Procyanidins (PCs), which are organic antioxidants, suppress oxidative stress, exhibit anti-apoptotic properties, and chelate metal ions. The potential defense mechanism of PCs against cerebral ...ischemia/reperfusion injury (CIRI) was investigated in this study. Pre-administration for 7 days of a PC enhanced nerve function and decreased cerebellar infarct volume in a mouse middle cerebral artery embolization paradigm. In addition, mitochondrial ferroptosis was enhanced, exhibited by mitochondrial shrinkage and roundness, increased membrane density, and reduced or absent ridges. The level of Fe
and lipid peroxidation that cause ferroptosis was significantly reduced by PC administration. According to the Western blot findings, PCs altered the expression of proteins associated with ferroptosis, promoting the expression of GPX4 and SLC7A11 while reducing the expression of TFR1, hence inhibiting ferroptosis. Moreover, the treatment of PCs markedly elevated the expression of HO-1 and Nuclear-Nrf2. The PCs' ability to prevent ferroptosis due to CIRI was decreased by the Nrf2 inhibitor ML385. Our findings showed that the protective effect of PCs may be achieved via activation of the Nrf2/HO-1 pathway and inhibiting ferroptosis. This study provides a new perspective on the treatment of CIRI with PCs.
Acetylshikonin (ASK) is a natural naphthoquinone derivative of traditional Chinese medicine Lithospermum erythrorhyzon. It has been reported that ASK has bactericidal, anti‐inflammatory and ...antitumour effects. However, whether ASK induces apoptosis and autophagy in acute myeloid leukaemia (AML) cells and the underlying mechanism are still unclear. Here, we explored the roles of apoptosis and autophagy in ASK‐induced cell death and the potential molecular mechanisms in human AML HL‐60 cells. The results demonstrated that ASK remarkably inhibited the cell proliferation, viability and induced apoptosis in HL‐60 cells through the mitochondrial pathway, and ASK promoted cell cycle arrest in the S‐phase. In addition, the increased formation of autophagosomes, the turnover from light chain 3B (LC3B) I to LC3B II and decrease of P62 suggested the induction of autophagy by ASK. Furthermore, ASK significantly decreased PI3K, phospho‐Akt and p‐p70S6K expression, while enhanced phospho‐AMP‐activated protein kinase (AMPK) and phospho‐liver kinase B1(LKB1) expression. The suppression of ASK‐induced the conversion from LC3B I to LC3B II caused by the application of inhibitors of AMPK (compound C) demonstrated that ASK‐induced autophagy depends on the LKB1/AMPK pathway. These data suggested that the autophagy induced by ASK were dependent on the activation of LKB1/AMPK signalling and suppression of PI3K/Akt/mTOR pathways. The cleavage of the apoptosis‐related markers caspase‐3 and caspase‐9 and the activity of caspase‐3 induced by ASK were markedly reduced by inhibitor of AMPK (compound C), an autophagy inhibitor 3‐methyladenine (3‐MA) and another autophagy inhibitor chloroquine (CQ). Taken together, our data reveal that ASK‐induced HL‐60 cell apoptosis is dependent on the activation of autophagy via the LKB1/AMPK and PI3K/Akt‐regulated mTOR signalling pathways.
•The GBRT algorithm is adopted to predict the FRP-concrete bond strength.•520 sets of single-shear test data are collected to train the model.•Emipirical models are compared to illustrate the model’s ...superior.•Typical machine learning models are used for comparison.•The mechanism behind the proposed model is investigated to prove its rationality.
Nowadays, externally bonding fiber reinforced polymer (FRP) plates or sheets have become a major maintenance approach for aged reinforced concrete flexure structures. However, the capacity of strengthend structure cannot be precisely estimated as a result of the critical FRP-concrete interfacial (FCI) bond strength unpredictable. In order to solve this issue, many experimental studies have been carried out with corresponding emipirical models proposed. Due to limited experiment samples, these models were found more or less lacking the generalization ability. Under this circumstance, in this study, an ensemble learning algorithm “gradient boosted regression trees” (GBRT) was employed to develop a prediction model for FCI bond strength prediction based on a collected comprehensive database containing 520 tested samples. The model’s performance has been thoroughly compared with the representative empirical models and the common utilized machine learning algorithms. The rationality of this model has also been discussed through feature importance analysis. The results showed that the model in this study exhibits the highest accuracy and is proven to be feasible for predicting FCI bond strength in actual practice.
The crystal structures of zirconium diboride have been thoroughly explored up to 200 GPa by applying the particle‐swarm optimization technique in company with first‐principles calculations. The ...hexagonal ZrB2 with space group of P6/mmm is always stable in the pressure region of 0–200 GPa. Structurally, this structure consists of the intriguing regular ZrB12 hexagonal column and the planar hexagonal B ring unit. In addition, the stable AlB2–ZrB2 configuration is mechanically and dynamically stable as confirmed by the respective calculations of elastic constants and phonon dispersion curves. The hardness values exhibit a shrinking variation upon further compression, which mainly originates from the decreasing brittleness and degree of the directionality of the covalent bonds with the growing pressure. Interestingly, the analyses of the Poisson's ratio, density of states, electron location function and Bader charge substantiate that a combination of covalent and ionic characters exists in the AlB2–ZrB2 crystalline with the formidable covalent interaction in the BB bonds, and partially covalent and partially ionic interactions in the ZrB bonds. The hardness value for this phase unexpectedly reaches 45.41 GPa under ambient pressure, higher than the lower limit of superhard materials.
The hexagonal ZrB2 with space group of P6/mmm is always stable in the pressure region of 0–200 GPa. The AlB2–ZrB2 structure consists of the intriguing regular ZrB12 hexagonal column and the planar hexagonal B ring unit. The bond nature in AlB2–ZrB2 configuration comprises a combination of covalent and ionic characteristics.
Machine learning (ML)–based data-driven approaches have become increasingly prevalent for predicting structural performance. Because a properly trained ML model can learn hidden patterns in databases ...of experimental samples, ML model performance sometimes exceeds that of mechanics-based predictive models, especially when the latter either conflates multiple phenomena into a single term or does not represent them at all. Nevertheless, there is almost always an inherent gap between the domain of the collected data—used in developing the predictive models—and the desired prediction domain. For instance, structural testing is often carried out on scaled components with approximated boundary conditions. Although mechanics-based models can usually bridge the said gaps, discrepancies are a perpetual challenge to the extrapolation capabilities of data-driven models. To address this issue, a new data-driven approach, a prior-knowledge embedded data-driven approach (PkeDA), is proposed herein, which integrates valuable prior knowledge embedded in empirical formulas into a data-driven model. A particular realization of this approach, based on artificial neural networks, PkeDA-ANN, is developed. To verify its feasibility and compare it with a model trained through a classic data-driven approach (CDA), a case study for predicting the bending capacities of reinforced concrete beams is carried out. The results indicate that when the model is trained via CDA, it exhibits good interpolation capabilities, as expected, but its extrapolation capabilities are observed to be severely limited. Under identical conditions, the proposed PkeDA was observed to have not only excellent interpolation and extrapolation capabilities but also to dramatically surpass the classic empirical formulas that have been developed for predicting the capacity of concrete beams under bending. As such, PkeDA appears to be a viable approach for developing highly accurate data-driven models when prior knowledge is available.
Rationale
Low‐molecular‐weight organic acids that generally contain one to three carboxyl groups are involved in many important biological processes; therefore, it is important to develop a ...quantitative method for analyzing organic acids in serum in order to allow an evaluation of metabolic changes. In this study, we evaluated a protocol for detecting 26 organic acids in serum based on ultrasound‐assisted derivatization by gas chromatography/mass spectrometry (GC/MS).
Methods
Serum samples were prepared using ultrasound‐assisted silane derivatization before GC/MS analysis to quantify concentrations of organic acids. Additionally, we investigated the variables affecting derivatization yields, including the extraction solvent, derivatization reagents, and derivatization conditions (reaction temperature, duration, and sonication parameters). The protocol was ultimately applied to detect organic acid profiles related to obesity.
Results
We used acetone as the extraction solvent and determined suitable derivatization conditions, as follows: BSTFA + 1% TMCS, 50°C, 10 min, and 100% ultrasound power. The protocol showed satisfactory linearity (r = 0.9958–0.9996), a low limit of detection (0.04–0.42 μmol/L), good reproducibility (coefficient of variation (CV) %: 0.32–13.76%), acceptable accuracy (recovery: 82.97–114.96%), and good stability within 5 days (CV%: 1.35–12.01% at room temperature, 1.24–14.09% at 4°C, and 1.01–11.67% at −20°C). Moreover, the protocol was successfully applied to obtain the organic acid profiles from obese and healthy control subjects.
Conclusions
We identified and validated a protocol for ultrasound‐assisted derivatization prior to GC/MS analysis for detecting 26 kinds of organic acids in serum. The results suggest the efficacy of this protocol for clinical applications to determine metabolic changes related to fluctuations in organic acid profiles.
Global antibiotics consumption has been on the rise, leading to increased antibiotics release into the environment, which threatens public health by selecting for antibiotic resistant bacteria and ...resistance genes, and may endanger the entire ecosystem by impairing primary production. Conventional bacteria-based treatment methods are only moderately effective in antibiotics removal, while abiotic approaches such as advanced oxidation and adsorption are costly and energy/chemical intensive, and may cause secondary pollution. Considered as a promising alternative, microalgae-based technology requires no extra chemical addition, and can realize tremendous CO2 mitigation accompanying growth related pollutants removal. Previous studies on microalgae-based antibiotics removal, however, focused more on the removal performances than on the removal mechanisms, and few studies have concerned the toxicity of antibiotics to microalgae during the treatment process. Yet understanding the removal mechanisms can be of great help for targeted microalgae-based antibiotics removal performances improvement. Moreover, most of the removal and toxicity studies were carried out using environment-irrelevant high concentrations of antibiotics, leading to reduced guidance for real-world situations. Integrating the two research fields can be helpful for both improving antibiotics removal and avoiding toxicological effects to primary producers by the residual pollutants. This study, therefore, aims to build a link connecting the occurrence of antibiotics in the aquatic environment, the removal of antibiotics by microalgae-based processes, and the toxicity of antibiotics to microalgae. Distribution of various categories of antibiotics in different water environments were summarized, together with the antibiotics removal mechanisms and performances in microalgae-based systems, and the toxicological mechanisms and toxicity of antibiotics to microalgae after either short-term or long-term exposure. Current research gaps and future prospects were also analyzed. The review could provide much valuable information to the related fields, and provoke interesting thoughts on integrating microalgae-based antibiotics removal research and toxicity research on the basis of environmentally relevant concentrations.
Display omitted
•Occurrence of antibiotics in various water environments was summarized.•Antibiotic removal mechanisms and outcomes in microalgae-based systems was analyzed.•Mechanisms of the toxicological effects of antibiotics on microalgae was outlined.•Toxicity to microalgae under short and long term antibiotic exposure was summarized.•Integrating removal and toxicity studies at real-world concentrations was suggested.
Climate change has a significant impact on agriculture. However, the impact investigation is currently limited to the analysis of meteorological data, and there is a dearth of long-term monitoring of ...crop phenology and soil moisture associated with climate change. In this study, temperature and precipitation (1957–2020) were recorded, crop growth (1981–2019) data were collected, and field experiments were conducted at central and eastern Gansu and southern Ningxia, China. The mean temperature increased by 0.36°C, and precipitation decreased by 11.17 mm per decade. The average evapotranspiration (ET) of winter wheat in 39 years from 1981 to 2019 was 362.1 mm, demonstrating a 22.1-mm decrease every 10 years. However, the ET of spring maize was 405.5 mm over 35 years (1985–2019), which did not show a downward trend. Every 10 years, growth periods were shortened by 5.19 and 6.47 d, sowing dates were delayed by 3.56 and 1.68 d, and maturity dates advanced by 1.76 and 5.51 d, respectively, for wheat and maize. A film fully-mulched ridge–furrow (FMRF) system with a rain-harvesting efficiency of 65.7-92.7% promotes deep rainwater infiltration into the soil. This leads to double the soil moisture in-furrow, increasing the water satisfaction rate by 110-160%. A 15-year grain yield of maize increased by 19.87% with the FMRF compared with that of half-mulched flat planting. Grain yield and water use efficiency of maize increased by 20.6 and 17.4% when the density grew from 4.5×104 to 6.75×104 plants ha–1 and improved by 12.0 and 12.7% when the density increased from 6.75×104 to 9.0×104 plants ha–1, respectively. Moreover, responses of maize yield to density and the corresponding density of the maximum yield varied highly in different rainfall areas. The density parameter suitable for water planting was 174 maize plants ha–1 with 10 mm rainfall. Therefore, management strategies should focus on adjusting crop planting structure, FMRF water harvesting system, and water-suitable planting to mitigate the adverse effects of climate change and enhance sustainable production of maize in the drylands.
Markers of neuroinflammation are increased in some patients with LRRK2 Parkinson's disease compared with individuals with idiopathic Parkinson's disease, suggesting possible differences in disease ...pathogenesis. Previous PET studies have suggested amplified dopamine turnover and preserved serotonergic innervation in LRRK2 mutation carriers. We postulated that patients with LRRK2 mutations might show abnormalities of central cholinergic activity, even before the diagnosis of Parkinson's disease.
Between June, 2009, and December, 2015, we recruited participants from four movement disorder clinics in Canada, Norway, and the USA. Patients with Parkinson's disease were diagnosed by movement disorder neurologists on the basis of the UK Parkinson's Disease Society Brain Bank criteria. LRRK2 carrier status was confirmed by bidirectional Sanger sequencing. We used the PET tracer N-11C-methyl-piperidin-4-yl propionate to scan for acetylcholinesterase activity. The primary outcome measure was rate of acetylcholinesterase hydrolysis, calculated using the striatal input method. We compared acetylcholinesterase hydrolysis rates between groups using ANCOVA, with adjustment for age based on the results of linear regression analysis.
We recruited 14 patients with LRRK2 Parkinson's disease, 16 LRRK2 mutation carriers without Parkinson's disease, eight patients with idiopathic Parkinson's disease, and 11 healthy controls. We noted significant between-group differences in rates of acetylcholinesterase hydrolysis in cortical regions (average cortex p=0·009, default mode network-related regions p=0·006, limbic network-related regions p=0·020) and the thalamus (p=0·008). LRRK2 mutation carriers without Parkinson's disease had increased acetylcholinesterase hydrolysis rates compared with healthy controls in the cortex (average cortex, p=0·046). Patients with LRRK2 Parkinson's disease had significantly higher acetylcholinesterase activity in some cortical regions (average cortex p=0·043, default mode network-related regions p=0·021) and the thalamus (thalamus p=0·004) compared with individuals with idiopathic disease. Acetylcholinesterase hydrolysis rates in healthy controls were correlated inversely with age.
LRRK2 mutations are associated with significantly increased cholinergic activity in the brain in mutation carriers without Parkinson's disease compared with healthy controls and in LRRK2 mutation carriers with Parkinson's disease compared with individuals with idiopathic disease. Changes in cholinergic activity might represent early and sustained attempts to compensate for LRRK2-related dysfunction, or alteration of acetylcholinesterase in non-neuronal cells.
Michael J Fox Foundation, National Institutes of Health, and Pacific Alzheimer Research Foundation.
PDF
