RESUMEN
Sealing wet porous membranes is a major challenge when fabricating cell encapsulation devices. Herein, we report the development of an Autoclavable Transparent Thermal Cutter (ATTC) for reliably sealing wet nanofibrous membranes. Notably, the ATTC is autoclavable and transparent, thus enabling in situ visualization of the sealing process in a sterile environment and ensuring an appropriate seal. In addition, the ATTC could generate smooth, arbitrary-shaped sealing ends with excellent mechanical properties when sealing PA6, PVDF, and TPU nanofibrous tubes and PP microporous membranes. Importantly, the ATTC could reliably seal wet nanofibrous tubes, which can shoulder a burst pressure up to 313.2 ± 19.3 kPa without bursting at the sealing ends. Furthermore, the ATTC sealing process is highly compatible with the fabrication of cell encapsulation devices, as verified by viability, proliferation, cell escape, and cell function tests. We believe that the ATTC could be used to reliably seal cell encapsulation devices with minimal side effects.
RESUMEN
This paper studies the projection test for high-dimensional mean vectors via optimal projection. The idea of projection test is to project high-dimensional data onto a space of low dimension such that traditional methods can be applied. We first propose a new estimation for the optimal projection direction by solving a constrained and regularized quadratic programming. Then two tests are constructed using the estimated optimal projection direction. The first one is based on a data-splitting procedure, which achieves an exact t-test under normality assumption. To mitigate the power loss due to data-splitting, we further propose an online framework, which iteratively updates the estimation of projection direction when new observations arrive. We show that this online-style projection test asymptotically converges to the standard normal distribution. Various simulation studies as well as a real data example show that the proposed online-style projection test retains the type I error rate well and is more powerful than other existing tests.
RESUMEN
Antibacterial hydrogel wound dressings hold great potential in eliminating bacteria and accelerating the healing process. However, it remains a challenge to fabricate hydrogel wound dressings that simultaneously exhibit excellent mechanical and photothermal antibacterial properties. Here we report the development of polydopamine-functionalized graphene oxide (rGO@PDA)/calcium alginate (CA)/Polypyrrole (PPy) cotton fabric-reinforced hydrogels (abbreviated as rGO@PDA/CA/PPy FHs) for tackling bacterial infections. The mechanical properties of hydrogels were greatly enhanced by cotton fabric reinforcement and an interpenetrating structure, while excellent broad-spectrum photothermal antibacterial properties based on the photothermal effect were obtained by incorporating PPy and rGO@PDA. Results indicated that rGO@PDA/CA/PPy FHs exhibited superior tensile strength in both the warp (289 ± 62.1 N) and weft directions (142 ± 23.0 N), similarly to cotton fabric. By incorporating PPy and rGO@PDA, the swelling ratio was significantly decreased from 673.5% to 236.6%, while photothermal conversion performance was significantly enhanced with a temperature elevated to 45.0 °C. Due to the synergistic photothermal properties of rGO@PDA and PPy, rGO@PDA/CA/PPy FHs exhibited excellent bacteria-eliminating efficiency for S. aureus (0.57%) and E. coli (3.58%) after exposure to NIR for 20 min. We believe that the design of fabric-reinforced hydrogels could serve as a guideline for developing hydrogel wound dressings with improved mechanical properties and broad-spectrum photothermal antibacterial properties for infected-wound treatment.
RESUMEN
BACKGROUND: Electrolyte disturbances are highly heterogeneous and severely affect the prognosis of critically ill patients. Our study was to determine whether data-driven phenotypes of seven electrolytes have prognostic relevance in critically ill patients. METHODS: We extracted patient information from three large independent public databases, and clustered the electrolyte distribution of ICU patients based on the extreme value, median value and coefficient of variation of electrolytes. Three plausible clinical phenotypes were calculated using K-means clustering algorithm as the basic clustering method. MIMIC-IV was considered a training set, and two others have been designated as verification set. The robustness of the model was then validated from different angles, providing dynamic and interactive visual charts for more detailed characterization of phenotypes. RESULTS: 15,340, 12,445 and 2147 ICU patients with electrolyte records during early ICU stay in MIMIC-IV, eICU-CRD and AmsterdamUMCdb were enrolled. After clustering, three reasonable and interpretable phenotypes are defined as α, ß and γ according to the order of clusters. The α and γ phenotype, with significant differences in electrolyte distribution and clinical variables, higher 28-day mortality and longer length of ICU stay (p < 0.001), was further demonstrated by robustness analysis. The α phenotype has significant kidney injury, while the ß phenotype has the best prognosis. In addition, the assignment methods of the three phenotypes were developed into a web-based tool for further verification and application. CONCLUSIONS: Three different clinical phenotypes were identified that correlated with electrolyte distribution and clinical outcomes. Further validation and characterization of these phenotypes is warranted.
