Toxicological responses in alfalfa (Medicago sativa) under joint stress of cadmium and napropamide

Joint effects of Cd2+ and napropamide in seeds, roots or leaves of alfalfa were investigated under different treatments. It was shown that single stress of Cd2+ or napropamide decreased chlorophyll content after 30 days of treatment in different concentrations. The decrease in chlorophyll content became insignificant under joint stress of Cd2+ and napropamide. It can be concluded that the interaction of Cd2+ and napropamide would aggravate the toxic effects on chlorophyll synthesis in leaves of alfalfa. The joint effect of Cd2+ and napropamide was markedly significant (p < 0.05) on the change of SP content in leaves in all treatment. Moreover, Cd2+ and napropamide mixture exposure can increase lignin content and present synergistic effect. In a mixture treated with Cd2+ and napropamide, 52% decrease in β-carotene content contrasted with the control in young leaves. The contents of protein thiols and non-protein thiols in the roots of alfalfa were significantly increased by Cd2+ treatment in all treatment levels. In contrast, increasing napropamide supply did not have any significant effect on the protein thiols and non-protein thiols content. The Cd2+ induced accumulation of O2•- in seeds could be increased by treatment with different Cd2+ concentration. Production of H2O2 and O2•- was also higher in the napropamide treatments than in the control. The addition of napropamide significantly increased the H2O2 and O2•- level in the seeds of alfalfa.Key words: Alfalfa, joint stress, cadmium, napropamide

C. elegans fatty acid two-hydroxylase regulates intestinal homeostasis by affecting heptadecenoic acid production

Background/Aims: The hydroxylation of fatty acids at the C-2 position is the first step of fatty acid α-oxidation and generates sphingolipids containing 2-hydroxy fatty acyl moieties. Fatty acid 2-hydroxylation is catalyzed by Fatty acid 2-hydroxylase (FA2H) enzyme. However, the precise roles of FA2H and fatty acid 2-hydroxylation in whole cell homeostasis still remain unclear. Methods: Here we utilize Caenorhabditis elegans as the model and systemically investigate the physiological functions of FATH-1/C25A1.5, the highly conserved worm homolog for mammalian FA2H enzyme. Immunostaining, dye-staining and translational fusion reporters were used to visualize FATH-1 protein and a variety of subcellular structures. The “click chemistry” method was employed to label 2-OH fatty acid in vivo. Global and tissue-specific RNAi knockdown experiments were performed to inactivate FATH-1 function. Lipid analysis of the fath-1 deficient mutants was achieved by mass spectrometry. Results: C. elegans FATH-1 is expressed at most developmental stages and in most tissues. Loss of fath-1 expression results in severe growth retardation and shortened lifespan. FATH-1 function is crucially required in the intestine but not the epidermis with stereospecificity. The “click chemistry” labeling technique showed that the FATH-1 metabolites are mainly enriched in membrane structures preferable to the apical side of the intestinal cells. At the subcellular level, we found that loss of fath-1 expression inhibits lipid droplets formation, as well as selectively disrupts peroxisomes and apical endosomes. Lipid analysis of the fath-1 deficient animals revealed a significant reduction in the content of heptadecenoic acid, while other major FAs remain unaffected. Feeding of exogenous heptadecenoic acid (C17: 1), but not oleic acid (C18: 1), rescues the global and subcellular defects of fath-1 knockdown worms. Conclusion: Our study revealed that FATH-1 and its catalytic products are highly specific in the context of chirality, C-chain length, spatial distribution, as well as the types of cellular organelles they affect. Such an unexpected degree of specificity for the synthesis and functions of hydroxylated FAs helps to regulate protein transport and fat metabolism, therefore maintaining the cellular homeostasis of the intestinal cells. These findings may help our understanding of FA2H functions across species, and offer potential therapeutical targets for treating FA2H-related diseases

Identifying interacting genetic variations by fish-swarm logic regression

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds

Prediction of Three-Dimensional Milling Forces Based on Finite Element

The model of milling force is mainly proposed to predict and analyze the cutting process based on finite element method in this paper. Firstly, milling finite element model is given based on orthogonal cutting principle, and then the influence laws of cutting parameters on chip formation are analyzed by using different simulation parameters. In addition, the three-dimensional milling forces are obtained from finite element models. Finally, the values of milling force by the milling experiment are also compared and analyzed with the simulation values to verify the feasibility and reasonability. It can be shown that milling forces match well between simulation and experiment results, which can provide many good basic data and analysis methods to optimize the machining parameters, reduce tool wear, and improve the workpiece surface roughness and adapt to the programming strategy of high speed machining

Prediction of acute kidney injury in patients with femoral neck fracture utilizing machine learning

BackgroundAcute kidney injury (AKI) is a common complication associated with significant morbidity and mortality in high-energy trauma patients. Given the poor efficacy of interventions after AKI development, it is important to predict AKI before its diagnosis. Therefore, this study aimed to develop models using machine learning algorithms to predict the risk of AKI in patients with femoral neck fractures.MethodsWe developed machine-learning models using the Medical Information Mart from Intensive Care (MIMIC)-IV database. AKI was predicted using 10 predictive models in three-time windows, 24, 48, and 72 h. Three optimal models were selected according to the accuracy and area under the receiver operating characteristic curve (AUROC), and the hyperparameters were adjusted using a random search algorithm. The Shapley additive explanation (SHAP) analysis was used to determine the impact and importance of each feature on the prediction. Compact models were developed using important features chosen based on their SHAP values and clinical availability. Finally, we evaluated the models using metrics such as accuracy, precision, AUROC, recall, F1 scores, and kappa values on the test set after hyperparameter tuning.ResultsA total of 1,596 patients in MIMIC-IV were included in the final cohort, and 402 (25%) patients developed AKI after surgery. The light gradient boosting machine (LightGBM) model showed the best overall performance for predicting AKI before 24, 48, and 72 h. AUROCs were 0.929, 0.862, and 0.904. The SHAP value was used to interpret the prediction models. Renal function markers and perioperative blood transfusions are the most critical features for predicting AKI. In compact models, LightGBM still performs the best. AUROCs were 0.930, 0.859, and 0.901.ConclusionsIn our analysis, we discovered that LightGBM had the best metrics among all algorithms used. Our study identified the LightGBM as a solid first-choice algorithm for early AKI prediction in patients after femoral neck fracture surgery

Synergistic effects of hybrid conductive nanofillers on the performance of 3D printed highly elastic strain sensors

In this work, thermoplastic polyurethane based conductive polymer composites containing carbon nanotubes (CNTs) and synthesized silver nanoparticles (AgNPs) were used to fabricate highly elastic strain sensors via fused deposition modeling. The printability of the materials was improved with the introduction of the nanofillers, and the size and content of the AgNPs significantly influenced the sensing performance of the 3D printed sensors. When the CNTs:AgNPs weight ratio was 5:1, the sensors exhibited outstanding performance with high sensitivity (GF = 43260 at 250% strain), high linearity (R 2 = 0.97 within 50% strain), fast response (~57 ms), and excellent repeatability (1000 cycles) due to synergistic effects. A modeling study based on the Simmons' tunneling theory was also undertaken to analyze the sensing mechanism. The sensor was applied to monitor diverse joint movements and facial motion, showing its potential for application in intelligent robots, prosthetics, and wear-able devices where customizability are usually demanded

Clay mineralogy indicates a mildly warm and humid living environment for the Miocene hominoid from the Zhaotong Basin, Yunnan, China

Global and regional environmental changes have influenced the evolutionary processes of hominoid primates, particularly during the Miocene. Recently, a new Lufengpithecus cf. lufengensis hominoid fossil with a late Miocene age of ~6.2 Ma was discovered in the Shuitangba (STB) section of the Zhaotong Basin in Yunnan on the southeast margin of the Tibetan Plateau. To understand the relationship between paleoclimate and hominoid evolution, we have studied sedimentary, clay mineralogy and geochemical proxies for the late Miocene STB section (~16 m thick; ca. 6.7–6.0 Ma). Our results show that Lufengpithecus cf. lufengensis lived in a mildly warm and humid climate in a lacustrine or swamp environment. Comparing mid to late Miocene records from hominoid sites in Yunnan, Siwalik in Pakistan, and tropical Africa we find that ecological shifts from forest to grassland in Siwalik are much later than in tropical Africa, consistent with the disappearance of hominoid fossils. However, no significant vegetation changes are found in Yunnan during the late Miocene, which we suggest is the result of uplift of the Tibetan plateau combined with the Asian monsoon geographically and climatically isolating these regions. The resultant warm and humid conditions in southeastern China offered an important refuge for Miocene hominoids

Flexible and high-performance piezoresistive strain sensors based on carbon nanoparticles@polyurethane sponges

In this work, flexible and high-performance piezoresistive strain sensors were fabricated by simple layer-by-layer electrostatic self-assembly of carbon nanoparticles on commercial polyurethane (PU) sponges. It was shown that the sponge-based strain sensors exhibited obviously positive and negative piezoresistive characteristics under tensile and compressive strains, respectively. The alternate assembly of carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) contributed to the construction of a more complete conductive network and significantly improved the sensing performance of the sensor due to the synergistic effect between CNTs and GNPs. Compared with the CNT@PU and CNT/GNP@PU sponge strain sensors, the CNT/GNP/CNT@PU sensor had a larger strain detection range and higher linearity. Besides, the CNT/GNP/CNT@PU sponge strain sensor showed high sensitivity (GF = 43,000 at 60% tensile strain and GF = −1.1 at 50% compressive strain), responsive capability to very small strain (0.05%) and outstanding stability during 3000 loading cycles. Due to its excellent sensing performance, the CNT/GNP/CNT@PU sensor enabled monitoring of various physiological activities, including finger movements, wrist bending and walking etc. In addition, a 5 × 5 sensor array based on the sponge-based strain sensor was prepared to achieve accurate identification of weight distribution. This study provides valuable information for the development of flexible strain sensors with high-performance and low-cost