Electroacupuncture blocked motor dysfunction and gut barrier damage by modulating intestinal NLRP3 inflammasome in MPTP-induced Parkinson's disease mice.

Parkinson's disease (PD) is a neurodegenerative disorder commonly accompanied by gut dysfunction. EA has shown anti-inflammatory and neuroprotective effects. Here, we aim to explore whether EA can treat Parkinson's disease by restoring the intestinal barrier and modulating NLRP3 inflammasome. We applied 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) to establish a PD mouse model and EA at the GV16, LR3, and ST36 for 12 consecutive days. The open-field test results indicated that EA alleviated depression and behavioral defects, upregulated the expressions of tyrosine hydroxylase (TH) and brain-derived neurotrophic factor (BDNF), and blocked the accumulation of α-synuclein (α-syn) in the midbrain. Moreover, EA blocked the damage to intestinal tissues of PD mice, indicative of suppressed NLRP3 inflammasome activation and increased gut barrier integrity. Notably, the antibiotic-treated mouse experiment validated that the gut microbiota was critical in alleviating PD dyskinesia and intestinal inflammation by EA. In conclusion, this study suggested that EA exhibited a protective effect against MPTP-induced PD by alleviating behavioral defects, reversing the block of motor dysfunction, and improving the gut barrier by modulating intestinal NLRP3 inflammasome. Above all, this study could provide novel insights into the pathogenesis and therapy of PD.

Overlooked interaction between redox-mediator and bisphenol-A in permanganate oxidation.

Research efforts on permanganate (Mn(VII)) combined with redox-mediator (RM), have received increasing attention due to their significant performance for bisphenol-A (BPA) removal. However, the mechanisms underpinning BPA degradation remain underexplored. Here we show the overlooked interactions between RM and BPA during permanganate oxidation by introducing an RM-N-hydroxyphthalimide (NHPI). We discovered that the concurrent generation of MnO2 and phthalimide-N-oxyl (PINO) radical significantly enhances BPA oxidation within the pH range of 5.0-6.0. The detection of radical cross-coupling products between PINO radicals and BPA or its derivatives corroborates the pivotal role of radical cross-coupling in BPA oxidation. Intriguingly, we observed the formation of an NHPI-BPA complex, which undergoes preferential oxidation by Mn(VII), marked by the emergence of an electron-rich domain in NHPI. These findings unveil the underlying mechanisms in the Mn(VII)/RM system and bridge the knowledge gap concerning BPA transformation via complexation. This research paves the way for further exploration into optimizing complexation sites and RM dosage, significantly enhancing the system's efficiency in water treatment applications.

Secular trend and projection of overweight and obesity among Chinese children and adolescents aged 7-18 years from 1985 to 2019: Rural areas are becoming the focus of investment.

BACKGROUND: The urban-rural disparities in overweight and obesity among children and adolescents are narrowing, and there is a need for long-term and updated data to explain this inequality, understand the underlying mechanisms, and identify priority groups for interventions. METHODS: We analyzed data from seven rounds of the Chinese National Survey on Students Constitution and Health (CNSSCH) conducted from 1985 to 2019, focusing on school-age children and adolescents aged 7-18 years. Joinpoint regression was used to identify inflection points (indicating a change in the trend) in the prevalence of overweight and obesity during the study period, stratified by urban/rural areas and sex. Annual percent change (APC), average annual percent change (AAPC), and 95% confidence interval (CI) were used to describe changes in the prevalence of overweight and obesity. Polynomial regression models were used to predict the prevalence of overweight and obesity among children and adolescents in 2025 and 2030, considering urban/rural areas, sex, and age groups. RESULTS: The prevalence of overweight and obesity in urban boys and girls showed an inflection point of 2000, with AAPC values of 10.09% (95% CI: 7.33-12.92%, t = 7.414, P <0.001) and 8.67% (95% CI: 6.10-11.30%, t = 6.809, P <0.001), respectively. The APC for urban boys decreased from 18.31% (95% CI: 4.72-33.67%, t = 5.926, P = 0.027) to 4.01% (95% CI: 1.33-6.75%, t = 6.486, P = 0.023), while the APC for urban girls decreased from 13.88% (95% CI: 1.82-27.38%, t = 4.994, P = 0.038) to 4.72% (95% CI: 1.43-8.12%, t = 6.215, P = 0.025). However, no inflection points were observed in the best-fit models for rural boys and girls during the period 1985-2019. The prevalence of overweight and obesity for both urban and rural boys is expected to converge at 35.76% by approximately 2027. A similar pattern is observed for urban and rural girls, with a prevalence of overweight and obesity reaching 20.86% in 2025. CONCLUSIONS: The prevalence of overweight and obesity among Chinese children and adolescents has been steadily increasing from 1985 to 2019. A complete reversal in urban-rural prevalence is expected by 2027, with a higher prevalence of overweight and obesity in rural areas. Urgent action is needed to address health inequities and increase investments, particularly policies targeting rural children and adolescents.

Multiomics Analysis Unravels Alteration in Molecule and Pathways Involved in Nondiabetic Chronic Wounds.

The prevalence of chronic wounds (CW) continues to grow. A thorough knowledge of the mechanism of CW formation remains elusive due to a lack of relevant studies. Furthermore, most previous studies concentrated on diabetic ulcers with relatively few investigations on other types. We performed this multiomics study to investigate the proteomic and metabolomic changes in wound and surrounding tissue from a cohort containing 13 patients with nondiabetic CW. Differentially expressed proteins (DEPs) and metabolites (DEMs) were filtered out and analyzed through multiomic profiling. The DEPs were further confirmed with the use of parallel reaction monitoring. Compared with the surrounding tissue, there were 82 proteins and 214 metabolites altered significantly in wound tissue. The DEPs were mainly enriched in focal adhesion (FA), extracellular matrix-receptor interaction (ERI), and the PI3K-Akt (PA) signaling pathway. Moreover, the DEMs were significantly enriched in amino sugar and nucleotide sugar metabolism and biosynthesis of nucleotide sugar pathways. In correlation analysis, we discovered that the PA signaling pathway, as well as its upstream and downstream pathways, coenriched some DEPs and DEMs. Additionally, we found that FBLN1, FBLN5, and EFEMP1 (FBLN3) proteins dramatically elevated in wound tissue and connected with the above signaling pathways. This multiomics study found that changes in FA, ERI, and PA signaling pathways had an impact on the cellular activities and functions of wound tissue cells. Additionally, increased expression of those proteins in wound tissue may inhibit vascular and skin cell proliferation and degrade the extracellular matrix, which may be one of the causes of CW formation.

Gender Differences in Prevalence and Associated Factors of Dyslipidemia in Initial-Treatment and Drug-Naïve Schizophrenia Patients.

Background: Dyslipidemia is frequently comorbid with schizophrenia (SCZ), and both conditions often demonstrate significant gender differences in their clinical features. This study specifically focuses on investigating the prevalence of dyslipidemia and the factors that contribute to it in initial-treatment and drug-naïve (ITDN) SCZ patients, specifically focusing on gender differences. Methods: A total of 224 male ITDN SCZ patients and 424 female ITDN SCZ patients were included in this study. Socio-demographic and general clinical data of the patients were collected, and routine biochemical parameters, such as lipid levels, fasting blood glucose, thyroid function, renal function, and blood cell counts, were measured. Patients were also assessed for psychopathology and disease severity using the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impression Scale - Severity of Illness (CGI-SI), respectively. In addition, a lipids score was calculated for assessing the severity of dyslipidemia. Results: The study revealed that the prevalence of dyslipidemia in male patients was 34.02% (83/224), whereas 33.25% (141/424) in females, indicating no statistically significant difference (χ2 = 0.04, p = 0.841). For males, the risk factors for dyslipidemia were high education levels and diastolic blood pressure (DBP), while red blood cell count (RBC) as a protective factor. Additionally, DBP was identified as a risk factor for dyslipidemia score. In females, systolic blood pressure (SBP) was identified as a risk factor for dyslipidemia, while being married and creatinine (CRE) levels were found to be protective factors. Moreover, SBP was revealed as a risk factor for dyslipidemia score. Conclusion: No significant gender differences were observed in the prevalence of dyslipidemia among the ITDN SCZ patients. However, notable gender differences were identified in the factors influencing dyslipidemia and its severity within this group. These findings suggest the necessity of implementing gender-specific interventions to address the potential risk factors associated with dyslipidemia.

Zn promoted GaZrOx ternary solid solution oxide combined with SAPO-34 effectively converts CO2 to light olefins with low CO selectivity.

We proposed a new strategy for CO2 hydrogenation to prepare light olefins by introducing Zn into GaZrOx to construct ZnGaZrOx ternary oxides, which was combined with SAPO-34 to prepare a high-performance ZnGaZrOx/SAPO-34 tandem catalyst for CO2 hydrogenation to light olefins. By optimizing the Zn doping content, the ratio and mode of the two-phase composite, and the process conditions, the 3.5%ZnGaZrOx/SAPO-34 tandem catalyst showed excellent catalytic performance and good high-temperature inhibition of the reverse water-gas shift (RWGS) reaction. The catalyst achieved 26.6% CO2 conversion, 82.1% C2=-C4= selectivity and 11.8% light olefins yield. The ZnGaZrOx formed by introducing an appropriate amount of Zn into GaZrOx significantly enhanced the spillover H2 effect and also induced the generation of abundant oxygen vacancies to effectively promote the activation of CO2. Importantly, the RWGS reaction was also significantly suppressed at high temperatures, with the CO selectivity being only 46.1% at 390°C.

Expandable-RCNN: toward high-efficiency incremental few-shot object detection.

This study aims at addressing the challenging incremental few-shot object detection (iFSOD) problem toward online adaptive detection. iFSOD targets to learn novel categories in a sequential manner, and eventually, the detection is performed on all learned categories. Moreover, only a few training samples are available for all sequential novel classes in these situations. In this study, we propose an efficient yet suitably simple framework, Expandable-RCNN, as a solution for the iFSOD problem, which allows online sequentially adding new classes with zero retraining of the base network. We achieve this by adapting the Faster R-CNN to the few-shot learning scenario with two elegant components to effectively address the overfitting and category bias. First, an IOU-aware weight imprinting strategy is proposed to directly determine the classifier weights for incremental novel classes and the background class, which is with zero training to avoid the notorious overfitting issue in few-shot learning. Second, since the above zero-retraining imprinting approach may lead to undesired category bias in the classifier, we develop a bias correction module for iFSOD, named the group soft-max layer (GSL), that efficiently calibrates the biased prediction of the imprinted classifier to organically improve classification performance for the few-shot classes, preventing catastrophic forgetting. Extensive experiments on MS-COCO show that our method can significantly outperform the state-of-the-art method ONCE by 5.9 points in commonly encountered few-shot classes.

Tumor-repopulating cells evade ferroptosis via PCK2-dependent phospholipid remodeling.

Whether stem-cell-like cancer cells avert ferroptosis to mediate therapy resistance remains unclear. In this study, using a soft fibrin gel culture system, we found that tumor-repopulating cells (TRCs) with stem-cell-like cancer cell characteristics resist chemotherapy and radiotherapy by decreasing ferroptosis sensitivity. Mechanistically, through quantitative mass spectrometry and lipidomic analysis, we determined that mitochondria metabolic kinase PCK2 phosphorylates and activates ACSL4 to drive ferroptosis-associated phospholipid remodeling. TRCs downregulate the PCK2 expression to confer themselves on a structural ferroptosis-resistant state. Notably, in addition to confirming the role of PCK2-pACSL4(T679) in multiple preclinical models, we discovered that higher PCK2 and pACSL4(T679) levels are correlated with better response to chemotherapy and radiotherapy as well as lower distant metastasis in nasopharyngeal carcinoma cohorts.

Machine learning for predicting halogen radical reactivity toward aqueous organic chemicalsl.

Rapid advances in machine learning (ML) provide fast, accurate, and widely applicable methods for predicting free radical-mediated organic pollutant reactivity. In this study, the rate constants (logk) of four halogen radicals were predicted using Morgan fingerprint (MF) and Mordred descriptor (MD) in combination with a series of ML models. The findings highlighted that making accurate predictions for various datasets depended on an effective combination of descriptors and algorithms. To further alleviate the challenge of limited sample size, we introduced a data combination strategy that improved prediction accuracy and mitigated overfitting by combining different datasets. The Light Gradient Boosting Machine (LightGBM) with MF and Random Forest (RF) with MD models based on the unified dataset were finally selected as the optimal models. The SHapley Additive exPlanations revealed insights: the MF-LightGBM model successfully captured the influence of electron-withdrawing/donating groups, while autocorrelation, walk count and information content descriptors in the MD-RF model were identified as key features. Furthermore, the important contribution of pH was emphasized. The results of the applicability domain analysis further supported that the developed model can make reliable predictions for query compounds across a broader range. Finally, a practical web application for logk calculations was built.

TFPI from erythroblasts drives heme production in central macrophages promoting erythropoiesis in polycythemia.

Bleeding and thrombosis are known as common complications of polycythemia for a long time. However, the role of coagulation system in erythropoiesis is unclear. Here, we discover that an anticoagulant protein tissue factor pathway inhibitor (TFPI) plays an essential role in erythropoiesis via the control of heme biosynthesis in central macrophages. TFPI levels are elevated in erythroblasts of human erythroblastic islands with JAK2V617F mutation and hypoxia condition. Erythroid lineage-specific knockout TFPI results in impaired erythropoiesis through decreasing ferrochelatase expression and heme biosynthesis in central macrophages. Mechanistically, the TFPI interacts with thrombomodulin to promote the downstream ERK1/2-GATA1 signaling pathway to induce heme biosynthesis in central macrophages. Furthermore, TFPI blockade impairs human erythropoiesis in vitro, and normalizes the erythroid compartment in mice with polycythemia. These results show that erythroblast-derived TFPI plays an important role in the regulation of erythropoiesis and reveal an interplay between erythroblasts and central macrophages.

Machine learning and deep learning to identifying subarachnoid haemorrhage macrophage-associated biomarkers by bulk and single-cell sequencing.

We investigated subarachnoid haemorrhage (SAH) macrophage subpopulations and identified relevant key genes for improving diagnostic and therapeutic strategies. SAH rat models were established, and brain tissue samples underwent single-cell transcriptome sequencing and bulk RNA-seq. Using single-cell data, distinct macrophage subpopulations, including a unique SAH subset, were identified. The hdWGCNA method revealed 160 key macrophage-related genes. Univariate analysis and lasso regression selected 10 genes for constructing a diagnostic model. Machine learning algorithms facilitated model development. Cellular infiltration was assessed using the MCPcounter algorithm, and a heatmap integrated cell abundance and gene expression. A 3 × 3 convolutional neural network created an additional diagnostic model, while molecular docking identified potential drugs. The diagnostic model based on the 10 selected genes achieved excellent performance, with an AUC of 1 in both training and validation datasets. The heatmap, combining cell abundance and gene expression, provided insights into SAH cellular composition. The convolutional neural network model exhibited a sensitivity and specificity of 1 in both datasets. Additionally, CD14, GPNMB, SPP1 and PRDX5 were specifically expressed in SAH-associated macrophages, highlighting its potential as a therapeutic target. Network pharmacology analysis identified some targeting drugs for SAH treatment. Our study characterised SAH macrophage subpopulations and identified key associated genes. We developed a robust diagnostic model and recognised CD14, GPNMB, SPP1 and PRDX5 as potential therapeutic targets. Further experiments and clinical investigations are needed to validate these findings and explore the clinical implications of targets in SAH treatment.

A Multi-view Molecular Pre-training with Generative Contrastive Learning.

Molecular representation learning can preserve meaningful molecular structures as embedding vectors, which is a necessary prerequisite for molecular property prediction. Yet, learning how to accurately represent molecules remains challenging. Previous approaches to learning molecular representations in an end-to-end manner potentially suffered information loss while neglecting the utilization of molecular generative representations. To obtain rich molecular feature information, the pre-training molecular representation model utilized different molecular representations to reduce information loss caused by a single molecular representation. Therefore, we provide the MVGC, a unique multi-view generative contrastive learning pre-training model. Our pre-training framework specifically acquires knowledge of three fundamental feature representations of molecules and effectively integrates them to predict molecular properties on benchmark datasets. Comprehensive experiments on seven classification tasks and three regression tasks demonstrate that our proposed MVGC model surpasses the majority of state-of-the-art approaches. Moreover, we explore the potential of the MVGC model to learn the representation of molecules with chemical significance.

Aberrant cortical morphology patterns are associated with cognitive impairment in patients with chronic heart failure.

A mounting body of evidences suggests that patients with chronic heart failure (HF) frequently experience cognitive impairments, but the neuroanatomical mechanism underlying these impairments remains elusive. In this retrospective study, 49 chronic HF patients and 49 healthy controls (HCs) underwent brain structural MRI scans and cognitive assessments. Cortical morphology index (cortical thickness, complexity, sulcal depth and gyrification) were evaluated. Correlations between cortical morphology and cognitive scores and clinical variables were explored. Logistic regression analysis was employed to identify risk factors for predicting 3-year major adverse cardiovascular events. Compared with HCs, patients with chronic HF exhibited decreased cognitive scores (p < .001) and decreased cortical thickness, sulcal depth and gyrification in brain regions involved cognition, sensorimotor, autonomic nervous system (family-wise error correction, all p values <.05). Notably, HF duration and New York Heart Association (NYHA) demonstrated negative correlations with abnormal cortex morphology, particularly HF duration and thickness in left precentral gyrus (r = -.387, p = .006). Cortical morphology characteristics exhibited positive associations with global cognition, particularly cortical thickness in left pars opercularis (r = .476, p < .001). NYHA class is an independent risk factor for adverse outcome (p = .001). The observed correlation between abnormal cortical morphology and global cognition suggested that cortical morphology may serve as a promising imaging biomarker and provide insights into neuroanatomical underpinnings of cognitive impairment in patients with chronic HF.

Photo-assisted natural chalcopyrite activated peracetic acid for efficient micropollutant degradation.

The effective activation of natural chalcopyrite (CuFeS2) on peracetic acid (PAA) to remove organic micropollutants was studied under visible light irradiation. Results showed than an effective sulfamethoxazole (SMX) degradation (95.0 %) was achieved under visible light irradiation for 30 min at pH 7.0. Quenching experiments, electron spin resonance analysis, and LC/MS spectrum demonstrated that HO• and CH3C(O)OO• were the main reactive species for SMX degradation, accounting for 43.3 % and 56.7 % of the contributions, respectively. Combined with X-ray photoelectron spectroscopy analysis, the photoelectrons generated on CuFeS2 activated by visible light enhanced the Fe3+/Fe2+ and Cu2+/Cu+ cycles on the surface, thereby activating PAA to generate HO•/CH3C(O)OO•. The removal rate of SMX decreased with the increase in wavelengths, due to the formation of low energy photons at longer wavelengths. Besides, the optimal pH for degradation of SMX by CuFeS2/PAA/Vis-LED process was neutral, which was attributed to the increasing easily activated anionic form of PAA during the increase in pH and the depletion of Fe species at alkaline conditions. Cl-, HCO3-, and HA slightly inhibited SMX degradation because of reactive species being quenched and/or shielding effect. Furthermore, the degradation efficiency of different pollutants by CuFeS2/PAA/Vis-LED was also measured, and the removal efficiency was different owing to the selectivity of CH3C(O)OO•. Finally, the process exhibited good applicability in real waters. Overall, this study provides new insight into visible light-catalyzed activation of PAA and suggests on further exploration of the intrinsic activation mechanism of PAA.

A neuron model with nonlinear membranes.

One-layer membrane separates the gradient field in and out of the cell, while some two-layer membranes filled with excitable media/material are important to regulate the energy flow when ions are propagated and diffused. The intracellular and extracellular media can be effectively separated by the membrane. It is important to clarify and describe the biophysical function and then the capacitive property can be reproduced in equivalent neural circuit. Here, we suggest the cell membrane has certain thickness and becomes flexible under external stimuli, therefore, it is considered as a kind of nonlinear media. To mimic the physical property of the two-layer cell membrane, a nonlinear resistor is used to connect two linear circuits, which is used to describe the electrical characteristic of two sides of the cell membrane, respectively. The combination of two linear circuits via a nonlinear resistor can describe the energy characteristic and firing mode in the flexible membrane of biophysical neurons. Circuit equations are defined and converted into equivalent nonlinear oscillator like a neuron. The voltage difference for the two capacitors can be consistent with the membrane potential for the neuron. The Hamilton energy function for this neuron can be mapped from the field energy in the electronic components, and it is also derived by using Helmholtz's theorem. The neuron can show similar spiking and bursting firing patterns, and uncertain diversity in membrane potentials is effective to support continuous firing patterns and mode transition under external stimulus. Furthermore, noisy disturbance is applied to induce coherence resonance. The results indicate that the lower coefficient variability and higher average energy level supports periodic firing in the neuron under coherence resonance. Therefore, this neuron model with nonlinear membranes (or two-layer form) is more suitable for identifying the biophysical property of biological neuron.

Low-dose IL-2 treatment confers anti-inflammatory effect against subarachnoid hemorrhage in mice.

Objective: Subarachnoid hemorrhage (SAH) was a stroke with high occurrence and mortality. At the early stage, SAH patients have severe cerebral injury which is contributed by inflammation. In this study, we aimed to explore the anti-inflammation effect of low-dose IL-2 in SAH mice. Methods: The 12-week-old C57BL/6J male mice were conducted with SAH surgery (Internal carotid artery puncture method). Different dose of IL-2 was injected intraperitoneally for 1 h, 1 day, and 2 days after SAH. Single-cell suspension and flow cytometry were used for the test of regulatory T (Treg) cells. Immunofluorescence staining was used to investigate the phenotypic polarization of microglia and inflammation response around neurons. Enzyme-Linked Immuno-sorbent Assay (ELISA) was applied to detect the level of pro-inflammatory factors. Results: Low-dose IL-2 could enrich the Treg cells and drive the microglia polarizing to M2. The level of pro-inflammatory factors, IL-1α, IL-6, and TNF-α decreased in the low-dose IL-2 group. The inflammation response around neurons was attenuated. Low-dose IL-2 could increase the number of Treg cells, which could exert a neuroprotective effect against inflammation after SAH. Conclusion: Low-dose IL-2 had the potential to be an effective clinical method to inhibit inflammation after SAH.

Vacuum-ultraviolet based advanced oxidation and reduction processes for water treatment.

The use of vacuum-ultraviolet (VUV) photolysis in water treatment has been gaining significant interest due to its efficacy in degrading refractory organic contaminants and eliminating oxyanions. In recent years, the reactive species driving pollutant decomposition in VUV-based advanced oxidation and reduction processes (VUV-AOPs and VUV-ARPs) have been identified. This review aims to provide a concise overview of VUV photolysis and its advancements in water treatment. We begin with an introduction to VUV irradiation, followed by a summary of the primary reactive species in both VUV-AOPs and VUV-ARPs. We then explore the factors influencing VUV-photolysis in water treatment, including VUV irradiation dose, catalysts or activators, dissolved gases, water matrix components (e.g., DOM and inorganic anions), and solution pH. In VUV-AOPs, the predominant reactive species are hydroxyl radicals (˙OH), hydrogen peroxide (H2O2), and ozone (O3). Conversely, in VUV-ARPs, the main reactive species are the hydrated electron (eaq-) and hydrogen atom (˙H). It is worth noting that VUV-based advanced oxidation/reduction processes (VUV-AORPs) can transit between VUV-AOPs and VUV-ARPs based on the externally added chemicals and dissolved gases in the solution. Increase of the VUV irradiation dose and the concentration of catalysts/activators enhances the degradation of contaminants, whereas DOM and inorganic anions inhibit the reaction. The pH influences the redox potential of ˙OH, the speciation of contaminants and activators, and thus the overall performance of the VUV-AOPs. Conversely, an alkaline pH is favored in VUV-ARPs because eaq- predominates at higher pH.

ROS-responsive nanoparticle delivery of ferroptosis inhibitor prodrug to facilitate mesenchymal stem cell-mediated spinal cord injury repair.

Spinal cord injury (SCI) is a traumatic condition that results in impaired motor and sensory function. Ferroptosis is one of the main causes of neural cell death and loss of neurological function in the spinal cord, and ferroptosis inhibitors are effective in reducing inflammation and repairing SCI. Although human umbilical cord mesenchymal stem cells (Huc-MSCs) can ameliorate inflammatory microenvironments and promote neural regeneration in SCI, their efficacy is greatly limited by the local microenvironment after SCI. Therefore, in this study, we constructed a drug-release nanoparticle system with synergistic Huc-MSCs and ferroptosis inhibitor, in which we anchored Huc-MSCs by a Tz-A6 peptide based on the CD44-targeting sequence, and combined with the reactive oxygen species (ROS)-responsive drug nanocarrier mPEG-b-Lys-BECI-TCO at the other end for SCI repair. Meanwhile, we also modified the classic ferroptosis inhibitor Ferrostatin-1 (Fer-1) and synthesized a new prodrug Feborastatin-1 (Feb-1). The results showed that this treatment regimen significantly inhibited the ferroptosis and inflammatory response after SCI, and promoted the recovery of neurological function in rats with SCI. This study developed a combination therapy for the treatment of SCI and also provides a new strategy for the construction of a drug-coordinated cell therapy system.

Placental inflammatory injury induced by chlorinated polyfluorinated ether sulfonate (F-53B) through NLRP3 inflammasome activation.

Chlorinated polyfluorinated ether sulfonate, commercially known as F-53B, has been associated with adverse birth outcomes. However, the reproductive toxicology of F-53B on the placenta remains poorly understood. To address this gap, we examined the impact of F-53B on placental injury and its underlying molecular mechanisms in vivo. Pregnant C57BL/6 J female mice were randomly allocated to three groups: the control group, F-53B 0.8 µg/kg/day group, and F-53B 8 µg/kg/day group. After F-53B exposure through free drinking water from gestational day (GD) 0.5-14.5, the F-53B 8 µg/kg/day group exhibited significant increases in placental weights and distinctive histopathological alterations, including inflammatory cell infiltration, heightened syncytiotrophoblast knots, and a loosened trophoblastic basement membrane. Within the F-53B 8 µg/kg/day group, placental tissue exhibited increased apoptosis, as indicated by increased caspase3 activation. Furthermore, F-53B potentially induced the NF-κB signaling pathway activation through IκB-α phosphorylation. Subsequently, this activation upregulated the expression of inflammatory cytokines and components of the NLRP3 inflammasome, including activated caspase1, IL-1ß, IL-18, and cleaved gasdermin D (GSDMD), ultimately leading to pyroptosis in the mouse placenta. Our findings reveal a pronounced inflammatory injury in the placenta due to F-53B exposure, suggesting potential reproductive toxicity at concentrations relevant to the human population. Further toxicological and epidemiological investigations are warranted to conclusively assess the reproductive health risks posed by F-53B.

Highly reversible zinc metal anode enabled by strong Brønsted acid and hydrophobic interfacial chemistry.

Uncontrollable zinc (Zn) plating and hydrogen evolution greatly undermine Zn anode reversibility. Previous electrolyte designs focus on suppressing H2O reactivity, however, the accumulation of alkaline byproducts during battery calendar aging and cycling still deteriorates the battery performance. Here, we present a direct strategy to tackle such problems using a strong Brønsted acid, bis(trifluoromethanesulfonyl)imide (HTFSI), as the electrolyte additive. This approach reformulates battery interfacial chemistry on both electrodes, suppresses continuous corrosion reactions and promotes uniform Zn deposition. The enrichment of hydrophobic TFSI- anions at the Zn|electrolyte interface creates an H2O-deficient micro-environment, thus inhibiting Zn corrosion reactions and inducing a ZnS-rich interphase. This highly acidic electrolyte demonstrates high Zn plating/stripping Coulombic efficiency up to 99.7% at 1 mA cm-2 ( > 99.8% under higher current density and areal capacity). Additionally, Zn | |ZnV6O9 full cells exhibit a high capacity retention of 76.8% after 2000 cycles.