Disparities in Access to Timely Waitlisting Among Pediatric Kidney Transplant Candidates.

BACKGROUND AND OBJECTIVES: Kidney transplantation with minimal or no dialysis exposure provides optimal outcomes for children with end-stage kidney disease. We sought to understand disparities in timely access to transplant waitlisting. METHODS: We conducted a retrospective, registry-based cohort study of candidates ages 3 to 17 added to the US kidney transplant waitlist 2015 to 2019. We defined "preemptive waitlisting" as waitlist addition before receiving dialysis and compared demographics of candidates based on preemptive status. We used competing risk regression to determine the association between preemptive waitlisting and transplantation. We then identified waitlist additions age >18 who initiated dialysis as children, thereby missing pediatric allocation prioritization, and evaluated the association between waitlisting with pediatric prioritization and transplantation. RESULTS: Among 4506 pediatric candidates, 48% were waitlisted preemptively. Female sex, Hispanic ethnicity, Black race, and public insurance were associated with lower adjusted relative risk of preemptive waitlisting. Preemptive listing was not associated with time from waitlist activation to transplantation (adjusted hazard ratio 0.94, 95% confidence interval 0.87-1.02). Among transplant recipients waitlisted preemptively, 68% had no pretransplant dialysis, whereas recipients listed nonpreemptively had median 1.6 years of dialysis at transplant. Among 415 candidates initiating dialysis as children but waitlisted as adults, transplant rate was lower versus nonpreemptive pediatric candidates after waitlist activation (adjusted hazard ratio 0.54, 95% confidence interval 0.44-0.66). CONCLUSIONS: Disparities in timely waitlisting are associated with differences in pretransplant dialysis exposure despite no difference in time to transplant after waitlist activation. Young adults who experience delays may miss pediatric prioritization, highlighting an area for policy intervention.

Single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease.

The emergence of single nucleus RNA sequencing (snRNA-seq) offers to revolutionize the study of Alzheimer's disease (AD). Integration with complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link cell subpopulations and molecular networks with a broader disease-relevant context. We report snRNA-seq profiles from superior frontal gyrus samples from 101 well characterized subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in hematological parameters. We observed an AD-associated CD83(+) microglial subtype with unique molecular networks and which is associated with immunoglobulin IgG4 production in the transverse colon. Our major observations were replicated in two additional, independent snRNA-seq data sets. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal disease biology.

Results From the Big Ten COVID-19 Cardiac Registry: Impact of SARS-COV-2 on Myocardial Involvement.

OBJECTIVE: COVID-19 has been associated with myocardial involvement in collegiate athletes. The first report from the Big Ten COVID-19 Cardiac Registry (Registry) was an ecological study that reported myocarditis in 37 of 1597 athletes (2.3%) based on local clinical diagnosis. Our objective was to assess the relationship between athlete and clinical characteristics and myocardial involvement. DESIGN: Cross-sectional study. SETTING: We analyzed data from 1218 COVID-19 positive Big Ten collegiate athletes who provided informed consent to participate in the Registry. PARTICIPANTS: 1218 athletes with a COVID-19-positive PCR test before June 1, 2021. ASSESSMENT OF INDEPENDENT VARIABLES: Demographic and clinical characteristics of athletes were obtained from the medical record. MAIN OUTCOME MEASURES: Myocardial involvement was diagnosed based on local clinical, cardiac magnetic resonance (CMR), electrocardiography, troponin assay, and echocardiography. We assessed the association of clinical factors with myocardial involvement using logistic regression and estimated the area under the receiver operating characteristic (ROC) curve. RESULTS: 25 of 1218 (2.0%) athletes met criteria for myocardial involvement. The logistic regression model used to predict myocardial involvement contained indicator variables for chest pain, new exercise intolerance, abnormal echocardiogram (echo), and abnormal troponin. The area under the ROC curve for these indicators was 0.714. The presence of any of these 4 factors in a collegiate athlete who tested positive for COVID-19 would capture 55.6% of cases. Among noncases without missing data, 86.9% would not be flagged for possible myocardial involvement. CONCLUSION: Myocardial involvement was infrequent. We predicted case status with good specificity but deficient sensitivity. A diagnostic approach for myocardial involvement based exclusively on symptoms would be less sensitive than one based on symptoms, echo, and troponin level evaluations. Abnormality of any of these evaluations would be an indication for CMR.

Consortium Profile: The Methylation, Imaging and NeuroDevelopment (MIND) Consortium.

Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.

Genetic testing in early-onset atrial fibrillation.

Atrial fibrillation (AF) is a globally prevalent cardiac arrhythmia with significant genetic underpinnings, as highlighted by recent large-scale genetic studies. A prominent clinical and genetic overlap exists between AF, heritable ventricular cardiomyopathies, and arrhythmia syndromes, underlining the potential of AF as an early indicator of severe ventricular disease in younger individuals. Indeed, several recent studies have demonstrated meaningful yields of rare pathogenic variants among early-onset AF patients (∼4%-11%), most notably for cardiomyopathy genes in which rare variants are considered clinically actionable. Genetic testing thus presents a promising opportunity to identify monogenetic defects linked to AF and inherited cardiac conditions, such as cardiomyopathy, and may contribute to prognosis and management in early-onset AF patients. A first step towards recognizing this monogenic contribution was taken with the Class IIb recommendation for genetic testing in AF patients aged 45 years or younger by the 2023 American College of Cardiology/American Heart Association guidelines for AF. By identifying pathogenic genetic variants known to underlie inherited cardiomyopathies and arrhythmia syndromes, a personalized care pathway can be developed, encompassing more tailored screening, cascade testing, and potentially genotype-informed prognosis and preventive measures. However, this can only be ensured by frameworks that are developed and supported by all stakeholders. Ambiguity in test results such as variants of uncertain significance remain a major challenge and as many as ∼60% of people with early-onset AF might carry such variants. Patient education (including pretest counselling), training of genetic teams, selection of high-confidence genes, and careful reporting are strategies to mitigate this. Further challenges to implementation include financial barriers, insurability issues, workforce limitations, and the need for standardized definitions in a fast-moving field. Moreover, the prevailing genetic evidence largely rests on European descent populations, underscoring the need for diverse research cohorts and international collaboration. Embracing these challenges and the potential of genetic testing may improve AF care. However, further research-mechanistic, translational, and clinical-is urgently needed.

Crystal structure determination and analyses of Hirshfeld surface, crystal voids, inter-molecular inter-action energies and energy frameworks of 1-benzyl-4-(methyl-sulfan-yl)-3a,7a-di-hydro-1H-pyrazolo-[3,4-d]pyrimidine.

The pyrazolo-pyrimidine moiety in the title mol-ecule, C13H12N4S, is planar with the methyl-sulfanyl substituent lying essentially in the same plane. The benzyl group is rotated well out of this plane by 73.64 (6)°, giving the mol-ecule an approximate L shape. In the crystal, C-H⋯π(ring) inter-actions and C-H⋯S hydrogen bonds form tubes extending along the a axis. Furthermore, there are π-π inter-actions between parallel phenyl rings with centroid-to-centroid distances of 3.8418 (12) Å. A Hirshfeld surface analysis of the crystal structure indicates that the most important contributions to the crystal packing are from H⋯H (47.0%), H⋯N/N⋯H (17.6%) and H⋯C/C⋯H (17.0%) inter-actions. The volume of the crystal voids and the percentage of free space were calculated to be 76.45 Å3 and 6.39%, showing that there is no large cavity in the crystal packing. Evaluation of the electrostatic, dispersion and total energy frameworks indicate that the cohesion of the crystal structure is dominated by the dispersion energy contributions.

Efficient Synthesis, Structural Characterization, Antibacterial Assessment, ADME-Tox Analysis, Molecular Docking and Molecular Dynamics Simulations of New Functionalized Isoxazoles.

This work describes the synthesis, characterization, and in vitro and in silico evaluation of the biological activity of new functionalized isoxazole derivatives. The structures of all new compounds were analyzed by IR and NMR spectroscopy. The structures of 4c and 4f were further confirmed by single crystal X-ray and their compositions unambiguously determined by mass spectrometry (MS). The antibacterial effect of the isoxazoles was assessed in vitro against Escherichia coli, Bacillus subtilis, and Staphylococcusaureus bacterial strains. Isoxazole 4a showed significant activity against E. coli and B. subtilis compared to the reference antibiotic drugs while 4d and 4f also exhibited some antibacterial effects. The molecular docking results indicate that the synthesized compounds exhibit strong interactions with the target proteins. Specifically, 4a displayed a better affinity for E. coli, S. aureus, and B. subtilis in comparison to the reference drugs. The molecular dynamics simulations performed on 4a strongly support the stability of the ligand-receptor complex when interacting with the active sites of proteins from E. coli, S. aureus, and B. subtilis. Lastly, the results of the Absorption, Distribution, Metabolism, Excretion and Toxicity Analysis (ADME-Tox) reveal that the molecules have promising pharmacokinetic properties, suggesting favorable druglike properties and potential therapeutic agents.

Quality Assurance Model for Breast Cancer Prognostication Using the Modified Magee Equations.

CONTEXT.­: The Oncotype DX recurrence score (RS) is a widely used test that provides prognostic information on the likelihood of disease recurrence and predictive information on the benefit of chemotherapy in early-stage, hormone receptor-positive breast cancer. Despite its widespread use, quality assurance of the RS does not receive the same level of scrutiny as other tests, such as human epidermal growth factor receptor 2 (HER2) immunohistochemistry. OBJECTIVE.­: To use modified Magee equations to calculate Magee score (MS) as a quality check of RS. DESIGN.­: The MS is an easily accessible prognostic model that uses histopathologic and immunohistochemical criteria. We identified cases where the RS and MS differed by 10 points or more or were in different risk categories. These instances were considered significant discordances. MS was presented along with RS at multidisciplinary tumor boards and all discrepancies were discussed to determine clinical significance and appropriate next steps. RESULTS.­: Twenty-five of 155 cases (16.1%) had discrepancies between RS and MS. Of these 25 cases, 3 (12%) had problems with either the RS or the histopathologic interpretation. Among the cases with concordant RS and MS, no RS or interpretive problems were identified. CONCLUSIONS.­: Use of the MS as a quality control check for the RS can help ensure appropriate treatment decisions in breast cancer patients. Pathologists can play a key role in ensuring the quality of molecular-based prognostic scores by using histopathologic models to ensure accurate risk stratification and improve clinical outcomes.

A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer.

The Gleason score is an important predictor of prognosis in prostate cancer. However, its subjective nature can result in over- or under-grading. Our objective was to train an artificial intelligence (AI)-based algorithm to grade prostate cancer in specimens from patients who underwent radical prostatectomy (RP) and to assess the correlation of AI-estimated proportions of different Gleason patterns with biochemical recurrence-free survival (RFS), metastasis-free survival (MFS), and overall survival (OS). Training and validation of algorithms for cancer detection and grading were completed with three large datasets containing a total of 580 whole-mount prostate slides from 191 RP patients at two centers and 6218 annotated needle biopsy slides from the publicly available Prostate Cancer Grading Assessment dataset. A cancer detection model was trained using MobileNetV3 on 0.5 mm × 0.5 mm cancer areas (tiles) captured at 10× magnification. For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. This strategy resulted in improved model generalizability in the test set compared with three different control experiments when evaluated on both needle biopsy slides and whole-mount prostate slides from different centers. In an additional test cohort of RP patients who were clinically followed over 30 years, quantitative Gleason pattern AI estimates achieved concordance indexes of 0.69, 0.72, and 0.64 for predicting RFS, MFS, and OS times, outperforming the control experiments and International Society of Urological Pathology system (ISUP) grading by pathologists. Finally, unsupervised clustering of test RP patient specimens into low-, medium-, and high-risk groups based on AI-estimated proportions of each Gleason pattern resulted in significantly improved RFS and MFS stratification compared with ISUP grading. In summary, deep learning-based quantitative Gleason scoring using a selective CutMix training strategy may improve prognostication after prostate cancer surgery.

Synthesis, Crystal Structure, Hirshfeld Surface Analysis, and Computational Approach of a New Pyrazolo[3,4-g]isoquinoline Derivative as Potent against Leucine-Rich Repeat Kinase 2 (LRRK2).

Ethyl-2-((8-cyano-3,5,9a-trimethyl-1-(4-oxo-4,5-dihydrothiazol-2-yl)-4-phenyl-3a,4,9,9a-tetrahydro-1H-pyrazolo[3,4-g]isoquinolin-7-yl)thio)acetate (5) was synthesized, and its structure was characterized by IR, MS, and NMR (1H and 13C) and verified by a single-crystal X-ray structure determination. Compound 5 adopts a "pincer" conformation. In the crystal, the hydrogen bonds of -H···O, C-H···O, and O-H···S form thick layers of molecules that are parallel to (101). The layers are linked by C-H···π(ring) interactions. The Hirshfeld surface analysis shows that intermolecular hydrogen bonding plays a more important role than both intramolecular hydrogen bonding and π···π stacking in the crystal. The intramolecular noncovalent interactions in 5 were studied by QTAIM, NCI, and DFT-NBO calculations. Based on structural activity relationship studies, leucine-rich repeat kinase 2 (LRRK2) was found to bind 5 and was further subjected to molecular docking studies, molecular dynamics, and ADMET analysis to probe potential drug candidacy.

A Multiomics, Molecular Atlas of Breast Cancer Survivors.

Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched healthy control cohort (N = 100) provides deep molecular phenotyping of breast cancer survivors. In this study, the BCS cohort had significantly higher polygenic risk scores for breast cancer than the control group. Carnitine and hexanoyl carnitine were significantly different. Several bile acid and fatty acid metabolites were significantly dissimilar, most notably the Omega-3 Index (O3I) (significantly lower in BCS). Proteomic and metagenomic analyses identified group and pathway differences, which warrant further investigation. The database built from this study contributes a wealth of data on breast cancer survivorship where there has been a paucity, affording the ability to identify patterns and novel insights that can drive new hypotheses and inform future research. Expansion of this database in the treatment-naïve, newly diagnosed, controlling for treatment confounders, and through the disease progression, can be leveraged to profile and contextualize breast cancer and breast cancer survivorship, potentially leading to the development of new strategies to combat this disease and improve the quality of life for its victims.

AARC Clinical Practice Guideline: Patient-Ventilator Assessment.

Given the important role of patient-ventilator assessments in ensuring the safety and efficacy of mechanical ventilation, a team of respiratory therapists and a librarian used Grading of Recommendations, Assessment, Development, and Evaluation methodology to make the following recommendations: (1) We recommend assessment of plateau pressure to ensure lung-protective ventilator settings (strong recommendation, high certainty); (2) We recommend an assessment of tidal volume (VT) to ensure lung-protective ventilation (4-8 mL/kg/predicted body weight) (strong recommendation, high certainty); (3) We recommend documenting VT as mL/kg predicted body weight (strong recommendation, high certainty); (4) We recommend an assessment of PEEP and auto-PEEP (strong recommendation, high certainty); (5) We suggest assessing driving pressure to prevent ventilator-induced injury (conditional recommendation, low certainty); (6) We suggest assessing FIO2 to ensure normoxemia (conditional recommendation, very low certainty); (7) We suggest telemonitoring to supplement direct bedside assessment in settings with limited resources (conditional recommendation, low certainty); (8) We suggest direct bedside assessment rather than telemonitoring when resources are adequate (conditional recommendation, low certainty); (9) We suggest assessing adequate humidification for patients receiving noninvasive ventilation (NIV) and invasive mechanical ventilation (conditional recommendation, very low certainty); (10) We suggest assessing the appropriateness of the humidification device during NIV and invasive mechanical ventilation (conditional recommendation, low certainty); (11) We recommend that the skin surrounding artificial airways and NIV interfaces be assessed (strong recommendation, high certainty); (12) We suggest assessing the dressing used for tracheostomy tubes and NIV interfaces (conditional recommendation, low certainty); (13) We recommend assessing the pressure inside the cuff of artificial airways using a manometer (strong recommendation, high certainty); (14) We recommend that continuous cuff pressure assessment should not be implemented to decrease the risk of ventilator-associated pneumonia (strong recommendation, high certainty); and (15) We suggest assessing the proper placement and securement of artificial airways (conditional recommendation, very low certainty).

Current laboratory testing practices for mismatch repair deficiency and microsatellite instability testing: A survey-based review of current laboratory practices.

OBJECTIVES: To describe mismatch repair (MMR) and microsatellite instability (MSI) testing practices in laboratories using the College of American Pathologists (CAP) MSI/MMR proficiency testing programs prior to the 2022 publication of the MSI/MMR practice guidelines copublished by CAP and the Association of Molecular Pathology (AMP). METHODS: Data from supplemental questionnaires provided with the 2020-B MSI/MMR programs to 542 laboratories across different practice settings were reviewed. Questionnaires contained 21 questions regarding the type of testing performed, specimen/tumor types used for testing, and clinical practices for checkpoint blockade therapy. RESULTS: Domestic laboratories test for MSI/MMR more often than international laboratories (P = .04) and academic hospitals/medical centers test more frequently than nonhospital sites/clinics (P = .03). The most commonly used testing modality is immunohistochemistry, followed by polymerase chain reaction, then next-generation sequencing. Most laboratories (72.6%; 347/478) reported awareness of the use of immune checkpoint inhibitor therapy for patients with high MSI or MMR-deficient results. CONCLUSIONS: The results demonstrate the state of MMR and MSI testing in laboratories prior to the publication of the CAP/AMP best practice guidelines, highlighting differences between various laboratory types. The findings indicate the importance of consensus guidelines and provide a baseline for comparison after their implementation.

Resistance Training using VAriable Resistance Suit (VARS) Increased Isometric and Isokinetic Muscle Strength.

While resistance training promotes muscle hypertrophy and strength, accessibility of equipment is a barrier. This study evaluated a wearable VAriable Resistance Suit (VARS) as a novel and alternative method to achieve muscle strength improvement. It was hypothesized that by providing adjustable, bi-directional and speed dependent resistance, VARS can target specific muscles to improve muscle strength via an accessible and portable device. Twelve untrained healthy male adults (22.08 ± 4.1 years old) participated in an 8-week long resistance training using VARS to strengthen four muscles (biceps brachii, triceps brachii, biceps femoris, rectus femoris) of their non-dominant arm and leg using VARS. The results showed significant improvements in the muscle strength measured by isokinetic dynamometer - 49.9±9.6% increase in isokinetic force and 30.6±7.6% increase in isometric force. Muscle size and body composition were also assessed using ultrasound imaging and bioelectrical impedance analysis, which did not show significant changes. The study demonstrates the efficacy and feasibility of VARS as a resistance training tool to achieve muscle strength improvement and its potential extension to clinical populations.

Associations between Computationally Derived Parent Emotional Sentiment Scores and Child ADHD and ODD Over Time.

Family emotional climate is often assessed as expressed emotion (EE) using the five-minute speech sample (FMSS). Parent EE is related to child externalizing behavior, but the relationship with ADHD apart from externalizing is unclear. We report the largest ADHD-non-ADHD study of EE to date, introduce computational scoring of the FMSS to assay parent negative sentiment, and use this to evaluate reciprocal parent-child effects over time in ADHD while considering comorbid ODD. Parents of 810 children (nADHD = 509), aged 7-13 years old, completed the FMSS at three points. The FMSS was expert-coded for EE-Criticism at Time 1 and Time 2, negative sentiment was scored at all three time points. Sentiment and EE-Criticism were moderately correlated (r =.39, p <.001, 95% CI [0.32, 0.46]), and each was similarly correlated with baseline ADHD symptoms (r's range 0.31-0.33, p <.001) and ODD symptoms (r(ODD-EE) = 0.35, p <.001; r(ODD-sentiment = 0.28, p <.001). A longitudinal, cross-lagged panel model revealed that increases over time in parental negative sentiment scores led to increased ODD symptoms. Parent sex (namely fathers, but not mothers) showed an interaction effect of sentiment with ADHD. ADHD and ODD are independently and jointly associated with parental EE-Criticism and negative sentiment assessed by the FMSS cross-sectionally. A recursive effects model is supported for ODD, but for ADHD effects depend on which parent is assessed. For fathers, ADHD was related to negative sentiment in complex manners but for mothers, negative sentiment was related primarily to ODD.

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

CONTEXT.­: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based models share some features of conventional laboratory testing methods. Accreditation requirements that specifically address clinical laboratories' use of ML remain in the early stages of development. OBJECTIVE.­: To identify relevant CAP accreditation requirements that may be applied to the clinical adoption of ML-based molecular oncology assays, and to provide examples of current and emerging ML applications in molecular oncology testing. DESIGN.­: CAP accreditation checklists related to molecular pathology and general laboratory practices (Molecular Pathology, All Common and Laboratory General) were reviewed. Examples of checklist requirements that are generally applicable to validation, revalidation, quality management, infrastructure, and analytical procedures of ML-based molecular oncology assays were summarized. Instances of ML use in molecular oncology testing were assessed from literature review. RESULTS.­: Components of the general CAP accreditation framework that exist for traditional molecular oncology assay validation and maintenance are also relevant for implementing ML-based tests in a clinical laboratory. Current and emerging applications of ML in molecular oncology testing include DNA methylation profiling for central nervous system tumor classification, variant calling, microsatellite instability testing, mutational signature analysis, and variant prediction from histopathology images. CONCLUSIONS.­: Currently, much of the ML activity in molecular oncology is within early clinical implementation. Despite specific considerations that apply to the adoption of ML-based methods, existing CAP requirements can serve as general guidelines for the clinical implementation of ML-based assays in molecular oncology testing.

Synthesis, crystal structure and Hirshfeld surface analysis of 1-[3-(2-oxo-3-phenyl-1,2-di-hydro-quinoxalin-1-yl)prop-yl]-3-phenyl-1,2-di-hydro-quinoxalin-2-one.

In the title compound, C31H24N4O2, the di-hydro-quinoxaline units are both essentially planar with the dihedral angle between their mean planes being 64.82 (4)°. The attached phenyl rings differ significantly in their rotational orientations with respect to the di-hydro-quinoxaline planes. In the crystal, one set of C-H⋯O hydrogen bonds form chains along the b-axis direction, which are connected in pairs by a second set of C-H⋯O hydrogen bonds. Two sets of π-stacking inter-actions and C-H⋯π(ring) inter-actions join the double chains into the final three-dimensional structure.

Ethyl 2-[(2-oxo-2H-chromen-6-yl)-oxy]acetate.

Ethyl 2-[(2-oxo-2H-chromen-6-yl)-oxy]acetate, C13H12O5, a member of the pharmacologically important class of coumarins, crystallizes in the monoclinic C2/c space group in the form of sheets, within which mol-ecules are related by inversion centers and 21 axes. Multiple C-H⋯O weak hydrogen-bonding inter-actions reinforce this pattern. The planes of these sheets are oriented in the approximate direction of the ac face diagonal. Inter-sheet inter-actions are a combination of coumarin system π-π stacking and additional C-H⋯O weak hydrogen bonds between ethyl acet-oxy groups.