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The severity of soil molybdenum (Mo) pollution is increasing, and effective management of contaminated soil is essential for the sustainable development of soil. To investigate this, a pot experiment was carried out to assess the impact of different rates of humic acid (HA) and fulvic acid (FA) on the mobility of Mo in soil solution and its uptake by alfalfa, wheat and green bristlegrass. The concentration of Mo in Plants and soil was determined using an Atomic Absorption Spectrophotometer. The findings revealed that the application of HA led to an increase in Mo accumulation in the shoot and root of green bristlegrass and wheat, ranging from 10.56 % to 28.73 % and 62.15–115.79 % (shoot), and 17.52–46.53 % and 6.29-81.25 % (root), respectively. Nonetheless, the use of HA resulted in a slight inhibition of plant Mo uptake, leading to reduced Mo accumulation in alfalfa roots compared to the control treatment (from 3284.49 mg/kg to 2140.78–2813.54 mg/kg). On the other hand, the application of FA decreased Mo accumulation in the wheat shoot (from 909.92 mg/kg to 338.54–837.45 mg/kg). Furthermore, the bioavailability of green bristlegrass (with HA) and wheat (with FA) decreased, and the percentage of residual fraction of Mo increased (from 0.39 % to 0.78–0.96 %, from 3.95 % to 3.97∼ 4.34 %). This study aims to elucidate the ternary interaction among Mo, humic substances, and plants (alfalfa, wheat, and green bristlegrass), to enhance both the activation and hyperaccumulation of Mo simultaneously.

Abstract Contamination of soils by Molybdenum (Mo) has raised increasing concern worldwide. Both fulvic acid (FA) and humic acid (HA) possess numerous positive properties, such as large specific surface areas and microporous structure that facilitates the immobilization of the heavy metal in soils. Despite these characteristics, there have been few studies on the microbiology effects of FA and HA. Therefore, this study aimed to assess the Mo immobilization effects of FA and HA, as well as the associated changes in microbial community in Mo-contaminated soils (with application rates of 0%, 0.5% and 1.0%). The result of the incubation demonstrated a decrease in soil pH (from 8.23 ~ 8.94 to 8.05 ~ 8.77). Importantly, both FA and HA reduced the exchangeable fraction and reducible fraction of Mo in the soil, thereby transforming Mo into a more stable form. Furthermore, the application of FA and HA led to an increase in the relative abundance of Actinobacteriota and Firmicutes, resulting in alterations to the microbial community structure. However, it is worth noting that due to the differing structures and properties of FA and HA, these outcomes were not entirely consistent. In summary, the aging of FA and HA in soil enhanced their capacity to immobilization Mo as a soil amendment. This suggests that they have the potential to serve as effective amendments for the remediation of Mo-contaminated soils.

Mn oxides are confined within the porous structure of activated coke (ACO) via impregnation followed by calcination treatment. The Mn-ACO sample calcined at 600 °C (Mn-ACO600) demonstrated superior performance despite containing only a minute atomic ratio of 0.11 % Mn on its surface. This treatment led to a slight increase in the specific surface area and pore volume of ACO, with a significant enhancement in the proportion of micropores, rising from 54.2 % in ACO to 71.8 % in Mn-ACO600. Raman spectroscopy indicated additional defects in Mn-ACO, while XPS analysis confirmed the coexistence of Mn(II), Mn(III), and Mn(IV) oxides. Although ACO adsorption alone was ineffective in removing acesulfame (ACE), Mn-ACO600 achieved a removal rate of 19.0 %. The introduction of peroxydisulfate (PDS) further boosted the degradation of Mn-ACO600, with a Kapp value that was 2.28 times of that of the combined Mn-ACO600 adsorption and PDS oxidation process, indicating a remarkable synergistic effect. To optimize the experimental conditions, a response surface methodology design analysis was conducted, revealing that solution pH and the dosage of Mn-ACO600 were crucial factors. Furthermore, the study confirmed non-radical oxidizing species, such as 1O2 and h+, played a predominant role in the process, with relatively minor contributions from radical oxidizing species.

AbstractTraditional landslide susceptibility assessment methods often rely on single models, which can be biased and less accurate. In this article, we introduce a two-tiered strategy to enhance landslide susceptibility predictions. Initially, we employ an ensemble stacking technique that combines the strengths of three machine learning classifiers. This combination leverages the support vector classifier (SVC) as the key meta-classifier to optimize and refine predictions. Subsequently, we integrate the extreme gradient boosting (XGB), random forest (RF) and gradient boosting decision tree (GBDT) models with SVC to create hybrid approaches. In this study, we evaluate and compare the effectiveness of six machine learning algorithms for predicting landslide susceptibility in Anhua County, Hunan Province, China. The results demonstrated that the stacking ensemble model outperforms traditional models. The XBG+SVC model achieves the highest AUC value (0.9468), which is followed by the GBDT+SVC (0.9316), RF+SVC (0.9162), XGB (0.9393), GBDT (0.9009), and RF (0.8693). These findings indicate that stacking machine learning approaches hold promise for landslide susceptibility mapping.

H4O14CoV4.4, monolinic, P2/m (no. 10), a = 8.1091(8) Å, b = 3.5128(2) Å, c = 9.7590(9) Å, β = 111.553(11)°, V = 258.55(4) Å3, Z = 1, Rgt(F) = 0.0401, wRref(F2) = 0.0922, T = 293(2) K.

In this study, we designed and developed a DOX nanodrug delivery system (PEG-GA@ZIF-8@DOX) using ZIF-8 as the carrier and glycyrrhetinic acid (GA) as the targeting ligand. We confirmed that DOX was loaded and PEG-GA was successfully modified on the surface of the nanoparticles. The in vitro release profile of the system was investigated at pH 5.0 and 7.4. The cellular uptake, in vitro cytotoxicity, and lysosomal escape characteristics were examined using HepG2 cells. We established an H22 tumor-bearing mouse model and evaluated the in vivo antitumor activity. The results showed that the system had a uniform nanomorphology. The drug loading capacity was 11.22 ± 0.87%. In acidic conditions (pH 5.0), the final release rate of DOX was 57.73%, while at pH 7.4, it was 25.12%. GA-mediated targeting facilitated the uptake of DOX by the HepG2 cells. PEG-GA@ZIF-8@DOX could escape from the lysosomes and release the drug in the cytoplasm, thus exerting its antitumor effect. When the in vivo efficacy was analyzed, we found that the tumor inhibition rate of PEG-GA@ZIF-8@DOX was 67.64%; it also alleviated the loss of the body weight of the treated mice. This drug delivery system significantly enhanced the antitumor effect of doxorubicin in vitro and in vivo, while mitigating its toxic side effects.