Composition and influencing factors of professionals’ capacity in public health emergency rescues: a qualitative study

ObjectiveTo explore the composition and influencing factors of professionals’ capacity in public health emergency rescues.MethodsA descriptive qualitative design was used in this study. Medical workers, managers, and members of an emergency rescue team in Hangzhou, Zhejiang, were recruited for participation through a purposive sampling method. The data were collected using semi-structured interviews and analyzed using a conventional content analysis method.FindingsA total of 2 themes and 13 sub-themes emerged from the analysis: ability composition (knowledge reserve, early warning assessment, information reporting, emergency response, self-protection, personal ability, coordination and cooperation, health education) and influencing factors (educational background, region, experience, hospital level, human resources, and financial investment).ConclusionThese findings offer a basis for the construction of a related indicator system and provide a reference for relevant departments to further optimize their emergency education and training, strengthen their emergency drills, and improve their emergency rescue abilities. The findings indicate that it is necessary to pay attention to the construction of an emergency rescue team, adjust the ratio of personnel, improve their remuneration, and promote work enthusiasm to improve the emergency rescue ability of an organization

3-Amino­benzonitrile–3,5-dinitro­benzoic acid (1/1)

The asymmetric unit of the title co-crystal, C7H6N2·C7H4N2O6, contains two formula units of both components. The crystal structure is stabilized by inter­molecular O—H⋯O, N—H⋯O, N—H⋯N and C—H⋯O hydrogen bonds, generating a two-dimensional wave-like network. π–π stacking inter­actions [centroid–centroid distances = 3.702 (2), 3.660 (2)and 3.671 (2) Å] stabilize the crystal packing

A New Chinese Medicine Intestine Formula Greatly Improves the Effect of Aminosalicylate on Ulcerative Colitis

Ulcerative colitis (UC) is a chronic lifelong inflammatory disorder of the colon. Current medical treatment of UC relies predominantly on the use of traditional drugs, including aminosalicylates, corticosteroids, and immunosuppressants, which failed to effectively control this disease’s progression and produced various side effects. Here, we report a new Chinese medicine intestine formula (CIF) which greatly improved the effect of mesalazine, an aminosalicylate, on UC. In the present study, 60 patients with chronic UC were treated with oral mesalazine alone or in combination with CIF enema. The combination of mesalazine and CIF greatly and significantly improved the clinical symptoms and colon mucosal condition and improved the Mayo Clinic Disease Activity Index and health-related quality of life, when compared to mesalazine alone. In particular, the addition of CIF further decreased serum levels of tumor necrosis factor-alpha and hypersensitivity C-reactive protein but in contrast increased interleukin-4. Thus, the results demonstrate the beneficial role of CIF in UC treatment, which may be mediated by the regulation of inflammation

Clinical value of the systemic immune-inflammation index in moyamoya disease

BackgroundMoyamoya disease (MMD) is a rare cerebrovascular disorder with unknown etiology. The underlying pathophysiological mechanism of moyamoya disease remains to be elucidated, but recent studies have increasingly highlighted that abnormal immune response may be a potential trigger for MMD. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are inflammatory markers that can reflect the immune-inflammation state of the disease.ObjectiveThe purpose of this study was to investigate SII, NLR, and PLR in patients with moyamoya disease.MethodsA total of 154 patients with moyamoya disease (MMD group) and 321 age- and sex-matched healthy subjects (control group) were included in this retrospective case–control study. Complete blood count parameters were assayed to calculate the SII, NLR, and PLR values.ResultsThe SII, NLR, and PLR values in the moyamoya disease group were significantly higher than those in the control group [754 ± 499 vs. 411 ± 205 (P < 0.001), 2.83 ± 1.98 vs. 1.81 ± 0.72 (P < 0.001), and 152 ± 64 vs. 120 ± 42 (P < 0.001), respectively]. The SII in the medium-moyamoya vessels of moyamoya disease was higher than that in the high-moyamoya vessels and low-moyamoya vessels (P = 0.005). Using the receiver operating characteristic (ROC) curve analysis to predict MMD, the highest area under the curve (AUC) was determined for SII (0.76 for SII, 0.69 for NLR, and 0.66 for PLR).ConclusionBased on the results of this study, patients with moyamoya disease admitted for inpatient care due to acute or chronic stroke have significantly higher SII, NLR, and PLR when compared to blood samples drawn from completely healthy controls in a non-emergent outpatient setting. While the findings may suggest that inflammation plays a role in moyamoya disease, further studies are warranted to corroborate such an association. In the middle stage of moyamoya disease, there may be a more intense imbalance of immune inflammation. Further studies are needed to determine whether the SII index contributes to the diagnosis or serves as a potential marker of an inflammatory response in patients with moyamoya disease

A Simple Method of Mapping Landslides Runout Zones Considering Kinematic Uncertainties

Landslides can be triggered by natural and human activities, threatening the safety of buildings and infrastructures. Mapping potential landslide runout zones are critical for regional risk evaluation. Although remote sensing technology has been widely used to discover unstable areas, an entire landslide runout zone is difficult to identify using these techniques alone. Some simplified methods based on empirical models are used to simulate full-scale movements, but these methods do not consider the kinematic uncertainties caused by random particle collisions in practice. In this paper, we develop a semi-empirical landslide dynamics method considering kinematic uncertainties to solve this problem. The uncertainties caused by the microtopography and anisotropy of the material are expressed by the diffusion angle. Monte Carlo (MC) simulations are adopted to calculate the probability of each cell. Compared with the existing Flow-R model, this method can more accurately and effectively estimate runout zones of the Yigong landslide where random particle collisions are intense. Combining the D-InSAR technique, we evaluate the runout zones in the Jinsha River from June 2019 to December 2020. This result shows that the method is of great significance in early warning and risk mitigation, especially in remote areas. The source area of the landslide and DEM resolution together affect the number of MC simulations required. A landslide with a larger volume requires a larger diffusion angle and more MC simulations

Identification of urban regions' functions in Chengdu, China, based on vehicle trajectory data.

Data about human trajectories has been widely used to study urban regions that are attractive to researchers and are considered to be hotspots. It is difficult, however, to quantify the function of urban regions based on the varieties of human behavior. In this research, we developed a clustering method to help discover the specific functions that exist within urban regions. This method applies the Gaussian Mixture Model (GMM) to classify regions' inflow and trip count characteristics. It regroups these urban regions using the Pearson Correlation Coefficient (PCC) clustering method based on those typical characteristics. Using a large amount of vehicle trajectory data (approximately 1,500,000 data points) in the Chinese city of Chengdu, we demonstrate that the method can discriminate between urban functional regions, by comparing the proportion of surface objects within each region. This research shows that vehicle trajectory data in different functional urban regions possesses different time-series curves, while similar types of functional regions can be identified by these curves. Compared with remote sensing images and other statistical methods which can provide only static results, our research can provide a timely and effective approach to determine an urban region's functions

Picroside II Shows Protective Functions for Severe Acute Pancreatitis in Rats by Preventing NF-κB-Dependent Autophagy

Picroside II, from the herb Picrorhiza scrophulariiflora Pennell, has antioxidant and anti-inflammatory activities. However, its function on severe acute pancreatitis (SAP) and molecular mechanism remains unknown. The effects of picroside II on the SAP induced by cerulean were investigated. SAP rats were treated with picroside II (25 mg/kg). The severity of SAP was evaluated by using biochemical and histological analyses. Pancreatic cancer cell PANC-1 was transfected with ptfLC3 (an indicator of autophagic activity), pcDNA3.1-NF-κB (nuclear factor kappa B), and pTZU6+1-NF-κB-shRNA and then treated with picroside II. Relative molecules related with NF-κB-dependent autophagy were detected by using Western blot. Autophagic activities were observed by phase-contrast and fluorescent microscopes. Acetylated LC3 was detected by immunoprecipitation. The results showed that picroside II treatment reduced the level of ALT, AST, NF-κB, IL-1β, IL-6, TNF-α, and SIRT1 (NAD+-dependent deacetylase) and increased the level of SOD and GSH. The autophagic activity was reduced when NF-κB was silenced, and the levels of TNF-α and SIRT1 were reduced. In contrast, the overexpression of NF-κB increased autophagic activity and the level of TNF-α, which activated SIRT1. SIRT1 deacetylated LC3 and increased autophagic activities. Picroside II ameliorates SAP by improving antioxidant and anti-inflammtory activities of SAP models via NF-κB-dependent autophagy