Unveiling the variability in cadmium accumulation and tolerance characteristics: a comparative study of Basma and Yunyan 87 tobacco varieties.

Tobacco (Nicotiana tabacum L.) shows promise for remediating Cd-contaminated soil due to its significant Cd accumulation capabilities. Although various tobacco varieties exhibit distinct Cd bioaccumulation capacities, a comprehensive understanding of the underlying mechanisms is lacking. This study, conducted using hydroponics, explores differences in Cd accumulation and tolerance mechanisms between two tobacco varieties, Basma and Yunyan 87. The results showed that Cd stress reduced the dry weight, tolerance index, and root morphology for both varieties. Basma exhibited a relatively smaller decline in these indices compared to Yunyan 87. Moreover, Basma demonstrated a higher Cd bioconcentration factor (BCF), concentration, and accumulated content, signifying its superior tolerance and bioaccumulation capacity to Cd compared to Yunyan 87. The Carbonyl Cyanide3-ChloroPhenylhydrazone (CCCP) addition resulted in reduced Cd accumulation and BCFs in both tobacco species. This effect was more pronounced in Basma, suggesting that Basma relies more on an active transport process than Yunyan 87. This could potentially explain its enhanced bioaccumulation ability. Subcellular Cd distribution analysis revealed Basma's preference for distributing Cd in soluble fractions, while Yunyan 87 favoured the cell wall fractions. Transmission electron microscope showed that Basma's organelles were less damaged than Yunyan 87's under Cd stress, possibly contributing to the superior tolerance of Basma. Therefore, these results provided a theoretical foundation for development of Cd-contaminated soil tobacco remediation technology.

Simulation of Starch Gel Printing and Deformation Process Using COMSOL.

The food industry holds immense promise for 3D printing technology. Current research focuses mainly on optimizing food material composition, molding characteristics, and printing parameters. However, there is a notable lack of comprehensive studies on the shape changes of food products, especially in modeling and simulating deformations. This study addresses this gap by conducting a detailed simulation of the starch gel printing and deformation process using COMSOL Multiphysics 6.2 software. Additive manufacturing (AM) technology is widely acclaimed for its user-friendly operation and cost-effectiveness. The 3D printing process may lead to changes in part dimensions and mechanical properties, attributable to the accumulation of residual stresses. Studies require a significant amount of time and effort to discover the optimal composition of the printed material and the most effective deformed 3D structure. There is a risk of failure, which can lead to wasted resources and research delays. To tackle this issue, this study thoroughly analyzes the physical properties of the gel material through COMSOL Multiphysics 6.2 software, It simulates the heat distribution during the 3D printing process, providing important insights into how materials melt and solidify. Three-part models with varying aspect ratios were meticulously designed to explore shape changes during both the printing process and exposure to an 80 °C environment, employing NMR and rheological characterization. Using the generalized Maxwell model for material simulation in COMSOL Multiphysics, the study predicted stress and deformation of the parts by analyzing solid heat transfer and solid mechanics physical fields. Simulation results showed that among three models utilizing a gel-PET plastic membrane bilayer structure, Model No. 1, with the largest aspect ratio, exhibited the most favorable deformation under an 80 °C baking environment. It displayed uniform bending in the transverse direction without significant excess warpage in the edge direction. In contrast, Models No. 2 and No. 3 showed varying degrees of excess warpage at the edges, with Model No. 3 exhibiting a more pronounced warpage. These findings closely aligned with the actual printing outcomes.

Association of phthalate exposure with type 2 diabetes and the mediating effect of oxidative stress: A case-control and computational toxicology study.

Phthalic acid esters (PAEs) are widely used as plasticizers and have been suggested to engender adverse effects on glucose metabolism. However, epidemiological data regarding the PAE mixture on type 2 diabetes (T2DM), as well as the mediating role of oxidative stress are scarce. This case-control study enrolled 206 T2DM cases and 206 matched controls in Guangdong Province, southern China. The concentrations of eleven phthalate metabolites (mPAEs) and the oxidative stress biomarker 8-hydroxy-2'-deoxyguanosine (8-OHdG) in urine were determined. Additionally, biomarkers of T2DM in paired serum were measured to assess glycemic status and levels of insulin resistance. Significantly positive associations were observed for mono-(2-ethylhexyl) phthalate (MEHP) and Mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) with T2DM (P < 0.001). Restricted cubic spline modeling revealed a non-linear dose-response relationship between MEHHP and T2DM (Pnon-linear = 0.001). The Bayesian kernel machine regression and quantile g-computation analyses demonstrated a significant positive joint effect of PAE exposure on T2DM risk, with MEHHP being the most significant contributor. The mediation analysis revealed marginal evidence that oxidative stress mediated the association between the mPAEs mixture and T2DM, while 8-OHdG respectively mediated 26.88 % and 12.24 % of MEHP and MEHHP on T2DM risk individually (Pmediation < 0.05). Di(2-ethylhexyl) phthalate (DEHP, the parent compound for MEHP and MEHHP) was used to further examine the potential molecular mechanisms by in silico analysis. Oxidative stress may be crucial in the link between DEHP and T2DM, particularly in the reactive oxygen species metabolic process and glucose import/metabolism. Molecular simulation docking experiments further demonstrated the core role of Peroxisome Proliferator Activated Receptor alpha (PPARα) among the DEHP-induced T2DM. These findings suggest that PAE exposure can alter oxidative stress via PPARα, thereby increasing T2DM risk.

Association between polycyclic aromatic hydrocarbons and infertility in U.S. women: National Health and Nutrition Examination Survey 2013-2016.

Although there is a body of research indicating the potential impact of polycyclic aromatic hydrocarbons (PAHs) exposure on male infertility, the understanding of how PAH might affect female infertility is still limited. This study aimed to evaluate associations of PAHs, both individually and as a mixture, with female infertility using multiple logistic regression, Bayesian kernel machine regression (BKMR), and quantile g-computation (QGC) models based on data from the National Health and Nutrition Examination Survey (NHANES) 2013-2016. The study included 729 female participants. Multiple logistic regression results indicated that there was a significant association between the third tertile of 2-hydroxy fluorene (2-OHFLU) and female infertility, and the OR was 2.84 (95% CI: 1.24-6.53, P value = 0.015) compared with the first tertile after adjusting for the potential covariates. The BKMR model revealed a positive overall trend between mixed PAH exposure and female infertility, particularly when the mixture was at or above the 55th percentile, where 2-hydroxynaphthalene (2-OHNAP) and 1-hydroxypyrene (1-OHPYR) were the primary influences of the mixture. The univariate exposure-response function indicated positive associations between individual PAH exposure, specifically 2-OHNAP, 2-OHFLU, and 1-OHPYR, and female infertility. The QGC model also indicated a positive trend between exposure to a mixture of PAHs and female infertility, although it did not reach statistical significance (OR = 1.33, 95%CI: 0.86-2.07), with 1-OHPYR having the greatest positive effect on the outcome. This study suggested that exposure to PAHs may be associated with female infertility and further research is needed to consolidate and confirm these findings.

Carbon dots and covalent organic frameworks based FRET immunosensor for sensitive detection of Escherichia coli O157:H7.

The combination of carbon dots (CDs) with covalent organic frameworks (COFs) was used to design an innovative sensor based on fluorescence resonance energy transfer (FRET) for the detection of Escherichia coli O157:H7 (E. coli O157:H7) in food samples. Carbon dots were used as fluorescence donors, covalent organic frameworks as fluorescence acceptors. The antibody (Ab) specific to E. coli O157:H7 was used to form a CD-Ab-COF immunosensor by linking CDs and COFs. The antibody was specifically bound with E. coli O157:H7, which caused the connection between CDs and COFs to be interrupted, and the carbon dots exhibited fluorescence restoration. The sensor exhibited a linear detection range spanning from 0 to 106 CFU/mL, with the limit of detection (LOD) of 7 CFU/mL. The analytical performance of the developed immunosensor was evaluated using spiked food samples with different concentrations of E. coli O157:H7, validating the capability of assessing risks in food testing.

Topological Analysis and Structural Determination of 3D Covalent Organic Frameworks.

3D covalent organic frameworks (3D COFs) constitute a new type of crystalline materials that consist of a range of porous structures with numerous applications in the fields of adsorption, separation, and catalysis. However, because of the complexity of the three-periodic net structure, it is desirable to develop a thorough structural comprehension, along with a means to precisely determine the actual structure. Indeed, such advancements would considerably contribute to the rational design and application of 3D COFs. In this review, the reported topologies of 3D COFs are introduced and categorized according to the configurations of their building blocks, and a comprehensive overview of diffraction-based structural determination methods is provided. The current challenges and future prospects for these materials will also be discussed.

A biomimetic cuproptosis amplifier for targeted NIR-II fluorescence/photoacoustic imaging-guided synergistic NIR-II photothermal immunotherapy.

The therapeutic efficacy of cuproptosis combined with phototheranostics is still hindered by easy copper efflux, nonspecific accumulation and limited light penetration depth. Here, a high-performance NIR-II semiconductor polymer was first synthesized through dual-donor engineering. Then a biomimetic cuproptosis amplifier (PCD@CM) was prepared by Cu(II)-mediated coordinative self-assembly of NIR-II ultrasmall polymer dots and the chemotherapeutic drug DOX, followed by camouflaging of tumor cell membranes. After homologous targeting delivery to tumor cells, overexpressed GSH in the tumor microenvironment (TME) triggers the disassembly of the amplifier and the release of therapeutic components through the reduction of Cu(II) to Cu(I), which enable NIR-II fluorescence/photoacoustic imaging-guided NIR-II photothermal therapy (PTT) and chemotherapy. The released Cu(I) induces the aggregation of lipoylated mitochondrial proteins accompanied by the loss of iron-sulfur proteins, leading to severe proteotoxic stress and eventually cuproptosis. NIR-II PTT and GSH depletion render tumor cells more sensitive to cuproptosis. The amplified cuproptosis sensitization provokes significant immune surveillance, triggering the immunogenic cell death (ICD) to promote cytotoxic T lymphocyte infiltration together with aPD-L1-mediated immune checkpoint blockade. This work proposes a new strategy to develop cuproptosis sensitization systems enhanced by NIR-II phototheranostics with homologous targeting and anti-tumor immune response capabilities.

Accelerating antibody discovery and design with artificial intelligence: Recent advances and prospects.

Therapeutic antibodies are the largest class of biotherapeutics and have been successful in treating human diseases. However, the design and discovery of antibody drugs remains challenging and time-consuming. Recently, artificial intelligence technology has had an incredible impact on antibody design and discovery, resulting in significant advances in antibody discovery, optimization, and developability. This review summarizes major machine learning (ML) methods and their applications for computational predictors of antibody structure and antigen interface/interaction, as well as the evaluation of antibody developability. Additionally, this review addresses the current status of ML-based therapeutic antibodies under preclinical and clinical phases. While many challenges remain, ML may offer a new therapeutic option for the future direction of fully computational antibody design.

Modulating hydrophilic properties of ß-cyclodextrin/carboxymethyl cellulose colloid particles to stabilize Pickering emulsions for food 3D printing.

This research investigated edible Pickering emulsions stabilized by polysaccharide complexes as inks for food 3D printing. The interface membrane structure in the Pickering emulsion system was formed using complexes consisting of ß-cyclodextrin (ß-CD) and carboxymethyl cellulose (CMC). Except for provide sufficient steric barrier and electrostatic repulsion to increase the stability of the Pickering emulsions, the interface membrane constructs also can demonstrate good biphasic wettability and lower oil/water interfacial tension. The hydrophilicity of complexes (ß-CD/CMC) was mainly adjusted by the ratio of ß-CD/CMC (Rß/C) and the substitution degree (DS) of CMC, which further adjusted the physical and chemical properties of Pickering emulsion to make it correspond to the rheological behavior applied to 3D printing. The stable Pickering emulsion (Rß/C = 2:2, DS = 1.2, weight ratio of oil phase (φ) = 65 %) displayed excellent printing potential by characterizations analysis of Pickering emulsions. The smoothness, viscosity, and self-supporting ability of the Pickering emulsion under the optimized conditions were further analyzed using a filling density printing experiment of a cuboid model. The emulsifying properties of ß-CD were adjusted by hydrophilic CMC to achieve the required amphipathic properties of the complexes to develop Pickering emulsions for food 3D printing.

Ratiometric Sensing for Ultratrace Tetracycline Using Electrochemically Active Metal-Organic Frameworks as Response Signals.

A novel ratiometric sensor using an electrochemically active metal-organic framework of Mo@MOF-808 and NH2-UiO-66 as response signals was developed to detect tetracycline (TET) in ultratrace quantities. To achieve the dual-response strategy, Mo@MOF-808, with a reduction peak at -1.06 V, and NH2-UiO-66, with an oxidation peak at 0.724 V, were used as signal probes directly. Concretely, Mo@MOF-808, single-stranded DNA (ssDNA), and complex system (Apt@NH2-UiO-66) of aptamer (Apt) and NH2-UiO-66 were sequentially immobilized on the electrode. With the addition of TET, Apt was hybridized with TET and Apt@NH2-UiO-66 was detached from the electrode, resulting in an increase in the current at -1.06 V and a decrease in the current at 0.724 V. Through this strategy, the sensor achieved a wide linear range (0.1-10000 nM) and a low limit of detection (0.009792 nM) for TET. Moreover, the ratiometric sensor exhibited better sensitivity, reproducibility, and stability than a single-signal sensor. Furthermore, the constructed sensor was successfully applied to detect TET in milk samples, suggesting excellent application prospects.

Fabrication of Pickering emulsions stabilized by citrus pectin modified with ß-cyclodextrin and its application in 3D printing.

Pickering emulsions stabilized by polysaccharide particles have received increasing attention because of their potential applications in three-dimensional (3D) printing. In this study, the citrus pectins (citrus tachibana, shaddock, lemon, orange) modified with ß-cyclodextrin (ß-CD) were used to stabilize Pickering emulsions reaching the requirements of 3D printing. In terms of pectin chemical structure, the steric hindrance provided by the RG I regions was more conducive to the stability of the complex particles. The modification of pectin by ß-CD provided the complexes a better double wettability (91.14 ± 0.14°-109.43 ± 0.22°) and a more negative ζ-potential, which was more beneficial for complexes to anchor at oil-water interface. In addition, the rheological properties, texture properties and stability of the emulsions were more responsive to the ratios of pectin/ß-CD (Rß/C). The results showed that the emulsions stabilized at a φ = 65 % and a Rß/C = 2:2 achieved the requirements (shear thinning behavior, self-supporting ability, and stability) of 3D printing. Furthermore, the application in 3D printing demonstrated that the emulsions under the optimal condition (φ = 65 % and Rß/C = 2:2) displayed excellent printing appearance, especially for the emulsions stabilized by ß-CD/LP particles. This study provides a basis for the selection of polysaccharide-based particles to prepare 3D printing inks which may be utilized in food manufacturing.

Association of urinary iodine concentration with prediabetes/diabetes in adults: Analysis of the NHANES 2005-2016.

BACKGROUND & AIMS: Iodine is required for synthesizing thyroid hormones and regulating human metabolism. Iodine deficiency can lead to thyroid function abnormalities, which are closely associated with disturbances in glucose-insulin homeostasis. Research on the relationship between iodine and diabetes/prediabetes in adults was sparse and inconsistent. We assessed trends in urinary iodine concentration (UIC) and diabetes/prediabetes prevalence and focused on the association between iodine and diabetes/prediabetes among U.S. adults. METHODS: We analyzed the National Health and Nutrition Examination Survey (NHANES) data from the 2005-2016 cycles. Linear regression was employed to evaluate UIC and prediabetes/diabetes prevalence trends over time. Both multiple logistic regression and restricted cubic splines (RCS) were performed to evaluate the association of UIC with diabetes/prediabetes. RESULTS: A distinctly declining trend in median UIC and a significant increase in diabetes prevalence in U.S. adults from 2005 to 2016 were observed. The fourth quartile of UIC was associated with a 30% lower risk for prediabetes, compared with the first quartile (OR=0.70, 95% CI: 0.56-0.86, Ptrend=0.001). However, UIC was not significantly associated with the prevalence of diabetes. The RCS model suggested a significant nonlinear relationship between UIC and the risk of diabetes (P for nonlinearity =0.0147). Stratification analysis showed that the negative associations of UIC with the risk of prediabetes were more pronounced in participants who were men, aged 46-65, overweight, light alcohol drinkers, and nonactive smokers. CONCLUSIONS: Overall, the adults' median UIC in the U.S. population was a declining trend. However, diabetes prevalence increased significantly from 2005 to 2016. Higher UIC was associated with a lower risk of prediabetes.

Laser induced trace doping of Pd on Ru nanoparticles for an efficient hydrogen evolution electrocatalyst.

Improving the activity and stability of electrocatalysts for the hydrogen evolution reaction (HER) plays an essential role in the practical application of electrochemical water splitting under alkaline conditions. Here, trace Pd-doped Ru nanoparticles have been achieved using the pulsed laser ablation in liquid technology, which exhibit efficient HER catalytic performance. It is evidenced that the Pd doping amount is maintained at a trace level and increases nonlinearly with the concentration of the Pd precursor. Molecular dynamics simulations demonstrate that the trace doping of Pd is due to the slow thermal decomposition rate of the Pd precursor. This work improves the mechanistic explanation of the metal doping induced by liquid-phase laser ablation, which may promote the fabrication and application of advanced laser-based nanostructures.

Highly Selective Pd Nanosheet Aerogel Catalyst with Hybrid Strain Induced by Laser Irradiation and P Doping Postprocess.

Strain engineering of electrocatalysts provides an effective strategy to improve the intrinsic catalytic activity. Here, the defect-rich crystalline/amorphous Pd nanosheet aerogel with hybrid microstrain and lattice strain is synthesized by combining laser irradiation and phosphorus doping methods. The surface strain exhibited by the microstrain and lattice strain shifts the d-band center of the electrocatalyst, enhancing the adsorption of intermediates in the ethanol oxidation reaction and thus improving the catalytic performances. The measured mass activity, specific activity and C1-path selectivity of the Pd nanosheet aerogel are 4.48, 3.06, and 5.06 times higher than those of commercial Pd/C, respectively. These findings afford a new strategy for the preparation of highl activity and C1 pathway selective catalysts and provide insight into the catalytic mechanism of strain-rich heterojunction materials based on tunable surface strain values.

Synergistic combination of targeted nano-nuclear-reactors and anti-PD-L1 nanobodies evokes persistent T cell immune activation for cancer immunotherapy.

BACKGROUND: Antitumor T cell immunotherapy as a novel cancer therapeutic strategy has shown enormous promise. However, the tumor microenvironment (TME) is characterized by the low immunogenicity, hypoxia, and immunosuppressive condition that dramatically limit effective T cell immunotherapy. Thus, an ideal immunotherapy strategy that is capable of reversing the immunosuppressive TME is highly imperative. RESULTS: In this article, we reported that Fe-doped and doxorubicin (DOX) loaded HA@Cu2-XS-PEG (PHCN) nanomaterials were rationally designed as targeted Fe-PHCN@DOX nano-nuclear-reactors, which evoked persistent T cell immune response together with anti-PD-L1 nanobodies. It was confirmed that nano-nuclear-reactors displayed strong nanocatalytic effect for effective antitumor effects. Consequently, they maximized the immunogenic cell death (ICD) effect for antigen presentation and then stimulated T cell activation. In addition, Fe-PHCN@DOX could reprogram M2-phenotype tumor-associated macrophages (TAMs) into M1-phenotype TAMs by relieving tumor hypoxia. Meanwhile, blockade of the anti-PD-L1 nanobody promoted T cell activation through targeting the PD-1/PD-L1 immunosuppressive pathway. Notably, in vivo tumor therapy verified that this nano-nuclear-reactor could be used as an excellent immunotherapy nanoplatform for tumor eradication and metastasis prevention with nanobody. CONCLUSIONS: Our findings demonstrated that nano-nuclear-reactors in combination with nanobody could evoke persistent T cell immune activation, suggesting them potential as a promising immunotherapy option for reversing immunosuppressive immune-cold tumors.

Application of Protein in Extrusion-Based 3D Food Printing: Current Status and Prospectus.

Extrusion-based 3D food printing is one of the most common ways to manufacture complex shapes and personalized food. A wide variety of food raw materials have been documented in the last two decades for the fabrication of personalized food for various groups of people. This review aims to highlight the most relevant and current information on the use of protein raw materials as functional 3D food printing ink. The functional properties of protein raw materials, influencing factors, and application of different types of protein in 3D food printing were also discussed. This article also clarified that the effective and reasonable utilization of protein is a vital part of the future 3D food printing ink development process. The challenges of achieving comprehensive nutrition and customization, enhancing printing precision and accuracy, and paying attention to product appearance, texture, and shelf life remain significant.

Structure-based identification and pathway elucidation of flavonoids in Camptotheca acuminate.

Flavonoid metabolism in Camptotheca acuminate remained an untapped area for years. A tandem MS approach was used and focused on the mining and characterizing of flavonoids in mature C. acuminate. Fifteen new flavonoids and forty-three known flavonoids, including fifteen flavone analogs, sixteen flavonol analogs, seven flavanone analogs, six chalcone analogs, four xanthone analogs, ten flavane analogs were mined and identified based on their MS/MS fragments. Fifty-three of them were firstly characterized in C. acuminate. Eight biosynthetic precursors for these flavonoids were also identified. We constructed a specific metabolic map for flavonoids according to their relative contents in the flowers, fruits, stems, and leaves of C. acuminate. Furthermore, the most probable genes involved in chalcone biosynthesis, flavonoid hydroxylation, methylation, and glycosylation were further mined and fished in the gene reservoir of C. acuminate according to their conserved domains and co-expression analysis. These findings enable us to acquire a better understanding of versatile flavonoid metabolism in C. acuminate.

Laser-assisted synthesis of Au aerogel with high-index facets for ethanol oxidation.

Gold (Au) can be used as an ideal metal electrocatalyst for ethanol and glucose oxidation reactions due to its high performance-to-cost ratio. In this paper, the Au aerogel with high-index facets was synthesized by using the laser ablation in liquid technology, which can improve the electrocatalytic activity of Au. The as-prepared Au aerogel showed excellent mass activity and specific activity toward ethanol oxidation reaction, which are 4.6 times and 2.1 times higher than Au/C, respectively. The 3D porous nature and rich defect of the Au aerogel provide more active sites. In addition, the high-index facets with under-coordinated atoms enhance the adsorption of ethanol and glucose molecules, thus improving the intrinsic catalytic activity of Au aerogel. The effect of high-index facets has also been investigated by density functional theory calculations. Furthermore, the Au aerogels also show good electrocatalytic activity and stability toward glucose oxidation reaction. These results are conducive to promote the practical application of Au in electrocatalysis.

A dual-signal fluorescent sensor based on MoS2 and CdTe quantum dots for tetracycline detection in milk.

A dual-signal fluorescent sensor was developed for tetracycline (TET) detection in milk with excellent reproducibility and stability. In this protocol, molybdenum disulfide quantum dots (MoS2 QDs) with blue fluorescence and cadmium telluride quantum dots (CdTe QDs) with yellow fluorescence were synthesized to establish the MoS2/CdTe-based sensor with two fluorescence emission peaks at 433 nm and 573 nm. With the addition of TET, the fluorescence of MoS2/CdTe were quenched by photoinduced electron transfer (PET), and the fluorescence of CdTe QDs were quenched more obvious than MoS2 QDs. With the strategy, a calibration curve was established between the TET concentration in the range of 0.1-1 µM and the ratio of fluorescence intensity at 573 nm and 433 nm (F573/F433). Furthermore, the dual-signal sensor was applied for TET detection in milk samples with the recovery of 95.53-104.22% and the relative standard deviation (RSD) less than 5%, indicating the strong application potential.

Discrimination of rice varieties using smartphone-based colorimetric sensor arrays and gas chromatography techniques.

A smartphone-based colorimetric sensor array system was established for discrimination of rice varieties having different geographical origins. Purposely, aroma profiling of nine rice varieties was performed using solid-phase microextraction gas chromatography-mass spectrometry. Alcohols, aldehydes, alkanes, ketones, heterocyclic compounds, and organic acids represent the abundant compounds. Colorimetric sensor array system produced a characteristic color difference map upon its exposure to volatile compounds of rice. Discrimination of rice varieties was subsequently achieved using principal component analysis, hierarchical clustering analysis, and k-nearest neighbors. Rice varieties from same geographical source were clustered together in the scatter plot of principal component analysis and hierarchical clustering analysis dendrogram. The k-nearest neighbors algorithm delivered optimal results with discrimination rate of 100% for both calibration and prediction sets using sensor array system. The smartphone-based colorimetric sensor array system and gas chromatography technique were able to effectively differentiate rice varieties with the advantage of being simple, rapid, and low-cost.