Pyrus betulaefolia ERF3 interacts with HsfC1a to coordinately regulate aquaporin PIP1;4 and NCED4 for drought tolerance.

Environmental disasters like drought reduce agricultural output and plant growth. Redox management significantly affects plant stress responses. An earlier study found that PbPIP1;4 transports H2O2 and promotes H2O2 downstream cascade signaling to restore redox equilibrium. However, this regulatory mechanism requires additional investigation. In this search, the AP2 domain-containing transcription factor was isolated by screening Y1H from the wild pear (Pyrus betulaefolia) cDNA library, named PbERF3. The overexpression of PbERF3 in pear callus and Arabidopsis enhanced plant resistance to drought and re-established redox balance. The transcripts of the NCEDs gene were upregulated under drought stress. The drought stress-related abscisic acid (ABA) signaling pathway modulates PbERF3. PbERF3 silencing lowered drought tolerance. Furthermore, yeast 2-hybrid, luciferase, bimolecular fluorescence complementation, and co-immunoprecipitation assays verified that PbERF3 physically interacted with PbHsfC1a. The PbERF3-PbHsfC1a heterodimer coordinately bound to PbPIP1;4 and PbNCED4 promoter, therefore activating both the H2O2 and the ABA signaling pathway. This work revealed a novel PbERF3-PbHsfC1a-PbNCED4-PbPIP1;4 regulatory module, in which PbERF3 interacts with PbHsfC1a to trigger the expression of target genes. This module establishes an interaction between the H2O2 signaling component PbPIP1;4 and the ABA pathways component PbNCED4, enabling a response to drought.

Ecdysterone improves oxidative damage induced by acute ischemic stroke via inhibiting ferroptosis in neurons through ACSL4.

ETHNOPHARMACOLOGICAL RELEVANCE: Acute ischemic stroke (AIS) is a prominent cause of disability and mortality around the world. Achyranthes bidentata Blume, a regularly prescribed traditional Chinese herb, plays a significant role in traditional Chinese stroke therapy due to its ability to promote blood circulation and remove stasis. Ecdysterone (EDS) is one of the key active components in Achyranthes bidentata Blume, which exhibits antioxidant and anti-cerebral hypoxia properties. However, whether EDS improves AIS and the mechanism of action of AIS is still unclear. AIM OF THE STUDY: The objective of this study was to observe whether EDS ameliorates oxidative damage caused by AIS by inhibiting ferroptosis in neurons via ACSL4. MATERIALS AND METHODS: In vivo, the Middle cerebral artery occlusion (MCAO) rat model was established for research. After treatment with EDS, Neurologic score, TTC, HE and FJC staining were performed, followed by measurements of oxidative stress-related indicators, the content of Fe2+, iron deposition levels and expression of ACSL4, NCOA4 and FTH1 in brain tissue. In vitro, oxygen-glucose deprivation and reperfusion (OGD/R) cell model was established. After treatment with EDS, cell viability, oxidative stress-related indicators, the content of Fe2+ and expression of ACSL4, NCOA4 and FTH1 were detected. In addition, the overexpression of ACSL4 and CETSA technology further elucidated that EDS improves AIS through ACSL4. RESULTS: The results showed that the treatment of EDS could improve the oxidative damage of MCAO rats by inhibiting ferroptosis, and then improve AIS. Importantly, EDS inhibited ferroptosis via ACSL4, thereby inhibiting oxidative stress in MCAO rats or OGD/R-induced PC12 cells. CONCLUSIONS: These results provide evidence that EDS ameliorates oxidative damage caused by AIS by inhibiting ferroptosis via ACSL4, and provide new insights into the potential use of EDS as an effective drug development candidate for AIS.

PuNDH9, a subunit of ETC Complex I regulates plant defense by interacting with PuPR1.

NAD+ and NADH play critical roles in energy metabolism, cell death, and gene expression. The NADH-ubiquinone oxidoreductase complex (Complex I) has been long known as a key enzyme in NAD+ and NADH metabolism. In the present study, we found and analyzed a new subunit of Complex I (NDH9), which was isolated from Pyrus ussuriensis combined with RT-PCR. Following infection with A. alternata, RT-qPCR analysis demonstrated an increase in the expression of PuNDH9. Genetic manipulation of PuNDH9 levels suggested that PuNDH9 plays key roles in NADH/NAD+ homeostasis, defense enzyme activities, ROS generation, cell death, gene expression, energy metabolism, and mitochondrial functions during the pear- A. alternata interaction. Furthermore, Y2H, GST-pull down, and a split-luciferase complementation imaging assays revealed that PuNDH9 interacts with PuPR1. We discover that PuNDH9 and PuPR1 synergistically activate defense enzyme activities, ROS accumulation, cell death, and plant defenses. Collectively, our findings reveal that PuNDH9 is likely important for plant defenses.

PbWRKY18 promotes resistance against black spot disease by activation of the chalcone synthase gene PbCHS3 in pear.

Flavonoids are plant pigments that play a major role in plant defense and have significant health benefits to humans. Chalcone synthase (CHS) is an important enzyme in flavonoid biosynthesis and investigation transcription factors (TFs) regulating its expression and downstream targets is critical to understanding its mechanism. Here, a novel TF, PbWRKY18, was isolated from the pear Pyrus betulaefolia. Its expression was evaluated in various tissues by RT-PCR, particularly in response to Alternaria alternata, the pathogen responsible for black spot disease, and exogenous hormone administration. The PbWRKY18 protein was primarily found in the nucleus where it regulated transcriptional activity. Yeast one-hybrid and dual-luciferase reporter assays showed a strong association between PbWRKY18 and the PbCHS3 promoter, which drives PbCHS3 expression. It was also found that PbCHS3 was critical for the development of resistance against black spot disease. In addition, PbWRKY18 was found to significantly increase the expression of PbCHS3 and salicylic acid-related genes, as well as defense enzyme activity and tolerance to black spot disease. PbWRKY18 or PbCHS3 knockdown in pear attenuates resistance to Alternaria alternata. In summary, the study identified a novel WRKY18-CHS3 axis involved in resistance against black spot disease in pear.

Tet1/DLL3/Notch1 signal pathway affects hippocampal neurogenesis and regulates depression-like behaviour in mice.

Ten-eleven translocation protein 1 (Tet1) is associated with the regulation of depression-like behaviour in mice. However, the mechanism by which Tet1 affects neurogenesis in mice to regulate depression-like behaviours remains unclear. In this study, the chronic social defeat stress (CSDS) paradigm was constructed by overexpressing Tet1 protein in the mouse hippocampus, and 5-ethynyl-2'-deoxyuridine (EdU, 50 mg/kg) was injected on the seventh day to explore the mechanism of the regulation of the Tet1/Delta-like protein 3 (DLL3)/Notch1 protein pathway in mice hippocampal neurogenesis and its influence on depression-like behaviour. Following CSDS, the expression level of Tet1 decreased significantly. Moreover, due to the downregulation of Tet1 protein, the maintenance of the DNA methylation and demethylation balance was affected, resulting in a significant increase in the methylation levels of Notch1 and DLL3 and a significant decrease in the protein expression levels of DLL3, Notch1, and brain-derived neurotrophic factor (BDNF). At the same time, the proliferation and differentiation of neurones were affected, which was related to a significant decrease in the number of EdU+, doublecortin (DCX)+, and Ki67+ cells in the hippocampus of the CSDS model mice. When the Tet1 protein was overexpressed in the mouse hippocampus, DLL3 and Notch1 protein expression levels were upregulated, promoting hippocampal neurogenesis and alleviating depression-like behaviour in mice. These findings suggest that regulation of the hippocampal Tet1/DLL3/Notch1 protein pathway to influence neurogenesis may be a therapeutic strategy for depression.

Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

OBJECTIVES: To prospectively investigate whether fully automated artificial intelligence (FAAI)-based coronary CT angiography (CCTA) image processing is non-inferior to semi-automated mode in efficiency, diagnostic ability, and risk stratification of coronary artery disease (CAD). MATERIALS AND METHODS: Adults with indications for CCTA were prospectively and consecutively enrolled at two hospitals and randomly assigned to either FAAI-based or semi-automated image processing using equipment workstations. Outcome measures were workflow efficiency, diagnostic accuracy for obstructive CAD (≥ 50% stenosis), and cardiovascular events at 2-year follow-up. The endpoints included major adverse cardiovascular events, hospitalization for unstable angina, and recurrence of cardiac symptoms. The non-inferiority margin was 3 percentage difference in diagnostic accuracy and C-index. RESULTS: In total, 1801 subjects (62.7 ± 11.1 years) were included, of whom 893 and 908 were assigned to the FAAI-based and semi-automated modes, respectively. Image processing times were 121.0 ± 18.6 and 433.5 ± 68.4 s, respectively (p <0.001). Scan-to-report release times were 6.4 ± 2.7 and 10.5 ± 3.8 h, respectively (p < 0.001). Of all subjects, 152 and 159 in the FAAI-based and semi-automated modes, respectively, subsequently underwent invasive coronary angiography. The diagnostic accuracies for obstructive CAD were 94.7% (89.9-97.7%) and 94.3% (89.5-97.4%), respectively (difference 0.4%). Of all subjects, 779 and 784 in the FAAI-based and semi-automated modes were followed for 589 ± 182 days, respectively, and the C-statistic for cardiovascular events were 0.75 (0.67 to 0.83) and 0.74 (0.66 to 0.82) (difference 1%). CONCLUSIONS: FAAI-based CCTA image processing significantly improves workflow efficiency than semi-automated mode, and is non-inferior in diagnosing obstructive CAD and risk stratification for cardiovascular events. CLINICAL RELEVANCE STATEMENT: Conventional coronary CT angiography image processing is semi-automated. This observation shows that fully automated artificial intelligence-based image processing greatly improves efficiency, and maintains high diagnostic accuracy and the effectiveness in stratifying patients for cardiovascular events. KEY POINTS: • Coronary CT angiography (CCTA) relies heavily on high-quality and fast image processing. • Full-automation CCTA image processing is clinically non-inferior to the semi-automated mode. • Full automation can facilitate the application of CCTA in early detection of coronary artery disease.

Saikosaponin-d alleviates depression by promoting NLRP3 ubiquitination and inhibiting inflammasome activation.

Saikosaponin-d (SSd) is a triterpene saponin from the roots of Bupleurum chinese. Recent studies have revealed its antidepressant activity, but its mechanism involved is unclear. This study's objective was to ascertain how SSd may reduce depression in depressed mice subjected to chronic unpredictable animal stress (CUMS) and to investigate the mechanisms underlying these effects. Models of CUMS depression were established and different groups were treated with SSd and escitalopram. After the last day of administration of the treatment, behavioral tests were performed. ELISA was used to measure the expression of IL-1ß, TNF-α, and IL-18, and western blot was used to measure the presence of proteins associated with NLRP3. Hippocampal neuronal damage was observed using Nissl staining, and NLRP3 ubiquitination assay was performed by immunoprecipitation and gene silencing. An inflammatory cell model was constructed by treating BV2 cells with lipopolysaccharides (LPS) and adenosine triphosphate (ATP) to verify the ubiquitination modification of NLRP3 by SSd. Behavioral tests demonstrated that SSd effectively alleviated depression-like symptoms. SSd should substantially limit the degrees of proteins associated with NLRP3, as properly as limit the harm to hippocampal neurons. Gene silencing results showed that SSd regulates NLRP3 through the E3 ubiquitin ligase MARCHF7. In vitro, SSd remarkably increased the protein expression of K48-linked ubiquitin in inflammatory BV2 cells, while decreasing the protein levels of NLRP3. Our findings suggest that SSd has antidepressant effects in CUMS mice by promoting ubiquitination of NLRP3 to inhibit inflammasome activation and improve the inflammatory state.

MR imaging characteristics of different pathologic subtypes of esophageal carcinoma.

OBJECTIVES: To describe the specific MRI characteristics of different pathologic subtypes of esophageal carcinoma (EC) METHODS: This prospective study included EC patients who underwent esophageal MRI and esophagectomy between April 2015 and October 2021. Pathomorphological characteristics of EC such as localized type (LT), ulcerative type (UT), protruding type (PT), and infiltrative type (IT) were assessed by two radiologists relying on the imaging characteristics of tumor, especially the specific imaging findings on the continuity of the mucosa overlying the tumor, the opposing mucosa, mucosa linear thickening, and transmural growth pattern. Intraclass correlation coefficients (ICC) were calculated for the consistency between two readers. The associations of imaging characteristics with different pathologic subtypes were assessed using multilogistic regression model (MLR). RESULTS: A total of 201 patients were identified on histopathology with a high inter-reader agreement (ICC = 0.991). LT showed intact mucosa overlying the tumor. IT showed transmural growth pattern extending from the mucosa to the adventitia and a "sandwich" appearance. The remaining normal mucosa on the opposing side was linear and nodular in UT. PT showed correlation with T1 staging and grade 1; IT showed correlation with T3 staging and grades 2-3. Four MLR models showed high predictive performance on the test set with AUCs of 0.94 (LT), 0.87 (PT), 0.96 (IT), and 0.97 (UT), respectively, and the predictors that contributed most to the models matched the four specific characteristics. CONCLUSIONS: Different pathologic subtypes of EC displayed specific MR imaging characteristics, which could help predict T staging and the degree of pathological differentiation. CLINICAL RELEVANCE STATEMENT: Different pathologic subtypes of esophageal carcinoma displayed specific MR imaging characteristics, which correspond to differences in the degree of differentiation, T staging, and sensitivity to radiotherapy, and could also be one of the predictive factors of cause-specific survival and local progression-free rates. KEY POINTS: Different types of EC had different characteristics on MR images. A total of 91/95 (96%) LTEC showed intact mucosa over the tumor, while masses or nodules are specific to PTEC; 21/27 (78%) ITEC showed a "sandwich" sign; and 33/35 (60%) UTEC showed linear and nodular opposing mucosa. In the association of tumor type with degree of differentiation and T staging, PTEC was predominantly associated with T1 and grade 1, and ITEC was associated with T3 and grades 2-3, while LTEC and UECT were likewise primarily linked with T2-3 and grades 2-3.

Inhibition of IL-6 methylation by Saikosaponin C regulates neuroinflammation to alleviate depression.

PURPOSE: Saikosaponin C (SSc) increases the expression of synaptic proteins and has a unexplored role in the prevention of AD and other neurodegeneration in humans. Therefore, we hypothesized that SSc has the potential to relief of depressive symptoms. Here, our study assessed the role of SSc on depression-like behaviors caused by a chronic social defeat stress (CSDS) in mice and explored the underlying mechanisms. METHODS: Behavioral tests were conducted to verify the efficacy of SSC in treating depression-like behavior in mice. The levels of IL-6, TNF-α and IL-1ß in brain tissue and BV2 cells were determined by ELISA. The effect of SSc on dendritic spine density was determined by Golgi staining. The percentage of monocytes in peripheral blood was measured using flow cytometry. The levels of STAT3 and DNMT1 under the influence of SSc were assessed by immunofluorescence. Protein expression of DNMT1, DNMT3a, DNMT3b, p-STAT3 and STAT3 in brain and BV2 cells was studied by Western blot. OE-DNMT1 was induced in the experiment to verify the inhibitory effect of DNMT1 on IL-6 methylation in SSC. Luciferase was used to detect SSC specific fragments affecting IL-6 methylation. RESULT: SSC treatment significantly alleviated depressive-like behavior, inhibited the levels of inflammatory cytokines including IL-6, IL-1ß and TNF-α, increased dendritic spine density and promoted synaptic plasticity in mice. SSC downregulated IL-6, STAT3 and DNMT1 expression in vivo and in vitro. SSC also decreased the percentage of monocytes in peripheral blood and suppressed neuroinflammation in mice. Overexpression of DNMT1 by shRNA abolished the inhibitory effect of SSc on IL-6 methylation. CONCLUSION: This study showed that SSc reduced IL6 methylation by inhibiting DNMT1 protein, induced a decrease in IL6 expression, promoted synaptic plasticity, and attenuated CSDS-induced depression-like behavior.

Comparison of Chest Radiograph Captions Based on Natural Language Processing vs Completed by Radiologists.

Importance: Artificial intelligence (AI) can interpret abnormal signs in chest radiography (CXR) and generate captions, but a prospective study is needed to examine its practical value. Objective: To prospectively compare natural language processing (NLP)-generated CXR captions and the diagnostic findings of radiologists. Design, Setting, and Participants: A multicenter diagnostic study was conducted. The training data set included CXR images and reports retrospectively collected from February 1, 2014, to February 28, 2018. The retrospective test data set included consecutive images and reports from April 1 to July 31, 2019. The prospective test data set included consecutive images and reports from May 1 to September 30, 2021. Exposures: A bidirectional encoder representation from a transformers model was used to extract language entities and relationships from unstructured CXR reports to establish 23 labels of abnormal signs to train convolutional neural networks. The participants in the prospective test group were randomly assigned to 1 of 3 different caption generation models: a normal template, NLP-generated captions, and rule-based captions based on convolutional neural networks. For each case, a resident drafted the report based on the randomly assigned captions and an experienced radiologist finalized the report blinded to the original captions. A total of 21 residents and 19 radiologists were involved. Main Outcomes and Measures: Time to write reports based on different caption generation models. Results: The training data set consisted of 74 082 cases (39 254 [53.0%] women; mean [SD] age, 50.0 [17.1] years). In the retrospective (n = 8126; 4345 [53.5%] women; mean [SD] age, 47.9 [15.9] years) and prospective (n = 5091; 2416 [47.5%] women; mean [SD] age, 45.1 [15.6] years) test data sets, the mean (SD) area under the curve of abnormal signs was 0.87 (0.11) in the retrospective data set and 0.84 (0.09) in the prospective data set. The residents' mean (SD) reporting time using the NLP-generated model was 283 (37) seconds-significantly shorter than the normal template (347 [58] seconds; P < .001) and the rule-based model (296 [46] seconds; P < .001). The NLP-generated captions showed the highest similarity to the final reports with a mean (SD) bilingual evaluation understudy score of 0.69 (0.24)-significantly higher than the normal template (0.37 [0.09]; P < .001) and the rule-based model (0.57 [0.19]; P < .001). Conclusions and Relevance: In this diagnostic study of NLP-generated CXR captions, prior information provided by NLP was associated with greater efficiency in the reporting process, while maintaining good consistency with the findings of radiologists.

Aorta and tracheobronchial invasion in esophageal cancer: comparing diagnostic performance of 3.0-T MRI and CT.

OBJECTIVES: To compare between the diagnostic performance of 3.0-T MRI and CT for aorta and tracheobronchial invasion in patients with esophageal cancer (EC). METHODS: We prospectively included patients with pathologically confirmed EC from November 2018 to June 2021, who had baseline stage of T3-4N0-2M0 and restaging after neoadjuvant chemotherapy. All patients underwent contrast-enhanced CT and MRI of the thorax. Two independent blinded radiologists scored image quality and the presence of invasion. Agreements between the two readers were calculated using kappa test. The sensitivity, specificity, accuracy, positive predict value (PPV), and negative predict value (NPV) of MRI and CT in evaluating invasion were calculated. The net reclassification index (NRI) was used to evaluate the change in the number of patients correctly classified by MRI and CT. RESULTS: A total of 70 patients (64.8 ± 9.0 years; 53 men) were enrolled. Inter-reader agreements of image quality scores and presence of invasion by MRI and CT between the two readers were almost perfect (kappa > 0.80). The accuracy of MRI in evaluating thoracic aorta invasion was significantly higher than that of CT (reader 1: 90.0% vs. 71.4%; reader 2: 92.9% vs. 70.0%, respectively), and the accuracy of MRI in evaluating tracheobronchial invasion also was significantly higher than that of CT (reader 1: 92.9% vs. 72.9%; reader 2: 95.7% vs. 70.0%, respectively). NRI values were positive in both the evaluation of aorta and tracheobronchial invasion. CONCLUSIONS: The accuracy of 3-T MRI in determining thoracic aorta and tracheobronchial invasion is significantly higher than that of CT. KEY POINTS: • 3.0-T MRI was significantly more accurate than CT in assessing invasion of the thoracic aorta in patients with esophageal cancer. • 3.0-T MRI was also significantly more accurate than CT in assessing tracheobronchial invasion in patients with esophageal cancer. • 3.0-T MRI has a higher diagnostic performance than CT in evaluating patients with suspected aortic or tracheobronchial invasion in esophageal cancer.

Motion artifact removal in coronary CT angiography based on generative adversarial networks.

OBJECTIVES: Coronary motion artifacts affect the diagnostic accuracy of coronary CT angiography (CCTA), especially in the mid right coronary artery (mRCA). The purpose is to correct CCTA motion artifacts of the mRCA using a GAN (generative adversarial network). METHODS: We included 313 patients with CCTA scans, who had paired motion-affected and motion-free reference images at different R-R interval phases in the same cardiac cycle and included another 53 CCTA cases with invasive coronary angiography (ICA) comparison. Pix2pix, an image-to-image conversion GAN, was trained by the motion-affected and motion-free reference pairs to generate motion-free images from the motion-affected images. Peak signal-to-noise ratio (PSNR), structural similarity (SSIM), Dice similarity coefficient (DSC), and Hausdorff distance (HD) were calculated to evaluate the image quality of GAN-generated images. RESULTS: At the image level, the median of PSNR, SSIM, DSC, and HD of GAN-generated images were 26.1 (interquartile: 24.4-27.5), 0.860 (0.830-0.882), 0.783 (0.714-0.825), and 4.47 (3.00-4.47), respectively, significantly better than the motion-affected images (p < 0.001). At the patient level, the image quality results were similar. GAN-generated images improved the motion artifact alleviation score (4 vs. 1, p < 0.001) and overall image quality score (4 vs. 1, p < 0.001) than those of the motion-affected images. In patients with ICA comparison, GAN-generated images achieved accuracy of 81%, 85%, and 70% in identifying no, < 50%, and ≥ 50% stenosis, respectively, higher than 66%, 72%, and 68% for the motion-affected images. CONCLUSION: Generative adversarial network-generated CCTA images greatly improved the image quality and diagnostic accuracy compared to motion-affected images. KEY POINTS: • A generative adversarial network greatly reduced motion artifacts in coronary CT angiography and improved image quality. • GAN-generated images improved diagnosis accuracy of identifying no, < 50%, and ≥ 50% stenosis.

Benign incidental cardiac findings in chest and cardiac CT imaging.

With the continuous expansion of the disease scope of chest CT and cardiac CT, the number of these CT examinations has increased rapidly. In addition to their common indications, many incidental cardiac findings can be observed when carefully evaluating the coronary arteries, valves, pericardium, ventricles, and large vessels. These findings may have clinical significance or risk of complications, but they are sometimes overlooked or may not be described in the final reports. Although most of the incidental findings are benign, timely detection and treatment can improve the management of chronic diseases or reduce the possibility of severe complications. In this review, we summarized the imaging findings, incidence rate, and clinical relevance of some benign cardiac findings such as coronary artery calcification, aortic and mitral valve calcification, aortic calcification, cardiac thrombus, myocardial bridge, aortic dilation, cardiac myxoma, pericardial cyst, and coronary artery fistula. Reporting incidental cardiac findings will help reduce the risk of severe complications or disease deterioration and contribute to the recovery of patients.

Detections of the position-vectors of the multi targets located in a circular space based on an asymmetric coupling semiconductor lasers network.

We present a novel scheme for the detections of the position-vectors of the multi targets distributed in a circular space using multi channels of the probe chaotic waves emitted by the asymmetric coupling semiconductor lasers network (ACSLN), where these probe waves possess the attractive features of the time-space uncorrelation and wide bandwidth. Using these features, the accurate measurement for the position-vectors of the multi targets can be achieved by correlating the multi channels of the probe waves with their corresponding reference waves. The further research results show that the detections for the position-vectors of the multi targets possess very low relative errors that are no more than 0.22%. The ranging-resolutions for the multi targets located in a circular space can be achieved as high as 3 mm by optimizing some key parameters, such as injection current and injection strength. In addition, the ranging-resolutions exhibit excellent strong anti-noise performance even when the signal-to-noise ratio and relative noise intensity appear obvious enhancement. The detections for the position-vectors of the multi targets based on the ACSLN offers interesting perspectives for the potential applications in the driverless cars and the object tracking system with omnidirectional vision.

Deep optical reservoir computing and chaotic synchronization predictions based on the cascade coupled optically pumped spin-VCSELs.

In this work, we utilize two cascade coupling modes (unidirectional coupling and bidirectional coupling) to construct a four-layer deep reservoir computing (RC) system based on the cascade coupled optically-pumped spin-VCSEL. In such a system, there are double sub-reservoirs in each layer, which are formed by the chaotic x-PC and y-PC emitted by the reservoir spin-VCSEL in each layer. Under these two coupling modes, the chaotic x-PC and y-PC emitted by the driving optically-pumped spin-VCSEL (D-Spin-VCSEL), as two learning targets, are predicted by utilizing the four-layer reservoirs. In different parameter spaces, it is further explored that the outputs of the double sub-reservoirs in each layer are respectively synchronized with the chaotic x-PC and y-PC emitted by the D-Spin-VCSEL. The memory capacities (MCs) for the double sub-reservoirs in each layer are even further investigated. The results show that under two coupling modes, the predictions of the double sub-reservoirs with higher-layer for these two targets have smaller errors, denoting that the higher-layer double sub-reservoirs possess better predictive learning ability. Under the same system parameters, the outputs of the higher-layer dual parallel reservoirs are better synchronized with two chaotic PCs emitted by the D-Spin-VCSEL, respectively. The larger MCs can also be obtained by the higher-layer double reservoirs. In particular, compared with the four-layer reservoir computing system under unidirectional coupling, the four-layer reservoir computing system under bidirectional coupling shows better predictive ability in the same parameter space. The chaotic synchronizations predicted by each layer double sub-reservoirs under bidirectional coupling can be obtained higher qualities than those under unidirectional coupling. By the optimization of the system parameters, the outputs of the fourth-layer double sub-reservoirs are almost completely synchronized with the chaotic x-PC and y-PC emitted by the D-Spin-VCSEL, respectively, due to their correlation coefficient used to measure synchronization quality can be obtained as 0.99. These results have potential applications in chaotic computation, chaotic secure communication and accurate prediction of time series.

Accurate separation of mixed high-dimension optical-chaotic signals using optical reservoir computing based on optically pumped VCSELs.

In this work, with the mixing fractions being known in advance or unknown, the schemes and theories for the separations of two groups of the mixed optical chaotic signals are proposed in detail, using the VCSEL-based reservoir computing (RC) systems. Here, two groups of the mixed optical chaotic signals are linearly combined with many beams of the chaotic x-polarization components (X-PCs) and Y-PCs emitted by the optically pumped spin-VCSELs operation alone. Two parallel reservoirs are performed by using the chaotic X-PC and Y-PC output by the optically pumped spin-VCSEL with both optical feedback and optical injection. Moreover, we further demonstrate the separation performances of the mixed chaotic signal linearly combined with no more than three beams of the chaotic X-PC or Y-PC. We find that two groups of the mixed optical chaos signals can be effectively separated by using two reservoirs in single RC system based on optically pumped Spin-VCSEL and their corresponding separated errors characterized by the training errors are no more than 0.093, when the mixing fractions are known as a certain value in advance. If the mixing fractions are unknown, we utilize two cascaded RC systems based on optically pumped Spin-VCSELs to separate each group of the mixed optical signals. The mixing fractions can be accurate predicted by using two parallel reservoirs in the first RC system. Based on the values of the predictive mixing fractions, two groups of the mixed optical chaos signals can be effectively separated by utilizing two parallel reservoirs in the second RC system, and their separated errors also are no more than 0.093. In the same way, the mixed optical chaos signal linearly superimposed with more than three beams of optical chaotic signals can be effectively separated. The method and idea for separation of complex optical chaos signals proposed by this paper may provide an impact to development of novel principles of multiple access and demultiplexing in multi-channel chaotic cryptography communication.

Measurement Accuracy and Repeatability of RECIST-Defined Pulmonary Lesions and Lymph Nodes in Ultra-Low-Dose CT Based on Deep Learning Image Reconstruction.

BACKGROUND: Deep learning image reconstruction (DLIR) improves image quality. We aimed to compare the measured diameter of pulmonary lesions and lymph nodes between DLIR-based ultra-low-dose CT (ULDCT) and contrast-enhanced CT. METHODS: The consecutive adult patients with noncontrast chest ULDCT (0.07-0.14 mSv) and contrast-enhanced CT (2.38 mSv) were prospectively enrolled. Patients with poor image quality and body mass index ≥ 30 kg/m2 were excluded. The diameter of pulmonary target lesions and lymph nodes defined by Response Evaluation Criteria in Solid Tumors (RECIST) was measured. The measurement variability between ULDCT and enhanced CT was evaluated by Bland-Altman analysis. RESULTS: The 141 enrolled patients (62 ± 12 years) had 89 RECIST-defined measurable pulmonary target lesions (including 30 malignant lesions, mainly adenocarcinomas) and 45 measurable mediastinal lymph nodes (12 malignant). The measurement variation of pulmonary lesions between high-strength DLIR (DLIR-H) images of ULDCT and contrast-enhanced CT was 2.2% (95% CI: 1.7% to 2.6%) and the variation of lymph nodes was 1.4% (1.0% to 1.9%). CONCLUSIONS: The measured diameters of pulmonary lesions and lymph nodes in DLIR-H images of ULDCT are highly close to those of contrast-enhanced CT. DLIR-based ULDCT may facilitate evaluating target lesions with greatly reduced radiation exposure in tumor evaluation and lung cancer screening.

Label-Free Delineation of Human Uveal Melanoma Infiltration With Pump-Probe Microscopy.

Uveal melanoma (UM) is the most frequent primary intraocular malignancy in adults, characterized by melanin depositions in melanocytes located in the uveal tract in the eyes. Differentiation of melanin species (eumelanin and pheomelanin) is crucial in the diagnosis and management of UM, yet it remains inaccessible for conventional histology. Here, we report that femtosecond time-resolved pump-probe microscopy could provide label-free and chemical-specific detection of melanin species in human UM based on their distinct transient relaxation dynamics at the subpicosecond timescale. The method is capable of delineating the interface between melanoma and paracancerous regions on various tissue conditions, including frozen sections, paraffin sections, and fresh tissues. Moreover, transcriptome sequencing was conducted to confirm the active eumelanin synthesis in UM. Our results may hold potential for sensitive detection of tumor boundaries and biomedical research on melanin metabolism in UM.

Edaravone Dexborneol Downregulates Neutrophil Extracellular Trap Expression and Ameliorates Blood-Brain Barrier Permeability in Acute Ischemic Stroke.

Background: Our previous work has shown that inflammatory processes play a detrimental role in the pathophysiology of acute ischemic stroke (AIS). Neutrophil extracellular traps (NETs) have been recognized as a key contributor to the proinflammatory response in AIS and could aggravate blood-brain barrier (BBB) damage. Recently, experimental and clinical researches showed that Edaravone Dexborneol (Eda.B), which is comprised of two active ingredients, Edaravone and (+)-Borneol, was effective in treatment of AIS. However, it is not clear whether the effects of Eda.B against AIS are related to NETs and BBB permeability. Methods: Experiment 1 was to detect the effects of Eda.B in AIS patients. Serum samples of volunteers and AIS patients were collected before and 3 days after Edaravone Dexborneol treatment. Markers of NETs and occludin were detected by ELISA kit. Experiment 2 was to explore the effects of Eda.B on experimental stroke mice. Male C57BL/6 mice were subjected to distal middle cerebral artery occlusion (MCAO) and treated with vehicle, Eda.B, or DeoxyribonueleaseI (DNase I). After stroke, the neurobehavioral tests, infarct volume, and cerebral blood flow evaluation were determined. Leakage of Evans blue was to assess the integrity of BBB. Western blot, real-time quantitative polymerase chain reaction (RT-qPCR), and immunofluorescence were used to examine the expression of NETs and tight junction- (TJ-) associated proteins. Results: Eda.B significantly improved neurological function and cerebral blood flow but reduced infarct volume after experimental stroke. Eda.B downregulated level of NETs in serum samples of AIS patients and tissue samples of MCAO mouse cortex. Eda.B and DNase I alleviated BBB permeability by upregulating TJ-associated proteins. Conclusion: NETs are related to the early stage of AIS. Eda.B exerted neuroprotective effects and ameliorated BBB permeability after AIS.

Temperature lapse rate estimation and snowmelt runoff simulation in a high-altitude basin.

As a key parameter of hydrological process modeling, the near-surface air temperature lapse rate reflects the vertical changes in air temperature characteristics in alpine basins but often lacks the support of sufficient ground observation data. This study estimated the lapse rate of the Lhasa River Basin (LRB) from the monthly air temperature dataset (2001-2015), which was derived based on good relationships between the observed air temperature at eight gauged stations and the corresponding gridded land surface temperature of MODIS. The estimated annual average air temperature lapse rate was approximately 0.62 °C/100 m. The monthly lapse rate in different years varied seasonally in the range of 0.45-0.8 °C/100 m; the maximum was in May, and the relatively low value occurred from September to January. The snow cover in the zones with relatively low altitudes showed seasonal variation, which was consistent with the air temperature variation. Permanent snow cover appeared in the area above 5000 m and expanded with increasing elevation.