Photoaffinity probe-based antimalarial target identification of artemisinin in the intraerythrocytic developmental cycle of Plasmodium falciparum.

Malaria continues to pose a serious global health threat, and artemisinin remains the core drug for global malaria control. However, the situation of malaria resistance has become increasingly severe due to the emergence and spread of artemisinin resistance. In recent years, significant progress has been made in understanding the mechanism of action (MoA) of artemisinin. Prior research on the MoA of artemisinin mainly focused on covalently bound targets that are alkylated by artemisinin-free radicals. However, less attention has been given to the reversible noncovalent binding targets, and there is a paucity of information regarding artemisinin targets at different life cycle stages of the parasite. In this study, we identified the protein targets of artemisinin at different stages of the parasite's intraerythrocytic developmental cycle using a photoaffinity probe. Our findings demonstrate that artemisinin interacts with parasite proteins in vivo through both covalent and noncovalent modes. Extensive mechanistic studies were then conducted by integrating target validation, phenotypic studies, and untargeted metabolomics. The results suggest that protein synthesis, glycolysis, and oxidative homeostasis are critically involved in the antimalarial activities of artemisinin. In summary, this study provides fresh insights into the mechanisms underlying artemisinin's antimalarial effects and its protein targets.

Large-Scale Synthesis of High-Loading Single Metallic Atom Catalysts by a Metal Coordination Route.

Single atom catalyst (SAC) is one of the most efficient and versatile catalysts with well-defined active sites. However, its facile and large-scale preparation, the prerequisite of industrial applications, has been very challenging. This dilemma originates from the Gibbs-Thomson effect, which renders it rather difficult to achieve high single atom loading (< 3 mol%). Further, most synthesizing procedures are quite complex, resulting in significant mass loss and thus low yields. Herein, a novel metal coordination route is developed to address these issues simultaneously, which is realized owing to the rapid complexation between ligands (e.g., biuret) and metal ions in aqueous solutions and subsequent in situ polymerization of the formed complexes to yield SACs. The whole preparation process involves only one heating step operated in air without any special protecting atmospheres, showing general applicability for diverse transition metals. Take Cu SAC for an example, a record yield of up to 3.565 kg in one pot and an ultrahigh metal loading 16.03 mol% on carbon nitride (Cu/CN) are approached. The as-prepared SACs are demonstrated to possess high activity, outstanding selectivity, and robust cyclicity for CO2 photoreduction to HCOOH. This research explores a robust route toward cost-effective, massive production of SACs for potential industrial applications.

Neoadjuvant SHR-1701 with or without chemotherapy in unresectable stage III non-small-cell lung cancer: A proof-of-concept, phase 2 trial.

We conducted a proof-of-concept, phase 2 trial to assess neoadjuvant SHR-1701 with or without chemotherapy, followed by surgery or radiotherapy, and then consolidation SHR-1701 in unresectable stage III non-small-cell lung cancer (NSCLC). In the primary cohort of patients receiving neoadjuvant combination therapy (n = 97), both primary endpoints were met, with a post-induction objective response rate of 58% (95% confidence interval [CI] 47-68) and an 18-month event-free survival (EFS) rate of 56.6% (95% CI 45.2-66.5). Overall, 27 (25%) patients underwent surgery; all achieved R0 resection. Among them, 12 (44%) major pathological responses and seven (26%) pathological complete responses were recorded. The 18-month EFS rate was 74.1% (95% CI 53.2-86.7) in surgical patients and 57.3% (43.0-69.3) in radiotherapy-treated patients. Neoadjuvant SHR-1701 with chemotherapy, followed by surgery or radiotherapy, showed promising efficacy with a tolerable safety profile in unresectable stage III NSCLC. Surgical conversion was feasible in a notable proportion of patients and associated with better survival outcomes.

Establishing a river health evaluation index system for seven rivers in Jiamusi City of China.

The Jiamusi section of the Songhua River is one of the first 17 model river construction sections in China. The implementation of river health assessments can determine the health dynamics of rivers and test the management's effectiveness. Targeting seven rivers, this study conducted river zoning and monitoring point deployment to conduct sufficient field research and monitoring. The authors selected hydrological and water resources, physical structure, water quality, aquatic life, social service functions, and management as guideline layers and 15 indicator layers. Subsequently, the authors established an evaluation index system to evaluate and analyze the ecological status and social service status of each river. The results showed that the Yindamu, Alingda, and Gejie rivers scored well as healthy rivers, with health evaluation scores of 78.98, 76.06, and 75.83, respectively. The Wangsanwu, Lujiagang, and Lingdangmai rivers are generally sub-healthy rivers with scores of 71.55, 67.97, and 60.7, respectively. The Yinggetu River has a score of 54.52 and is therefore assessed as unhealthy. Based on the scientific evaluation index method, this study analyses the current river health state in Jiamusi City to provide the basis for the evaluation of the river chief's work and future river management.

Comprehensive Analysis and Experimental Validation of FOXD2 as a Novel Potential Prognostic Biomarker Associated with Immune Infiltration in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: The role of Forkhead Box D2 (FOXD2) in head and neck squamous cell carcinoma (HNSC) has never been studied. OBJECT: Our object was to explore the role of FOXD2 in HNSC. METHODS: Clinical data for patients with HNSC was obtained from TCGA. Our study examined the atypical expression of FOXD2 in both HNSC and pan-cancer, along with its diagnostic and prognostic implications, as well as the association between FOXD2 expression and clinical characteristics, immune infiltration, immune checkpoint genes, and MSI. Gene set enrichment analysis (GESA) was used to investigate the potential regulation network of FOXD2 in HNSC. We analyze the genomic alterations of FOXD2 in HNSC. GSE13397 and qRT-PCR were used for the validation of FOXD2 expression. RESULTS: FOXD2 was aberrantly expressed in 24 tumors. FOXD2 was significantly up-regulated in HNSC compared to normal head and neck tissue (p < 0.001). High FOXD2 expression was associated with the histologic grade of the patient with HNSC (p < 0.001), lymphovascular infiltration (p = 0.002) and lymph node neck dissection (p = 0.002). In HNSC, an autonomous correlation between FOXD2 expression and OS was observed (HR: 1.36; 95% CI: 1.04-1.78; p = 0.026). FOXD2 was associated with the neuronal system, neuroactive ligand-receptor interaction, and retinoblastoma gene in cancer. FOXD2 was associated with immune infiltration, immune checkpoints, and MSI. The somatic mutation rate of FOXD2 in HNSC was 0.2%. FOXD2 was significantly up-regulated in HNSC cell lines. CONCLUSION: Our findings suggest that FOXD2 has the potential to serve as a prognostic biomarker and immunotherapeutic target for individuals with HNSC.

Optical Analysis Method for Turbid Media Based on Wedge-Shaped Cells at Different Angles.

The wedge-shaped sample cell, by offering a comprehensive representation of scattering information in turbid media, significantly enhances the informational content conveyed by spectral images compared to flat sample cells. To further refine the accuracy of turbid medium component detection utilizing wedge-shaped sample cells, this work undertakes modeling and analysis of the influence of different wedge angles on detection precision. In this study, employing a 5° gradient in the incident angle of light, we investigate the impact of incident angles ranging from 10 to 45° on the turbid medium component analysis. Validation experiments are performed by utilizing solutions of Indian ink and fat emulsion at varying ratios. Experimental findings demonstrate that under identical experimental conditions, the wedge-shaped sample cell model at an incident angle of 35° yields optimal analysis results. Utilizing partial least-squares regression (PLSR) for the corresponding optical parameters, the highest value of Rp reached 0.980, with an RMSEP of 0.002. When compared to the model with a 30° incident angle, Rp increased by 0.033, and RMSEP decreased by 0.008. In comparison to the flat sample cell model, Rp increased by 0.041, and RMSEP decreased by 0.004. This study, through continuous variation of wedge angles and PLSR modeling and prediction, further enhances the accuracy of turbid medium component detection, laying an experimental foundation for subsequent analysis of turbid medium components based on wedge-shaped sample cells.

Chemoproteomics-based profiling reveals potential antimalarial mechanism of Celastrol by disrupting spermidine and protein synthesis.

BACKGROUND: Malaria remains a global health burden, and the emergence and increasing spread of drug resistance to current antimalarials poses a major challenge to malaria control. There is an urgent need to find new drugs or strategies to alleviate this predicament. Celastrol (Cel) is an extensively studied natural bioactive compound that has shown potentially promising antimalarial activity, but its antimalarial mechanism remains largely elusive. METHODS: We first established the Plasmodium berghei ANKA-infected C57BL/6 mouse model and systematically evaluated the antimalarial effects of Cel in conjunction with in vitro culture of Plasmodium falciparum. The potential antimalarial targets of Cel were then identified using a Cel activity probe based on the activity-based protein profiling (ABPP) technology. Subsequently, the antimalarial mechanism was analyzed by integrating with proteomics and transcriptomics. The binding of Cel to the identified key target proteins was verified by a series of biochemical experiments and functional assays. RESULTS: The results of the pharmacodynamic assay showed that Cel has favorable antimalarial activity both in vivo and in vitro. The ABPP-based target profiling showed that Cel can bind to a number of proteins in the parasite. Among the 31 identified potential target proteins of Cel, PfSpdsyn and PfEGF1-α were verified to be two critical target proteins, suggesting the role of Cel in interfering with the de novo synthesis of spermidine and proteins of the parasite, thus exerting its antimalarial effects. CONCLUSIONS: In conclusion, this study reports for the first time the potential antimalarial targets and mechanism of action of Cel using the ABPP strategy. Our work not only support the expansion of Cel as a potential antimalarial agent or adjuvant, but also establishes the necessary theoretical basis for the development of potential antimalarial drugs with pentacyclic triterpenoid structures, as represented by Cel. Video Abstract.

High-Fat, High-Calorie Breast Milk in Women with Overweight or Obesity and Its Association with Maternal Serum Insulin Concentration and Triglycerides Levels.

The childhood obesity epidemic continues to be a challenge. Maternal obesity and excessive infant weight gain are strong predictors of childhood obesity, which itself is a major risk factor for adult obesity. The primary source of nutrition during early life is breast milk, and its composition is impacted by maternal habitus and diet. We thus studied the relationship between maternal BMI, serum lipids and insulin, and breast milk fat and calorie content from foremilk to hindmilk. Women who were exclusively breastfeeding at 7-8 weeks postpartum were BMI classified as Normal (18.5-24.9, n = 9) and women with Overweight/Obese (OW/OB ≥ 25, n = 13). Maternal blood and continuous breast milk samples obtained from foremilk to hindmilk were analyzed, and infant milk intake was assessed. Women with OW/OB had significantly higher milk fat and calorie content in the first foremilk and last hindmilk sample as compared to Normal BMI women. Amongst all women, maternal serum triglycerides, insulin, and HOMA were significantly correlated with foremilk triglyceride concentration, suggesting that maternal serum triglyceride and insulin action contribute to human milk fat content. As the milk fat content of OW/OB women has caloric implications for infant growth and childhood obesity, these results suggest the potential for modulating milk fat content by a reduction in maternal serum lipids or insulin.

Transcutaneous electrical acupoint stimulation for prevention of postoperative urinary retention: A systematic review.

Introduction: Transcutaneous electrical acupoint stimulation (TEAS) has been proposed for postoperative urinary retention (POUR). This meta-analysis evaluated the effect of TEAS in preventing POUR. Methods: Databases were searched until February 6, 2023. Randomized controlled trials (RCTs) about TEAS for preventing POUR were included. The primary concern was the incidence of POUR, with post-void residual urine volume as a secondary outcome. Results: Fourteen studies with 2865 participants were identified. TEAS reduced the incidence of POUR (RR = 0.44, 95%CI = 0.33 to 0.58, P < 0.00001) and decreased the post-void residual urine volume (MD = -75.41 mL, 95%CI = -118.76 to -32.06, P = 0.0007). The preventive effect on POUR was found in patients receiving anorectal, gynecologic, orthopedic and biliary surgery, but not urinary surgery. Dilatational- and continuous-wave TEAS had a great outcome in preventing POUR. Intraoperative TEAS, preoperative and intraoperative TEAS, and postoperative TEAS were beneficial, and TEAS was more beneficial when compared with sham TEAS and blank control. It is nevertheless difficult to rule out publication bias. Conclusions: TEAS could prevent POUR. Due to insufficient evidence, multicenter, large-sample and high-quality RCTs should be conducted. (Registration:INPLASY202320095).

A new andrographolide derivative ADA targeting SIRT3-FOXO3a signaling mitigates cognitive impairment by activating mitophagy and inhibiting neuroinflammation in Apoe4 mice.

BACKGROUND: Alzheimer's disease (AD) is one of the most common neurodegenerative diseases and mitophagy deficit was identified as the typical abnormality in early stage of AD. The neuroprotective effect of andrographolide (AGA) has been confirmed, anda acetylated derivative of AGA (3,14,19-triacetylandrographolide, ADA) was considered to have stronger efficacy. PURPOSE: The current study aims to investigate the impact of ADA on cognitive ability in a sporadic AD model and explore its potential mechanism. STUDY DESIGN/ METHODS: Apoe4 mouse was adopted for evaluating the impact of AGA on cognitive impairment through a serious of behavioral tests. The molecular mechanism of ADA involved in mitophagy and neuroinflammation was investigated in detailby Western blot, ELISA, immunofluorescence and transmission electron microscopy in Apoe4 mice, as well as Apoe4-transfected BV2 cells and HT22 cells. RESULTS: ADA application significantly improved cognitive impairment of Apoe4 mice, and lessened Aß load and neuronal damage, which has stronger activity than its prototype AGA. Accumulated mitophagy markers LC3II, P62, TOM20, PINK1 and Parkin, and decreased mitophagy receptor BNIP3 in hippocampus of Apoe4 mice were greatly reversed after ADA treatment. Meanwhile, ADA promoted the recruitment of BNIP3 to mitochondria, and the transport of damaged mitochondria to lysosome, indicating that disturbed mitophagy in AD mice was restored by ADA. Inhibited SIRT3 and FOXO3a in Apoe4 mice brains were elevated after ADA treatment. ADA also lightened the neuroinflammation caused by NLRP3 inflammasome activation. Additionally, damaged mitophagy and/or activated NLRP3 inflammasome were also observed in BV2 cells and HT22 cells transfected with Apoe4, all of which were rescued by ADA incubation. Noteworthily, SIRT3 inhibitor 3-TYP could abolish the impact of ADA on mitophagy and NLRP3 inflammasome in vitro. CONCLUSION: ADA exerted stronger cognition-enhancing ability in relative to AGA, and ADA could repaire mitophagy deficiency via SIRT3-FOXO3a pathway, and subsequently inhibite NLRP3 inflammasome to mitigate AD pathology.

Simultaneously Enhanced Thermoelectric and Mechanical Performance in SnSe-Based Nanocomposites Produced via Sintering SnSe and KCu7S4 Nanomaterials.

Both thermoelectric and mechanical properties are important to the practical applications of thermoelectric materials. Herein, we develop a strategy for alloying KCu7S4 to improve the dimensionless figure of merit (zT), compressive strength, and Vickers hardness of polycrystalline SnSe. Through chemical synthesis and particle mixing in solutions, powders with SnSe nanoparticles and KCu7S4 nanowires are produced, and the subsequent spark plasma sintering triggers the reaction between the two chalcogenides, resulting in the formation of Cu2SnSe3 nanoparticles and substitution of Cu and S in the SnSe matrix. The composition tuning and secondary phase formation effectively enhance the power factor and diminish the lattice thermal conductivity, leading to a maximum zT of 1.13 at 823 K for the optimal sample, which is improved by 135% over that of SnSe. Simultaneously, the compressive strength and hardness are also enhanced, as exemplified by a high compressive strength of 135 MPa that is enhanced by ∼81% compared to that of SnSe. The current study demonstrates effective composite and composition design toward enhanced thermoelectric and mechanical performance in polycrystalline SnSe.

Stress/cell death pathways, neuroinflammation, and neuropathic pain.

Neuropathic pain is a common and debilitating modality of chronic pain induced by a lesion or disease of the somatosensory nervous system. Albeit the elucidation of numerous pathophysiological mechanisms and the development of potential treatment compounds, safe and reliable therapies of neuropathic pain remain poor. Multiple stress/cell death pathways have been shown to be implicated in neuroinflammation during neuropathic pain. Here, we summarize the current knowledge of stress/cell death pathways and present an overview of the roles and molecular mechanisms of stress/cell death pathways in neuroinflammation during neuropathic pain, covering intrinsic and extrinsic apoptosis, autophagy, mitophagy, ferroptosis, pyroptosis, necroptosis, and phagoptosis. Small molecule compounds that modulate stress/cell death pathways in alleviating neuropathic pain are discussed mainly based on preclinical neuropathic pain models. These findings will contribute to in-depth understanding of the pathological processes during neuropathic pain as well as bridge the gap between basic and translational research to uncover new neuroprotective interventions.

Triptolide inhibits the proinflammatory potential of myeloid-derived suppressor cells via reducing Arginase-1 in rheumatoid arthritis.

Triptolide (TPT) is widely used in the treatment of rheumatoid arthritis (RA). However, its regulatory mechanisms are not fully understood. This study demonstrated that Myeloid-derived suppressor cells (MDSCs) were expanded in both RA patients and arthritic mice. The frequency of MDSCs was correlated with RA disease severity and T helper 17 (Th17) responses. MDSCs from RA patients promoted the polarization of Th17 cells in vitro, which could be substantially attenuated by blocking arginase-1 (Arg-1). TPT inhibited the differentiation of MDSCs, particularly the monocytic MDSCs (M-MDSCs) subsets, as well as the expression of Arg-1 in a dose dependent manner. Alongside, TPT treatment reduced the potential of MDSCs to promote the polarization of IL-17+ T cell in vitro. Consistently, TPT immunotherapy alleviated adjuvant-induced arthritis (AIA) in a mice model, and reduced the frequency of MDSCs, M-MDSCs and IL-17+ T cells simultaneously. The presented data suggest a pathogenic role of MDSCs in RA and may function as a novel and effective therapeutic target for TPT in RA.

Integration of dosimetric parameters, clinical factors, and radiomics to predict symptomatic radiation pneumonitis in lung cancer patients undergoing combined immunotherapy and radiotherapy.

PURPOSE: This study aimed to combine clinical/dosimetric factors and handcrafted/deep learning radiomic features to establish a predictive model for symptomatic (grade ≥ 2) radiation pneumonitis (RP) in lung cancer patients who received immunotherapy followed by radiotherapy. MATERIALS AND METHODS: This study retrospectively collected data of 73 lung cancer patients with prior receipt of ICIs who underwent thoracic radiotherapy (TRT). Of these 73 patients, 41 (56.2 %) developed symptomatic grade ≥ 2 RP. RP was defined per multidisciplinary clinician consensus using CTCAE v5.0. Regions of interest (ROIs) (from radiotherapy planning CT images) utilized herein were gross tumor volume (GTV), planning tumor volume (PTV), and PTV-GTV. Clinical/dosimetric (mean lung dose and V5-V30) parameters were collected, and 107 handcrafted radiomic (HCR) features were extracted from each ROI. Deep learning-based radiomic (DLR) features were also extracted based on pre-trained 3D residual network models. HCR models, Fusion HCR model, Fusion HCR + ResNet models, and Fusion HCR + ResNet + Clinical models were built and compared using the receiver operating characteristic (ROC) curve with measurement of the area under the curve (AUC). Five-fold cross-validation was performed to avoid model overfitting. RESULTS: HCR models across various ROIs and the Fusion HCR model showed good predictive ability with AUCs from 0.740 to 0.808 and 0.740-0.802 in the training and testing cohorts, respectively. The addition of DLR features improved the effectiveness of HCR models (AUCs from 0.826 to 0.898 and 0.821-0.898 in both respective cohorts). The best performing prediction model (HCR + ResNet + Clinical) combined HCR & DLR features with 7 clinical/dosimetric characteristics and achieved an average AUC of 0.936 and 0.946 in both respective cohorts. CONCLUSIONS: In patients undergoing combined immunotherapy/RT for lung cancer, integrating clinical/dosimetric factors and handcrafted/deep learning radiomic features can offer a high predictive capacity for RP, and merits further prospective validation.

Dosimetric predictors of radiation pneumonitis in patients with prior immunotherapy exposure: A multi-institutional analysis.

BACKGROUND AND PURPOSE: Combining immune checkpoint inhibitors (ICIs) and thoracic radiotherapy (TRT) may magnify the radiation pneumonitis (RP) risk. Dosimetric parameters can predict RP, but dosimetric data in context of immunotherapy are very scarce. To address this knowledge gap, we performed a large multicenter investigation to identify dosimetric predictors of RP in this under-studied population. MATERIALS AND METHODS: All lung cancer patients from five institutions who underwent conventionally-fractionated thoracic intensity-modulated radiotherapy with prior ICI receipt were retrospectively compiled. RP was defined per CTCAE v5.0. Statistics utilized logistic regression modeling and receiver operating characteristic (ROC) analysis. RESULTS: The vast majority of the 192 patients (median follow-up 14.7 months) had non-small cell lung cancer, received PD-1 inhibitors, and did not receive concurrent systemic therapy with TRT. Grades 1-5 RP occurred in 21.9%, 25.0%, 8.3%, 1.6%, and 1.0%, respectively. The mean MLD for patients with grades 1-5 RP was 10.7, 11.6, 12.6, 14.7, and 12.8 Gy, respectively. On multivariable analysis, tumor location and mean lung dose (MLD) significantly predicted for any-grade and grade ≥ 2 pneumonitis. Only MLD significantly predicted for grade ≥ 3 RP. ROC analysis was able to pictorially model RP risk probabilities for a variety of MLD thresholds, which can be an assistive tool during TRT treatment planning. CONCLUSION: This study, by far the largest to date of dosimetric predictors of RP in the immunotherapy era, illustrates that MLD is the most critical dose-volume parameter influencing RP risk. These data may provide a basis for revising lung dose constraints in efforts to better prevent RP in this rapidly expanding ICI/TRT population.

Microarray Expression Profile of Exosomal circRNAs from High Glucose Stimulated Human Renal Tubular Epithelial Cells.

Introduction: Circular RNA (circRNAs) are a type of non-coding RNA (ncRNAs) with a wealth of functions. Recently, circRNAs have been identified as important regulators of diabetic kidney disease (DKD), owing to their stability and enrichment in exosomes. However, the role of circRNAs in exosomes of tubular epithelial cells in DKD development has not been fully elucidated. Methods: In our study, microarray technology was used to analyze circRNA expression in cell supernatant exosomes isolated from HK-2 cells with or without high glucose (HG) treatment. The small interfering RNAs (siRNA) and plasmid overexpression were used to validate functions of differentially expressed circRNAs. Results: We found that exosome concentration was higher in HG-stimulated HK-2 cells than in controls. A total of 235 circRNAs were significantly increased and 458 circRNAs were significantly decreased in the exosomes of the HG group. In parallel with the microarray data, the qPCR results showed that the expression of circ_0009885, circ_0043753, and circ_0011760 increased, and the expression of circ_0032872, circ_0004716, and circ_0009445 decreased in the HG group. Rescue experiments showed that the effects of high glucose on regulation of CCL2, IL6, fibronetin, n cadherin, e cadherin and epcam expression can be reversed by inhibiting or overexpressing these circRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses indicated that circRNA parental genes are associated with glucose metabolism, lipid metabolism, and inflammatory processes, which are important in DKD development. Further analysis of circRNA/miRNA interactions indicated that 152 differentially expressed circRNAs with fold change (FC) ≥1.5 could be paired with 43 differentially expressed miRNAs, which are associated with diabetes or DKD. Discussion: Our results indicate that exosomal circRNAs may be promising diagnostic and therapeutic biomarkers, and may play a critical role in the progression of DKD.

Strongly Coupled Ag/Sn-SnO2 Nanosheets Toward CO2 Electroreduction to Pure HCOOH Solutions at Ampere-Level Current.

Electrocatalytic reduction of CO2 converts intermittent renewable electricity into value-added liquid products with an enticing prospect, but its practical application is hampered due to the lack of high-performance electrocatalysts. Herein, we elaborately design and develop strongly coupled nanosheets composed of Ag nanoparticles and Sn-SnO2 grains, designated as Ag/Sn-SnO2 nanosheets (NSs), which possess optimized electronic structure, high electrical conductivity, and more accessible sites. As a result, such a catalyst exhibits unprecedented catalytic performance toward CO2-to-formate conversion with near-unity faradaic efficiency (≥ 90%), ultrahigh partial current density (2,000 mA cm-2), and superior long-term stability (200 mA cm-2, 200 h), surpassing the reported catalysts of CO2 electroreduction to formate. Additionally, in situ attenuated total reflection-infrared spectra combined with theoretical calculations revealed that electron-enriched Sn sites on Ag/Sn-SnO2 NSs not only promote the formation of *OCHO and alleviate the energy barriers of *OCHO to *HCOOH, but also impede the desorption of H*. Notably, the Ag/Sn-SnO2 NSs as the cathode in a membrane electrode assembly with porous solid electrolyte layer reactor can continuously produce ~ 0.12 M pure HCOOH solution at 100 mA cm-2 over 200 h. This work may inspire further development of advanced electrocatalysts and innovative device systems for promoting practical application of producing liquid fuels from CO2.

AMGCN-L: an adaptive multi-time-window graph convolutional network with long-short-term memory for depression detection.

Objective.Depression is a common chronic mental disorder characterized by high rates of prevalence, recurrence, suicide, and disability as well as heavy disease burden. An accurate diagnosis of depression is a prerequisite for treatment. However, existing questionnaire-based diagnostic methods are limited by the innate subjectivity of medical practitioners and subjects. In the search for a more objective diagnostic methods for depression, researchers have recently started to use deep learning approaches.Approach.In this work, a deep-learning network, named adaptively multi-time-window graph convolutional network (GCN) with long-short-term memory (LSTM) (i.e. AMGCN-L), is proposed. This network can automatically categorize depressed and non-depressed people by testing for the existence of inherent brain functional connectivity and spatiotemporal features contained in electroencephalogram (EEG) signals. AMGCN-L is mainly composed of two sub-networks: the first sub-network is an adaptive multi-time-window graph generation block with which adjacency matrices that contain brain functional connectivity on different time periods are adaptively designed. The second sub-network consists of GCN and LSTM, which are used to fully extract the innate spatial and temporal features of EEG signals, respectively.Main results.Two public datasets, namely the patient repository for EEG data and computational tools, and the multi-modal open dataset for mental-disorder analysis, were used to test the performance of the proposed network; the depression recognition accuracies achieved in both datasets (using tenfold cross-validation) were 90.38% and 90.57%, respectively.Significance.This work demonstrates that GCN and LSTM have eminent effects on spatial and temporal feature extraction, respectively, suggesting that the exploration of brain connectivity and the exploitation of spatiotemporal features benefit the detection of depression. Moreover, the proposed method provides effective support and supplement for the detection of clinical depression and later treatment procedures.

Ferroptosis: a new regulatory mechanism in neuropathic pain.

Neuropathic pain (NP) is pain caused by damage to the somatosensory system. It is a common progressive neurodegenerative disease that usually presents with clinical features such as spontaneous pain, touch-evoked pain, nociceptive hyperalgesia, and sensory abnormalities. Due to the complexity of the mechanism, NP often persists. In addition to the traditionally recognized mechanisms of peripheral nerve damage and central sensitization, excessive iron accumulation, oxidative stress, neuronal inflammation, and lipid peroxidation damage are distinctive features of NP in pathophysiology. However, the mechanisms linking these pathological features to NP are not fully understood. The complexity of the pathogenesis of NP greatly limits the development of therapeutic approaches for NP. Ferroptosis is a novel form of cell death discovered in recent years, in which cell death is usually accompanied by massive iron accumulation and lipid peroxidation. Ferroptosis-inducing factors can affect glutathione peroxidase directly or indirectly through different pathways, leading to decreased antioxidant capacity and accumulation of lipid reactive oxygen species (ROS) in cells, ultimately leading to oxidative cell death. It has been shown that ferroptosis is closely related to the pathophysiological process of many neurological disorders such as NP. Possible mechanisms involved are changes in intracellular iron ion levels, alteration of glutamate excitability, and the onset of oxidative stress. However, the functional changes and specific molecular mechanisms of ferroptosis during this process still need to be further explored. How to intervene in the development of NP by regulating cellular ferroptosis has become a hot issue in etiological research and treatment. In this review, we systematically summarize the recent progress of ferroptosis research in NP, to provide a reference for further understanding of its pathogenesis and propose new targets for treatment.