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Objective To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener" that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API). Methods We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text. Results Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across 5 healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements. Discussion and Conclusion Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs, (2) increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases. [ABSTRACT FROM AUTHOR]

Objective The timely stratification of trauma injury severity can enhance the quality of trauma care but it requires intense manual annotation from certified trauma coders. The objective of this study is to develop machine learning models for the stratification of trauma injury severity across various body regions using clinical text and structured electronic health records (EHRs) data. Materials and Methods Our study utilized clinical documents and structured EHR variables linked with the trauma registry data to create 2 machine learning models with different approaches to representing text. The first one fuses concept unique identifiers (CUIs) extracted from free text with structured EHR variables, while the second one integrates free text with structured EHR variables. Temporal validation was undertaken to ensure the models' temporal generalizability. Additionally, analyses to assess the variable importance were conducted. Results Both models demonstrated impressive performance in categorizing leg injuries, achieving high accuracy with macro-F1 scores of over 0.8. Additionally, they showed considerable accuracy, with macro-F1 scores exceeding or near 0.7, in assessing injuries in the areas of the chest and head. We showed in our variable importance analysis that the most important features in the model have strong face validity in determining clinically relevant trauma injuries. Discussion The CUI-based model achieves comparable performance, if not higher, compared to the free-text-based model, with reduced complexity. Furthermore, integrating structured EHR data improves performance, particularly when the text modalities are insufficiently indicative. Conclusions Our multi-modal, multiclass models can provide accurate stratification of trauma injury severity and clinically relevant interpretations. [ABSTRACT FROM AUTHOR]

Objectives: This study combines two innovative mouse models in a major gene discovery project to assess the influence of host genetics on asbestos related disease (ARD). Conventional genetics studies provided evidence that some susceptibility to mesothelioma is genetic. However, the identification of host modifier genes, the roles they may play, and whether they contribute to disease susceptibility remain unknown. Here we report a study designed to rapidly identify genes associated with mesothelioma susceptibility by combining the Collaborative Cross (CC) resource with the well-characterised MexTAg mesothelioma mouse model. Methods: The CC is a powerful mouse resource that harnesses over 90% of common genetic variation in the mouse species, allowing rapid identification of genes mediating complex traits. MexTAg mice rapidly, uniformly, and predictably develop mesothelioma, but only after asbestos exposure. To assess the influence of host genetics on ARD, we crossed 72 genetically distinct CC mouse strains with MexTAg mice and exposed the resulting CC-MexTAg (CCMT) progeny to asbestos and monitored them for traits including overall survival, the time to ARD onset (latency), the time between ARD onset and euthanasia (disease progression) and ascites volume. We identified phenotype-specific modifier genes associated with these traits and we validated the role of human orthologues in asbestos-induced carcinogenesis using human mesothelioma datasets. Results: We generated 72 genetically distinct CCMT strains and exposed their progeny (2,562 in total) to asbestos. Reflecting the genetic diversity of the CC, there was considerable variation in overall survival and disease latency. Surprisingly, however, there was no variation in disease progression, demonstrating that host genetic factors do have a significant influence during disease latency but have a limited role once disease is established. Quantitative trait loci (QTL) affecting ARD survival/latency were identified on chromosomes 6, 12 and X. Of the 97-protein coding candidate modifier genes that spanned these QTL, eight genes (CPED1, ORS1, NDUFA1, HS1BP3, IL13RA1, LSM8, TES and TSPAN12) were found to significantly affect outcome in both CCMT and human mesothelioma datasets. Conclusion: Host genetic factors affect susceptibility to development of asbestos associated disease. However, following mesothelioma establishment, genetic variation in molecular or immunological mechanisms did not affect disease progression. Identification of multiple candidate modifier genes and their human homologues with known associations in other advanced stage or metastatic cancers highlights the complexity of ARD and may provide a pathway to identify novel therapeutic targets. [ABSTRACT FROM AUTHOR]

As patients continue to live longer from diseases that predispose them to right ventricular (RV) dysfunction or failure, many more patients will require surgery for acute or chronic health issues. Because RV dysfunction results in significant perioperative morbidity if not adequately assessed or managed, understanding appropriate assessment and treatments is important in preventing subsequent morbidity and mortality in the perioperative period. In light of the epidemiology of right heart disease, a working knowledge of right heart anatomy and physiology and an understanding of the implications of right-sided heart function for perioperative care are essential for perioperative practitioners. However, a significant knowledge gap exists concerning this topic. This manuscript is one part of a collection of papers from the PeriOperative Quality Initiative (POQI) IX Conference focusing on "Current Perspectives on the Right Heart in the Perioperative Period." This review aims to provide perioperative clinicians with an essential understanding of right heart physiology by answering five key questions on this topic and providing an explanation of seven fundamental concepts concerning right heart physiology. [ABSTRACT FROM AUTHOR]

Background Large vessel recanalization (LVR) before endovascular therapy (EVT) for acute large vessel ischemic strokes is a poorly understood phenomenon. Better understanding of predictors for LVR is important for optimizing stroke triage and patient selection for bridging thrombolysis. Methods In this retrospective cohort study, consecutive patients presenting to a comprehensive stroke center for EVT treatment were identified from 2018 to 2022. Demographic information, clinical characteristics, intravenous thrombolysis (IVT) use, and LVR before EVT were recorded. Factors independently associated with different rates of LVR were identified, and a prediction model for LVR was constructed. Results 640 patients were identified. 57 (8.9%) patients had LVR before EVT. A minority (36.4%) of LVR patients had significant improvements in National Institutes of Health Stroke Scale. Independent predictors for LVR were identified and used to construct the 8-point HALT score: hyperlipidemia (1 point), atrial fibrillation (1 point), location of vascular occlusion (internal carotid: 0 points, M1: 1 point, M2: 2 points, vertebral/basilar: 3 points), and thrombolysis at least 1.5 hours before angiography (3 points). The HALT score had an area under the receiver-operating curve (AUC) of 0.85 (95% CI 0.81 to 0.90, P<0.001) for predicting LVR. LVR before EVT occurred in only 1 of 302 patients (0.3%) with low (0-2) HALT scores. Conclusions IVT at least 1.5 hours before angiography, site of vascular occlusion, atrial fibrillation, and hyperlipidemia are independent predictors for LVR. The 8-point HALT score proposed in this study may be a valuable tool for predicting LVR before EVT. [ABSTRACT FROM AUTHOR]

Objective The classification of clinical note sections is a critical step before doing more fine-grained natural language processing tasks such as social determinants of health extraction and temporal information extraction. Often, clinical note section classification models that achieve high accuracy for 1 institution experience a large drop of accuracy when transferred to another institution. The objective of this study is to develop methods that classify clinical note sections under the SOAP ("Subjective," "Object," "Assessment," and "Plan") framework with improved transferability. Materials and methods We trained the baseline models by fine-tuning BERT-based models, and enhanced their transferability with continued pretraining, including domain-adaptive pretraining and task-adaptive pretraining. We added in-domain annotated samples during fine-tuning and observed model performance over a varying number of annotated sample size. Finally, we quantified the impact of continued pretraining in equivalence of the number of in-domain annotated samples added. Results We found continued pretraining improved models only when combined with in-domain annotated samples, improving the F 1 score from 0.756 to 0.808, averaged across 3 datasets. This improvement was equivalent to adding 35 in-domain annotated samples. Discussion Although considered a straightforward task when performing in-domain, section classification is still a considerably difficult task when performing cross-domain, even using highly sophisticated neural network-based methods. Conclusion Continued pretraining improved model transferability for cross-domain clinical note section classification in the presence of a small amount of in-domain labeled samples. [ABSTRACT FROM AUTHOR]

Many preclinical and clinical studies support the use of antisense oligonucleotides (ASOs) as effective therapeutic strategies. However, acquiring ASOs for research purposes may be limited by partnerships with the pharmaceutical companies. Our lab previously developed an effective ASO strategy to lower human tau and reverse pathology in aged tauopathy model mice. Testing the efficacy of purchased tau lowering ASOs would provide support for these reagents as broad research tools. Purchased mouse and human tau lowering ASOs were infused or injected intracerebroventricularly into wildtype and tau transgenic mice. Following treatment, brain tissue evaluated for ASO distribution and levels of tau mRNA, protein, and phosphorylated tau. We show that purchased ASOs enter cell types of the brain and effectively decrease mouse or human tau mRNA and protein levels. Human tau lowering ASO treatment in PS19 mice decreased phosphorylated tau and gliosis relative to saline-treated PS19 mice, consistent with our previous study using a non-commercial tau lowering ASO. The results of this study demonstrate the efficacy of purchased tau targeting ASOs in vivo to support their broad use by researchers. [ABSTRACT FROM AUTHOR]

Weighting data appropriately in stock assessment models is necessary to diagnose model mis-specification, estimate uncertainty, and when combining data sets. Age- and length-composition data are often fitted using a multinomial distribution and then reweighted iteratively, and the Dirichlet-multinomial ("DM") likelihood provides a model-based alternative that estimates an additional parameter and thereby "self-weights" data. However, the DM likelihood requires specifying an input sample size (n input), which is often unavailable and results are sensitive to n input. We therefore introduce the multivariate-Tweedie (MVTW) as alternative with three benefits: (1) it can identify both overdispersion (downweighting) or underdispersion (upweighting) relative to the n input; (2) proportional changes in ninput are exactly offset by parameters; and (3) it arises naturally when expanding data arising from a hierarchical sampling design. We use an age-structured simulation to show that the MVTW (1) can be more precise than the DM in estimating data weights, and (2) can appropriately upweight data when needed. We then use a real-world state-space assessment to show that the MVTW can easily be adapted to other software. We recommend that stock assessments explore the sensitivity to specifying DM, MVTW, and logistic-normal likelihoods, particularly when the DM estimates an effective sample size approaching ninput. [ABSTRACT FROM AUTHOR]

This paper summarizes the psychological insights and related design challenges that have emerged in the field of Explainable AI (XAI). This summary is organized as a set of principles, some of which have recently been instantiated in XAI research. The primary aspects of implementation to which the principles refer are the design and evaluation stages of XAI system development, that is, principles concerning the design of explanations and the design of experiments for evaluating the performance of XAI systems. The principles can serve as guidance, to ensure that AI systems are human-centered and effectively assist people in solving difficult problems. [ABSTRACT FROM AUTHOR]

Astrocyte-specific ion pump α2-Na+/K+-ATPase plays a critical role in the pathogenesis of amyotrophic lateral sclerosis (ALS). Here, we test the effect of Atp1a2 mRNA-specific antisense oligonucleotides (ASOs) to induce α2-Na+/K+-ATPase knockdown in the widely used ALS animal model, SOD1*G93A mice. Two ASOs led to efficient Atp1a2 knockdown and significantly reduced SOD1 aggregation in vivo. Although Atp1a2 ASO-treated mice displayed no off-target or systemic toxicity, the ASO-treated mice exhibited an accelerated disease onset and shorter lifespan than control mice. Transcriptomics studies reveal downregulation of genes involved in oxidative response, metabolic pathways, trans-synaptic signaling, and upregulation of genes involved in glutamate receptor signaling and complement activation, suggesting a potential role for these molecular pathways in de-coupling SOD1 aggregation from survival in Atp1a2 ASO-treated mice. Together, these results reveal a role for α2-Na+/K+-ATPase in SOD1 aggregation and highlight the critical effect of temporal modulation of genetically validated therapeutic targets in neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Introduction/Aims: Analysis of biofluids, especially cerebrospinal fluid (CSF), is critically important for amyotrophic lateral sclerosis (ALS) research. Collection of CSF is typically performed by lumbar puncture (LP). Previous studies have demonstrated the safety of LPs in patients with other neurodegenerative diseases, such as Alzheimer's disease, although there are no published studies of the safety of LPs in patients with ALS. We performed a retrospective analysis of complications resulting from LPs. Methods: This is a retrospective study of LPs performed between 2015 and 2021 on a total of 233 participants (healthy controls [n = 63], ALS [n = 154], and disease controls [n = 16]) as part of clinical research studies at the Washington University ALS Center. We used bivariate logistical analyses looking for associations between participant characteristics and adverse events (AEs), and likelihood ratio tests were used for significance testing. Results: We found an overall AE rate of 21.03%. AEs included headache, back pain, vasovagal syncope, and severe headache requiring epidural blood patch. Participants with ALS were not more likely to experience post‐LP AEs compared to controls (odds ratio [OR] 0.61 [0.32–1.18]). Post‐LP headaches were significantly less likely in participants with ALS (OR 0.36 [0.15–0.83]). Discussion: Our findings demonstrate that LP is a safe procedure for participants with ALS, with a similar or lower rate of AEs than in participants without ALS. [ABSTRACT FROM AUTHOR]

This study contributes to the participative budgeting and budget misrepresentation literature by exploring: (1) whether managers' judgments of fair behaviors are malleable and context-dependent and (2) if these judgments of fair behavior impact cost reporting misrepresentations. Two experiments investigate these questions. Experiment 1 (n = 42) tests whether the behavior that managers judge to be "fair" differs based on the decision context (i.e., initial economic position [IEP]). Experiment 2 (n = 130) investigates: (1) how managers' deployment of fairness beliefs influences their reporting misrepresentations and (2) how decision aids that reduce task complexity impact managers' deployment of fairness beliefs in their misreporting decisions. The study found that managers deploy fairness beliefs (i.e., honesty or equality) consistent with maximizing their context-relevant income. Hence, fairness beliefs constrain misrepresentations in predictable ways. In addition, we find more accounting information is not always beneficial. The presence of decision aids actually increases misrepresentations when managers are initially advantaged (i.e., start with more resources than others). The implications from these findings are relevant to the honesty and budgeting literature and provide novel findings of how managers' preferences for fairness constrain managers from maximizing their income. The chapter demonstrates that contextual factors can influence the deployment of managers' fairness beliefs which, in turn, differentially impact their reporting misrepresentation. Another contribution is that providing decision aids, which reduce task complexity, may not always benefit companies, since such aids may increase misrepresentation under certain conditions. [ABSTRACT FROM AUTHOR]

Background Elevated International Normalized Ratio (INR) is a marker of coagulopathy, but its impact on outcomes following mechanical thrombectomy (MT) in patients with stroke is unclear. This study investigates the impact of mild INR elevations on clinical outcomes following MT. Methods In this retrospective cohort study, consecutive patients with stroke treated with MT were identified from 2015 to 2020 at a Comprehensive Stroke Center. Demographic information, past medical history, INR, National Institutes of Health Stroke Scale score, use of tissue plasminogen activator, and last known normal to arteriotomy time were recorded. Outcome measures included modified Thrombolysis in Cerebral Infarction (mTICI) score, modified Rankin Scale (mRS) score at 90 days, and intracerebral hemorrhage (ICH). Patients were divided into two groups: normal INR (0.8-1.1) and mildly elevated INR (1.2-1.7). Results A total of 489 patients were included for analysis, of which 349 had normal INR and 140 had mildly elevated INR. After multivariable adjustments, mildly elevated INR was associated with lower odds of excellent outcomes (mRS 0-1, OR 0.24, p=0.009), lower odds of functional independence (mRS 0-2, OR 0.38, p=0.038), and higher odds of 90-day mortality (OR 3.45, p=0.018). Elevated INR was not associated with a higher likelihood of ICH, and there were no differences in rates of HI1, HI2, PH1, or PH2 hemorrhagic transformations; however, elevated INR was associated with significantly higher odds of 90-day mortality in patients with ICH (OR 6.22, p=0.024). This effect size was larger than in patients without ICH (OR 3.38, p<0.001). Conclusion In patients with stroke treated with MT, mildly elevated INR is associated with worse clinical outcomes after recanalization and may worsen the mortality risk of hemorrhagic transformations. [ABSTRACT FROM AUTHOR]

Background High levels of platelet inhibition have been associated with hemorrhagic complications following Pipeline embolization of intracranial aneurysms. We therefore titrate clopidogrel dosing to maintain a moderate level of platelet inhibition using the VerifyNow P2Y12 assay. However, many patients demonstrate dramatic increases in platelet inhibition following treatment despite being on a consistent antiplatelet regimen. We therefore elected to explore the incidence of this phenomenon and possible predisposing factors. Methods All successful Pipeline aneurysm treatments performed at our institution from 2011 to 2019 with moderate procedure-day platelet inhibition levels as indicated by a VerifyNow PRU of 60-235 were included. Patients who received glycoprotein IIb/IIIa inhibitors and those treated for ruptured/symptomatic lesions were excluded. The incidence of excessive platelet inhibition defined by a PRU<60 within 8 weeks of treatment was noted. Multivariable logistic regression was performed to determined independent predictors of the phenomenon. Results Some 190 treatments were performed in 178 qualifying patients. A post-procedure PRU <60 occurred following 79% of treatments, documented on average after 8.5 (range 1-47) days. A higher procedure day hematocrit level (P=0.003, OR 1.09, 95% CI 1.029 to 1.152) was an independent predictor of reaching a PRU <60, while intra-procedural midazolam exposure (P=0.044, OR 0.44, 95% CI 0.201 to 0.980) and a higher procedure-day PRU (P=0.047, OR 0.99, 95% CI 0.982 to 1.000) were associated with a reduced odds. Time-since-procedure and hematocrit levels were associated with excessive platelet inhibition when excluding patients who initially demonstrated hyperresponse. Conclusion Elevations in platelet inhibition were frequently observed following flow diversion with Pipeline. [ABSTRACT FROM AUTHOR]

Objective: To determine the target population and optimize the study design of the phase 3 clinical trial evaluating reldesemtiv in participants with amyotrophic lateral sclerosis (ALS). Methods: We evaluated the phase 2 study of reldesemtiv, FORTITUDE-ALS, to inform eligibility criteria and design features that would increase trial efficiency and reduce participant burden of the phase 3 trial. Results: In FORTITUDE-ALS, the effect of reldesemtiv was particularly evident among participants in the intermediate- and fast-progressing tertiles for pre-study disease progression. These participants most often had symptom onset ≤24 months and an ALS Functional Rating Scale-Revised (ALSFRS-R) total score ≤44 at baseline. Compared with the overall FORTITUDE-ALS population, the subgroup meeting these criteria declined by fewer ALSFRS-R points at 12 weeks (difference of least-squares mean [SE] versus placebo 1.84 [0.49] and 0.87 [0.35] for the overall population). These inclusion criteria will be used for the phase 3 clinical trial, COURAGE-ALS, in which the primary outcome is the change in ALSFRS-R total score at week 24. We also measure durable medical equipment use and evaluate strength in muscles expected to change rapidly. To reduce participant burden, study visits are often remote, and strength evaluation is simplified to reduce time and effort. Conclusions: In COURAGE-ALS, the phase 3 clinical trial to evaluate reldesemtiv, the sensitivity of detecting a potential treatment effect may be increased by defining eligibility criteria that limit the proportion of participants who have slower disease progression. Implementing remote visits and simplifying strength measurements will reduce both site and participant burden. ClinicalTrials.gov identifiers: NCT03160898 (FORTITUDE-ALS) and NCT04944784 (COURAGE-ALS) [ABSTRACT FROM AUTHOR]

Background: Opioid use has come under increasing scrutiny, driven in part by the opioid crisis and growing concerns that up to 6% of opioid-naïve patients may become chronic opioid users. This has resulted in a revaluation of perioperative practice. For this reason, we implemented a multidisciplinary pathway to reduce perioperative opioid usage through education and standardization of practice. Methods: A single-centre retrospective evaluation was performed after 1 year, comparing the outcomes to those of the 2 years prior to pathway implementation. Comparisons were made between pre- vs. post pathway change by 2:1 propensity matching between cohorts. Univariate linear regression models were created using demographic variables with those that were p < 0.15 included in the final model and using post-operative opioid use (in oral morphine equivalents, OME) as the primary outcome. Results: We found that intraoperative opioid use was significantly decreased 38.2 mg (28.3) vs. 18.0 mg (40.4) oral morphine equivalents (OME), p <.001, as was post-operative opioid use for the duration of the hospitalization, 46.3 mg (49.5) vs. 35.49 mg (43.7) OME, p = 0.002. In subgroup analysis of those that received some intraoperative opioids (n = 152) and those that received no opioids (n = 34), we found that both groups required fewer opioids in the post-operative period 47.0 mg (47.7) vs. 32.4 mg (40.6) OME, p = 0.001, + intraoperative opioids, 62.4 mg (62.9) vs. 35.8 mg (27.7) OME, p = 0.13, - intraoperative opioids. Time to discharge from the PACU was reduced in both groups 215 min (199) vs. 167 min (122), p < 0.003, + intraoperative opioids and 253 min (270) vs. 167 min (105), p = 0.028, - intraoperative opioids. The duration of time until meeting discharge criteria from PACU was 221 min (205) vs. 170 min (120), p = 0.001. Hospital length of stay (LOS) was significantly reduced 1.4 days (1.3) vs. 1.2 days (0.8), p = 0.005. Both sub-groups demonstrated reduced hospital LOS 1.5 days (1.4) vs. 1.2 days (0.8), p = 0.0047, + intraoperative opioids and 1.7 days (1.6) vs. 1.3 days (0.9), p = 0.0583, - intraoperative opioids. Average pain scores during PACU admission and post-PACU until discharge were not statistically different between cohorts. Conclusions: These findings underscore the effectiveness of a multidisciplinary approach to reduce opioids. Furthermore, it demonstrates improved patient outcomes as measured by both shorter PACU and almost 50% reduction in perioperative opioid use whilst maintaining similar analgesia as indicated by patient-reported pain scores. [ABSTRACT FROM AUTHOR]

PURPOSE: Radiotherapy (RT) toxicities can impair survival and quality of life, yet remain understudied. Real-world evidence holds potential to improve our understanding of toxicities, but toxicity information is often only in clinical notes. We developed natural language processing (NLP) models to identify the presence and severity of esophagitis from notes of patients treated with thoracic RT. METHODS: Our corpus consisted of a gold-labeled data set of 1,524 clinical notes from 124 patients with lung cancer treated with RT, manually annotated for Common Terminology Criteria for Adverse Events (CTCAE) v5.0 esophagitis grade, and a silver-labeled data set of 2,420 notes from 1,832 patients from whom toxicity grades had been collected as structured data during clinical care. We fine-tuned statistical and pretrained Bidirectional Encoder Representations from Transformers–based models for three esophagitis classification tasks: task 1, no esophagitis versus grade 1-3; task 2, grade ≤1 versus >1; and task 3, no esophagitis versus grade 1 versus grade 2-3. Transferability was tested on 345 notes from patients with esophageal cancer undergoing RT. RESULTS: Fine-tuning of PubMedBERT yielded the best performance. The best macro-F1 was 0.92, 0.82, and 0.74 for tasks 1, 2, and 3, respectively. Selecting the most informative note sections during fine-tuning improved macro-F1 by ≥2% for all tasks. Silver-labeled data improved the macro-F1 by ≥3% across all tasks. For the esophageal cancer notes, the best macro-F1 was 0.73, 0.74, and 0.65 for tasks 1, 2, and 3, respectively, without additional fine-tuning. CONCLUSION: To our knowledge, this is the first effort to automatically extract esophagitis toxicity severity according to CTCAE guidelines from clinical notes. This provides proof of concept for NLP-based automated detailed toxicity monitoring in expanded domains. #Natural language processing models are able to phenotype radiotherapy-related esophagitis from electronic health record notes. This is the first study demonstrating the ability of models to extract adverse event severity according to Common Terminology Criteria for Adverse Events grade. [ABSTRACT FROM AUTHOR]

Objective: Accumulation of misfolded superoxide dismutase‐1 (SOD1) is a pathological hallmark of SOD1‐related amyotrophic lateral sclerosis (ALS) and is observed in sporadic ALS where its role in pathogenesis is controversial. Understanding in vivo protein kinetics may clarify how SOD1 influences neurodegeneration and inform optimal dosing for therapies that lower SOD1 transcripts. Methods: We employed stable isotope labeling paired with mass spectrometry to evaluate in vivo protein kinetics and concentration of soluble SOD1 in cerebrospinal fluid (CSF) of SOD1 mutation carriers, sporadic ALS participants and controls. A deaminated SOD1 peptide, SDGPVKV, that correlates with protein stability was also measured. Results: In participants with heterozygous SOD1A5V mutations, known to cause rapidly progressive ALS, mutant SOD1 protein exhibited ~twofold faster turnover and ~ 16‐fold lower concentration compared to wild‐type SOD1 protein. SDGPVKV levels were increased in SOD1A5V carriers relative to controls. Thus, SOD1 mutations impact protein kinetics and stability. We applied this approach to sporadic ALS participants and found that SOD1 turnover, concentration, and SDGPVKV levels are not significantly different compared to controls. Interpretation: These results highlight the ability of stable isotope labeling approaches and peptide deamidation to discern the influence of disease mutations on protein kinetics and stability and support implementation of this method to optimize clinical trial design of gene and molecular therapies for neurological disorders. Trial Registration: Clinicaltrials.gov: NCT03449212. [ABSTRACT FROM AUTHOR]

PURPOSE: There is an unmet need to empirically explore and understand drivers of cancer disparities, particularly social determinants of health. We explored natural language processing methods to automatically and empirically extract clinical documentation of social contexts and needs that may underlie disparities. METHODS: This was a retrospective analysis of 230,325 clinical notes from 5,285 patients treated with radiotherapy from 2007 to 2019. We compared linguistic features among White versus non-White, low-income insurance versus other insurance, and male versus female patients' notes. Log odds ratios with an informative Dirichlet prior were calculated to compare words over-represented in each group. A variational autoencoder topic model was applied, and topic probability was compared between groups. The presence of machine-learnable bias was explored by developing statistical and neural demographic group classifiers. RESULTS: Terms associated with varied social contexts and needs were identified for all demographic group comparisons. For example, notes of non-White and low-income insurance patients were over-represented with terms associated with housing and transportation, whereas notes of White and other insurance patients were over-represented with terms related to physical activity. Topic models identified a social history topic, and topic probability varied significantly between the demographic group comparisons. Classification models performed poorly at classifying notes of non-White and low-income insurance patients (F1 of 0.30 and 0.23, respectively). CONCLUSION: Exploration of linguistic differences in clinical notes between patients of different race/ethnicity, insurance status, and sex identified social contexts and needs in patients with cancer and revealed high-level differences in notes. Future work is needed to validate whether these findings may play a role in cancer disparities. NLP methods can help researchers explore social contexts and needs that may be relevant for treatment and outcomes of patients with cancer. [ABSTRACT FROM AUTHOR]

To evaluate the Milano-Torino staging (MiToS) and King's staging systems as potential outcome measures for clinical trials in amyotrophic lateral sclerosis (ALS) by assessing these outcomes in FORTITUDE-ALS. This was a post hoc analysis of the phase 2b FORTITUDE-ALS trial (NCT03160898), a double-blind, randomized, dose-ranging, placebo-controlled, parallel-group study of reldesemtiv in patients with ALS. The treatment period was 12 weeks, with a follow-up assessment at week 16. Patients were retrospectively classified into MiToS and King's stages. Outcomes were the mean time maintaining baseline stage and risk of progression from the baseline stage to a later stage. The full analysis set consisted of 456 patients randomized 3:1 (reldesemtiv n = 342, placebo n = 114) who received at least one dose of double-blind study drug and had at least one post-baseline assessment. At baseline, MiToS and King's stages were balanced between the reldesemtiv and placebo groups: >99% of patients were in MiToS stage 0 or 1 and King's stage 1, 2 or 3. Time of maintaining the baseline stage was similar in both groups, for each staging system. The two staging systems exhibited considerably disparate results for risk of progression from baseline to a later stage: hazard ratio (HR) = 0.62 (95% confidence interval [CI] 0.38, 0.99) for MiToS and HR = 0.96 (95% CI 0.63, 1.44) for King's. This exploratory analysis showed the feasibility of MiToS and King's staging as potential outcome measures in ALS. Additional studies of these staging systems are needed to further explore their utility in ALS clinical trials. [ABSTRACT FROM AUTHOR]

Even though enlarged lymph nodes and tonsils are commonly identified in patients diagnosed with monkeypox,[[1]] descriptions of lymph node pathology in human monkeypox infection are lacking. Keywords: lymph node; lymphadenitis; lymphadenopathy; Monkeypox; pathology EN lymph node lymphadenitis lymphadenopathy Monkeypox pathology 953 956 4 04/05/23 20230501 NES 230501 To the Editor: In July 2022, an outbreak of human monkeypox was reported in several nonendemic countries. [Extracted from the article]

Objective: The objective of this study was to use a novel combined pharmacoepidemiologic and amyotrophic lateral sclerosis (ALS) mouse model approach to identify potential motor neuron protective medications. Methods: We constructed a large, population‐based case‐control study to investigate motor neuron disease (MND) among US Medicare beneficiaries aged 66 to 90 in 2009. We included 1,128 incident MND cases and 56,400 age, sex, race, and ethnicity matched controls. We calculated MND relative risk for >1,000 active ingredients represented in Part D (pharmacy) claims in 2006 to 2007 (>1 year before diagnosis/reference). We then applied a comprehensive screening approach to select medications for testing in SOD1G93A mice: sulfasalazine, telmisartan, and lovastatin. We treated mice with the human dose equivalent of the medication or vehicle via subcutaneous osmotic pump before onset of weakness. We then assessed weight, gait, and survival. In additional mice, we conducted histological studies. Results: We observed previously established medical associations for MND and an inverse dose–response association between lovastatin and MND, with 28% reduced risk at 40 mg/day. In SOD1G93A mouse studies, sulfasalazine and telmisartan conferred no benefit, whereas lovastatin treatment delayed onset and prolonged survival. Lovastatin treated mice also had less microgliosis, misfolded SOD1, and spinal motor neuron loss in the ventral horn. Interpretation: Lovastatin reduced the risk of ALS in humans, which was confirmed in an ALS mouse model by delayed symptom onset, prolonged survival, and preservation of motor neurons. Although further studies to understand the mechanism are required, lovastatin may represent a potential neuroprotective therapy for patients with ALS. These data demonstrate the utility of a combined pharmacoepidemiologic and mouse model approach. ANN NEUROL 2023;93:881–892 [ABSTRACT FROM AUTHOR]

Motivated by the mixed findings in prior archival studies, this study conducts three experiments to examine the relationships among analysts' intrinsic valuation estimates (V), stock recommendations (REC) and stock returns. Experiment 1, built on implications from prospect theory, provides direct observations on analysts' asymmetric use of the valuation to price (V/P) ratio in making their REC. Experiments 2 and 3 indicate differences and similarities between professional and nonprofessional investors in using analysts' V and REC in making their investment-related judgments. Our results provide implications for both research and practice. [ABSTRACT FROM AUTHOR]

The role of live vegetation fuel properties in altering fire behaviour is increasingly being recognised. The techniques utilised to assess how fuel characteristics impact fire behaviour, however, use apparatuses that do not accurately represent the exposure of plants to fire. This study presents a replicable and precise laboratory method of testing flammability metrics in live vegetation, particularly Acacia floribunda , C assinia arcuata and Pinus radiata. Two heating regimes were tested – a static heat flux to reflect current methods and a dynamic (increasing) heat flux to more accurately replicate an approaching fire front. Piloted ignition and autoignition were used for both heating regimes to test the effect of different ignition mechanisms on flammability metrics. The pilot igniter increased the number of samples that reached flaming ignition, and decreased the time and energy required to reach all flammability metrics. Significant differences were observed between heating regimes, suggesting it is important to test flammability of live plants under a dynamic heating regime that most accurately replicates an approaching fire front. Adoption of this methodology is recommended to ensure more realistic and standardised data on flammability of individual plant species and plant communities. This will lead to better-informed and more accurate wildfire behaviour modelling. The role of live vegetation in altering fire behaviour is increasingly being recognised. To accurately represent the exposure of a live plant to an approaching fire front, a replicable and precise method of testing flammability was developed. It provides a more realistic representation of plant flammability in the natural environment. [ABSTRACT FROM AUTHOR]

Age-based stock assessments are sometimes rejected by review panels due to large retrospective patterns. When this occurs, data-limited approaches are often used to set catch advice, under the assumption that these simpler methods will not be impacted by the problems causing retrospective patterns in the age-based assessment. This assumption has never been formally evaluated. Closed-loop simulations were conducted where a known source of error caused a retrospective pattern in an age-based assessment. Twelve data-limited methods, an ensemble of a subset of these methods, and a statistical catch-at-age model with retrospective adjustment were all evaluated to examine their ability to prevent overfishing and rebuild overfished stocks. Overall, none of the methods evaluated performed best across the scenarios. A number of methods performed consistently poorly, resulting in frequent and intense overfishing and low stock sizes. The retrospective adjusted statistical catch-at-age assessment performed better than a number of the alternatives explored. Thus, using a data-limited approach to set catch advice will not necessarily result in better performance than relying on the age-based assessment with a retrospective adjustment. [ABSTRACT FROM AUTHOR]

The American Society of Colon and Rectal Surgeons (ASCRS) and the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) are dedicated to ensuring high-quality innovative patient care for surgical patients by advancing the science, prevention, and management of disorders and diseases of the colon, rectum, and anus as well as minimally invasive surgery. The ASCRS and SAGES society members involved in the creation of these guidelines were chosen because they have demonstrated expertise in the specialty of colon and rectal surgery and enhanced recovery. This consensus document was created to lead international efforts in defining quality care for conditions related to the colon, rectum, and anus and develop clinical practice guidelines based on the best available evidence. While not proscriptive, these guidelines provide information on which decisions can be made and do not dictate a specific form of treatment. These guidelines are intended for the use of all practitioners, healthcare workers, and patients who desire information about the management of the conditions addressed by the topics covered in these guidelines. These guidelines should not be deemed inclusive of all proper methods of care nor exclusive of methods of care reasonably directed toward obtaining the same results. The ultimate judgment regarding the propriety of any specific procedure must be made by the physician in light of all the circumstances presented by the individual patient. This clinical practice guideline represents a collaborative effort between the American Society of Colon and Rectal Surgeons (ASCRS) and the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and was approved by both societies. [ABSTRACT FROM AUTHOR]

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data. [ABSTRACT FROM AUTHOR]

To estimate the health utilities and quality-adjusted life years (QALYs) in patients with amyotrophic lateral sclerosis (ALS) receiving reldesemtiv versus placebo in FORTITUDE-ALS. We performed a post hoc analysis of clinical trial data from FORTITUDE-ALS (NCT03160898). This Phase IIb, double-blind, randomized, dose-ranging, placebo-controlled, parallel-group, 12-week trial evaluated reldesemtiv in patients with ALS. Health utilities from the five-level version of the EuroQol five-dimensional questionnaire (EQ-5D-5L) were estimated using ALS Functional Rating Scale-Revised (ALSFRS-R) scores collected during the trial. QALYs were estimated using the area under the curve method. The full analysis set consisted of 456 patients (reldesemtiv n = 342, placebo n = 114), who received at least one dose of the double-blind study drug, and had ALSFRS-R assessed at baseline and at least one post-baseline assessment. The difference in EQ-5D-5L utility least-squares (LS) mean change from baseline to week 12 for reldesemtiv versus placebo, adjusted for baseline values, was statistically significant (0.03, 95% confidence interval [CI]: 0.01, 0.05; p =.0008). The incremental QALY of reldesemtiv versus placebo adjusted for baseline utility values showed a modest, but statistically significant, difference (0.004, 95% CI: 0.001, 0.007; p =.0058). This post hoc analysis of FORTITUDE-ALS suggests that reldesemtiv showed a modest but significant benefit in health utilities and QALYs compared with placebo. Future long-term studies that include direct collection of EQ-5D-5L data will be needed to confirm our findings. NCT03160898 [ABSTRACT FROM AUTHOR]

Malebranche claims that God always, or nearly always, acts by general volitions. However, two possible interpretations of this claim have led to competing understandings of Malebranche's occasionalism. The General Content interpretation (GC) holds that God forms as few volitions as possible, and that aside from a limited number of particular volitions, God's normal mode of action consists simply in willing the general laws themselves. The Particular Content interpretation (PC) affirms that God forms a distinct volition for each event or state of affairs, but that those volitions count as general when they are issued "in accordance with" some general law. This essay examines five lines of evidence that purport to reveal Malebranche's commitment to PC and explains why they all fail. As a result, GC emerges unscathed as a consistent and viable interpretation, and, at the same time, much of the case for PC is undermined. [ABSTRACT FROM AUTHOR]

Objective: To provide a scoping review of papers on clinical natural language processing (NLP) shared tasks that use publicly available electronic health record data from a cohort of patients.Materials and Methods: We searched 6 databases, including biomedical research and computer science literature databases. A round of title/abstract screening and full-text screening were conducted by 2 reviewers. Our method followed the PRISMA-ScR guidelines.Results: A total of 35 papers with 48 clinical NLP tasks met inclusion criteria between 2007 and 2021. We categorized the tasks by the type of NLP problems, including named entity recognition, summarization, and other NLP tasks. Some tasks were introduced as potential clinical decision support applications, such as substance abuse detection, and phenotyping. We summarized the tasks by publication venue and dataset type.Discussion: The breadth of clinical NLP tasks continues to grow as the field of NLP evolves with advancements in language systems. However, gaps exist with divergent interests between the general domain NLP community and the clinical informatics community for task motivation and design, and in generalizability of the data sources. We also identified issues in data preparation.Conclusion: The existing clinical NLP tasks cover a wide range of topics and the field is expected to grow and attract more attention from both general domain NLP and clinical informatics community. We encourage future work to incorporate multidisciplinary collaboration, reporting transparency, and standardization in data preparation. We provide a listing of all the shared task papers and datasets from this review in a GitLab repository. [ABSTRACT FROM AUTHOR]

Objective: Electronic consultation (eConsult) content reflects important information about referring clinician needs across an organization, but is challenging to extract. The objective of this work was to develop machine learning models for classifying eConsult questions for question type and question content. Another objective of this work was to investigate the ability to solve this task with constrained expert time resources.Materials and Methods: Our data source is the San Francisco Health Network eConsult system, with over 700 000 deidentified questions from the years 2008-2017, from gastroenterology, urology, and neurology specialties. We develop classifiers based on Bidirectional Encoder Representations from Transformers, experimenting with multitask learning to learn when information can be shared across classifiers. We produce learning curves to understand when we may be able to reduce the amount of human labeling required.Results: Multitask learning shows benefits only in the neurology-urology pair where they shared substantial similarities in the distribution of question types. Continued pretraining of models in new domains is highly effective. In the neurology-urology pair, near-peak performance is achieved with only 10% of the urology training data given all of the neurology data.Discussion: Sharing information across classifier types shows little benefit, whereas sharing classifier components across specialties can help if they are similar in the balance of procedural versus cognitive patient care.Conclusion: We can accurately classify eConsult content with enough labeled data, but only in special cases do methods for reducing labeling effort apply. Future work should explore new learning paradigms to further reduce labeling effort. [ABSTRACT FROM AUTHOR]

Introduction/Aims: We investigated the age‐ and sex‐specific incidence and survival of Medicare beneficiaries with amyotrophic lateral sclerosis (ALS) in patients 66 to 90 years of age. Methods: We identified all incident ALS cases within a population‐based sample of Medicare beneficiaries in 2009 (total: 22 000 177 person‐years at risk for ALS). We calculated age‐ and sex‐specific incidence in 2009 according to multiple, progressively more stringent case definitions. Our most inclusive definition required one ALS code, whereas the most restrictive definition required at least one additional ALS code more than 6 months after the first code, including one from a neurologist. We identified associated imaging studies and electrodiagnostic testing and followed all cases through the end of 2014 to determine survival. Results: The overall incidence for our most inclusive definition was 22.84 per 100 000 person‐years for men and 16.05 per 100 000 person‐years for women. The overall incidence was 5.72 per 100 000 person‐years for men and 3.99 per 100 000 person‐years for women for our most restrictive definition. For our most inclusive definition, fewer than 39.7% of cases ever had an ALS diagnosis from a neurologist, more than 50% had an electrodiagnostic test or imaging study, and 40.1% survived less than 1 year after diagnosis, with 25.5% of these cases surviving no more than 6 months. Cases not meeting the most restrictive definition were more likely than those who did meet the restrictive definition to be older, black, or Asian. Discussion: The oldest and marginalized Medicare beneficiaries diagnosed with ALS are less likely to be included in epidemiological studies with restrictive definitions, but future studies will need to assess the accuracy of diagnosis. [ABSTRACT FROM AUTHOR]

The foundation of W. Matthews Grant's project in Free Will and God's Universal Causality is his Non-Occasionalist version of Divine Universal Causality (NODUC), which affirms the traditional concurrentist idea that God and secondary causes cooperate non-superfluously in such a way that they both produce the entire effect. Grant defends NODUC's concurrentist account by responding to 'The Metaphysical Objection', which alleges that concurrentism places an inconsistent set of demands upon secondary causes. I argue that Grant's responses to that objection are unconvincing, and thus, he fails to demonstrate that NODUC is a stable foundation for the rest of his project. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by motor neuron loss. ALS is now associated with mutations in numerous genes, many of which cause disease in part through toxic gain-of-function mechanisms. Antisense oligonucleotides (ASOs) are small sequences of DNA that can reduce expression of a target gene at the post-transcriptional level, making them attractive for neutralizing mutant or toxic gene products. Advancements in the medicinal chemistries of ASOs have improved their pharmacodynamic profile to allow safe and effective delivery to the central nervous system. ASO therapies for ALS have rapidly developed over the last two decades, and ASOs that target SOD1, C9orf72, FUS, and ATXN2 are now in clinical trials for familial or sporadic forms of ALS. This review discusses the current state of ASO therapies for ALS, outlining their successes from preclinical development to early clinical trials. [ABSTRACT FROM AUTHOR]

That 1 Peter uses participles where imperatives are expected is clear. Why it does so is not. Scholarly discussion has focused on whether the participles are independent or dependent. Early grammarians argued that these participles were dependent but struggled to explain why the participles appeared far from their head verb. Modern grammarians have argued that they are independent, yet they have given insufficient attention to why the participle is used instead of the imperative. This article suggests a path forward, which vindicates the earlier interpretation by providing a discourse explanation for the "imperatival participles." Stated simply, the participle is operating according to its normal function by structuring the discourse. That the participles in 1 Peter are far from their head verb shows the complex structuring of the letter, with the main imperatives moving the discourse along and the participles expressing ways that those head verbs may be accomplished. [ABSTRACT FROM AUTHOR]