of cardiac arrest to levels approaching those produced by a single dose of intranasal nalmefene. These data are consistent with evidence that synthetics have indeed disrupted conventional wisdom in the treatment of opioid overdose.

Abstract Synucleinopathies‐related disorders such as Lewy body dementia (LBD) and isolated/idiopathic REM sleep behavior disorder (iRBD) have been associated with neuroinflammation. In this study, we examined whether the human leukocyte antigen (HLA) locus plays a role in iRBD and LBD. In iRBD, HLA‐DRB1*11:01 was the only allele passing FDR correction (OR = 1.57, 95% CI = 1.27–1.93, p = 2.70e‐05). We also discovered associations between iRBD and HLA‐DRB1 70D (OR = 1.26, 95%CI = 1.12–1.41, p = 8.76e‐05), 70Q (OR = 0.81, 95%CI = 0.72–0.91, p = 3.65e‐04) and 71R (OR = 1.21, 95%CI = 1.08–1.35, p = 1.35e‐03). Position 71 (pomnibus = 0.00102) and 70 (pomnibus = 0.00125) were associated with iRBD. Our results suggest that the HLA locus may have different roles across synucleinopathies.

BackgroundAnti-IgLON5 disease is a rare chronic autoimmune disorder characterized by IgLON5 autoantibodies predominantly of the IgG4 subclass. Distinct pathogenic effects were described for anti-IgLON5 IgG1 and IgG4, however, with uncertain clinical relevance.MethodsIgLON5-specific IgG1-4 levels were measured in 46 sera and 20 cerebrospinal fluid (CSF) samples from 13 HLA-subtyped anti-IgLON5 disease patients (six females, seven males) using flow cytometry. Intervals between two consecutive serum or CSF samplings (31 and 10 intervals, respectively) were categorized with regard to the immunomodulatory treatment active at the end of the interval, changes of anti-IgLON5 IgG1 and IgG4 levels, and disease severity. Intrathecal anti-IgLON5 IgG4 synthesis (IS) was assessed using a quantitative method.ResultsThe median age at onset was 66 years (range: 54–75), disease duration 10 years (range: 15–156 months), and follow-up 25 months (range: 0–83). IgLON5-specific IgG4 predominance was observed in 38 of 46 (83%) serum and 11 of 20 (55%) CSF samples. Anti-IgLON5 IgG4 levels prior clinical improvement in CSF but not serum were significantly lower than in those prior stable/progressive disease. Compared to IgLON5 IgG4 levels in serum, CSF levels in HLA-DRB1*10:01 carriers were significantly higher than in non-carriers. Indeed, IgLON5-specific IgG4 IS was demonstrated not only in four of five HLA-DRB1*10:01 carriers but also in one non-carrier. Immunotherapy was associated with decreased anti-IgGLON5 IgG serum levels. In CSF, lower anti-IgLON5 IgG was associated with immunosuppressive treatments used in combination, that is, corticosteroids and/or azathioprine plus intravenous immunoglobulins or rituximab.ConclusionOur findings might indicate that CSF IgLON5-specific IgG4 is frequently produced intrathecally, especially in HLA-DRB1*10:01 carriers. Intrathecally produced IgG4 may be clinically relevant. While many immunotherapies reduce serum IgLON5 IgG levels, more intense immunotherapies induce clinical improvement and may be able to target intrathecally produced anti-IgLON5 IgG. Further studies need to confirm whether anti-IgLON5 IgG4 IS is a suitable prognostic and predictive biomarker in anti-IgLON5 disease.

Abstract Introduction: Demonstrating the impact of implementation science presents a new frontier for the field, and operationalizing downstream impact is challenging. The Translational Science Benefits Model (TSBM) offers a new approach for assessing and demonstrating research impact. Here we describe integration of the TSBM into a mentored training network. Methods: Washington University’s Clinical and Translational Science Awards TSBM team collaborated with a National Institute of Mental Health-supported training program, the Implementation Research Institute (IRI), a 2-year training institute in mental health implementation science. This partnership included three phases: (1) introductory workshop on research impact, (2) workshop on demonstrating impact, and (3) sessions to guide dissemination, including interactive tools and consultation with the TSBM research team. Fifteen IRI alumni were invited to participate in the pilot; six responded agreeing to participate in the training, develop TSBM case studies, and provide feedback about their experiences. Participants applied the tools and gave feedback on design, usability, and content. We present their case studies and describe how the IRI used the results to incorporate TSBM into future trainings. Results: The case studies identified 40 benefits spanning all four TSBM domains, including 21 community, 11 policy, five economic, and three clinical benefits. Participants reported that TSBM training helped them develop a framework for talking about impact. Selecting benefits was challenging for early-stage projects, suggesting the importance of early training. Conclusions: The case studies showcased the institute’s impact and the fellows’ work and informed refinement of tools and methods for incorporating TSBM into future IRI training.

Abstract Aims The objective of this study is to establish a predictive model using transparent machine learning (ML) to identify any drivers that characterize therapeutic inertia. Methods Data in the form of both descriptive and dynamic variables collected from electronic records of 1.5 million patients seen at clinics within the Italian Association of Medical Diabetologists between 2005–2019 were analyzed using logic learning machine (LLM), a “clear box” ML technique. Data were subjected to a first stage of modeling to allow ML to automatically select the most relevant factors related to inertia, and then four further modeling steps individuated key variables that discriminated the presence or absence of inertia. Results The LLM model revealed a key role for average glycated hemoglobin (HbA1c) threshold values correlated with the presence or absence of insulin therapeutic inertia with an accuracy of 0.79. The model indicated that a patient's dynamic rather than static glycemic profile has a greater effect on therapeutic inertia. Specifically, the difference in HbA1c between two consecutive visits, what we call the HbA1c gap, plays a crucial role. Namely, insulin therapeutic inertia is correlated with an HbA1c gap of 11 mmol/mol (1.0%). Conclusions The results reveal, for the first time, the interrelationship between a patient's glycemic trend defined by sequential HbA1c measurements and timely or delayed initiation of insulin therapy. The results further demonstrate that LLM can provide insight in support of evidence‐based medicine using real world data.

REM-sleep behavior disorder often precedes Parkinson’s disease or dementia. Here, the authors perform a genome-wide association study for REM-sleep behavior disorder, and discover how it potentially affects gene expression in the brain.

OBJECTIVES/GOALS: The Translational Science Benefits Model offers an approach for evaluating the downstream health and social impact of research. Using the new Translating for Impact Toolkit of nine web-based tools, researchers can create free, secure accounts to plan, track, and demonstrate the impact of their work. METHODS/STUDY POPULATION: Development of the online toolkit includes 6 phases: 1) Review of existing tools, 2) Development of fillable PDF tool prototypes, 3) Pilot testing, 4) Development of web-based tools, 5) Usability testing, and 6) Refinement of web-based tools. First, we reviewed existing tools for measuring research impact. We then created prototypes of nine tools, published on the TSBM website, and pilot tested with researchers. Based on feedback and testing, we developed and launched web-based versions of the tools. We are currently conducting usability testing with researchers, which we will use to evaluate the ease-of-use and quality of the tools, identify areas for improvement, and refine the tools. RESULTS/ANTICIPATED RESULTS: Researchers can sign up for user accounts, create projects, invite collaborators and program administrators, and save progress as the complete the nine tools in the Translating for Impact Toolkit. The tools are divided into three steps: Plan (Roadmap to Impact, Benefits 2x2, Partner Mapper, and Team Manager), Track (Impact Tracker), and Demonstrate (Product Navigator, Case Study Builder, Impact Profile, and Dissemination Planner). The toolkit also includes a dashboard that provides a quick snapshot of translational impact for each project. The toolkit will help both individual translational scientists demonstrate the impact of their work and CTSA hubs evaluate impact of their projects. DISCUSSION/SIGNIFICANCE: The TSBM online toolkit is a free, secure, easy-to-use platform researchers can use to plan for, track, and demonstrate the impacts of their work. The toolkit provides a structured process that will help the next generation of scientists prioritize and promote translational impact in their work.

OBJECTIVES/GOALS: The Translational Science Benefits Model (TSBM) offers an approach for evaluating research impact on public health and society. Since its development in 2017, there has been an increased focus on science’s impacts on equity. This poster describes efforts to integrate equity into the TSBM. METHODS/STUDY POPULATION: Adaptation of the TSBM includes 3 phases: 1) literature scan of equity impacts, 2) community engagement listening sessions, and 3) model refinement. First, we conducted a scan of the clinical and translational sciences literature for articles that measured equity impacts associated with the TSBM. From the articles, we extracted both equity considerations related to existing TSBM benefits and potential equity-focused benefits. Next, we will present the dimensions of new and existing benefits to several community member panels engaged in research and evaluation. We will use their input to prioritize and refine adaptations to the model (phase 3). RESULTS/ANTICIPATED RESULTS: Our literature scan identified equity dimensions of the original 30 TSBM benefits and 15 potential benefits for inclusion in the model, including community partnerships, community capacity building, workforce development, and social determinants of health, among others. To ensure that community priorities also inform identification of equity impacts of clinical and translational research, we will review and refine the model through a series of community engagement sessions planned for Fall 2023. The sessions will inform final adaptations, which will result in an expanded approach evaluating the impact of scientific activities to include impacts on health equity. DISCUSSION/SIGNIFICANCE: The TSBM provides a framework for clinical and translational scientists to plan for, track, and demonstrate the broader impacts of their work. Including equity impacts can help increase consideration of equity in science and help to more clearly make the link between research and equity impact.

Abstract Background Closing mucosal defects to reach mucosal healing is an important goal of therapy in inflammatory bowel disease (IBD). Among other cells, monocyte‐derived macrophages are centrally involved in such intestinal wound healing. We had previously demonstrated that the anti‐α4β7 integrin antibody vedolizumab blocks the recruitment of non‐classical monocytes as biased progenitors of wound healing macrophages to the gut and delays wound healing. However, although important for the interpretation of disappointing results in recent phase III trials in IBD, the effects of the anti‐β7 antibody etrolizumab on wound healing are unclear so far. Methods We analyzed the expression of etrolizumab targets on human and mouse monocyte subsets by flow cytometry and assessed their function in adhesion and homing assays. We explored wound‐associated monocyte recruitment dynamics with multiphoton microscopy and compared the effects of etrolizumab and vedolizumab surrogate (‐s) antibodies on experimental wound healing and wound‐associated macrophage abundance. Finally, we investigated wound healing macrophage signatures in the large intestinal transcriptome of patients with Crohn's disease treated with etrolizumab. Results Human and mouse non‐classical monocytes expressed more αEβ7 integrin than classical monocytes and were a target of etrolizumab‐s, which blocked non‐classical monocyte adhesion to MAdCAM‐1 and E‐Cadherin as well as gut homing in vivo. Intestinal wound healing was delayed on treatment with etrolizumab‐s along with a reduction of peri‐lesional wound healing macrophages. Wound healing macrophage signatures in the colon of patients with Crohn's disease were substantially down‐regulated on treatment with etrolizumab, but not with placebo. Conclusions Combined blockade of αEβ7 and α4β7 with etrolizumab seems to exceed the effect of anti‐α4β7 treatment on intestinal wound healing, which might help to inform further investigations to understand the recent observations in the etrolizumab phase III trial program.

IntroductionMacrophages play an important role in intestinal wound healing. However, the trajectories from circulating monocytes to gut macrophages are incompletely understood.MethodsTaking advantage of mice depleted for non-classical monocytes due to deficiency for the transcription factor Nr4a1, we addressed the relevance of non-classical monocytes for large intestinal wound healing using flow cytometry, in vivo wound healing assays and immunofluorescence.ResultsWe show that wound healing in Nr4a1-deficient mice is substantially delayed and associated with reduced peri-lesional presence of macrophages with a wound healing phenotype.DiscussionOur data suggest that non-classical monocytes are biased towards wound healing macrophages. These insights might help to understand, how targeting monocyte recruitment to the intestine can be used to modulate intestinal macrophage functions.