Search

Postconsumer plastics are generally perceived as valueless with only a small portion of plastic waste being closed-loop recycled into similar products while most of them are discarded in landfills. Depositing plastic waste in landfills not only harms the environment but also signifies a substantial economic loss. Alternatively, constructing value-added chemical feedstocks via mining the waste-derived intermediate species as a carbon (C) source under mild electrochemical conditions is a sustainable strategy to realize the circular economy. This proof-of-concept work provides an attractive turning trash to treasure strategy by integrating electrocatalytic polyethylene terephthalate (PET) plastic upcycling with a chemical C-S coupling reaction to synthesize organosulfur compounds, hydroxymethanesulfonate (HMS). HMS can be produced efficiently (Faradaic efficiency, FE of ∼70%) via deliberately capturing electrophilic intermediates generated in the PET monomer (ethylene glycol, EG) upcycling process, followed by coupling them with nucleophilic sulfur (S) species (i.e., SO32- and HSO3-). Unlike many previous studies conducted under alkaline conditions, PET upcycling was performed over an amorphous MnO2 catalyst under near-neutral conditions, allowing for the stabilization of electrophilic intermediates. The compatibility of this strategy was further investigated by employing biomass-derived compounds as substrates. Moreover, comparable HMS yields can be achieved with real-world PET plastics, showing its enormous potential in practical application. Lastly, Density function theory (DFT) calculation reveals that the C-C cleavage step of EG is the rate-determining step (RDS), and amorphous MnO2 significantly decreases the energy barriers for both RDS and C-S coupling when compared to the crystalline counterpart.

Upcycling plastic wastes into value-added chemicals is a promising approach to put end-of-life plastic wastes back into their ecocycle. As one of the polyesters that is used daily, polyethylene terephthalate (PET) plastic waste is employed here as the model substrate. Herein, a nickel (Ni)-based catalyst was prepared via electrochemically depositing copper (Cu) species on Ni foam (NiCu/NF). The NiCu/NF formed Cu/CuO and Ni/NiO/Ni(OH)2 core-shell structures before electrolysis and reconstructed into NiOOH and CuOOH/Cu(OH)2 active species during the ethylene glycol (EG) oxidation. After oxidation, the Cu and Ni species evolved into more reduced species. An indirect mechanism was identified as the main EG oxidation (EGOR) mechanism. In EGOR, NiCu60s/NF catalyst exhibited an optimal Faradaic efficiency (FE, 95.8%) and yield rate (0.70 mmol cm-2 h-1) for formate production. Also, over 80% FE of formate was achieved when a commercial PET plastic powder hydrolysate was applied. Furthermore, commercial PET plastic water bottle waste was employed as a substrate for electrocatalytic upcycling, and pure terephthalic acid (TPA) was recovered only after 1 h electrolysis. Lastly, density functional theory (DFT) calculation revealed that the key role of Cu was significantly reducing the Gibbs free-energy barrier (ΔG) of EGORs rate-determining step (RDS), promoting catalysts dynamic evolution, and facilitating the C-C bond cleavage.

Abstract A fundamental objective of genomics is to track variations in gene expression program. While metabolic RNA labeling-based single-cell RNA sequencing offers insights into temporal biological processes, its limited applicability only to in vitro models challenges the study of in vivo gene expression dynamics. Herein, we introduce Dyna-vivo-seq, a strategy that enables time-resolved dynamic transcription profiling in vivo at the single-cell level by examining new and old RNAs. The new RNAs can offer an additional dimension to reveal cellular heterogeneity. Leveraging new RNAs, we discern two distinct high and low metabolic labeling populations among proximal tubular (PT) cells. Furthermore, we identify 90 rapidly responding transcription factors during the acute kidney injury in female mice, highlighting that high metabolic labeling PT cells exhibit heightened susceptibility to injury. Dyna-vivo-seq provides a powerful tool for the characterization of dynamic transcriptome at the single-cell level in living organism and holds great promise for biomedical applications.

Organized chronic subdural hematoma is a rare form of chronic subdural hematoma. The optimal treatment method is still controversial. Preoperative middle meningeal artery embolization and craniotomy are effective methods for chronic subdural hematoma. However, there are not many reports investigating the effectiveness of these methods in treating organized chronic subdural hematoma. We report the case of a 61-year-old male patient who had a twist-drill craniostomy to treat a left hemisphere subdural hematoma. After surgery, there was a recurrence on the same side in the form of an organized subdural hematoma. The patient received preoperative left middle meningeal artery embolization. After 3 months of follow-up, a small portion of the hematoma remained, causing pressure and slightly shifting the midline to the right by 6.5 mm, and the patient no longer had clinical symptoms.

Abstract The main cause of corneal blindness worldwide is keratitis, especially the infectious form caused by bacteria, fungi, viruses, and Acanthamoeba. The key to effective management of infectious keratitis hinges on prompt and precise diagnosis. Nevertheless, the current gold standard, such as cultures of corneal scrapings, remains time-consuming and frequently yields false-negative results. Here, using 23,055 slit-lamp images collected from 12 clinical centers nationwide, this study constructed a clinically feasible deep learning system, DeepIK, that could emulate the diagnostic process of a human expert to identify and differentiate bacterial, fungal, viral, amebic, and noninfectious keratitis. DeepIK exhibited remarkable performance in internal, external, and prospective datasets (all areas under the receiver operating characteristic curves > 0.96) and outperformed three other state-of-the-art algorithms (DenseNet121, InceptionResNetV2, and Swin-Transformer). Our study indicates that DeepIK possesses the capability to assist ophthalmologists in accurately and swiftly identifying various infectious keratitis types from slit-lamp images, thereby facilitating timely and targeted treatment.

Post-reperfusion syndrome (PRS) is a severe and highly lethal syndrome that occurs after declamping the portal vein forceps during liver transplantation. It is marked by severe hemodynamic disturbances manifested by decreased mean arterial pressure, increased heart rate and elevated pulmonary artery pressure. The complex pathogenesis of PRS remains understudied. It is generally believed to be related to the large amount of acidic, cold blood that enters the circulation after release of the portal clamp. This blood is rich in oxygen-free radicals and metabolic toxins, which not only aggravate the ischemia-reperfusion injury of the liver but also further attack the systemic organs indiscriminately. Considering the range of possible adverse prognoses including acute kidney injury, delirium and graft nonfunction, it is imperative that clinicians increase their awareness and prevention of PRS. The aim of this article is to review the current risk factors, pathophysiological mechanisms and prevention strategies for PRS.

Tumor microenvironments (TMEs) have received increasing attention in recent years as they play pivotal roles in tumorigenesis, progression, metastases, and resistance to the traditional modalities of cancer therapy like chemotherapy. With the rapid development of nanotechnology, effective antineoplastic nanotherapeutics targeting the aberrant hallmarks of TMEs have been proposed. The appropriate design and fabrication endow nanomedicines with the abilities for active targeting, TMEs-responsiveness, and optimization of physicochemical properties of tumors, thereby overcoming transport barriers and significantly improving antineoplastic therapeutic benefits. This review begins with the origins and characteristics of TMEs and discusses the latest strategies for modulating the TMEs by focusing on the regulation of biochemical microenvironments, such as tumor acidosis, hypoxia, and dysregulated metabolism. Finally, this review summarizes the challenges in the development of smart anti-cancer nanotherapeutics for TME modulation and examines the promising strategies for combination therapies with traditional treatments for further clinical translation.

Abstract Background Dry eye is a chronic and multifactorial ocular surface disease caused by tear film instability or imbalance in the microenvironment of the ocular surface. It can lead to various discomforts such as inflammation of the ocular surface and visual issues. However, the mechanism of dry eye is not clear, which results in dry eye being only relieved but not cured in clinical practice. Finding multiple environmental pathways for dry eye and exploring the pathogenesis of dry eye have become the focus of research. Studies have found that changes in microbiota may be related to the occurrence and development of dry eye disease. Methods Entered the keywords “Dry eye”, “Microbiota”, “Bacteria” through PUBMED, summarised the articles that meet the inclusion criteria and then filtered them while the publication time range of the literature was defined in the past 5 years, with a deadline of 2023.A total of 13 clinical and 1 animal-related research articles were screened out and included in the summary. Results Study found that different components of bacteria can induce ocular immune responses through different receptors present on the ocular surface, thereby leading to an imbalance in the ocular surface microenvironment. Changes in the ocular surface microbiota and gut microbiota were also found when dry eye syndrome occurs, including changes in diversity, an increase in pro-inflammatory bacteria, and a decrease in short-chain fatty acid-related bacterial genera that produce anti-inflammatory effects. Fecal microbiota transplantation or probiotic intervention can alleviate signs of inflammation on the ocular surface of dry eye animal models. Conclusions By summarizing the changes in the ocular surface and intestinal microbiota when dry eye occurs, it is speculated and concluded that the intestine may affect the occurrence of eye diseases such as dry eye through several pathways and mechanisms, such as the occurrence of abnormal immune responses, microbiota metabolites- intervention of short-chain fatty acids, imbalance of pro-inflammatory and anti-inflammatory factors, and release of neurotransmitters, etc. Analyzing the correlation between the intestinal tract and the eyes from the perspective of microbiota can provide a theoretical basis and a new idea for relieving dry eyes in multiple ways in the future.

Abstract Background Innate/adaptive immunity is the key to anti-tumor therapy. However, its causal relationship to Gastrointestinal (GI) cancer remains unclear. Methods Immunity genes were extracted from the MSigDB database. The Genome-wide association studies (GWAS) summary data of GI cancer were integrated with expression quantitative trait loci (eQTL) and DNA methylation quantitative trait loci (mQTL) associated with genes. Summary-data-based Mendelian randomization (SMR) and co-localization analysis were used to reveal causal relationships between genes and GI cancer. Two-sample MR analysis was used for sensitivity analysis. Single cell analysis clarified the enrichment of genes. Results Three-step SMR analysis showed that a putative mechanism, cg17294865 CpG site regulating HLA-DRA expression was negatively associated with gastric cancer risk. HLA-DRA was significantly differentially expressed in monocyte/macrophage and myeloid cells in gastric cancer. Conclusion This study provides evidence that upregulating the expression level of HLA-DRA can reduce the risk of gastric cancer.

Much effort has been devoted to improving treatment efficiency for osteosarcoma (OS). However, most current approaches result in poor therapeutic responses, thus indicating the need for the development of other therapeutic options. This study developed a multifunctional nanoparticle, PDA-MOF-E-M, an aggregation of OS targeting, programmed death targeting, and near-infrared (NIR)-aided targeting. At the same time, a multifunctional nanoparticle that utilises Fe-MOFs to create a cellular iron-rich environment and erastin as a ferroptosis inducer while ensuring targeted delivery to OS cells through cell membrane encapsulation is presented. The combination of PDA-MOF-E-M and PTT increased intracellular ROS and LPO levels and induced ferroptosis-related protein expression. A PDA-based PTT combined with erastin showed significant synergistic therapeutic improvement in the anti-tumour efficiency of the nanoparticle in vitro and vivo. The multifunctional nanoparticle efficiently prevents the osteoclasia progression of OS xenograft bone tumors in vivo. Finally, this study provides guidance and a point of reference for clinical approaches to treating OS.

Active sites are atomic sites within catalysts that drive reactions and are essential for catalysis. Spatially confining guest metals within active site microenvironments has been predicted to improve catalytic activity by altering the electronic states of active sites. Using the hydrogen evolution reaction (HER) as a model reaction, we show that intercalating zinc single atoms between layers of 1T-MoS2 (Zn SAs/1T-MoS2) enhances HER performance by decreasing the overpotential, charge transfer resistance, and kinetic barrier. The confined Zn atoms tetrahedrally coordinate to basal sulfur (S) atoms and expand the interlayer spacing of 1T-MoS2 by ∼3.4%. Under confinement, the Zn SAs donate electrons to coordinated S atoms, which lowers the free energy barrier of H* adsorption-desorption and enhances HER kinetics. In this work, which is applicable to all types of catalytic reactions and layered materials, HER performance is enhanced by controlling the coordination geometry and electronic states of transition metals confined within active-site microenvironments.

In this study, a coupla risk combinations and coping strategies have been developed for confronting conflicts between population–economy development and water resource management (PEWM) due to population–industry transformation (PIT) into a floodplain of the economic belt under climate change. A location-entropy-based PVAR (Panel Vector Autoregression) model coupla-risk analysis (LPCR) can be introduced into PEWM to reflect the adverse effects of population–industry transformation on a special function area (e.g., floodplain) of the economic belt, where the coupla risk map has been addressed. Meanwhile, an adaptive scenario analysis-based stochastic–fuzzy method (ASSF) can be joined to deal with multiple uncertainties and their interactions due to subjective and artificial factors. The proposed LPCR and ASSF can be integrated into a risk-based stochastic–fuzzy scenario method framework (RASF) to apply for a practical PEWM case study of the Yongding River floodplain in the context of the coordinative development of the Beijing–Tianjin–Hebei economic belt, China. The results can be presented as follows: 1) the PIT was accelerated into the floodplain due to the fact that it can require more water resources, where each additional unit can promote the regional gross domestic product (GDP) by 0.019 units, increasing the water demand by 0.046 units. It can strengthen various risks such as water shortage, soil loss, and flood control investment in a floodplain of the economic belt; 2) the farmland returning to wetland (CFW) can decrease the water demand and shortage ratio (would be 0% at highest) for irrigation in the long run, but this would reduce the direct economic income of irrigation in the short run; 3) backward irrigative schemes and low water utilization efficiency require a cleaner production mode, which could reduce water shortages by 77.23 × 10^3 m3 at the highest; and 4) the combined policy (S12) can reduce coupla risks (including the risk of water shortage, soil loss, and flood) compared to other individual policies (S2, S4, S6, and S8). The findings can assist local decision-makers to gain insights into adjusting interegional strategies not only for remitting population–resource stress in core cities but also for improving the resilience against drought and flood in a floodplain area, which is conducive of the special function of the floodplain to support an integrated sustainable development of the economic belt.

The existing methods for evaluating voltage sag severity do not sufficiently consider the effect of the multiple line characteristic factors on the line failure probability, which leads to a large error in the evaluation results. Therefore, an evaluation method for voltage sag severity based on multiple line characteristic factors fusion is proposed. Firstly, based on line historical fault data, the influence degree of multiple line characteristic factors on line fault which employ association rules to quantify is researched. Secondly, by improving the D-S evidence theory to fuse multiple line characteristic factors, an accurate line annual failure probability model is established, and the voltage sag severity of nodes by introducing maximum entropy into the method of fault positions are obtained. Finally, a comprehensive voltage sag severity index considering both voltage sag severity of power grid side and tolerance characteristics of sensitive equipment on the user side is proposed to evaluate node voltage sag severity. Based on the actual power quality monitoring data for validation and comparison with the evaluation cases that do not fully consider the line characteristic factors, the results show that the proposed method can effectively improve the accuracy of voltage sag severity evaluation.

Recently, poly(ethylene oxide) (PEO)-based solid polymer electrolytes have been attracting great attention, and efforts are currently underway to develop PEO-based composite electrolytes for next generation high performance all-solid-state lithium metal batteries. In this article, a novel sandwich structured solid-state PEO composite electrolyte is developed for high performance all-solid-state lithium metal batteries. The PEO-based composite electrolyte is fabricated by hot-pressing PEO, LiTFSI and Ti3C2Tx MXene nanosheets into glass fiber cloth (GFC). The as-prepared GFC@PEO-MXene electrolyte shows high mechanical properties, good electrochemical stability, and high lithium-ion migration number, which indicates an obvious synergistic effect from the microscale GFC and the nanoscale MXene. Such as, the GFC@PEO-1 wt% MXene electrolyte shows a high tensile strength of 43.43 ​MPa and an impressive Young's modulus of 496 ​MPa, which are increased by 1205% and 6048% over those of PEO. Meanwhile, the ionic conductivity of GFC@PEO-1 wt% MXene at 60 ​°C reaches 5.01 ​× ​10−2 ​S ​m−1, which is increased by around 200% compared with that of GFC@PEO electrolyte. In addition, the Li/Li symmetric battery based on GFC@PEO-1 wt% MXene electrolyte shows an excellent cycling stability over 800 ​h (0.3 ​mA ​cm−2, 0.3 ​mAh cm−2), which is obviously longer than that based on PEO and GFC@PEO electrolytes due to the better compatibility of GFC@PEO-1 wt% MXene electrolyte with Li anode. Furthermore, the solid-state Li/LiFePO4 battery with GFC@PEO-1 wt% MXene as electrolyte demonstrates a high capacity of 110.2–166.1 ​mAh g−1 in a wide temperature range of 25–60 ​°C, and an excellent capacity retention rate. The developed sandwich structured GFC@PEO-1 wt% MXene electrolyte with the excellent overall performance is promising for next generation high performance all-solid-state lithium metal batteries.

Objective To investigate the predictive value of albumin-bilirubin (ALBI) score combined with liver function index and carcinoembryonic antigen (CEA) for liver metastasis of colorectal cancer. Methods We retrospectively analyzed the clinical data of patients with colorectal cancer who underwent surgical treatment in the Second Hospital & Clinical Medical Hospital, Lanzhou University from January 2016 to July 2021 and were followed up for 24 months. According to the follow-up results, the enrolled patients were divided into liver metastasis group and non-liver metastasis group, and were randomly divided into modeling group and validation group by a ratio of 2∶1. The risk factors of liver metastasis in the patients with colorectal cancer were analyzed. Lasso-Logistic regression was used to construct the prediction model. Bootstrap method was used for internal verification. Receiver operating characteristic curve, calibration curve and clinical decision curve were used to evaluate the reliability of the prediction model. Finally, a nomogram was drawn to show the prediction results. Results A total of 195 patients who met the inclusion and exclusion criteria were enrolled, including 130 in the modeling group and 65 in the validation group. Through Lasso regression variable screening and Logistic regression analysis, the results showed that ALBI score(OR=8.062, 95% CI: 2.545-25.540), alanine transaminase (ALT) (OR=1.037, 95% CI: 1.004-1.071) and CEA (OR=1.025, 95% CI: 1.008-1.043) were independent predictors of liver metastasis in colorectal cancer. The area under curve (AUC) of the combined prediction of liver metastasis of colorectal cancer in the modeling group was 0.921, the sensitivity was 78%, the specificity was 95%, the C-index was 0.921, the H-L fitting curve χ2=0.851, P=0.654, and the slope of the calibration curve was close to 1, suggesting that the accuracy of the model was high, and the DCA curve showed that the model had good clinical application value. For the data of the modeling group, the Bootstrap method was used for internal verification of 1000 resamplings. The accuracy was 0.869, the kappa consistency was 0.709, and the AUC was 0.913. When ALBI score, ALT and CEA were used to diagnose liver metastasis of colorectal cancer alone, the AUC of CEA was the largest (0.897), and the combination of the three had the highest efficacy in the diagnosis of liver metastasis of colorectal cancer. In the validation group, the AUC, sensitivity, specificity, C-index of the combined prediction of liver metastasis of colorectal cancer were 0.918, 85.0%, 95.6%, 0.918, respectively, and H-L fitting curve χ2=0.586, P=0.746. Conclusions ALBI score, ALT and CEA have certain predictive value for liver metastasis of colorectal cancer. The combined diagnosis of liver metastasis of colorectal cancer has high efficacy, and the risk prediction model constructed has a good predictive effect.