Triply Interlocked [2]catenanes: Rational Synthesis, Reversible Conversion Studies and Unprecedented Application in Photothermal Responsive Elastomer.

Triply interlocked [2]catenane complexes featuring two identical, mechanically interlocked units are extraordinarily rare chemical compounds, whose properties and applications remain open to detailed studies. Herein, we introduce the rational design of a new ligand precursor, L1, suitable for the synthesis of six triply interlocked [2]catenanes by coordination-driven self-assembly. The interlocked compounds can be reversibly converted into the corresponding simple triangular prism metallacage by addition of H2O or DMF solvents to their CH3OH solutions, thereby demonstrating the importance of π···π stacking and hydrogen bonding interactions in the formation of triply interlocked [2]catenanes. Moreover, extensive studies have been conducted to assess the remarkable photothermal conversion performance. Complex 6a, exhibiting outstanding photothermal conversion performance (conversion efficiency in solution : 31.82%), is used to prepare novel photoresponsive elastomer in combination with thermally activated liquid crystal elastomer. The resultant material displays robust response to near-infrared (NIR) laser and the capability of completely reforming the shape and reversible actuation, paving the way for the application of half-sandwich organometallic units in photo-responsive smart materials.

Role of peritumoral tissue analysis in predicting characteristics of hepatocellular carcinoma using ultrasound-based radiomics.

Predicting the biological characteristics of hepatocellular carcinoma (HCC) is essential for personalized treatment. This study explored the role of ultrasound-based radiomics of peritumoral tissues for predicting HCC features, focusing on differentiation, cytokeratin 7 (CK7) and Ki67 expression, and p53 mutation status. A cohort of 153 patients with HCC underwent ultrasound examinations and radiomics features were extracted from peritumoral tissues. Subgroups were formed based on HCC characteristics. Predictive modeling was carried out using the XGBOOST algorithm in the differentiation subgroup, logistic regression in the CK7 and Ki67 expression subgroups, and support vector machine learning in the p53 mutation status subgroups. The predictive models demonstrated robust performance, with areas under the curves of 0.815 (0.683-0.948) in the differentiation subgroup, 0.922 (0.785-1) in the CK7 subgroup, 0.762 (0.618-0.906) in the Ki67 subgroup, and 0.849 (0.667-1) in the p53 mutation status subgroup. Confusion matrices and waterfall plots highlighted the good performance of the models. Comprehensive evaluation was carried out using SHapley Additive exPlanations plots, which revealed notable contributions from wavelet filter features. This study highlights the potential of ultrasound-based radiomics, specifically the importance of peritumoral tissue analysis, for predicting HCC characteristics. The results warrant further validation of peritumoral tissue radiomics in larger, multicenter studies.

Multifaceted roles of lymphatic and blood endothelial cells in the tumor microenvironment of hepatocellular carcinoma: A comprehensive review.

The tumor microenvironment is a complex network of cells, extracellular matrix, and signaling molecules that plays a critical role in tumor progression and metastasis. Lymphatic and blood vessels are major routes for solid tumor metastasis and essential parts of tumor drainage conduits. However, recent studies have shown that lymphatic endothelial cells (LECs) and blood endothelial cells (BECs) also play multifaceted roles in the tumor microenvironment beyond their structural functions, particularly in hepatocellular carcinoma (HCC). This comprehensive review summarizes the diverse roles played by LECs and BECs in HCC, including their involvement in angiogenesis, immune modulation, lymphangiogenesis, and metastasis. By providing a detailed account of the complex interplay between LECs, BECs, and tumor cells, this review aims to shed light on future research directions regarding the immune regulatory function of LECs and potential therapeutic targets for HCC.

The effect of fine particulate matter (PM2.5) pollution on health inequality: an intergenerational perspective.

Air pollution poses a serious challenge to public health and simultaneously exacerbating regional & intergenerational health inequality. This research introduces PM2.5 pollution into the intergenerational health transmission model, and estimates its impact on health inequality in China using Ordered Logit Regression (OLR) and Multi-scale Geographically Weighted Regression (MGWR) model. The results indicate that PM2.5 pollution exacerbate the intergenerational health inequality, and its impacts show inconsistency across family income levels, parental health insurance status, and area of residence. Specifically, it is more difficult for offspring in low-income families to escape from the influence of unhealthy family to become upwardly mobile. Additionally, this health inequality is more significant in households in which at least one parent does not have health insurance. Moreover, the intergenerational solidification caused by PM2.5 pollution is higher in the east and lower in the west. Both the PM2.5 level and solidification effect are high in Beijing-Tianjin-Hebei region, Yangtze River Delta region and central areas of China, which is the focus of air pollution management. These findings suggest that more emphasis should be placed on family-based health promotion. In areas with high PM2.5 pollution levels, resources, subsidies and air pollution protection should be provided for less healthy families with lower incomes and no health insurance.

Ultrasensitive and Rapid Circulating Tumor DNA Liquid Biopsy Using Surface-Confined Gene Amplification on Dispersible Magnetic Nano-Electrodes.

Circulating tumor DNA (ctDNA) detection has been acknowledged as a promising liquid biopsy approach for cancer diagnosis, with various ctDNA assays used for early detection and treatment monitoring. Dispersible magnetic nanoparticle-based electrochemical detection methods have been proposed as promising candidates for ctDNA detection based on the detection performance and features of the platform material. This study proposes a nanoparticle surface-localized genetic amplification approach by integrating Fe3O4-Au core-shell nanoparticles into polymerase chain reactions (PCR). These highly dispersible and magnetically responsive superparamagnetic nanoparticles act as nano-electrodes that amplify and accumulate target ctDNA in situ on the nanoparticle surface upon PCR amplification. These nanoparticles are subsequently captured and subjected to repetitive electrochemical measurements to induce reconfiguration-mediated signal amplification for ultrasensitive (∼3 aM) and rapid (∼7 min) metastatic breast cancer ctDNA detection in vitro. The detection platform can also detect metastatic biomarkers from in vivo samples, highlighting the potential for clinical applications and further expansion to rapid and ultrasensitive multiplex detection of various cancers.

PV Panel Model Parameter Estimation by Using Particle Swarm Optimization and Artificial Neural Network.

Photovoltaic (PV) panels are one of the popular green energy resources and PV panel parameter estimations are one of the popular research topics in PV panel technology. The PV panel parameters could be used for PV panel health monitoring and fault diagnosis. Recently, a PV panel parameters estimation method based in neural network and numerical current predictor methods has been developed. However, in order to further improve the estimation accuracies, a new approach of PV panel parameter estimation is proposed in this paper. The output current and voltage dynamic responses of a PV panel are measured, and the time series of the I-V vectors will be used as input to an artificial neural network (ANN)-based PV model parameter range classifier (MPRC). The MPRC is trained using an I-V dataset with large variations in PV model parameters. The results of MPRC are used to preset the initial particles' population for a particle swarm optimization (PSO) algorithm. The PSO algorithm is used to estimate the PV panel parameters and the results could be used for PV panel health monitoring and the derivation of maximum power point tracking (MMPT). Simulations results based on an experimental I-V dataset and an I-V dataset generated by simulation show that the proposed algorithms can achieve up to 3.5% accuracy and the speed of convergence was significantly improved as compared to a purely PSO approach.

Hierarchical chiral MOFs with the induced chirality of AIE ligands exhibiting non-reciprocal CPL.

Two pairs of chiral MOFs with hierarchical chiral structures were constructed through assembly of achiral AIE-type multidentate linkers and chiral camphoric acid. Non-reciprocal circularly polarized luminescence (CPL) can be observed on the macroscopic due to the coexistence of optical anisotropic and chiroptical nature. This study provides a new perspective to recognize and construct chiral crystalline materials.

Encapsulation engineering of porous crystalline frameworks for delayed luminescence and circularly polarized luminescence.

Delayed luminescence (DF), including phosphorescence and thermally activated delayed fluorescence (TADF), and circularly polarized luminescence (CPL) exhibit common and broad application prospects in optoelectronic displays, biological imaging, and encryption. Thus, the combination of delayed luminescence and circularly polarized luminescence is attracting increasing attention. The encapsulation of guest emitters in various host matrices to form host-guest systems has been demonstrated to be an appealing strategy to further enhance and/or modulate their delayed luminescence and circularly polarized luminescence. Compared with conventional liquid crystals, polymers, and supramolecular matrices, porous crystalline frameworks (PCFs) including metal-organic frameworks (MOFs), covalent-organic frameworks (COFs), zeolites and hydrogen-bonded organic frameworks (HOFs) can not only overcome shortcomings such as flexibility and disorder but also achieve the ordered encapsulation of guests and long-term stability of chiral structures, providing new promising host platforms for the development of DF and CPL. In this review, we provide a comprehensive and critical summary of the recent progress in host-guest photochemistry via the encapsulation engineering of guest emitters in PCFs, particularly focusing on delayed luminescence and circularly polarized luminescence. Initially, the general principle of phosphorescence, TADF and CPL, the combination of DF and CPL, and energy transfer processes between host and guests are introduced. Subsequently, we comprehensively discuss the critical factors affecting the encapsulation engineering of guest emitters in PCFs, such as pore structures, the confinement effect, charge and energy transfer between the host and guest, conformational dynamics, and aggregation model of guest emitters. Thereafter, we summarize the effective methods for the preparation of host-guest systems, especially single-crystal-to-single-crystal (SC-SC) transformation and epitaxial growth, which are distinct from conventional methods based on amorphous materials. Then, the recent advancements in host-guest systems based on PCFs for delayed luminescence and circularly polarized luminescence are highlighted. Finally, we present our personal insights into the challenges and future opportunities in this promising field.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Dietary Iron Overload Triggers Hepatic Metabolic Disorders and Inflammation in Laying Hen.

Iron, an essential trace element, is involved in various physiological processes; however, consumption of excessive iron possesses detrimental effects. In practical feed production, the iron content added to feeds often far exceeds the actual demand, resulting in an excess of iron in the body. The liver as a central regulator of iron homeostasis is susceptible to damage caused by disorders in iron metabolism. A model of hepatic iron overload in laying hens was developed in this study by incorporating iron into their diet, and the specific mechanisms underlying iron overload-induced hepatic injury were investigated. Firstly, this study revealed that a high-iron diet resulted in hepatic iron overload, accompanied by impaired liver function. Next, assessment of oxidative stress markers indicated a decrease in activities of T-SOD and CAT, coupled with an increase in MDA content, pointing to the iron-overloaded liver oxidative stress. Thirdly, the impact of iron overload on hepatic glycolipid and bile acid metabolism-related gene expressions were explored, including PPAR-α, GLUT2, and CYP7A1, highlighting disruptions in hepatic metabolism. Subsequently, analyses of inflammation-related genes such as iNOS and IL-1ß at both protein and mRNA levels demonstrated the presence of inflammation in the liver under conditions of dietary iron overload. Overall, this study provided comprehensive evidence that dietary iron overload contributed to disorders in glycolipid and bile acid metabolism, accompanied by inflammatory responses in laying hens. Further detailing the specific pathways involved and the implications of these findings could offer valuable insights for future research and practical applications in poultry nutrition.

Naturally Crosslinked Biocompatible Carbonaceous Liquid Metal Aqueous Ink Printing Wearable Electronics for Multi-Sensing and Energy Harvesting.

Achieving flexible electronics with comfort and durability comparable to traditional textiles is one of the ultimate pursuits of smart wearables. Ink printing is desirable for e-textile development using a simple and inexpensive process. However, fabricating high-performance atop textiles with good dispersity, stability, biocompatibility, and wearability for high-resolution, large-scale manufacturing, and practical applications has remained challenging. Here, water-based multi-walled carbon nanotubes (MWCNTs)-decorated liquid metal (LM) inks are proposed with carbonaceous gallium-indium micro-nanostructure. With the assistance of biopolymers, the sodium alginate-encapsulated LM droplets contain high carboxyl groups which non-covalently crosslink with silk sericin-mediated MWCNTs. E-textile can be prepared subsequently via printing technique and natural waterproof triboelectric coating, enabling good flexibility, hydrophilicity, breathability, wearability, biocompatibility, conductivity, stability, and excellent versatility, without any artificial chemicals. The obtained e-textile can be used in various applications with designable patterns and circuits. Multi-sensing applications of recognizing complex human motions, breathing, phonation, and pressure distribution are demonstrated with repeatable and reliable signals. Self-powered and energy-harvesting capabilities are also presented by driving electronic devices and lighting LEDs. As proof of concept, this work provides new opportunities in a scalable and sustainable way to develop novel wearable electronics and smart clothing for future commercial applications.

Early vs Late Fixation of Extremity Fractures Among Adults With Traumatic Brain Injury.

Importance: The optimal timing for fixation of extremity fractures after traumatic brain injury (TBI) remains controversial. Objective: To investigate whether patients who underwent extremity fixation within 24 hours of TBI experienced worse outcomes than those who had the procedure 24 hours or more after TBI. Design, Setting, and Participants: This cohort study used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. Patients 16 years or older with TBI who underwent internal extremity fixation met inclusion criteria. To compare outcomes, patients who underwent the procedure within 24 hours were propensity score matched with those who underwent it 24 hours or later. Patients were treated from December 9, 2014, to December 17, 2017. Data analysis was conducted between August 1, 2022, and December 25, 2023. Main Outcomes and Measures: The primary outcome was an unfavorable functional status at 6 months (Glasgow Outcome Scale-Extended [GOSE] score ≤4). Results: A total of 253 patients were included in this study. The median age was 41 (IQR, 27-57) years, and 184 patients (72.7%) were male. The median Injury Severity Score (ISS) was 41 (IQR, 27-49). Approximately half of the patients (122 [48.2%]) had a mild TBI while 120 (47.4%) had moderate to severe TBI. Seventy-four patients (29.2%) underwent an internal extremity fixation within 24 hours, while 179 (70.8%) had the procedure 24 hours or later. At 6 months, 86 patients (34.0%) had an unfavorable functional outcome. After propensity score matching, there were no statistically significant differences in unfavorable functional outcomes at 6 months (odds ratio [OR], 1.12 [95% CI, 0.51-1.99]; P = .77) in patients with TBI of any severity. Similar results were observed in patients with mild TBI (OR, 0.71 [95% CI, 0.22-2.29]; P = .56) and moderate to severe TBI (OR, 1.08 [95% CI, 0.32-3.70]; P = .90). Conclusions and Relevance: The outcomes of extremity fracture fixation performed within 24 hours after TBI appear not to be worse than those of procedures performed 24 hours or later. This finding suggests that early fixation after TBI could be considered in patients with mild head injuries.

Generation of a DMD loss-of-function mutant human embryonic stem cell lines by CRISPR base editing.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive disorder, which is caused mostly by frame-disrupting, out-of-frame variation in the dystrophin (DMD) gene. Loss-of- function mutations are the most common type of mutation in DMD, accounting for approximately 60-90% of all DMD variations. In this study, we used adenine base editing to generate a human embryonic stem cell line with splice-site mutations to mimic exon deletion variants in clinical Duchenne muscular dystrophy patients. This cell line has differentiation potential and a normal karyotypic.

miR-15b-5p promotes HgCl2-induced chicken embryo kidney cells ferroptosis by targeting ß-TrCP-mediated ATF4 ubiquitin degradation.

Mercuric chloride (HgCl2), a widespread environmental pollutant, induces ferroptosis in chicken embryonic kidney (CEK) cells. Whereas activating transcription factor 4 (ATF4), a critical mediator of oxidative homeostasis, plays a dual role in ferroptosis, but its precise mechanisms in HgCl2-induced ferroptosis remain elusive. This study aims to investigate the function and molecular mechanism of ATF4 in HgCl2-induced ferroptosis. Our results revealed that ATF4 was downregulated during HgCl2-induced ferroptosis in CEK cells. Surprisingly, HgCl2 exposure has no significant impact on ATF4 mRNA level. Further investigation indicated that HgCl2 enhanced the expression of the E3 ligase beta-transducin repeat-containing protein (ß-TrCP) and increased ATF4 ubiquitination. Subsequent findings identified that miR-15b-5p as an upstream modulator of ß-TrCP, with miR-15b-5p downregulation observed in HgCl2-exposed CEK cells. Importantly, miR-15b-5p mimics suppressed ß-TrCP expression and reversed HgCl2-induced cellular ferroptosis. Mechanistically, HgCl2 inhibited miR-15b-5p, and promoted ß-TrCP-mediated ubiquitin degradation of ATF4, thereby inhibited the expression of antioxidant-related target genes and promoted ferroptosis. In conclusion, our study highlighted the crucial role of the miR-15b-5p/ß-TrCP/ATF4 axis in HgCl2-induced nephrotoxicity, offering a new therapeutic target for understanding the mechanism of HgCl2 nephrotoxicity.

Application of Polymeric CO2 Thickener Polymer-Viscosity-Enhance in Extraction of Low-Permeability Tight Sandstone.

The conventional production technique employed for low-permeability tight reservoirs exhibits limited productivity. To solve the problem, an acetate-type supercritical carbon dioxide (scCO2) thickener, PVE, which contains a large number of microporous structures, was prepared using the atom transfer radical polymerization (ATRP) method. The product exhibited an ability to decrease the minimum miscibility pressure of scCO2 during a solubility test and demonstrated a favorable extraction efficiency in a low-permeability tight core displacement test. At 15 MPa and 70 °C, PVE-scCO2 at a concentration of 0.2% exhibits effective oil recovery rates of 5.61% for the 0.25 mD core and 2.65% for the 5 mD core. The result demonstrates that the incorporation of the thickener PVE can effectively mitigate gas channeling, further improve oil displacement efficiency, and inflict minimal damage to crude oil. The mechanism of thickening was analyzed through molecular simulation. The calculated trend of thickening exhibited excellent agreement with the experimental measurement rule. The simulation results demonstrate that the contact area between the polymer and CO2 increases in direct proportion to both the number of thickener molecules and the viscosity of the system. The study presents an effective strategy for mitigating gas channeling during scCO2 flooding and has a wide application prospect.

One-Step Electrochemical Synthesis of Multiyolk-Shell Nanocoils for Exceptional Photocatalytic Performance.

Multiyolk-shell (mYS) nanostructures have garnered significant interest in various photocatalysis applications such as water splitting and waste treatment. Nonetheless, the complexity and rigorous conditions for the synthesis have hindered their widespread implementation. This study presents a one-step electrochemical strategy for synthesizing multiyolk-shell nanocoils (mYSNC), wherein multiple cores of noble metal nanoparticles, such as Au, are embedded within the hollow coil-shaped FePO4 shell structures, mitigating the challenges posed by conventional methods. By capitalizing on the dissimilar dissolution rates of bimetallic alloy nanocoils in an electrochemically programmed solution, nanocoils of different shapes and materials, including two variations of mYSNCs are successfully fabricated. The resulting Au-FePO4 mYSNCs exhibit exceptional photocatalytic performance for environmental remediation, demonstrating up to 99% degradation of methylene blue molecules within 50 min and 95% degradation of tetracycline within 100 min under ultraviolet-visible (UV-vis) light source. This remarkable performance can be attributed to the abundant electrochemical active sites, internal voids facilitating efficient light harvesting with coil morphology, amplified localized surface plasmon resonance (LSPR) at the plasmonic nanoparticle-semiconductor interface, and effective band engineering. The innovative approach utilizing bimetallic alloys demonstrates precise geometric control and design of intricate multicomponent hybrid composites, showcasing the potential for developing versatile hollow nanomaterials for catalytic applications.

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.