Light-driven C-H activation mediated by 2D transition metal dichalcogenides.

C-H bond activation enables the facile synthesis of new chemicals. While C-H activation in short-chain alkanes has been widely investigated, it remains largely unexplored for long-chain organic molecules. Here, we report light-driven C-H activation in complex organic materials mediated by 2D transition metal dichalcogenides (TMDCs) and the resultant solid-state synthesis of luminescent carbon dots in a spatially-resolved fashion. We unravel the efficient H adsorption and a lowered energy barrier of C-C coupling mediated by 2D TMDCs to promote C-H activation and carbon dots synthesis. Our results shed light on 2D materials for C-H activation in organic compounds for applications in organic chemistry, environmental remediation, and photonic materials.

A data-driven intravoxel mean diffusivities distribution approach for molecular classifications and MIB-1 prediction of gliomas.

BACKGROUND: Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes. PURPOSE: We developed a data-driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB-1 labeling index (LI) levels and molecular status of gliomas. METHODS: An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR ∈ [ 30 , 300 ] $ \in [ {30,\ 300} ]$ . Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years ± $ \pm $ 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo-echo planar imaging (SE-EPI) diffusion-weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C-means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions ( f n , n = 1 - 6 ${{f}_n},\ n = 1 -6$ ) and diffusivities of the maximum peaks ( D p e a k ${{D}_{peak}}$ ). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann-Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation. RESULTS: The simulation results showed that the FCN-based MDD approach (FCN-MDD) achieved higher CSS than non-negative least squares-based MDD (NNLS-MDD). For in vivo data, the spectra of ET and NET obtained by FCN-MDD are more distinguishable than NNLS-MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non-enhancing tumor, edema, and necrosis). f 3 , f 4 , D p e a k ${{f}_3},\ {{f}_4},{{D}_{peak}}$ showed a positive and negative correlation with MIB-1 respectively ( r = 0.568 , r = - 0.521 , r = - 0.654 $r = 0.568,\ r = - 0.521,\ r = - 0.654$ , all p < 0.001 $p < 0.001$ ). The AUC of D p e a k ${{D}_{peak}}$ for predicting MIB-1 LI levels was 0.900 (95% CI, 0.826-0.974), versus 0.781 (0.677-0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model ( f 1 + f 3 ${{f}_1} + {{f}_3}$ ) was 0.873 (95% CI, 0.802-0.944). CONCLUSION: The proposed FCN-MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS-MDD method. FCN-MDD also enabled qualitative and quantitative evaluation of the composition of gliomas.

Sensitive detection of H2S based on Ce doped ZnCo2O4 hollow microspheres at low working temperature.

In order to develop a highly efficient H2S gas sensor at low working temperature, in this work, a kind of novel Ce-doped ZnCo2O4 hollow microspheres (Ce/ZnCo2O4 HMSs) were successfully synthesized using a template-free one-pot method, showing a sensitive response toward H2S. The microstructure and morphology of the material were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The gas-sensing performance of the composite was investigated, showing that the ZnCo2O4 doped with 6 mol% Ce had the highest response to 20 ppm H2S at a low operating temperature of 160 °C with a response value of 67.42, which was about 2 times higher than that of original ZnCo2O4. The prepared Ce/ZnCo2O4 HMS sensor in response to H2S exhibited a linear range of 0.1-200 ppm with a low detection limit of 0.1 ppm under the conditions of ambient humidity of 45% and ambient temperature of 20 °C. Meanwhile, it also possessed good selectivity, repeatability and reproducibility. The response value of the sensor decreased by 5.32% after 7 months of continuous monitoring of H2S in an atmospheric environment of a pig farm, indicating that the sensor had a long-term stability and continuous service life with important application prospects.

Development of xanthan gum intelligent oil-in-water ink and its application in pork freshness preservation.

To optimize the stability of oil-based inks and ensure their wide application in freshness indication, new natural indicator inks were prepared using a stable oil-in-water structure. This study selected natural Lycium ruthenicum anthocyanin as the dye and glucose as the pigment carrier. Soybean oil was introduced as a linker and xanthan gum as a thickener, and an oil-in-water ink with the function of freshness indication was successfully developed. In ensuring the safety of ink labels for use on food packaging, particular attention is paid to the origin and properties of the materials used. All ingredients are of food-grade or bio-friendly provenance, thereby ensuring the safety of the product when in direct contact with food. We measured the viscosity, particle size and fineness of the ink for micro characterization and evaluated its macro printing performance by its printing effect on A4 paper. According to the experimental results, when the water-oil ratio of the ink is 10:5, the average particle size of the emulsion system is 822.83 nm, and the fineness reaches 5 µm. These values are relatively low, which indicates that the stability of the ink system is high at this time, and the ink shows excellent rheological and printing characteristics. With this water-to-oil ratio, the ink can show the best results when printed on A4 paper, clearly displaying image details. In addition, in fresh pork applications, inks with a 10: 5 water-to-oil ratio provide an accurate and highly sensitive indication of the freshness of pork. When the freshness of the pork changes, the ink color responds promptly. This high sensitivity makes the ink ideal for use as a food freshness indication tool, providing consumers with an intuitive and reliable reference for pork freshness. As a further innovation, combining this ink-printed label with a WeChat app not only allows consumers to know the freshness of the food in real-time but also tracks the supply chain information of the food, providing a more comprehensive application prospect for freshness-indicating products.

Nonlinear association between atherogenic index of plasma and type 2 diabetes mellitus in overweight and obesity patients: evidence from Chinese medical examination data.

BACKGROUND: The atherogenic index of plasma (AIP) is closely associated with the onset of diabetes, with obesity being a significant risk factor for type 2 diabetes mellitus (T2DM). However, the association between the AIP and T2DM in overweight and obese populations has been infrequently studied. Therefore, this study aimed to explore this association in overweight and obese individuals with T2DM. METHODS: This cross-sectional analysis utilized data from 40,633 participants with a body mass index (BMI) ≥ 24 kg/m2 who were screened from January 2018 to December 2023 at Henan Provincial People's Hospital. Participants were categorized into groups of overweight and obese individuals with and without diabetes according to the T2DM criteria. The AIP, our dependent variable, was calculated using the formula log10 [(TG mol/L)/HDL-C (mol/L)]. We investigated the association between the AIP and T2DM in overweight and obese individuals using multivariate logistic regression, subgroup analysis, generalized additive models, smoothed curve fitting, and threshold effect analysis. Additionally, mediation analysis evaluated the role of inflammatory cells in AIP-related T2DM. RESULTS: Overweight and obese patients with T2DM exhibited higher AIP levels than those without diabetes. After adjusting for confounders, our results indicated a significant association between the AIP and the risk of T2DM in overweight and obese individuals (odds ratio (OR) = 5.17, 95% confidence interval (CI) 4.69-5.69). Notably, participants with a high baseline AIP (Q4 group) had a significantly greater risk of T2DM than those in the Q1 group, with an OR of 3.18 (95% CI 2.94-3.45). Subgroup analysis revealed that the association between the AIP and T2DM decreased with increasing age (interaction P < 0.001). In overweight and obese populations, the association between AIP and T2DM risk displayed a J-shaped nonlinear pattern, with AIP > - 0.07 indicating a significant increase in T2DM risk. Various inflammatory cells, including neutrophils, leukocytes, and monocytes, mediated 4.66%, 4.16%, and 1.93% of the associations, respectively. CONCLUSION: In overweight and obese individuals, the AIP was independently associated with T2DM, exhibiting a nonlinear association. Additionally, the association between the AIP and T2DM decreased with advancing age. Multiple types of inflammatory cells mediate this association.

NIR-responsive electrospun nanofiber dressing promotes diabetic-infected wound healing with programmed combined temperature-coordinated photothermal therapy.

BACKGROUND: Diabetic wounds present significant challenges, specifically in terms of bacterial infection and delayed healing. Therefore, it is crucial to address local bacterial issues and promote accelerated wound healing. In this investigation, we utilized electrospinning to fabricate microgel/nanofiber membranes encapsulating MXene-encapsulated microgels and chitosan/gelatin polymers. RESULTS: The film dressing facilitates programmed photothermal therapy (PPT) and mild photothermal therapy (MPTT) under near-infrared (NIR), showcasing swift and extensive antibacterial and biofilm-disrupting capabilities. The PPT effect achieves prompt sterilization within 5 min at 52 °C and disperses mature biofilm within 10 min. Concurrently, by adjusting the NIR power to induce local mild heating (42 °C), the dressing stimulates fibroblast proliferation and migration, significantly enhancing vascularization. Moreover, in vivo experimentation successfully validates the film dressing, underscoring its immense potential in addressing the intricacies of diabetic wounds. CONCLUSIONS: The MXene microgel-loaded nanofiber dressing employs temperature-coordinated photothermal therapy, effectively amalgamating the advantageous features of high-temperature sterilization and low-temperature promotion of wound healing. It exhibits rapid, broad-spectrum antibacterial and biofilm-disrupting capabilities, exceptional biocompatibility, and noteworthy effects on promoting cell proliferation and vascularization. These results affirm the efficacy of our nanofiber dressing, highlighting its significant potential in addressing the challenge of diabetic wounds struggling to heal due to infection.

RiskFormer: Exploring the temporal associations between multi-type aberrant driving events and crash occurrence.

With the development of driving behavior monitoring technologies, commercial transportation enterprises have leveraged aberrant driving event detection results for evaluating crash risk and triggering proactive interventions. The state-of-the-art applications were established based upon instant associations between events and crash occurrence, which assumed crash risk surged with aberrant events. Consequently, the generated crash risk monitoring results merely contain discrete abrupt changes, failing to depict the time-varying trend of crash risk and posing challenges for interventions. Given the multiple types of aberrant events and their various temporal combinations, the key to depict crash risk time-varying trend is the analysis of multi-type events' temporal coupling influence. Existing studies employed event frequency to model combined influence, lacking the capability to differentiate the temporal sequential characteristics of events. Hence, there is an urgent need to further explore multi-type events' temporal coupling influence on crash risk. In this study, the temporal associations between multi-type aberrant driving events and crash occurrence are explored. Specifically, a contrastive learning method, fusing prior domain knowledge and empirical data, was proposed to analyze the single event temporal influence on crash risk. After that, a novel Crash Risk Evaluation Transformer (RiskFormer) was developed. In the RiskFormer, a unified encoding method for different events, as well as a self-attention mechanism, were established to learn multi-type events' temporal coupling influence. Empirical data from online ride-hailing services were employed, and the modeling results unveiled three distinct time-varying patterns of crash risk, including decay, increasing, and increasing-decay pattern. Additionally, RiskFormer exhibited remarkable crash risk evaluation performance, demonstrating a 12.8% improvement in the Area Under Curve (AUC) score compared to the conventional instant-association-based model. Furthermore, the practical utility of RiskFormer was illustrated through a crash risk monitoring sample case. Finally, applications of the proposed methods and their further investigations have been discussed.

Multiple-view 3D digital image correlation based on pseudo-overlapped imaging.

The restriction of the field of view (FOV) enlargement and spatial resolution increase during optical monitoring was investigated. Traditional optical instruments usually have a fixed FOV in one test; thus, they have low accuracy for small samples under large motions/deformations. To improve the spatial resolution in a relatively large FOV of an optical instrument, a multiple-view 3D digital image correlation (3D-DIC) method based on pseudo-overlapped imaging is proposed. Using a set of optical components, pseudo-overlapped imaging can image two FOVs with the same camera, which converts one pair of cameras to four virtual cameras. Each virtual camera has the same whole pixels. Therefore, compared with the conventional 3D-DIC system, the proposed method simultaneously enlarges FOVs and increases spatial resolutions by two times. The efficiency, accuracy, and feasibility of the technique were validated through experiments.

Lysosomal cation channel TRPML1 suppression sensitizes acute myeloid leukemia cells to chemotherapeutics by inhibiting autophagy.

Despite the implementation of novel therapeutic regimens and extensive research efforts, chemoresistance remains a formidable challenge in the treatment of acute myeloid leukemia (AML). Notably, the involvement of lysosomes in chemoresistance has sparked interest in developing lysosome-targeted therapies to sensitize tumor cells to currently approved chemotherapy or as innovative pharmacological approaches. Moreover, as ion channels on the lysosomal membrane are critical regulators of lysosomal function, they present potential as novel targets for enhancing chemosensitivity. Here, we discovered that the expression of a lysosomal cation channel, namely transient receptor potential mucolipin 1 (TRPML1), was elevated in AML cells. Inhibiting TRPML1 individually does not impact the proliferation and apoptosis of AML cells. Importantly, inhibition of TRPML1 demonstrated the potential to modulate the sensitivity of AML cells to chemotherapeutic agents. Exploration of the underlying mechanisms revealed that suppression of TRPML1 impaired autophagy while concurrently increasing the production of reactive oxygen species (ROS) and ROS-mediated lipid peroxidation (Lipid-ROS) in AML cells. Finally, the knockdown of TRPML1 significantly reduced OCI-AML3 tumor growth following chemotherapy in a mouse model of human leukemia. In summary, targeting TRPML1 represents a promising approach for combination therapy aimed at enhancing chemosensitivity in treating AML.

Associations of E-proteinoid 3 receptor genetic polymorphisms with salt sensitivity, longitudinal blood pressure changes, and hypertension incidence in Chinese adults.

The E-proteinoid 3 receptor (PTGER3), a member of the prostaglandin E2 (PGE2) subtype receptor, belongs to the G-protein-coupled superfamily of receptors. Animal studies have demonstrated its involvement in salt sensitivity by regulating sodium reabsorption. This study aimed to investigate the association between genetic variants of PTGER3 and salt sensitivity, longitudinal blood pressure (BP) changes, and the incidence of hypertension in Chinese adults. A chronic salt intake intervention was conducted involving 514 adults from 124 families in the 2004 Baoji Salt-Sensitivity Study Cohort in northern China. These participants followed a 3-day regular baseline diet, followed by a 7-day low-salt diet (3.0 g/d) and a 7-day high-salt diet (18 g/d), and were subsequently followed for 14 years. The findings revealed a significant relationship between the single nucleotide polymorphism (SNP) rs17482751 of PTGER3 and diastolic blood pressure (DBP) response to high salt intervention. Additionally, SNPs rs11209733, rs3765894, and rs2268062 were significantly associated with longitudinal changes in systolic blood pressure (SBP), DBP, and mean arterial pressure (MAP) during the 14-year follow-up period. SNP rs6424414 was significantly associated with longitudinal changes in DBP over 14 years. Finally, SNP rs17482751 showed a significant correlation with the incidence of hypertension over 14 years. These results emphasize the significant role of PTGER3 gene polymorphism in salt sensitivity, longitudinal BP changes, and the development of hypertension in the Chinese population.

Integrated analysis of single-cell RNA-seq, bulk RNA-seq, Mendelian randomization, and eQTL reveals T cell-related nomogram model and subtype classification in rheumatoid arthritis.

Objective: Rheumatoid arthritis (RA) is a systemic disease that attacks the joints and causes a heavy economic burden on humans worldwide. T cells regulate RA progression and are considered crucial targets for therapy. Therefore, we aimed to integrate multiple datasets to explore the mechanisms of RA. Moreover, we established a T cell-related diagnostic model to provide a new method for RA immunotherapy. Methods: scRNA-seq and bulk-seq datasets for RA were obtained from the Gene Expression Omnibus (GEO) database. Various methods were used to analyze and characterize the T cell heterogeneity of RA. Using Mendelian randomization (MR) and expression quantitative trait loci (eQTL), we screened for potential pathogenic T cell marker genes in RA. Subsequently, we selected an optimal machine learning approach by comparing the nine types of machine learning in predicting RA to identify T cell-related diagnostic features to construct a nomogram model. Patients with RA were divided into different T cell-related clusters using the consensus clustering method. Finally, we performed immune cell infiltration and clinical correlation analyses of T cell-related diagnostic features. Results: By analyzing the scRNA-seq dataset, we obtained 10,211 cells that were annotated into 7 different subtypes based on specific marker genes. By integrating the eQTL from blood and RA GWAS, combined with XGB machine learning, we identified a total of 8 T cell-related diagnostic features (MIER1, PPP1CB, ICOS, GADD45A, CD3D, SLFN5, PIP4K2A, and IL6ST). Consensus clustering analysis showed that RA could be classified into two different T-cell patterns (Cluster 1 and Cluster 2), with Cluster 2 having a higher T-cell score than Cluster 1. The two clusters involved different pathways and had different immune cell infiltration states. There was no difference in age or sex between the two different T cell patterns. In addition, ICOS and IL6ST were negatively correlated with age in RA patients. Conclusion: Our findings elucidate the heterogeneity of T cells in RA and the communication role of these cells in an RA immune microenvironment. The construction of T cell-related diagnostic models provides a resource for guiding RA immunotherapeutic strategies.

Non-O blood types are associated with a greater risk of large artery atherosclerosis stroke and dysregulation of cholesterol metabolism: an observational study.

BACKGROUND: Previous research on ABO blood types and stroke has been controversial, predominantly suggesting heightened risk of stroke in non-O blood types. Nonetheless, investigations into the correlation and underlying mechanisms between ABO blood groups and stroke subtypes, especially within Chinese cohorts, remain limited. METHODS: The ABO blood types of 9,542 ischaemic stroke (IS) patients were inferred using two ABO gene loci (c.261G > del; c.802G > A). The healthy population was derived from the 1000 Genomes Project. Patients were classified by the causative classification system (CCS). Volcano plot and gene ontology (GO) analysis were employed to explore protein differential expression among blood types. Additionally, HT29 and SW480 cell lines with downregulated ABO expression were generated to evaluate its impact on cholesterol uptake and efflux. RESULTS: A greater proportion of stroke patients had non-O blood types (70.46%) than did healthy individuals (61.54%). Notable differences in blood type distributions were observed among stroke subtypes, with non-O blood type patients mainly classified as having large artery atherosclerosis (LAA). Clinical baseline characteristics, such as the low-density lipoprotein cholesterol level, activated partial thromboplastin time and thrombin time, varied significantly among blood types. A volcano plot revealed 17 upregulated and 42 downregulated proteins in the O blood type. GO term analysis indicated that downregulated proteins were primarily associated with lipid metabolism pathways. In vitro experiments revealed that reducing ABO gene expression decreased cholesterol uptake and increased cholesterol efflux. CONCLUSIONS: This study revealed that the non-O blood type increased the risk of LAA stroke through cholesterol metabolism.

Large Non-Hysteretic Volume Magnetostriction in a Strong and Ductile High-Entropy Alloy.

Rapid development of smart technologies poses a big challenge for magnetostrictive materials, which should not only permit isotropic and hysteresis-free actuation (i.e., non-hysteretic volume change) in magnetic fields, but also have high strength and high ductility. Unfortunately, the magnetostriction from self-assembly of ferromagnetic domains is volume-conserving; the volume magnetostriction from field-induced first-order phase transition has large intrinsic hysteresis; and most prototype magnetostrictive materials are intrinsically brittle. Here we report a magnetic high-entropy alloy (HEA) Fe35Co35Al10Cr10Ni10 that can rectify these challenges, exhibiting an unprecedented combination of large non-hysteretic volume magnetostriction, high tensile strength and large elongation strain, over a wide working temperature range from room temperature down to 100 K. Its exceptional properties stem from a dual-phase microstructure, where the face-centered-cubic (FCC) matrix phase with nano-scale compositional and structural fluctuations can enable a magnetic-field-induced transition from low-spin small-volume state to high-spin large-volume state, and the ordered body-centered-cubic (BCC) B2 phase contributes to mechanical strengthening. The present findings may provide insights into designing unconventional and technologically-important magnetostrictive materials. This article is protected by copyright. All rights reserved.

Yolov8n-FADS: A Study for Enhancing Miners' Helmet Detection Accuracy in Complex Underground Environments.

A new algorithm, Yolov8n-FADS, has been proposed with the aim of improving the accuracy of miners' helmet detection algorithms in complex underground environments. By replacing the head part with Attentional Sequence Fusion (ASF) and introducing the P2 detection layer, the ASF-P2 structure is able to comprehensively extract the global and local feature information of the image, and the improvement in the backbone part is able to capture the spatially sparsely distributed features more efficiently, which improves the model's ability to perceive complex patterns. The improved detection head, SEAMHead by the SEAM module, can handle occlusion more effectively. The Focal Loss module can improve the model's ability to detect rare target categories by adjusting the weights of positive and negative samples. This study shows that compared with the original model, the improved model has 29% memory compression, a 36.7% reduction in the amount of parameters, and a 4.9% improvement in the detection accuracy, which can effectively improve the detection accuracy of underground helmet wearers, reduce the workload of underground video surveillance personnel, and improve the monitoring efficiency.

Stratifying TAD boundaries pinpoints focal genomic regions of regulation, damage, and repair.

Advances in chromatin mapping have exposed the complex chromatin hierarchical organization in mammals, including topologically associating domains (TADs) and their substructures, yet the functional implications of this hierarchy in gene regulation and disease progression are not fully elucidated. Our study delves into the phenomenon of shared TAD boundaries, which are pivotal in maintaining the hierarchical chromatin structure and regulating gene activity. By integrating high-resolution Hi-C data, chromatin accessibility, and DNA double-strand breaks (DSBs) data from various cell lines, we systematically explore the complex regulatory landscape at high-level TAD boundaries. Our findings indicate that these boundaries are not only key architectural elements but also vibrant hubs, enriched with functionally crucial genes and complex transcription factor binding site-clustered regions. Moreover, they exhibit a pronounced enrichment of DSBs, suggesting a nuanced interplay between transcriptional regulation and genomic stability. Our research provides novel insights into the intricate relationship between the 3D genome structure, gene regulation, and DNA repair mechanisms, highlighting the role of shared TAD boundaries in maintaining genomic integrity and resilience against perturbations. The implications of our findings extend to understanding the complexities of genomic diseases and open new avenues for therapeutic interventions targeting the structural and functional integrity of TAD boundaries.

Diagnostic value of carbohydrate antigen 50 in biliary tract cancer: A large-scale multicenter study.

BACKGROUND: To date, carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) have been widely used for the screening, diagnosis and prediction of biliary tract cancer (BTC) patients. However, few studies with large sample sizes of carbohydrate antigen 50 (CA50) were reported in BTC patients. METHODS: A total of 1121 patients from the Liver Cancer Clin-Bio Databank of Anhui Hepatobiliary Surgery Union between January 2017 and December 2022 were included in this study (673 in the training cohort and 448 in the validation cohort): among them, 458 with BTC, 178 with hepatocellular carcinoma (HCC), 23 with combined hepatocellular-cholangiocarcinoma, and 462 with nontumor patients. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the diagnostic efficacy and clinical usefulness. RESULTS: ROC curves obtained by combining CA50, CA19-9, and AFP showed that the AUC value of the diagnostic MODEL 1 was 0.885 (95% CI 0.856-0.885, specificity 70.3%, and sensitivity 84.0%) in the training cohort and 0.879 (0.841-0.917, 76.7%, and 84.3%) in the validation cohort. In addition, comparing iCCA and HCC (235 in the training cohort, 157 in the validation cohort), the AUC values of the diagnostic MODEL 2 were 0.893 (95% CI 0.853-0.933, specificity 96%, and sensitivity 68.6%) in the training cohort and 0.872 (95% CI 0.818-0.927, 94.2%, and 64.6%) in the validation cohort. CONCLUSION: The model combining CA50, CA19-9, and AFP not only has good diagnostic value for BTC but also has good diagnostic value for distinguishing iCCA and HCC.

Kirigami enabled reconfigurable three-dimensional evaporator arrays for dynamic solar tracking and high efficiency desalination.

A kirigami-engineered composite hydrogel membrane is exploited for the construction of three dimensional (3D) solar-tracking evaporator arrays with outstanding evaporation performance and salt tolerance. The hybrid nanofiber network in the hydrogel membrane offers favorable water transport dynamics combined with excellent structural robustness, which are beneficial for the engineering of 3D dynamic structures. Periodic triangular cuts patterned into the membrane allow formation and reconfiguration of 3D conical arrays controlled by uniaxial stretching. With these structures, the tilt angles of the membrane surface are actively tuned to follow the solar trajectory, leading to a solar evaporation rate ~80% higher than that of static planar devices. Furthermore, the tapered 3D flaps and their micro-structured surfaces are capable of localized salt crystallization for prolonged solar desalination, enabling a stable evaporation rate of 3.4 kg m-2 hour-1 even in saturated brine. This versatile design may facilitate the implementation of solar evaporators for desalination and provide inspirations for other soft functional devices with dynamic 3D configurations.

Symmetry breaking of highly symmetrical nanoclusters for triggering highly optical activity.

Developing new approaches to fulfill the enantioseparation of nanocluster racemates and construct cluster-based nanomaterials with optical activity remains highly desired in cluster science, because it is an essential prerequisite for fundamental research and extensive applications of these nanomaterials. We herein propose a strategy termed "active-site exposing and partly re-protecting" to trigger the symmetry breaking of highly symmetrical nanoclusters and to render cluster crystals optically active. The vertex PPh3 of the symmetrical Ag29(SSR)12(PPh3)4 (SSR = 1, 3-benzenedithiol) nanocluster was firstly dissociated in the presence of counterions with large steric hindrance, and then the exposed Ag active sites of the obtained Ag29(SSR)12 nanocluster were partly re-protected by Ag+, yielding an Ag29(SSR)12-Ag2 nanocluster with a symmetry-breaking construction. Ag29(SSR)12-Ag2 followed a chiral crystallization mode, and its crystal displayed strong optical activity, derived from CD and CPL characterizations. Overall, this work presents a new approach (i.e., active-site exposing and partly re-protecting) for the symmetry breaking of highly symmetrical nanoclusters, the enantioseparation of nanocluster racemates, and the achievement of highly optical activity.

Decoding the immune landscape: a comprehensive analysis of immune-associated biomarkers in cervical carcinoma and their implications for immunotherapy strategies.

Background and aims: Cervical cancer, a prevalent gynecological malignant tumor, poses a significant threat to women's health and lives. Immune checkpoint inhibitor (ICI) therapy has emerged as a promising avenue for treating cervical cancer. For patients with persistent or recurrent metastatic cervical cancer, If the sequence of dead receptor ligand-1 (PD-L1) is positive, ICI show significant clinical efficacy. PD-L1 expression serves as a valuable biomarker for assessing ICI therapeutic efficacy. However, the complex tumor immune microenvironment (TIME), encompassing immune cell composition and tumor-infiltrating lymphocyte (TIL) status, also exerts a profound influence on tumor immunity and prognosis. Given the remarkable strides made by ICI treatments in improving the survival rates of cervical cancer patients, it becomes essential to identify a comprehensive biomarker that integrates various TIME aspects to enhance the effectiveness of ICI treatment. Therefore, the quest for biomarkers linked to multiple facets of TIME in cervical cancer is a vital pursuit. Methods: In this study, we have developed an Immune-Associated Gene Prognostic Index (IRGPI) with remarkable prognostic value specifically for cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). The Cancer Genome Atlas CESC dataset (n = 305) was meticulously analyzed to pinpoint key immune-related genes via weighted gene co-expression network analysis and differential gene expression assays. Subsequently, we employed Cox regression analysis to construct the IRGPI. Furthermore, the composition of immune cells and TIL status were examined using CIBERSORT and TIDE. Tumor expression of Epigen, LCN10, and P73 were determined with immunohistochemistry. Results: The resulting IRGPI, composed of EPGN, LCN10, and TP73 genes, displayed a strong negative correlation with patient survival. The discovery was validated with a patient cohort from our hospital. The IRGPI not only predicts the composition of immune cell subtypes such as Macrophages M1, NK cells, Mast cells, Plasma cells, Neutrophils, Dendritic cells, T cells CD8, and T cells CD4 within CESC, but also indicates TIL exclusion, dysfunction, and PD-1 and PD-L1 expression. Therefore, the IRGPI emerges as a promising biomarker not only for prognostic assessment but also for characterizing multiple immune features in CESC. Additionally, our results underscored the significant associations between the IRGPI and immune cell composition, TIL exclusion, and dysfunction, along with PD-1 and PD-L1 expression in the TIME. Conclusion: Consequently, the IRGPI stands out as a biomarker intimately connected to both the survival and TIME status of CESC patients, offering potential insights into immunotherapy strategies for CESC.

Intercalating Organic Hybrid Cadmium Antimony Sulfide Nanoparticles into Graphene Oxide Nanosheets for Electrochemical Lithium Storage.

Inorganic metal sulfides have received extensive investigation as anode materials in lithium-ion batteries (LIBs). However, applications of crystalline organic hybrid metal sulfides as anode materials in LIBs are quite rare. In addition, combining the nanoparticles of crystalline organic hybrid metal sulfides with conductive materials is expected to enhance the electrochemical lithium storage performance. Nevertheless, due to the difficulty of harvesting the nanoparticles of crystalline organic hybrid metal sulfides, this approach has never been tried to date. Herein, nanoparticles of a crystalline organic hybrid cadmium antimony sulfide (1,4-DABH2)Cd2Sb2S6 (DCAS) were prepared by a top-down method, including the procedures of solvothermal synthesis, ball milling, and ultrasonic pulverization. Thereafter, the nanoparticles of DCAS with sizes of ∼500 nm were intercalated into graphene oxide nanosheets through a freeze-drying treatment and a DCAS@GO composite was obtained. Compared with the reported Sb2S3- and CdS-based composites, the DCAS@GO composite exhibited superior electrochemical Li+ ion storage performance, including a high capacity of 1075.6 mAh g-1 at 100 mA g-1 and exceptional rate tolerances (646.8 mAh g-1 at 5000 mA g-1). In addition, DCAS@GO can provide a high capacity of 705.6 mAh g-1 after 500 cycles at 1000 mA g-1. Our research offers a viable approach for preparing the nanoparticles of crystalline organic hybrid metal sulfides and proves that intercalating organic hybrid metal sulfide nanoparticles into GO nanosheets can efficiently boost the electrochemical Li+ ion storage performance.