NR0B2 Is a Key Factor for Gastric Diseases: A GEO Database Analysis Combined with Drug-Target Mendelian Randomization.

Small Heterodimer Partner (SHP; NR0B2) is an orphan receptor that acts as a transcriptional regulator, controlling various metabolic processes, and is a potential therapeutic target for cancer. Examining the correlation between the expression of NR0B2 and the risk of gastric diseases could open a new path for treatment and drug development. The Gene Expression Omnibus (GEO) database was utilized to explore NR0B2 gene expression profiles in gastric diseases. Co-expressed genes were identified through Weighted Correlation Network Analysis (WGCNA), and GO enrichment was performed to identify potential pathways. The Xcell method was employed to analyze immune infiltration relationships. To determine the potential causal relationship between NR0B2 expression and gastric diseases, we identified six single-nucleotide polymorphisms (SNPs) as a proxy for NR0B2 expression located within 100 kilobases of NR0B2 and which are associated with triglyceride homeostasis and performed drug-target Mendelian randomization (MR). Bioinformatics analysis revealed that NR0B2 expression levels were reduced in gastric cancer and increased in gastritis. GO analysis and Gene Set Enrichment Analysis (GSEA) showed that NR0B2 is widely involved in oxidation-related processes. Immune infiltration analyses found that NR0B2 was associated with Treg. Prognostic analyses showed that a low expression of NR0B2 is a risk factor for the poor prognoses of gastric cancer. MR analyses revealed that NR0B2 expression is associated with a risk of gastric diseases (NR0B2 vs. gastric cancer, p = 0.006, OR: 0.073, 95%CI: 0.011-0.478; NR0B2 vs. gastric ulcer, p = 0.03, OR: 0.991, 95%CI: 0.984-0.999; NR0B2 vs. other gastritis, p = 0.006, OR:3.82, 95%CI: 1.468-9.942). Our study confirms the causal relationship between the expression of NR0B2 and the risk of gastric diseases, and highlights its role in the progression of gastric cancer. The present study opens new avenues for exploring the potential of drugs that either activate or inhibit the NR0B2 receptor in the treatment of gastric diseases.

Cholecystokinin regulates atrial natriuretic peptide secretion through activation of NOX4-Sirt1-LEF1 signaling in beating rat hypoxic atria.

The mammalian cardiac myocytes not only synthesize and secrete atrial natriuretic peptide (ANP), but also express cholecystokinin (CCK) and its receptors (CCK1R and CCK2R). However, atrial CCK expression patterns and its effects on ANP secretion during hypoxia are unclear. Therefore, this study is aimed to investigate the effect of hypoxia on the expression levels of CCK and its receptors, as well as the underlying mechanisms involved in regulating hypoxia-induced ANP secretion in isolated beating atria. The results of this study showed that acute hypoxia significantly upregulated expression of CCK and CCK1R as well as CCK2R through activation of hypoxia-inducible factor 1α-apelin signaling. Endogenous CCK induced by hypoxia markedly upregulated the expression of silent information regulator factor 2-related enzyme 1 (Sirt1) and its downstream nuclear factor erythroid­2­related factor 2 (Nrf2) via the activation of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4), leading to increase of activating T cell factor (TCF) 3 and TCF4/ lymphoid enhancer factor (LEF) 1, ultimately promoting hypoxia-induced ANP secretion. In addition, siRNA-mediated knockdown of LEF1 dramatically attenuated hypoxia-induced increase of ANP expression in HL-1 atrial myocytes. These results indicated endogenous CCK induced by hypoxia promoted hypoxia-induced ANP secretion by activation of NOX4-Sirt1-TCF3/4-LEF1 signaling pathway.

Fluorescence hyperspectral imaging technology combined with chemometrics for kiwifruit quality attribute assessment and non-destructive judgment of maturity.

Dry matter content (DMC), firmness and soluble solid content (SSC) are important indicators for assessing the quality attributes and determining the maturity of kiwifruit. However, traditional measurement methods are time-consuming, labor-intensive, and destructive to the kiwifruit, leading to resource wastage. In order to solve this problem, this study has tracked the flowering, fruiting, maturing and collecting processes of Ya'an red-heart kiwifruit, and has proposed a non-destructive method for kiwifruit quality attribute assessment and maturity identification that combines fluorescence hyperspectral imaging (FHSI) technology and chemometrics. Specifically, first of all, three different spectral data preprocessing methods were adopted, and PLSR was used to evaluate the quality attributes (DMC, firmness, and SSC) of kiwifruit. Next, the differences in accuracy of different models in discriminating kiwifruit maturity were compared, and an ensemble learning model based on LightGBM and GBDT models was constructed. The results indicate that the ensemble learning model outperforms single machine learning models. In addition, the application effects of the 'Convolutional Neural Network'-'Multilayer Perceptron' (CNN-MLP) model under different optimization algorithms were compared. To improve the robustness of the model, an improved whale optimization algorithm (IWOA) was introduced by modifying the acceleration factor. Overall, the IWOA-CNN-MLP model performs the best in discriminating the maturity of kiwifruit, with Accuracytest of 0.916 and Loss of 0.23. In addition, compared with the basic model, the accuracy of the integrated learning model SG-MSC-SEL was improved by about 12%-20 %. The research findings will provide new perspectives for the evaluation of kiwifruit quality and maturity discrimination using FHSI and chemometric methods, thereby promoting further research and applications in this field.

Evolution and modeling of texture changes and drying kinetics of bamboo shoots under high-humidity air-impingement blanching.

This study investigated the effect of hot water blanching (HWB), high-humidity air-impingement blanching (HHAIB), different HHAIB blanching times (2, 4, 6, 8, and 10 min), and different HHAIB blanching temperatures (80, 85, 90, and 95°C) on texture quality, lignin content, weight loss, color, microstructure, and drying kinetics of bamboo shoots. After HWB treatment, the lignin content of bamboo shoots was apparently lower than that of HHAIB and the samples obtained the highest weight loss value of 6.13%. Both the texture values (brittleness and chewiness) and lignin content of bamboo shoots exhibited an overall downward trend as the HHAIB blanching time and blanching temperature increased. Specifically, the lignin content of bamboo shoots decreased from 5.59% to 4.58% with an increase in HHAIB blanching time from 2 to 10 min and dropped from 5.48% to 4.63% as HHAIB blanching temperature increased from 80 to 85°C, respectively. The lignin content was proved to be positively correlated (p < 0.05) with texture attributes (brittleness and chewiness). A second polynomial model was obtained for fitting the variation kinetics of lignin content during thermal processing. Reducing the HHAIB blanching time and blanching temperature would obtain a lower weight loss and a better color performance (ΔE and L*). Additionally, microstructure observation revealed that the distribution density of microchannels initially increased and then decreased with the extension of blanching time, while it continuously became firmer as HHAIB blanching temperature increased. Overall, the optimal processing parameters were achieved under the HHAIB blanching temperature of 85°C for 6 min, ensuring a high-quality performance of bamboo shoot products.

A rapid and reliable targeted LC-MS/MS method for quantitative analysis of the Tryptophan-NAD metabolic network disturbances in tissues and blood of sleep deprivation mice.

BACKGROUND: TRY-NAD metabolic network includes TRY (tryptophan), 5-HT (5-hydroxytryptamine), KYN (kynurenine), and NAD (nicotinamide adenine dinucleotide) pathway, which plays a significant role in neurological diseases and ageing. It is important to monitor these metabolites for studying the pathological anatomy of disease and treatment of responses evaluation. Although previous studies have reported quantitative methods for several metabolites in the network, the bottlenecks of simultaneously quantifying the whole metabolic network are their similar structures, diverse physico-chemical properties, and instability. Standardized protocols for the whole metabolic network are still missing, which hinders the in-depth study of TRY-NAD metabolic network in laboratory research and clinical screening. RESULTS: We developed a LC-MS/MS method for quantifying 28 metabolites in the TRY-NAD network simultaneously. Optimization was done for the mass spectral parameters, chromatographic conditions and sample pretreatment process. The developed method was fully validated in terms of standard curves, sensitivity, carryover, recovery, matrix effect, accuracy, precision, and stability. The pretreatment of 30 samples only takes 90 min, and the LC-MS/MS running time of one sample is only 13 min. With this method, we bring to light the chaos of global TRY-NAD metabolic network in sleep deprivation mice for the first time, including serum, clotted blood cells, hippocampus, cerebral cortex, and liver. NAD pathway levels in brain and blood decreased, whereas the opposite happened in the liver. The 5-HT pathway decreased and the concentration of KYN increased significantly in the brain. The concentration of many metabolites in KYN pathway (NAD+ de novo synthesis pathway) increased in the liver. SIGNIFICANCE: This method is the first time to determine the metabolites of KYN, 5-HT and NAD pathway at the same time, and it is found that TRY-NAD metabolic network will be disordered after sleep deprivation. This work clarifies the importance of the pH of the extraction solution, the time and temperature control in pretreatment in standardized protocols building, and overcoming the problems of inconsistent sample pretreatment, separation, matrix effect interference and potential metabolite degradation. This method exhibits great prospects in providing more information on metabolic disturbances caused by sleep deprivation as well as neurological diseases and ageing.

Potential adaptation of scleractinian coral Pocillopora damicornis during hypo-salinity stress caused by extreme pre-flood rainfall over south China.

Global warming intensifies the water cycle, resulting in significant increases in precipitation and river runoff, which brings severe hypo-salinity stress to nearshore coral reefs. Ecological investigations have found that some corals exhibit remarkable adaptability to hypo-salinity stress during mass-bleaching events. However, the exact cause of this phenomenon remains unclear. To elucidate the potential molecular mechanism leading to high tolerance to hypo-salinity stress, Pocillopora damicornis was used as a research object in this study. We compared the differences in transcriptional responses and symbiotic microbiomes between bleaching and unbleaching P. damicornis during hypo-salinity stress caused by extreme pre-flood rainfall over South China in 2022. The results showed that: (1) Under hypo-salinity stress, the coral genes related to immune defense and cellular stress were significantly upregulated in bleaching corals, indicating more severe immune damage and stress, and the Symbiodiniaceae had no significant gene enrichment. Conversely, metabolic genes related to glycolysis/gluconeogenesis were significantly downregulated in unbleaching corals, whereas Symbiodiniaceae genes related to oxidative phosphorylation were significantly upregulated to meet the energy requirements of coral holobiont; (2) C1d was the dominant Symbiodiniaceae subclade in all samples, with no significant difference between the two groups; (3) The symbiotic bacterial community structure was reorganized under hypo-salinity stress. The abundance of opportunistic bacteria increased significantly in bleaching coral, whereas the relative abundance of probiotics was higher in unbleaching coral. This may be due to severe immune damage, making the coral more susceptible to opportunistic infection and bleaching. These results suggest that long-term hypo-salinity acclimation in the Pearl River Estuary enhances the tolerance of some corals to hypo-salinity stress. Corals with higher tolerance may reduce energy consumption by slowing down their metabolism, improve the energy metabolism of Symbiodiniaceae to meet the energy requirements of the coral holobiont, and alter the structure of symbiotic bacterial communities to avoid bleaching.

Biomechanical features and parametric calibration of a bilayer bonded particle model for the cornstalk during harvest.

The optimal discrete element model and bonding parameters that match the structural features of cornstalks during harvest were obtained. Based on the differences in mechanical properties of the stem bark and stem pith in the inter-nodal cornstalk, the biomechanical-specific parameters were measured using the compression, shear, and bending tests. The bonded particle models of stem bark and stem pith were constructed using fraction particles with radii of 1 mm and 1.47 mm, which were further bound to form a bilayer-bonded particle model of the cornstalk. The Plackett-Burman, steepest ascent, and response surface tests were conducted to identify the factors and their optimal values that significantly impacted the stem bark-stem bark, stem pith-stem pith, and stem bark-stem pith bonding parameters. The cornstalk's shear and bending mechanical properties were assessed to verify the overall characteristic parameters. The findings revealed that the cornstalk model created, and the calibrated bonding parameters, were highly accurate and capable of simulating the shearing and bending behaviors of the real cornstalk. The inter-nodal cornstalk's bonded particle model created and the identified bonding parameters for the cornstalk could contribute to a theoretical and research basis for the next stage in cornstalk modeling with nodes and other applications.

Research on nondestructive detection of sweet-waxy corn seed varieties and mildew based on stacked ensemble learning and hyperspectral feature fusion technology.

The variety and quality of corn seeds are crucial factors affecting crop yield and farmers' economic benefits. This study adopts an innovative method based on a hyperspectral imaging system combined with stacked ensemble learning, aiming to achieve varieties classification and mildew detection of sweet-waxy corn seeds. First, data interference is eliminated by extracting the spectral and texture information of each corn sample and preprocessing the data. Secondly, a stacked ensemble learning model (Stack) was constructed by stacking base models and meta-models. Its results were compared with those of the base models, including Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF).Finally, the overall performance of the model is improved through the information fusion strategy of hyperspectral data and texture information. The research results indicate that the GBDT-Stack model, which integrates spectral and texture data, demonstrated optimal performance in the comprehensive classification of both corn seed varieties and mold detection. On the test set, the model achieved an average prediction accuracy of 97.01%. Specifically, the model achieved a test set accuracy ranging from 94.49% to 97.58% for different corn seed varieties and a test set accuracy of 98.89% for mildew detection. This model not only classifies corn seed varieties but also accurately detects mildew, demonstrating its wide applicability. The method has huge potential and is of great significance for improving crop yield and quality.

YOLOC-tiny: a generalized lightweight real-time detection model for multiripeness fruits of large non-green-ripe citrus in unstructured environments.

This study addresses the challenges of low detection precision and limited generalization across various ripeness levels and varieties for large non-green-ripe citrus fruits in complex scenarios. We present a high-precision and lightweight model, YOLOC-tiny, built upon YOLOv7, which utilizes EfficientNet-B0 as the feature extraction backbone network. To augment sensing capabilities and improve detection accuracy, we embed a spatial and channel composite attention mechanism, the convolutional block attention module (CBAM), into the head's efficient aggregation network. Additionally, we introduce an adaptive and complete intersection over union regression loss function, designed by integrating the phenotypic features of large non-green-ripe citrus, to mitigate the impact of data noise and efficiently calculate detection loss. Finally, a layer-based adaptive magnitude pruning strategy is employed to further eliminate redundant connections and parameters in the model. Targeting three types of citrus widely planted in Sichuan Province-navel orange, Ehime Jelly orange, and Harumi tangerine-YOLOC-tiny achieves an impressive mean average precision (mAP) of 83.0%, surpassing most other state-of-the-art (SOTA) detectors in the same class. Compared with YOLOv7 and YOLOv8x, its mAP improved by 1.7% and 1.9%, respectively, with a parameter count of only 4.2M. In picking robot deployment applications, YOLOC-tiny attains an accuracy of 92.8% at a rate of 59 frames per second. This study provides a theoretical foundation and technical reference for upgrading and optimizing low-computing-power ground-based robots, such as those used for fruit picking and orchard inspection.

Diel transcriptional responses of coral-Symbiodiniaceae holobiont to elevated temperature.

Coral exhibits diel rhythms in behavior and gene transcription. However, the influence of elevated temperature, a key factor causing coral bleaching, on these rhythms remains poorly understood. To address this, we examined physiological, metabolic, and gene transcription oscillations in the Acropora tenuis-Cladocopium sp. holobiont under constant darkness (DD), light-dark cycle (LD), and LD with elevated temperature (HLD). Under LD, the values of photosystem II efficiency, reactive oxygen species leakage, and lipid peroxidation exhibited significant diel oscillations. These oscillations were further amplified during coral bleaching under HLD. Gene transcription analysis identified 24-hour rhythms for specific genes in both coral and Symbiodiniaceae under LD. Notably, these rhythms were disrupted in coral and shifted in Symbiodiniaceae under HLD. Importantly, we identified over 20 clock or clock-controlled genes in this holobiont. Specifically, we suggested CIPC (CLOCK-interacting pacemaker-like) gene as a core clock gene in coral. We observed that the transcription of two abundant rhythmic genes encoding glycoside hydrolases (CBM21) and heme-binding protein (SOUL) were dysregulated by elevated temperature. These findings indicate that elevated temperatures disrupt diel gene transcription rhythms in the coral-Symbiodiniaceae holobiont, affecting essential symbiosis processes, such as carbohydrate utilization and redox homeostasis. These disruptions may contribute to the thermal bleaching of coral.

Widely targeted metabolomic analysis reveals effects of yellowing process time on the flavor of vine tea (Ampelopsis grossedentata).

The bitter and astringent taste and miscellaneous smell of vine tea prevent its further development. In this study, we used a processing technology that mimics yellow tea to improve the flavor of vine tea and revealed its internal reasons through metabolomics. Sensory evaluation showed the yellowing process for 6-12 h reduced the bitterness and astringency significantly, and enriched the aroma. The improvement of taste was mainly related to the down-regulation of anthocyanins (54.83-97.38%), the hydrolysis of gallated catechins (34.80-47.81%) and flavonol glycosides (18.56-44.96%), and the subsequent accumulation of d-glucose (33.68-78.04%) and gallic acid (220.96-252.09%). For aroma, increase of total volatile metabolite content (23.88-25.44%) and key compounds like geraniol (239.32-275.21%) induced the changes. These results identified the positive effects of yellowing process on improvements in vine tea flavor and the key compounds that contribute to these changes.

Comprehensive Analysis Reveals the Difference in Volatile Oil between Bupleurum marginatum var. stenophyllum (Wolff) Shan et Y. Li and the Other Four Medicinal Bupleurum Species.

Volatile oil serves as a traditional antipyretic component of Bupleuri Radix. Bupleurum marginatum var. stenophyllum (Wolff) Shan et Y. Li belongs to the genus Bupleurum and is distinguished for its high level of saikosaponins and volatile oils; nonetheless, prevailing evidence remains inconclusive regarding its viability as an alternative resource of other official species. This study aims to systematically compare the volatile oil components of both dried and fresh roots of B. marginatum var. stenophyllum and the four legally available Bupleurum species across their chemical, molecular, bionics, and anatomical structures. A total of 962 compounds were determined via GC-MS from the dried roots; B. marginatum var. stenophyllum showed the greatest differences from other species in terms of hydrocarbons, esters, and ketones, which was consistent with the results of fresh roots and the e-nose analysis. A large number of DEGs were identified from the key enzyme family of the monoterpene synthesis pathway in B. marginatum var. stenophyllum via transcriptome analysis. The microscopic observation results, using different staining methods, further showed the distinctive high proportion of phloem in B. marginatum var. stenophyllum, the structure which produces volatile oils. Together, these pieces of evidence hold substantial significance in guiding the judicious development and utilization of Bupleurum genus resources.

Comprehensive analysis of the mitochondrial genome of Rehmannia glutinosa: insights into repeat-mediated recombinations and RNA editing-induced stop codon acquisition.

Rehmannia glutinosa is an economically significant medicinal plant. Yet, the structure and sequence of its mitochondrial genome has not been published, which plays a crucial role in evolutionary analysis and regulating respiratory-related macromolecule synthesis. In this study, the R. glutinosa mitogenome was sequenced employing a combination of Illumina short reads and Nanopore long reads, with subsequent assembly using a hybrid strategy. We found that the predominant configuration of the R. glutinosa mitogenome comprises two circular chromosomes. The primary structure of the mitogenome encompasses two mitochondrial chromosomes corresponding to the two major configurations, Mac1-1 and Mac1-2. The R. glutinosa mitogenome encoded an angiosperm-typical set of 24 core genes, nine variable genes, three rRNA genes, and 15 tRNA genes. A phylogenetic analysis using the 16 shared protein-coding genes (PCG) yielded a tree consistent with the phylogeny of Lamiales species and two outgroup taxa. Mapping RNA-seq data to the coding sequences (CDS) of the PCGs revealed 507 C-to-U RNA editing sites across 31 PCGs of the R. glutinosa mitogenome. Furthermore, one start codon (nad4L) and two stop codons (rpl10 and atp6) were identified as products of RNA editing events in the R. glutinosa mitogenome.

Comparative chloroplast genomes: insights into the identification and phylogeny of rapid radiation genus Rhodiola.

Rhodiola L. is a genus exhibiting rapid radiation and represents a typical case for studying plastid gene adaptation in species that spread from high altitudes to low altitudes. In this study, 23 samples of 18 Rhodiola species were collected from the Qinghai-Tibetan Plateau and five scattered alpine areas, and the plastid genomes (plastomes) of these species were sequenced, annotated, and compared between high-altitude and widely distributed groups. The plastomes of Rhodiola were found to be highly conserved in terms of gene size, content, and order but highly variable in several lineage-specific features, such as codon usage bias, IR boundary shifting, and distinct repeat sequence structures binding to SSRs. Codon usage in the genes of photosystem II exhibited an obvious preference, reflecting significant environmental adaptation pressures. In this study, three repeat regions compounded with trinucleotide and mononucleotide repeats were found for the first time in R. forrestii, R. himalensis, and R. yunnanensis. High-variability regions such as ndhF, ycf1, trnH-psbA, and rpoC1-rpoB were screened, laying the foundation for the precise identification of these species. The phylogenetic analysis revealed the occurrence of cyto-nuclear discordance, likely originating from the frequent interspecific hybridization events observed within Rhodiola species during rapid radiation. Dioecious and hermaphrodite species can be broadly categorized into two subclades, probably they have different environmental adaptation strategies in response to climate change. In addition, the phylogenetic tree supported the monophyly of R. forrestii and R. yunnanensis, which compose R. Sect. Pseudorhodiola. In conclusion, plastome data enrich the genetic information available for the Rhodiola genus and may provide insight into species migration events during climate change.

The microbiome dynamics and interaction of endosymbiotic Symbiodiniaceae and fungi are associated with thermal bleaching susceptibility of coral holobionts.

The thermal bleaching percentage of coral holobionts shows interspecific differences under heat-stress conditions, which are closely related to the coral-associated microbiome. However, the ecological effects of community dynamics and interactions between Symbiodiniaceae and fungi on coral thermal bleaching susceptibility remain unclear. In this study, we analyzed the diversity, community structure, functions, and potential interaction of Symbiodiniaceae and fungi among 18 coral species from a high thermal bleaching risk atoll using next-generation sequencing. The results showed that heat-tolerant C3u sub-clade and Durusdinium dominated the Symbiodiniaceae community of corals and that there were no core amplicon sequence variants in the coral-associated fungal community. Fungal richness and the abundance of confirmed functional animal-plant pathogens were significantly positively correlated with the coral thermal bleaching percentage. Fungal indicators, including Didymellaceae, Chaetomiaceae, Schizophyllum, and Colletotrichum, were identified in corals. Each coral species had a complex Symbiodiniaceae-fungi interaction network (SFIN), which was driven by the dominant Symbiodiniaceae sub-clades. The SFINs of coral holobionts with low thermal bleaching susceptibility exhibited low complexity and high betweenness centrality. These results indicate that the extra heat tolerance of coral in Huangyan Island may be linked to the high abundance of heat-tolerant Symbiodiniaceae. Fungal communities have high interspecific flexibility, and the increase of fungal diversity and pathogen abundance was correlated with higher thermal bleaching susceptibility of corals. Moreover, fungal indicators were associated with the degrees of coral thermal bleaching susceptibility, including both high and intermediate levels. The topological properties of SFINs suggest that heat-tolerant coral have limited fungal parasitism and strong microbial network resilience.IMPORTANCEGlobal warming and enhanced marine heatwaves have led to a rapid decline in coral reef ecosystems worldwide. Several studies have focused on the impact of coral-associated microbiomes on thermal bleaching susceptibility in corals; however, the ecological functions and interactions between Symbiodiniaceae and fungi remain unclear. We investigated the microbiome dynamics and potential interactions of Symbiodiniaceae and fungi among 18 coral species in Huangyan Island. Our study found that the Symbiodiniaceae community of corals was mainly composed of heat-tolerant C3u sub-clade and Durusdinium. The increase in fungal diversity and pathogen abundance has close associations with higher coral thermal bleaching susceptibility. We first constructed an interaction network between Symbiodiniaceae and fungi in corals, which indicated that restricting fungal parasitism and strong interaction network resilience would promote heat acclimatization of corals. Accordingly, this study provides insights into the role of microorganisms and their interaction as drivers of interspecific differences in coral thermal bleaching.

Inversion of heavy metal content in soil using hyperspectral characteristic bands-based machine learning method.

The global concern regarding the adverse effects of heavy metal pollution in soil has grown significantly. Accurate prediction of heavy metal content in soil is crucial for environmental protection. This study proposes an inversion analysis method for heavy metals (As, Cd, Cr, Cu, Ni, Pb) in soil based on hyperspectral and machine learning algorithms for 21 soil reference materials from multiple provinces in China. On this basis, an integrated learning model called Stacked RF (the base model is XGBoost, LightGBM, CatBoost, and the meta-model is RF) was established to perform soil heavy metal inversion. Specifically, three popular algorithms were initially employed to preprocess the spectral data, then Random Forest (RF) was used to select the best feature bands to reduce the impact of noise, finally Stacking and four basic machine learning algorithms were used to establish comparisons and analysis of inversion model. Compared with traditional machine learning methods, the stacking model showcases enhanced stability and superior accuracy. Research results indicate that machine learning algorithms, especially ensemble learning models, have better inversion effects on heavy metals in soil. Overall, the MF-RF-Stacking model performed best in the inversion of the six heavy metals. The research results will provide a new perspective on the ensemble learning model method for soil heavy metal content inversion using data of hyperspectral characteristic bands collected from soil reference materials.

Linking coral fluorescence phenotypes to thermal bleaching in the reef-building Galaxea fascicularis from the northern South China Sea.

Coral fluorescence phenotypes have been suggested as an adaptation to a broad range of environmental conditions, yet the mechanisms linking thermal bleaching tolerance in reef-building coral populations, associated with fluorescence phenotypes due to GFP-like proteins, remains unclear. In this study, the relationship between the thermal sensitivity and phenotypic plasticity of corals was investigated using two phenotypes of Galaxea fascicularis, green and brown. The results reveal that brown G. fascicularis was more susceptible to bleaching than green G. fascicularis when exposed to a higher growth temperature of 32 °C. Both phenotypes of G. fascicularis were associated with the thermotolerant Symbiodiniaceae symbiont, Durusdinium trenchii. However, the brown G. fascicularis showed a significant decrease in Symbiodiniaceae cell density and a significant increase in pathogenic bacteria abundance when the growth temperature was raised from 29 to 32 °C. The physiological traits and transcriptomic profiles of Symbiodiniaceae were not notably affected, but there were differences in the transcriptional levels of certain genes between the two phenotype hosts of G. fascicularis. Under heat stress of 32 °C, the gene encoding green fluorescent protein (GFP)-like and chromosome-associated proteins, as well as genes related to oxidative phosphorylation, cell growth and death showed lower transcriptional levels in the brown G. fascicularis compared to the green G. fascicularis. Overall, the results demonstrate that the green form of G. fascicularis is better able to tolerate ocean warming and defend against pathogenic bacteria, likely due to higher gene transcription levels and defense ability. Supplementary Information: The online version contains supplementary material available at 10.1007/s42995-023-00190-1.

The Rapid Non-Destructive Differentiation of Different Varieties of Rice by Fluorescence Hyperspectral Technology Combined with Machine Learning.

A rice classification method for the fast and non-destructive differentiation of different varieties is significant in research at present. In this study, fluorescence hyperspectral technology combined with machine learning techniques was used to distinguish five rice varieties by analyzing the fluorescence hyperspectral features of Thai jasmine rice and four rice varieties with a similar appearance to Thai jasmine rice in the wavelength range of 475-1000 nm. The fluorescence hyperspectral data were preprocessed by a first-order derivative (FD) to reduce the background and baseline drift effects of the rice samples. Then, a principal component analysis (PCA) and t-distributed stochastic neighborhood embedding (t-SNE) were used for feature reduction and 3D visualization display. A partial least squares discriminant analysis (PLS-DA), BP neural network (BP), and random forest (RF) were used to build the rice classification models. The RF classification model parameters were optimized using the gray wolf algorithm (GWO). The results show that FD-t-SNE-GWO-RF is the best model for rice classification, with accuracy values of 99.8% and 95.3% for the training and test sets, respectively. The fluorescence hyperspectral technique combined with machine learning is feasible for classifying rice varieties.

Legacy and emerging per- and polyfluoroalkyl substances in the Shuidong bay of South China: Occurrence, partitioning behavior, and ecological risks.

With the phase-out of legacy per- and polyfluoroalkyl substances (PFASs), PFAS alternatives have been increasingly used in industrial production and daily life. However, available information on the occurrence of PFASs and PFAS alternatives in semi-enclosed bays remains limited. As a representative semi-enclosed bay in Guangdong Province, China, Shuidong Bay has experienced severe anthropogenic pollution (industrial, shipping, cultural, and domestic) in recent decades. Water pollution in Shuidong Bay has worsened, and PFASs have been identified as ubiquitous environmental pollutants in this bay. In this study, 23 PFASs, including 5 emerging PFASs, were analyzed in water, suspended particulate matter (SPM), and sediment samples collected from Shuidong Bay. We determined that perfluorobutanoic acid (PFBA) was the predominant PFAS compound in seawater, whereas 6:2 fluorotelomer sulfonic acid (FTS) and perfluorooctane sulfonamide acetate (FOSAA) were dominant in SPM and sediment, respectively. The sediment-water partitioning coefficients were greatly dependent on the perfluorinated carbon chain length. Chlorophyll a concentration had a significant effect on the dissolved concentrations of PFASs in seawater. The ecological risk assessment indicated that the PFASs detected in the seawater and sediment samples posed no considerable risks to aquatic organisms. This study provides a valuable reference for evaluating PFAS contamination in Shuidong Bay and conducting ecological risk assessments for aquatic organisms.

Evolutionary radiation and microbial community dynamics shape the thermal tolerance of Fungiidae in the southern South China Sea.

Fungiidae have shown increased thermal adaptability in coral reef ecosystems under global warming. This study analyzes the evolutionary divergence and microbial communities of Fungiidae in the Sanjiao Reef of the southern South China Sea and explores the impact of coral evolution radiation and microbial dynamics on the heat tolerance of Fungiidae. The results found that Cycloseris was an ancient branch of Fungiidae, dating back approximately 147.8953 Mya, and Fungiidae differentiated into two ancestral clades (clades I and II) before 107.0312 Ma. Fungiidae exhibited specific symbioses with the Cladocopium C27 sub-clade. Notably, the Cladocopium C1 sub-clade has a high relative abundance in clade I, whereas the heat-tolerant Cladocopium C40 and C3u sub-clades subdominante in clade II. Regarding bacterial communities, Cycloseris costulata, the earliest divergent species, had higher bacterial ß-diversity, while the latest divergent species, Lithophyllon scabra, displayed lower bacterial α-diversity and higher community stability. Beneficial bacteria dominante Fungiidae's bacterial community (54%). The co-occurrence network revealed that microbial networks in clade II exhibited lower complexity and greater resilience than those in clade I. Our study highlights that host evolutionary radiation and microbial communities shaped Fungiidae's thermal tolerance. The variability in subdominant Symbiodiniaceae populations may contribute to interspecific differences in thermal tolerance along the evolutionary branches of Fungiidae. The presence of abundant beneficial bacteria may further enhance the thermal ability of the Fungiidae. Furthermore, the later divergent species of Fungiidae have stronger heat tolerance, possibly driven by the increased regulation ability of the host on the bacterial community, greater microbial community stability, and interaction network resistance.IMPORTANCECoral reefs are facing significant threats due to global warming. The heat tolerance of coral holobionts depends on both the coral host and its microbiome. However, the association between coral evolutionary radiation and interspecific differences in microbial communities remains unclear. In this study, we investigated the role of evolutionary radiation and microbial community dynamics in shaping the thermal acclimation potential of Fungiidae in the Sanjiao Reef of the southern South China Sea. The study's results suggest that evolutionary radiation enhances the thermal tolerance of Fungiidae. Fungiidae species that have diverged more recently have exhibited a higher presence of heat-tolerant Symbiodiniaceae taxa, more stable bacterial communities, and a robust and resilient microbial interaction network, improving the thermal adaptability of Fungiidae. In summary, this study provides new insights into the thermal adaptation patterns of corals under global warming conditions.