Explore the vast range of titles available.

Coupling algal cultivation with wastewater treatment due to their potentials to alleviate energy crisis and reduce environmental burden has attracted the increased attention in recent years. However, these microalgal-based processes are challenging since daily and seasonal temperature fluctuation may affect microalgal growth in wastewater, and the effects of the temperature regimes on microalgal biomass production and wastewater nutrient removal remain unclear. In this study, Chlorella vulgaris was continuously cultured for 15 days in municipal wastewater to investigate the effects on the algal biomass and wastewater nutrient removal in three temperature regimes: (1) low temperature (4 °C), (2) high temperature (35 °C), and (3) alternating high-low temperature (35 °C in the day: 4 °C at night). Compared with the other two temperature regimes, the high-low temperature conditions generated the most biomass (1.62 g L -1 ), the highest biomass production rate (99.21 mg L -1 day -1 ), and most efficient removal of COD, TN, NH 3 -N, and TP (83.0%, 96.5%, 97.8%, and 99.2%, respectively). In addition, the polysaccharides, proteins, lipid content, and fatty acid methyl ester composition analysis indicates that in alternating high-low temperature condition, biomass production increased the potential for biofuel production, and there was the highest lipid content (26.4% of total dry biomass). The results showed that the nutrients except COD were all efficiently removed in these temperature conditions, and the alternating high-low temperature condition showed great potential to generate algal biomass and alleviate the wastewater nutrients. This study provides some valuable information for large-scale algal cultivation in wastewater and microalgal-based wastewater treatments.

Background: Although N6-methyladenosine (m6A) plays a very important role in different biological processes, its function in the brain has not been fully explored. Thus, we investigated the roles of the RNA demethylases Alkbh5/Fto in cerebral ischemia-reperfusion injury. Methods: We used a rat model and primary neuronal cell culture to study the role of m6A and Alkbh5/Fto in the cerebral cortex ischemic penumbra after cerebral ischemia-reperfusion injury. We used Alkbh5-shRNA and Lv-Fto (in vitro) to regulate the expression of Alkbh5/Fto to study their regulation of m6A in the cerebral cortex and to study brain function after ischemia-reperfusion injury. Results: We found that RNA m6A levels increased consecutive to the increase of Alkbh5 expression in both the cerebral cortex of rats after middle cerebral artery occlusion, and in primary neurons after oxygen deprivation/reoxygenation. In contrast, Fto expression decreased after these perturbations. Our results suggest that knocking down Alkbh5 can aggravate neuronal damage. This is due to the demethylation of Alkbh5 and Fto, which selectively demethylate the Bcl2 transcript, preventing Bcl2 transcript degradation and enhancing Bcl2 protein expression. Conclusion: Collectively, our results demonstrate that the demethylases Alkbh5/Fto co-regulate m6A demethylation, which plays a crucial role in cerebral ischemia-reperfusion injury. The results provide novel insights into potential therapeutic mechanisms for stroke.

Cruise ships are distinguished as special passenger ships, transporting passengers to various ports and giving importance to comfort. High comfort can attract lots of passengers and generate substantial profits. Vibration and noise are the most important indicators for assessing the comfort of cruise ships. Existing methods for analyzing vibration and noise data have shown limitations in uncovering essential information and discerning critical disparities in vibration and noise levels across different ship districts. Conversely, the rapid development in machine learning present an opportunity to leverage sophisticated algorithms for a more insightful examination of vibration and noise aboard cruise ships. This study designed a machine learning-driven approach to analyze the vibration and noise data. Drawing data from China’s first large-scale cruise ship, encompassing 127 noise samples, this study sets up a classification task, where decks were assigned as labels and frequencies served as features. Essential information was extracted by investigating this problem. Several machine learning algorithms, including feature ranking, selection, and classification algorithms, were adopted in this method. One or two essential noise frequencies related to each of the decks, except the 10th deck, were obtained, which were partly validated by the traditional statistical methods. Such findings were helpful in reducing and controlling the vibration and noise in cruise ships. Furthermore, the study develops a classifier to distinguish noise samples, which utilizes random forest as the classification algorithm with eight optimal frequency features identified by LightGBM. This classifier yielded a Matthews correlation coefficient of 0.3415. This study gives a new direction for investigating vibration and noise in ships.

Background Pancreatic cancer is a highly malignant tumor of the digestive system. Objective Exosomal circular RNA can be used as a biomarker for the early diagnosis of pancreatic cancer. Methods The expression of various differentially expressed circRNAs in pancreatic cancer tissues was analyzed by gene chip, exosome expression was verified by electron microscopy and Western blotting, and the expression of exosomal circRNA in pancreatic cancer cells, tissues, and plasma were determined by quantitative reverse transcription‐polymerase chain reaction (qRT‐PCR). Results Compared with healthy controls, hsa_circ_0006220 and hsa_circ_0001666 were highly expressed in exosomes in the plasma of pancreatic cancer patients. The AUC values were 0.7817 for hsa_circ_0006220, 0.8062 for hsa_circ_0001666, and 0.884 for the combined diagnosis. In addition, clinicopathological features revealed that the expression of hsa_circ_0006220 in plasma exosomes from pancreatic cancer patients was associated with CA19‐9 levels (p = 0.0001) and lymph node metastasis (p = 0.0005). The expression of hsa_circ_0001666 was correlated with both tumor size (p = 0.0157) and CA19‐9 level (p = 0.0001). Conclusions The high expression of exosomal hsa_circ_0001666 and hsa_circ_0006220 suggests that these can be used as new biomarkers for the diagnosis and treatment of pancreatic cancer. Pancreatic cancer is a highly malignant tumor of the digestive system. Exosomal circular RNA can be used as a biomarker for the early diagnosis of pancreatic cancer. The expression of various differentially expressed circRNAs in pancreatic cancer tissues was analyzed by gene chip, exosome expression was verified by electron microscopy and Western blotting, and the expression of exosomal circRNA in pancreatic cancer cells, tissues, and plasma were determined by quantitative reverse transcription PCR (qRT‐PCR). Exosomes hsa_circ_0001666 and hsa_circ_0006220 were highly expressed in pancreatic cancer tissues, cell lines, and plasma samples of pancreatic cancer patients and were related to clinical staging. The high expression of exosomal hsa_circ_0001666 and hsa_circ_000622 suggests that these can be used as new biomarkers for the diagnosis and treatment of pancreatic cancer.

Marine coral sand-clay mixtures (MCCM) are widely used in marine engineering, with their mechanical behavior strongly influenced by clay content. This study investigates the effects of 3D-printed triaxial geogrid reinforcement on MCCM through triaxial testing. Based on the experimental results, a dataset was established, while a novel machine learning model named GP-BPNN was proposed, integrating genetic algorithm (GA), particle swarm optimization (PSO), and backpropagation neural network (BPNN). This model was applied for the first time to predict the strength of MCCM. Results show that lower clay content, more reinforcement layers, and higher confining pressure significantly enhance the strength and cohesion of MCCM, with little effect on the internal friction angle. The strength first decreases, then increases, and finally decreases again with increasing water content. Particle breakage is influenced by clay content and water content; moreover, fractal analysis reveals a linear relationship between the breakage rate and the fractal dimension. SEM images reveal the interaction between MCCM and the geogrid. Additional stress and matrix suction analyses highlight the effects of reinforcement layers and water content on the strength. These findings offer insight into triaxial geogrid-reinforced MCCM behavior and provide guidance for marine engineering construction.

Background: Although N 6 -methyladenosine (m 6 A) plays a very important role in different biological processes, its function in the brain has not been fully explored. Thus, we investigated the roles of the RNA demethylases Alkbh5/Fto in cerebral ischemia-reperfusion injury. Methods: We used a rat model and primary neuronal cell culture to study the role of m 6 A and Alkbh5/Fto in the cerebral cortex ischemic penumbra after cerebral ischemia-reperfusion injury. We used Alkbh5-shRNA and Lv-Fto ( in vitro ) to regulate the expression of Alkbh5/Fto to study their regulation of m 6 A in the cerebral cortex and to study brain function after ischemia-reperfusion injury. Results: We found that RNA m 6 A levels increased consecutive to the increase of Alkbh5 expression in both the cerebral cortex of rats after middle cerebral artery occlusion, and in primary neurons after oxygen deprivation/reoxygenation. In contrast, Fto expression decreased after these perturbations. Our results suggest that knocking down Alkbh5 can aggravate neuronal damage. This is due to the demethylation of Alkbh5 and Fto, which selectively demethylate the Bcl2 transcript, preventing Bcl2 transcript degradation and enhancing Bcl2 protein expression. Conclusion: Collectively, our results demonstrate that the demethylases Alkbh5/Fto co-regulate m 6 A demethylation, which plays a crucial role in cerebral ischemia-reperfusion injury. The results provide novel insights into potential therapeutic mechanisms for stroke.

Plant and algal LDs are gaining popularity as a promising non-chemical technology for the production of lipids and oils. In general, these organelles are composed of a neutral lipid core surrounded by a phospholipid monolayer and various surface-associated proteins. Many studies have shown that LDs are involved in numerous biological processes such as lipid trafficking and signaling, membrane remodeling, and intercellular organelle communications. To fully exploit the potential of LDs for scientific research and commercial applications, it is important to develop suitable extraction processes that preserve their properties and functions. However, research on LD extraction strategies is limited. This review first describes recent progress in understanding the characteristics of LDs, and then systematically introduces LD extraction strategies. Finally, the potential functions and applications of LDs in various fields are discussed. Overall, this review provides valuable insights into the properties and functions of LDs, as well as potential approaches for their extraction and utilization. It is hoped that these findings will inspire further research and innovation in the field of LD-based technology.

Marine coral sand–clay mixtures (MCCM) are promising green fill materials in civil engineering projects, where their strength characteristics play a vital role in ensuring structural safety and stability. To investigate these properties, a series of triaxial shear tests were performed under diverse conditions, including variations in asperity spacing, asperity height, the number of reinforcement layers, confining pressure, and axial strain. This experimental campaign yielded a robust strength dataset for MCCM. Utilizing this dataset, several predictive models were developed, including a standard Support Vector Machine (SVM), an SVM optimized via Genetic Algorithm (GA-SVM), an SVM enhanced by Particle Swarm Optimization (PSO-SVM), and a hybrid model incorporating Logical Development Algorithm preprocessing a SVM model (LDA-SVM). Among these models, the LDA-SVM model exhibited the best performance, achieving a test RMSE of 1.67245 and a correlation coefficient (R) of 0.996, demonstrating superior prediction accuracy and strong generalization ability. Sensitivity analyses revealed that asperity spacing, asperity height, and confining pressure are the most influential factors affecting MCCM strength. Moreover, an explicit empirical equation was derived from the LDA-SVM model, allowing practitioners to estimate strength without relying on complex machine learning tools. The results of this study offer practical guidance for the optimized design and safety evaluation of MCCM in civil engineering applications.

Marine coral sand-clay mixtures (MCCM) are widely used as fill materials in ocean engineering, where their strength is influenced by marine clay content. This study investigates the mechanical behavior of textured polymer layer-reinforced MCCM using 3D-printed technology with varying asperity heights, spacings, and reinforcement layers. Triaxial tests reveal that increased reinforcement, higher asperities, and smaller spacings enhance strength and internal friction angle with minimal effect on cohesion. Particle breakage increases with reinforcement, and fractal analysis shows a linear relationship between fractal dimension and breakage rate. SEM images reveal the complex interfacial interaction mechanisms between the MCCM and the polymer layer. A comprehensive dataset from these tests supports the development of predictive models, including BPNN, GA-BPNN, PSO-BPNN, and LDA-BPNN, with the LDA-BPNN showing the highest accuracy and generalization. Compared with existing approaches, the proposed model framework achieves significant improvements in predictive performance and robustness. Sensitivity analysis identifies asperity spacing and asperity height as key factors. An empirical formula derived from the LDA-BPNN enables practical strength prediction, offering valuable guidance for marine construction design.