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Abstract Objective Inflammation, malnutrition, and cancer are intricately interconnected. Despite this, only a few studies have delved into the relationship between inflammatory malnutrition and the risk of death among cancer survivors. This study aimed to specifically investigate the association between the categorically defined Naples prognostic score (NPS) and the prognosis of cancer survivors. Methods Data from 42,582 participants in the National Health and Nutrition Examination Survey (NHANES, 1999–2018) were subjected to analysis. Naples prognostic scores (NPS) were computed based on serum albumin (ALB), total cholesterol (TC), neutrophil to lymphocyte ratio (NLR), and lymphocyte to monocyte ratio (LMR), and participants were stratified into three groups accordingly. Cancer status was ascertained through a self-administered questionnaire, while mortality data were sourced from the National Death Index up to December 31, 2019. Multiple logistic regression was employed to estimate the odds ratio (OR) with a 95% confidence interval (CI) between NPS and cancer prevalence within the U.S. community population. Kaplan-Meier survival analysis and the Log-rank test were utilized to compare survival disparities among the three groups. Additionally, Cox proportional regression was utilized to estimate the hazard ratio (HR) with a 95% CI. Results The incidence of cancers was 9.86%. Among the participants, 8140 individuals (19.1%) were classified into Group 0 (NPS 0), 29,433 participants (69.1%) into Group 1 (NPS 1 or 2), and 5009 participants (11.8%) into Group 2 (NPS 3 or 4). After adjusting for confounding factors, the cancer prevalence for the highest NPS score yielded an odds ratio (OR) of 1.64 (95% CI: 1.36, 1.97) (P(for trend)

Abstract Electrocatalytic CO2 reduction (CO2RR), an emerging sustainable energy technology to convert atmospheric CO2 into value‐added chemicals, has received extensive attention. However, the high thermodynamic stability of CO2 and the competitive hydrogen evolution reaction lead to poor catalytic performances, hardly meeting industrial application demands. Due to abundant reserves and favorable CO selectivity, zinc (Zn)‐based catalysts have been considered one of the most prospective catalysts for CO2‐to‐CO conversion. A series of advanced zinc‐based electrocatalysts, including Zn nanosheets, Zn single atoms, defective ZnO, and metallic Zn alloys, have been widely reported for CO2RR. Despite significant progress, a comprehensive and fundamental summary is still lacking. Herein, this review provides a thorough discussion of effective modulation strategies such as morphology design, doping, defect, heterointerface, alloying, facet, and single‐atom, emphasizing how these methods can influence the electronic structure and adsorption properties of intermediates, as well as the catalytic activity of Zn‐based materials. Moreover, the challenges and opportunities of Zn‐based catalysts for CO2RR are also discussed. This review is expected to promote the broader application of efficient Zn‐based catalysts in electrocatalytic CO2RR, thus contributing to a future of sustainable energy.

Abstract Clinical deployment of oligonucleotides requires delivery technologies that improve stability, target tissue accumulation and cellular internalization. Exosomes show potential as ideal delivery vehicles. However, an affordable generalizable system for efficient loading of oligonucleotides on exosomes remain lacking. Here, we identified an Exosomal Anchor DNA Aptamer (EAA) via SELEX against exosomes immobilized with our proprietary CP05 peptides. EAA shows high binding affinity to different exosomes and enables efficient loading of nucleic acid drugs on exosomes. Serum stability of thrombin inhibitor NU172 was prolonged by exosome-loading, resulting in increased blood flow after injury in vivo. Importantly, Duchenne Muscular Dystrophy PMO can be readily loaded on exosomes via EAA (EXOEAA-PMO). EXOEAA-PMO elicited significantly greater muscle cell uptake, tissue accumulation and dystrophin expression than PMO in vitro and in vivo. Systemic administration of EXOEAA-PMO elicited therapeutic levels of dystrophin restoration and functional improvements in mdx mice. Altogether, our study demonstrates that EAA enables efficient loading of different nucleic acid drugs on exosomes, thus providing an easy and generalizable strategy for loading nucleic acid therapeutics on exosomes.

Abstract Background Long noncoding RNAs (lncRNAs) have emerged as key players in tumorigenesis and tumour progression. However, the biological functions and potential mechanisms of lncRNAs in colorectal cancer (CRC) are unclear. Methods The novel lncRNA POU6F2-AS1 was identified through bioinformatics analysis, and its expression in CRC patients was verified via qRT–PCR and FISH. In vitro and in vivo experiments, such as BODIPY staining, Oil Red O staining, triglyceride (TAG) assays, and liquid chromatography mass spectrometry (LC-MS) were subsequently performed with CRC specimens and cells to determine the clinical significance, and functional roles of POU6F2-AS1. Biotinylated RNA pull-down, RIP, Me-RIP, ChIP, and patient-derived organoid (PDO) culture assays were performed to confirm the underlying mechanism of POU6F2-AS1. Results The lncRNA POU6F2-AS1 is markedly upregulated in CRC and associated with adverse clinicopathological features and poor overall survival in CRC patients. Functionally, POU6F2-AS1 promotes the growth and lipogenesis of CRC cells both in vitro and in vivo. Mechanistically, METTL3-induced m6A modification is involved in the upregulation of POU6F2-AS1. Furthermore, upregulated POU6F2-AS1 could tether YBX1 to the FASN promoter to induce transcriptional activation, thus facilitating the growth and lipogenesis of CRC cells. Conclusions Our data revealed that the upregulation of POU6F2-AS1 plays a critical role in CRC fatty acid metabolism and might provide a novel promising biomarker and therapeutic target for CRC.

Abstract Selenium is an essential multifunctional trace element in diverse organisms. The only Se-glycosyltransferase identified that catalyzes the incorporation of selenium in selenoneine biosynthesis is SenB from Variovorax paradoxus. Although the biochemical function of SenB has been investigated, its substrate specificity, structure, and catalytic mechanism have not been elucidated. Here, we reveal that SenB exhibits sugar donor promiscuity and can utilize six UDP-sugars to generate selenosugars. We report crystal structures of SenB complexed with different UDP-sugars. The key elements N20/T23/E231 contribute to the sugar donor selectivity of SenB. A proposed catalytic mechanism is tested by structure-guided mutagenesis, revealing that SenB yields selenosugars by forming C-Se glycosidic bonds via spontaneous deprotonation and disrupting Se-P bonds by nucleophilic water attack, which is initiated by the critical residue K158. Furthermore, we functionally and structurally characterize two other Se-glycosyltransferases, CbSenB from Comamonadaceae bacterium and RsSenB from Ramlibacter sp., which also exhibit sugar donor promiscuity.

Abstract Ulcerative colitis (UC) manifests clinically with chronic intestinal inflammation and microflora dysbiosis. Although biologics can effectively control inflammation, efficient delivery to the colon and colon epithelial cells remains challenging. Milk‐derived extracellular vesicles (EV) show promise as an oral delivery tool, however, the ability to load biologics into EV presents challenges to therapeutic applications. Here, we demonstrate that fusing cell‐penetrating peptide (TAT) to green fluorescent protein (GFP) enabled biologics loading into EV and protected against degradation in the gastrointestinal environment in vitro and in vivo after oral delivery. Oral administration of EV loaded with anti‐tumour necrosis factor‐α (TNF‐α) nanobody (VHHm3F) (EVVHH) via TAT significantly reduced tissue TNF‐α levels and alleviated pathologies in mice with acute UC, compared to VHH alone. In mice with chronic UC, simultaneously introducing VHH and an antimicrobial peptide LL37 into EV (EVLV), then administering orally improved intestinal barrier, inflammation and microbiota balance, resulted in relief of UC‐induced depression and anxiety. Collectively, we demonstrated that oral delivery of EVLV effectively alleviated UC in mice and TAT efficiently loaded biologics into EV to confer protection from degradation in the gastrointestinal tract. This therapeutic strategy is promising for UC and is a simple and generalizable approach towards drug‐loaded orally‐administrable EV treatment for other diseases.

Abstract Wearable photothermal materials can capture light energy in nature and convert it into heat energy, which is critical for flexible outdoor sports. However, the conventional flexible photothermal membranes with low specific surface area restrict the maximum photothermal capability, and loose structure of electrospun membrane limits durability of wearable materials. Here, an ultrathin nanostructure candle soot/multi‐walled carbon nanotubes/poly (L‐lactic acid) (CS/MWCNTs/PLLA) photothermal membrane is first prepared via solvent‐induced recrystallization. The white blood cell membrane‐like nanowrinkles with high specific surface area are achieved for the first time and exhibit optimal light absorption. The solvent‐induced recrystallization also enables the membrane to realize large strength and durability. Meanwhile, the membranes also show two‐sided heterochromatic features and transparency in thick and thin situations, respectively, suggesting outstanding fashionability. The nano‐wrinkled photothermal membranes by novel solvent‐induced recrystallization show high flexibility, fashionability, strength, and photothermal characteristics, which have huge potential for outdoor warmth and winter sportswear.

Abstract Background Although both preclinical and clinical studies have shown the great application potential of MSCs (mesenchymal stem/stromal cells) in treating many kinds of diseases, therapeutic inconsistency resulting from cell heterogeneity is the major stumbling block to their clinical applications. Cell population diversity and batch variation in the cell expansion medium are two major inducers of MSC heterogeneity. Methods Cell population diversity was investigated through single-cell RNA sequencing analysis of human MSCs derived from the umbilical cord and expanded with fully chemically defined medium in the current study. Then, the MSC subpopulation with enhanced anti-inflammatory effects was studied in vitro and in vivo. Results Our data showed that MSCs contain different populations with different functions, including subpopulations with enhanced functions of exosome secretion, extracellular matrix modification and responses to stimuli (regeneration and immune response). Among them, CD317+ MSCs have improved differentiation capabilities and enhanced immune suppression activities. Underlying mechanism studies showed that higher levels of TSG6 confer enhanced anti-inflammatory functions of CD317+ MSCs. Conclusions Thus, CD317+ MSCs might be a promising candidate for treating immunological disorder-related diseases.

To provide new insights into the development and utilization of Douchi artificial starters, three common strains (Aspergillus oryzae, Mucor racemosus, and Rhizopus oligosporus) were used to study their influence on the fermentation of Douchi. The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi. Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi, and its umami taste was more prominent in sensory evaluation (P < 0.01), while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines, making the aroma, sauce, and Douchi flavor more abundant. According to the Pearson and PLS analyses results, sweetness was significantly negatively correlated with phenylalanine, cysteine, and acetic acid (P < 0.05), bitterness was significantly negatively correlated with malic acid (P < 0.05), the sour taste was significantly positively correlated with citric acid and most free amino acids (P < 0.05), while astringency was significantly negatively correlated with glucose (P < 0.001). Thirteen volatile compounds such as furfuryl alcohol, phenethyl alcohol, and benzaldehyde caused the flavor difference of three types of Douchi. This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

ObjectiveThe objective of this study was to provide a multi-modal deep learning framework for forecasting the survival of rectal cancer patients by utilizing both digital pathological images data and non-imaging clinical data.Materials and methodsThe research included patients diagnosed with rectal cancer by pathological confirmation from January 2015 to December 2016. Patients were allocated to training and testing sets in a randomized manner, with a ratio of 4:1. The tissue microarrays (TMAs) and clinical indicators were obtained. Subsequently, we selected distinct deep learning models to individually forecast patient survival. We conducted a scanning procedure on the TMAs in order to transform them into digital pathology pictures. Additionally, we performed pre-processing on the clinical data of the patients. Subsequently, we selected distinct deep learning algorithms to conduct survival prediction analysis using patients’ pathological images and clinical data, respectively.ResultsA total of 292 patients with rectal cancer were randomly allocated into two groups: a training set consisting of 234 cases, and a testing set consisting of 58 instances. Initially, we make direct predictions about the survival status by using pre-processed Hematoxylin and Eosin (H&E) pathological images of rectal cancer. We utilized the ResNest model to extract data from histopathological images of patients, resulting in a survival status prediction with an AUC (Area Under the Curve) of 0.797. Furthermore, we employ a multi-head attention fusion (MHAF) model to combine image features and clinical features in order to accurately forecast the survival rate of rectal cancer patients. The findings of our experiment show that the multi-modal structure works better than directly predicting from histopathological images. It achieves an AUC of 0.837 in predicting overall survival (OS).ConclusionsOur study highlights the potential of multi-modal deep learning models in predicting survival status from histopathological images and clinical information, thus offering valuable insights for clinical applications.

The mortality rate of gastric varices bleeding can reach 20% within 6 weeks. Isolated gastric varices (IGVs) refer to gastric varices without esophageal varices and typically arise as a common complication of left portal hypertension. Although IGVs commonly form in the setting of splenic vein occlusion, the combination of antiphospholipid syndrome and protein S deficiency leading to splenic vein occlusion is rare. We herein present a case of a 28-year-old woman with intermittent epigastric pain and melena. She was diagnosed with antiphospholipid syndrome based on the triad of pregnancy morbidity, unexplained venous occlusion, and positive lupus anticoagulant. Laparoscopic splenectomy and pericardial devascularization were performed for the treatment of IGVs. During the 6-month postoperative follow-up, repeated endoscopy and contrast-enhanced computed tomography revealed disappearance of the IGVs. This is the first description of splenic vein occlusion associated with both antiphospholipid syndrome and protein S deficiency. We also provide a review of the etiology, clinical manifestations, diagnosis, and treatment methods of IGVs.

Electrospun fibre has shown great potential in tissue engineering and regenerative medicine due to its high specific surface area and extracellular matrix-mimicking structure. However, fabricating an electrospun fibrous scaffold with controllable complex 3D macroscopic configuration remains a challenge. In the present study, a novel method was designed to transform 2D electrospun poly (L-lactic acid) (PLLA) fibrous membrane to tubular PLLA fibrous scaffolds with 3D complex but tailored configuration. The electrospun PLLA fibrous membrane was rolled around a designed mould and then treated with acetone. Treated vascular grafts’ length, diameter, and shape can be tailored by the mould parameters. Moreover, treated vascular grafts achieve favourable mechanical properties (Young’s modulus = 155 MPa, tensile stress = 8.79 MPa and radial force = 2.2 N) and the mechanical properties could be engineered on demand. In addition, treated vascular grafts kept their initial structure and size during long-term in vitro experiments once they were formed. In addition, with the acetone-induced recrystallization of PLLA, pristine solid PLLA fibres were changed to hierarchical porous PLLA fibres with ultra-high specific surface area (28.9 m2/g) and wettability (water contact angle = 101.32°), which has positive effects on cell adhesion and proliferation ability. A7r5 in vitro experiment shows that the proliferation rate of treated vascular grafts increased 153% at day 4 and 170.6% at day 7 compared with pristine vascular grafts.

The exhaust outlet space arrangement is a crucial part to avoid casualties and economic losses in the event of contaminant gas leakage. To handle this problem, this work proposed a novel optimization method based on the coupling of the genetic algorithm (GA) and ant colony algorithm optimization (ACO), and the fitness function used in the optimization method is constructed as an implicit form. In this proposed optimization method, the ACO is used to obtain the implicit fitness function value, while the GA is selected to conduct the space arrangement optimization based on the iteration results transferred from ACO. With the help of this novel methodology, the influence of obstacles in space could be well considered into the space arrangement optimization, which leads to a reliable optimization result of the exhaust outlet configuration. Moreover, to validate the accuracy and efficiency of this coupling method, the optimization results are taken into the computational fluid dynamics numerical model to give a comparison with the conventional configuration. The comparison results indicate that the exhaust outlet arrangement following the optimization results shows a lower gas concentration value during the diffusion process. In addition, based on this optimal exhaust outlet space arrangement, the models with various leakage rates are also investigated and discussed in the numerical work. It is believed that the proposed method could provide an effective measure for the space arrangement optimization and the design of gas leakage protection.

Clinical cognitive advancement within the Alzheimer’s disease (AD) continuum is intimately connected with sustained accumulation of tau protein pathology. The biological brain age and its gap show great potential for pathological risk and disease severity. In the present study, we applied multivariable linear support vector regression to train a normative brain age prediction model using tau brain images. We further assessed the predicted biological brain age and its gap for patients within the AD continuum. In the AD continuum, evaluated pathologic tau binding was found in the inferior temporal, parietal-temporal junction, precuneus/posterior cingulate, dorsal frontal, occipital, and inferior-medial temporal cortices. The biological brain age gaps of patients within the AD continuum were notably higher than those of the normal controls (p < 0.0001). Significant positive correlations were observed between the brain age gap and global tau protein accumulation levels for mild cognitive impairment (r = 0.726, p < 0.001), AD (r = 0.845, p < 0.001), and AD continuum (r = 0.797, p < 0.001). The pathologic tau-based age gap was significantly linked to neuropsychological scores. The proposed pathologic tau-based biological brain age model could track the tau protein accumulation trajectory of cognitive impairment and further provide a comprehensive quantification index for the tau accumulation risk.

Two-dimensional van der Waals heterostructures have good application prospects in solar energy conversion due to their excellent optoelectronic performance. In this work, the electronic structures of Sc2CF2/Sc2CCl2, Sc2CF2/Sc2CBr2, and Sc2CCl2/Sc2CBr2 heterostructures, as well as their properties in photocatalysis and photovoltaics, have been comprehensively studied using the first-principles method. Firstly, both of the three thermodynamically and dynamically stable heterostructures are found to have type-II band alignment with band gap values of 0.58 eV, 0.78 eV, and 1.35 eV. Meanwhile, the photogenerated carriers in Sc2CF2/Sc2CCl2 and Sc2CF2/Sc2CBr2 heterostructures are predicated to follow the direct Z-scheme path, enabling their abilities for water splitting. As for the Sc2CCl2/Sc2CBr2 heterostructure, its photovoltaic conversion efficiency is estimated to be 20.78%. Significantly, the light absorption coefficients of Sc2CF2/Sc2CCl2, Sc2CF2/Sc2CBr2, and Sc2CCl2/Sc2CBr2 heterostructures are enhanced more than those of the corresponding monolayers. Moreover, biaxial strains have been observed to considerably tune the aforementioned properties of heterostructures. All the theoretical results presented in this work demonstrate the application potential of Sc2CX2/Sc2CY2 (X, Y = F, Cl, Br) heterostructures in photocatalysis and photovoltaics.

With the continuous advancement of urbanization and industrialization, non-grain production on cropland (NGPCL) is gradually becoming more widespread. This phenomenon will compress the space for grain production and trigger a global food crisis. How to scientifically understand and effectively control NGPCL has become a scientific issue. This study, conducted at the plot scale, establishes a measurement index for NGPCL and further explores the characteristics and driving mechanisms of NGPCL in mountainous areas. The results indicate the following: (1) Compared to plots for food-growing, plots for non-grain production tend to be more dispersed, with terraces showing the most significant dispersion, while plains exhibit the highest degree of aggregation. (2) In terms of irrigation conditions, irrigated land and dry land are more likely to undergo NGPCL. In terms of topography, slope croplands have the highest probability of being used for NGPCL. (3) Regions with steeper slopes, higher elevations, greater differences in altitude from the settlement, farther distances from settlements and roads, yet closer proximity to forests, are more likely to engage in NGPCL. (4) Different plot characteristics have varying impacts on NGPCL. Plot characteristics primarily affect the costs and returns of grain production, driving farmers to change their production patterns and triggering NGPCL.

Background: Dysbiosis is associated with colorectal cancer (CRC) and adenomas (CRA). However, the robustness of diagnostic models based on microbial signatures in multiple cohorts remains unsatisfactory.Materials and Methods: In this study, we used machine learning models to screen metagenomic signatures from the respective cross-cohort datasets of CRC and CRA (selected from CuratedMetagenomicData, each disease included 4 datasets). Then select a CRC and CRA data set from the CuratedMetagenomicData database and meet the requirements of having both metagenomic data and clinical data. This data set will be used to verify the inference that integrating clinical features can improve the performance of microbial disease prediction models.Results: After repeated verification, we selected 20 metagenomic features that performed well and were stably expressed within cross-cohorts to represent the diagnostic role of bacterial communities in CRC/CRA. The performance of the selected cross-cohort metagenomic features was stable for multi-regional and multi-ethnic populations (CRC, AUC: 0.817–0.867; CRA, AUC: 0.766–0.833). After clinical feature combination, AUC of our integrated CRC diagnostic model reached 0.939 (95% CI: 0.932–0.947, NRI=30%), and that of the CRA integrated model reached 0.925 (95%CI: 0.917–0.935, NRI=18%).Conclusion: In conclusion, the integrated model performed significantly better than single microbiome or clinical feature models in all cohorts. Integrating cross-cohort common discriminative microbial features with clinical features could help construct stable diagnostic models for early non-invasive screening for CRC and CRA.

ABSTRACT Early identification of severe 2019 coronavirus disease (COVID-19) cases is of great significance. We included 92 COVID-19 patients and 22 healthy controls and collected their laboratory test data and stool for metagenomic sequencing analysis. We found that the proportion of severe COVID-19 cases was significantly increased in patients with reduced lymphocytes and elevated neutrophils and had unique intestinal microbiota. Pseudothermotoga hypogea and Lachnospiraceae bacterium GAM79 were the species of bacteria that markedly decreased in COVID-19 patients compared to control individuals. For COVID-19 patients, Enterococcus sp. DA9, Caldicellulosiruptor obsidiansis, and Enterococcus faecium were the species of bacteria that significantly altered among patients with normal lymphocytes and neutrophils and patients with decreased lymphocytes and/or increased neutrophils, respectively. Fecal abundances of Enterococcus sp. DA9, Prevotella intermedia, and Bifidobacterium dentium were correlated with COVID-19 disease severity. Decreased lymphocytes and increased neutrophils, combined with decreased Bifidobacterium dentium and Prevotella intermedia, and increased Enterococcus sp. DA9 have the highest power to predict severe cases of COVID-19 patients (area under receiver operating characteristic curve: 0.79). In conclusion, changes in the abundance of intestinal bacteria can reflect the severity of COVID-19 disease, and the combination with lymphocytes and neutrophils might be prognostic factors of COVID-19. IMPORTANCE The 2019 coronavirus disease (COVID-19) patients had a unique profile of gut bacteria. In this study, we characterized the intestinal bacteria in our COVID-19 cohorts and found that there was an increased incidence of severe cases in COVID-19 patients with decreased lymphocytes and increased neutrophils. Levels of lymphocytes and neutrophils and abundances of intestinal bacteria correlated with the severity of COVID-19.

Analyzing land subsidence using Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technology holds significant importance for the secure development of urban areas. Shenzhen, being a crucial component of the Pearl River Delta, faces the threat of land subsidence, similar to most deltaic cities. Numerous studies have already indicated the presence of severe land subsidence in certain localities of Shenzhen. However, due to limitations in data scope and research methodologies, the comprehensive spatial-temporal distribution of land subsidence across the entire city of Shenzhen remains unclear. This study initially employed MT-InSAR technology to process a total of 534 Sentinel-1A SAR images from three different frames (P11F71, P113F71, P11F65), covering the entire city of Shenzhen. This processing resulted in the generation of subsidence rate maps and subsidence time series. Subsequently, the temporal evolution patterns of the subsidence were analyzed while significant subsidence regions were identified. By integrating information from optical images reflecting human activities on the Earth’s surface, the study deduced the subsidence mechanisms in various significant subsidence areas. Research findings indicate that land subsidence in Shenzhen is primarily caused by construction activities, with a concentration in the western coastal areas of Shenzhen, reaching a maximum rate of 80 mm/yr, located at the estuary of Dongbao River (113.770385, 22.745305). The cumulative subsidence from March 2017 to June 2023 amounts to 500 mm. The expansion of the Qinglinjing Reservoir has led to an increased demand for water, resulting in a significant rise in formation pressure and subsequent land subsidence. InSAR land subsidence monitoring and analysis in urban areas can address the spatial and temporal resolution limitations of traditional subsidence monitoring methods, providing effective recommendations for widespread subsidence prevention and control.

Remote sensing (RS) is often employed to estimate suspended sediment concentration (SSC) in rivers, and the availability of hyperspectral imagery enhances the effectiveness of RS-based water quality monitoring due to its high spectral resolution. Yet, the necessity of hyperspectral imagery for SSC estimation in rivers has not been fully validated. This study thus compares the performance of hyperspectral RS with that of multispectral RS by conducting field-scale experiments in shallow rivers. In the field experiments, we measured radiance from a water body mixed with suspended sediments using a drone-mounted hyperspectral sensor, with the sediment and riverbed types considered as controlling factors. We retrieved the SSC from UAV imagery using an optimal band ratio analysis, which successfully estimated SSC distributions in the sand bed conditions with both multispectral and hyperspectral data. In the vegetated bed conditions, meanwhile, the prediction accuracy decreased significantly due to the temporally varying bottom reflectance associated with the random movement of vegetation caused by near-bed turbulence. This is because temporally inhomogeneous bottom reflectance distorts the relationship between the SSC and total reflectance. Nevertheless, the hyperspectral imaging exhibited better prediction accuracy than the multispectral imaging, effectively extracting optimal spectral bands sensitive to back-scattered reflectance from sediments while constraining the bottom reflectance caused by the vegetation-covered bed.

Focus structures, a complex aspect of information structure in language, have garnered significant attention in psycholinguistics. The question of whether Chinese preschoolers aged 4–6 years possess the ability to process focus structures in oral communication, and how cognitive factors influence this ability, remains a research focal point. To address this, we recruited 100 Chinese preschoolers aged 4–6 years as participants in our study. This study manipulated the positions of focus particles in sentences to investigate the impact of phonological awareness on young children’s comprehension of focus structures. Additionally, we examined the mediating roles of cognitive flexibility and inhibitory control. Our findings indicate the following: (1) phonological awareness positively predicted the accuracy of focus structural processing; (2) inhibitory control did not significantly predict the accuracy of focus structural processing; and (3) cognitive flexibility partially mediated the relationship between phonological awareness and focus structural comprehension. These results confirmed the predictive effect of cognitive flexibility on children’s comprehension of focus structures. Moreover, they demonstrate that young children’s phonological awareness can predict their focus structure comprehension ability through the mediating role of cognitive flexibility. This suggests that children’s cognitive flexibility can aid in understanding sentences with focus structures.

As one of the most significant disturbance sources in the upper marine environment of the South China Sea, tropical cyclones (typhoons) serve as a typical research subject for investigating the energy transfer process between the ocean and atmosphere. Utilizing satellite remote sensing data and focusing on Typhoon Rey No. 22’s transit event in 2021, this study quantitatively analyzes typhoon-induced energy input through heat pumping and cold suction at both surface and subsurface levels of the ocean. Additionally, it explores the response characteristics and feedback mechanisms of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the South China Sea to typhoon events. The research results show that the SST variation along the typhoon track displayed an asymmetric pattern, with a more pronounced warming on the right side and a cold anomaly lasting for 3–5 days on the left side. The subsurface warm anomaly dominated on the right side, showing a maximum temperature difference of 1.54 °C, whereas Ekman suction-induced upwelling led to cooling effects both at the subsurface and surface level on the left side, resulting in a maximum temperature difference of −3.28 °C. During the typhoon event, there was a significant decrease in sea surface heat flux, reaching 323.36 W/m2, accompanied by corresponding changes in SST due to processes such as upwelling, seawater mixing, and air–sea heat transfer dynamics where anomalies arising from oceanic dynamic processes and exchange through sea surface heat flux contributed equally. Furthermore, strong suction-induced upwelling during the typhoon influenced chlorophyll concentration within the central and western regions of the South China Sea (13.5° N–16.5° N, 111° E–112.5° E), resulting in significant enhancement and reaching its peak value at approximately 0.65 mg/L. The average chlorophyll concentration increased by approximately 0.31 mg/L.

In a SAR image acquired by the ERS-2 satellite, crossed “X-shape” internal solitary waves (ISWs) south to Dongsha Island are found to be a wave–wave interaction composed of five solitons: two head waves, two tail waves, and the overlapped part. To explain this remote sensing phenomenon, based on a high-resolution three-dimensional MIT general circulation model (MITgcm) using realistic topography and tidal forcing, the “X-shape” internal waves are reproduced at the same location. The development processes of the waves indicate that the “X-shape” ISWs are two waves diffracted from one internal wave southeast to Dongsha Island. During the propagation, the amplitude of their overlapped part of the “X-shape” ISWs becomes significantly larger than the sum of the amplitudes of both head waves, which proves that nonlinear wave–wave interaction has occurred. Based on wave–wave interaction theory, the theoretical maximum value of the amplitude of the overlapped part at the initial moment is calculated as 14.12 m, which is in good agreement with the model results of 14 m. Meanwhile, the variation of the theoretical amplitude of the overlapped part is basically consistent with that of the modeled one, confirming the occurrence of the wave–wave interaction. Besides, when the waves propagate over varying water depths, the type of the wave–wave interaction can change rather than being fixed from the start.

The dispersion coefficients are crucial in understanding the spreading of pollutant clouds in river flows, particularly in the context of the depth-averaged two-dimensional (2D) advection–dispersion equation (ADE). Traditionally, the 2D stream-tube routing procedure (2D STRP) has been the predominant method for determining both the longitudinal and transverse dispersion coefficients of the 2D ADE under transient concentration conditions. This study aims to quantitatively analyze and address the limitations of the 2D STRP using hypothetically generated data. The findings of these evaluations revealed that the existing 2D STRP failed to accurately reproduce reliable results when the tracer clouds reached wall boundaries. This limitation prompted the development of the 2D STRP-i, which effectively resolves this drawback. The newly developed routing-based observation method, 2D STRP-i, enables the reliable estimation of dispersion coefficients, considering the effect of the wall boundary. The results indicated that the existing 2D STRP yielded 2D dispersion coefficients with relative errors ranging from 40% to 200%, while 2D STRP-i consistently yielded relative errors of 3% to 5% on average. When applied to tracer test data obtained through remote sensing, the 2D STRP-i demonstrated its ability to accurately observe temporal concentration distributions, even when wall boundaries have a significant impact on contaminant transport.