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Marine accidents cause not only significant economic losses, but also severe environmental pollution and inestimable human casualties, which have become a worldwide concern. To better cope with this concern, this paper adopts temporal association rules (TARs) to mine and discover the domino effect in marine accidents. Using the dataset of 5754 marine domino accidents (MDAs) collected from the International Maritime Organization and IHS Markit Company, the main findings of this paper are as follows. First, 'hull damage' was found to be the most frequent accident in MDAs, and 'collision' was more likely to cause the damage in the whole hull. Second, 'oil spill' was most often observed as a final marine accident. Meanwhile, 'foundered' was more likely to cause 'oil spill' in both oil tanker and general cargo ship MDAs. Third, it is pointed out that most probable scenarios involved 'hull damage' as the basic accident which ended with 'foundered' and 'oil spill' as top accidents. These findings not only advance our knowledge of marine accidents from the perspective of the domino effect, but also provide insights into improving marine safety.

To assess risk factors of reintubation in intensive care unit patients on mechanical ventilation.We conducted a systematic review of literature (inception to May 2022) and a meta-analysis. Data are reported as pooled odds ratios for categorical variables and mean differences for continuous variables.A total of 2459 studies were retrieved of which 38 studies were included in a meta-analysis involving 22,304 patients. Risk factors identified were: older age, higher APACHE II scores, COPD, pneumonia, shock, low SaOWe identified 21 factors associated with increased risk for reintubation. These allow to recognize the patient at high risk for reintubation at an early stage. Future studies may combine these factors to develop comprehensive predictive algorithms allowing appropriate vigilance.

Inflammatory bowel disease (IBD) is a kind of chronic inflammation that occurs in gastrointestinal tract, including Ulcerative colitis (UC) and Crohn's disease (CD). Although UC and CD are associated with intestinal inflammation and epithelial damage, they are quite different. The etiology of IBD has not been fully determined, but there is extensive evidence that its pathogenesis involves environmental, genetic, immune and microbial factors. The diagnosis and treatment of IBD is challenging due to its recurrent episodes and complex evolution. Metabolomics, as a new developing technology, can be used to qualitatively and quantitatively study small metabolic molecules in samples of patients, which include stool, urine, serum, plasma and tissues, and is increasingly valued in the diagnosis and treatment of IBD. This article sums up the recent progress of metabolomics in helping to diagnose and treat IBD diseases, hoping to provide biomarkers and new targets for the diagnosis and treatment of IBD. In addition, we present the limitations of the current study of metabolomics and highlight some solutions.

"San-Bai Decoction" (SBD) has been a traditional Chinese medicine compound preparation for replenishing Qi and promoting blood circulation, whitening skin, and removing blemishes since ancient times. However, its chemical composition and antioxidant activity are not clear thus far, which limits the in-depth study on its pharmacodynamic material basis and efficacy. The objective of this study was to establish the fingerprint profile of SBD, assess its antioxidant activity by measuring 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability, and find the spectrum-effect relationship of SBD by Grey Relation Analysis (GRA) and Partial Least Squares Regression (PLS). In this study, the fingerprint of SBD was established by high performance liquid chromatography (HPLC), and 20 common peaks were found, among which 6 peaks were designated. The similarities between the fingerprints of 12 batches of SBD and the reference fingerprint (R) were all greater than 0.900. Meanwhile, the antioxidant activities of all batches were concentration-dependent in their linear regression equation. The result of GRA showed that the correlation order of 20 common peaks for DPPH radical scavenging was X13 X7 X3 X6 X10 X11 X4 X12 X2 X18 X9 X5 X19 X1 X20 X16 X17 X15 X8 X14. At the same time, PLS study demonstrated that the contribution of six identified characteristic peaks to DPPH radical scavenging ability was X1 = X7 X6 X19 X20 X16. In this study, the spectrum-effect relationship of SBD between its HPLC fingerprint and the antioxidant activity can be used to screen the pharmacodynamic substance basis of its antioxidant action and lay the foundation for establishing quality standards and product development.

Two new labdane diterpenoids denoted Scoparicol A (1) and Scoparicol B (2) were isolated from the aerial parts of Scoparia dulcis L. The new structures were determined by various spectroscopic techniques, including 1H NMR, 13C NMR, HMBC, HSQC, 1H-1HCOSY, ROESY, and HRESIMS. Both compounds were tested for their attenuating effect on palmitate-induced viability at 25 and 50 μM, separately. The results showed that the two new compounds significantly attenuated palmitate-induced viability in MIN6 cells.

SUMMARY: Resveratrol is a polyphenol known to have many beneficial biological activities. In our study, we investigated the effect of supplementing chicken feed with different concentrations of resveratrol. A total of 2,160 Jingfen white egg chickens in their 210-d old were selected for this study. They were randomly distributed into 4 diet groups with 6 replicates each. Each replicate group contained 90 chickens. Diets were supplemented with 1 of 4 doses of resveratrol: 0, 200, 400, and 800 mg/kg. Relative to that in controls, the egg production rate and mean daily food intake significantly increased upon 200 mg/kg resveratrol treatment (P < 0.05). The feed-to-egg ratio also significantly diminished in these animals (P < 0.05), as did the cull/death rate. Resveratrol was also linked with extended egg shelf lives and improved sensory scores. Supplementation with 400 mg/kg resveratrol significantly reduced levels of total serum cholesterol and triglycerides and activities of alanine transaminase and aspartate transaminase (P < 0.05). These results therefore show that 200 mg/kg resveratrol supplementation improved the performance of laying hens, whereas 400 mg/kg dose was associated with better lipid metabolism, reduced egg cholesterol content, extended egg shelf life, improved antioxidant activity, and improved egg sensory scores.

Mangrove forests are productive ecosystems but are vulnerable to tropical cyclones. In this study, we quantified the damage of mangroves from Hurricane Irma at a large-scale using Landsat data, and modeled the risk of mangroves to hurricanes using three internal/physical metrics (a vegetation index, canopy height, and distance to open ocean) and two external/hurricane-related metrics (hurricane track and storm surge inundation). Four machine learning techniques including Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbor (k-NN) were examined and compared with the Multiple Linear Regression (MLR) method to identify the best risk model for damage projection from future hurricanes. The models were calibrated and validated using data before and after Hurricane Irma. Machine learning algorithms had a better performance than the linear model, and RF achieved the best result with a correlation coefficient (r) of 0.84 in predicting mangrove damages. The model also produced an encouraging result to hindcast mangrove damages from Hurricane Wilma. We applied object-based modeling and mapping techniques and produced mangrove damage maps from Irma and a worst-case scenario hurricane with an intensity of Category 5 and a track along the mangrove distribution. A total of 332 km2 of mangroves were severely damaged from Irma, and 635 km2 would be devastated from the modeled scenario. The techniques developed here can be used for other mangrove forests exposed to tropical cyclones.

Metformin hydrochloride (Met) is the first-line drug to treat type 2 diabetes and has shown high efficiency in reducing Alzheimer's disease in recent studies. Herein, a borneol W/O/W composite submicron emulsion containing Met (B-Met-W/O/W SE) was prepared, expecting longer in-vivo circulation time, better bioavailability and brain targeting of Met drug. In the optimized formulation, the mean droplets size, polydispersity index and encapsulation efficiency of the composite were 386.5 nm, 0.219 and 87.26%, respectively. FTIR analysis confirmed that Met interacted with carriers in B-Met-W/O/W SE. Compared with Met free drug, in-vitro release of Met in B-Met-W/O/W SE delivery system was much slower. In pharmacokinetic studies in rats, the AUC, MRT and t1/2 of the B-Met-W/O/W SE system were respectively 1.27, 2.49 and 4.02-fold higher than Met free drug system. The drug-targeting index of B-Met-W/O/W SE system to the brain tissue was also higher than that of Met free drug system and Met-W/O/W SE system. These results indicated that B-Met-W/O/W SE drug delivery system is a promising candidate in treating clinical Alzheimer's disease.

Tidal salt marshes sequester and store blue carbon at both short and long time scales. Marsh soils shape and maintain the ecosystem by supporting complex biogeochemical reactions, deposition of sediment, and accumulation of organic matter. In this study, we examined the potential of imaging spectroscopy techniques to indirectly quantify and map tidal marsh soil properties at a National Estuarine Research Reserve in Georgia, USA. A framework was developed to combine modern digital image processing techniques for marsh soil mapping, including object-based image analysis (OBIA), machine learning modeling, and ensemble analysis. We also evaluated the efficacy of airborne hyperspectral sensors in estimating marsh soil properties compared to spaceborne multispectral sensors, WorldView-2 and QuickBird. The pros and cons of object-based modeling and mapping were assessed and compared with traditional pixel-based mapping methods. The results showed that the designed framework was effective in quantifying and mapping three marsh soil properties using the composite reflectance from salt marsh environment: soil salinity, soil water content, and soil organic matter content. Multispectral sensors were successful in quantifying soil salinity and soil water content but failed to model soil organic matter. The study also demonstrated the value of minimum noise fraction transformation and ensemble analysis techniques for marsh soil mapping. The results suggest that imaging spectroscopy based modeling is a promising tool to quantify and map marsh soil properties at a local scale, and is a potential alternative to traditional soil data acquisition to support carbon cycle research and the conservation and restoration of tidal marshes.

Light Detection and Ranging (LiDAR) Digital Elevation Models (DEMs) are frequently applied in modeling coastal environments. We present an object-based correction approach for accurate and precise DEMs by integrating LiDAR point data, aerial imagery, and Real Time Kinematic-Global Positioning Systems. Four machine learning techniques (Random Forest, Support Vector Machine, k-Nearest Neighbor, and Artificial Neural Network) were compared with the commonly used bias-correction method. The Random Forest object-based model produced best predictions for two study areas: Nine Mile (Mean Bias Error (MBE) reduced 0.18 to −0.02 m, Root Mean Square Error (RMSE) reduced 0.22 to 0.08 m) and Flamingo (MBE reduced 0.17 to 0.02 m, RMSE reduced 0.24 to 0.10 m). A Monte Carlo model was developed to combine errors into the object-based machine learning corrected DEMs, and uncertainty maps spatially revealed the likelihood of error. The object-based correction approach provides an attractive alternative to the bias-correction method.

The East China Sea (ECS) is seriously impacted by harmful algal blooms (HABs). Therefore, early assessments of HAB risk in this area are extremely important. Using long-term historical HAB observation data and satellite-derived sea surface temperatures (SSTs), we found that the annual number of HAB events was positively correlated with the mean March SST and negatively correlated with the SST change rate from March to July in nearshore waters (50 m). A simple method of HAB risk assessment was therefore proposed based on either March SST (threshold: 13 °C) or SST change rate (threshold: 3.6 °C/month). Validation against a k-means classification scheme indicated that the overall accuracy based on the March SST threshold was 85%, with a kappa coefficient of 0.69. The SST-based method facilitates the assessment of HAB risk in the ECS 1-2 months in advance, thus helping to reduce the damage caused by HABs.

Purpose The 2019 COVID-19 pandemic poses a challenge to adolescent psychological health. The aim of this study was to survey junior high and high school students in China to better understand the psychological consequences, such as anxiety, depression, and stress, of the COVID-19 pandemic. Methods A cross-sectional online survey using structural questionnaires was conducted from April 7, 2020, to April 24, 2020. Demographic information and general information related to the pandemic were collected. Psychological consequences were assessed by the Impact of Event Scale-Revised and the Depression, Anxiety and Stress Scale. Influencing factors were assessed by the Brief Resilience Scale and Coping Style Questionnaire. Results Our sample comprised 493 junior high school students (male = 239, mean age = 13.93 years) and 532 high school students (male = 289, mean age = 17.08 years). Resilience and positive coping were protective factors for the occurrence of depressive, anxiety, and stress symptoms in junior high and high school students (p < .05). Positive coping was a protective factor for trauma-related distress in junior high school students (p < .05). Negative coping is a risk factor for depression, anxiety, stress symptoms, and trauma-related distress in junior high and high school students (p < .05). Conclusions During the COVID-19 pandemic in China, more than one fifth of junior high and high school students' mental health was affected. Our findings suggested that resilience and positive coping lead to better psychological and mental health status among students. In contrast, negative coping is a risk factor for mental health.

Yttrium (Y) accumulation in soil is a serious environment problem in China. To understand the mechanisms involved in Y tolerance and detoxification in rice seedling, the bioaccumulation, subcellular distribution, and chemical forms of Y was investigated in the present study. The results show that the content of Y both in roots and shoots increases with the increasing concentration of Y, and a large amount of Y is stored in roots. Subcellular distribution of Y in rice indicates that the majority of Y is bound to cell wall. Meanwhile, various chemical forms of Y is absorbed by rice. The greatest amount of Y is extracted by 2% hydrate acetic acid (HAc) and 0.6 mol/L HCl (particularly 2% HAc), which indicates that most of Y is combined with un-dissolved phosphate and oxalate (particularly phosphate). Cluster analysis, based on Y abundance levels, reveals the relationship between Y distribution patterns and chemical forms. Our results imply that Y forming of precipitates with phosphate (and/or oxalate) and depositing in the cell wall may be a key strategy for Y detoxicity and tolerance in rice.

Large-scale biomass quantification of sawgrass (Cladium jamaicense) marsh is critical to understand the carbon and energy cycle in the Florida Everglades. There is also a need to monitor biomass changes in the coastal Everglades due to continuing sea level rise. Previous research in biomass estimation of coastal marshes has focused on pixel-based parametric modeling methods. In this study, an object-based ensemble analysis approach was developed to map sawgrass biomass at multiple scales using Landsat data. Four machine learning regression algorithms including Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbor (k-NN), and Artificial Neural Network (ANN) were evaluated and compared to the commonly used Multiple Linear Regression (MLR) method for both live and total sawgrass biomass estimation. A weighted combining scheme was developed to integrate predictions from comparable models for ensemble analysis. Nonparametric machine learning models had better performance than the parametric approach. ANN and SVM produced similar results in live biomass estimation with the correlation coefficient (r) larger than 0.9, while ANN achieved the best result for the total biomass estimation (r = 0.94). Sawgrass biomass maps were produced for two harvest seasons in 2014 and 2016 at three detail levels, which successfully revealed the spatial and temporal (seasonal and interannual) sawgrass biomass variations. Ensemble analysis of the ANN and SVM predictions of live sawgrass biomass not only made the estimation more reliable, but also generated an uncertainty map to identify the regions with a robust biomass prediction, as well as challenging areas for biomass quantification. It is concluded that the object-based ensemble analysis is a promising alternative to the commonly used pixel-based biomass modeling techniques.

Two new aminoethylstilbene isoquinoline alkaloids denoted litsine B (1) and Litsine C (2) were isolated from an ethanol extract from the root bark of Litsea glutinosa. The structures of the new chemical entities were established using 1D and 2D NMR spectroscopy in combination with high resolution mass spectrometry. Both compounds were tested for their effect on glucose consumption in HepG2 cells at different concentrations. The results showed that compound 2 significantly increased the glucose uptake.

The pathogenesis of obstructive sleep apnea (OSA) remains controversial. The role of anatomic stenosis is indisputable, and neural regulation of the upper airway remains to be elucidated. The upper airway maintains patency through the upper airway reflex. Lesions in any link of the reflex can increase the collapsibility of the upper airway. In this study, we investigated sensorimotor nerve lesions and their possible relationship with OSA. Tissue samples were obtained from the pharyngopalatine arch in 47 patients with OSA and 45 control participants to examine changes in the expression levels of myelin basic protein (MBP) and agrin through immunohistochemistry and western blotting. Downregulation of MBP in the mucosa reflects myelinated degeneration of mucosal sensory nerve axons, whereas upregulation of agrin in the neuromuscular junction reflects synaptic regeneration following denervation. The two neural factors correlate significantly with polysomnographic parameters, such as the apnea hypopnea index and lowest oxygen saturation. Our findings suggest that sensorimotor nerve damage in the upper airway of patients with OSA may be associated closely with the mechanism of OSA.

Quantifying end of summer season Active Layer Thickness (ALT) of permafrost is critical for understanding the effects of climate warming, disturbance, and hydrologic changes on permafrost. Current research mainly focuses on ALT estimation and mapping at large scales using process-based or statistical-empirical models with biophysical variables as predictors. Here we modeled multi-year ALT field measurements between 2014 and 2019 at a site in Interior Alaska using 1-m hyperspectral imaging data and an object-based ensemble approach at a local scale (1 km2), examined the efficacy of the multispectral sensor WorldView (WV)-2 for ALT estimation, and explored the potential of integrating single-date imaging data with multi-year in-situ measurements for mapping the spatial and temporal variation of ALT. Modeling results showed hyperspectral imaging was accurate for estimating ALT with a correlation coefficient (r) larger than 0.7, while application of WV-2 data produced an r around 0.4. Reasonable ALT patterns were generated, and the spatial and temporal variation of ALT was delineated between the shallowest (2015) and deepest (2019) years using hyperspectral data. This study suggests hyperspectral imaging is a promising tool for predicting field ALT measurements and monitoring ALT change at local scales. We expect this study will stimulate hyperspectral optical sensors for permafrost studies in general, and particularly for ALT upscaling.

Wetlands play a critical role in the global carbon (C) budget by sequestering carbon dioxide (CO2) and storing significant amounts of C, but climate change is altering C dynamics in these ecosystems. Therefore, predicting and mapping net ecosystem exchange (NEE) of CO2 in wetlands has emerged as a focus of research to better understand where, how, and when biogeochemical cycles will be modified by human and natural disturbances like climate change. To address this, we developed an object-based machine learning ensemble approach to upscale eddy covariance (EC) CO2 flux measurements across two major wetland ecosystems (cypress swamp and freshwater marshes) in the Greater Everglades of south Florida. We linked 30-m Landsat, water depth, and air temperature data with EC flux measurements using the temporally composite concept for model development, and mapped fluxes within Big Cypress National Preserve (BCNP) and Everglades National Park (ENP) to characterize two distinct seasonal flux patterns. Using an ensemble analysis of three machine learning model outputs (Artificial Neural Network, Support Vector Machine, and Random Forest), our models of NEE at BCNP had a high predictive power with a R2 greater than 0.8, while NEE was predicted at ENP with a R2 greater than 0.5. We also generated an uncertainty map to quantify the prediction diversity caused by application of multiple models in upscaling. This uncertainty map identifies regions that are either easy or challenging to predict from model based analyses. We conclude that integration of Landsat, water depth, and air temperature data is valuable for quantifying CO2 exchange between the atmosphere and Everglades ecosystems, and the developed paradigm is promising for upscaling EC flux measurements in wetlands to study and mitigate disturbances to wetland ecosystem services such as hurricanes, fires, water management and/or climate change.

Metal halide perovskite solar cells (PSCs) have made remarkable progress recently. However, the large number of defects in the polycrystalline perovskite film has an important impact on the carrier recombination and ion migration in the device. The non-radiative recombination is regarded as the main way of charge loss, which largely determines the performance of PSCs. Here, a small molecule, 2-mercaptopyrimidine (MPM), was selected as the surface passivator for MAPbI3 perovskite films. It is revealed that both S and N atoms in MPM can interact with uncoordinated Pb2+ to passivation the surface defects. As a result, the devices based on MPM passivation achieve a higher power conversion efficiency (PCE) of 19.71% than the control devices (17.85%) due to the reduced surface defect state density. Moreover, MPM-passivated PSCs also possess superior humidity stability, retaining 94% and 82% of the initial PCEs after 720 and 480 h aging in air with a relative humidity of 30% and 60%, respectively.

An investigation on the chemical constituents in the root barks of Litsea glutinosa was performed for the first time. Three new lignan glycosides named Litseasins A–C (1–3), together with a known one (4), were obtained. The structures of the new compounds were established through extensive spectroscopic analyses including HR-ESI–MS, NMR, and circluar dichroism (CD). The new compounds were evaluated for their anti-inflammatory activities on lipopolysaccharide (LPS)-induce nitric oxide (NO) production in RAW264.7 murine macrophage cells. However, these compounds showed no inhibition on LPS-induced NO productions.

Mapping plant communities and documenting their changes is critical to the on-going Florida Everglades restoration project. In this study, a framework was designed to map dominant vegetation communities and inventory their changes in the Florida Everglades Water Conservation Area 2A (WCA-2A) using time series Landsat images spanning 1996–2016. The object-based change analysis technique was combined in the framework. A hybrid pixel/object-based change detection approach was developed to effectively collect training samples for historical images with sparse reference data. An object-based quantification approach was also developed to assess the expansion/reduction of a specific class such as cattail (an invasive species in the Everglades) from the object-based classifications of two dates of imagery. The study confirmed the results in the literature that cattail was largely expanded during 1996–2007. It also revealed that cattail expansion was constrained after 2007. Application of time series Landsat data is valuable to document vegetation changes for the WCA-2A impoundment. The digital techniques developed will benefit global wetland mapping and change analysis in general, and the Florida Everglades WCA-2A in particular.

Different microstructured MnO 2 was synthesized as a pseudocapacitive material by using a facile hydrothermal method. MnSO 4 ·H 2 O and (NH 4 ) 2 S 2 O 8 were reacted at 120 °C for 12 h to form MnO 2 , for which the morphology and phase composition of the MnO 2 formed could be well controlled. The obtained MnO 2 samples were comparatively characterized in terms of their crystallographic structure, microstructure and electrochemical performance. The results revealed that the MnO 2 was controllably formed in different microstructures (nanorod, hollow urchin and smooth ball) with different crystalline phase compositions. The average specific capacitance of MnO 2 nanorod, hollow urchin and smooth ball at a scan rate of 5 mV/s was 317, 204 and 276 F/g, respectively, indicating that MnO 2 nanorod displayed the best electrochemical capacity. All the synthesized MnO 2 , however, showed a good reversibility and cycling stability, roughly 70% of the initial capacitance retained after 2000 charge/discharge cycles. This work sheds light on a facile approach for synthesis of high-performance metal oxide electrode materials with controllable microstructure.

Background DNA topoisomerase (Topo) inhibition plays key role in breast cancer treatment. Stephania hainanensis H. S. Lo et Y. Tsoong (S. hainanensis), a Li nationality plant that has abundant aporphine alkaloids, can inhibit Topo. Purpose To identify a dual Topo inhibitor, a deep and systematic study of active aporphine alkaloids in S. hainanensis and their mechanisms of inhibiting breast cancer proliferation and Topo activity are essential. Study design This study aimed to assess the anti-breast cancer and Topo inhibitory activities of oxocrebanine and explore the underlying mechanisms. Methods The growth inhibitory activities of 12 compounds in S. hainanensis were screened by MTT assay in MCF-7, SGC-7901, HepG-2 cells, and compared with the effects on human normal mammary epithelial MCF-10A cells as non cancer control cells. The Topo inhibitory activity was assessed by DNA relaxation and unwinding assays, kDNA decatenation assay and western blot. Cell cycle and autophagy analyses were carried out with flow cytometry and staining. Acridine orange staining and α-tubulin morphology were observed by fluorescence microscopy. Western blot was used to examine microtubule assembly dynamics and the expression levels of key proteins associated with DNA damage, autophagy and mitotic arrest. Results Oxocrebanine was the anti-breast cancer active alkaloid in S. hainanensis. It exhibited the best inhibitory effect on MCF-7 cells with an IC50 of 16.66 μmol/l, and had only weak effect on the proliferation of MCF-10A cells. Oxocrebanine inhibited Topo I and II α in a cell-free system and in MCF-7 cells. The DNA unwinding assay suggested that oxocrebanine intercalated with DNA as a catalytic inhibitor. Oxocrebanine regulated the levels of Topo I and IIα and DNA damage-related proteins. Oxocrebanine led to the mitotic arrest, and these effects occurred through both p53-dependent and p53-independent pathways. Oxocrebanine induced autophagy, abnormal α-tubulin morphology and stimulated enhanced microtubule dynamics. Conclusion Oxocrebanine was the anti-breast cancer active aporphine alkaloid in S. hainanensis. Oxocrebanine was a Topo I/IIα dual inhibitor, catalytic inhibitor and DNA intercalator. Oxocrebanine caused DNA damage, autophagy, and mitotic arrest in MCF-7 cells. Oxocrebanine also disrupted tubulin polymerization. Accordingly, oxocrebanine held a great potential for development as a novel dual Topo inhibitor for effective breast cancer treatment.

The bitter gourd (Momordica charantia L.) is a world-famous medical vegetable involved in multiple pharmacological activities especially known for its lipid- and glucose-lowering effects. As a result of its abundance of triterpenes and saponins (collectively called triterpenoids), growing evidence shows that they have a variety of biological effects, including anti-diabetic, anti-tumor, anti-bacterial, anti-viral, and anti-inflammatory activities. These studies indicate that triterpenoids (triterpenes) which are thought to play a key role in mediating diverse biological effects are likely to be underestimated in bitter gourd. To date, there is no comprehensive review specifying the composition and pharmacological activities of triterpenoids in this medical food. In this review, we focused on the structural diversity and biological function of M. charantia-derived triterpenes and saponins for the first time. The summarized information emphasizes the chemical complexity and promising clinical utility of M. charantia-derived triterpenoids which deserve more effort to be isolated, chemically characterized, functionally clarified, and eventually should be developed as new drugs or adjuvant treatment.

All-inorganic CsPbI2Br perovskite with relatively high phase stability and a suitable band gap has been considered as a promising candidate for photovoltaic application. However, in comparison with its organic–inorganic counterparts, it still shows unsatisfactory efficiency and high moisture sensitivity. Here, polyethylene glycol (PEG) is introduced into the CsPbI2Br precursor solution. It is revealed that Lewis base PEG interacts with Pb2+, which can slow down the crystallization rate, regulate the energy levels, and passivate the defect density of CsPbI2Br films. As a result, the optimized devices with PEG exhibit a power conversion efficiency (PCE) of 13.59% under one sun illumination (100 mW cm‒2), which is considerably higher than that of the control devices (10.09%), owing to the reduced nonradiative recombination losses for the former CsPbI2Br films. The results demonstrate that using polymer additives to improve the device performance is an effective strategy for all-inorganic perovskite solar cells.

Quantification of the urban composition is important in urban planning and management. Previous research has primarily focused on unmixing medium-spatial resolution multispectral imagery using spectral mixture analysis (SMA) in order to estimate the abundance of urban components. For this study an object-based multiple endmember spectral mixture analysis (MESMA) approach was applied to unmix the 30-m Earth Observing-1 (EO-1)/Hyperion hyperspectral imagery. The abundance of two physical urban components (vegetation and impervious surface) was estimated and mapped at multiple scales and two defined geographic zones. The estimation results were validated by a reference dataset generated from fine spatial resolution aerial photography. The object-based MESMA approach was compared with its corresponding pixel-based one, and EO-1/Hyperion hyperspectral data was compared with the simulated EO-1/Advanced Land Imager (ALI) multispectral data in the unmixing modeling. The pros and cons of the object-based MESMA were evaluated. The result illustrates that the object-based MESMA is promising for unmixing the medium-spatial resolution hyperspectral imagery to quantify the urban composition, and it is an attractive alternative to the traditional pixel-based mixture analysis for various applications.

As one of the active pharmaceutical ingredients in Gamboge, Gambogenic acid (GNA) has shown diverse anti-tumor activities. To reduce the vascular irritation of GNA and improve its water solubility, tumor targeting, and bioavailability, GNA loaded Zein nanoparticles (GNA@Zein NPs) was further coated by polydopamine (PDA) to develop GNA@Zein-PDA NPs by anti-solvent precipitation and surface modification. The results showed that particle size and Zeta potential of GNA@Zein-PDA NPs were about 310 nm and −40.8 mV with core–shell morphology confirmed by TEM. GNA@Zein-PDA NPs increased the water solubility of GNA by more than 700 times and showed pH-sensitive release behavior in PBS with pH 6.86. In vitro cytotoxicity tests showed that GNA@Zein-PDA NPs had higher inhibitory activity on HepG2 cells than free GNA, and their IC50 were 1.59 μg/mL and 9.89 μg/mL, respectively. Additionally, the hemolysis and vascular irritation assay showed that GNA@Zein-PDA NPs had good cytocompatibility and reduced the irritation of GNA to blood vessels. Moreover, the in vivo pharmacokinetic experiments exhibited that the Cmax and AUC0-t of GNA@Zein-PDA NPs were significantly improved approximately by 2.09-fold and 3.48-fold over that of GNA, respectively. In conclusion, GNA@Zein-PDA NPs solve many defects of GNA and provide a tumor-targeting drug delivery for GNA.

A rapid, simple and reliable method using amoxicillin-D4 as internal standard (IS) for determination of amoxicillin (AMO) in porcine tissues was developed. The analytical methodology used a phosphate buffer (0.01 M, pH = 6.3) with trichloroacetic acid (50 mg/mL) for extraction and Oasis® HLB cartridges for clean-up followed by UPLC-MS/MS analysis. The optimized method was validated according to EU guideline 2002/657/EC and FDA guideline. The LOQ in muscle, fat, liver and kidney were set to 10 μg/kg which was below the maximum residue limits, while the LOD were set to 5 μg/kg. Results showed that using AMO-D4 as IS can effectively eliminate relative matrix interference and improve the recovery and precision. A good linearity was observed at the range of 10−500 μg/kg with a correlation coefficients (R2) larger than 0.99. The mean recoveries were higher than 87.0 %, and the RSDs were lower than 11.2 %. This method could be applied to conveniently analysis the residue of AMO in different porcine tissues.