Suchergebnisse

Wei Wu,1,* Yan-Qing Yang,2,* Yang Yang,1,* Yu-Ming Yang,2 Hong Wang,2 Kai-Yuan Zhang,1 Li Guo,3 Hong-Fei Ge,1 Jie Liu,2 Hua Feng11Department of Neurosurgery, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, People's Republic of China; 2Key Laboratory of Flexible Electronics (KLOFE) Institute of Advanced Materials (IAM), Nanjing Tech University, Nanjing 211800, People's Republic of China; 3Department of Endocrinology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, People's Republic of China*These authors contributed equally to this workBackground: In vivo fluorescence imaging in the second near-infrared (NIR-II, 1000–1700 nm) window using organic fluorophores has great advantages, but generally suffers from a relatively low fluorescence quantum yield (mostly less than 2%). In this study, organic nanoparticles (L1013 NPs) with a high fluorescence quantum yield (9.9%) were systhesized for in vivo imaging.Methods: A molecule (BTPPA) with donor-acceptor-donor structure and aggregation-induced emission enabling moieties was prepared. BTPPA molecules were then encapsulated into nanoparticles (L1013 NPs) using a nanoprecipitation method. The L1013 NPs were intravenously injected into the mice (including normal, stroke and tumor models) for vascular and tumor imaging.Results: L1013 NPs excited at 808 nm exhibit NIR-II emission with a peak at 1013 nm and an emission tail extending to 1400 nm. They have a quantum yield of 9.9% and also show excellent photo/colloidal stabilities and negligible in vitro and in vivo toxicity. We use L1013 NPs for noninvasive real-time visualization of mouse hindlimb and cerebral vessels (including stroke pathology) under a very low power density (4.6–40 mW cm‒2) and short exposure time (40–100 ms). Moreover, L1013 NPs are able to localize tumor pathology, with a tumor-to-normal tissue ratio of 11.7±1.3, which is unusually high for NIR-II fluorescent imaging through passive targeting strategy.Conclusion: L1013 NPs demonstrate the potential for a range of clinical applications, especially for tumor surgery.Keywords: fluorescence NIR-II imaging, aggregation-induced emission, organic nanoparticle, vascular imaging, tumor imaging

The use of foams to deliver bioactive agents and drugs is increasing in pharmaceutics. One example is the use of foam as a delivery system for polidocanol (POL) in sclerotherapy, with the addition of bioactive compounds to improve the delivery system being a current subject of study. This work shows the influence of two bioactive additives on the structure and stability of POL foam: hyaluronic acid (HA) and Pluronic-F68 (F68). HA is a natural non-surface-active biopolymer present in the extracellular matrix while F68 is a surface-active poloxamer that is biocompatible with plasma-derived fluids. Both additives increase the bulk viscosity of the sample, improving foam stability. However, HA doubled and F68 quadruplicated the foam half lifetime of POL. HA reduced the size and polydispersity of the bubble size distribution and increased the surface elasticity with respect to POL. Both facts have a positive impact in terms of foam stability. F68 also altered bubble structure and increased surface elasticity, again contributing to the enhancement of foam stability. The surface characterization of these systems is important, as in foam sclerotherapy it is crucial to assure the presence of POL at the surface of the bubbles in order to deliver the sclerosant agent in the target vein. ; Junta de Andalucia NANOFOAM-PI12.2956 ; Instituto de Salud Carlos III Spanish Government MAT2017-82182-R RTI2018-101309-B-C21 ; Consejeria de Economia, Conocimiento, Empresas y Universidad ; European Union (EU) SOMM17/6109/UGR

OBJECTIVES: Since 2010, the Chinese government has gradually increased its investment in the training of general practitioners (GPs) to support their role as 'gatekeepers' in the healthcare system. However, this training is still organised from the perspective of specialist care. We aimed to assess the appropriateness of the principal GP admission training programme curricula in China, including Residents Training for GPs (RTGP), Residents Training for Assistant GPs (RTAGP) and Training for Specialists with General Practice interest (TSGP). SETTING: The study focussed on GP training programmes in Shanghai, China. PARTICIPANTS: Data on disease competences developed in three GP clinical training programmes (RTGP, RTAGP and TSGP) were derived from official programme training manuals. Data on the proportion of outpatient visits for each disease were taken from the Shanghai community healthcare centres grassroots outpatient database. PRIMARY AND SECONDARY OUTCOME MEASURES: We first conducted a quantitative analysis by comparing the structure of current training curricula with actual outpatient utilisation patterns across all community healthcare institutions in Shanghai from 2014 to 2018. Qualitative analysis was then conducted to evaluate GP training programmes based on Donabedian's model. RESULTS: Quantitative analysis showed that the distribution of diseases for which competences were taught did not match the composition of outpatient visits in community healthcare institutions. Concerns identified through qualitative analysis included teachers who were mostly specialists, lack of equipment for differential diagnosis in community healthcare institutions, insufficient teaching of referral standards and GP training in large hospitals that consistently neglected communication skills. CONCLUSIONS: The establishment and implementation of admission training programmes for GPs in China lacks a focus on general practice training and may be improved by adopting an evidence-based general perspective aligned with the medical ...

National forest inventories in tropical regions are sparse and have large uncertainty in capturing the physiographical variations of forest carbon across landscapes. Here, we produce for the first time the spatial patterns of carbon stored in forests of Democratic Republic of Congo (DRC) by using airborne LiDAR inventory of more than 432,000 ha of forests based on a designed probability sampling methodology. The LiDAR mean top canopy height measurements were trained to develop an unbiased carbon estimator by using 92 1-ha ground plots distributed across key forest types in DRC. LiDAR samples provided estimates of mean and uncertainty of aboveground carbon density at provincial scales and were combined with optical and radar satellite imagery in a machine learning algorithm to map forest height and carbon density over the entire country. By using the forest definition of DRC, we found a total of 23.3 ± 1.6 GtC carbon with a mean carbon density of 140 ± 9 MgC ha-1 in the aboveground and belowground live trees. The probability based LiDAR samples capture variations of structure and carbon across edaphic and climate conditions, and provide an alternative approach to national ground inventory for efficient and precise assessment of forest carbon resources for emission reduction (ER) programs. ; SCOPUS: ar.j ; info:eu-repo/semantics/published

Live woody vegetation is the largest reservoir of biomass carbon, with its restoration considered one of the most effective natural climate solutions. However, terrestrial carbon fluxes remain the largest uncertainty in the global carbon cycle. Here, we develop spatially explicit estimates of carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show that live biomass has removed 4.9 to 5.5 PgC year −1 from the atmosphere, offsetting 4.6 ± 0.1 PgC year −1 of gross emissions from disturbances and adding substantially (0.23 to 0.88 PgC year −1 ) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink ; This study was funded by NASA Interdisciplinary Science Program (NNH16ZDA001N-IDS). M.L. and Y. Yang have been supported by the NASA Postdoctoral Program, administered by Universities Space Research Association under contract with NASA.G.-J.N. was supported by the European Union H2020-VERIFY project (776810).