A Signal Processing Method to Explore Similarity in Protein Flexibility

Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM) provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods

Antilymphoid antibody preconditioning and tacrolimus monotherapy for pediatric kidney transplantation

Objective: Heavy post-transplant immunosuppression may contribute to long-term immunosuppression dependence by subverting tolerogenic mechanisms; thus, we sought to determine if this undesirable consequence could be mitigated by pretransplant lymphoid depletion and minimalistic post-transplant monotherapy. Study design: Lymphoid depletion in 17 unselected pediatric recipients of live (n = 14) or deceased donor kidneys (n = 3) was accomplished with antithymocyte globulin (ATG) (n = 8) or alemtuzumab (n = 9). Tacrolimus was begun post-transplantation with subsequent lengthening of intervals between doses (spaced weaning). Maintenance immunosuppression, morbidity, graft function, and patient/graft survival were collated. Results: Steroids were added temporarily to treat rejection in two patients (both ATG subgroup) or to treat hemolytic anemia in two others. After 16 to 31 months (mean 22), patient and graft survival was 100% and 94%, respectively. The only graft loss was in a nonweaned noncompliant recipient. In the other 16, serum creatinine was 0.85 ± 0.35 mg/dL and creatinine clearance was 90.8 ± 22.1 mL/1.73 m2. All 16 patients are on monotherapy (15 tacrolimus, one sirolimus), and 14 receive every other day or 3 times per week doses. There were no wound or other infections. Two patients developed insulin-dependent diabetes. Conclusion: The strategy of lymphoid depletion and minimum post-transplant immunosuppression appears safe and effective for pediatric kidney recipients. © 2006 Elsevier Inc. All rights reserved

Identifying Caregiver Availability Using Medical Notes With Rule-Based Natural Language Processing: Retrospective Cohort Study

BackgroundIdentifying caregiver availability, particularly for patients with dementia or those with a disability, is critical to informing the appropriate care planning by the health systems, hospitals, and providers. This information is not readily available, and there is a paucity of pragmatic approaches to automatically identifying caregiver availability and type. ObjectiveOur main objective was to use medical notes to assess caregiver availability and type for hospitalized patients with dementia. Our second objective was to identify whether the patient lived at home or resided at an institution. MethodsIn this retrospective cohort study, we used 2016-2019 telephone-encounter medical notes from a single institution to develop a rule-based natural language processing (NLP) algorithm to identify the patient’s caregiver availability and place of residence. Using note-level data, we compared the results of the NLP algorithm with human-conducted chart abstraction for both training (749/976, 77%) and test sets (227/976, 23%) for a total of 223 adults aged 65 years and older diagnosed with dementia. Our outcomes included determining whether the patients (1) reside at home or in an institution, (2) have a formal caregiver, and (3) have an informal caregiver. ResultsTest set results indicated that our NLP algorithm had high level of accuracy and reliability for identifying whether patients had an informal caregiver (F1=0.94, accuracy=0.95, sensitivity=0.97, and specificity=0.93), but was relatively less able to identify whether the patient lived at an institution (F1=0.64, accuracy=0.90, sensitivity=0.51, and specificity=0.98). The most common explanations for NLP misclassifications across all categories were (1) incomplete or misspelled facility names; (2) past, uncertain, or undecided status; (3) uncommon abbreviations; and (4) irregular use of templates. ConclusionsThis innovative work was the first to use medical notes to pragmatically determine caregiver availability. Our NLP algorithm identified whether hospitalized patients with dementia have a formal or informal caregiver and, to a lesser extent, whether they lived at home or in an institutional setting. There is merit in using NLP to identify caregivers. This study serves as a proof of concept. Future work can use other approaches and further identify caregivers and the extent of their availability