Novel ferrocenyl peptide bioconjugates as anti-cancer agents

The aim of this project was to explore the structure-activity relationship (SAR) of novel ferrocenyl based anti-cancer bioconjugates. A series of N-(1’-methyl-6-ferrocenyl-2-naphthoyl) and N- (1’-ethyl-6-ferrocenyl-2-naphthoyl) amino acid and dipeptide esters and a series of N-(ferrocenylmethylamino acid)-fluorinated-benzene carboxamide derivatives have been synthesized, characterized and biologically evaluated for their anti-proliferative activity on various cancer cell lines. The synthesis of each series of compounds was achieved by coupling the free N-terminus of various amino acid and dipeptide esters to the carboxyl group of methyl and ethyl ferrocenyl naphthoic acid or the free N-terminus of the ferrocenylmethylamine to the carboxylic acid group of the N-(fluorobenzoyl)-amino acid using the conventional N-(3-dimethylaminopropyl)-N’-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) coupling protocol. All compounds were fully characterized by a combination of spectroscopic techniques, including 1H, 13C and 19F NMR, IR, UV-Vis and MS. Biological evaluation was performed in vitro against the human cervical carcinoma cells (ATCC HTB-35, SiHa) and human liver cells (ATCC CCL-13, Chang liver, HeLa markers) for N-(1’-alkyl-6-ferrocenyl-2-naphthoyl) amino acid and dipeptide esters and vincristine. N-(1’-ethyl-6-ferrocenyl-2-naphthoyl)-glycine-D-alanine ethyl ester had an IC50 of 8.75 μM on cervical cancer cells, which is significantly more cytotoxic than chemotherapeutic medication vincristine. And it has low toxicity against Chang liver cells. The results can suggest that there are differences in susceptibilities to novel ferrocenyl amino acid and dipeptide bioconjugates toxicity between cervical carcinoma and liver cells. Therefore N-(1’-ethyl-6-ferrocenyl-2-naphthoyl)-glycine-D-alanine ethyl ester is a potential anti-cancer agent with selectivity. Another series of N-(ferrocenylmethylamino acid) fluorinated benzene carboxamide derivatives were tested on the estrogen positive (ER+) breast cancer cell line, MCF-7. N-(ferrocenylmethyl-L-alanine)-3,4,5-trifluorobenzene carboxamide, N-(ferrocenylmethyl-L-alanine)-2,3,4,5,6-pentafluorobenzene carboxamide and N-(ferrocenylmethylglycine)-2,3,4,5,6-pentafluorobenzene carboxamide all have strong anti-proliferative effects, with the IC50 values between 0.57-2.14 μM

Uptake, sequestration and tolerance of cadmium at cellular levels in the hyperaccumulator plant species Sedum alfredii.

Sedum alfredii is one of a few plant species known to hyperaccumulate cadmium (Cd). Uptake, localization, and tolerance of Cd at cellular levels in shoots were compared in hyperaccumulating (HE) and non-hyperaccumulating (NHE) ecotypes of Sedum alfredii. X-ray fluorescence images of Cd in stems and leaves showed only a slight Cd signal restricted within vascular bundles in the NHEs, while enhanced localization of Cd, with significant tissue- and age-dependent variations, was detected in HEs. In contrast to the vascular-enriched Cd in young stems, parenchyma cells in leaf mesophyll, stem pith and cortex tissues served as terminal storage sites for Cd sequestration in HEs. Kinetics of Cd transport into individual leaf protoplasts of the two ecotypes showed little difference in Cd accumulation. However, far more efficient storage of Cd in vacuoles was apparent in HEs. Subsequent analysis of cell viability and hydrogen peroxide levels suggested that HE protoplasts exhibited higher resistance to Cd than those of NHE protoplasts. These results suggest that efficient sequestration into vacuoles, as opposed to rapid transport into parenchyma cells, is a pivotal process in Cd accumulation and homeostasis in shoots of HE S. alfredii. This is in addition to its efficient root-to-shoot translocation of Cd

Deep learning classification and recognition method for milling surface roughness combined with simulation data

To address the problem that a deep neural network needs a sufficient number of training samples to have a good prediction performance, this paper firstly used the Z-Map algorithm to generate a simulated profile of the milling surface and construct an optical simulation model of surface imaging to supplement the training sample size of the neural network. Then the Deep CORAL model was used to match the textures of the simulated samples and the actual samples across domains to solve the problem that the simulated samples were not in the same domain as the actual milling samples. Experimental results have shown that high texture matching could be achieved between optical simulation images and actual images, laying the foundation for expanding the actual milled workpiece images with the simulation images. The deep convolutional neural model Xception was used to predict the classification of six classes of data sets with the inclusion of simulation images, and the accuracy was improved from 86.48% to 92.79% compared with the model without the inclusion of simulation images. The proposed method solves the problem of the need for a large number of samples for deep neural networks and lays the foundation for similar methods to predict surface roughness for different machining processes

Functional variant of the carboxypeptidase M (CPM) gene may affect silica-related pneumoconiosis susceptibility by its expression: a multistage case-control study.

ObjectivesIn a genome-wide association study, we discovered chromosome 12q15 (defined as rs73329476) as a silica-related pneumoconiosis susceptibility region. However, the causal variants in this region have not yet been reported.MethodsWe systematically screened eight potentially functional single-neucleotide polymorphism (SNPs) in the genes near rs73329476 (carboxypeptidase M (CPM) and cleavage and polyadenylation specific factor 6 (CPSF6)) in a case-control study including 177 cases with silicosis and 204 healthy controls, matched to cases with years of silica dust exposure. We evaluated the associations between these eight SNPs and the development of silicosis. Luciferase reporter gene assays were performed to test the effects of selected SNP on the activity of CPM in the promoter. In addition, a two-stage case-control study was performed to investigate the expression differences of the two genes in peripheral blood leucocytes from a total of 64 cases with silicosis and 64 healthy controls with similar years of silica dust exposure as the cases.ResultsWe found a strong association between the mutant rs12812500 G allele and the susceptibility of silicosis (OR=1.45, 95% CI 1.03 to 2.04, p=0.034), while luciferase reporter gene assays indicated that the mutant G allele of rs12812500 is strongly associated with increased luciferase levels compared with the wild-type C allele (p<0.01). Moreover, the mRNA (peripheral blood leucocytes) expression of the CPM gene was significantly higher in subjects with silicosis compared with healthy controls.ConclusionsThe rs12812500 variant of the CPM gene may increase silicosis susceptibility by affecting the expression of CPM, which may contribute to silicosis susceptibility with biological plausibility

Analysis and Radiometric Calibration for Backscatter Intensity of Hyperspectral LiDAR Caused by Incident Angle Effect

Hyperspectral LiDAR (HSL) is a new remote sensing detection method with high spatial and spectral information detection ability. In the process of laser scanning, the laser echo intensity is affected by many factors. Therefore, it is necessary to calibrate the backscatter intensity data of HSL. Laser incidence angle is one of the important factors that affect the backscatter intensity of the target. This paper studied the radiometric calibration method of incidence angle effect for HSL. The reflectance of natural surfaces can be simulated as a combination of specular reflection and diffuse reflection. The linear combination of the Lambertian model and Beckmann model provides a comprehensive theory that can be applied to various surface conditions, from glossy to rough surfaces. Therefore, an adaptive threshold radiometric calibration method (Lambertian-Beckmann model) is proposed to solve the problem caused by the incident angle effect. The relationship between backscatter intensity and incident angle of HSL is studied by combining theory with experiments, and the model successfully quantifies the difference between diffuse and specular reflectance coefficients. Compared with the Lambertian model, the proposed model has higher calibration accuracy, and the average improvement rate to the samples in this study was 22.67%. Compared with the results before calibration with the incidence angle of less than 70 degrees, the average improvement rate of the Lambertian-Beckmann model was 62.26%. Moreover, we also found that the green leaves have an obvious specular reflection effect near 650-720 nm, which might be related to the inner microstructure of chlorophyll. The Lambertian-Beckmann model was more helpful to the calibration of leaves in the visible wavelength range. This is a meaningful and a breakthrough exploration for HSL.Peer reviewe

Associations between composite dietary antioxidant index and estimated 10-year atherosclerotic cardiovascular disease risk among U.S. adults

BackgroundAtherosclerotic cardiovascular disease (ASCVD) remains the leading cause of death and disability both in U.S. and worldwide. Antioxidants have been proved critical in mitigating the development of atherosclerosis. This study aimed to investigate the associations between composite dietary antioxidant index (CDAI) and estimated 10-year ASCVD risk among U.S. adults.MethodsData extracted from the National Health and Nutrition Examination Survey were analyzed. A total of 10,984 adults aged 18 years and above were included in this study. CDAI was calculated based on the dietary intake reported in their 24-h recall interviews. The estimated 10-year ASCVD risk was calculated via Pooled Cohort Equations (PCE).ResultsAfter adjusting potential confounders, it was indicated that CDAI score was negatively correlated with 10-year ASCVD risk (OR 0.97, 95% CI 0.95–0.99). Stratify CDAI score by quartile, results showed that participants in the second, third, and fourth quartiles had lower ASCVD odds ratio (Q2: OR 0.87, 95% CI 0.69–1.09; Q3: OR 0.78, 95% CI 0.62–0.98; Q4: OR 0.74, 95% CI 0.59–0.94) than those in the first quartile (Q1, lowest CDAI score group), which was confirmed by the trend test as well (p < 0.05). Subgroup analyses stratified by sex, age, race/ethnicity, and smoking status did not show significant effect modification.ConclusionHigher dietary antioxidants intake is associated with lower ASCVD risk among U.S. adults, for which policymakers and healthcare professionals may consider increasing the consumption of antioxidant-rich foods as a preventive strategy for ASCVD

Deepened winter snow cover enhances net ecosystem exchange and stabilizes plant community composition and productivity in a temperate grassland

Global warming has greatly altered winter snowfall patterns, and there is a trend towards increasing winter snow in semi-arid regions in China. Winter snowfall is an important source of water during early spring in these water-limited ecosystems, and it can also affect nutrient supply. However, we know little about how changes in winter snowfall will affect ecosystem productivity and plant community structure during the growing season. Here, we conducted a 5-year winter snow manipulation experiment in a temperate grassland in Inner Mongolia. We measured ecosystem carbon flux from 2014 to 2018 and plant biomass and species composition from 2015 to 2018. We found that soil moisture increased under deepened winter snow in early growing season, particularly in deeper soil layers. Deepened snow increased the net ecosystem exchange of CO 2 (NEE) and reduced intra- and inter-annual variation in NEE. Deepened snow did not affect aboveground plant biomass (AGB) but significantly increased root biomass. This suggested that the enhanced NEE was allocated to the belowground, which improved water acquisition and thus contributed to greater stability in NEE in deep-snow plots. Interestingly, the AGB of grasses in the control plots declined over time, resulting in a shift towards a forb-dominated system. Similar declines in grass AGB were also observed at three other locations in the region over the same time frame and are attributed to 4 years of below-average precipitation during the growing season. By contrast, grass AGB was stabilized under deepened winter snow and plant community composition remained unchanged. Hence, our study demonstrates that increased winter snowfall may stabilize arid grassland systems by reducing resource competition, promoting coexistence between plant functional groups, which ultimately mitigates the impacts of chronic drought during the growing season