Hydroxyl group-induced enhancement of antioxidant activity of resveratrol over pterostilbene by binding to lactoferrin

The reduced antioxidant capacity of trans-resveratrol (Res) than the second generation of Res, namely pterostilbene (Pte), severely prohibits its in-depth intriguing radical-scavenging applications in food formulations. Herein, a unique chemical structure-dependent strategy was proposed to specifically enhance the radical scavenging activity of Res over Pte, relying on the two more hydroxyl groups on the A-benzene ring of Res, thus facilitating its binding with lactoferrin (LF) to form stable complexes through more hydrogen bonds. We prepared LF-Res and LF-Pte complexes, revealed their binding mechanisms by multispectral analysis and molecular docking/dynamics simulations, further evaluated their antioxidant properties via ABTS and DPPH assays and a model of inhibiting apple browning, eventually elucidated their structure-binding-property relationships. This contribution offers a new approach to restore the antioxidant capability of Res, also paves the way to precisely regulate the fascinating bioactivities of hydrophobic compounds by protein-binding in a chemical structure-, especially hydroxyl group-dependent manner.

Inhibition Effect of Okanin Toward Human Cytochrome P450 3A4 and 2D6 with Multi-spectroscopic Studies and Molecular Docking

Okanin, a major flavonoid of a popular herb tea, Coreopsis tinctoria Nutt., showed strong inhibition on CYP3A4 and CYP2D6. The strong interaction between okanin and CYPs were determined by enzyme kinetics, multispectral technique and molecular docking. The inhibition type of two enzymes, CYP3A4 and CYP2D6, by okanin are mixed and non-competitive inhibition type, respectively. The IC50 values and the binding constant of okanin to CYP3A4 can be deduced that the interaction was stronger than that of CYP2D6. The Conformations of CYP3A4 and CYP2D6 were changed by okanin. The evidence from fluorescence measurement along with molecular docking verified that these two CYPs were bound with okanin by hydrogen bonds and hydrophobic forces. Our investigation suggested that okanin may lead to interactions between herb and drug by inhibiting CYP3A4 and CYP2D6 activities, thus its consumption should be taken with caution.

[Diagnostic Study of Multi-spectral Intelligent Analyzer in Diagnosis of the Infiltration Degree of Lung Adenocarcinoma]

BACKGROUND

Lung cancer is one of the most common malignant tumors in the world. The accuracy of intraoperative frozen section (FS) in the diagnosis of lung adenocarcinoma infiltration cannot fully meet the clinical needs. The aim of this study is to explore the possibility of improving the diagnostic efficiency of FS in lung adenocarcinoma by using the original multi-spectral intelligent analyzer.

METHODS

Patients with pulmonary nodules who underwent surgery in the Department of Thoracic Surgery, Beijing Friendship Hospital, Capital Medical University from January 2021 to December 2022 were included in the study. The multispectral information of pulmonary nodule tissues and surrounding normal tissues were collected. A neural network model was established and the accuracy of the neural network diagnostic model was verified clinically.

RESULTS

A total of 223 samples were collected in this study, 156 samples of primary lung adenocarcinoma were finally included, and a total of 1,560 sets of multispectral data were collected. The area under the curve (AUC) of spectral diagnosis in the test set (10% of the first 116 cases) of the neural network model was 0.955 (95%CI: 0.909-1.000, P<0.05), and the diagnostic accuracy was 95.69%. In the clinical validation group (the last 40 cases), the accuracy of spectral diagnosis and FS diagnosis were both 67.50% (27/40), and the AUC of the combination of the two was 0.949 (95%CI: 0.878-1.000, P<0.05), and the accuracy was 95.00% (38/40).

CONCLUSIONS

The accuracy of the original multi-spectral intelligent analyzer in the diagnosis of lung invasive adenocarcinoma and non-invasive adenocarcinoma is equivalent to that of FS. The application of the original multi-spectral intelligent analyzer in the diagnosis of FS can improve the diagnostic accuracy and reduce the complexity of intraoperative lung cancer surgery plan.
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Extensive assessment of climate change impacts on coastal zone paddy growth using multispectral analysis and hydrodynamic modeling

Global warming has led to sea levels raise (SLRs) and Malaysia is no exception to this problem. Especially for low-lying coastal areas including the Kuala Kedah area which is active in agricultural and fisheries activities. Farmers have had to bear up to 75 % of yield losses due to seawater breaches since 2016. Therefore, this study is designed to assess the impact of seawater encroachment on water quality through spatial technology approaches and hydrodynamic modeling related to the growth of paddy trees. The study was conducted during two different paddy cultivation seasons namely Season 1-2019 and Season 2-2019 which take place in the southwest and northeast monsoon in Kuala Kedah, Malaysia. The study involved three phases, which are the assessment of salinity and pH concentration levels, the assessment of the health of paddy crops through multispectral image analysis involving three plant indices (VI), namely Normalized Difference Vegetation Index (NDVI), Blue Normalized Difference Vegetation Index (BNDVI) and Normalized Difference Red Edge (NDRE), and finally, the assessment of the impact of SLR through the numerical method in MIKE 21 for hydrodynamic modeling considering two conditions that are without mitigation factor (K1) and with existing mitigating factor (K2). According to the findings, the salinity concentration trend is decreasing across the growth stage during Season 1-2019, whereas it is the contrary during Season 2-2019. It was discovered that during the study period for both tidal events, 73 % of the 44 sampling points in Season 1-2019, as opposed to just 3 % in Season 2-2019, were categorized as Class 4 and Class 5. Even though there were fluctuations throughout the observation, the pH reading is still within the allowed range of 6.5 to 9.0 for the estuary area. Following that, the ANOVA analysis proved that salinity concentration a statistically significant difference with tidal variations and pH levels. Moreover, the multispectral image analysis findings revealed that the VI value was correlated with both the yield and the health of the rice crop, with R-square values of 0.842 compared to 0.706 and 0.575 for NDVI and BNDVI values, respectively. It confirmed that NDRE granted a more accurate and reliable measurements. Additionally, the hydrodynamic simulation results demonstrated that, if the mitigation factors were considered in the modeling, overflow seawater to the mainland could be reduced by up to 20 %, reducing the impact of coastal flooding on the local area as well as the nearby rice cultivation area. Ultimately, these three elements-water quality, vegetation index, and hydrodynamic modeling-can assist in identifying the underlying cause of the problem and develop short and long-term solutions.

Inhibition effect of 1-acetoxy-6α-(2-methylbutyryl)eriolanolide toward soluble epoxide hydrolase: Multispectral analysis, molecular dynamics simulation, biochemical, and in vitro cell-based studies

Soluble epoxide hydrolase (sEH) serves as a potential target in inflammation-related diseases. Based on the bioactivity-guided separation, a new sesquiterpenoid inulajaponoid A (1) was isolated from Inula japonica with a sEH inhibitory effect, together with five known compounds, such as 1-O-acetyl-6-O-isobutyrylbritannilactone (2), 6β-hydroxytomentosin (3), 1β,8β-dihydroxyeudesma-4(15),11(13)-dien-12,6α-olide (4), (4S,6S,7S,8R)-1-O-acetyl-6-O-(3-methylvaleryloxy)-britannilactone (5), and 1-acetoxy-6α-(2-methylbutyryl)eriolanolide (6). Among them, compounds 1 and 6 were assigned as mixed and uncompetitive inhibitors, respectively. The result of immunoprecipitation (IP)-MS demonstrated the specific binding of compound 6 to sEH in the complex system, which was further confirmed by the fluorescence-based binding assay showing its equilibrium dissociation constant (K_d = 2.43 μM). The detail molecular stimulation revealed the mechanism of action of compound 6 with sEH through the hydrogen bond of amino acid residue Gln384. Furthermore, this natural sEH inhibitor (6) could suppress the MAPK/NF-κB activation to regulate inflammatory mediators, such as NO, TNF-α, and IL-6, which confirmed the anti-inflammatory effect of inhibition of sEH by 6. These findings provided a useful insight to develop sEH inhibitors upon the sesquiterpenoids.

A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features

The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Current methods take a holistic approach to landscape heritage and promote an interdisciplinary dialogue to facilitate complementary landscape management strategies. With the socio-economic values of the "natural" and "cultural" landscape heritage increasingly recognised worldwide, remote sensing tools are being used more and more to facilitate the recording and management of landscape heritage. The advent of freeware cloud computing services has enabled significant improvements in landscape research allowing the rapid exploration and processing of satellite imagery such as the Landsat and Copernicus Sentinel datasets. This research represents one of the first applications of the Google Earth Engine (GEE)  Python application programming interface (API) in studies of historic landscapes. The complete free and open-source software (FOSS) cloud protocol proposed here consists of a Python code script developed in Google Colab, which could be adapted and replicated in different areas of the world. A multi-temporal approach has been adopted to investigate the potential of Sentinel-2 satellite imagery to detect buried hydrological and anthropogenic features along with spectral index and spectral decomposition analysis. The protocol's effectiveness in identifying palaeo-riverscape features has been tested in the Po Plain (N Italy).

A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features

The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Current methods take a holistic approach to landscape heritage and promote an interdisciplinary dialogue to facilitate complementary landscape management strategies. With the socio-economic values of the "natural" and "cultural" landscape heritage increasingly recognised worldwide, remote sensing tools are being used more and more to facilitate the recording and management of landscape heritage. The advent of freeware cloud computing services has enabled significant improvements in landscape research allowing the rapid exploration and processing of satellite imagery such as the Landsat and Copernicus Sentinel datasets. This research represents one of the first applications of the Google Earth Engine (GEE)  Python application programming interface (API) in studies of historic landscapes. The complete free and open-source software (FOSS) cloud protocol proposed here consists of a Python code script developed in Google Colab, which could be adapted and replicated in different areas of the world. A multi-temporal approach has been adopted to investigate the potential of Sentinel-2 satellite imagery to detect buried hydrological and anthropogenic features along with spectral index and spectral decomposition analysis. The protocol's effectiveness in identifying palaeo-riverscape features has been tested in the Po Plain (N Italy).

Temporal multispectral and 3D analysis of Cerro de Pasco, Peru

Mining operations across the world often lead to contamination of land, water resources, ecosystems and in some cases, entire communities.Results of recent health and ground sampling studies revealed extensive lead contamination within the populace and around the City of Cerro de Pasco, Peru. Tailings excavated from a large open pit zinc mine in the center of the city have been aggregated in four large stockpiles within close proximity to neighborhoods, schools, and hospitals. Visual comparison of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) imagery from 2001 and Sentinel-2 imagery from 2018 suggests a size increase in one tailing stockpile in particular near the neighborhood of Paragsha. Due to ongoing mining efforts, the hypothesis motivating the work presented here is that Pb-bearing minerals would be detectable through multispectral analysis, an increase in Pb mineral percent abundance would be observed and tailing stockpile volume would be detectable between 2001 and 2016. This hypothesis is tested using Spectral Angle Mapper (SAM), Adaptive Coherence Estimator (ACE), and Jeffries-Matusita distance calculation on ASTER (2001) and Sentinel-2 (2018) VNIR and SWIR bands. Volume and area estimate of tailing stockpiles were calculated using a photogrammetrically derived point cloud. SAM detected the presence of five Pb-bearing minerals around Cerro de Pasco and Paragsha. The results of the temporal SAM analysis displayed an increase of approximately 17% of Pb-bearing minerals around the greater Cerro de Pasco city area and approximately 11% for the neighborhood of Paragsha. Jeffries-Matusita distance results suggest clear correlation between contamination sources and affected locations. Total tailing stockpile volume was measured to be approximately 200,300,000 m³. Volume for Pile 4 was estimated to have increased by approximately 46,000,000 m³ between 2001 and 2018. These presented results will hopefully inspire and guide future remote sensing campaigns, perhaps involving a UAV or aircraft-based hyperspectral instrument.

Combinatorial multispectral, thermodynamics, docking and site-directed mutagenesis reveal the cognitive characteristics of honey bee chemosensory protein to plant semiochemical

In the chemoreceptive system of insects, there are always some soluble binding proteins, such as some antennal-specific chemosensory proteins (CSPs), which are abundantly distributed in the chemosensory sensillar lymph. The antennal-specific CSPs usually have strong capability to bind diverse semiochemicals, while the detailed interaction between CSPs and the semiochemicals remain unclear. Here, by means of the combinatorial multispectral, thermodynamics, docking and site-directed mutagenesis, we detailedly interpreted a binding interaction between a plant semiochemical β-ionone and antennal-specific CSP1 from the worker honey bee. Thermodynamic parameters (ΔH < 0, ΔS > 0) indicate that the interaction is mainly driven by hydrophobic forces and electrostatic interactions. Docking prediction results showed that there are two key amino acids, Phe44 and Gln63, may be involved in the interacting process of CSP1 to β-ionone. In order to confirm the two key amino acids, site-directed mutagenesis were performed and the binding constant (K_A) for two CSP1 mutant proteins was reduced by 60.82% and 46.80% compared to wild-type CSP1. The thermodynamic analysis of mutant proteins furtherly verified that Phe44 maintained an electrostatic interaction and Gln63 contributes hydrophobic and electrostatic forces. Our investigation initially elucidates the physicochemical mechanism of the interaction between antennal-special CSPs in insects including bees to plant semiochemicals, as well as the development of twice thermodynamic analysis (wild type and mutant proteins) combined with multispectral and site-directed mutagenesis methods.

Tumor invasion unit in gastric cancer revealed by QDs-based in situ molecular imaging and multispectral analysis

In tumor tissues, cancer cells, tumor infiltrating macrophages and tumor neo-vessels in close spatial vicinity with one another form tumor invasion unit, which is a biologically important tumor microenvironment of metastasis to facilitate cancer invasion and metastasis. Establishing an in situ molecular imaging technology to simultaneously reveal these three components is essential for the in-depth investigation of tumor invasion unit. In this report, we have developed a computer-aided algorithm by quantum dots (QDs)-based multiplexed molecular imaging technique for such purpose. A series of studies on gastric cancer tumor tissues demonstrated that the tumor invasion unit was correlated with major unfavorable pathological features and worse clinical outcomes, which illustrated the significantly negative impacts and predictive power of tumor invasion unit on patient overall survival. This study confirmed the technical advantages of QDs-based in situ and simultaneous molecular imaging of key cancer molecules to gain deeper insights into the biology of cancer invasion.