Recovery of 1887 metagenome-assembled genomes from the South China Sea.

The South China Sea (SCS) is a marginal sea characterized by strong land-sea biogeochemical interactions. SCS has a distinctive landscape with a multitude of seamounts in its basin. Seamounts create "seamount effects" that influence the diversity and distribution of planktonic microorganisms in the surrounding oligotrophic waters. Although the vertical distribution and community structure of marine microorganisms have been explored in certain regions of the global ocean, there is a lack of comprehensive microbial genomic surveys for uncultured microorganisms in SCS, particularly in the seamount regions. Here, we employed a metagenomic approach to study the uncultured microbial communities sampled from the Xianbei seamount region to the North Coast waters of SCS. A total of 1887 non-redundant prokaryotic metagenome-assembled genomes (MAGs) were reconstructed, of which, 153 MAGs were classified as high-quality MAGs based on the MIMAG standards. The community structure and genomic information provided by this dataset could be used to analyze microbial distribution and metabolism in the SCS.

Upconversion Nanoparticles Based Sensing: From Design to Point-of-Care Testing.

Rare earth-doped upconversion nanoparticles (UCNPs) have achieved a wide range of applications in the sensing field due to their unique anti-Stokes luminescence property, minimized background interference, excellent biocompatibility, and stable physicochemical properties. However, UCNPs-based sensing platforms still face several challenges, including inherent limitations from UCNPs such as low quantum yields and narrow absorption cross-sections, as well as constraints related to energy transfer efficiencies in sensing systems. Therefore, the construction of high-performance UCNPs-based sensing platforms is an important cornerstone for conducting relevant research. This work begins by providing a brief overview of the upconversion luminescence mechanism in UCNPs. Subsequently, it offers a comprehensive summary of the sensors' types, design principles, and optimized design strategies for UCNPs sensing platforms. More cost-effective and promising point-of-care testing applications implemented based on UCNPs sensing systems are also summarized. Finally, this work addresses the future challenges and prospects for UCNPs-based sensing platforms.

Stamped production of single-crystal hexagonal boron nitride monolayers on various insulating substrates.

Controllable growth of two-dimensional (2D) single crystals on insulating substrates is the ultimate pursuit for realizing high-end applications in electronics and optoelectronics. However, for the most typical 2D insulator, hexagonal boron nitride (hBN), the production of a single-crystal monolayer on insulating substrates remains challenging. Here, we propose a methodology to realize the facile production of inch-sized single-crystal hBN monolayers on various insulating substrates by an atomic-scale stamp-like technique. The single-crystal Cu foils grown with hBN films can stick tightly (within 0.35 nm) to the insulating substrate at sub-melting temperature of Cu and extrude the hBN grown on the metallic surface onto the insulating substrate. Single-crystal hBN films can then be obtained by removing the Cu foil similar to the stamp process, regardless of the type or crystallinity of the insulating substrates. Our work will likely promote the manufacturing process of fully single-crystal 2D material-based devices and their applications.

Enhanced detection of endocrine disrupting chemicals in on-chip microfluidic biosensors using aptamer-mediated bridging flocculation and upconversion luminescence.

Exposure to endocrine-disrupting chemicals (EDCs) can lead to detrimental impacts on human health, making their detection a critical issue. A novel approach utilizing on-chip microfluidic biosensors was developed for the simultaneous detection of two EDCs, namely, bisphenol A (BPA) and diethylstilbestrol (DES), based on upconversion nanoparticles doped with thulium (Tm) and erbium (Er), respectively. From the perspective of single nanoparticles, the construction of an active core-inert shell structure enhanced the luminescence of nanoparticles by 2.28-fold (Tm) and 1.72-fold (Er). From the perspective of the nanoparticle population, the study exploited an aptamer-mediated bridging flocculation mechanism and effectively enhanced the upconversion luminescence of biosensors by 8.94-fold (Tm) and 7.10-fold (Er). A chip with 138 tangential semicircles or quarter-circles was designed and simulated to facilitate adequate mixing, reaction, magnetic separation, and detection conditions. The on-chip microfluidic biosensor demonstrated exceptional capabilities for the simultaneous detection of BPA and DES with ultrasensitive detection limits of 0.0076 µg L-1, and 0.0131 µg L-1, respectively. The first reported aptamer-mediated upconversion nanoparticle bridging flocculation provided enhanced luminescence and detection sensitivity for biosensors, as well as offering a new perspective to address the instability of nanobiosensors.

Label-free detection of trace level zearalenone in corn oil by surface-enhanced Raman spectroscopy (SERS) coupled with deep learning models.

Surface-enhanced Raman spectroscopy (SERS) and deep learning models were adopted for detecting zearalenone (ZEN) in corn oil. First, gold nanorods were synthesized as a SERS substrate. Second, the collected SERS spectra were augmented to improve the generalization ability of regression models. Third, five regression models, including partial least squares regression (PLSR), random forest regression (RFR), Gaussian progress regression (GPR), one-dimensional convolutional neural networks (1D CNN), and two-dimensional convolutional neural networks (2D CNN), were developed. The results showed that 1D CNN and 2D CNN models possessed the best prediction performance, i.e., determination of prediction set (RP2) = 0.9863 and 0.9872, root mean squared error of prediction set (RMSEP) = 0.2267 and 0.2341, ratio of performance to deviation (RPD) = 6.548 and 6.827, limit of detection (LOD) = 6.81 × 10-4 and 7.24 × 10-4 µg/mL. Therefore, the proposed method offers an ultrasensitive and effective strategy for detecting ZEN in corn oil.

Universal epitaxy of non-centrosymmetric two-dimensional single-crystal metal dichalcogenides.

The great challenge for the growth of non-centrosymmetric 2D single crystals is to break the equivalence of antiparallel grains. Even though this pursuit has been partially achieved in boron nitride and transition metal dichalcogenides (TMDs) growth, the key factors that determine the epitaxy of non-centrosymmetric 2D single crystals are still unclear. Here we report a universal methodology for the epitaxy of non-centrosymmetric 2D metal dichalcogenides enabled by accurate time sequence control of the simultaneous formation of grain nuclei and substrate steps. With this methodology, we have demonstrated the epitaxy of unidirectionally aligned MoS2 grains on a, c, m, n, r and v plane Al2O3 as well as MgO and TiO2 substrates. This approach is also applicable to many TMDs, such as WS2, NbS2, MoSe2, WSe2 and NbSe2. This study reveals a robust mechanism for the growth of various 2D single crystals and thus paves the way for their potential applications.

Simultaneous quantification of total flavonoids and phenolic content in raw peanut seeds via NIR spectroscopy coupled with integrated algorithms.

Peanuts are nutritionally valuable for both humans and animals due to their high content of flavonoids and phenolic compounds. Herein, we explored the potential of near-infrared (NIR) spectroscopy coupled with efficient variable selection algorithms for quantitative prediction of total flavonoids (TFC) and total phenolics content (TPC) in raw peanut seeds. Spectrophotometrically, the reference results of the extracts for TFC and TPC were analysed and recorded. The integrated application of the synergy interval coupled competitive adaptive reweighted sampling-partial least squares (Si-CARS-PLS) were used for prediction. The model performance appraisal was based on the correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD). The Si-CARS-PLS performed optimally for TFC (Rp = 0.9137, RPD = 2.49) and TPC (Rp = 0.9042, RPD = 2.31), respectively. Moreover, the model (Si-CARS-PLS) was found to have an acceptable fit for the analytes under study since it achieved 0.88 for TFC and 0.86 for TPC based on the external validation. Therefore, these results showed that NIR coupled with Si-CARS-PLS could be used for the quantitative prediction of flavonoids and phenolic contents in raw peanut seeds.

Competitive Ratiometric Aptasensing with Core-Internal Standard-Shell Structure Based on Surface-Enhanced Raman Scattering.

Reproducibility and stability are important indicators for the evaluation of quantitative sensing methods based on surface-enhanced Raman scattering (SERS) technology. Developing a SERS substrate with self-calibration capabilities is vital for effectively quantifying targets. In this work, a competitive ratiometric SERS aptasensor was developed. 4-Aminothiophenol as an internal standard (IS) was embedded in the substrate followed by gradually loading with the aptamer and methylene blue functionalizing of the complementary sequences of the aptamer (MB-cDNA). Recognition and binding of the target to the aptamer resulted in the shedding of MB-cDNA after magnetic separation reducing the SERS signal of MB, allowing for the ratiometric determination of the target based on the constant intensity from the IS. For the selective detection of okadaic acid (OA), a good negative correlation was achieved between the SERS ratiometric intensity and OA concentration in the range of 0.5-100 ng/mL. The magnetic separation strategy effectively simplifies the production steps of the aptasensor, and the ratiometric strategy effectively improved the reproducibility and stability of the OA sensing. This ratiometric aptasensor has been successfully employed to detect OA in food and environmental samples and is expected to be extended to detect other targets.

Identification and Expression Analysis of Dsx and Its Positive Transcriptional Regulation of IAG in Black Tiger Shrimp (Penaeus monodon).

Doublesex (Dsx) is a polymorphic transcription factor of the DMRTs family, which is involved in male sex trait development and controls sexual dimorphism at different developmental stages in arthropods. However, the transcriptional regulation of the Dsx gene is largely unknown in decapods. In this study, we reported the cDNA sequence of PmDsx in Penaeus monodon, which encodes a 257 amino acid polypeptide. It shared many similarities with Dsx homologs and has a close relationship in the phylogeny of different species. We demonstrated that the expression of the male sex differentiation gene Dsx was predominantly expressed in the P. monodon testis, and that PmDsx dsRNA injection significantly decreased the expression of the insulin-like androgenic gland hormone (IAG) and male sex-determining gene while increasing the expression of the female sex-determining gene. We also identified a 5'-flanking region of PmIAG that had two potential cis-regulatory elements (CREs) for the PmDsx transcription. Further, the dual-luciferase reporter analysis and truncated mutagenesis revealed that PmDsx overexpression significantly promoted the transcriptional activity of the PmIAG promoter via a specific CRE. These results suggest that PmDsx is engaged in male reproductive development and positively regulates the transcription of the PmIAG by specifically binding upstream of the promoter of the PmIAG. It provides a theoretical basis for exploring the sexual regulation pathway and evolutionary dynamics of Dmrt family genes in P. monodon.

Intelligent evaluation of free amino acid and crude protein content in raw peanut seed kernels using NIR spectroscopy paired with multivariable calibration.

Given the nutritional importance of peanuts, this study examined the free amino acid (FAA) and crude protein (CP) content in raw peanut seeds. Near-infrared spectroscopy (NIRS) was employed in combination with variable selection algorithms after successful reference data analysis using colorimetric and Kjeldahl methods. Ensuing the application of partial least squares (PLS) as a full spectral model, the genetic algorithm (GA), bootstrapping soft shrinkage (BOSS), uninformative variable elimination (UVE), and random frog (RF) models were tested and assessed. A comparison of correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) was performed to appraise the performance of the built models. Using RF-PLS, an unsurpassed outcome was achieved for FAA (Rp = 0.937, RPD = 3.38) and CP (Rp = 0.9261, RPD = 3.66). These findings demonstrated that NIR in combination with RF-PLS could be utilized for quantitative, rapid, and nondestructive prediction of FAA and CP in raw peanut seed samples.

Recyclable flexible upconversion-luminescence sensing platform for quantifying sulfite based on inner filter effect.

The widespread applications of sulfur dioxide and its derivatives is a double-edged sword in terms of ensuring environmental and food safety. In this work, a recyclable flexible upconversion-luminescence sensor was developed for the determination of sulfite in environmental and foodstuff samples. The upconversion nanoparticles (UCNPs) were uniformly doped with polydimethylsiloxane (PDMS) prepolymer and moulded to prepare a flexible upconversion-luminescence substrate, which was further modified with pararosaniline (PRA) dye based on the typical carbodiimide coupling procedure. The principle of the work was based on the inner filter effect (IFE) mechanism between PRA dye and UCNPs. In the presence of target sulfite ions, it selectively binds to PRA moieties fixed on the surface of the flexible sensor, resulting in its bleaching and restoration of the upconversion fluorescence. Under the optimized conditions, a linear response for sulfite concentration in the range of 10-100 nM was obtained. The limit of detection was calculated as 2.24 nM, and the proposed sensor was successfully regenerated and recycled six times. The method was applied in real rainwater samples with spiked recoveries in the range of 94.85%-99.39%, and the coefficient of variation ranged from 1.65% to 4.93%. Hence, the proposed flexible upconversion-luminescence sensor held the attractive potential for efficient sulfite determination in real environmental and food samples.

Visualizing the Anomalous Catalysis in Two-Dimensional Confined Space.

Confined nanospaces provide a new platform to promote catalytic reactions. However, the mechanism of catalytic enhancement in the nanospace still requires insightful exploration due to the lack of direct visualization. Here, we report operando investigations on the etching and growth of graphene in a two-dimensional (2D) confined space between graphene and a Cu substrate. We observed that the graphene layer between the Cu and top graphene layer was surprisingly very active in etching (more than 10 times faster than the etching of the top graphene layer). More strikingly, at a relatively low temperature (∼530 °C), the etched carbon radicals dissociated from the bottom layer, in turn feeding the growth of the top graphene layer with a very high efficiency. Our findings reveal the in situ dynamics of the anomalous confined catalytic processes in 2D confined spaces and thus pave the way for the design of high-efficiency catalysts.

Application of NIR spectroscopy for rapid quantification of acid and peroxide in crude peanut oil coupled multivariate analysis.

Two key parameters (acidity and peroxide content) for evaluation of the oxidation level in crude peanut oil have been studied. The titrimetric analysis was carried out for reference data collection. Then, near-infrared spectroscopy in combination with chemometric algorithms such as partial least square (PLS); bootstrapping soft shrinkage-PLS (BOSS-PLS); uninformative variable elimination-PLS (UVE-PLS), and competitive-adaptive reweighted sampling-PLS (CARS-PLS) were attempted and assessed. The correlation coefficients of prediction (Rp), root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to individually evaluate the performance of the models. Optimum results were noticed with CARS-PLS, 0.9517 ≤ Rc ≤ 0.9670, 0.9503 ≤ Rp ≤ 0.9637, 0.0874 ≤ RMSEP ≤ 0.5650, and 3.14 ≤ RPD ≤ 3.64. Therefore, this affirmed that the near-infrared spectroscopy coupled with CARS-PLS could be used as a simple, fast, and non-invasive technique for quantifying acid value and peroxide value in crude peanut oil.

Fabricating a nano-bionic sensor for rapid detection of H2S during pork spoilage using Ru NPs modulated catalytic hydrogenation conversion.

Rapid, sensitive and on-site monitoring of meat spoilage is highly essential for food safety. Hydrogen sulfide (H2S) a typical volatile, produced during enzymatic hydrolysis is considered as a reliable marker for evaluating meat freshness. Herein, a novel nano-bionic sensor based on the superior catalytic activity of ruthenium nanoparticles (Ru NPs) has been fabricated for H2S quantification. The activity sites of Ru NPs were poisoned in the presence of H2S, thereby affecting its catalytic efficiency via reducing the degradation of azo dye. The developed nano-bionic sensor achieved a selective response toward H2S, with capability for on-site surveillance of the pork freshness in the linear range (0-1800 nM). A higher correlation was obtained between the H2S content and the total viable count during the 9-period pork spoilage process (R2 = 0.9633 and 0.9769). Moreover, the proposed method exhibits high selectivity in the presence of other characteristic volatiles encountered during the pork storage process.

Towards chirality control of graphene nanoribbons embedded in hexagonal boron nitride.

The integrated in-plane growth of graphene nanoribbons (GNRs) and hexagonal boron nitride (h-BN) could provide a promising route to achieve integrated circuitry of atomic thickness. However, fabrication of edge-specific GNRs in the lattice of h-BN still remains a significant challenge. Here we developed a two-step growth method and successfully achieved sub-5-nm-wide zigzag and armchair GNRs embedded in h-BN. Further transport measurements reveal that the sub-7-nm-wide zigzag GNRs exhibit openings of the bandgap inversely proportional to their width, while narrow armchair GNRs exhibit some fluctuation in the bandgap-width relationship. An obvious conductance peak is observed in the transfer curves of 8- to 10-nm-wide zigzag GNRs, while it is absent in most armchair GNRs. Zigzag GNRs exhibit a small magnetic conductance, while armchair GNRs have much higher magnetic conductance values. This integrated lateral growth of edge-specific GNRs in h-BN provides a promising route to achieve intricate nanoscale circuits.

Investigation of nonlinear relationship of surface enhanced Raman scattering signal for robust prediction of thiabendazole in apple.

Thiabendazole (TBZ) is extensively used in agriculture to control molds; residue of TBZ may pose a threat to humans. Herein, surface-enhanced Raman spectroscopy (SERS) coupled variable selected regression methods have been proposed as simple and rapid TBZ quantification technique. The nonlinear correlation between the TBZ and SERS data was first diagnosed by augmented partial residual plots method and calculated by runs test. Au@Ag NPs with strong enhancement factor (EF = 4.07 × 106) of Raman signal was used as SERS active material to collect spectra from TBZ. Subsequently, three nonlinear regression models were comparatively investigated and the competitive adaptive reweighted sampling-extreme learning machine (CARS-ELM) achieved a higher correlation coefficient (Rp2 = 0.9406) and the lower root-mean-square-error of prediction (RMSEP = 0.5233 mg/L). Finally, recoveries of TBZ in apple samples were 83.02-93.54% with relative standard deviation (RSD) value < 10%. Therefore, SERS coupled CARS-ELM could be employed as a rapid and sensitive approach for TBZ detection in Fuji apples.

Development of a novel wavelength selection method VCPA-PLS for robust quantification of soluble solids in tomato by on-line diffuse reflectance NIR.

This work was attempted to evaluate the feasibility of a constructed on-line NIR platform coupled with efficient algorithms for rapid and robust quantification of quality parameter in cherry tomato. Specifically, a system was developed based on shortwave NIR spectroscopy for on-line quality inspection of cherry tomatoes. The spectra were recorded in diffuse reflectance mode from 900 to 1700 nm, and the conveyor belt speed was fixed to five samples per second. Three novel methods, namely variable combination population analysis (VCPA), uninformative variable elimination (UVE) and competitive adaptive reweighed sampling algorithm (CARS) were coupled with partial least square (PLS) for selecting optimal dataset, and modeling. The obtained results showed that under the optimal tuning parameters (N = 100, k = 500, ω = 14, σ = 10%), a total of 512 original variables, only 9 variables (1.75%) were extracted by VCPA. Subsequently, VCPA-PLS yielded outstanding performance in predicting soluble solid content in cherry tomatoes, with a higher correlation coefficient (RP = 0.9053), and lower root mean square errors (RMSEP = 0.382) in prediction set. This methodology demonstrated the versatile potential of the proposed installation coupled with VCPA methods for on-line detection of total soluble solids in cherry tomatoes.

Prolonged mitotic arrest induced by Wee1 inhibition sensitizes breast cancer cells to paclitaxel.

Wee1 kinase is a crucial negative regulator of Cdk1/cyclin B1 activity and is required for normal entry into and exit from mitosis. Wee1 activity can be chemically inhibited by the small molecule MK-1775, which is currently being tested in phase I/II clinical trials in combination with other anti-cancer drugs. MK-1775 promotes cancer cells to bypass the cell-cycle checkpoints and prematurely enter mitosis. In our study, we show premature mitotic cells that arise from MK-1775 treatment exhibited centromere fragmentation, a morphological feature of mitotic catastrophe that is characterized by centromeres and kinetochore proteins that co-cluster away from the condensed chromosomes. In addition to stimulating early mitotic entry, MK-1775 treatment also delayed mitotic exit. Specifically, cells treated with MK-1775 following release from G1/S or prometaphase arrested in mitosis. MK-1775 induced arrest occurred at metaphase and thus, cells required 12 times longer to transition into anaphase compared to controls. Consistent with an arrest in mitosis, MK-1775 treated prometaphase cells maintained high cyclin B1 and low phospho-tyrosine 15 Cdk1. Importantly, MK-1775 induced mitotic arrest resulted in cell death regardless the of cell-cycle phase prior to treatment suggesting that Wee1 inhibitors are also anti-mitotic agents. We found that paclitaxel enhances MK-1775 mediated cell killing. HeLa and different breast cancer cell lines (T-47D, MCF7, MDA-MB-468 and MDA-MB-231) treated with different concentrations of MK-1775 and low dose paclitaxel exhibited reduced cell survival compared to mono-treatments. Our data highlight a new potential strategy for enhancing MK-1775 mediated cell killing in breast cancer cells.