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Lactic acid bacteria (LAB) are probiotic bacteria that are used to ferment various lactic-fermented foods, such as yogurt, kimchi, some wines, soy sauce, and cured meats. Lactobacillus gasseri, a human-sourced LAB species, has a variety of probiotic effects, including maintaining gastrointestinal homeostasis, promoting vaginal health, regulating immunity, treating obesity, and providing antioxidant activity. There is increasing research interest in L. gasseri, but there are few sources or isolated strains of L. gasseri, necessitating the screening of functionally enriched strains from different sources to discover new useful strains. This review summarizes methods for identification and screening of L. gasseri, building upon previous studies, discusses the functions and applications of L. gasseri in food and its limitations and future development trends. The aim is to provide a theoretical basis for the future application of L. gasseri in the development of new types of food additives, dietary supplements, and biotherapeutic agents. [ABSTRACT FROM AUTHOR]

Exploring the different spin states of central metals in the complex to regulate the anti-tumor activity of cancer cells is of great significance in drug design and clinical use. However, it is a challenge to build a strong coupling between spin states and anti-tumor activities in one system. Herein, we present two complexes {FeII2L2[PdII(CN)4]2}·2H2O (L = Bztpen (1), Bztppn (2); Bztpen = N-benzyl-N,N′,N′-tris(2-pyridylmethyl)ethylenediamine, Bztppn = N-benzyl-N,N′,N′-tris(2-pyridylmethyl)propylenediamine) showing different cytotoxic activities actuated by fine-tuning the structure with different spin states of Fe(II). Magnetic susceptibility measurements and X-ray diffraction revealed that the Fe(II) ion in complexes 1 and 2 remains in the LS and HS state, respectively, at room temperature. Cytotoxicity tests indicate that complex 1 is more biologically effective than complex 2. In complex 2, however, the high-spin Fe(II) played a key role in regulating its in vitro antitumor effects and seems to be associated with ROS-mediated apoptosis. These findings offer a new avenue for developing anti-cancer drugs by designing complexes with different spin states. [ABSTRACT FROM AUTHOR]

Mitochondria play a crucial role in mediating apoptosis and have emerged as a promising therapeutic target for the treatment of cancer. Nevertheless, exploration of mitochondrial apoptosis as a mechanism for anticancer activity in vitro remains notably sparse. Herein, the ligands 4′,4″′‐(phenylazanediyl)bis(([1,1′‐biphenyl]‐4‐carboxylic acid)) (H2L1) and 4′,4″′‐(phenylazanediyl)bis(3‐fluoro‐[1,1′‐biphenyl]‐4‐carboxylic acid) (H2L2) were synthesized and further combined with organotin precursors and auxiliary ligands (4,4′‐bipy = 4,4′‐bipyridine, 4,4′‐bpe = 4,4′‐vinylenedipyridine) to give eight organotin complexes [(Ph3Sn)2L] (1a and 2a), [(Et3Sn)2L]n (1b and 2b), [(n‐Bu3Sn)2L(4,4′‐bipy)]n (1c and 2c), [(n‐Bu3Sn)2L(4,4′‐bpec)]n (1d and 2d). The complexes were characterized by X‐ray single crystal diffraction, NMR (1H, 13C, and 119Sn), IR, and UV–Vis spectroscopy. The complexes exhibited strong anticancer activity against the four cancer cells and a certain degree of broad‐spectrum with the IC50 ranging from 0.25 to 22.43 μM. Furthermore, complexes 2a and 2b were selected as representatives to further investigate their anticancer mechanisms. The results suggested that these complexes could target mitochondria after cellular uptake, thereby inducing intracellular ROS production, leading to MMP collapse and activation of caspase‐3, that is, these complexes potentially exert their anticancer effects through the mitochondria‐mediated apoptotic pathway. [ABSTRACT FROM AUTHOR]

To make an accurate estimation of leaf are index (LAI) based on machine learning methods and images from UAV, we compared the several mainstream machine learning methods for maize LAI prediction, such as Artificial Neural Network method (ANN), Gaussian Process Regression method (GPR), Support Vector Regression method (SVR), and Gradient Boosting Decision Tree (GBDT). For this purpose, field experiments that considering apply of different amount of organic fertilizer, different amount of inorganic fertilizer, different amount of crop residue, and different planting density were carried out. Based on these experiments, field campaign were conducted to obtain UAV multispectral images and LAI data at different growth stages in maize. Based on above data, firstly, correlation analysis was used to select LAI-sensitive spectral indices, and then the Partial Least Squares Regression method (PLSR) and ANN, GPR, SVR, GBDT were coupled to design the LAI prediction models, respectively, and their performance for LAI prediction were compared. The results showed that the LAI prediction model constructed by PLSR+GBDT method had the highest accuracy and the best stability. The models of R² and RMSE values were 0.90 and 0.25, and the verified R² and RMSE values were 0.90 and 0.29 during validation, respectively. The model based on PLSR+GPR model was followed, with R² and RMSE values of 0.86 and 0.30 during calibration, and R² and RMSE values of 0.89 and 0.29 during validation, respectively. Besides, it had faster training speed and could give the uncertainty of the prediction. The model designed by PLSR+ANN method had R² and RMSE values of 0.85 and 0.31 during calibration, and R² and RMSE values of 0.89 and 0.30 during validation, respectively. The model designed by PLSR+SVR method had R² and RMSE values of 0.86 and 0.32, and R² and RMSE values of 0.90 and 0.33, respectively. Therefore, PLSR+GBDT method and PLSR+GPR method are recommended as the optimal methods for designing maize LAI prediction models. [ABSTRACT FROM AUTHOR]

High‐entropy alloy nanoparticles (HEA NPs) have aroused great interest globally with their unique electrochemical, catalytic, and mechanical properties, as well as diverse activity and multielement tunability for multi‐step reactions. Herein, a facile low‐temperature synthesis method at atmospheric pressure is employed to synthesize Pd‐enriched‐HEA‐core and Pt‐enriched‐HEA‐shell NPs with a single phase of face‐centred cubic structure. Interestingly, the lattice of both Pd‐enriched‐HEA‐core and Pt‐enriched‐HEA‐shell enlarge during the formation process of HEA, with tensile strains included in the core and shell of HEA. The as‐obtained PdAgSn/PtBi HEA NPs show excellent electrocatalytic activity and durability for methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR). The specific (mass) activity of PdAgSn/PtBi HEA NPs for MOR is 4.7 mA cm−2 (2874 mA mg(Pd+Pt)−1), about 1.7 (5.9) and 1.5 (4.8) times higher than that of commercial Pd/C and Pt/C catalysts, respectively. Additional to high‐entropy effect, Pt sites and Pd sites on the interface of the HEA act synergistically to facilitate the multi‐step process towards EOR. This study offers a promising way to find a feasible route for scalable HEA manufacturing with promising applications. [ABSTRACT FROM AUTHOR]