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Background: Isoflurane is a commonly used general anesthetic widely employed in clinical surgeries. Recent studies have indicated that isoflurane might induce negative impacts on the nervous system, notably by triggering neuronal apoptosis. This process is pivotal to the development and emergence of neurological disorders; its misregulation could result in functional deficits and the initiation of diseases within nervous system. However, the potential molecular mechanism of isoflurane on the neuronal apoptosis remains fully unexplored. This study aims to investigate the regulatory role of the sirtuin 1-mechanistic target of rapamycin (SIRT1-mTOR) signaling pathway in autophagy during isoflurane-induced apoptosis of fetal rat brain neuronal cells. Methods: Terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assay, real-time quantitative polymerase chain reaction (qPCR), and Western blot were utilized to evaluate the apoptotic status of hippocampal tissue cells in fetal mice after sevoflurane exposure. Our further investigation was commenced with flow cytometry, immunofluorescence, qPCR, and Western blot to determine the impact of autophagy on sevoflurane-induced apoptosis in these neurons. On the other hand, we conducted an additional set of analyses, including flow cytometric analysis, qPCR, and Western blot, to further elucidate the neuroprotective potential of autophagy in neural cells of fetal mice subjected to sevoflurane-induced apoptosis. Results: Our findings indicated that a 3% sevoflurane treatment led to a significant rise in apoptosis among fetal rat hippocampal tissue cells and neurons. Levels of apoptosis-associated proteins, cleaved-caspase-3 and Bcl-2 associated X protein (Bax), were found to be markedly higher, coinciding with an enhancement in autophagy as evidenced by increased microtubule-associated proteins 1A/1B-light chain 3 (LC3) and decreased p62 expression. Concurrently, there was a notable up-regulation of sirtuin 1 (SIRT1) and a down-regulation of mechanistic target of rapamycin (mTOR) expression. In conclusion, our research elucidated the pivotal function of cellular autophagy in an apoptosis induced by sevoflurane in fetal rat nerve cells. Through experimental manipulation, we observed that interference with SIRT1 resulted in a reduction of both cleaved-caspase-3 and Bax levels. This intervention also beget a diminished expression of the autophagy-associated factor LC3 and an up-regulation of p62. Furthermore, inhibition against mTOR reversed the effects induced by SIRT1 interference, suggesting a complex interplay amid these regulatory pathways. Conclusions: SIRT1 possesses a capacity to modulate apoptosis in the hippocampal neurons of fetal rats triggered by sevoflurane, with mTOR functioning as an inhibitory factor within this signaling pathway.

Over the modern satellite era, substantial climatic changes have been observed in the Antarctic, including atmospheric and oceanic warming, ice sheet thinning and a general Antarctic-wide expansion of sea ice, followed by a more recent rapid loss. Although these changes, featuring strong zonal asymmetry, are partially influenced by increasing greenhouse gas emissions and stratospheric ozone depletion, tropical–polar teleconnections are believed to have a role through Rossby wave dynamics. In this Review, we synthesize understanding of tropical teleconnections to the Southern Hemisphere extratropics arising from the El Niño–Southern Oscillation, Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation, focusing on the mechanisms and long-term climatic impacts. These teleconnections have contributed to observed Antarctic and Southern Ocean changes, including regional rapid surface warming, pre-2015 sea ice expansion and its sudden reduction thereafter, changes in ocean heat content and accelerated thinning of most of the Antarctic ice sheet. However, due to limited observations and inherent model biases, uncertainties remain in understanding and assessing the importance of these teleconnections versus those arising from greenhouse gases, ozone recovery and internal variability. Sustained pan-Antarctic efforts towards long-term observations, and more realistic dynamics and parameterizations in high-resolution climate models, offer opportunities to reduce these uncertainties.

Not only is scrap steel an indispensable ferritic raw material for the modern steel industry, but it is also the only green raw material that can replace iron ore in large quantities. The quality of the scrap steel directly affects the quality of molten steel, which makes it necessary to sort and grade scrap steel before it enters the furnace. Most iron and steel enterprises determine the grade of scrap steel mainly by visual inspection and caliper-based measurements by quality management personnel. As a result, this process is prone to human errors and low efficiency. Therefore, given that the major challenges of scrap inspection include the many categories of scrap, complex actual detection scenarios, and challenges in manual system connection, a deep learning network model CSSNet was proposed for scrap classification and rating based on the Squeeze-Excitation (SE) attention mechanism, and images of the scrap unloading process were collected for model training and validation. First, a 1∶3 physical model of scrap steel quality inspection was built to simulate this process. High-resolution visual sensors were used to collect images of diverse types of scrap steel in the scene of trucks unloading scrap steel. Then, a cross-stage local network was used to extract the features of the collected scrap images, the spatial pyramid structure was used to solve the problem of feature loss, and the attention mechanism was used to focus on the correlation between channels and retain the channel with the most feature information. Finally, model training and validation were done using two datasets containing seven labels for classification. In the model prediction stage, the constructed scrap steel quality inspection model CSSNet was used to judge the scrap steel category and quality to verify the accuracy and detection efficiency of the model. Based on the self-made scrap steel validation dataset, its performance was compared with mainstream single-stage object detection packages such as YOLOv4, YOLOv5s, and the two-stage object detection model Faster R-CNN. The model was found to be able to effectively rate different grades of scrap steel, with the classification accuracy rate of all categories has reached 83.7% and an mAP value of 88.8%. The performance of the CSSNet model is better than the other three target detection models. CSSNet can not only fully meet the needs of the actual production applications in terms of accuracy, real-time performance, and identification and rating efficiency but also surpass the traditional manual scrap quality inspection method, address multiple issues in the evaluation of scrap steel quality, and realize automated scrap steel quality testing.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by synovial inflammation, cartilage destruction, pannus formation and bone erosion. Various immune cells, including macrophages, are involved in RA pathogenesis. The heterogeneity and plasticity of macrophages render them pivotal regulators of both the induction and resolution of the inflammatory response. Predominantly, two different phenotypes of macrophages have been identified: classically activated M1 macrophages exacerbate inflammation via the production of cytokines, chemokines and other inflammatory mediators, while alternatively activated M2 macrophages inhibit inflammation and facilitate tissue repair. An imbalance in the M1/M2 macrophage ratio is critical during the initiation and progression of RA. Macrophage polarization is modulated by various transcription factors, epigenetic elements and metabolic reprogramming. Curcumin, an active component of turmeric, exhibits potent immunomodulatory effects and is administered in the treatment of multiple autoimmune diseases, including RA. The regulation of macrophage polarization and subsequent cytokine production as well as macrophage migration is involved in the mechanisms underlying the therapeutic effect of curcumin on RA. In this review, we summarize the underlying mechanisms by which curcumin modulates macrophage function and polarization in the context of RA to provide evidence for the clinical application of curcumin in RA treatment.

Introduction Rheumatoid arthritis (RA) is a progressive inflammatory autoimmune disease characterised by chronic systemic inflammation, which can cause swelling, stiffening and destruction of articular cartilage and bone. Early diagnosis and treatment of RA can improve outcomes and slow the progression of joint damage. Preliminary exploratory research had hinted an expected effect of modified Zhiwang decoction (MZWD) in treating early RA. However, few randomised clinical trials have evaluated the effectiveness of MZWD in early RA. Therefore, a parallel-group randomised controlled trial was designed to evaluate the efficacy and safety of MZWD combined with methotrexate (MTX) on early RA.Methods and analysis This is a prospective, parallel-group, single-centre randomised controlled clinical study. A total of 150 patients will be randomly assigned to either the treatment (n=75) or control group (n=75). The treatment group will receive MZWD and MTX, and the control group will receive MTX for 12 weeks. The primary outcome of this study is Disease Activity Score-28, and the secondary outcomes are Fatigue Scale-14, Visual Analogue Scale pain scores and traditional Chinese medicine symptom scores. Safety outcomes, including adverse events and results of ECG and laboratory tests, will be monitored.Ethics and dissemination Ethics approval was obtained from the Clinical Research Ethics Committee of the China-Japan Friendship Hospital (no. 2022-KY-124) on 8 July 2022. The findings will be disseminated in peer-reviewed publications.Trial registration number ClinicalTrials.gov Registry (NCT05508815).