Peptides are emerging as a new class of biomaterials due to their unique chemical, physical, and biological properties. The development of peptide-based biomaterials is driven by the convergence of protein engineering and macromolecular self-assembly. This review covers the basic principles, applications, and prospects of peptide-based biomaterials. We focus on both chemically synthesized and genetically encoded peptides, including poly-amino acids, elastin-like polypeptides, silk-like polymers and other biopolymers based on repetitive peptide motifs. Applications of these engineered biomolecules in protein purification, controlled drug delivery, tissue engineering, and biosurface engineering are discussed.

Hematopoietic cells of various lineages are organized in distinct cellular architectures in the bone marrow hematopoietic compartment (BMHC). The homogeneous Kroghian model, which deals only with a single cell type, may not be sufficient to accurately describe oxygen transfer in the BMHC. Thus, for cellular architectures of physiological significance, more complex biophysical-transport models were considered and compared against simulations using the homogeneous Kroghian model. The effects of the heterogeneity of model parameters on the oxygen tension (pO(2)) distribution were examined using the multilayer Kroghian model. We have also developed two-dimensional Kroghian models to simulate several cellular architectures in which a cell cluster (erythroid cluster) or an individual cell (megakaryocyte or adipocyte) is located in the BMHC predominantly occupied by mature granulocytes. pO(2) distributions in colony-type cellular arrangements (erythroblastic islets, granulopoietic loci, and lymphocytic nodules) in the BMHC were also evaluated by modifying the multilayer Kroghian model. The simulated results indicate that most hematopoietic progenitors experience low pO(2) values, which agrees with the finding that low pO(2) promotes the expansion of various hematopoietic progenitors. These results suggest that the most primitive stem cells, which are located even further away from BM sinuses, are likely located in a very low pO(2) environment.

Human bone marrow (BM) is a tissue of complex architectural organization, which includes granulopoietic loci, erythroblastic islets, and lymphocytic nodules. Oxygen tension (pO(2)) is an important determinant of hematopoietic stem and progenitor cell proliferation and differentiation. Thus, understanding the impact of the BM architectural organization on pO(2) levels in extravascular hematopoietic tissue is an important biophysical problem. However, currently it is impossible to measure pO(2) levels and their spatial variations in the BM. Homogeneous Kroghian models were used to estimate pO(2) distribution in the BM hematopoietic compartment (BMHC) and to conservatively simulate pO(2)-limited cellular architectures. Based on biophysical data of hematopoietic cells and characteristics of BM physiology, we constructed a tissue cylinder solely occupied by granulocytic progenitors (the most metabolically active stage of the most abundant cell type) to provide a physiologically relevant limiting case. Although the number of possible cellular architectures is large, all simulated pO(2) profiles fall between two extreme cases: those of homogeneous tissues with adipocytes and granulocytic progenitors, respectively. This was illustrated by results obtained from a parametric criterion derived for pO(2) depletion in the extravascular tissue. Modeling results suggest that stem and progenitor cells experience a low pO(2) environment in the BMHC.

ImportanceSARS-CoV-2 infection is associated with persistent, relapsing, or new symptoms or other health effects occurring after acute infection, termed postacute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. Characterizing PASC requires analysis of prospectively and uniformly collected data from diverse uninfected and infected individuals.ObjectiveTo develop a definition of PASC using self-reported symptoms and describe PASC frequencies across cohorts, vaccination status, and number of infections.Design, Setting, and ParticipantsProspective observational cohort study of adults with and without SARS-CoV-2 infection at 85 enrolling sites (hospitals, health centers, community organizations) located in 33 states plus Washington, DC, and Puerto Rico. Participants who were enrolled in the RECOVER adult cohort before April 10, 2023, completed a symptom survey 6 months or more after acute symptom onset or test date. Selection included population-based, volunteer, and convenience sampling.ExposureSARS-CoV-2 infection.Main Outcomes and MeasuresPASC and 44 participant-reported symptoms (with severity thresholds).ResultsA total of 9764 participants (89% SARS-CoV-2 infected; 71% female; 16% Hispanic/Latino; 15% non-Hispanic Black; median age, 47 years [IQR, 35-60]) met selection criteria. Adjusted odds ratios were 1.5 or greater (infected vs uninfected participants) for 37 symptoms. Symptoms contributing to PASC score included postexertional malaise, fatigue, brain fog, dizziness, gastrointestinal symptoms, palpitations, changes in sexual desire or capacity, loss of or change in smell or taste, thirst, chronic cough, chest pain, and abnormal movements. Among 2231 participants first infected on or after December 1, 2021, and enrolled within 30 days of infection, 224 (10% [95% CI, 8.8%-11%]) were PASC positive at 6 months.Conclusions and RelevanceA definition of PASC was developed based on symptoms in a prospective cohort study. As a first step to providing a framework for other investigations, iterative refinement that further incorporates other clinical features is needed to support actionable definitions of PASC.

Background Three-dimensional optical (3DO) body scanning has been proposed for automatic anthropometry. However, conventional measurements fail to capture detailed body shape. More sophisticated shape features could better indicate health status. Objectives The objectives were to predict DXA total and regional body composition, serum lipid and diabetes markers, and functional strength from 3DO body scans using statistical shape modeling. Methods Healthy adults underwent whole-body 3DO and DXA scans, blood tests, and strength assessments in the Shape Up! Adults cross-sectional observational study. Principal component analysis was performed on registered 3DO scans. Stepwise linear regressions were performed to estimate body composition, serum biomarkers, and strength using 3DO principal components (PCs). 3DO model accuracy was compared with simple anthropometric models and precision was compared with DXA. Results This analysis included 407 subjects. Eleven PCs for each sex captured 95% of body shape variance. 3DO body composition accuracy to DXA was: fat mass R2 = 0.88 male, 0.93 female; visceral fat mass R2 = 0.67 male, 0.75 female. 3DO body fat test-retest precision was: root mean squared error = 0.81 kg male, 0.66 kg female. 3DO visceral fat was as precise (%CV = 7.4 for males, 6.8 for females) as DXA (%CV = 6.8 for males, 7.4 for females). Multiple 3DO PCs were significantly correlated with serum HDL cholesterol, triglycerides, glucose, insulin, and HOMA-IR, independent of simple anthropometrics. 3DO PCs improved prediction of isometric knee strength (combined model R2 = 0.67 male, 0.59 female; anthropometrics-only model R2 = 0.34 male, 0.24 female). Conclusions 3DO body shape PCs predict body composition with good accuracy and precision comparable to existing methods. 3DO PCs improve prediction of serum lipid and diabetes markers, and functional strength measurements. The safety and accessibility of 3DO scanning make it appropriate for monitoring individual body composition, and metabolic health and functional strength in epidemiological settings. This trial was registered at clinicaltrials.gov as NCT03637855.