The determinants of effective defluorination by the LiAl-LDHs.

Millions of people in poor areas are still under the threat of fluoride contamination. How to effectively separate fluorine in water is an important step to reduce the ecological risk. In this paper, we performed a systematic DFT calculation focused on the defluorination behavior between the LiAl- and MgAl-LDHs. The results indicated that the LiAl-LDHs exhibited high chemical activity before the defluorination, because of the better electronic structure. After the defluorination, the LiAl-LDHs with adsorbed-F- were also more stable than the MgAl-LDHs. In addition, the existence of coordination covalent bond for the adsorbed-F- attached to the LiAl-LDHs was confirmed. This is an important reason for the high defluorination efficiency by the LiAl-LDHs. In addition, a series of weak interaction, including hydrogen bond and van der Waals interaction were also observed. Finally, a LiAl-LDHs with excellent fluoride removal properties were synthesized well by simple hydrothermal method. The results showed that our synthesized LiAl-LDHs with the capacity of 156.09 mg/g, could be effectively defluorinated in water. Notably, it surpasses most materials and has potential applications.

The role of doped-Mn on enhancing arsenic removal by MgAl-LDHs.

To meet the challenges posed by global arsenic water contamination, the MgAlMn-LDHs with extraordinary efficiency of arsenate removal was developed. In order to clarify the enhancement effect of the doped-Mn on the arsenate removal performance of the LDHs, the cluster models of the MgAlMn-LDHs and MgAl-LDHs were established and calculated by using density functional theory (DFT). The results shown that the doped-Mn can significantly change the electronic structure of the LDHs and improve its chemical activity. Compared with the MgAl-LDHs that without the doped-Mn, the HOMO-LUMO gap was smaller after doping. In addition, the -OH and Al on the laminates were also activated to improve the adsorption property of the LDHs. Besides, the doped-Mn existed as a novel active site. On the other hand, the MgAlMn-LDHs with the doped-Mn, the increased of the binding energy, as well as the decreased of the ion exchange energy of interlayer Cl-, making the ability to arsenate removal had been considerably elevated than the MgAl-LDHs. Furthermore, there is an obvious coordination covalent bond between arsenate and the laminates of the MgAlMn-LDHs that with the doped-Mn.

To live or die: "Fine-tuning" adaptation revealed by systemic analyses in symbiotic bathymodiolin mussels from diverse deep-sea extreme ecosystems.

Hydrothermal vents (HVs) and cold seeps (CSs) are typical deep-sea extreme ecosystems with their own geochemical characteristics to supply the unique living conditions for local communities. Once HVs or CSs stop emission, the dramatic environmental change would pose survival risks to deep-sea organisms. Up to now, limited knowledge has been available to understand the biological responses and adaptive strategy to the extreme environments and their transition from active to extinct stage, mainly due to the technical difficulties and lack of representative organisms. In this study, bathymodiolin mussels, the dominant and successful species surviving in diverse deep-sea extreme ecosystems, were collected from active and extinct HVs (Southwest Indian Ocean) or CSs (South China Sea) via two individual cruises. The transcriptomic analysis and determination of multiple biological indexes in stress defense and metabolic systems were conducted in both gills and digestive glands of mussels, together with the metagenomic analysis of symbionts in mussels. The results revealed the ecosystem- and tissue-specific transcriptional regulation in mussels, addressing the autologous adaptations in antioxidant defense, energy utilization and key compounds (i.e. sulfur) metabolism. In detail, the successful antioxidant defense contributed to conquering the oxidative stress induced during the unavoidable metabolism of xenobiotics commonly existing in the extreme ecosystems; changes in metabolic rate functioned to handle toxic matters in different surroundings; upregulated gene expression of sulfide:quinone oxidoreductase indicated an active sulfide detoxification in mussels from HVs and active stage of HVs & CSs. Coordinately, a heterologous adaptation, characterized by the functional compensation between symbionts and mussels in energy utilization, sulfur and carbon metabolism, was also evidenced by the bacterial metagenomic analysis. Taken together, a new insight was proposed that symbiotic bathymodiolin mussels would develop a "finetuning" strategy combining the autologous and heterologous regulations to fulfill the efficient and effective adaptations for successful survival.

Development of a Machine Learning Algorithm to Forecast the Likelihood of Postoperative Neurological Complications in Patients With Parotid Tumors.

Objective: The objective of this study was to create and verify a machine learning-driven predictive model to forecast the likelihood of facial nerve impairment in patients with parotid tumors following surgery. Methods: We retrospectively collected data from patients with parotid tumors between 2013 and 2023 to develop a prediction model for postoperative facial nerve dysfunction using 5 ML techniques: Logistic Regression (Logit), Random Forest (RF), XGBoost (XGB), Artificial Neural Network (ANN), and Support Vector Machine (SVM). Predictor variables were screened using binomial-LASSO regression. Results: The study had a total of 403 participants, out of which 56 individuals encountered facial nerve damage after the surgery. By employing binomial-LASSO regression, we have successfully identified 8 crucial predictive variables: tumor kind, tumor pain, surgeon's experience, tumor volume, basophil percentage, red blood cell count, partial thromboplastin time, and prothrombin time. The models utilizing ANN and Logit achieved higher area under the curve (AUC) values, namely 0.829, which was significantly better than the SVM model that had an AUC of 0.724. There were no noticeable disparities in the AUC values between the ANN and Logit models, as well as between these models and other techniques like RF and XGB. Conclusion: Using machine learning, our prediction model accurately predicts the likelihood that patients with parotid tumors may experience facial nerve damage following surgery. By using this model, doctors can assess patients' risks more accurately before to surgery, and it may also help optimize postoperative treatment techniques. It is anticipated that this tool would enhance patients' quality of life and therapeutic outcomes.

Comparative study of integrated bio-responses in deep-sea and nearshore mussels upon abiotic condition changes: Insight into distinct regulation and adaptation.

Deep-sea mussels, one of the dominant species in most deep-sea ecosystems, have long been used as model organisms to investigate the adaptations and symbiotic relationships of deep-sea macrofauna under laboratory conditions due to their ability to survive under atmospheric pressure. However, the impact of additional abiotic conditions beyond pressure, such as temperature and light, on their physiological characteristics remains unknown. In this study, deep-sea mussels (Gigantidas platifrons) from cold seep of the South China Sea, along with nearshore mussels (Mytilus coruscus) from the East China Sea, were reared in unfavorable abiotic conditions for up to 8 days. Integrated biochemical indexes including antioxidant defense, immune ability and energy metabolism were investigated in the gill and digestive gland, while cytotoxicity was determined in hemocytes of both types of mussels. The results revealed mild bio-responses in two types of mussels in the laboratory, represented by the effective antioxidant defense with constant total antioxidant capability level and malondialdehyde content. There were also disparate adaptations in deep-sea and nearshore mussels. In deep-sea mussels, significantly increased immune response and energy reservation were observed in gills, together with the elevated cytotoxicity in hemocytes, implying the more severe biological adaptation was required, mainly due to the symbiotic bacteria loss under laboratory conditions. On the contrary, insignificant biological responses were exhibited in nearshore mussels except for the increased energy consumption, indicating the trade-off strategy to use more energy to deal with potential stress. Overall, this comparative study highlights the basal bio-responses of deep-sea and nearshore mussels out of their native environments, providing evidence that short-term culture of both mussels under easily achievable laboratory conditions would not dramatically alter their biological status. This finding will assist in broadening the application of deep-sea mussels as model organism in future research regardless of the specialized research equipment.

Analysis of rice characteristic volatiles and their influence on rice aroma.

Rice aroma, one of the most important qualities of rice, was the comprehensive result of volatiles in rice and human sense. In this study, the main volatile compounds in rice were analyzed by using gas chromatography-mass spectrometry and gas chromatography-olfactometry, and their correlations with sensory score were investigated. A total of eighty-five volatiles were found in rice samples. By combining odor activity value and correlation analysis, nine volatiles were considered as potential characteristic volatiles in rice aroma, namely hexanal, 2-pentylfuran, octanal, 2-acetyl-1-pyrroline (2-AP), 1-octen-3-ol, trans-2-octenal, decanal, trans-2-nonenal and trans, trans-2,4-decadienal. It was found that the volatiles negatively correlated with sensory scores were positively correlated with hexanal. It indicated that hexanal might be a representative of the negative volatiles of rice aroma. The effects of the nine potential characteristic volatiles on rice aroma were investigated by using sensory analysis. The results showed that the odor intensity and preference level of 2-AP, hexanal, and 1-octen-3-ol were significantly affected by the content. Furthermore, the aroma of cooked rice was significantly different after adding 2-AP, hexanal or trans, trans-2,4-decadienal. Rice aroma was increased by adding 2-AP and deteriorated by adding hexanal or trans, trans-2,4-decadienal, indicating that 2-AP contributed positively to rice aroma while hexanal and trans, trans-2,4-decadienal contributed negatively to rice aroma. Hexanal, 2-AP, and trans, trans-2,4-decadienal were suggested to be the key characteristic volatiles for future aroma evaluation.

Design of a high-performance ternary LDHs containing Ni, Co and Mn for arsenate removal.

To cope with the current serious arsenate pollution problem, a new ternary layered double hydroxides (LDHs) containing Ni, Co and Mn with good performance was developed, guiding by DFT calculations. First, Ni, Co and Mn were screened as the metal sources to constitute the LDHs, due to their high ionic charge density. Then, Ni(II), Co(II) and Mn(III)-O octahedra were selected as the primary units for structuring the LDHs, because of their good chemical activity. Meanwhile, the ratio of metals in the ternary LDHs, favoring for arsenate removal, was optimized at 1:2:1. In addition, the synergistic effect among various metals in the LDHs was considered. The results suggested that in the case of single doping, all three metals can act as the center to promote chemical activity independently. On the contrary, when combined together, there is only one unilateral active center. Moreover, the existence of ligand covalent bonds between arsenate and LDHs was confirmed. Finally, a promising new NiCo2Mn-LDHs with the maximum adsorption capacity of 407.23 mg/g for arsenate removal had been prepared.

As(III) removal from wastewater and direct stabilization by in-situ formation of Zn-Fe layered double hydroxides.

In order to remove and stabilize As(III) simultaneously from wastewater, a novel and effective method based on the in-situ formation of As(III)-containing Zn-Fe layered double hydroxides (ZnFe-As-LDHs) was developed. The influence of pH, Zn/Fe, Fe/As and adding rate on the formation of ZnFe-As-LDHs were investigated. Under the optimal conditions, the concentration of As(III) decreased from 100 to 0.13 mg/L and As leaching concentration of the ultimate sludge was 1.87 mg/L, which could meet the arsenic leaching criteria (5 mg/L) regulated by US EPA. Compared with the "ex-situ" sludge obtained by As(III) adsorbed on the pre-formed ZnFe-LDHs, the As(III) removal efficiency increased by 21.6 % and the stability of the sludge increased by 94.2 % on the in-situ formation of LDHs, which mainly attributed to 55.06 % oxidation of As(III) and co-precipitation of As with Zn and Fe. Additionally, a possible in-situ formation pathway for ZnFe-As-LDHs was illustrated. At the beginning of the process, non-crystalline ferric arsenate formed and then transformed to amorphous ferrihydrite as precursors, followed by the formation of LDHs. This work demonstrated that co-precipitating As with Zn and Fe in the wastewater to in-situ form LDHs exhibited excellent potential for removal and direct stabilization of As(III).