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Abstract Background Post-translational modification pathway of protein ubiquitination is intricately associated with tumorigenesis. We previously reported elevated ubiquitin-conjugating enzyme 2T (UBE2T) as an independent risk factor in stage I lung adenocarcinoma and promoting cellular proliferation. However, its underlying mechanisms needed further investigation. Methods Immunohistochemistry was used to assess the expression of UBE2T and retinoic acid receptor-related orphan receptor α (RORA) in stage I LUAD. Cell proliferation, migration, and invasion of LUAD cell lines were measured by Cell Counting Kit-8 assay (CCK-8), Colony-forming assay and Transwell assay, respectively. Western blot analysis was performed to determine the expression of epithelial-mesenchymal transition (EMT) markers. A xenograft model was established to evaluate the proliferative capacity of UBE2T and its interaction with RORA in promoting LUAD. Mechanistic insights into the promotion of early-stage LUAD by UBE2T were obtained through luciferase reporter assay, chromatin immunoprecipitation and co-immunoprecipitation. Results UBE2T and RORA expression was significantly up- and down-regulated in early-stage LUAD patients which’s proved to be associated with unfavorable outcomes, strengthened cell proliferation, migration, EMT and invasion through its interaction with RORA both in vivo and in vitro. The growth NSCLC xenografts was reduced by down-expression of UBE2T but was suppressed by RORA knockout. Mechanistically, UBE2T mediated the ubiquitination of the intermediate transcription factor PBX1, which played a transcriptional role in downstream regulation of RORA. Conclusion The oncogenic role of UBE2T and the UBE2T-PBX1-RORA axis in driving malignant progression in Stage I LUAD had been established. UBE2T might be a novel and promising therapeutic target for LUAD treatment.

As a alternative for natural enzymes, nanozymes has shown enzyme-like activity and selectivity in the field of various kinds of biomedical application, which has attracted considerable research interest. Recently, single-atom catalysts (SACs) have been extensively studied due to their similar active centers, coordination environment and better stability to natural enzymes. Metal-organic frameworks (MOFs) have been demonstrated as highly promising precursors for the synthesis of various types of SACs. MOF-derived SACs can not only significantly enhance the catalytic activity, but also improve the selectivity of nanozymes due to tunable coordination environment and structure, thereby receiving widespread attention in biomedicine. This review provided an overview of the preparation strategies for MOF-derived SACs, and then detailed the latest research progress of the SACs in the biomedical field for cancer, antibacterial, antioxidation and biosensors. Finally, the challenges and potential future opportunities of MOF-derived SACs in biomedical applications are proposed.

Abstract Photo-thermal-coupling ammonia decomposition presents a promising strategy for utilizing the full-spectrum to address the H2 storage and transportation issues. Herein, we exhibit a photo-thermal-catalytic architecture by assembling gallium nitride nanowires-supported ruthenium nanoparticles on a silicon for extracting hydrogen from ammonia aqueous solution in a batch reactor with only sunlight input. The photoexcited charge carriers make a predomination contribution on H2 activity with the assistance of the photothermal effect. Upon concentrated light illumination, the architecture significantly reduces the activation energy barrier from 1.08 to 0.22 eV. As a result, a high turnover number of 3,400,750 is reported during 400 h of continuous light illumination, and the H2 activity per hour is nearly 1000 times higher than that under the pure thermo-catalytic conditions. The reaction mechanism is extensively studied by coordinating experiments, spectroscopic characterizations, and density functional theory calculation. Outdoor tests validate the viability of such a multifunctional architecture for ammonia decomposition toward H2 under natural sunlight.

Abstract Background This study aimed to investigate the potential variance in the prevalence of early‐onset scoliosis among children aged 4–7 years and analyze the influencing factors. The goal was to establish a crucial reference point for monitoring and evaluating spinal curvature development in preschoolers, ultimately to reduce the occurrence of adverse health outcomes. Methods Children aged 4–7 years within the main urban area of Nanjing were selected using a stratified random sampling method. A team of four senior therapists conducted screenings for spinal curvature among children using visual inspection, the Adams forward bending test, and an electronic scoliometer to measure the angle of trunk rotation (ATR) and identify children displaying signs of scoliosis. Children with suspected scoliosis in the initial screening underwent X‐ray Cobb angle assessment for confirmation. The prevalence of early‐onset scoliosis was then determined from the screening results. R version 4.2.0 software was used to analyze the factors associated with scoliosis among children using partial least squares structural equation modeling. Results A total of 2281 children were included in this study, consisting of 1211 boys and 1070 girls, with a mean age of 5.44 ± 0.81 years (ranging from 4 to 7 years). Among them, 7.58% exhibited positive signs of scoliosis, 5.87% had early‐onset scoliosis, and the positive predictive value was 77.5%. Significant differences in ATR were observed among children in different age groups (Kruskal–Wallis = 15, p = 0.0104) and by sex (t = 3.17, p = 0.00153). Significant variations in ATR were noted in children with scoliosis (t = −22.7, p

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)

Purpose Meteorin-like (Metrnl) is a novel adipokine which is highly expressed in adipose tissue and has a beneficial effect on glucose and lipid metabolism. High density lipoprotein cholesterol (HDL-C) is well recognized to be inversely associated with cardiovascular events. However, the relationship between serum Metrnl levels and HDL-C in the type 2 diabetes mellitus (T2DM) remains unclear. Therefore, the present study aimed to evaluate the association of serum Metrnl with HDL-C levels in T2DM. Materials and Methods Eighty participants with T2DM were included in this cross-sectional study. They were divided into two groups according to HDL-C levels: Group1 (lower HDL-C group): HDL-C < 1.04 mmol/L; Group2 (higher HDL-C group): HDL-C ≥ 1.04 mmol/L. Serum Metrnl levels were measured by enzyme-linked immunosorbent assay (ELISA). Results As compared with lower HDL-C levels groups, serum Metrnl levels were significantly higher in the group with higher HDL-C. Binary logistic regression analysis showed serum Metrnl levels were positively associated with HDL-C group after adjustment with sex, age, body mass index (BMI), mean arterial pressure (MAP), fasting blood glucose (FPG), triglyceride (TG). Furthermore, serum Metrnl levels were inversely correlated with insulin resistance index (HOMA-IR). HDL-C levels were lowest in the group with the lowest Metrnl levels group and remained positively associated with Metrnl after adjustment for sex, age, BMI, TG, and HOMA-IR by using multivariate logistic regression analysis. Conclusion Serum Metrnl levels were positively associated with HDL-C levels in patients with T2DM.This suggests that increasing serum Metrnl levels maybe a candidate for improving lipid metabolism and preventing cardiovascular events in T2DM. Registry and the Registration No. of the Study/Trial The study was registered in the Chinese clinical trial registry (ChiCTR- 2100047148).

ObjectiveThe purpose of this study was to construct a diagnostic model by exploring the potential predictors of high-risk Papillary Thyroid Microcarcinoma (PTMC) and verifying its reliability.MethodsA retrospective analysis of PTMC patients who underwent surgical treatment from 2004 to 2015 in the SEER database (training set) and the clinical pathological ultrasound information of PTMC patients at the Sichuan Provincial People's Hospital from 2020 to 2022 (external validation set) was conducted. In the training set, univariate and multivariate logistic regression analyses were used to screen independent predictive factors for high-risk PTMC patients in pathology. A nomogram diagnostic model was further constructed. Additionally, ROC curves and calibration curves were drawn to evaluate the efficiency of the model. In the external validation set, the diagnostic model was indirectly evaluated based on preoperative ultrasound imaging features to explore the feasibility and reliability of diagnosing high-risk PTMC through preoperative ultrasound imaging features.ResultsA total of 1628 patients were included in the training set, and 530 patients were included in the test set. The independent risk factors for pathological high-risk PTMC were sex, age, tumor maximum diameter, tumor invasive, and cervical lymph nodes (P

BackgroundDeer antler stem cells (AnSCs) exhibit properties of both embryonic and mesenchymal stem cells, with superior self-renewal and proliferation, which drive rapid antler growth and regeneration. AnSCs and their derived small extracellular vesicles (sEVs) hold promising potential for applications in regeneration medicine. Due to the restricted proliferative capacity inherent in primary cells, the production capacity of AnSCs and their sEVs are limited. Human telomerase reverse transcriptase (hTERT) is the most important telomerase subunit, hTERT gene insertion has been successfully employed in generating immortalized cell lines.ResultsIn this study, we successfully established immortalized AnSCs by transducing the hTERT gene using lentivirus. Compared to primary AnSCs, hTERT-AnSCs demonstrated extended passage potential and accelerated proliferation rates while maintaining the mesenchymal stem cell surface markers CD44 and CD90. Additionally, hTERT-AnSCs retained the capacity for osteogenic, adipogenic, and chondrogenic differentiation. sEVs derived from hTERT-AnSCs exhibited a particle size distribution similar to that of AnSCs, both displaying a cup-shaped morphology and expressing CD81, ALIX, and TSG101, while notably lacking GM130 expression.ConclusionWe successfully isolated primary stem cells from deer antler and established the immortalized hTERT-AnSCs. Remarkably, this cell line maintains its stem cell characteristics even after 40 passages. The sEVs derived from these cells exhibit identical morphological and structural features to those of primary AnSCs. This research provides essential technical support for the application of AnSCs and their sEVs in regenerative medicine.

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 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 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 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.

Heterostructures are highly promising photocatalyst candidates for water splitting due to their advanced properties than those of pristine components. The ZnO/Sc2CF2 heterostructure was designed in this work, and its electronic structure was investigated to explore its potential for water splitting. The assessments of binding energy, phonon spectrum, ab initio molecular dynamics, and elastic constants provide strong evidence for its stability. The ZnO/Sc2CF2 heterostructure has an indirect band gap of 1.93 eV with a type-Ⅰ band alignment. The electronic structure can be modified with strain, leading to a transition in band alignment from type-Ⅰ to type-Ⅱ. The heterostructure is suitable for water splitting since its VBM and CBM stride over the redox potential. The energy barrier and built-in electric field, resulting from the charge transfer, facilitate the spatial separation of photogenerated carriers, enhancing their utilization efficiency for redox processes. The photogenerated carriers in the heterostructures with lattice compression greater than 6% follow the direct-Z transfer mechanism. The ZnO/Sc2CF2 heterostructure is confirmed with high photocatalytic activity by a Gibbs free energy change of HER, which is 0.89 eV and decreases to −0.52 eV under an 8% compressive strain. The heterostructure exhibits a remarkable enhancement in both absorption range and intensity, which can be further improved with strains. All these findings suggest that the ZnO/Sc2CF2 heterostructure is an appreciated catalyst for efficient photocatalytic water splitting.

Crystallization is important to the pharmaceutical, the chemical, and the materials fields, where the morphology of crystals is one of the key factors affecting the quality of crystallization. High-throughput screening based on microfluidic droplets is a potent technique to accelerate the discovery and development of new crystal morphologies with active pharmaceutical ingredients. However, massive crystal morphologies’ datum needs to be identified completely and accurately, which is time-consuming and labor-intensive. Therefore, effective morphologies’ detection and small-target tracking are essential for high-efficiency experiments. In this paper, a new improved algorithm YOLOv8 (YOLO-PBESW) for detecting indomethacin crystals with different morphologies is proposed. We enhanced its capability in detecting small targets through the integration of a high-resolution feature layer P2, and the adoption of a BiFPN structure. Additionally, in this paper, adding the EMA mechanism before the P2 detection head was implemented to improve network attention towards global features. Furthermore, we utilized SimSPPF to replace SPPF to mitigate computational costs and reduce inference time. Lastly, the CIoU loss function was substituted with WIoUv3 to improve detection performance. The experimental findings indicate that the enhanced YOLOv8 model attained advancements, achieving AP metrics of 93.3%, 77.6%, 80.2%, and 99.5% for crystal wire, crystal rod, crystal sheet, and jelly-like phases, respectively. The model also achieved a precision of 85.2%, a recall of 83.8%, and an F1 score of 84.5%, with a mAP of 87.6%. In terms of computational efficiency, the model’s dimensions and operational efficiency are reported as 5.46 MB, and it took 12.89 ms to process each image with a speed of 77.52 FPS. Compared with state-of-the-art lightweight small object detection models such as the FFCA-YOLO series, our proposed YOLO-PBESW model achieved improvements in detecting indomethacin crystal morphologies, particularly for crystal sheets and crystal rods. The model demonstrated AP values that exceeded L-FFCA-YOLO by 7.4% for crystal sheets and 3.9% for crystal rods, while also delivering a superior F1-score. Furthermore, YOLO-PBESW maintained a lower computational complexity, with parameters of only 11.8 GFLOPs and 2.65 M, and achieved a higher FPS. These outcomes collectively demonstrate that our method achieved a balance between precision and computational speed.

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.

Abstract Background In the midst of digital transformation, schools are transforming their classrooms as they prepare students for a world increasingly automated by new technologies, including artificial intelligence (AI). During curricular implementation, it has not made sense to teachers to teach AI as a stand-alone subject as it is not a traditional discipline in schools. As such, subject matter teachers may need to take on the responsibility of integrating AI content into discipline-based lessons to help students make connections and see its relevance rather than present AI as separate content. This paper reports on a study that piloted a new lesson package in science classrooms to introduce students to the idea of AI. Specifically, the AI-integrated science lesson package, designed by the research team, provided an extended activity that used the same context as an existing lesson activity. Three science teachers from different schools piloted the lesson package with small groups of students and provided feedback on the materials and implementation. Findings The findings revealed the teachers’ perceptions of integrating AI into science lessons in terms of the connection between AI and science, challenges when implementing the AI lesson package and recommendations on improvements. First, the teachers perceived that AI and science have similarities in developing accurate models with quality data and using simplified reasoning, while they thought that AI and science play complementary roles when solving scientific problems. Second, the teachers thought that the biggest challenge in implementing the lesson package was a lack of confidence in content mastery, while the package would be challenging to get buy-in from teachers regarding curriculum adaptation and targeting the appropriate audience. Considering these challenges, they recommended that comprehensive AI resources be provided to teachers, while this package can be employed for science enrichment programs after-school. Conclusions The study has implications for curriculum writers who design lesson packages that introduce AI in science classrooms and for science teachers who wish to contribute to the development of AI literacy for teachers and the extension of the range of school science and STEM to students.

The oxygen reduction reaction (ORR) electrocatalytic activity of Pt-based catalysts can be significantly improved by supporting Pt and its alloy nanoparticles (NPs) on a porous carbon support with large surface area. However, such catalysts are often obtained by constructing porous carbon support followed by depositing Pt and its alloy NPs inside the pores, in which the migration and agglomeration of Pt NPs are inevitable under harsh operating conditions owing to the relatively weak interaction between NPs and carbon support. Here we develop a facile electrospinning strategy to in-situ prepare small-sized PtZn NPs supported on porous nitrogen-doped carbon nanofibers. Electrochemical results demonstrate that the as-prepared PtZn alloy catalyst exhibits excellent initial ORR activity with a half-wave potential (E1/2) of 0.911 ​V versus reversible hydrogen electrode (vs. RHE) and enhanced durability with only decreasing 11 ​mV after 30,000 potential cycles, compared to a more significant drop of 24 ​mV in E1/2 of Pt/C catalysts (after 10,000 potential cycling). Such a desirable performance is ascribed to the created triple-phase reaction boundary assisted by the evaporation of Zn and strengthened interaction between nanoparticles and the carbon support, inhibiting the migration and aggregation of NPs during the ORR.

Abstract We apply an equal-velocity quark combination model to study the $$\varLambda _{c}^{+}/D^{0}$$ Λ c + / D 0 ratio in the range $$p_{T}\lesssim 10$$ p T ≲ 10 GeV/c in pp collisions at $$\sqrt{s}=13$$ s = 13 TeV. We decompose the ratio into four parts which are related to quark numbers, light-flavor quark $$p_{T}$$ p T spectrum, charm quark $$p_{T}$$ p T spectrum, momentum correlation between light and charm quarks, respectively. Their influence on $$\varLambda _{c}^{+}/D^{0}$$ Λ c + / D 0 ratio is individually studied. The curvature property of light-flavor quark $$p_{T}$$ p T spectrum is the main reason of the non-monotonic $$p_{T}$$ p T dependence of $$\varLambda _{c}^{+}/D^{0}$$ Λ c + / D 0 ratio exhibited in high multiplicity events. Moreover, the multiplicity dependence of $$\varLambda _{c}^{+}/D^{0}$$ Λ c + / D 0 ratio as the function of $$p_{T}$$ p T is mainly because of the multiplicity dependence of light-flavor quark $$p_{T}$$ p T spectrum. Using the light-flavor quark $$p_{T}$$ p T spectrum obtained from experimental data of light-flavor hadrons and charm quark $$p_{T}$$ p T spectrum obtained from FONLL and/or PYTHIA calculations, the $$p_{T}$$ p T dependence of experimental data of $$\varLambda _{c}^{+}/D^{0}$$ Λ c + / D 0 ratio in high multiplicity events and that in low multiplicity events in pp collisions at $$\sqrt{s}=13$$ s = 13 TeV are reasonably understood.

Triply periodical minimal surface (TPMS) structures have attracted much attention in the biomaterials, aerospace, and automotive industries because they are lightweight, have high strength, and can absorb energy and shocks. In this study, uniform skeletal (USK), uniform sheet (USH), grade skeletal (GSK), and grade sheet (GSH) diamond lattice structures with the same 20% volume fraction were fabricated by selective laser melting (SLM) using AlSi10Mg metal powder. Their mechanical properties, deformation behavior, and energy absorption performance were systematically investigated by compression tests and finite element analysis (FEA). The skeleton structures had a higher elastic modulus, yield strength, and more severe stress fluctuation than the sheet structures. In addition, comparing the 45° shear deformation for as-built uniform structures accompanied by a mixture of ductile and brittle fracture modes, both gradient structures fractured by a sub-layer pattern from the layer with a lower volume fraction. Furthermore, the numerical simulation results illustrated that the stress of the skeleton structures was mainly concentrated at the skeleton joint, while the sheet structures were distributed evenly on the thin wall, without being concentrated in the interconnection region. For skeleton structures, heat treatment controlled the failure degree by improving the microstructure of the material, while for GSH structures at 300 °C, the fracture mode changed from the previous layer-by-layer fracture to a 45° shear failure. The accumulated energy absorption of gradient structures was more than that of the uniform structure, especially the GSH structures and the energy absorption efficiency of the skeleton structures was higher.

Flexible electrochemical sensors can adhere to any bendable surface with conformal contact, enabling continuous data monitoring without compromising the surface’s dynamics. Among various materials that have been explored for flexible electronics, metal–organic frameworks (MOFs) exhibit dynamic responses to physical and chemical signals, offering new opportunities for flexible electrochemical sensing technologies. This review aims to explore the role of electrocatalysis in MOF films specifically designed for flexible electrochemical sensing applications, with a focus on their design, fabrication techniques, and applications. We systematically categorize the design and fabrication techniques used in preparing MOF films, including in situ growth, layer-by-layer assembly, and polymer-assisted strategies. The implications of MOF-based flexible electrochemical sensors are examined in the context of wearable devices, environmental monitoring, and healthcare diagnostics. Future research is anticipated to shift from traditional microcrystalline powder synthesis to MOF thin-film deposition, which is expected to not only enhance the performance of MOFs in flexible electronics but also improve sensing efficiency and reliability, paving the way for more robust and versatile sensor technologies.

Heterostructure catalysts are highly anticipated in the field of photocatalytic water splitting. AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures are proposed in this work, and the electronic structures were revealed with the first-principles method to explore their photocatalytic properties for water splitting. The results found that the thermodynamically stable AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures are indirect semiconductors with reduced band gaps of 1.75 eV and 1.84 eV, respectively. These two heterostructures have been confirmed to have type-Ⅰ band alignments, with both VBM and CBM contributed to by the Sc2CF2 layer. AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures exhibit the potential for photocatalytic water splitting as their VBM and CBM stride over the redox potential of water. Gibbs free energy changes in HER occurring on AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures are as low as −0.31 eV and −0.59 eV, respectively. The Gibbs free energy change in HER on the AlN (GaN) layer is much lower than that on the Sc2CF2 surface, owing to the stronger adsorption of H on AlN (GaN). The AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures possess significant improvements in absorption range and intensity compared to monolayered AlN, GaN, and Sc2CF2. In addition, the band gaps, edge positions, and absorption properties of AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures can be effectively tuned with strains. All the results indicate that AlN/Sc2CF2 and GaN/Sc2CF2 heterostructures are suitable catalysts for photocatalytic water splitting.

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.

Abstract Nickel‐nitrogen‐carbon single‐atom catalysts have attracted widespread interest for CO2 electroreduction but they suffer from poor stability. Herein, we report on the preparation of Cl‐ and N‐doped porous carbon nanosheets with atomically dispersed NiN4Cl active sites (NiN4Cl‐ClNC) through a molten‐salt‐assisted pyrolysis strategy. The optimized NiN4Cl‐ClNC catalyst delivers exceptional CO2 conversion activity with outstanding stability for over 220 h at −0.7 V versus RHE and a high CO Faradaic efficiency of 98.7% at a CO partial current density of 12.4 mA cm‒2. Moreover, NiN4Cl‐ClNC displays a remarkable CO partial current density of approximately 349.4 mA cm−2 in flow‐cell, meeting the requirements of industrial applications. Operando attenuated total reflectance surface‐enhanced infrared absorption spectroscopy and density functional theory calculations are used to understand the outstanding activity and stability. Results reveal that the introduced axial Ni‐Cl bond on the Ni center and Cl─C bond on the carbon support synergetically induce electronic delocalization, which not only stabilizes Ni against leaching but also facilitates the formation of the COOH* intermediate that is found to be the rate‐determining step.

Abstract Long noncoding RNAs (lncRNAs) play critical roles in tumorigenesis and tumor metastasis. However, the underlying mechanisms of lncRNAs in colorectal cancer (CRC) need further exploration. By using data from The Cancer Genome Atlas (TCGA) and GEO databases, we identified a novel CRC-related lncRNA, LINC01594, that is significantly upregulated in CRC and associated with poor prognosis. In vitro and in vivo, gain- and loss-of-function experiments demonstrated that LINC01594 promotes metastasis in CRC. LINC01594 functions as a DNMT1 scaffold, increasing the level of CELF6 promoter methylation. LINC01594 also competitively binds the transcription factor p53, decreasing CELF6 expression. This inhibited the exon skipping of CD44 V4–V7 induced by CELF6. In summary, this study highlights a novel CRC biomarker and therapeutic target, LINC01594, and the findings suggest that the LINC01594-CELF6-CD44 axis might serve as a biomarker and therapeutic target in CRC.

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.

Chlorine-containing disinfectants have been widely used all over the world to prevent COVID-19. However, little is known about the potential risk of chlorine-containing disinfectants in the marine environment. Phaeodactylum tricornutum (P. tricornutum) is a typical marine economic diatom, often used as an effective biomarker in ecotoxicology research. Here, the present study has investigated the effect of different effective chlorine concentrations on photosynthesis of P. tricornutum by chlorophyll fluorescence spectroscopy. Results have demonstrated that chlorine exposure promoted the chlorophyll fluorescence intensity at initial stage (24 h), suggesting that a large amount of energy is emitted in the form of fluorescence. However, the chlorophyll fluorescence intensity could not be detected under the high effective chlorine concentrations (6.7 × 10−3, 1.0 × 10−2, 1.3 × 10−2 and 1.7 × 10−2 mg L−1) after 48 h, indicating that the chlorine had high toxicity leading to the death of microalgae. In addition, the emission spectra of P. tricornutum were determined to contain two distinct fluorescence peaks representing the core antenna of photosystem II (685 nm) and the photosystem I complexes (710 nm) in the control group. The fluorescence emission peak value at 685 nm is significantly lower than the peak value at 710 nm in the control group, whereas chlorine treatments were opposite. It can be concluded that microalgae can regulate the distribution of excitation energy between the two photosystems to ensure that algae can utilize light energy. The result also found that the peak position of fluorescence emission spectra has a blue shift in all of NaClO treatments. The fluorescence intensity of microalgae excited at 467 nm was lower than that at 439 nm in chlorine treatments, illustrating chlorophyll b antenna was more easily damaged than chlorophyll a antenna. Our findings are providing new insights into the changing mechanism of chlorophyll fluorescence on P. tricornutum under chlorine stress and valuable data for risk assessment of marine environments.

Abstract Methane (CH4) is the second most potent greenhouse gas (GHG), and China emerges as the largest anthropogenic CH4 emitter by country. Current limited CH4 monitoring systems in China are unfortunately inadequate to support carbon management. Here we use the Weather Research and Forecasting model (WRF) coupled with a GHG module and satellite constrained emissions to simulate the spatiotemporal distribution of CH4 over East Asia in 2017. Model evaluations using both satellite retrievals and ground-based observations indicate reliable performance. We further inter-compare four proper orthogonal decomposition (POD)-based sensor placement algorithms and find they are able to capture main spatial features of surface CH4 under an oversampled condition. The QR pivot algorithm exhibits superiority in capturing high CH4, and it offers the best reconstruction with both high efficiency and accuracy. Areas with high CH4 concentrations and intense anthropogenic activities remain underrepresented by current CH4 sampling studies, leading to notable reconstruction error over central and eastern China. Optimal planning of 160 sensors guided by the QR pivot algorithm can yield reasonable reconstruction performance and costs of site construction. Our results can provide valuable references for future planning of CH4 monitoring sites.

Societal Impact Statement Apples are affordable and accessible fruit with tremendous biodiversity. Among over 10,000 identified apple cultivars, only a few are commercially available. Habitual fruit consumption is correlated with the prevention of Type 2 diabetes and related complications. Particularly, (poly)phenols found in apples are major contributors to their antidiabetic properties. Here, we have screened (poly)phenol‐rich extracts of 476 apple accessions in Canada's Apple Biodiversity Collection for antidiabetic properties. The results of this work provide insights into the prevention and management of Type 2 diabetes by identifying high (poly)phenol‐containing specialty apples for use in fresh fruit form or value‐added functional food ingredients. Summary The recent trend in sedentary lifestyles and nutritionally‐imbalanced diets has elevated the prevalence of Type 2 diabetes in many parts of the world. Some pharmacological glycemic management can cause undesirable gastrointestinal side effects or hypoglycemia. Thus, there is a growing interest in safe glycemic management using dietary (poly)phenols. In this study, (poly)phenol‐rich extracts of 476 apple accessions from Canada's Apple Biodiversity Collection (ABC) and six major apple (poly)phenols were assessed for in vitro antidiabetic properties against the activities of α‐glucosidase, α‐amylase, and dipeptidyl peptidase‐4 (DPP‐4) and the formation of advanced glycation end products (AGE). Apple (poly)phenol extracts varied in their antidiabetic activities in a dose‐dependent manner. High (poly)phenol‐containing apples demonstrated that their total phenolic contents (TPC) were inversely correlated with the IC50 values of α‐glucosidase, α‐amylase, and AGE formation, but not DPP‐4. Concentrations of major (poly)phenol compounds such as procyanidin B2, phloridzin, and epicatechin in apples were significantly inversely correlated with IC50 values of α‐glucosidase in the high (poly)phenol‐containing apples. High TPC apples are not suitable for marketing for fresh fruit consumption due to bitterness and astringency; however, these apples show potential to use in the development of value‐added functional food ingredients or nutraceuticals for blood glucose management. The high TPC apple, “S23‐03‐749,” an advanced breeding line of dessert apple, presents a novel option as a specialty apple cultivar for the dietary management of glycemia.

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.

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.

Abstract As the atmospheric carbon dioxide (CO2) level keeps hitting the new record, humanity is facing an ever‐daunting challenge to efficiently mitigate CO2 from the atmosphere. Though electrochemical CO2 reduction presents a promising pathway to convert CO2 to valuable fuels and chemicals, the general lack of suitable electrocatalysts with high activity and selectivity severely constrains this approach. Herein, a novel class of electrocatalysts is investigated, the quasi‐copper‐mers, in which the CuN4 rather than Cu atom itself serve as the basic building block. The respective quasi‐copper‐monomers, ‐dimers, and ‐trimers hosted in a graphene‐like substrate are first synthesized and then performed both experimental characterization and density functional theory (DFT) calculations to examine their atomic structures, evaluate their electrocatalytical performance and understand their underlying mechanisms. The experimental results show that the quasi‐copper‐trimers not only outperform the quasi‐copper‐dimer and quasi‐copper‐monomer when catalyzing CO2 to CO, it also shows a superior selectivity against the competing hydrogen evolution reaction (HER). The DFT calculations not only support the experimental observations, but also reveal the volcano curve and the physical origin for the qausi‐copper‐trimer superiority. The present work thus presents a new strategy in the design of high‐performance electrocatalysts with high activity and selectivity.

Metal selenides have been explored as promising sodium storage materials owing to their high theoretical capacity. However, sluggish Na+ diffusion and low electronic conductivity of selenides still hinder their practical applications. Herein, FeSe2-xSx microspheres have been prepared via a self-doping solvothermal method using NH4Fe(SO4)2 as both the Fe and S source, followed by gas phase selenization. The density functional theory calculation results reveal that S doping not only improves the Na adsorption, but also lower the diffusion energy barrier of Na atoms at the S doping sites, at the same time enhance the electronic conductivity of FeSe2-xSx. The carbon-free nature of the FeSe2-xSx microspheres results in a low specific surface area and a high tap density, leading to an initial columbic efficiency of 85.6%. Compared with pure FeSe2, such FeSe2-xSx delivers a high reversible capacity of 373.6 mAh·g−1 at a high current density of 5 ​A·g−1 after 2000 cycles and an enhanced rate performance of 305.8 mAh·g−1 at even 50 ​A·g−1. Finally, the FeSe2-xSx//NVP pouch cells have been assembled, achieving high energy and volumetric energy densities of 118 ​Wh·kg−1 and 272 ​mWh·cm−3, respectively, confirming the potential of applications for the FeSe2-xSx microspheres.

Lithium (Li) metal batteries (LMBs) are regarded as promising next-generation rechargeable batteries owing to the high theoretical specific capacity and the lowest potential of the Li metal anode (LMA). Nevertheless, the practical applications of LMA have been restricted by uncontrollable Li dendrite growth, enormous volume change and unstable interfaces between LMA and electrolyte. Among all the available strategies, the rational designs of artificial interphase layers (AILs) are the promising methods to solve these problems at the interfaces between LMA and electrolyte. In this review, we generally summarize the recent typical examples of in/ex-situ formed AILs for stabilizing LMA/electrolyte interfaces. Particular considerations have been taken on the components and structure characterizations in the design principle of AILs for suppressing uncontrollable Li dendrites growth, constructing stable interfaces and addressing the huge volume variation. Finally, the remaining challenges and the research direction for high performance AILs for safe and stable LMBs are provided.

An apple's aroma is a major determinant of its desirability by consumers. To better understand the aroma of apples, 2-dimensional gas-chromatography mass-spectrometry (2D-GCMS) was used to quantify 106 volatile organic compounds (VOCs) from 515 apple varieties. We identified esters and aldehydes as the most abundant classes of VOCs, with butyl acetate and hexyl acetate being present in nearly every variety. Principal component analysis (PCA) revealed that the primary axis of variation in the apple volatilome is correlated with harvest date, with early-harvested apples expressing a greater number and higher concentration of VOCs compared to late-harvested apples. Genome-wide association studies (GWAS) using 250,579 single nucleotide polymorphisms (SNPs) identified a significant association between SNPs near the alcohol acyltransferase (AAT1) locus and the abundance of several esters. Additionally, strong associations were observed between SNPs at the NAC18.1 transcription factor locus and the abundances of 1-hexanol and 1-butanol, which serve as precursors for hexyl acetate and butyl acetate, respectively. These findings provide a foundation for understanding the genetic basis of apple aroma production and pave the way for the genomics-assisted enhancement of the aroma profiles of apple varieties to meet consumer preferences.

Apples are an important dietary source of polyphenols as antioxidants that contribute to human health. Based on total phenolic content and total antioxidant capacity data gathered from a large apple biodiversity collection, we applied untargeted metabolomics analyses to further understand the phenolic composition in select accessions with very low and very high phenolic contents, as well as in commercial cultivars. The liquid chromatography-mass spectrometry (LC-MS) analysis provided both qualitative and quantitative information, with 2,946 features detected using the positive mode of electrospray ionization. We found significant variation in total polyphenols, and strong correlations between total phenolic content and total antioxidant capacity. Polyphenolic compounds significantly associated with each group of apples were quantified, and new features were putatively identified. This study provides new knowledge regarding the specific polyphenols that contribute to the variation in total phenolic content and antioxidant capacity among apples, and new insights into the biochemical regulations of polyphenol biosynthesis and composition.

Abstract Background Our recent studies found that intestinal mechanical signals can regulate mucus synthesis and secretion of intestinal goblet cells through piezo type mechanosensitive ion channel component 1 (Piezo1), but the detailed molecular mechanisms remain to be investigated. Previous studies using a water avoidance stress (WAS) model reported decreased intestinal mucus accompanied by abnormal intestinal motility. It has also been reported that the expression of mucin2 was negatively correlated with histone H3 lysine 9 trimethylation (H3K9me3), a key regulator of histone methylation, and that mechanical stimulation can affect methylation. In this study, we aimed to determine whether and how Piezo1 expressed on goblet cells regulates mucus barrier function through methylation modification. Methods A murine WAS model was established and treated with Yoda1 (Piezo1 agonist), and specific Piezo1 flox-mucin2 Cre mice were also tested. The mucus layer thickness and mucus secretion rate of mouse colonic mucosa were detected by a homemade horizontal Ussing chamber, intestinal peristaltic contraction was detected by the ink propulsion test and organ bath, goblet cells and mucus layer morphology were assessed by HE and Alcian blue staining, mucus permeability was detected by FISH, and the expression levels of Piezo1, H3K9me3 and related molecules were measured by Western blots and immunofluorescence. LS174T cells were cultured on a shaker board in vitro to simulate mechanical stimulation. Piezo1 and H3K9me3 were inhibited, and changes in mucin2 and methylation-related pathways were detected by ELISAs and Western blots. ChIP-PCR assays were used to detect the binding of H3K9me3 and mucin2 promoters under mechanical stimulation. Results Compared with those of the controls, the mucus layer thickness and mucus secretion rate of the mice exposed to WAS were significantly decreased, the mucus permeability increased, the number of goblet cells decreased, and the intestinal contraction and peristalsis were also downregulated and disordered. Intraperitoneal injection of Yoda1 improved mucus barrier function and intestinal contraction. In the colonic mucosa of mice exposed to WAS, Piezo1 was decreased, and histone H3 lysine 9 trimethylation (H3K9me3) and methyltransferase suppressor of variegation 3–9 homolog 1 (SUV39h1) were increased, but activating Piezo1 alleviated these effects of WAS. Piezo1 flox-mucin2 Cre mice showed decreased mucus expression and increased methylation compared to wild-type mice. Cell experiments showed that mechanical stimulation induced the activation of Piezo1, decreased H3K9me3 and SUV39h1, and upregulated mucin2 expression. Inhibition of Piezo1 or H3K9me3 blocked the promoting effect of mechanical stimulation on LS174T mucin2 expression. The binding of H3K9me3 to the mucin2 promoter decreased significantly under mechanical stimulation, but this could be blocked by the Piezo1 inhibitor GsMTx4. Conclusion Piezo1 mediates mechanical stimulation to inhibit SUV39h1, thereby reducing H3K9me3 production and its binding to the mucin2 promoter, ultimately promoting mucin2 expression in goblet cells. This study further confirmed that piezo1 on goblet cells could regulate mucus barrier function through methylation.

This paper studies electromagnetoelastic static investigation of a sandwich doubly curved microshell subjected to multi-field loading based on a new thickness stretching included refined higher order shear/normal deformable model. Modified-couple-stress-theory (MCST) is used for accounting small-scale-dependency. The numerical results are derived using an analytical method. The effect of small scale parameter in micro scale, initial electric and magnetic potentials and foundation parameters is studied on the electromagnetoelastic bending results. It is confirmed an enhancing in stiffness of small scale shell with an increase in micro length scale parameter.