PTSD and lower respiratory symptoms: A systematic review of longitudinal associations in early 9/11 World Trade Center responders.

OBJECTIVE: The objective of this systematic review is to examine longitudinal associations between post-traumatic stress disorder (PTSD) and lower respiratory symptoms (LRS) specifically among responders present at the World Trade Center (WTC) site on September 11, 2001 (9/11). This group, which we refer to as "9/11 early responders," appears to have particularly high rates of both mental and physical illness relative to other 9/11-exposed populations. METHODS: We performed a systematic literature review to examine associations between PTSD and LRS among 9/11 early responders in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. After a structured search of Pubmed and the Fire Department of New York (FDNY) WTC bibliography for relevant articles, we identified 4 articles commenting on associations between PTSD and LRS in this population; all 4 passed quality review and were included in our primary analysis. 10 other articles we found in our research discussed rates of PTSD and LRS, but not associations between them, in the population in question; we commented on these in a secondary analysis. RESULTS: The data demonstrate that there are significant associations between PTSD and LRS among 9/11 early responders. The data also suggest that both of these phenomena are more prevalent among 9/11 early responders relative to other 9/11-exposed populations. CONCLUSIONS: These findings are relevant for optimizing care for the population in question, as well as for other survivors of past and future disasters with both psychiatric and medical sequelae.

Greater Social Functioning Associated With Lower Depressive Symptomatology Among Black Belt African Americans Enrolled in the Southeastern Collaboration to Improve Blood Pressure Control Study.

Objective: In many populations, higher social functioning is associated with lower depressive symptomatology, which in turn is associated with improved cardiovascular health. This study aimed to establish an association between social functioning and depressive symptomatology, which has not yet been demonstrated in the African American Black Belt. This would be an important finding in a region with high cardiovascular morbidity.Methods: This observational study used baseline data from 1,225 African American Black Belt residents with uncontrolled hypertension in the Southeastern Collaboration to Improve Blood Pressure Control (SEC) trial. Three Patient Reported Outcomes Measurement Information System (PROMIS) questionnaires-the emotional support, instrumental support, and social isolation questionnaires-and marital status assessed social functioning. The 8-item Patient Health Questionnaire assessed depressive symptomatology. Multivariable logistic regression models examined associations between social functioning and depressive symptomatology separately and then simultaneously. Data were collected from May 2017 to April 2021.Results: Social functioning was higher than US-reported averages, and the prevalence of moderate to severe depressive symptomatology was low (20.8%) among primary care populations. In a separate model, lower emotional support, lower instrumental support, and increased social isolation were significantly associated with greater depressive symptomatology (odds ratio [OR] = 1.56, 95% CI, 1.20-2.02; OR = 1.33, 95% CI, 1.01-1.77; and OR = 2.39, 95% CI, 1.81-3.16, respectively). In a simultaneous model, only increased perceived social isolation remained significantly associated with greater depressive symptomatology (OR = 2.24, 95% CI, 1.67-3.00).Conclusions: Greater social functioning is associated with lower depressive symptom burden in the Black Belt region. Future research into the directionality of this association could assist in the development of interventions to improve regional mental and cardiovascular health.Trial Registration: ClinicalTrials.gov identifier: NCT02866669.

A comparison of attentional neural network architectures for modeling with electronic medical records.

OBJECTIVE: Attention networks learn an intelligent weighted averaging mechanism over a series of entities, providing increases to both performance and interpretability. In this article, we propose a novel time-aware transformer-based network and compare it to another leading model with similar characteristics. We also decompose model performance along several critical axes and examine which features contribute most to our model's performance. MATERIALS AND METHODS: Using data sets representing patient records obtained between 2017 and 2019 by the Kaiser Permanente Mid-Atlantic States medical system, we construct four attentional models with varying levels of complexity on two targets (patient mortality and hospitalization). We examine how incorporating transfer learning and demographic features contribute to model success. We also test the performance of a model proposed in recent medical modeling literature. We compare these models with out-of-sample data using the area under the receiver-operator characteristic (AUROC) curve and average precision as measures of performance. We also analyze the attentional weights assigned by these models to patient diagnoses. RESULTS: We found that our model significantly outperformed the alternative on a mortality prediction task (91.96% AUROC against 73.82% AUROC). Our model also outperformed on the hospitalization task, although the models were significantly more competitive in that space (82.41% AUROC against 80.33% AUROC). Furthermore, we found that demographic features and transfer learning features which are frequently omitted from new models proposed in the EMR modeling space contributed significantly to the success of our model. DISCUSSION: We proposed an original construction of deep learning electronic medical record models which achieved very strong performance. We found that our unique model construction outperformed on several tasks in comparison to a leading literature alternative, even when input data was held constant between them. We obtained further improvements by incorporating several methods that are frequently overlooked in new model proposals, suggesting that it will be useful to explore these options further in the future.

Exploiting hierarchy in medical concept embedding.

OBJECTIVE: To construct and publicly release a set of medical concept embeddings for codes following the ICD-10 coding standard which explicitly incorporate hierarchical information from medical codes into the embedding formulation. MATERIALS AND METHODS: We trained concept embeddings using several new extensions to the Word2Vec algorithm using a dataset of approximately 600,000 patients from a major integrated healthcare organization in the Mid-Atlantic US. Our concept embeddings included additional entities to account for the medical categories assigned to codes by the Clinical Classification Software Revised (CCSR) dataset. We compare these results to sets of publicly released pretrained embeddings and alternative training methodologies. RESULTS: We found that Word2Vec models which included hierarchical data outperformed ordinary Word2Vec alternatives on tasks which compared naïve clusters to canonical ones provided by CCSR. Our Skip-Gram model with both codes and categories achieved 61.4% normalized mutual information with canonical labels in comparison to 57.5% with traditional Skip-Gram. In models operating on two different outcomes, we found that including hierarchical embedding data improved classification performance 96.2% of the time. When controlling for all other variables, we found that co-training embeddings improved classification performance 66.7% of the time. We found that all models outperformed our competitive benchmarks. DISCUSSION: We found significant evidence that our proposed algorithms can express the hierarchical structure of medical codes more fully than ordinary Word2Vec models, and that this improvement carries forward into classification tasks. As part of this publication, we have released several sets of pretrained medical concept embeddings using the ICD-10 standard which significantly outperform other well-known pretrained vectors on our tested outcomes.

Light Absorptive Properties of Articular Cartilage, ECM Molecules, Synovial Fluid, and Photoinitiators as Potential Barriers to Light-Initiated Polymer Scaffolding Procedures.

OBJECTIVE: Many in vivo procedures to repair chondral defects use ultraviolet (UV)-photoinitiated in situ polymerization within the cartilage matrix. Chemical species that absorb UV light might reduce the effectiveness of these procedures by acting as light absorption barriers. This study evaluated whether any of the individual native biochemical components in cartilage and synovial fluid interfered with the absorption of light by common scaffolding photosensitizers. MATERIALS: UV-visible spectroscopy was performed on each major component of cartilage in solution, on bovine synovial fluid, and on four photosensitizers, riboflavin, Irgacure 2959, quinine, and riboflavin-5'-phosphate. Molar extinction and absorption coefficients were calculated at wavelengths of maximum absorbance and 365 nm. Intact articular cartilage was also examined. RESULTS: The individual major biochemical components of cartilage, Irgacure 2959, and quinine did not exhibit a significant absorption at 365 nm. Riboflavin and riboflavin-5'-phosphate were more effectual light absorbers at 365 nm, compared with the individual native species. Intact cartilage absorbed a significantly greater amount of UV light in comparison with the native species. CONCLUSION: Our results indicate that none of the individual native species in cartilage will interfere with the absorption of UV light at 365 nm by these commonly used photoinitiators. Intact cartilage slices exhibited significant light absorption at 365 nm, while also having distinct absorbance peaks at wavelengths less than 300 nm. Determining the UV absorptive properties of the biomolecules native to articular cartilage and synovial fluid will aid in optimizing scaffolding procedures to ensure sufficient scaffold polymerization at a minimum UV intensity.

Thermophilic Proteins as Versatile Scaffolds for Protein Engineering.

Literature from the past two decades has outlined the existence of a trade-off between protein stability and function. This trade-off creates a unique challenge for protein engineers who seek to introduce new functionality to proteins. These engineers must carefully balance the mutation-mediated creation and/or optimization of function with the destabilizing effect of those mutations. Subsequent research has shown that protein stability is positively correlated with "evolvability" or the ability to support mutations which bestow new functionality on the protein. Since the ultimate goal of protein engineering is to create and/or optimize a protein's function, highly stable proteins are preferred as potential scaffolds for protein engineering. This review focuses on the application potential for thermophilic proteins as scaffolds for protein engineering. The relatively high inherent thermostability of these proteins grants them a great deal of mutational robustness, making them promising scaffolds for various protein engineering applications. Comparative studies on the evolvability of thermophilic and mesophilic proteins have strongly supported the argument that thermophilic proteins are more evolvable than mesophilic proteins. These findings indicate that thermophilic proteins may represent the scaffold of choice for protein engineering in the future.

Photocrosslinked tyramine-substituted hyaluronate hydrogels with tunable mechanical properties improve immediate tissue-hydrogel interfacial strength in articular cartilage.

Articular cartilage lacks the ability to self-repair and a permanent solution for cartilage repair remains elusive. Hydrogel implantation is a promising technique for cartilage repair; however for the technique to be successful hydrogels must interface with the surrounding tissue. The objective of this study was to investigate the tunability of mechanical properties in a hydrogel system using a phenol-substituted polymer, tyramine-substituted hyaluronate (TA-HA), and to determine if the hydrogels could form an interface with cartilage. We hypothesized that tyramine moieties on hyaluronate could crosslink to aromatic amino acids in the cartilage extracellular matrix. Ultraviolet (UV) light and a riboflavin photosensitizer were used to create a hydrogel by tyramine self-crosslinking. The gel mechanical properties were tuned by varying riboflavin concentration, TA-HA concentration, and UV exposure time. Hydrogels formed with a minimum of 2.5 min of UV exposure. The compressive modulus varied from 5 to 16 kPa. Fluorescence spectroscopy analysis found differences in dityramine content. Cyanine-3 labelled tyramide reactivity at the surface of cartilage was dependent on the presence of riboflavin and UV exposure time. Hydrogels fabricated within articular cartilage defects had increasing peak interfacial shear stress at the cartilage-hydrogel interface with increasing UV exposure time, reaching a maximum shear stress 3.5× greater than a press-fit control. Our results found that phenol-substituted polymer/riboflavin systems can be used to fabricate hydrogels with tunable mechanical properties and can interface with the surface tissue, such as articular cartilage.