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Statins are known to be anti-inflammatory, but the mechanism remains poorly understood. Here, we show that macrophages, either treated with statin in vitro or from statin-treated mice, have reduced cholesterol levels and higher expression of Jmjd3, a H3K27me3 demethylase. We provide evidence that lowering cholesterol levels in macrophages suppresses the adenosine triphosphate (ATP) synthase in the inner mitochondrial membrane and changes the proton gradient in the mitochondria. This activates nuclear factor kappa-B (NF-κB) and Jmjd3 expression, which removes the repressive marker H3K27me3. Accordingly, the epigenome is altered by the cholesterol reduction. When subsequently challenged by the inflammatory stimulus lipopolysaccharide (M1), macrophages, either treated with statins in vitro or isolated from statin-fed mice, express lower levels proinflammatory cytokines than controls, while augmenting anti-inflammatory Il10 expression. On the other hand, when macrophages are alternatively activated by IL-4 (M2), statins promote the expression of Arg1, Ym1, and Mrc1. The enhanced expression is correlated with the statin-induced removal of H3K27me3 from these genes prior to activation. In addition, Jmjd3 and its demethylase activity are necessary for cholesterol to modulate both M1 and M2 activation. We conclude that upregulation of Jmjd3 is a key event for the anti-inflammatory function of statins on macrophages.

The advent of immune-checkpoint inhibitors (ICIs) has revolutionized the treatment of malignant solid tumors in the last decade, producing lasting benefits in a subset of patients. However, unattended excessive immune responses may lead to immune-related adverse events (irAEs). IrAEs can manifest in different organs within the body, with pulmonary toxicity commonly referred to as immune checkpoint inhibitor-related pneumonitis (CIP). The CIP incidence remains high and is anticipated to rise further as the therapeutic indications for ICIs expand to encompass a wider range of malignancies. The diagnosis and treatment of CIP is difficult due to the large individual differences in its pathogenesis and severity, and severe CIP often leads to a poor prognosis for patients. This review summarizes the current state of clinical research on the incidence, risk factors, predictive biomarkers, diagnosis, and treatment for CIP, and we address future directions for the prevention and accurate prediction of CIP.

Epicardial adipose tissue (EAT) significantly contributes to the progression of cardiovascular diseases (CVDs). However, manually quantifying EAT volume is labor-intensive and susceptible to human error. Although there have been some deep learning-based methods for automatic quantification of EAT, they are mostly uninterpretable and fail to harness the complete anatomical characteristics. In this study, we proposed an enhanced deep learning method designed for EAT quantification on coronary computed tomography angiography (CCTA) scan, which integrated both data-driven method and specific morphological information. A total of 108 patients who underwent routine CCTA examinations were included in this study. They were randomly assigned to training set (n = 60), validation set (n = 8), and test set (n = 40). We quantified and calculated the EAT volume based on the CT attenuation values within the predicted pericardium. The automatic method demonstrated strong agreement with expert manual quantification, yielding a median Dice score coefficients (DSC) of 0.916 (Interquartile Range (IQR): 0.846–0.948) for 2D slices. Meanwhile, the median DSC for the 3D volume was 0.896 (IQR: 0.874–0.908) between these two measures, with an excellent correlation of 0.980 (p < 0.001) for EAT volumes. Additionally, our model's Bland-Altman analysis revealed a low bias of -2.39 cm³. The incorporation of pericardial anatomical structures into deep learning methods can effectively enhance the automatic quantification of EAT. The promising results demonstrate its potential for clinical application. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) inflicts terrifying consequences, which can cause permanent paralysis. During acute SCI, the damaged tissue undergoes pathological processes such as ischemia, hypoxia, and edema, simultaneously causing a significant accumulation of reactive oxygen species (ROS) in the injured spinal cord. The continuous accumulation of ROS destroys cell integrity, promotes the secretion of proinflammatory factors, and further exacerbates edema and necrosis in the damaged spinal cord tissue, ultimately leading to neuronal apoptosis and failure of axon regeneration. Therefore, it is crucial to combat oxidative stress following SCI. In our study, we utilized environmentally friendly methods to extract Onion exosomes (Onion-ex), which inherit onions' antioxidant, anti-inflammatory, and neuroprotective properties of onions. Surprisingly, we observed that Onion-ex had an unexpected positive impact on functional recovery following SCI. Furthermore, our findings indicate that the antioxidative stress mechanism of Onion-ex depends on the KEAP1/NRF2/ARE signaling pathway. Onion-ex's remarkable therapeutic effects and biological safety provide valuable insights for clinical treatment involving plant-derived exosomes. [ABSTRACT FROM AUTHOR]

Introduction: Aconiti lateralis radix praeparata (ALRP), the sub root of Aconitum carmichaelii Debx., is a traditional Chinese medicine with good pharmacological effects. Heishunpian (HSP), prepared through the process of brine immersing, boiling, rinsing, dyeing, and steaming ALRP is one of the most widely used forms of decoction pieces in clinical practice. Objectives: This study aims to investigate the mechanisms of component changes and transformations during the processing from ALRP to HSP, and to screen for their quality markers through UHPLC‐QTOF‐MS analysis. Methods: Samples from ALRP to HSP during processing were prepared and analyzed by UHPLC‐QTOF‐MS. By comparing the differences between before and after each processing step, the purpose of processing and the transformation of components during processing were studied. In addition, multiple batches of ALRP and HSP were determined, and potential quality markers were screened. Results: Through the analysis of ALRP and five key processing samples, 55 components were identified. Immersing in brine, rinsing, and dyeing were the main factors of component loss, and boiling caused a slight loss of components. Some components were enhanced during the steaming process. Combining the screened differences components between multiple ALRP and HSP, 10 components were considered as potential quality biomarkers. Conclusion: This study found that the adjacent hydroxyl groups of the ester group may have a positive impact on the hydrolysis of the ester group, and 10 quality markers were preliminarily screened. It provides a reference for quality control and clinical application of ALRP and HSP. To screen quality markers based on the processing of Aconiti lateralis radix praeparata (ALRP) to Heishunpian (HSP), samples during processing and multiple batches of ALRP and HSP were prepared and analyzed by UHPLC‐QTOF‐MS. Fifty‐five components were identified, including diterpenoid alkaloids, isoquinoline alkaloids, and organic amine alkaloids. Immersing in brine, rinsing, and dyeing were the main factors of component loss, and some components were enhanced during the steaming process. Ten components were considered as potential quality markers. [ABSTRACT FROM AUTHOR]

The advent of immune-checkpoint inhibitors (ICIs) has revolutionized the treatment of malignant solid tumors in the last decade, producing lasting benefits in a subset of patients. However, unattended excessive immune responses may lead to immune-related adverse events (irAEs). IrAEs can manifest in different organs within the body, with pulmonary toxicity commonly referred to as immune checkpoint inhibitor-related pneumonitis (CIP). The CIP incidence remains high and is anticipated to rise further as the therapeutic indications for ICIs expand to encompass a wider range of malignancies. The diagnosis and treatment of CIP is difficult due to the large individual differences in its pathogenesis and severity, and severe CIP often leads to a poor prognosis for patients. This review summarizes the current state of clinical research on the incidence, risk factors, predictive biomarkers, diagnosis, and treatment for CIP, and we address future directions for the prevention and accurate prediction of CIP. [ABSTRACT FROM AUTHOR]

Background: Pyroptosis is an inflammatory type of programmed cell death, and could overcome the drug-resistance induced by anti-apoptotic effect of cancers. Carvedilol (CVL), a β-adrenergic receptors antagonist, has shown anti-inflammatory response and anti-cancer effect. The aim of this study is to investigate whether pyroptosis can be activated by CVL in prostate cancer (PCa). Methods and results: Datasets were used to analyze the expressions of pyroptosis-related proteins. Intracellular morphological change, cell viability, LDH and Il-1β release by cells,, and Hoechst/PI staining were used to detect the occurrence of pyroptosis. Realtime-PCR, western blot, immunofluorescence, and immunohistochemistry (IHC) were used to investigate the expressions of pyroptosis-related proteins. Datasets analyze showed the expressions of NLRP3, Caspase 1, ASC and GSDMD were all decreased in PCa comparing with normal tissues, but without prognostic significance. CVL treatment weakened the viabilities of PCa cells. Cell morphology changing, cytoplasmic vacuole formation, membrane integrity loss, LDH and IL-1β release and PI positive cells increasing were observed. NLRP3, Caspase 1, ASC, GSDMD and N-GSDMD expressions were elevated after CVL treatment, accompanied by a tendency of NF-κB transferring into nucleus. In vivo, CVL inhibited the growth of subcutaneous transplanted tumor. IHC showed CVL increased the expressions of NLRP3, ASC, and GSDMD, and decreased the expression of Ki-67 in transplanted tumor tissues. Conclusion: This study demonstrated that CVL could induce pyroptosis in PCa cells through NLRP3-caspase1-ASC inflammasome by promoting nuclear translocation of NF-κB, which would lay a foundation for the application of adrenergic receptor antagonist in PCa. [ABSTRACT FROM AUTHOR]

Qingpi, a well‐known traditional Chinese medicine for qi‐regulating and commonly processed into three types of pieces, has been widely used in the clinical application of liver disease for thousands of years. In this study, an ultra‐high‐performance liquid chromatography‐quadrupole‐time of flight‐mass spectrometry approach along with multivariate statistical analysis was developed to assess and characterize the differentiations of three processed products and confirm the potential quality markers of Qingpi. In addition, a systematic analysis combined with network pharmacology and molecular docking was performed to clarify the potential mechanism of Qingpi for the treatment of liver disease. As a result, 18 components were identified and an integrated network of Qingpi‐Components‐Target‐Pathway‐Liver Disease was constructed. Eight compounds were finally screened out as the potential quality markers acting on ten main targets and pathways of liver disease. Molecular docking analysis results indicated that the quality markers had a good binding activity with the targets. Overall, this work preliminarily identified the potential quality markers of three processed products of Qingpi, and predicted its targets in the prevention and treatment of liver disease, which can provide supporting information for further study of the pharmacodynamic substances and mechanisms of Qingpi. [ABSTRACT FROM AUTHOR]

Benzimidazoles (BMZs) are a class of veterinary drugs with a benzimidazole ring, the abuse of which poses a serious threat to ecological balance and human health. Consequently, the development of broad-spectrum antibodies and rapid assays are crucial for detecting BMZs in food samples. Herein, we scientifically designed three hapten structures, predicted the availability of the hapten with computational chemistry, and subsequently verified the broad-spectrum with immunological experiments. A broad-spectrum monoclonal antibody (6F10) was prepared based on the predicted hapten-2. Molecular recognition studies illustrated intricate interactions between mAb 6F10 binding to BMZs attributed to halogen bonds and π-π/π-alkyl interactions, revealing key amino acid sites and demonstrating the reliability of the hapten prediction strategies. Finally, a broad-spectrum, rapid, and sensitive lateral flow immunoassay based on aggregation-induced emission microspheres with high fluorescence intensity was established. The LOD values of the proposed method for eight kinds of BMZs were 0.027, 0.032, 0.058, 0.091, 0.087, 0.246, 0.369, and 0.311 ng mL -1 , respectively. In this work, a hapten prediction strategy based on a computational chemistry method effectively guided the preparation of antibodies for broad-spectrum recognition of BMZs, and the molecular recognition studies verified the interaction of mAb 6F10 with BMZs, enabling broad-spectrum and sensitive detection of BMZs in milk., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: This study aimed to investigate cortical activation and functional connectivity in the cortex during working memory (WM) tasks in patients with Alzheimer's disease (AD) using functional near-infrared spectroscopy (fNIRS)., Methods: A total of 17 older adults with AD and 17 cognitively normal (CN) participants were recruited. fNIRS was utilized to monitor oxygenated hemoglobin (HbO) concentrations in the frontotemporal lobe, while participants performed WM tasks to examine WM impairments in subjects with AD. Student's t-test for continuous variables and the chi-square test for categorical variables were used to compare the clinical and HbO variables between the AD and CN groups. Functional connectivity was analyzed using Pearson's correlation coefficient between the time series of each channel-to-channel pair., Results: The changes in HbO concentrations and cortical activations during the WM task showed that the HbO concentration curve of the CN group was higher than that of the AD group during the encoding and maintenance phases of the WM task. Although in the brain region scale, there were no significant differences in average HbO concentrations between the two groups, many channels located in the frontal and temporal lobes showed significant differences ( p  < 0.05) in the average HbO (channels 7 and 32) and slope HbO values (channels 7, 8, 9, 23, 30, 34, and 38) during the WM task. The average functional connectivity of the AD group was significantly lower than that of the CN group ( p  < 0.05). The functional connectivity was stronger in the frontopolar (FP) region than in other areas in both groups., Conclusion: This study revealed there were significant differences in HbO concentration in older adult patients with AD compared to CN during the WM task. The characteristics of HbO measured by the fNIRS technique can be valuable for distinguishing between AD and CN in older adults., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ruan, Li, Xu, Zhao, Mei and Zheng.)

Background: Perception is frequently impaired in patients with Alzheimer's disease (AD). Several patients exhibit visual or haptic hallucinations., Case Summary: A 71-year-old Chinese man presented with visual and haptic hallucinations he had been experiencing for 2 weeks. The clinical manifestations were the feeling of insects crawling and biting the limbs and geison. He looked for the insects while itching and scratching, which led to skin breakage on the limbs. He was treated with topical and anti-allergic drugs in several dermatology departments without any significant improvement. After admission, the patient was administered risperidone (0.5 mg) and duloxetine (2 mg/day). One week later, the dose of risperidone was increased to 2 mg/day, and that of duloxetine was increased to 60 mg/day. After 2 weeks of treatment, the patient's sensation of insects crawling and biting disappeared, and his mood stabilized., Conclusion: This patient manifested psychiatric behavioral symptoms caused by AD brain atrophy. It was important to re-evaluate the patient's cognitive-psychological status when the patient repeatedly went to the hospital for treatment. Follow-up attention to cognitive function and the consideration of perceptual deficits as early manifestations of AD should be considered., Competing Interests: Conflict-of-interest statement: The authors declare that they have no conflict of interest., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Surface-enhanced Raman spectroscopy (SERS), a rapid, low-cost, non-invasive, ultrasensitive, and label-free technique, has been widely used in-situ and ex-situ biomedical diagnostics questions. However, analyzing and interpreting the untargeted spectral data remains challenging due to the difficulty of designing an optimal data pre-processing and modelling procedure. In this paper, we propose a Multi-branch Attention Raman Network (MBA-RamanNet) with a multi-branch attention module, including the convolutional block attention module (CBAM) branch, deep convolution module (DCM) branch, and branch weights, to extract more global and local information of characteristic Raman peaks which are more distinctive for classification tasks. CBAM, including channel and spatial aspects, is adopted to enhance the distinctive global information on Raman peaks. DCM is used to supplement local information of Raman peaks. Autonomously trained branch weights are applied to fuse the features of each branch, thereby optimizing the global and local information of the characteristic Raman peaks for identifying diseases. Extensive experiments are performed for two different neurological disorders classification tasks via untargeted serum SERS data. The results demonstrate that MBA-RamanNet outperforms commonly used CNN methods with an accuracy of 88.24% for the classification of healthy controls, mild cognitive impairment, Alzheimer's disease, and Non-Alzheimer's dementia; an accuracy of 90% for the classification of healthy controls, elderly depression, and elderly anxiety., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 Optica Publishing Group.)