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A functional clock in only two dorsal clock neurons is sufficient to restore the basal circadian activity pattern of Drosophila melanogaster
Full text linkCircadian clocks form complex networks to orchestrate the behavior and physiology of animals. Elucidating the organization of these clock networks is critical to understanding how circadian clocks achieve robust timing. Clock neurons have been best characterized in the model organis
In Our Words: A Storytelling Series
No full texthttps://digitalcommons.wustl.edu/homepage_slideshow/1002/thumbnail.jp
Glofitamab in relapsed/refractory mantle cell lymphoma: Results from a phase I/II study
Full text linkPURPOSE: Patients with relapsed/refractory (R/R) mantle cell lymphoma (MCL) have a poor prognosis. The phase I/II NP30179 study (ClinicalTrials.gov identifier: NCT03075696) evaluated glofitamab monotherapy in patients with R/R B-cell lymphomas, with obinutuzumab pretreatment (Gpt) to mitigate the risk of cytokine release syndrome (CRS) with glofitamab. We present data for patients with R/R MCL.
METHODS: Eligible patients with R/R MCL (at least one previous therapy) received Gpt (1,000 or 2,000 mg) 7 days before the first glofitamab dose (single dose or split over 2 days if required). Glofitamab step-up dosing was administered once a day on days 8 (2.5 mg) and 15 (10 mg) of cycle 1, with a target dose of 16 or 30 mg once every 3 weeks from cycle 2 day 1 onward, for 12 cycles. Efficacy end points included investigator-assessed complete response (CR) rate, overall response rate (ORR), and duration of CR.
RESULTS: Of 61 enrolled patients, 60 were evaluable for safety and efficacy. Patients had received a median of two previous therapies (range, 1-5). CR rate and ORR were 78.3% (95% CI, 65.8 to 87.9) and 85.0% (95% CI, 73.4 to 92.9), respectively. In patients who had received previous treatment with a Bruton tyrosine kinase inhibitor (n = 31), CR rate was 71.0% (95% CI, 52.0 to 85.8) and ORR was 74.2% (95% CI, 55.4 to 88.1). CRS after glofitamab administration occurred in 70.0% of patients, with a lower incidence in the 2,000 mg (63.6% [grade ≥2, 22.7%]) versus 1,000 mg (87.5%; grade ≥2, 62.5%) Gpt cohort. Four adverse events led to glofitamab withdrawal (all infections).
CONCLUSION: Fixed-duration glofitamab induced high CR rates in heavily pretreated patients with R/R MCL; the safety profile was manageable with appropriate support
Measuring stigma in pediatric oncology: A cross-sectional analysis of three global sites
Full text linkPURPOSE: Stigma contributes to fear and shame, resulting in delays in care-seeking behavior among individuals with cancer. As a social construct, stigma is affected by language, religion, culture, and local norms. This study explored pediatric cancer stigma at the time of diagnosis across diverse settings through the adaptation of two stigma measures.
METHODS: This study was conducted with adolescents and caregivers of children with osteosarcoma and retinoblastoma at three centers in Jordan, Guatemala, and Zimbabwe. The Stigma-related Social Problems (SSP) and the eight-item Stigma Scale for Chronic Illness (SSCI-8) measures were translated into Arabic, Spanish, and Shona and contextually adapted for use with adolescents and caregiver proxies. Adapted measures were pilot-tested and iteratively revised.
RESULTS: Extensive adaptations were made to both measures to make them relevant to the local pediatric contexts. The final measures were used in nine patients and 28 caregivers. The exploratory analysis found that domain-specific and overall scale scores for both measures indicate a higher level of stigma than those found in previous studies (SSP: patient [51.23], caregiver [40.74]; SSCI-8: patient [50.41], caregiver [49.78]). Paired, patient-caregiver proxy responses were analyzed, with disagreement between the pairs for both scales.
CONCLUSION: Adapted measures detected high levels of stigma among patients with pediatric cancer and their caregiver proxies and demonstrated a lack of concordance in the reports. This suggests the importance of studying stigma in this population and the need to ask patients about their stigma without using proxy measures. The required adaptations suggest a need for stigma measures developed specifically for pediatric cancer
Increasing Awareness and Use of the Emergency Manual in the Operating Room
Full text linkBackground and Review of Literature: Operating room emergency manuals function as cognitive aids, facilitating evidence-based treatment, error reduction, and better patient outcomes in diverse patient care and equipment-related emergencies. A concerning amalgam of stress, infrequent occurrence, and lack of standardized response hinders anesthesia providers’ practical experience during unexpected crises, potentially leading to errors and safety concerns.
Purpose: The purpose is to increase anesthesia providers’ utilization of the digital Stanford Emergency Manual (SEM).
Methods: All anesthesia providers at the project sites were invited to complete pre-intervention and post-intervention surveys throughout the project timeline. Surveys assessed participants’ awareness of the digital SEM and their perceptions of familiarity, accessibility, and usefulness.
Implementation Plan/Procedure: Educational materials and surveys were disseminated and conducted electronically either in-person, via email, or via QR codes on posted flyers. First, a pre-intervention survey was conducted. Second, the educational and reference aid interventions were implemented and distributed. Third, two post-intervention surveys were conducted over a twelve-week period following the conclusion of the interventions.
Implications/Conclusion: Anesthesia providers’ familiarity with, awareness of, and accessibility to the digital SEM may enhance its use in practice, which can also increase safety of team members and patient care delivery as well as reduce healthcare costs. This project may also inform the needs regarding education and training of anesthesia providers\u27 use of the SEM
MethylGrapher: Genome-graph-based processing of DNA methylation data from whole genome bisulfite sequencing
Full text linkGenome graphs, including the recently released draft human pangenome graph, can represent the breadth of genetic diversity and thus transcend the limits of traditional linear reference genomes. However, there are no genome-graph-compatible tools for analyzing whole genome bisulfite sequencing (WGBS) data. To close this gap, we introduce methylGrapher, a tool tailored for accurate DNA methylation analysis by mapping WGBS data to a genome graph. Notably, methylGrapher can reconstruct methylation patterns along haplotype paths precisely and efficiently. To demonstrate the utility of methylGrapher, we analyzed the WGBS data derived from five individuals whose genomes were included in the first Human Pangenome draft as well as WGBS data from ENCODE (EN-TEx). Along with standard performance benchmarking, we show that methylGrapher fully recapitulates DNA methylation patterns defined by classic linear genome analysis approaches. Importantly, methylGrapher captures a substantial number of CpG sites that are missed by linear methods, and improves overall genome coverage while reducing alignment reference bias. Thus, methylGrapher is a first step toward unlocking the full potential of Human Pangenome graphs in genomic DNA methylation analysis
Evaluating dimensionality reduction of comorbidities for predictive modeling in individuals with Neurofibromatosis type 1
Full text linkOBJECTIVE: Dimensionality reduction techniques aim to enhance the performance of machine learning (ML) models by reducing noise and mitigating overfitting. We sought to compare the effect of different dimensionality reduction methods for comorbidity features extracted from electronic health records (EHRs) on the performance of ML models for predicting the development of various sub-phenotypes in children with Neurofibromatosis type 1 (NF1).
MATERIALS AND METHODS: EHR-derived data from pediatric subjects with a confirmed clinical diagnosis of NF1 were used to create 10 unique comorbidities code-derived feature sets by incorporating dimensionality reduction techniques using raw International Classification of Diseases codes, Clinical Classifications Software Refined, and Phecode mapping schemes. We compared the performance of logistic regression, XGBoost, and random forest models utilizing each feature set.
RESULTS: XGBoost-based predictive models were most successful at predicting NF1 sub-phenotypes. Overall, features based on domain knowledge-informed mapping schema performed better than unsupervised feature reduction methods. High-level features exhibited the worst performance across models and outcomes, suggesting excessive information loss with over-aggregation of features.
DISCUSSION: Model performance is significantly impacted by dimensionality reduction techniques and varies by specific ML algorithm and outcome being predicted. Automated methods using existing knowledge and ontology databases can effectively aggregate features extracted from EHRs.
CONCLUSION: Dimensionality reduction through feature aggregation can enhance the performance of ML models, particularly in high-dimensional datasets with small sample sizes, commonly found in EHRs health applications. However, if not carefully optimized, it can lead to information loss and data oversimplification, potentially adversely affecting model performance
Ultra high density imaging arrays in diffuse optical tomography for human brain mapping improve image quality and decoding performance
Full text linkFunctional magnetic resonance imaging (fMRI) has dramatically advanced non-invasive human brain mapping and decoding. Functional near-infrared spectroscopy (fNIRS) and high-density diffuse optical tomography (HD-DOT) non-invasively measure blood oxygen fluctuations related to brain activity, like fMRI, at the brain surface, using more-lightweight equipment that circumvents ergonomic and logistical limitations of fMRI. HD-DOT grids have smaller inter-optode spacing (~ 13 mm) than sparse fNIRS (~ 30 mm) and therefore provide higher image quality, with spatial resolution ~ 1/2 that of fMRI, when using the several source-detector distances (13-40 mm) afforded by the HD-DOT grid. Herein, simulations indicated reducing inter-optode spacing to 6.5 mm, creating a higher-density grid with more source-detector distances, would further improve image quality and noise-resolution tradeoff, with diminishing returns below 6.5 mm. We then constructed an ultra-high-density DOT system (6.5-mm spacing) with 140 dB dynamic range that imaged stimulus-evoked activations with 30-50% higher spatial resolution and repeatable multi-focal activity with excellent agreement with participant-matched fMRI. Further, this system decoded visual stimulus position with 19-35% lower error than previous HD-DOT, throughout occipital cortex
SLC35A2 gene product modulates paramyxovirus fusion events during infection
Full text linkParamyxoviruses are significant human and animal pathogens that include mumps virus (MuV), Newcastle disease virus (NDV) and the murine parainfluenza virus Sendai (SeV). Despite their importance, few host factors implicated in paramyxovirus infection are known. Using a recombinant SeV expressing destabilized eGFP (rSeVCdseGFP) in a loss-of-function CRISPR screen, we identified the CMP-sialic acid transporter (CST) gene SLC35A1 and the UDP-galactose transporter (UGT) gene SLC35A2 as essential for paramyxovirus infection. As expected, SLC35A1 knockout (KO) cells showed drastic reduction in infections with SeV, NDV and MuV due to the lack of cell surface sialic acids receptors. However, SLC35A2 KO cells revealed unknown critical roles for this factor in virus-cell and cell-to-cell fusion events for the different paramyxoviruses. While UGT was essential for virus-cell fusion during SeV entry to the cell, it was not required for NDV or MuV entry. Importantly, UGT promoted the formation of syncytia during MuV infection, suggesting a role in cell-to-cell virus spread. Our findings demonstrate that paramyxoviruses can bind to or enter A549 cells in the absence of canonical galactose-bound sialic-acid decorations and show that UGT facilitates paramyxovirus fusion processes involved in entry and spread
Robust cluster prediction across data types validates association of sex and therapy response in GBM
Full text linkBACKGROUND: Previous studies have described sex-specific patient subtyping in glioblastoma. The cluster labels associated with these legacy data were used to train a predictive model capable of recapitulating this clustering in contemporary contexts.
METHODS: We used robust ensemble machine learning to train a model using gene microarray data to perform multi-platform predictions including RNA-seq and potentially scRNA-seq.
RESULTS: The engineered feature set was composed of many previously reported genes that are associated with patient prognosis. Interestingly, these well-known genes formed a predictive signature only for female patients, and the application of the predictive signature to male patients produced unexpected results.
CONCLUSIONS: This work demonstrates how annotated legacy data can be used to build robust predictive models capable of multi-target predictions across multiple platforms