NecroGlobalGCN: Integrating micronecrosis information in HCC prognosis prediction via graph convolutional neural networks.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) ranks fourth in cancer mortality, underscoring the importance of accurate prognostic predictions to improve postoperative survival rates in patients. Although micronecrosis has been shown to have high prognostic value in HCC, its application in clinical prognosis prediction requires specialized knowledge and complex calculations, which poses challenges for clinicians. It would be of interest to develop a model to help clinicians make full use of micronecrosis to assess patient survival. METHODS: To address these challenges, we propose a HCC prognosis prediction model that integrates pathological micronecrosis information through Graph Convolutional Neural Networks (GCN). This approach enables GCN to utilize micronecrosis, which has been shown to be highly correlated with prognosis, thereby significantly enhancing prognostic stratification quality. We developed our model using 3622 slides from 752 patients with primary HCC from the FAH-ZJUMS dataset and conducted internal and external validations on the FAH-ZJUMS and TCGA-LIHC datasets, respectively. RESULTS: Our method outperformed the baseline by 8.18% in internal validation and 9.02% in external validations. Overall, this paper presents a deep learning research paradigm that integrates HCC micronecrosis, enhancing both the accuracy and interpretability of prognostic predictions, with potential applicability to other pathological prognostic markers. CONCLUSIONS: This study proposes a composite GCN prognostic model that integrates information on HCC micronecrosis, collecting large dataset of HCC histopathological images. This approach could assist clinicians in analyzing HCC patient survival and precisely locating and visualizing necrotic tissues that affect prognosis. Following the research paradigm outlined in this paper, other prognostic biomarker integration models with GCN could be developed, significantly enhancing the predictive performance and interpretability of prognostic model.

Global research trends in postoperative ileus from 2011 to 2023: A scientometric study.

BACKGROUND: Postoperative ileus (POI) is a common complication after abdominal surgery with high morbidity, which hinders patient recovery, prolongs hospitalization, and increases healthcare costs. Therefore, POI has become a global public health challenge. POI triggering is multifactorial. Autonomic and hormonal mechanisms are generally involved in POI pathogenesis. Recent studies have shown that beta adrenergic signaling of enteric glia is a POI trigger. Currently, the status quo, trends, and frontiers of global research on POI remain unclear. AIM: To explore the current status, trends, and frontiers of POI research from 2011 to the present based on bibliometric analysis. METHODS: Publications published on POI research from 2011 to 2023 were retrieved on June 1, 2023, from the Web of Science Core Collection. CiteSpace 6.2.R2 and VOSviewer were used to conduct bibliometric visualization. RESULTS: In total, 778 POI records published from 2011 to 2023 were retrieved. Over the past few decades, the annual cumulative number of related articles has linearly increased, with China and the United States of America contributing prominently. All publications were from 59 countries and territories. China and the University of Bonn were the top contributing country and institution, respectively. Neurogastroenterology & Motility was the most prolific journal. The Journal of Gastrointestinal Surgery had the highest number of citations. Wehner Sven was the most productive author. Burst keywords (e.g., colon, prolonged ileus, acupuncture, paralytic ileus, pathophysiology, rectal cancer, gastrointestinal function, risk) and a series of reference citation bursts provided evidence for the research frontiers in recent years. CONCLUSION: This study demonstrates trends in the published literature on POI and provides new insights for researchers. It emphasizes the importance of multidisciplinary cooperation in the development of this field.

Customizing H2O-Poor Electric Double Layer and Boosting Texture Exposure of Zn (101) Plane towards Super-High Areal Capacity Zinc Metal Batteries.

The catastrophic dendrite hyperplasia and parasitic reactions severely impede the future deployment of aqueous Zn-ion batteries. Controlling zinc orientation growth is considered to be an effective method to overcome the aforementioned concerns, especially for regulating the (002) plane of deposited Zn. Unfortunately, Zn (002) texture is difficult to obtain stable cycling under high deposition capacity resulting from its large lattice distortion and nonuniform distribution in electric field. Herein, different from traditional cognition, a crystallization orientation regulation tactic is proposed to boost Zn (101) texture exposure and inhibit zinc dendrite proliferation during plating/stripping. Experimental results and theoretical calculations demonstrate the malate molecules preferentially adsorb on the Zn (002) facet, leading to the texture exposure of distinctive Zn (101) plane. Meanwhile, the -COOH and -OH groups of malate molecules exhibit strong adsorption on the Zn anode surface and chelate with Zn2+, achieving H2O-poor electrical double layer. Very impressively, the multifunctional malate additive enlists zinc anode to survive for 600 h under a harsh condition of 15 mAh cm-2/15 mAh cm-2. Moreover, the symmetric cell harvests highly-reversible cycling life of 6600 h at 5 mA cm-2/1.25 mAh cm-2, remarkably outperforming the ZnSO4 electrolyte. The assembled Zn//MnO2 full cells also demonstrate prominent electrochemical reversibility.

[Stabilization of Cd-contaminated Soil with Thiol-modified Biochar and Response of Soil Microorganisms].

To explore the stabilization effect of livestock manure biochar on Cd-contaminated soil and its impact on the soil environment, a pot experiment was conducted to investigate the stabilization efficiency of cattle manure-biochar （BC） and thiol-modified biochar （SBC） on Cd in soil and their effect on the soil properties and microbial community. The structural equation model （SEM） was used to analyze the effect pathways of BC and SBC on the soil microbial community. The results showed that BC and SBC increased soil pH, available potassium, available phosphorus, and organic matter content but decreased soil available nitrogen content compared with those in CK. The stabilization efficiency of BC for Cd in soil was 14.97%, which was much lower than that of SBC （85.71%）. Moreover, SBC increased the abundance of dominant bacterial phyla in soil, with Proteobacteria, Bacteroidota, and Cyanobacteria increasing most significantly. SBC decreased the diversity of soil microorganisms, but the decrease was insignificant （P≥0.05） compared with that in CK and BC. SEM analysis indicated that the available phosphorus, available potassium, organic matter, and soil pH were the key factors influencing Cd availability in soil, whereas organic matter and Cd availability were the key factors affecting the soil microbial community. Overall, SBC could stabilize Cd effectively and increase the abundance of dominant bacteria and has great potential in the remediation of Cd-contaminated soil.

Unlocking the potential of LHPP: Inhibiting glioma growth and cell cycle via the MDM2/p53 pathway.

The recurrence of glioma after treatment has remained an intractable problem for many years. Recently, numerous studies have explored the pivotal role of the mouse double minute 2 (MDM2)/p53 pathway in cancer treatment. Lysine phosphate phosphohistidine inorganic pyrophosphate phosphatase (LHPP), a newly discovered tumor suppressor, has been confirmed in numerous studies on tumors, but its role in glioma remains poorly understood. Expression matrices in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were analyzed using gene set enrichment analysis (GSEA), revealing significant alterations in the p53 pathway among glioma patients with high LHPP expression. The overexpression of LHPP in glioma cells resulted in a reduction in cell proliferation, migration, and invasive ability, as well as an increase in apoptosis and alterations to the cell cycle. The present study has identified a novel inhibitory mechanism of LHPP against glioma, both in vivo and in vitro. The results demonstrate that LHPP exerts anti-glioma effects via the MDM2/p53 pathway. These findings may offer a new perspective for the treatment of glioma in the clinic.

Promoting smartphone-based keratitis screening using meta-learning: A multicenter study.

OBJECTIVE: Keratitis is the primary cause of corneal blindness worldwide. Prompt identification and referral of patients with keratitis are fundamental measures to improve patient prognosis. Although deep learning can assist ophthalmologists in automatically detecting keratitis through a slit lamp camera, remote and underserved areas often lack this professional equipment. Smartphones, a widely available device, have recently been found to have potential in keratitis screening. However, given the limited data available from smartphones, employing traditional deep learning algorithms to construct a robust intelligent system presents a significant challenge. This study aimed to propose a meta-learning framework, cosine nearest centroid-based metric learning (CNCML), for developing a smartphone-based keratitis screening model in the case of insufficient smartphone data by leveraging the prior knowledge acquired from slit-lamp photographs. METHODS: We developed and assessed CNCML based on 13,009 slit-lamp photographs and 4,075 smartphone photographs that were obtained from 3 independent clinical centers. To mimic real-world scenarios with various degrees of sample scarcity, we used training sets of different sizes (0 to 20 photographs per class) from the HUAWEI smartphone to train CNCML. We evaluated the performance of CNCML not only on an internal test dataset but also on two external datasets that were collected by two different brands of smartphones (VIVO and XIAOMI) in another clinical center. Furthermore, we compared the performance of CNCML with that of traditional deep learning models on these smartphone datasets. The accuracy and macro-average area under the curve (macro-AUC) were utilized to evaluate the performance of models. RESULTS: With merely 15 smartphone photographs per class used for training, CNCML reached accuracies of 84.59%, 83.15%, and 89.99% on three smartphone datasets, with corresponding macro-AUCs of 0.96, 0.95, and 0.98, respectively. The accuracies of CNCML on these datasets were 0.56% to 9.65% higher than those of the most competitive traditional deep learning models. CONCLUSIONS: CNCML exhibited fast learning capabilities, attaining remarkable performance with a small number of training samples. This approach presents a potential solution for transitioning intelligent keratitis detection from professional devices (e.g., slit-lamp cameras) to more ubiquitous devices (e.g., smartphones), making keratitis screening more convenient and effective.

MLKL-mediated endothelial necroptosis drives vascular damage and mortality in systemic inflammatory response syndrome.

The hypersecretion of cytokines triggers life-threatening systemic inflammatory response syndrome (SIRS), leading to multiple organ dysfunction syndrome (MODS) and mortality. Although both coagulopathy and necroptosis have been identified as important factors in the pathogenesis of SIRS, the specific cell types that undergo necroptosis and the interrelationships between coagulopathy and necroptosis remain unclear. In this study, we utilized visualization analysis via intravital microscopy to demonstrate that both anticoagulant heparin and nonanticoagulant heparin (NAH) pretreatment protect mice against TNF-α-induced mortality in SIRS. Moreover, the deletion of Mlkl or Ripk3 resulted in decreased coagulation and reduced mortality in TNF-α-induced SIRS. These findings suggest that necroptosis plays a key role upstream of coagulation in SIRS-related mortality. Furthermore, using a genetic lineage tracing mouse model (Tie2-Cre;Rosa26-tdT), we tracked endothelial cells (ECs) and verified that EC necroptosis is responsible for the vascular damage observed in TNF-α-treated mice. Importantly, Mlkl deletion in vascular ECs in mice had a similar protective effect against lethal SIRS by blocking EC necroptosis to protect the integrity of the endothelium. Collectively, our findings demonstrated that RIPK3-MLKL-dependent necroptosis disrupted vascular integrity, resulting in coagulopathy and multiorgan failure, eventually leading to mortality in SIRS patients. These results highlight the importance of targeting vascular EC necroptosis for the development of effective treatments for SIRS patients.

Trusted artificial intelligence for environmental assessments: An explainable high-precision model with multi-source big data.

Environmental assessments are critical for ensuring the sustainable development of human civilization. The integration of artificial intelligence (AI) in these assessments has shown great promise, yet the "black box" nature of AI models often undermines trust due to the lack of transparency in their decision-making processes, even when these models demonstrate high accuracy. To address this challenge, we evaluated the performance of a transformer model against other AI approaches, utilizing extensive multivariate and spatiotemporal environmental datasets encompassing both natural and anthropogenic indicators. We further explored the application of saliency maps as a novel explainability tool in multi-source AI-driven environmental assessments, enabling the identification of individual indicators' contributions to the model's predictions. We find that the transformer model outperforms others, achieving an accuracy of about 98% and an area under the receiver operating characteristic curve (AUC) of 0.891. Regionally, the environmental assessment values are predominantly classified as level II or III in the central and southwestern study areas, level IV in the northern region, and level V in the western region. Through explainability analysis, we identify that water hardness, total dissolved solids, and arsenic concentrations are the most influential indicators in the model. Our AI-driven environmental assessment model is accurate and explainable, offering actionable insights for targeted environmental management. Furthermore, this study advances the application of AI in environmental science by presenting a robust, explainable model that bridges the gap between machine learning and environmental governance, enhancing both understanding and trust in AI-assisted environmental assessments.

Source-specific probabilistic health risk assessment of dust PAHs in urban parks based on positive matrix factorization and Monte Carlo simulation.

Understanding the health risks of polycyclic aromatic hydrocarbons (PAHs) in dust from city parks and prioritizing sources for control are essential for public health and pollution management. The combination of Source-specific and Monte Carlo not only reduces management costs, but also improves the accuracy of assessments. To evaluate the sources of PAHs in urban park dust and the possible health risks caused by different sources, dust samples from 13 popular parks in Kaifeng City were analyzed for PAHs using gas chromatograph-mass spectrometer (GC-MS). The results showed that the surface dust PAH content in the study area ranged from 332.34 µg·kg-1 to 7823.03 µg·kg-1, with a mean value of 1756.59 µg·kg-1. Nemerow Composite Pollution Index in the study area ranged from 0.32 to 14.41, with a mean of 2.24, indicating that the overall pollution warrants attention. Four pollution sources were identified using the positive matrix factorization (PMF) model: transportation source, transportation-coal and biomass combustion source, coke oven emission source, and petroleum source, with contributions of 33.74%, 25.59%, 22.14%, and 18.54%, respectively. The Monte Carlo cancer risk simulation results indicated that park dust PAHs pose a potential cancer risk to all three populations (children, adult male and adult female). Additionally, the cancer risk for children was generally higher than that for adult males and females, with transportation sources being the main contributor to the carcinogenic risk. Lastly, sensitivity analyses results showed that the toxic equivalent concentration (CS) is the parameter contributing the most to carcinogenic risk, followed by Exposure duration (ED).

Tough and thermal insulating cellulose-based aerogel fiber via long yarn-assisted interfacial polyelectrolyte complexation spinning.

Cellulose-based aerogel fibers are recognized as a promising candidate for wearable thermal insulation textiles due to their high porosity, extremely low thermal conductivity, and environmental friendliness. Unfortunately, their practical application in textiles is severely limited by their brittleness. Herein, a novel "long yarn-assisted interfacial polyelectrolyte complexation (YAIPC) spinning" technique is proposed to fabricate cellulose-based aerogel fibers with a unique core-shell structure. The as-prepared core-shell aerogel fibers show excellent thermal insulation performance (34.3 mW m-1 K-1) and robust mechanical strength (∼100 MPa, 31.5 MJ m-3), providing great potential as wearable thermal insulating materials. Accordingly, our research would open a new avenue for designing and constructing wearable aerogel fibers and textiles.

A Synergistically Regulated Cathode/Electrolyte Interphase With High Stability and Rapid Zn2+ Migration Toward Advanced Flexible Zinc-Ion Batteries.

Na3V2(PO4)3(NVP), as a representative sodium superionic conductor with a stable polyanion framework, is considered a cathode candidate for aqueous zinc-ion batteries attributed to their high discharge platform and open 3D structure. Nevertheless, the structural stability of NVP and the cathode-electrolyte interphase (CEI) layer formed on NVP can be deteriorated by the aqueous electrolyte to a certain extent, which will result in slow Zn2+ migration. To solve these problems, doping Si elements to NVP and adding sodium acetate (NaAc) to the electrolyte are utilized as a synergistic regulation route to enable a highly stable  CEI with rapid Zn2+ migration. In this regard, Ac- competitively takes part in the solvation structure of Zn2+ in aqueous electrolyte, weakening the interaction between water and Zn2+, and meanwhile a highly stable CEI is formed to avoid structural damage and enable rapid Zn2+ migration. The NVPS/C@rGO electrode exhibits a notable capacity of 115.5 mAh g-1 at a current density of 50 mA g-1 in the mixed electrolyte (3 M ZnOTF2+3 M NaAc). Eventually, a collapsible "sandwich" soft pack battery is designed and fabricated and can be used to power small fans and LEDs, which proves the practical application of aqueous zinc-ion batteries in flexible batteries.

Effects of intrauterine infusion of autologous platelet-rich plasma gel on endometrial thickness and outcomes of frozen-thawed embryo transfer in women with thin endometrium.

PURPOSE: The purpose of this study is to determine whether intrauterine infusion of autologous platelet-rich plasma (PRP) gel increases endometrial thickness (EMT) and improves the outcomes of frozen-thawed embryo transfer (FET) in women with thin endometrium. METHODS: This study included 111 women (aged 25-44 years) who had thin endometrium. All patients had at least one previous cycle canceled because of thin endometrium or previous embryo transfer cycles and an EMT < 7 mm. Forty-seven women underwent intrauterine infusion of autologous PRP gel on three occasions during endometrial preparation and the remaining women served as controls. The final EMT was measured by ultrasound before the start of the luteal phase, and FET-related outcome parameters were monitored. RESULTS: Mean EMT was greater in women who received PRP gel than in those who did not (6.7 mm vs. 6.3 mm, respectively, p < 0.05). FET was attempted in all women. The 47 women who underwent infusion of PRP had a significantly higher pregnancy rate (18 pregnancies (38.3%), with 17 (36.2%) ongoing) compared with 64 control women (ten pregnancies (18.5%), nine (16.7%) ongoing). However, there was no significant reduction in the miscarriage rate. CONCLUSION: Intrauterine infusion of autologous PRP gel during endometrial preparation for FET cycles can improve the EMT, clinical pregnancy rate, and ongoing pregnancy rate in women with thin endometrium.

Spin Manipulation of Heterogeneous Molecular Electrocatalysts by an Integrated Magnetic Field for Efficient Oxygen Redox Reactions.

Understanding the spin-dependent activity of nitrogen-coordinated single metal atom (M-N-C) electrocatalysts for oxygen reduction and evolution reactions (ORR and OER) remains challenging due to the lack of structure-defined catalysts and effective spin manipulation tools. Herein, both challenges using a magnetic field integrated heterogeneous molecular electrocatalyst prepared by anchoring cobalt phthalocyanine (CoPc) deposited carbon black on polymer-protected magnet nanoparticles, are addressed. The built-in magnetic field can shift the Co center from low- to high-spin (HS) state without atomic structure modification, affording one-order higher turnover frequency, a 50% increased H2O2 selectivity for ORR, and a ≈4000% magnetocurrent enhancement for OER. This catalyst can significantly minimize magnet usage, enabling safe and continuous production of a pure H2O2 solution for 100 h from a 100 cm2 electrolyzer. The new strategy demonstrated here also applies to other metal phthalocyanine-based catalysts, offering a universal platform for studying spin-related electrochemical processes.

Exploratory research on the effective chemical basis of Tanreqing injection for treating acute lung injury: in vivo, in vitro and in silico.

ETHNOPHARMACOLOGICAL RELEVANCE: Sepsis-induced acute lung injury (ALI) presents with significant morbidity and mortality in clinical settings. Tanreqing Injection (TRQI) has been clinically recommended for the treatment of ALI; however, the specific active chemical constituents remain unidentified. AIM OF THE STUDY: This study aimed to elucidate the potential pharmacologically active components and the underlying mechanisms of TRQI in the treatment of sepsis-induced ALI. MATERIALS AND METHODS: High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) techniques were employed to identify the effective chemical constituents of TRQI. Additionally, an in vitro study was conducted using Raw264.7 macrophage cells stimulated with lipopolysaccharide (LPS) to evaluate the inhibitory effects of TRQI. An acute lung injury model produced by LPS was intraperitoneal injection in mice to assess the ALI-inhibitory effect of TRQI. The lung's pathological characteristics were examined using hematoxylin and eosin staining. Enzyme-linked immunosorbent assay (ELISA) and QPCR were performed to confirm the pharmaceutical effect. Network pharmacology was employed for mechanistic exploration, incorporating GO, and PPI analyses of targets. Src inhibitor and JNK agonist used to investigate the dependence of associated signaling pathways. RESULTS: Combining pharmacokinetic characteristics, lung first-pass effect and anti-inflammatory effects, the main components of TRQI for treating sepsis induced ALI were narrowed down to seven compounds: chlorogenic acid, scutellarin, wogonoside, oroxyloside, oroxylin A and baicalein. Network pharmacology indicated that Src/JNK signaling pathway, may be the main regulatory pathway for treatment of actue lung injury. Next by using Src inhibitor, Src inhibition partly diminished the protective effects of TRQI in LPS-injected mice. Pretreatment with JNK agonist anisomycin abolished the protective effects of lung injury in vivo. CONCLUSIONS: TRQI is injected, the seven compounds could be presented in vivo, which can improve ALI by inhibiting Src-JNK signaling.

Urban traffic tiny object detection via attention and multi-scale feature driven in UAV-vision.

The unmanned aerial vehicle (UAV) city patrol is of great significance in ensuring the safety of residents' lives and properties, as well as maintaining the normal operation of the city. However, the detection of UAV images faces challenges such as numerous small-scale objects, complex backgrounds, and high requirements for detection speed. In response to these issues, we introduce a Real-time Small Object Detection network in UAV-vision (RTS-Net), tailored for UAV patrols. Initially, we introduce a multiscale feature fusion module (MFFM) designed to augment the expressiveness of features across scales, thereby enhancing the detection of smaller objects. Subsequently, leveraging attention mechanisms, we present the coordinated attention detection module (CADM), which bolsters the detection model's ability to accurately segregate objects from the background in expansive, complex scenarios. Lastly, a lightweight real-time feature extraction module (RFEM) is crafted to diminish model computational complexity and boost inference speed. On the UAV road patrol image dataset we constructed, our proposed method attains a detection accuracy of 89.9 % mAP, breaking previous records. It surpasses all prevailing detection methods, particularly for small-scale objects. Simultaneously, it achieves an inference speed of 163.9 FPS. The experimental results show that RTS-Net can satisfy the accurate and efficient detection of ground objects by various different UAV platforms in different complex scenarios.

A solar-driven nanocellulose Janus aerogel with excellent floating stability and dual functions of oil-water separation and photocatalytic degradation of organic pollutants.

Effective and practical cleanup of viscous crude oil spills is extremely important in real harsh marine environments. Herein, we designed a solar-driven, nanocellulose-based Janus aerogel (Janus-A) with excellent floating stability and dual function of oil-water separation and degradation of aqueous organic pollutants. Janus-A, with its amphiprotic nature, was prepared through polypyrrole (PPy) deposition, freeze-drying, octyltrichlorosilane (OTS) impregnation, TiO2 spraying on the bottom surface, and UV irradiation treatment. The photothermal conversion effect of PPy coating raised the surface temperature of aerogel to 75.8 °C within 6 min under one simulated solar irradiation, which greatly reduced the viscosity of the crude oil and increased the absorption capacity of the aerogel to 36.7 g/g. Benefiting from the balance between the buoyancy generated by the hydrophobic part and water absorption of the hydrophilic part, Janus-A showed excellent floating stability under simulated winds and waves. In addition, Janus-A exhibited high degradation efficiency for organic pollutants in water owing to the synergistic photocatalytic properties of TiO2 and PPy. These excellent performances make Janus-A ideal for integrated water-oil separation and water remediation.

A novel scoring system based on magnetic resonance imaging for the prediction of the difficulty of ultrasound-guided high-intensity focused ultrasound ablation for uterine fibroids.

OBJECTIVE: To develop a novel scoring system based on magnetic resonance imaging (MRI) for predicting the difficulty of ultrasound-guided high-intensity focused ultrasound (USgHIFU) ablation for uterine fibroids. MATERIALS AND METHODS: A total of 637 patients with uterine fibroids were enrolled. Sonication time, non-perfused volume ratio (NPVR), and ultrasound energy delivered for ablating 1 mm3 of fibroid tissue volume (E/V) were each classified as three levels and assigned scores from 0 to 2, respectively. Treatment difficulty level was then assessed by adding up the scores of sonication time, NPVR and E/V for each patient. The patients with score lower than 3 were categorized into low difficulty group, with score equal to or greater than 3 were categorized into high difficulty group. The potential predictors for treatment difficulty were compared between the two groups. Multifactorial logistic regression analysis model was created by analyzing the variables. The difficulty score system was developed using the beta coefficients of the logistic model. RESULTS: Signal intensity on T2WI, fibroid location index, largest diameter of fibroids, abdominal wall thickness, homogeneity of the signal of fibroids, and uterine position were independent influencing factors for the difficulty of USgHIFU for uterine fibroids. A prediction equation was obtained: difficulty score = 17 × uterine position (anteverted =0, retroverted =1)+71 × signal intensity (hypointense = 0, isointense/hyperintense = 1) +8 × enhancement (homogenous = 0, heterogeneous = 1)+25×(largest diameter of fibroids-20) +35 × (fibroid location index -0.2) +1×(abdominal wall thickness -5). CONCLUSIONS: This scoring system established based on MRI findings can be used to reliably predict the difficulty level of USgHIFU treatment of uterine fibroids.

Progress of metal-loaded biochar-activated persulfate for degradation of emerging organic contaminants.

In recent years, studies on the degradation of emerging organic contaminants by sulfate radical (SO4-·) based advanced oxidation processes (SR-AOPs) have triggered increasing attention. Metal-loaded biochar (Me-BC) can effectively prevent the agglomeration and leaching of transition metals, and its good physicochemical properties and abundant active sites induce outstanding in activating persulfate (PS) for pollutant degradation, which is of great significance in the field of advanced oxidation. In this paper, we reviewed the preparation method and stability of Me-BC, the effect of metal loading on the physicochemical properties of biochar, the pathways of pollutant degradation by Me-BC-activated PS (including free radical pathways: SO4-·, hydroxyl radical (·OH), superoxide radicals (O2-·); non-free radical pathways: singlet oxygen (1O2), direct electron transfer), and discussed the activation of different active sites (including metal ions, persistent free radicals, oxygen-containing functional groups, defective structures, etc.) in the SR-AOPs system. Finally, the prospect was presented for the current research progress of Me-BC in SR-AOPs technology.

Single-atom catalysts activate persulfate to degrade emerging organic contaminants in aqueous environments.

Single-atom catalysts (SACs) exhibit outstanding catalytic activity due to their highly dispersed metal centers. Activating persulfates (PS) with SACs can generate various reactive oxygen species (ROS) to efficiently degrade emerging organic contaminants (EOCs) in aqueous environments, offering unique advantages such as high reaction rates and excellent stability. This technique has been extensively researched and holds enormous potential applications. In this paper, we comprehensively elaborated on the synthesis methods of SACs and their limitations, and factors influencing the catalytic performance of SACs, including metal center characteristics, coordination environment, and types of substrates. We also analyzed practical considerations for application. Subsequently, we discussed the mechanism of SACs activating PS for EOCs degradation, encompassing adsorption processes, radical pathways, and non-radical pathways. Finally, we provide prospects and outline our vision for future research, aiming to guide advancements in applying this technique.

Administration of methylprednisolone do not affect the spinal scar component of spinal cord injury.

OBJECTIVE: The aim of this study is to evaluate the impact of methylprednisolone (MP) on scar composition following spinal cord injury (SCI). DESIGN: A total of 40 adult Sprague Dawley rats underwent right hemisection injuries to the spinal cord. INTERVENTIONS: The rats were randomly divided into two groups: the vehicle group and the MP group. In the MP group, rats received intraperitoneal injections of MP at a dose of 30 mg/kg for 7 consecutive days, while the vehicle group received intraperitoneal injections of saline as a control. Weekly assessments of hindlimb performance in the rat models were conducted using the Basso-Beattie-Bresnahan test (BBB) score and the horizontal ladder-walking test. Changes in scar components were identified through immunofluorescence staining, and an axonal regeneration assay was employed to evaluate regrowth under inhibitory conditions. RESULTS: The administration of MP led to a significant improvement in BBB scores compared to the control group at 7 days post-injury, although this improvement was not consistent. Furthermore, rats in the MP group did not demonstrate progressive improvement in horizontal ladder walking. Notably, there were no significant changes in the content of scar components in the injured area following MP treatment, and the axon length of neurons treated with MP did not exhibit significant extension compared to the vehicle group. CONCLUSIONS: Our findings indicate that the administration of MP does not effectively enhance hindlimb motor function or promote neuronal axon growth within a scarred environment after SCI.