Wavelet analysis of DNA walks

A wavelet transform of the DNA "walk" constructed from a genomic sequence offers a direct visualization of short and long-range patterns in nucleotide sequences. We study sequences that encode diverse biological functions, taken from a variety of genomes. Pattern irregularities in the transform are frequently associated with sequences of biological interest. Exonic regions, for example, visualize differently under wavelet analysis than introns, and ribosomal RNA regions display distinct universal signatures. DNA walk wavelet analysis can provide a sensitive and rapid assessment of the putative biological significance of genomic DNA

Patterns of care partner communication for persons living with dementia in the emergency department

Abstract Background: Nearly half of all persons living with dementia (PLwD) will visit the emergency department (ED) in any given year and ED visits by PLwD are associated with short-term adverse outcomes. Care partner engagement is critical in the care of PLwD, but little is known about their patterns of communication with ED clinicians. Methods: We performed a retrospective electronic health record (EHR) review of a random sampling of patients ≥ 65 years with a historical diagnosis code of dementia who visited an ED within a large regional health network between 1/2014 and 1/2022. ED notes within the EHRs were coded for documentation of care partner communication and presence of a care partner in the ED. Logistic regression was used to identify patient characteristics associated with the composite outcome of either care partner communication or care partner presence in the ED. Results: A total of 460 patients were included. The median age was 83.0 years, 59.3% were female, 11.3% were Black, and 7.6% Hispanic. A care partner was documented in the ED for 22.4% of the visits and care partner communication documented for 43.9% of visits. 54.8% of patients had no documentation of care partner communication nor evidence of a care partner at the bedside. In multivariate logistic regression, increasing age (OR, (95% CI): 1.06 (1.04-1.09)), altered mental status (OR: 2.26 (1.01-5.05)), and weakness (OR: 3.38 (1.49-7.65)) significantly increased the probability of having care partner communication documented or a care partner at the bedside. Conclusions: More than half of PLwD in our sample did not have clinician documentation of communication with a care partner or a care partner in the ED. Further studies are needed to use these insights to improve communication with care partners of PLwD in the ED

Cluster Analysis of Primary Care Physician Phenotypes for Electronic Health Record Use: Retrospective Cohort Study

BackgroundElectronic health records (EHRs) have become ubiquitous in US office-based physician practices. However, the different ways in which users engage with EHRs remain poorly characterized. ObjectiveThe aim of this study is to explore EHR use phenotypes among ambulatory care physicians. MethodsIn this retrospective cohort analysis, we applied affinity propagation, an unsupervised clustering machine learning technique, to identify EHR user types among primary care physicians. ResultsWe identified 4 distinct phenotype clusters generalized across internal medicine, family medicine, and pediatrics specialties. Total EHR use varied for physicians in 2 clusters with above-average ratios of work outside of scheduled hours. This finding suggested that one cluster of physicians may have worked outside of scheduled hours out of necessity, whereas the other preferred ad hoc work hours. The two remaining clusters represented physicians with below-average EHR time and physicians who spend the largest proportion of their EHR time on documentation. ConclusionsThese findings demonstrate the utility of cluster analysis for exploring EHR use phenotypes and may offer opportunities for interventions to improve interface design to better support users’ needs

Designed Phosphoprotein Recognition in <i>Escherichia coli</i>

Protein phosphorylation is a central biological mechanism for cellular adaptation to environmental changes. Dysregulation of phosphorylation signaling is implicated in a wide variety of diseases. Thus, the ability to detect and quantify protein phosphorylation is highly desirable for both diagnostic and research applications. Here we present a general strategy for detecting phosphopeptide–protein interactions in <i>Escherichia coli</i>. We first redesign a model tetratricopeptide repeat (TPR) protein to recognize phosphoserine in a sequence-specific fashion and characterize the interaction with its target phosphopeptide <i>in vitro</i>. We then combine <i>in vivo</i> site-specific incorporation of phosphoserine with split mCherry assembly to observe the designed phosphopeptide–protein interaction specificity in <i>E. coli</i>. This <i>in vivo</i> strategy for detecting and characterizing phosphopeptide–protein interactions has numerous potential applications for the study of natural interactions and the design of novel ones

Designed Phosphoprotein Recognition in <i>Escherichia coli</i>

Protein phosphorylation is a central biological mechanism for cellular adaptation to environmental changes. Dysregulation of phosphorylation signaling is implicated in a wide variety of diseases. Thus, the ability to detect and quantify protein phosphorylation is highly desirable for both diagnostic and research applications. Here we present a general strategy for detecting phosphopeptide–protein interactions in <i>Escherichia coli</i>. We first redesign a model tetratricopeptide repeat (TPR) protein to recognize phosphoserine in a sequence-specific fashion and characterize the interaction with its target phosphopeptide <i>in vitro</i>. We then combine <i>in vivo</i> site-specific incorporation of phosphoserine with split mCherry assembly to observe the designed phosphopeptide–protein interaction specificity in <i>E. coli</i>. This <i>in vivo</i> strategy for detecting and characterizing phosphopeptide–protein interactions has numerous potential applications for the study of natural interactions and the design of novel ones

Designed Phosphoprotein Recognition in <i>Escherichia coli</i>

Protein phosphorylation is a central biological mechanism for cellular adaptation to environmental changes. Dysregulation of phosphorylation signaling is implicated in a wide variety of diseases. Thus, the ability to detect and quantify protein phosphorylation is highly desirable for both diagnostic and research applications. Here we present a general strategy for detecting phosphopeptide–protein interactions in <i>Escherichia coli</i>. We first redesign a model tetratricopeptide repeat (TPR) protein to recognize phosphoserine in a sequence-specific fashion and characterize the interaction with its target phosphopeptide <i>in vitro</i>. We then combine <i>in vivo</i> site-specific incorporation of phosphoserine with split mCherry assembly to observe the designed phosphopeptide–protein interaction specificity in <i>E. coli</i>. This <i>in vivo</i> strategy for detecting and characterizing phosphopeptide–protein interactions has numerous potential applications for the study of natural interactions and the design of novel ones