Regulating Protons to Tailor the Enol Conversion of Quinone for High-Performance Aqueous Zinc Batteries.

Quinone-based electrodes using carbonyl redox reactions are promising candidates for aqueous energy storage due to their high theoretical specific capacity and high-rate performance. However, the proton storage manners and their influences on the electrochemical performance of quinone are still not clear. Herein, we reveal that proton storage could determine the products of the enol conversion and the electrochemical stability of the organic electrode. Specifically, the protons preferentially coordinated with the prototypical pyrene-4,5,9,10-tetraone (PTO) cathode, and increasing the proton concentration in the electrolyte can improve its working potentials and cycling stability by tailoring the enol conversion reaction. We also found that exploiting Al2(SO4)3 as a pH buffer can increase the energy density of the Zn||PTO batteries from 242.8 to 284.6 Wh kg-1. Our research has a guiding significance for emphasizing proton storage of organic electrodes based on enol conversion reactions and improving their electrochemical performance.

Asymmetric Synthesis and Biological Evaluation of Platensilin, Platensimycin, Platencin, and Their Analogs via a Bioinspired Skeletal Reconstruction Approach.

Platensilin, platensimycin, and platencin are potent inhibitors of ß-ketoacyl-acyl carrier protein synthase (FabF) in the bacterial and mammalian fatty acid synthesis system, presenting promising drug leads for both antibacterial and antidiabetic therapies. Herein, a bioinspired skeleton reconstruction approach is reported, which enables the unified synthesis of these three natural FabF inhibitors and their skeletally diverse analogs, all stemming from a common ent-pimarane core. The synthesis features a diastereoselective biocatalytic reduction and an intermolecular Diels-Alder reaction to prepare the common ent-pimarane core. From this intermediate, stereoselective Mn-catalyzed hydrogen atom-transfer hydrogenation and subsequent Cu-catalyzed carbenoid C-H insertion afford platensilin. Furthermore, the intramolecular Diels-Alder reaction succeeded by regioselective ring opening of the newly formed cyclopropane enables the construction of the bicyclo[3.2.1]-octane and bicyclo[2.2.2]-octane ring systems of platensimycin and platencin, respectively. This skeletal reconstruction approach of the ent-pimarane core facilitates the preparation of analogs bearing different polycyclic scaffolds. Among these analogs, the previously unexplored cyclopropyl analog 47 exhibits improved antibacterial activity (MIC80 = 0.0625 µg/mL) against S. aureus compared to platensimycin.

Prediction and Interpretation Microglia Cytotoxicity by Machine Learning.

Ameliorating microglia-mediated neuroinflammation is a crucial strategy in developing new drugs for neurodegenerative diseases. Plant compounds are an important screening target for the discovery of drugs for the treatment of neurodegenerative diseases. However, due to the spatial complexity of phytochemicals, it becomes particularly important to evaluate the effectiveness of compounds while avoiding the mixing of cytotoxic substances in the early stages of compound screening. Traditional high-throughput screening methods suffer from high cost and low efficiency. A computational model based on machine learning provides a novel avenue for cytotoxicity determination. In this study, a microglia cytotoxicity classifier was developed using a machine learning approach. First, we proposed a data splitting strategy based on the molecule murcko generic scaffold, under this condition, three machine learning approaches were coupled with three kinds of molecular representation methods to construct microglia cytotoxicity classifier, which were then compared and assessed by the predictive accuracy, balanced accuracy, F1-score, and Matthews Correlation Coefficient. Then, the recursive feature elimination integrated with support vector machine (RFE-SVC) dimension reduction method was introduced to molecular fingerprints with high dimensions to further improve the model performance. Among all the microglial cytotoxicity classifiers, the SVM coupled with ECFP4 fingerprint after feature selection (ECFP4-RFE-SVM) obtained the most accurate classification for the test set (ACC of 0.99, BA of 0.99, F1-score of 0.99, MCC of 0.97). Finally, the Shapley additive explanations (SHAP) method was used in interpreting the microglia cytotoxicity classifier and key substructure smart identified as structural alerts. Experimental results show that ECFP4-RFE-SVM have reliable classification capability for microglia cytotoxicity, and SHAP can not only provide a rational explanation for microglia cytotoxicity predictions, but also offer a guideline for subsequent molecular cytotoxicity modifications.

Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution.

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 µg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 µg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

Natural anti-neuroinflammatory inhibitors in vitro and in vivo from Aglaia odorata.

Fifty compounds including seven undescribed (1, 13, 18-20, 30, 31) and forty-three known (2-12, 14-17, 21-29, 32-50) ones were isolated from the extract of the twigs and leaves of Aglaia odorata with anti-neuroinflammatory activities. Their structures were determined by a combination of spectral analysis and calculated spectra (ECD and NMR). Among them, compounds 13-25 were found to possess tertiary amide bonds, with compounds 16, 17, and 19-21 existing detectable cis/trans mixtures in 1H NMR spectrum measured in CDCl3. Specifically, the analysis of the cis-trans isomerization equilibrium of tertiary amides in compounds 19-24 was conducted using NMR spectroscopy and quantum chemical calculations. Bioactivity evaluation showed that the cyclopenta[b]benzofuran derivatives (2-6, 8, 10, 12) could inhibit nitric oxide production at the nanomolar concentration (IC50 values ranging from 2 to 100 nM) in lipopolysaccharide-induced BV-2 cells, which were 413-20670 times greater than that of the positive drug (minocycline, IC50 = 41.34 µM). The cyclopenta[bc]benzopyran derivatives (13-16), diterpenoids (30-35), lignan (40), and flavonoids (45, 47, 49, 50) also demonstrated significant inhibitory activities with IC50 values ranging from 1.74 to 38.44 µM. Furthermore, the in vivo anti-neuroinflammatory effect of rocaglaol (12) was evaluated via immunofluorescence, qRT-PCR, and western blot assays in the LPS-treated mice model. The results showed that rocaglaol (12) attenuated the activation of microglia and decreased the mRNA expression of iNOS, TNF-α, IL-1ß, and IL-6 in the cortex and hippocampus of mice. The mechanistic study suggested that rocaglaol might inhibit the activation of the NF-κB signaling pathway to relieve the neuroinflammatory response.

Characteristic terpenylated coumarins from Ferula ferulaeoides as potential inhibitors on overactivation of microglia.

A total of 37 characteristic terpenylated coumarins (1-25), including 17 undescribed compounds (1-5, 6a/6b, 7-10, 11a/11b-13a/13b), have been isolated from the root of Ferula ferulaeoides. Meanwhile, twelve pairs of enantiomers (6a/6b, 11a/11b-15a/15b, 17a/17b, 18a/18b, 20a/20b-22a/22b, and 25a/25b) were chirally purified. The structures of these new compounds were elucidated using HRESIMS, UV, NMR, and calculated 13C NMR with a custom DP4 + analysis. The absolute configurations of all the compounds were determined for the first time using electronic circular dichroism (ECD). Then, their inhibitory effects on nitric oxide (NO) production were evaluated with LPS-induced BV-2 microglia. Compared with the positive control minocycline (IC50 = 59.3 µM), ferulaferone B (2) exhibited stronger inhibitory potency with an IC50 value of 12.4 µM. The immunofluorescence investigation indicated that ferulaferone B (2) could inhibit Iba-1 expression in LPS-stimulated BV-2 microglia.

Axially chiral dihydrophenanthrene dimers from Pholidota yunnanensis with anti-neuroinflammatory activities.

Axially chiral compounds are well known in medicinal chemistry of natural products, but their absolute configurations and bioactivities are rarely reported and studied. In this study, eleven undescribed axially chiral dihydrophenanthrene dimers, as well as twenty-five known dihydrophenanthrenes, were isolated from the entire plant of Pholidota yunnanensis. Their structures were elucidated by comprehensive spectroscopic analysis. A method for determining the absolute configurations of enantiomers was developed based on the rotational barriers and calculated ECD spectra. Additionally, the activities of all isolated compounds were assessed in LPS-induced BV-2 microglial cells. Most dihydrophenanthrenes exhibited significant NO inhibitory activities, and compound 7 showed the most potent inhibitory effect with an IC50 value of 1.5 µM, compared to the positive control minocycline. The immunofluorescence and western blot results revealed that compound 7 suppressed the expression of Iba-1, iNOS and COX-2 in LPS-stimulated BV-2 microglial cells.

Ionizing radiation induces neurotoxicity in Xenopus laevis embryos through neuroactive ligand-receptor interaction pathway.

Ionizing radiation (IR) poses a significant threat to both the natural environment and biological health. Exposure to specific doses of ionizing radiation early in an organism's development can lead to developmental toxicity, particularly neurotoxicity. Through experimentation with Xenopus laevis (X. laevis), we examined the effects of radiation on early developmental stage. Our findings revealed that radiation led to developmental abnormalities and mortality in X. laevis embryos in a dose-dependent manner, disrupting redox homeostasis and inducing cell apoptosis. Additionally, radiation caused neurotoxic effects, resulting in abnormal behavior and neuron damage in the embryos. Further investigation into the underlying mechanisms of radiation-induced neurotoxicity indicated the potential involvement of the neuroactive ligand-receptor interaction pathway, which was supported by RNA-Seq analysis. Validation of gene expression associated with this pathway and analysis of neurotransmitter levels confirmed our hypothesis. In addition, we further validated the important role of this signaling pathway in radiation-induced neurotoxicity through edaravone rescue experiments. This research establishes a valuable model for radiation damage studying and provides some insight into radiation-induced neurotoxicity mechanisms.

The efficacy of exercise training for improving body composition in patients with breast cancer: A systematic review and meta-analysis of randomized controlled trials.

OBJECTIVES: To evaluate the efficacy of exercise in improving body composition in patients with breast cancer; the effects of exercise on weight and BMI were evaluated as secondary outcomes. DATA SOURCES: Cochrane Library, EMBASE, PubMed and Web of Science were searched for randomized controlled trials published in English from database inception to 29 November 2023. METHODS: The effects of exercise on body composition in patients with breast cancer were explored. After separately extracting the data, two reviewers assessed the overall quality of the evidence as well as the methodological quality of the included studies. RESULTS: Fourteen studies with 1241 participants were included, of which 12 studies were eligible for meta-analysis. Exercise significantly reduced body fat (mean difference [MD], -0.33; 95% CI, -0.37 to -0.29; P < 0.00001) and increased lean mass (MD, 0.42; 95% CI, 0.34 to 0.49; P < 0.00001) in patients with breast cancer. Further, exercise intervention was associated with increased BMI of patients with breast cancer (MD, 0.03; 95% CI, 0.01 to 0.06; P = 0.01), while no significant difference in weight was detected between the exercise and the non-exercise groups. Subgroup analysis results showed that only resistance exercise reduced fat mass (MD, -0.22; 95% CI, -0.27 to -0.16; P < 0.00001). CONCLUSIONS: Exercise effectively improves body composition in patients with breast cancer. Clinicians should encourage patients to engage in exercise and develop optimized exercise prescriptions.

Tamarixetin ameliorates cerebral ischemia-reperfusion injury via suppressing nicotinamide adenine dinucleotide phosphate oxidase 2/nucleotide-binding oligomerization domain like receptor family pyrin domain-containing 3 inflammasome activation.

Tamarixetin, a natural dietary flavone, exhibits remarkable potential for the treatment of ischemic stroke. The present article aimed to explore the impact of tamarixetin on ischemic stroke and elucidate the underlying mechanisms. Effects of tamarixetin on ischemic stroke were evaluated in rats using the middle cerebral artery occlusion and reperfusion (MCAO/R) model, by assessing the neurological deficit scores, brain water content, brain infraction, and neuronal damage. The levels of proinflammatory cytokines, NLRP3 inflammasome activation, reactive oxygen species (ROS) production, and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase expression were measured in MCAO/R rats and lipopolysaccharide-stimulated cells. Tamarixetin administration improved the neurological dysfunction and neuronal loss in MCAO/R rats. In addition, tamarixetin reduced microglial hyperactivation and proinflammatory cytokines expression in vivo and in vitro. Tamarixetin attenuated NF-κB p65 phosphorylation and promoter activity, reduced NLRP3 expression and caspase-1 cleavage, and downregulated IL-1ß and IL-18 secretions to suppress NLRP3 inflammasome activation. The levels of superoxide anion, hydrogen peroxide, and ROS were also suppressed by tamarixetin. The downregulation of NADP+ and NADPH levels, and gp91phox expression indicated the ameliorative effects of tamarixetin on NADPH oxidase activation. In the gp91phox knockdown cells treated with lipopolysaccharide, the effects of tamarixetin on NADPH oxidase activation, ROS generation, and NLRP3 inflammasome activation were diminished. Moreover, tamarixetin protects neurons against microglial hyperactivation in vitro. Our findings support the potential of tamarixetin as a therapeutic agent for ischemic stroke, and its mechanism of action involves the inhibition of NADPH oxidase-NLRP3 inflammasome signaling.

Sesquiterpenes from Wikstroemia lungtzeensis with anti-neuroinflammatory effects.

An anti-neuroinflammatory activities-guided phytochemical research of Wikstroemia lungtzeensis was performed for the first time. Three undescribed carotane-type sesquiterpenes, excoecafolinols C-E (1-3), and nine known sesquiterpene derivatives were isolated from the effective ethyl acetate extract of W. lungtzeensis. Their structures were determined based on multiple spectroscopic techniques and electronic circular dichroism (ECD) spectra. Furthermore, the anti-neuroinflammatory activities of the identified compounds were evaluated in lipopolysaccharide-stimulated BV-2 cells. Among them, six components (1, 2, 4, 7, 11, 12) exhibited significant inhibitory effects on nitric oxide (NO) production, with IC50 values ranging from 10.48 to 49.41 µM (positive control minocycline, IC50 53.20 µM). Carotane-type sesquiterpenes (1, 2, 4) with high content and significant inhibitory effects, are considered to be major active ingredients of W. lungtzeensis, which might serve as potential therapeutic agents for neurodegenerative diseases.

Phase Engineering of High-Entropy Alloy for Enhanced Electrocatalytic Nitrate Reduction to Ammonia.

Directly electrochemical conversion of nitrate (NO3 -) is an efficient and environmentally friendly technology for ammonia (NH3) production but is challenged by highly selective electrocatalysts. High-entropy alloys (HEAs) with unique properties are attractive materials in catalysis, particularly for multi-step reactions. Herein, we first reported the application of HEA (FeCoNiAlTi) for electrocatalytic NO3 - reduction to NH3 (NRA). The bulk HEA is active for NRA but limited by the unsatisfied NH3 yield of 0.36 mg h-1 cm-2 and Faradaic efficiency (FE) of 82.66 %. Through an effective phase engineering strategy, uniform intermetallic nanoparticles are introduced on the bulk HEA to increase electrochemical active surface area and charge transfer efficiency. The resulting nanostructured HEA (n-HEA) delivers enhanced electrochemical NRA performance in terms of NH3 yield (0.52 mg h-1 cm-2) and FE (95.23 %). Further experimental and theoretical investigations reveal that the multi-active sites (Fe, Co, and Ni) dominated electrocatalysis for NRA over the n-HEA. Notably, the typical Co sites exhibit the lowest energy barrier for NRA with *NH2 to *NH3as the rate-determining step.

Tellurium with Reversible Six-Electron Transfer Chemistry for High-Performance Zinc Batteries.

Chalcogens, especially tellurium (Te), as conversion-type cathodes possess promising prospects for zinc batteries (ZBs) with potential rich valence supply and high energy density. However, the conversion reaction of Te is normally restricted to the Te2-/Te0 redox with a low voltage plateau at ∼0.59 V (vs Zn2+/Zn) rather than the expected positive valence conversion of Te0 to Ten+, inhibiting the development of Te-based batteries toward high output voltage and energy density. Herein, the desired reversible Te2-/Te0/Te2+/Te4+ redox behavior with up to six-electron transfer was successfully activated by employing a highly concentrated Cl--containing electrolyte (Cl- as strong nucleophile) for the first time. Three flat discharge plateaus located at 1.24, 0.77, and 0.51 V, respectively, are attained with a total capacity of 802.7 mAh g-1. Furthermore, to improve the stability of Ten+ products and enhance the cycling stability, a modified ionic liquid (IL)-based electrolyte was fabricated, leading to a high-performance Zn∥Te battery with high areal capacity (7.13 mAh cm-2), high energy density (542 Wh kgTe-1 or 227 Wh Lcathdoe+anode-1), excellent cycling performance, and a low self-discharge rate based on 400 mAh-level pouch cell. The results enhance the understanding of tellurium chemistry in batteries, substantially promising a remarkable route for advanced ZBs.

Clinical characterization of familial 1p36.3 microduplication.

Unlike the 1p36 microdeletion syndrome, which has been extensively described, 1p36.3 microduplications have rarely been reported. We report the two siblings of familial 1p36.3 microduplication, presenting with a severe global developmental delay, epilepsy, and a few dysmorphic features. They were referred to moderate-to-severe developmental delay (DD) and intellectual disability (ID). Both were considered eyelid myoclonus with absence of epilepsy (Jeavons syndrome). The EEG is characterized by widespread 2.5-3.5 Hz spikes and spike slow complex wave, eye closure sensitivity, and photosensitivity. The children has same dysmorphic features, including mild bitemporal narrowing and sloping forehead, sparse eyebrows, hypertelorism, ptosis, strabismus, infraorbital creases, wide nasal bridge with bulbous nasal tip, dystaxia, hallux valgus, and flat feet. Family exome sequencing revealed a maternally inherited 3.2-Mb microduplication of chromosomal band 1p36.3p36.2. However, DNA purified from blood samples of either parent did not find evidence for a microduplication of 1p36 in somatic tissue, indicating that such a mutation might be carried in the germline of the parents as gonadal mosaicism. No other family members of the affected siblings' parents were reported to be affected by the symptoms found.

Ring-Oven-Assisted In Situ Synthesis of Metal-Organic Frameworks on the Lab-On-Paper Device for Chemiluminescence Detection of Nitrite in Whole Blood.

In situ synthesis of metal-organic frameworks (MOFs) on flexible materials for the fabrication of functional platforms and micro-devices is challenging. The time-/precursor-consuming procedure and uncontrollable assembly are stumbling blocks for constructing this platform. Herein, a novel in situ MOF synthesis method on paper substrates by use of the ring-oven-assisted technique was reported. Utilizing the ring-oven's heating and washing function, MOFs can be synthesized in 30 min on the designated position of paper chips with extremely low-volume precursors. The principle of this method was explained by steam condensation deposition. The MOFs' growth procedure was theoretically calculated by crystal sizes and the results conformed to the Christian equation. As different MOFs (Cu-MOF-74, Cu-BTB, Cu-BTC) can be synthesized successfully on paper-based chips, the ring-oven-assisted in situ synthesis method has great generality. Then, the prepared Cu-MOF-74 loading paper-based chip was applied to the chemiluminescence (CL) detection of nitrite (NO2-), based on the catalysis effect of Cu-MOF-74 on the NO2--H2O2 CL system. Also, by the delicate design of the paper-based chip, NO2- can be detected with the detection limit (DL) of 0.5 nM in whole blood samples without sample pretreatment. This work establishes a distinctive method for the in situ synthesis of MOFs and the application of MOFs on paper-based CL chips.

Tetrakis(4-pyridylphenyl)ethylene-based Zinc Metal-Organic Framework with Aggregation-Induced Chemiluminescence Emission on a Paper Platform for Formaldehyde Detection in Breath.

Volatile formaldehyde (FA) in exhaled breath (EB) is considered as a biomarker for lung cancer (LC). On-the-spot selective and sensitive detection of gaseous FA is rather important for LC screening and diagnosis. Herein, a tetrakis(4-pyridylphenyl)ethylene (Py-TPE)-based zinc metal-organic framework (MOF) with excellent aggregation-induced emission (AIE) property was utilized for absorption and selective detection of FA in EB. The porous Zn-Py-TPE served as a gaseous confinement cavity for the adsorption of FA in EB. Interestingly, Zn-Py-TPE was aggregated on paper, and then aggregation-induced chemiluminescence (CL) emission can be triggered by only adding bis(2,4,6-trichlorophenyl)oxalate (TCPO). Though without H2O2, the CL of Zn-Py-TPE-TCPO was enhanced greatly by FA. FA promoted the aggregation of Zn-Py-TPE on paper by forming halogen bonding between FA and Zn-Py-TPE, which contributed to the better selectivity. FA can also stimulate the production of more singlet oxygen (1O2) in the Zn-Py-TPE-TCPO CL system. Hence, FA could be detected via the proposed Zn-Py-TPE-TCPO system with a quantification linear range of 1.0-100.0 ppb and detection limit of 0.3 ppb. This portable, low-cost, and sensitive paper-based platform can achieve trace FA detection in EB and is expected to provide an on-the-spot screening platform for lung cancer.

Mutational profiling of circulating tumor DNA and clinical characteristics in lymphoma: Based on next generation sequencing.

Liquid biopsy has been experimented with to identify the mutation of lymphoma based on next-generation sequencing (NGS). We applied NGS analysis to circulating tumor DNA (ctDNA) in 20 lymphoma patients. Then, we compared treatment outcomes, and clinical characteristics among these patients, then investigated mutational profiling. Two independent cohorts of 241 patients with mature B cell lymphoma in Mature B-cell malignancies data set (MBN) data set and 50 diffuse large B-cell lymphoma (DLBCL) patients in DLBCL data set, were used to examine the association between gene mutations and prognosis. We found ctDNA positive group had significantly more relapsed/PD (7/12, 58.3%) and less CR/PR patients (1/12, 8.3%) compared to negative group (0, 0%) (5/8, 62.5%) (p < 0.001). Somatic alterations were identified in 12 of 20 patients and the total 11 mutations were: Ataxia telangiectasia mutated (ATM), TP53, BCL2, BTG2, CD28, EP300, IDH2, IRF8, JAK3, NOTCH1, and NRAS. ATM (S2168L) was found in SLL and TLBL for the first time. BTG2 (c.292_293del), CD28 (P119T), IRF8 (E74D) and NOTCH1 (c.4348 G > A) were newly detected in DLBCL, angioimmunoblastic T-cell lymphoma, primary central nervous system lymphoma, and BCL for the first time respectively. We also disclosed an unreported mutation EP300 (c.1058_1059insC) in DLBCL. Our cases implied ctDNA detection consistent with the FISH of tissue samples to some extent, speculating new molecular subtypes of DLBCL, finding some potential drug-resistant mutations, and suggesting disease recurrence. Moreover, in MBN and DLBCL datasets, patients with TP53 mutation had a significantly shorter OS (all p < 0.05) in both circulating free DNA and tumor tissue. The mutations (no SNP) of NOTCH1 (all p < 0.05) significantly contributed to worse OS in the two cohorts.

WTAP dysregulation-mediated HMGN3-m6A modification inhibited trophoblast invasion in early-onset preeclampsia.

Early-onset preeclampsia (ePE) originates from abnormal implantation and placentation that involves trophoblast invasion, but its pathophysiology is not entirely understood. N6-methyladenosine (m6A) regulators mediate the progression of various cancers. The invasiveness of trophoblast cells is similar to that of tumor cells. However, little is known regarding the potential role of m6A modification in ePE and the underlying mechanism. This study aimed to explore the m6A level in placental tissue samples collected from ePE patients and to investigate whether m6A modification was an essential part of PE pathogenesis. The m6A level in placental tissue samples of 80 PE participants was examined. MeRIP-microarray, RNA-Seq, luciferase reporter assay, and RNA immunoprecipitation chip (RIP) assay were performed. The m6A level in the ePE group was significantly reduced compared with the control group. Wilms' tumor 1-associating protein (WTAP) regulated trophoblast cell migration and invasion. Mechanistically, the high mobility group nucleosomal binding domain 3 (HMGN3) gene was a target gene of WTAP in trophoblast (p < .05). WTAP enhanced the stability of HMGN3 mRNA through binding with its 3'-UTR m6A site(+485A, +522A). HMGN3 was recognized by m6A recognition protein insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), which was inhibited when knocking down WTAP. Both m6A and WTAP levels were downregulated in ePE. The m6A modification mediated by WTAP/IGF2BP1/HMGN3 axis might contribute to abnormal trophoblast invasion. Our work provided a foundation for further exploration of RNA epigenetic regulatory patterns in ePE, and indicated a new treatment strategy for ePE.

Introduction to 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Transportation infrastructures, including roads, bridges, tunnels, stations, airports and subways, play fundamental roles in modern society. Engineering failures of transportation infrastructures may result in significant damage to the public. The traditional methods are to monitor, store and analyse the information during the infrastructure and material design, testing, construction, numerical simulations, evaluation, operation, maintenance and preservation, using mechanistic-based, material-based and statistics-based approaches. In recent decades, artificial intelligence (AI) has drawn the attention of many researchers and has been used as a powerful tool to understand and analyse the engineering failures in transportation infrastructure and materials. AI has the advantages of conveniently characterizing infrastructure materials in multi-scale, extracting failure information from images and cloud points, evaluating performance from the signals of sensors, predicting the long-term performance of infrastructure based on big data and optimizing infrastructure maintenance strategies, etc. In the future, AI techniques will be more effective and promising for data collection, transmission, fusion, mining and analysis, which will help engineers quickly detect, analyse and finally prevent the engineering failures of transportation infrastructure and materials. This theme issue presents the latest developments of AI in failure analysis of transportation infrastructure and materials. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.

Automatic pavement texture recognition using lightweight few-shot learning.

Texture is a crucial characteristic of roads, closely related to their performance. The recognition of pavement texture is of great significance for road maintenance professionals to detect potential safety hazards and carry out necessary countermeasures. Although deep learning models have been applied for recognition, the scarcity of data has always been a limitation. To address this issue, this paper proposes a few-shot learning model based on the Siamese network for pavement texture recognition with a limited dataset. The model achieved 89.8% accuracy in a four-way five-shot task classifying the pavement textures of dense asphalt concrete, micro surface, open-graded friction course and stone matrix asphalt. To align with engineering practice, global average pooling (GAP) and one-dimensional convolution are implemented, creating lightweight models that save storage and training time. Comparative experiments show that the lightweight model with GAP implemented on dense layers and one-dimensional convolution on convolutional layers reduced storage volume by 94% and training time by 99%, despite a 2.9% decrease in classification accuracy. Moreover, the model with only GAP implemented on dense layers achieved the highest accuracy at 93.5%, while reducing storage volume and training time by 83% and 6%, respectively. This article is part of the theme issue 'Artificial intelligence in failure analysis of transportation infrastructure and materials'.