Predicting the efficiency of arsenic immobilization in soils by biochar using machine learning.

Arsenic (As) pollution in soils is a pervasive environmental issue. Biochar immobilization offers a promising solution for addressing soil As contamination. The efficiency of biochar in immobilizing As in soils primarily hinges on the characteristics of both the soil and the biochar. However, the influence of a specific property on As immobilization varies among different studies, and the development and application of arsenic passivation materials based on biochar often rely on empirical knowledge. To enhance immobilization efficiency and reduce labor and time costs, a machine learning (ML) model was employed to predict As immobilization efficiency before biochar application. In this study, we collected a dataset comprising 182 data points on As immobilization efficiency from 17 publications to construct three ML models. The results demonstrated that the random forest (RF) model outperformed gradient boost regression tree and support vector regression models in predictive performance. Relative importance analysis and partial dependence plots based on the RF model were conducted to identify the most crucial factors influencing As immobilization. These findings highlighted the significant roles of biochar application time and biochar pH in As immobilization efficiency in soils. Furthermore, the study revealed that Fe-modified biochar exhibited a substantial improvement in As immobilization. These insights can facilitate targeted biochar property design and optimization of biochar application conditions to enhance As immobilization efficiency.

3D Reconstruction from a Single Sketch via View-dependent Depth Sampling.

Reconstructing a 3D shape based on a single sketch image is challenging due to the inherent sparsity and ambiguity present in sketches. Existing methods lose fine details when extracting features to predict 3D objects from sketches. Upon analyzing the 3D-to-2D projection process, we observe that the density map, characterizing the distribution of 2D point clouds, can serve as a proxy to facilitate the reconstruction process. In this work, we propose a novel sketch-based 3D reconstruction model named SketchSampler. It initiates the process by translating a sketch through an image translation network into a more informative 2D representation, which is then used to generate a density map. Subsequently, a two-stage probabilistic sampling process is employed to reconstruct a 3D point cloud: firstly, recovering the 2D points (i.e., the x and y coordinates) by sampling the density map; and secondly, predicting the depth (i.e., the z coordinate) by sampling the depth values along the ray determined by each 2D point. Additionally, we convert the reconstructed point cloud into a 3D mesh for wider applications. To reduce ambiguity, we incorporate hidden lines in sketches. Experimental results demonstrate that our proposed approach significantly outperforms other baseline methods.

Extracellular Matrix Remodelling of the Periodontium under Orthodontic Force.

As the biological mechanisms of orthodontic tooth movement have been explored further, scholars have gradually focused on the remodelling mechanism of the extracellular matrix (ECM) in the periodontal ligament (PDL). The ECM of the PDL consists of various types of collagens and other glycoproteins. The specific process and mechanism of ECM remodelling during orthodontic tooth movement remains unclear. Collagen I and III, which constitute major components of the PDL, are upregulated under orthodontic force. The changes in the contents of ECM proteins also depend on the expression of ECM-related enzymes, which organise new collagen fibre networks to adapt to changes in tooth position. The matrix metalloproteinase family is the main enzyme that participates in collagen hydrolysis and renewal and changes its expression under orthodontic force. Moreover, ECM adhesion molecules, such as integrins, are also regulated by orthodontic force and participate in the dynamic reaction of cell adhesion and separation with the ECM. This article reviews the changes in ECM components, related enzymes and adhesion molecules in the PDL under orthodontic force to lay the foundation for the exploration of the regulatory mechanism of ECM remodelling during orthodontic tooth movement.

Characterization of the UDP-glycosyltransferase UGT33D1 in silkworm Bombyx mori.

Uridine diphosphate (UDP)-glycosyltransferases (UGTs) are important metabolizing enzymes functioning by adding a sugar moiety to a small lipophilic substrate molecule and play critical roles in drug/toxin metabolism for all realms of life. In this study, the silkworm Bombyx mori UGT33D1 gene was characterized in detail. UGT33D1 was found localized in the endoplasmic reticulum (ER) compartment just like other animal UGTs and was mainly expressed in the silkworm midgut. We first reported that UGT33D1 was important to BmNPV infection, as silencing UGT33D1 inhibited the BmNPV infection in silkworm BmN cells, while overexpressing the gene promoted viral infection. The molecular pathways regulated by UGT33D1 were analysed via transcriptome sequencing upon UGT33D1 knockdown, highlighting the important role of the gene in maintaining a balanced oxidoreductive state of the organism. In addition, proteins that physically interact with UGT33D1 were identified through immunoprecipitation and mass spectrometry analysis, which includes tubulin, elongation factor, certain ribosomal proteins, histone proteins and zinc finger proteins that had been previously reported for human UGT-interacting proteins. This study provided preliminary but important functional information on UGT33D1 and is hoped to trigger deeper investigations into silkworm UGTs and their functional mechanisms.

Long-term Trends of Dissolved Organic Carbon Dynamics in a Subtropical Forest Responding to Environmental Changes.

Dissolved organic carbon (DOC) dynamics are critical to carbon cycling in forest ecosystems and sensitive to global change. Our study, spanning from 2001 to 2020 in a headwater catchment in subtropical China, analyzed DOC and water chemistry of throughfall, litter leachate, soil waters at various depths, and streamwater. We focused on DOC transport through hydrological pathways and assessed the long-term trends in DOC dynamics amidst environmental and climatic changes. Our results showed that the annual DOC deposition via throughfall and stream outflow was 14.2 ± 2.2 and 1.87 ± 0.83 g C m-2 year-1, respectively. Notably, there was a long-term declining trend in DOC deposition via throughfall (-0.195 mg C L-1 year-1), attributed to reduced organic carbon emissions from clean air actions. Conversely, DOC concentrations in soil waters and stream waters showed increasing trends, primarily due to mitigated acid deposition. Moreover, elevated temperature and precipitation could partly explain the long-term rise in DOC leaching. These trends in DOC dynamics have significant implications for the stability of carbon sink in terrestrial, aquatic, and even oceanic ecosystems at regional scales.

Vascular Plugs Improve Pulmonary Arteriovenous Malformation Occlusion over Coil Embolization Alone: A Proof-of-Concept Study using Dual Energy Computed Tomography.

PURPOSE: To evaluate efficacy of pulmonary arteriovenous malformation (PAVM) embolization using dual-energy computed tomography (DECT) and spectral curve analysis by characterizing contrast enhancement and vascular perfusion as a surrogate of the degree of vascular occlusion after embolotherapy. METHODS: Nine consecutive adult patients underwent embolization for 21 PAVMs (size range 0.4-2.0cm; 15/21 simple angioarchitecture) and subsequent post-embolization chest DECT angiography. Twelve PAVMS were treated with vascular plugs ± coils, whereas nine PAVMs were treated with coils-only. Virtual spectral curves (VSC) were generated using dual-energy image post-processing in order to measure embolization effectiveness. RESULTS: Complete occlusion of target PAVM was achieved in all cases on digital subtraction angiography at the end of the embolization procedure. With a median follow-up of 12.7 months, the vascular plug group demonstrated significantly less vascular opacification compared to the coils-only group, as measured by opacification between upstream feeding artery and and different downstream vasculature locations (Δslope1: median 79.1 versus 28.6, p=0.0030; Δslope2: 76.4 versus 28.6, p=0.0197; Δslope3: 78.9 versus 28.6, p=0.0041). Persistence occurred in three PAVMs based on size criteria, which demonstrated higher vascular vascular opacification by DECT (Δslope1: 72 versus 28.6, p=0.253; Δslope2: 65.1 versus 32.7, p=0.326; Δslope3: 72.9 versus 53.5, p=0.733), although statistical significance was not reached. CONCLUSION: Similar to emerging literature, DECT showed improved occlusion in PAVMs treated with vascular plugs compared to coils alone.

Silver-Catalyzed Decarboxylative Nitrooxylation of Aliphatic Carboxylic Acids.

Here, we present a silver-catalyzed decarboxylative nitrooxylation via a radical-based approach. The substrate scope of this reaction prototype extends to nonactivated primary and secondary carboxylic acids. This protocol provides a practical method for the synthesis of an unprecedented family of organic nitrates and exhibits wide functional group compatibility. Preliminary mechanistic studies reveal that a high-valent silver(II) nitrate complex is a versatile NO3 resource pool, allowing for facile C-O bond formation.

Comprehensive transcriptomic and metabolomic insights into simultaneous CO2 sequestration and nitrate removal by the Chlorella vulgaris and Pseudomonas sp. consortium.

Simultaneous CO2 sequestration and nitrate removal can be achieved by co-cultivation of Chlorella vulgaris with Pseudomonas sp. However, a comprehensive understanding of the synergistic mechanism between C. vulgaris and Pseudomonas sp. remains unknown. In this study, transcriptomics and metabolomics analysis were employed to elucidate the synergistic mechanism of C. vulgaris and Pseudomonas sp. Transcriptomic and metabolomic analyses identified 3664 differentially expressed genes and 314 metabolites. Transcriptome analysis revealed that co-culture with Pseudomonas sp. promoted the photosynthesis of C. vulgaris by promoting the synthesis of photosynthetic pigments and photosynthesis-antenna proteins. Furthermore, it stimulated pathways associated with energy metabolism from carbon sources, such as the Calvin cycle, glycolytic pathway, and TCA cycle. Additionally, Pseudomonas sp. reduced nitrate levels in the co-culture system by denitrification, and microalgae regulated nitrate uptake by down-regulating the transcript levels of nitrate transporter genes. Metabolomic analysis indicated that nutrient exchange was conducted between algae and bacteria, and amino acids, phytohormones, and organic heterocyclic compounds secreted by the bacteria promoted the growth metabolism of microalgae. After supplementation with differential metabolites, the carbon fixation rate and nitrate removal rate of the co-culture system reached 0.549 g L-1 d-1 and 135.4 mg L-1 d-1, which were increased by 20% and 8%, respectively. This study provides a theoretical insight into microalgae-bacteria interaction and its practical application, as well as a novel perspective on flue gas treatment management.

Survival trends among patients with metastatic non-small cell lung cancer before and after the approval of immunotherapy in the United States: A Surveillance, Epidemiology, and End Results database-based study.

BACKGROUND: In 2015, the US Food and Drug Administration approved nivolumab as the first immunotherapy for patients with advanced non-small cell lung cancer (NSCLC). However, population-based survival benefit studies after the introduction of immunotherapy in lung cancer are lacking. This study examined overall survival (OS) and cancer-specific survival in patients with NSCLC in the pre immunotherapy and immunotherapy eras. METHODS: This study used the Surveillance, Epidemiology, and End Results database, which spanned 17 registries from 2000 to 2020. Two cohorts were delineated: preimmunotherapy (2010-2014) and immunotherapy (2015-2020), which coincided with nivolumab's approval. RESULTS: This study included 191,802 patients, 90,807 in the preimmunotherapy era and 100,995 in the immunotherapy era. OS was significantly higher in the immunotherapy era, as shown by Kaplan-Meier curves (1-year OS, 40.1% vs. 33.5%; 3-year OS, 17.8% vs. 11.7%; 5-year OS, 10.7% vs. 6.8%; median OS, 8 vs. 7 months; p < .001 by log-rank test). Similarly, cancer-specific survival improved in the immunotherapy era (1-year survival, 44.0% vs. 36.8%; 3-year survival, 21.7% vs. 14.4%; 5-year survival, 14.3% vs. 9.0%; median OS, 10 vs. 8 months; p < .001 by log-rank test). Survival rates were significantly better in the immunotherapy era, as confirmed by multivariate analysis with a Cox proportional hazards model after adjusting for age, sex, race, income, and geographical area (adjusted hazard ratio, 0.830; 95% CI, 0.821-0.840; p < .001). CONCLUSIONS: In summary, the survival rate of patients with metastatic NSCLC has improved since the introduction of immunotherapy.

Carvedilol to prevent hepatic decompensation of cirrhosis in patients with clinically significant portal hypertension stratified by new non-invasive model (CHESS2306).

Background & Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvedilol-treating cohort. Results: In the meta-analysis with six studies (n = 819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new "CSPH risk" model. In the HVPG cohort (n = 151), the new model accurately predicted CSPH with cutoff values of 0 and -0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n = 1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <-0.68 (low-risk), -0.68 to 0 (medium-risk), and >0 (high-risk). In the carvedilol-treated cohort, patients with high-risk CSPH treated with carvedilol (n = 81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n = 613 before propensity score matching [PSM], n = 162 after PSM). Conclusions: Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Colonization of microbiota derived from Macaca fascicularis, Bama miniature pigs, beagle dogs, and C57BL/6J mice alleviates DSS-induced colitis in germ-free mice.

Fecal microbiota transplantation (FMT) is an innovative and promising treatment for inflammatory bowel disease (IBD), which is related to the capability of FMT to supply functional microorganisms to improve recipient gut health. Numerous studies have highlighted considerable variability in the efficacy of FMT interventions for IBD. Several factors, including the composition of the donor microorganisms, significantly affect the efficacy of FMT in the treatment of IBD. Consequently, identifying the functional microorganisms in the donor is crucial for enhancing the efficacy of FMT. To explore potential common anti-inflammatory bacteria with therapeutic implications for IBD, germ-free (GF) BALB/c mice were pre-colonized with fecal microbiota obtained from diverse donors, including Macaca fascicularis (MCC_FMT), Bama miniature pigs (BP_FMT), beagle dogs (BD_FMT), and C57BL/6 J mice (Mice_FMT). Subsequently, mice were treated with dextran sodium sulfate (DSS). As expected, the symptoms of colitis were alleviated by MCC_FMT, BP_FMT, BD_FMT, and Mice_FMT, as demonstrated by the prevention of an elevated disease activity index in mice. Additionally, the utilization of distinct donors protected the intestinal barrier and contributed to the regulation of cytokine homeostasis. Metagenomic sequencing data showed that the microbial community structure and dominant species were significantly different among the four groups, which may be linked to variations in the anti-inflammatory efficacy observed in the respective groups. Notably, Lactobacillus reuteri and Flavonifractor plautii were consistently present in all four groups. L. reuteri exhibited a significant negative correlation with IL-1ß, and animal studies further confirmed its efficacy in alleviating IBD, suggesting the presence of common functional bacteria across different donors that exert anti-inflammatory effects. This study provides essential foundational data for the potential clinical applications of FMT.IMPORTANCEDespite variations in efficacy observed among donors, numerous studies have underscored the potential of fecal microbiota transplantation (FMT) for managing inflammatory bowel disease (IBD), indicating the presence of shared anti-IBD bacterial species. In the present study, the collective anti-inflammatory efficacy observed across all four donor groups prompted the identification of two common bacterial species using metagenomics. A significant negative correlation between Lactobacillus reuteri and IL-1ß was revealed. Furthermore, mice gavaged with L. reuteri successfully managed the colitis challenge induced by dextran sodium sulfate (DSS), suggesting that L. reuteri may act as an efficacious bacterium mediating shared anti-inflammatory effects among variable donors. This finding highlights the utilization of variable donors to screen FMT core bacteria, which may be a novel strategy for developing FMT applications.

Unveiling the role of ferroptosis in the progression from NAFLD to NASH: recent advances in mechanistic understanding.

Non-alcoholic fatty liver disease (NAFLD) is a prevalent and significant global public health issue. Nonalcoholic steatohepatitis (NASH) represents an advanced stage of NAFLD in terms of pathology. However, the intricate mechanisms underlying the progression from NAFLD to NASH remain elusive. Ferroptosis, characterized by iron-dependent cell death and distinguished from other forms of cell death based on morphological, biochemical, and genetic criteria, has emerged as a potential participant with a pivotal role in driving NAFLD progression. Nevertheless, its precise mechanism remains poorly elucidated. In this review article, we comprehensively summarize the pathogenesis of NAFLD/NASH and ferroptosis while highlighting recent advances in understanding the mechanistic involvement of ferroptosis in NAFLD/NASH.

A Prognostic Model Based on Nutritional Indexes for Patients With Pan-Cancer: A Real-World Cohort Study.

BACKGROUND: The aim was to identify the nutritional indexes, construct a prognostic model, and develop a nomogram for predicting individual survival probability in pan-cancers. METHODS: Nutritional indicators, clinicopathological characteristics, and previous major treatment details of the patients were collected. The enrolled patients were randomly divided into training and validation cohorts. Least absolute shrinkage and selection operator (Lasso) regression cross-validation was used to determine the variables to include in the cox regression model. The training cohort was used to build the prediction model, and the validation cohort was used to further verify the discrimination, calibration, and clinical effectiveness of the model. RESULTS: A total of 2020 patients were included. The median OS was 56.50 months (95% CI, 50.36-62.65 months). In the training cohort of 1425 patients, through Lasso regression cross-validation, 13 characteristics were included in the model. Cox proportional hazards model was developed and visualized as a nomogram. The C-indexes of the model for predicting 1-, 3-, 5-, and 10-year OS were 0.848, 0.826, 0.814, and 0.799 in the training cohort and 0.851, 0.819, 0.814, and 0.801 in the validation cohort. The model showed great calibration in the two cohorts. Patients with a score of less than 274.29 had a better prognosis (training cohort: HR, 6.932; 95% CI, 5.723-8.397; log-rank p < 0.001; validation cohort: HR, 8.429; 95% CI, 6.180-11.497; log-rank p < 0.001). CONCLUSION: The prognostic model based on the nutritional indexes of pan-cancer can divide patients into different survival risk groups and performed well in the validation cohort.

PEDF-34 attenuates neurological deficit and suppresses astrocyte-dependent neuroinflammation by modulating astrocyte polarization via 67LR/JNK/STAT1 signaling pathway after subarachnoid hemorrhage in rats.

BACKGROUND: Reactive astrocytes participate in various pathophysiology after subarachnoid hemorrhage (SAH), including neuroinflammation, glymphatic-lymphatic system dysfunction, brain edema, BBB disruption, and cell death. Astrocytes transform into two new reactive phenotypes with changed morphology, altered gene expression, and secretion profiles, termed detrimental A1 and beneficial A2. This study investigates the effect of 67LR activation by PEDF-34, a PEDF peptide, on neuroinflammation and astrocyte polarization after the experimental SAH. METHODS: A total of 318 male adult Sprague-Dawley rats were used in experiments in vivo, of which 272 rats were subjected to the endovascular perforation model of SAH and 46 rats underwent sham surgery. 67LR agonist (PEDF-34) was administrated intranasally 1 h after SAH. 67LR-specific inhibitor (NSC-47924) and STAT1 transcriptional activator (2-NP) were injected intracerebroventricularly 48 h before SAH. Short- and long-term neurological tests, brain water content, immunostaining, Nissl staining, western blot, and ELISA assay were performed. In experiments in vitro, primary astrocyte culture with hemoglobin (Hb) stimulation was used to mimic SAH. The expression of the PEDF-34/67LR signaling pathway and neuro-inflammatory cytokines were assessed using Western blot, ELISA, and immunohistochemistry assays both in vivo and in vitro. RESULTS: Endogenous PEDF and 67LR expressions were significantly reduced at 6 h after SAH. 67LR was expressed in astrocytes and neurons. Intranasal administration of PEDF-34 significantly reduced brain water content, pro-inflammatory cytokines, and short-term and long-term neurological deficits after SAH. The ratio of p-JNK/JNK and p-STAT1/STAT1 and the expression of CFB and C3 (A1 astrocytes marker), significantly decreased after PEDF-34 treatment, along with fewer expression of TNF-α and IL-1ß at 24 h after SAH. However, 2-NP (STAT1 transcriptional activator) and NSC-47924 (67LR inhibitor) reversed the protective effects of PEDF-34 in vivo and in vitro by promoting A1 astrocyte polarization with increased inflammatory cytokines. CONCLUSION: PEDF-34 activated 67LR, attenuating neuroinflammation and inhibiting astrocyte A1 polarization partly via the JNK/STAT1 pathway, suggesting that PEDF-34 might be a potential treatment for SAH patients.

Perioperative and oncologic outcomes of robot-assisted versus open surgery for pancreatic ductal adenocarcinoma: a systematic review and meta-analysis.

This systematic review and meta-analysis aimed to compare perioperative and oncologic outcomes in patients with pancreatic ductal adenocarcinoma (PDAC) treated with robotic-assisted surgery versus open laparotomy. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Randomized controlled trials (RCTs) and cohort studies up to June 15, 2024, were identified using PubMed, EMBASE, and Google Scholar. Additionally, reference lists of included studies, relevant review articles, and clinical guidelines were manually searched. The primary outcomes evaluated were length of stay, 90-day mortality, postoperative pancreatic fistula (POPF), and Post-pancreatectomy haemorrhage (PPH). Secondary outcomes included estimated blood loss, reoperation rate, lymph node yield, and operative time. The final analysis included 10 retrospective cohort studies involving 23,272 patients (2,179 robotic-assisted and 21,093 open surgery). There were no significant differences between the two procedures in terms of postoperative pancreatic fistula, Post-pancreatectomy haemorrhage, lymph node yield, and operative time. However, patients undergoing robotic-assisted surgery had shorter lengths of stay, lower 90-day mortality, and less estimated blood loss compared to those undergoing open surgery. The reoperation rate was higher for the robotic-assisted group. Robotic-assisted surgery for pancreatic ductal adenocarcinoma is safe and feasible. Compared to open surgery, it offers better perioperative and short-term oncologic outcomes, but with a higher risk of reoperation.

Dorsal raphe nucleus to basolateral amygdala 5-HTergic neural circuit modulates restoration of consciousness during sevoflurane anesthesia.

The advent of general anesthesia (GA) has significant implications for clinical practice. However, the exact mechanisms underlying GA-induced transitions in consciousness remain elusive. Given some similarities between GA and sleep, the sleep-arousal neural nuclei and circuits involved in sleep-arousal, including the 5-HTergic system, could be implicated in GA. Herein, we utilized pharmacology, optogenetics, chemogenetics, fiber photometry, and retrograde tracing to demonstrate that both endogenous and exogenous activation of the 5-HTergic neural circuit between the dorsal raphe nucleus (DR) and basolateral amygdala (BLA) promotes arousal and facilitates recovery of consciousness from sevoflurane anesthesia. Notably, the 5-HT1A receptor within this pathway holds a pivotal role. Our findings will be conducive to substantially expanding our comprehension of the neural circuit mechanisms underlying sevoflurane anesthesia and provide a potential target for modulating consciousness, ultimately leading to a reduction in anesthetic dose requirements and side effects.

PolarFormer: A Transformer-based Method for Multi-lesion Segmentation in Intravascular OCT.

Several deep learning-based methods have been proposed to extract vulnerable plaques of a single class from intravascular optical coherence tomography (OCT) images. However, further research is limited by the lack of publicly available large-scale intravascular OCT datasets with multi-class vulnerable plaque annotations. Additionally, multi-class vulnerable plaque segmentation is extremely challenging due to the irregular distribution of plaques, their unique geometric shapes, and fuzzy boundaries. Existing methods have not adequately addressed the geometric features and spatial prior information of vulnerable plaques. To address these issues, we collected a dataset containing 70 pullback data and developed a multi-class vulnerable plaque segmentation model, called PolarFormer, that incorporates the prior knowledge of vulnerable plaques in spatial distribution. The key module of our proposed model is Polar Attention, which models the spatial relationship of vulnerable plaques in the radial direction. Extensive experiments conducted on the new dataset demonstrate that our proposed method outperforms other baseline methods. Code and data can be accessed via this link: https://github.com/sunjingyi0415/IVOCT-segementaion.

Asiatic acid induces ferroptosis of RA-FLS via the Nrf2/HMOX1 pathway to relieve inflammation in rheumatoid arthritis.

BACKGROUND: Ferroptosis is a distinct iron-dependent non-apoptotic type of programmed cell death that is implicated in the pathophysiology of rheumatoid arthritis (RA). Although asiatic acid (AA) is documented to have significant anti-inflammatory effects in various diseases, it is not known whether it can regulate RA via ferroptosis. METHODS: The effects of AA on rheumatoid arthritis fibroid-like synoviocytes (RA-FLS) were assessed in vitro, and a rat model of type II collagen-induced arthritis (CIA) was established to evaluate the effectiveness of AA treatment in vivo. RESULTS: AA significantly reduced both viability and colony formation in cultured RA-FLS, while increasing the levels of reactive oxygen species (ROS), ferrous iron (Fe2+), malondialdehyde (MDA), and lactate dehydrogenase (LDH), as well as the expression of COX2. Furthermore, AA induced ferroptosis in RA-FLS by promoting Fe2+ accumulation through downregulation of the expression of Keap1 and FTH1 and upregulation of Nrf2 and HMOX1. In vivo, AA treatment was found to reduce toe swelling and the arthritis score in CIA rats, as well as relieve inflammation and ankle damage and significantly upregulate the expression of Nrf2 and HMOX1 in the synovial fluid. CONCLUSION: Treatment with AA significantly reduced the viability of RA-FLS and triggered ferroptosis by promoting accumulation of Fe2+via the Nrf2-HMOX1 pathway, and was effective in relieving inflammation in CIA model rats. These findings suggest that the use of AA may be a promising strategy for the clinical treatment of RA.

Photonic implementation of the input and reservoir layers for a reservoir computing system based on a single VCSEL with two Mach-Zehnder modulators.

Hardware implementation of reservoir computing (RC), which could reduce the power consumption of machine learning and significantly enhance data processing speed, holds the potential to develop the next generation of machine learning hardware devices and chips. Due to the existing solution only implementing reservoir layers, the information processing speed of photonics RC system are limited. In this paper, a photonic implementation of a VMM-RC system based on single Vertical Cavity Surface Emitting Laser (VCSEL) with two Mach Zehnder modulators (MZMs) has been proposed. Unlike previous work, both the input and reservoir layers are realized in the optical domain. Additionally, the impact of various mask signals, such as Two-level mask, Six-level mask, and chaos mask signal, employed in system, has been investigated. The system's performance improves with the use of more complex mask(t). The minimum Normalized mean square error (NMSE) can reach 0.0020 (0.0456) for Santa-Fe chaotic time series prediction in simulation (experiment), while the minimum Word Error Rate (WER) can 0.0677 for handwritten digits recognition numerically. The VMM-RC proposed is instrumental in advancing the development of photonic RC by overcoming the long-standing limitations of photonic RC systems in reservoir implementation. Linear matrix computing units (the input layer) and nonlinear computing units (the reservoir layer) are simultaneously implemented in the optical domain, significantly enhancing the information processing speed of photonic RC systems.