The effects of simvastatin on the bone microstructure and mechanics of ovariectomized mice: a micro-CT and micro-finite element analysis study.

BACKGROUND: Osteoporosis is a major health concern for postmenopausal women, and the effect of simvastatin (Sim) on bone metabolism is controversial. This study aimed to investigate the effect of simvastatin on the bone microstructure and bone mechanical properties in ovariectomized (OVX) mice. METHODS: 24 female C57BL/6J mice (8-week-old) were randomly allocated into three groups including the OVX + Sim group, the OVX group and the control group. At 8 weeks after operation, the L4 vertebral bones were dissected completely for micro-Computed Tomography (micro-CT) scanning and micro-finite element analysis (µFEA). The differences between three groups were compared using ANOVA with a LSD correction, and the relationship between bone microstructure and mechanical properties was analyzed using linear regression. RESULTS: Bone volume fraction, trabecular number, connectivity density and trabecular tissue mineral density in the OVX + Sim group were significantly higher than those in the OVX group (P < 0.05). For the mechanical properties detected via µFEA, the OVX + Sim group had lower total deformation, equivalent elastic strain and equivalent stress compared to the OVX group (P < 0.05). In the three groups, the mechanical parameters were significantly correlated with bone volume fraction and trabecular bone mineral density. CONCLUSIONS: The findings suggested that simvastatin had a potential role in the treatment of osteoporosis. The results of this study could guide future research on simvastatin and support the development of simvastatin-based treatments to improve bone health.

First report of leaf rot on Lonicera japonica caused by Rhizopus arrhizus in China.

Lonicera japonica is a perennial shrub that has been used since ancient times as a medicine to clear heat and detoxify poisons. Its branches (the vine of L. japonica) and unopened flower buds (honeysuckle) can be used as medicine to treat external wind heat or febrile disease fever (Shang, Pan, Li, Miao, & Ding, 2011). In July 2022, a serious disease was observed in L. japonica individuals planted in an area of experimental base of Nanjing Agricultural University (N 32°02', E 118°86'), Nanjing, Jiangsu Province, China. More than 200 Lonicera plants were surveyed, and the incidence of leaf rot in Lonicera leaves was over 80%. The initial symptoms were of chlorotic spots and gradual development of visible white mycelia and powdery substances (fungal spores) were observed on the leaves. Both the front and back of the leaves gradually appeared as brown diseased spots. Thus, a combination of multiple disease spots causes leaf wilting and the leaves eventually fall off. Leaves with typical symptoms were collected and cut into approximately 5 mm square fragments. The tissues were sterilized in 1% NaOCl for 90 s and 75% ethanol for 15 s and then washed with sterile water three times. The treated leaves were cultured on Potato Dextrose Agar (PDA) medium at 25℃. When mycelia grew around the leaf pieces, fungal plugs were collected along the outer edge of the colony and transferred to fresh PDA plates using a cork borer. Eight fungal strains with the same morphology were obtained after three rounds of subculturing. The colony was initially white with a fast growth rate, and occupied a 9-cm-diameter culture dish within 24 h. The colony turned gray-black in the later stages. After 2 days, small black sporangia spots appeared on top of the hyphae. The sporangia were yellow when immature, and black at maturity. The spores were oval with an average size of 29.6 (22.4-36.9) × 35.3 (25.8-45.2) µm (n = 50) in diameter. To identify the pathogen, fungal hyphae were scraped, and the fungal genome was extracted using a kit (BioTeke, Cat#DP2031). The internal transcribed spacer region (ITS) of the fungal genome was amplified with primers ITS1/ITS4, and the results of ITS sequencing were uploaded to the GenBank database with accession number OP984201. The phylogenetic tree was constructed using the neighbor-joining method with MEGA11 software. Phylogenetic analysis based on ITS showed that the fungus was grouped together with Rhizopus arrhizus (MT590591) and had high bootstrap support. Thus, the pathogen was identified as R. arrhizus. To verify Koch's postulates, 60 ml of a spore suspension (1×104 conidia/ml) was sprayed onto the surface of 12 healthy Lonicera plants, and the other 12 plants were sprayed with sterile water as a control. All plants were kept in the greenhouse at 25°C with 60% relative humidity. After 14 d, the infected plants showed symptoms similar to those of the original diseased plants. The strain was isolated again from the diseased leaves of artificially inoculated plants and verified as the original strain by sequencing. The results showed that R. arrhizus was the pathogen responsible for Lonicera leaf rot. Previous studies have shown that R. arrhizus causes garlic bulb rot (Zhang et al., 2022) and Jerusalem artichoke tuber rot (Yang et al., 2020). To our knowledge, this is the first report of R. arrhizus causing Lonicera leaf rot disease in China. Information regarding the identification of this fungus may be helpful for controlling the leaf rot disease.

Hybrid wavelength selection strategy combined with ATR-FTIR spectroscopy for preliminary exploration of vintage labeling traceability of sauce-flavor baijiu.

The allure of substantial profits has perpetuated the illicit trade of counterfeit vintage labels for baijiu. While various approaches have been employed to intelligently ascertain the vintage of baijiu, many of them are both cost-intensive and time-consuming. This work pioneered the use of Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometric analysis, offering a non-destructive and economically viable method for discriminating sauce-flavor baijiu across different aging periods (1-, 2-, and 3-year). In this research, principal component analysis (PCA) was first conducted to explore clustering trends among distinct vintage groups. Subsequently, the effect of spectral pre-processing on modeling performance was explored. For wavelength selection, four wavelength selection methods (ReliefF, random forest variable importance (RFVI), variable importance in projection (VIP), and Venn) were first used to identify the subset of candidate features that potentially best mapped the vintage labels. Immediately following this, to explore the possibility of further improving the identification capabilities of the model as well as to reduce the redundant data that may still be present, sequential backward selection (SBS) was utilized for secondary feature reduction within the subset of candidates. The amalgamation of these two techniques is termed a "hybrid wavelength selection strategy." Additionally, the dimensionality reduction effects of PCA and kernel principal component analysis (KPCA) were compared to demonstrate the robustness of the proposed method. Finally, classification models such as partial least squares discriminant analysis (PLS-DA), random forest (RF), and grasshopper optimization algorithm-based support vector machine (GOA-SVM) were developed. The results show that the spectral data need not be pre-processed, and the proposed hybrid wavelength selection strategy can further improve the identification ability of the model. Among the many models developed, ReliefF-SBS-GOA-SVM emerged as the most proficient classification model, yielding accuracy, sensitivity, and specificity rates of 94.44%, 95.23%, and 94.44%, respectively. This method not only holds promise for the discrimination of baijiu class attributes such as brand, origin, flavor, and vintage but also exhibits potential applicability in other non-targeted identification studies involving spectroscopy methodologies.

ATR-FTIR spectroscopy combined with chemometrics to assess the spectral markers of irradiated baijius and their potential application in irradiation dose control.

Although some methods have been proposed for the identification of irradiated baijius, they are often costly, time-consuming, and destructive. It is also unclear what instrumentation can be used to fully characterize the quality changes in irradiated baijius. To address this issue, this study pioneers the use of attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy in combination with chemometrics to open up new avenues for characterizing irradiated baijius and their quality control. Principal component analysis, five spectral pre-processing methods (Savitzky-Golay smoothing (S-G), second-order derivative (SD), multiple scattering correction (MSC), S-G + SD and S-G + MSC), five wavelength selection methods (random forest variable importance (RFVI), two-dimensional correlation spectroscopy (2D-COS), variable importance in projection (VIP), ReliefF, and Venn), and three classification models (partial least squares-discriminant analysis (PLS-DA), random forest (RF), and grasshopper optimization algorithm-based support vector machine (GOA-SVM)) were integrated into the analytical framework of ATR-FTIR spectroscopy, aiming to accurately identify baijiu samples according to different irradiation doses and to search for irradiation-induced spectral difference characteristics (spectral markers). The results showed that SD was the best spectral pre-processing method, and RF models constructed using the 20 most competitive and discriminative spectral markers (selected by Venn) could achieve accurate identification of baijiu samples based on irradiation dose (0, 4, 6, and 8 kGy). After Pearson correlation analysis, the five significantly (P＜0.05) changed spectral markers (1596, 2025, 2309, 2329, and 2380 cm-1) were attributed to changes in the content of total acids, alcohols, and aromatic compounds. These findings demonstrate for the first time the potential of ATR-FTIR spectroscopy as a fast, low-cost, and non-destructive tool for the characterization and identification of irradiated baijiu samples. This approach may also offer a promising solution for labeling management of irradiated foods, vintage identification of baijius, and brand protection.

Manganese induces tumor cell ferroptosis through type-I IFN dependent inhibition of mitochondrial dihydroorotate dehydrogenase.

Ferroptosis is a novel form of regulated cell death characterized by the iron-dependent accumulation of lipid peroxides to lethal levels, which is morphologically, biochemically, and genetically distinct from apoptosis, necroptosis, autophagy, and pyroptosis. Manganese play an important role in innate immunity and antitumor immunity. Many manganese-based nanomaterials induce tumor cell death by catalyzing the production of reactive oxygen species (ROS) within the tumor. However, the exact underlying mechanisms remain unclear. As research on ferroptosis advances and its regulatory mechanisms in tumors continue to be refined, more evidence has suggested that triggering ferroptosis in tumor cells is an effective strategy for tumor treatment. In this study, we found that administration of MnCl2 to tumor cells resulted in lipid peroxidation and increased the levels of mitochondrial ROS, consequently leading to ferroptosis. Dihydroorotate dehydrogenase (DHODH)-mediated ferroptosis defence is a targetable vulnerability in cancer. We show that MnCl2 downregulated DHODH expression in tumor cells, resulting in increased mitochondrial ROS and lipid peroxidation to induce ferroptosis. In addition, MnCl2 enhanced the phosphorylation levels of STING, TBK1, and IRF3 and upregulated the expression of type-I interferon (IFN), produced by the cGAS-STING signaling pathway. When inhibiting the cGAS-STING signaling pathway or type-I IFN, DHODH expression was restored, reversing lipid peroxidation and ROS production and rescuing MnCl2-induced ferroptosis.. Knockout of IFNAR1 or overexpression of DHODH weakens the antitumor effect of MnCl2. Mechanistically, these results revealed that Manganese treatment-activated cGAS-STING signaling promote mitochondrial lipid peroxidation and ROS production by releasing type-I IFNs that reduce DHODH function and thereby inducing ferroptosis in tumor cells. This may provide a new strategy to complement existing antitumor treatment regimens.

Novel EGFR­bispecific recombinant immunotoxin based on cucurmosin shows potent anti­tumor efficiency in vitro.

Epidermal growth factor receptor (EGFR) is overexpressed in various tumors and is associated with cancer initiation, progression, and poor prognosis. Despite the achievements made by tyrosine kinase inhibitors and monoclonal antibodies in certain cases, many patients have not benefited from such treatment due to resistance. Immunotoxins (ITs) are antibody­cytotoxin chimeric molecules with specific cell killing ability, which have achieved different degrees of success in the treatment of a wide range of cancers in clinical trials. The aim of the current study was to examine a novel targeting EGFR recombinant immunotoxin Bs/cucurmosin (CUS) generated by fusing CUS to the EGFR­specific nanobody 7D12­9G8. Bs/CUS was successfully expressed in Escherichia coli strain BL21 (DE3) in a soluble form. Furthermore, it retained binding capacity and specificity with EGFR and was superior to rE/CUS, a monospecific IT we reported previously. In vitro results showed that Bs/CUS could be internalized into the cytoplasm and selectively kill cells in the picomolar range. Flow cytometry showed that Bs/CUS killed the cells mediated by the apoptosis pathway. Taken together, results of the current study indicated that Bs/CUS is a promising candidate that should be further evaluated as a cancer therapeutic for the treatment of EGFR­positive tumors.

Fe-doped cryptomelane synthesized by refluxing at atmosphere: Structure, properties and photocatalytic degradation of phenol.

Fe-doped cryptomelanes were synthesized by refluxing at ambient pressure, followed by characterization with multiple techniques and test in photocatalytic degradation of phenol. The introduction of Fe(III) into the structure of cryptomelane results in a decrease in particle size and the contents of Mn and K(+), and an increase in the Mn average oxidation state (AOS), specific surface area and UV-vis light absorption ability. Mn and Fe K-edge extended X-ray absorption fine structure spectroscopy analysis indicates that some Fe(III) is incorporated into the framework of cryptomelane by replacing Mn(III) while the remaining Fe(3+) is adsorbed in the tunnel cavity. These Fe-doped cryptomelanes have significantly improved the photocatalytic degradation rate of phenol, with the sample of ∼3.04 wt.% Fe doping being the most reactive and achieving a degradation rate of 36% higher than that of the un-doped one. The enhanced reactivity can be ascribed to the increase in the coherent scattering domain size of the crystals, Mn AOS and light absorption, as well as the presence of sufficient K(+) in the tunnel. The results imply that metal doping is an effective way to improve the performance of cryptomelane in pollutants removal and has the potential for modification of Mn oxide materials.