Supramolecular assemblies with spatio-temporal sequential drug delivery capability treat spinal cord injury via neuroprotection and immunoregulation.

Spinal cord injury (SCI) can result in irreversible motor and sensory deficits. However, up to data, clinical first-line drugs have ambiguous benefits and debilitating side effects, mainly due to the insufficient accumulation, poor physiological barrier penetration, and lack of spatio-temporal controlled release at lesion tissue. Herein, we proposed a supramolecular assemblies composed of hyperbranched polymer-formed core/shell structure through host-guest interactions. Such HPAA-BM@CD-HPG-C assemblies co-loaded with p38 inhibitor (SB203580) and insulin-like growth factor 1(IGF-1) are able to achieve time- and space-programmed sequential delivery benefiting from their cascaded responsiveness. The core-shell disassembly of HPAA-BM@CD-HPG-C occurs in acidic micro-environment around lesion, achieving preferentially the burst release of IGF-1 to protect survival neurons. Subsequently, the HPAA-BM cores containing SB203580 are endocytosed by the recruited macrophages and degraded by intracellular GSH, accelerating the release of SB203580 to promote the conversion from M1 to M2 macrophage. Hence, the successive synergy of neuroprotection and immunoregulation effects contribute to subsequent nerve repair and locomotor recovery as demonstrated in vitro and in vivo studies. Thus, our fabrication provides a strategy that multiple drugs co-delivery in a spatio-temporal selective manner adapting to the disease progression through self-cascaded disintegration, are expected to realize multidimensional precise treatment of SCI.

Clinical, radiological, and laboratory characteristics and risk factors for severity and mortality of 289 hospitalized COVID-19 patients.

BACKGROUND: The coronavirus disease 2019 (COVID-19) has become a global pandemic, with 10%-20% of severe cases and over 508 000 deaths worldwide. OBJECTIVE: This study aims to address the risk factors associated with the severity of COVID-19 patients and the mortality of severe patients. METHODS: 289 hospitalized laboratory-confirmed COVID-19 patients were included in this study. Electronic medical records, including patient demographics, clinical manifestation, comorbidities, laboratory tests results, and radiological materials, were collected and analyzed. According to the severity and outcomes of the patients, they were divided into three groups: nonsurvived (n = 49), survived severe (n = 78), and nonsevere (n = 162) groups. Clinical, laboratory, and radiological data were compared among these groups. Principal component analysis (PCA) was applied to reduce the dimensionality and visualize the patients on a low-dimensional space. Correlations between clinical, radiological, and laboratory parameters were investigated. Univariate and multivariate logistic regression methods were used to determine the risk factors associated with mortality in severe patients. Longitudinal changes of laboratory findings of survived severe cases and nonsurvived cases during hospital stay were also collected. RESULTS: Of the 289 patients, the median age was 57 years (range, 22-88) and 155 (53.4%) patients were male. As of the final follow-up date of this study, 240 (83.0%) patients were discharged from the hospital and 49 (17.0%) patients died. Elder age, underlying comorbidities, and increased laboratory variables, such as leukocyte count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), procalcitonin (PCT), D-dimer, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and blood urea nitrogen (BUN) on admission, were found in survived severe cases compared to nonsevere cases. According to the multivariate logistic regression analysis, elder age, a higher number of affected lobes, elevated CRP levels on admission, increased prevalence of chest tightness/dyspnea, and smoking history were independent risk factors for death of severe patients. A trajectory in PCA was observed from "nonsevere" toward "nonsurvived" via "severe and survived" patients. Strong correlations between the age of patients, the affected lobe numbers, and laboratory variables were identified. Dynamic changes of laboratory findings of survived severe cases and nonsurvived cases during hospital stay showed that continuing increase of leukocytes and neutrophil count, sustained lymphopenia and eosinopenia, progressing decrease in platelet count, as well as high levels of NLR, CRP, PCT, AST, BUN, and serum creatinine were associated with in-hospital death. CONCLUSIONS: Survived severe and nonsurvived COVID-19 patients had distinct clinical and laboratory characteristics, which were separated by principle component analysis. Elder age, increased number of affected lobes, higher levels of serum CRP, chest tightness/dyspnea, and smoking history were risk factors for mortality of severe COVID-19 patients. Longitudinal changes of laboratory findings may be helpful in predicting disease progression and clinical outcome of severe patients.