Glutathione S-transferase activity facilitates rice tolerance to the barnyard grass root exudate DIMBOA.

BACKGROUND: In paddy fields, the noxious weed barnyard grass secretes 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one (DIMBOA) to interfere with rice growth. Rice is unable to synthesize DIMBOA. Rice cultivars with high or low levels of allelopathy may respond differently to DIMBOA. RESULTS: In this study, we found that low concentrations of DIMBOA (≤ 0.06 mM) promoted seedling growth in allelopathic rice PI312777, while DIMBOA (≤ 0.08 mM) had no significant influence on the nonallelopathic rice Lemont. DIMBOA treatment caused changes in the expression of a large number of glutathione S-transferase (GST) proteins, which resulting in enrichment of the glutathione metabolic pathway. This pathway facilitates plant detoxification of heterologous substances. The basal levels of GST activity in Lemont were significantly higher than those in PI312777, while GST activity in PI312777 was slightly induced by increasing DIMBOA concentrations. Overexpression of GST genes (Os09g0367700 and Os01g0949800) in these two cultivars enhanced rice resistance to DIMBOA. CONCLUSIONS: Taken together, our results indicated that different rice accessions with different levels of allelopathy have variable tolerance to DIMBOA. Lemont had higher GST activity, which helped it tolerate DIMBOA, while PI312777 had lower GST activity that was more inducible. The enhancement of GST expression facilitates rice tolerance to DIMBOA toxins from barnyard grass root exudates.

Excessive accumulation of epicardial adipose tissue promotes microvascular obstruction formation after myocardial ischemia/reperfusion through modulating macrophages polarization.

BACKGROUND: Owing to its unique location and multifaceted metabolic functions, epicardial adipose tissue (EAT) is gradually emerging as a new metabolic target for coronary artery disease risk stratification. Microvascular obstruction (MVO) has been recognized as an independent risk factor for unfavorable prognosis in acute myocardial infarction patients. However, the concrete role of EAT in the pathogenesis of MVO formation in individuals with ST-segment elevation myocardial infarction (STEMI) remains unclear. The objective of the study is to evaluate the correlation between EAT accumulation and MVO formation measured by cardiac magnetic resonance (CMR) in STEMI patients and clarify the underlying mechanisms involved in this relationship. METHODS: Firstly, we utilized CMR technique to explore the association of EAT distribution and quantity with MVO formation in patients with STEMI. Then we utilized a mouse model with EAT depletion to explore how EAT affected MVO formation under the circumstances of myocardial ischemia/reperfusion (I/R) injury. We further investigated the immunomodulatory effect of EAT on macrophages through co-culture experiments. Finally, we searched for new therapeutic strategies targeting EAT to prevent MVO formation. RESULTS: The increase of left atrioventricular EAT mass index was independently associated with MVO formation. We also found that increased circulating levels of DPP4 and high DPP4 activity seemed to be associated with EAT increase. EAT accumulation acted as a pro-inflammatory mediator boosting the transition of macrophages towards inflammatory phenotype in myocardial I/R injury through secreting inflammatory EVs. Furthermore, our study declared the potential therapeutic effects of GLP-1 receptor agonist and GLP-1/GLP-2 receptor dual agonist for MVO prevention were at least partially ascribed to its impact on EAT modulation. CONCLUSIONS: Our work for the first time demonstrated that excessive accumulation of EAT promoted MVO formation by promoting the polarization state of cardiac macrophages towards an inflammatory phenotype. Furthermore, this study identified a very promising therapeutic strategy, GLP-1/GLP-2 receptor dual agonist, targeting EAT for MVO prevention following myocardial I/R injury.

Left atrial conduit strain derived from cardiac magnetic resonance is an independent predictor of left ventricular reverse remodeling in patients with nonischemic cardiomyopathy.

BACKGROUND: In some patients with nonischemic cardiomyopathy (NICM), left ventricular (LV) function improves with medical assistance, resulting in left ventricular reverse remodeling (LVRR). However, predictors of LVRR are not fully understood. The left atrium (LA) has been reported as a prognostic predictor in patients with heart failure (HF). The present study aimed to evaluate clinical predictors of LVRR related to LA function on cardiac magnetic resonance (CMR). METHODS: A total of 103 patients with reduced left ventricular ejection fraction (LVEF) were enrolled in this retrospective study between September 2015 and July 2021. CMR parameters, including strain data, were measured in all patients. Echocardiographic data obtained approximately 2 years after enrollment were analyzed to assess LVRR. RESULTS: LVRR occurred in 46 patients (44.7%) during follow-up. The value of LA conduit strain was higher in the LVRR group than in the non-LVRR group (6.6 [interquartile range (IQR): 5.6-9.3]% versus 5.0 [IQR: 3.0-6.2]%; p < 0.001). The multivariate logistic regression analysis showed that LA conduit strain was an independent predictor of LVRR (odds ratio [OR]: 1.216, 95% confidence interval [CI]: 1.050-1.408; p = 0.009). The area under the receiver operating characteristic (ROC) curve of the LA conduit strain was 0.746, and the cutoff value was 6.2%. The Kaplan‒Meier analysis revealed that the incidence of adverse cardiac events was significantly lower in patients with LA conduit strain > 6.2% compared to those with ⩽6.2%. (log-rank test, p = 0.019). CONCLUSIONS: LA conduit strain derived from CMR is an independent predictor of LVRR in patients with NICM.

Plasticity and crosstalk of mesenchymal stem cells and macrophages in immunomodulation in sepsis.

Sepsis is a multisystem disease characterized by dysregulation of the host immune response to infection. Immune response kinetics play a crucial role in the pathogenesis and progression of sepsis. Macrophages, which are known for their heterogeneity and plasticity, actively participate in the immune response during sepsis. These cells are influenced by the ever-changing immune microenvironment and exhibit two-sided immune regulation. Recently, the immunomodulatory function of mesenchymal stem cells (MSCs) in sepsis has garnered significant attention. The immune microenvironment can profoundly impact MSCs, prompting them to exhibit dual immunomodulatory functions akin to a double-edged sword. This discovery holds great importance for understanding sepsis progression and devising effective treatment strategies. Importantly, there is a close interrelationship between macrophages and MSCs, characterized by the fact that during sepsis, these two cell types interact and cooperate to regulate inflammatory processes. This review summarizes the plasticity of macrophages and MSCs within the immune microenvironment during sepsis, as well as the intricate crosstalk between them. This remains an important concern for the future use of these cells for immunomodulatory treatments in the clinic.

Oncoproteins E6 and E7 upregulate topoisomerase I to activate the cGAS-PD-L1 pathway in cervical cancer development.

Background: Cervical cancer (CC) stands as a significant health threat to women globally, with high-risk human papillomaviruses as major etiologic agents. The DNA damage repair (DDR) protein topoisomerase I (TOP1) has been linked to various cancers, yet its distinct roles and mechanisms in CC are not fully elucidated. Methods: We investigated TOP1 expression in cervical intraepithelial neoplasia (CIN) and CC tissues utilizing qRT-PCR and IHC, correlating findings with patient prognosis. Subsequent knockdown studies were performed in vitro and in vivo to evaluate the influence of TOP1 on tumor growth, DNA repair, and inflammatory responses. Results: TOP1 was highly expressed in CIN and CC, negatively correlating with patient prognosis. Inhibition of TOP1 impeded CC cell growth and disrupted DNA repair. TOP1 was shown to regulate tumor-promoting inflammation and programmed death-ligand 1 (PD-L1) production in a cGAS-dependent manner. HPV oncoproteins E6 and E7 upregulated TOP1 and activated the cGAS-PD-L1 pathway. Conclusions: TOP1 acts as a DNA repair mediator, promoting CC development and immune evasion. Targeting the TOP1-cGAS-PD-L1 axis could be a potential therapeutic strategy for CC.

Elevated Ozone Reduces the Quality of Tea Leaves but May Improve the Resistance of Tea Plants.

Tropospheric ozone (O3) pollution can affect plant nutritional quality and secondary metabolites by altering plant biochemistry and physiology, which may lead to unpredictable effects on crop quality and resistance to pests and diseases. Here, we investigated the effects of O3 (ambient air, Am; ambient air +80 ppb of O3, EO3) on the quality compounds and chemical defenses of a widely cultivated tea variety in China (Camellia sinensis cv. 'Baiye 1 Hao') using open-top chamber (OTC). We found that elevated O3 increased the ratio of total polyphenols to free amino acids while decreasing the value of the catechin quality index, indicating a reduction in leaf quality for green tea. Specifically, elevated O3 reduced concentrations of amino acids and caffeine but shows no impact on the concentrations of total polyphenols in tea leaves. Within individual catechins, elevated O3 increased the concentrations of ester catechins but not non-ester catechins, resulting in a slight increase in total catechins. Moreover, elevated O3 increased the emission of biogenic volatile organic compounds involved in plant defense against herbivores and parasites, including green leaf volatiles, aromatics, and terpenes. Additionally, concentrations of main chemical defenses, represented as condensed tannins and lignin, in tea leaves also increased in response to elevated O3. In conclusion, our results suggest that elevated ground-level O3 may reduce the quality of tea leaves but could potentially enhance the resistance of tea plants to biotic stresses.

Camellia sinensis polysaccharide attenuates inflammatory responses via the ROS-mediated pathway by endocytosis.

Polysaccharide CSTPs extracted from Camellia sinensis tea-leaves possessed unique against oxidative damage by scavenging ROS. Herein, acid tea polysaccharide CSTPs-2 with tightly packed molecular structure was isolated, purified and characterized in this research. Furthermore, the effects of CSTPs-2 on ROS-involved inflammatory responses and its underlying mechanisms were investigated. The results suggest that CSTPs-2 dramatically reduced the inflammatory cytokines overexpression and LPS-stimulated cell damage. CSTPs-2 could trigger the dephosphorylation of downstream AKT/MAPK/NF-κB signaling proteins and inhibit nuclear transfer of p-NF-κB to regulate the synthesis and release of inflammatory mediators in LPS-stimulated cells by ROS scavenging. Importantly, the impact of CSTPs-2 in downregulating pro-inflammatory cytokines and mitigating ROS overproduction is associated with clathrin- or caveolae-mediated endocytosis uptake mechanisms, rather than TLR-4 receptor-mediated endocytosis. This study presents a novel perspective for investigating the cellular uptake mechanism of polysaccharides in the context of anti-inflammatory mechanisms.

Automated detection and classification of coronary atherosclerotic plaques on coronary CT angiography using deep learning algorithm.

Background: Coronary artery disease (CAD) is the leading cause of mortality worldwide. Recent advances in deep learning technology promise better diagnosis of CAD and improve assessment of CAD plaque buildup. The purpose of this study is to assess the performance of a deep learning algorithm in detecting and classifying coronary atherosclerotic plaques in coronary computed tomographic angiography (CCTA) images. Methods: Between January 2019 and September 2020, CCTA images of 669 consecutive patients with suspected CAD from Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine were included in this study. There were 106 patients included in the retrospective plaque detection analysis, which was evaluated by a deep learning algorithm and four independent physicians with varying clinical experience. Additionally, 563 patients were included in the analysis for plaque classification using the deep learning algorithm, and their results were compared with those of expert radiologists. Plaques were categorized as absent, calcified, non-calcified, or mixed. Results: The deep learning algorithm exhibited higher sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy {92% [95% confidence interval (CI): 89.5-94.1%], 87% (95% CI: 84.2-88.5%), 79% (95% CI: 76.1-82.4%), 95% (95% CI: 93.4-96.3%), and 89% (95% CI: 86.9-90.0%)} compared to physicians with ≤5 years of clinical experience in CAD diagnosis for the detection of coronary plaques. The algorithm's overall sensitivity, specificity, PPV, NPV, accuracy, and Cohen's kappa for plaque classification were 94% (95% CI: 92.3-94.7%), 90% (95% CI: 88.8-90.3%), 70% (95% CI: 68.3-72.1%), 98% (95% CI: 97.8-98.5%), 90% (95% CI: 89.8-91.1%) and 0.74 (95% CI: 0.70-0.78), indicating strong performance. Conclusions: The deep learning algorithm has demonstrated reliable and accurate detection and classification of coronary atherosclerotic plaques in CCTA images. It holds the potential to enhance the diagnostic capabilities of junior radiologists and junior intervention cardiologists in the CAD diagnosis, as well as to streamline the triage of patients with acute coronary symptoms.

Correction to: Unveiling the next generation of MRI contrast agents: current insights and perspectives on ferumoxytol-enhanced MRI.

[This corrects the article DOI: 10.1093/nsr/nwae057.].

Unveiling the next generation of MRI contrast agents: current insights and perspectives on ferumoxytol-enhanced MRI.

Contrast-enhanced magnetic resonance imaging (CE-MRI) is a pivotal tool for global disease diagnosis and management. Since its clinical availability in 2009, the off-label use of ferumoxytol for ferumoxytol-enhanced MRI (FE-MRI) has significantly reshaped CE-MRI practices. Unlike MRI that is enhanced by gadolinium-based contrast agents, FE-MRI offers advantages such as reduced contrast agent dosage, extended imaging windows, no nephrotoxicity, higher MRI time efficiency and the capability for molecular imaging. As a leading superparamagnetic iron oxide contrast agent, ferumoxytol is heralded as the next generation of contrast agents. This review delineates the pivotal clinical applications and inherent technical superiority of FE-MRI, providing an avant-garde medical-engineering interdisciplinary lens, thus bridging the gap between clinical demands and engineering innovations. Concurrently, we spotlight the emerging imaging themes and new technical breakthroughs. Lastly, we share our own insights on the potential trajectory of FE-MRI, shedding light on its future within the medical imaging realm.

Performance assessment of an artificial intelligence-based coronary artery calcium scoring algorithm in non-gated chest CT scans of different slice thickness.

Background: The coronary artery calcium score (CACS) has been shown to be an independent predictor of cardiovascular events. The traditional coronary artery calcium scoring algorithm has been optimized for electrocardiogram (ECG)-gated images, which are acquired with specific settings and timing. Therefore, if the artificial intelligence-based coronary artery calcium score (AI-CACS) could be calculated from a chest low-dose computed tomography (LDCT) examination, it could be valuable in assessing the risk of coronary artery disease (CAD) in advance, and it could potentially reduce the occurrence of cardiovascular events in patients. This study aimed to assess the performance of an AI-CACS algorithm in non-gated chest scans with three different slice thicknesses (1, 3, and 5 mm). Methods: A total of 135 patients who underwent both LDCT of the chest and ECG-gated non-contrast enhanced cardiac CT were prospectively included in this study. The Agatston scores were automatically derived from chest CT images reconstructed at slice thicknesses of 1, 3, and 5 mm using the AI-CACS software. These scores were then compared to those obtained from the ECG-gated cardiac CT data using a conventional semi-automatic method that served as the reference. The correlations between the AI-CACS and electrocardiogram-gated coronary artery calcium score (ECG-CACS) were analyzed, and Bland-Altman plots were used to assess agreement. Risk stratification was based on the calculated CACS, and the concordance rate was determined. Results: A total of 112 patients were included in the final analysis. The correlations between the AI-CACS at three different thicknesses (1, 3, and 5 mm) and the ECG-CACS were 0.973, 0.941, and 0.834 (all P<0.01), respectively. The Bland-Altman plots showed mean differences in the AI-CACS for the three thicknesses of -6.5, 15.4, and 53.1, respectively. The risk category agreement for the three AI-CACS groups was 0.868, 0.772, and 0.412 (all P<0.01), respectively. While the concordance rates were 91%, 84.8%, and 62.5%, respectively. Conclusions: The AI-based algorithm successfully calculated the CACS from LDCT scans of the chest, demonstrating its utility in risk categorization. Furthermore, the CACS derived from images with a slice thickness of 1 mm was more accurate than those obtained from images with slice thicknesses of 3 and 5 mm.

Observation of Anomalous Planar Hall Effect Induced by One-Dimensional Weak Antilocalization.

The confinement of electrons in one-dimensional (1D) space highlights the prominence of the role of electron interactions or correlations, leading to a variety of fascinating physical phenomena. The quasi-1D electron states can exhibit a unique spin texture under spin-orbit interaction (SOI) and thus could generate a robust spin current by forbidden electron backscattering. Direct detection of such 1D spin or SOI information, however, is challenging due to complicated techniques. Here, we identify an anomalous planar Hall effect (APHE) in the magnetotransport of quasi-1D van der Waals (vdW) topological materials as exemplified by Bi4Br4, which arises from the quantum interference correction of 1D weak antilocalization (WAL) to the ordinary planar Hall effect and demonstrates a deviation from the usual sine and cosine curves. The occurrence of 1D WAL is correlated to the line-shape Fermi surface and persistent spin texture of (100) topological surface states of Bi4Br4, as revealed by both our angle-resolved photoemission spectroscopy and first-principles calculations. By generalizing the observation of APHE to other non-vdW bulk materials, this work provides a possible characteristic of magnetotransport for identifying the spin/SOI information and quantum interference behavior of 1D states in 3D topological material.

A base editor for the long-term restoration of auditory function in mice with recessive profound deafness.

A prevalent recessive mutation (c.2485C>T, p.Q829X) within the OTOF gene leads to profound prelingual hearing loss. Here we show that in Otof mice harbouring a mutation (c.2482C>T, p.Q828X) homozygous to human OTOF that faithfully mimics the hearing-loss phenotype, a base editor (consisting of the deaminase ABE7.10max and the Cas9 variant SpCas9-NG) packaged in adeno-associated viruses and injected into the inner ear of the mice via the round-window membrane effectively corrected the pathogenic mutation, with no apparent off-target effects. The treatment restored the levels of the otoferlin protein in 88% of the inner hair cells and stably rescued the auditory function of the mice to near-wild-type levels for over 1.5 years while improving synaptic exocytosis in the inner hair cells. We also show that an adenine base editor that targets the prevalent human OTOF mutation restored hearing in humanized mice to levels comparable to those of the wild-type counterparts. Base editors may be effective for the treatment of hereditary deafness.