De-epimerizing DyKAT of ß-lactones generated by isothiourea-catalysed enantioselective [2 + 2] cycloaddition.

An enantioselective isothiourea-catalysed [2 + 2] cycloaddition of C(1)-ammonium enolates with pyrazol-4,5-diones is used to construct spirocyclic ß-lactones in good yields, excellent enantioselectivity (99 : 1 er) but with modest diastereocontrol (typically 70 : 30 dr). Upon ring-opening with morpholine or alternative nucleophilic amines and alcohols ß-hydroxyamide and ß-hydroxyester products are generated with enhanced diastereocontrol (up to >95 : 5 dr). Control experiments show that stereoconvergence is observed in the ring-opening of diastereoisomeric ß-lactones, leading to a single product (>95 : 5 dr, >99 : 1 er). Mechanistic studies and DFT analysis indicate a substrate controlled Dynamic Kinetic Asymmetric Transformation (DyKAT) involving epimerisation at C(3) of the ß-lactone under the reaction conditions, coupled with a hydrogen bond-assisted nucleophilic addition to the Si-face of the ß-lactone and stereodetermining ring-opening. The scope and limitations of a one-pot protocol consisting of isothiourea-catalysed enantio-determining [2 + 2] cycloaddition followed by diastereo-determining ring-opening are subsequently developed. Variation within the anhydride ammonium enolate precursor, as well as N(1) and C(3) within the pyrazol-4,5-dione scaffold is demonstrated, giving a range of functionalised ß-hydroxyamides with high diastereo- and enantiocontrol (>20 examples, up to >95 : 5 dr and >99 : 1 er) via this DyKAT.

α-Phenylthioaldehydes for the effective generation of acyl azolium and azolium enolate intermediates.

α-Phenylthioaldehydes are readily prepared using a simple multi-step procedure and herein are introduced as a new precursor for the NHC-catalysed generation of acyl azolium and azolium enolate intermediates that are of widespread synthetic interest and utility. Treatment of α-phenylthioaldehydes with an NHC precatalyst and base produces an efficient redox rearrangement via a Breslow intermediate, elimination of thiophenolate, and subsequent rebound addition to the generated acyl azolium to give the corresponding thiol ester. In the presence of an external alcohol, competition between redox rearrangement and redox esterification can be controlled through judicious choice of the N-aryl substituent within the NHC precatalyst and the base used in the reaction. With NEt3 as base, NHCs bearing electron-withdrawing (N-C6F5 or N-C6H2Cl3) substituents favour redox rearrangement, while triazolium precatalysts with electron-rich N-aryl substituents (N-Ph, N-Mes) result in preferential redox esterification. Using DBU, redox esterification is preferred due to transesterification of the initially formed thiol ester product. Additionally, α-phenylthioaldehyde-derived azolium enolates have been used in enantioselective formal [4 + 2]-cycloaddition reactions to access dihydropyridinone heterocycles with high enantioselectivity (up to >95 : 5 dr, 98 : 2 er).

Prospective Evaluation of Artificial Intelligence Triage of Incidental Pulmonary Emboli on Contrast-Enhanced CT Examinations of the Chest or Abdomen.

Background: Artificial intelligence (AI) algorithms improved detection of incidental pulmonary embolism (IPE) on contrast-enhanced CT (CECT) examinations in retrospective studies; however, prospective validation studies are lacking. Objective: To assess the effect on radiologists' real-world diagnostic performance and report turnaround times of a radiology department's clinical implementation of an AI triage system for detecting IPE on CECT examinations of the chest or abdomen. Methods: This prospective single-center study included consecutive adult patients who underwent CECT of the chest or abdomen for reasons other than PE detection from May 12, 2021 to June 30, 2021 (phase 1) or from July 1, 2021 to September 29, 2021 (phase 2). Before phase 1, the radiology department installed a commercially available AI triage algorithm for IPE detection that automatically processed CT examinations and notified radiologists of positive results through an interactive floating widget. In phase 1, the widget was inactive, and radiologists interpreted examinations without AI assistance. In phase 2, the widget was activated, and radiologists interpreted examinations with AI assistance. A review process involving a panel of radiologists was implemented to establish the reference standard for the presence of IPE. Diagnostic performance and report turnaround times were compared using Pearson Chi-square test and Wilcoxon rank-sum test, respectively. Results: Phase 1 included 1467 examinations in 1434 patients (mean age, 53.8±18.5 years; 753 male, 681 female); phase 2 included 3182 examinations in 2886 patients (mean age, 55.4±18.2 years; 1520 male, 1366 female). The frequency of IPE was 1.4% (20/1467) in phase 1 and 1.6% (52/3182) in phase 2. Radiologists without AI, in comparison with radiologists with AI, showed significantly lower sensitivity (80.0% vs 96.2%, P=.03), without a significant difference in specificity (99.1% vs 99.9%, P=.58), for detection of IPE. The mean report turnaround time for IPE-positive examinations was not significantly different between radiologists without AI and radiologists with AI (78.3 vs 64.6 min, P=.26). Conclusion: An AI triage system improved radiologists' sensitivity for IPE detection on CECT examinations of the chest or abdomen without significant change in report turnaround times. Clinical Impact: This prospective real-world study supports the use of AI assistance for maximizing IPE detection.

Developing emotional preparedness and mental resilience through high-fidelity simulation: a 'bridge too far' for institutions teaching major trauma management and mass-casualty medicine?

BACKGROUND: Clinical acumen represents only part of being adequately equipped to attend a major incident. The emotive sights, sounds and smells of these dynamic environments are all-encompassing experiences, and responders must also be armed with the emotional preparedness to perform their clinical or managerial duties effectively, as well as the mental resilience to facilitate professional continuance. Despite this, limited training and a sparsity of evidence exists to guide developments within this domain. Historically, major incident training has focused on clinical theory acquisition, but irrespective of how comprehensive the learning materials, they are of little consequence if tandem steps to cultivate mental resilience and emotional preparedness are absent. High-Fidelity Simulation (HFS) has a growing reputation as an effective means of bridging important gaps between theory and practice. This pilot study aimed to measure student's self-reported perception of their readiness to respond to a major incident following a large-scale HFS. METHODS: Quantitative data was obtained from a sample of 108 students undertaking paramedic science, physician associate studies and adult nursing degree programmes. A bespoke questionnaire was developed to measure self-reported clinical acumen, mental and emotional preparedness. RESULTS: 91% of students agreed the combination of theoretical training and HFS provided made them feel clinically prepared to attend a real major incident; 86% agreed this experience had developed their mental resilience and 90% agreed that they felt emotionally prepared to attend a major incident. CONCLUSION: Within this pilot study, the blend of theoretical training and HFS contributed to self-reported clinical acumen, mental and emotional preparation, in learners training to work in disaster environments or emergency medicine settings.

Depressive symptoms in adolescence and adult educational and employment outcomes: a structured life course analysis.

BACKGROUND: Depression is a common mental health disorder that often starts during adolescence, with potentially important future consequences including 'Not in Education, Employment or Training' (NEET) status. METHODS: We took a structured life course modeling approach to examine how depressive symptoms during adolescence might be associated with later NEET status, using a high-quality longitudinal data resource. We considered four plausible life course models: (1) an early adolescent sensitive period model where depressive symptoms in early adolescence are more associated with later NEET status relative to exposure at other stages; (2) a mid adolescent sensitive period model where depressive symptoms during the transition from compulsory education to adult life might be more deleterious regarding NEET status; (3) a late adolescent sensitive period model, meaning that depressive symptoms around the time when most adults have completed their education and started their careers are the most strongly associated with NEET status; and (4) an accumulation of risk model which highlights the importance of chronicity of symptoms. RESULTS: Our analysis sample included participants with full information on NEET status (N = 3951), and the results supported the accumulation of risk model, showing that the odds of NEET increase by 1.015 (95% CI 1.012-1.019) for an increase of 1 unit in depression at any age between 11 and 24 years. CONCLUSIONS: Given the adverse implications of NEET status, our results emphasize the importance of supporting mental health during adolescence and early adulthood, as well as considering specific needs of young people with re-occurring depressed mood.

Enantioselective Synthesis in Continuous Flow: Polymer-Supported Isothiourea-Catalyzed Enantioselective Michael Addition-Cyclization with α-Azol-2-ylacetophenones.

A packed reactor bed incorporating a polymer-supported isothiourea HyperBTM catalyst derivative has been used to promote the enantioselective synthesis of a range of heterocyclic products derived from α-azol-2-ylacetophenones and -acetamides combined with alkyl, aryl, and heterocyclic α,ß-unsaturated homoanhydrides in continuous flow via an α,ß-unsaturated acyl-ammonium intermediate. The products are generated in good to excellent yields and generally in excellent enantiopurity (up to 97:3 er). Scale-up is demonstrated on a 15 mmol scale, giving the heterocyclic product in 68% overall yield with 98:2 er after recrystallization.

How well do parents identify their child's baby teeth? Engagement and accuracy of parent-reported information on a tooth checklist survey.

OBJECTIVES: Naturally exfoliated primary teeth are being increasingly collected in child development studies. Most of these odontological collections and tooth biobanks use parent-reported information from questionnaires or tooth checklists to collect data on offspring teeth. To the best of the authors' knowledge, no studies have assessed parental engagement in tooth checklists, nor parental accuracy in identifying their child's baby tooth. This study aimed to evaluate these dimensions by analysing data from the about this tooth checklist returned with donated primary teeth in a natural experimental study called STRONG (the Stories Teeth Record of Newborn Growth). METHODS: Parental self-reported information were analysed on checklists returned with 825 primary teeth belonging to 199 children. The percentage of blank answers was calculated for each question. The accuracy of parents-reported tooth identification was evaluated by comparing parental ratings to researchers' ratings. Reliability of researchers' tooth identification was first evaluated by calculating intra-observer and inter-observer agreements, as well as Cohen's Kappa values. The percentage of accuracy of parents' tooth identification (relative to researcher's) was then calculated, and logistic regressions were used to evaluate if time elapsed between when exfoliation occurred and the checklist was completed associated with parental accuracy in tooth identification. RESULTS: Parents returned 98.4% of the checklists and completed 74.9% to 97.7% of the questions. Excellent reliability was demonstrated for researchers' intra- and inter-rater tooth identification (agreement percentages >90%; Cohen's Kappa values >.83). Moderate accuracy of parents-reported tooth identifications was found, with parents correctly identifying 49.5% of the donated tooth. Better parental accuracies were highlighted for partial identifications (87.1% of correct jaw, 75.6% of correct tooth type, and 65.8% of correct lateralization). Logistic regressions showed the odds of correct parental identifications decreased on average by 1.8% every 30 days of distance between tooth exfoliation and checklist completion. CONCLUSIONS: While parental engagement is high, parents-reported tooth identifications have moderate accuracy, which decreases over time. High accuracy is however found for partial identifications. Parent-reported information on the accompanying questionnaire of naturally exfoliated primary teeth collection or tooth biobanks, even when filled in a long time after exfoliation took place, should be encouraged. However, expert identifications of teeth should remain best practice.

The relationship between type, timing and duration of exposure to adverse childhood experiences and adolescent self-harm and depression: findings from three UK prospective population-based cohorts.

BACKGROUND: Adverse childhood experiences (ACEs) are well-established risk factors for self-harm and depression. However, despite their high comorbidity, there has been little focus on the impact of developmental timing and the duration of exposure to ACEs on co-occurring self-harm and depression. METHODS: Data were utilised from over 22,000 children and adolescents participating in three UK cohorts, followed up longitudinally for 14-18 years: the Avon Longitudinal Study of Parents and Children (ALSPAC), the Millennium Cohort Study (MCS) and the Environmental Risk (E-Risk) Longitudinal Twin Study. Multinomial logistic regression models estimated associations between each ACE type and a four-category outcome: no self-harm or depression, self-harm alone, depression alone and self-harm with co-occurring depression. A structured life course modelling approach was used to examine whether the accumulation (duration) of exposure to each ACE, or a critical period (timing of ACEs) had the strongest effects on self-harm and depression in adolescence. RESULTS: The majority of ACEs were associated with co-occurring self-harm and depression, with consistent findings across cohorts. The importance of timing and duration of ACEs differed across ACEs and across cohorts. For parental mental health problems, longer duration of exposure was strongly associated with co-occurring self-harm and depression in both ALSPAC (adjusted OR: 1.18, 95% CI: 1.10-1.25) and MCS (1.18, 1.11-1.26) cohorts. For other ACEs in ALSPAC, exposure in middle childhood was most strongly associated with co-occurring self-harm and depression, and ACE occurrence in early childhood and adolescence was more important in the MCS. CONCLUSIONS: Efforts to mitigate the impact of ACEs should start in early life with continued support throughout childhood, to prevent long-term exposure to ACEs contributing to risk of self-harm and depression in adolescence.

Strengths-weaknesses-opportunities-threats analysis of artificial intelligence in anesthesiology and perioperative medicine.

The use of artificial intelligence (AI) and machine learning (ML) in anesthesiology and perioperative medicine is quickly becoming a mainstay of clinical practice. Anesthesiology is a data-rich medical specialty that integrates multitudes of patient-specific information. Perioperative medicine is ripe for applications of AI and ML to facilitate data synthesis for precision medicine and predictive assessments. Examples of emergent AI models include those that assist in assessing depth and modulating control of anesthetic delivery, event and risk prediction, ultrasound guidance, pain management, and operating room logistics. AI and ML support analyzing integrated perioperative data at scale and can assess patterns to deliver optimal patient-specific care. By exploring the benefits and limitations of this technology, we provide a basis of considerations for evaluating the adoption of AI models into various anesthesiology workflows. This analysis of AI and ML in anesthesiology and perioperative medicine explores the current landscape to understand better the strengths, weaknesses, opportunities, and threats (SWOT) these tools offer.

CXCL10/IgG1 Axis in Multiple Sclerosis as a Potential Predictive Biomarker of Disease Activity.

BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is a heterogeneous disease, and its course is difficult to predict. Prediction models can be established by measuring intrathecally synthesized proteins involved in inflammation, glial activation, and CNS injury. METHODS: To determine how these intrathecal proteins relate to the short-term, i.e., 12 months, disease activity in relapsing-remitting MS (RRMS), we measured the intrathecal synthesis of 46 inflammatory mediators and 14 CNS injury or glial activation markers in matched serum and CSF samples from 47 patients with MS (pwMS), i.e., 23 RRMS and 24 clinically isolated syndrome (CIS), undergoing diagnostic lumbar puncture. Subsequently, all pwMS were followed for ≥12 months in a retrospective follow-up study and ultimately classified into "active", i.e., developing clinical and/or radiologic disease activity, n = 18) or "nonactive", i.e., not having disease activity, n = 29. Disease activity in patients with CIS corresponded to conversion to RRMS. Thus, patients with CIS were subclassified as "converters" or "nonconverters" based on their conversion status at the end of a 12-month follow-up. Twenty-seven patients with noninflammatory neurologic diseases were included as negative controls. Data were subjected to differential expression analysis and modeling techniques to define the connectivity arrangement (network) between neuroinflammation and CNS injury relevant to short-term disease activity in RRMS. RESULTS: Lower age and/or higher CXCL13 levels positively distinguished active/converting vs nonactive/nonconverting patients. Network analysis significantly improved the prediction of short-term disease activity because active/converting patients featured a stronger positive connection between IgG1 and CXCL10. Accordingly, analysis of disease activity-free survival demonstrated that pwMS, both RRMS and CIS, with a lower or negative IgG1-CXCL10 correlation, have a higher probability of activity-free survival than the patients with a significant correlation (p < 0.0001, HR ≥ 2.87). DISCUSSION: Findings indicate that a significant IgG1-CXCL10 positive correlation predicts the risk of short-term disease activity in patients with RRMS and CIS. Thus, the present results can be used to develop a predictive model for MS activity and conversion to RRMS.

General-Purpose Large Language Models Versus a Domain-Specific Natural Language Processing Tool for Label Extraction From Chest Radiograph Reports.

GPT-4 outperformed a radiology domain-specific natural language processing model in classifying imaging findings from chest radiograph reports, both with and without predefined labels. Prompt engineering for context further improved performance. The findings indicate a role for large language models to accelerate artificial intelligence model development in radiology by automating data annotation.

Ambulance clinicians implementing evidence-based practice: mind the gap! Attitudes, perceptions and experiences of student paramedics.

Background: Evidence-based practice (EBP) represents the conscientious and judicious use of the best contemporaneous evidence in partnership with patient values and clinical expertise to guide healthcare professionals. As a result, EBP is a recommended component of undergraduate education and considered fundamental for improving patient outcomes. EBP principles have thus become deeply rooted in higher education curricula, but only in recent years has this begun to permeate the world of paramedic practice. Despite this paradigm, the impact of EBP may be limited because ambulance clinicians may struggle with implementation, as a variety of barriers influence translation and application. Methods: A survey study aimed to gain insight into the epistemological and metacognitive barriers impacting student experience in order to help improve teaching and learning practices. Results: A sample of 64 students, across two different undergraduate paramedic science programmes, were recruited. Of these, 70% of BSc (Hons) students versus 33% of DipHE students agreed to some extent or greater that EBP represented minimal benefit in real-world practice due to Trust policy and the guidelines set out by the Joint Royal Colleges Ambulance Liaison Committee (Welch's t = 2.571, df = 26, p = 0.016 two-sided). Furthermore, 25% felt standard operating procedures negatively impacted their ability to implement EBP, and 39% reported their EBP learning had improved their ability to implement improved levels of patient care. Conclusion: A disparity between theoretical learning and EBP implementation was identified. EBP may not dovetail with standard operating procedure within UK ambulance Trusts, resulting in confusion among student paramedics as to the true worth of EBP.

Understanding divergent substrate stereoselectivity in the isothiourea-catalysed conjugate addition of cyclic α-substituted ß-ketoesters to α,ß-unsaturated aryl esters.

The development of enantioselective synthetic methods capable of generating vicinal stereogenic centres, where one is tetrasubstituted (such as either an all-carbon quaternary centre or where one or more substituents are heteroatoms), is a recognised synthetic challenge. Herein, the enantioselective conjugate addition of a range of carbo- and heterocyclic α-substituted ß-ketoesters to α,ß-unsaturated aryl esters using the isothiourea HyperBTM as a Lewis base catalyst is demonstrated. Notably, divergent diastereoselectivity is observed through the use of either cyclopentanone-derived or indanone-derived substituted ß-ketoesters with both generating the desired stereodefined products with high selectivity (>95 : 5 dr, up to 99 : 1 er). The scope and limitations of these processes are demonstrated, alongside application on gram scale. The origin of the divergent substrate selectivity has been probed through the use of DFT-analysis, with preferential orientation driven by dual stabilising CH⋯O interactions. The importance of solvation with strongly polar transition-states is highlighted and the SMD solvation model is demonstrated to capture solvation effects reliably.

Access to a Diverse Array of Bridged Benzo[1,5]oxazocine and Benzo[1,4]diazepine Structures.

The preparation of bridged benzo[1,5]oxazocines and benzo[1,4]diazepines is demonstrated from simple aniline and aldehyde starting materials. A one-pot condensation/6π electrocyclization is followed by an intramolecular trapping of the 2,3-dihydroquinoline intermediate by nitrogen or oxygen nucleophiles to give bridged seven- and eight-membered products. Using 3-hydroxypyridinecarboxaldehydes results in a stable zwitterionic structure that can undergo a diastereoselective reduction under hydrogenative conditions. A similar cyclization/hydrogenation pathway with excellent diastereoselectivity is also demonstrated from 2-pyridyl-substituted 1,2,3,4-tetrahydroquinolines.

Sensitive Periods for the Effect of Child Maltreatment on Psychopathology Symptoms in Adolescence.

Introduction: Child maltreatment is among the strongest risk factors for mental disorders. However, little is known about whether there are ages when children may be especially vulnerable to its effects. We sought to identify potential sensitive periods when exposure to the 2 most common types of maltreatment (neglect and harsh physical discipline) had a particularly detrimental effect on youth mental health. Methods: Data came from the Future of Families and Child Wellbeing Study (FFCWS), a birth cohort oversampled from "fragile families" (n = 3,474). Maltreatment was assessed at 3, 5, and 9 years of age using an adapted version of the Parent-Child Conflict Tactics Scales (CTS-PC). Using least angle regression, we examined the relationship between repeated measures of exposure to maltreatment on psychopathology symptoms at age 15 years (Child Behavior Checklist; CBCL/6-18). For comparison, we evaluated the strength of evidence to support the existence of sensitive periods in relation to an accumulation of risk model. Results: We identified sensitive periods for harsh physical discipline, whereby psychopathology symptom scores were highest among girls exposed at age 9 years (r2 = 0.67 internalizing symptoms; r2 = 1% externalizing symptoms) and among boys exposed at age 5 years (r2 = 0.41%). However, for neglect, the accumulation of risk model explained more variability in psychopathology symptoms for both boys and girls. Conclusion: Child maltreatment may have differential effects based on the child's sex, type of exposure, and the age at which it occurs. These findings provide additional evidence for clinicians assessing the benefits and drawbacks of screening efforts and point toward possible mechanisms driving increased vulnerability to psychopathology.

Prospective Evaluation of AI Triage of Pulmonary Emboli on CT Pulmonary Angiograms.

Background Artificial intelligence (AI) algorithms have shown high accuracy for detection of pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies in academic studies. Purpose To determine whether use of an AI triage system to detect PE on CTPA studies improves radiologist performance or examination and report turnaround times in a clinical setting. Materials and Methods This prospective single-center study included adult participants who underwent CTPA for suspected PE in a clinical practice setting. Consecutive CTPA studies were evaluated in two phases, first by radiologists alone (n = 31) (May 2021 to June 2021) and then by radiologists aided by a commercially available AI triage system (n = 37) (September 2021 to December 2021). Sixty-two percent of radiologists (26 of 42 radiologists) interpreted studies in both phases. The reference standard was determined by an independent re-review of studies by thoracic radiologists and was used to calculate performance metrics. Diagnostic accuracy and turnaround times were compared using Pearson χ2 and Wilcoxon rank sum tests. Results Phases 1 and 2 included 503 studies (participant mean age, 54.0 years ± 17.8 [SD]; 275 female, 228 male) and 1023 studies (participant mean age, 55.1 years ± 17.5; 583 female, 440 male), respectively. In phases 1 and 2, 14.5% (73 of 503) and 15.9% (163 of 1023) of CTPA studies were positive for PE (P = .47). Mean wait time for positive PE studies decreased from 21.5 minutes without AI to 11.3 minutes with AI (P < .001). The accuracy and miss rate, respectively, for radiologist detection of any PE on CTPA studies was 97.6% and 12.3% without AI and 98.6% and 6.1% with AI, which was not significantly different (P = .15 and P = .11, respectively). Conclusion The use of an AI triage system to detect any PE on CTPA studies improved wait times but did not improve radiologist accuracy, miss rate, or examination and report turnaround times. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Murphy and Tee in this issue.