Advances and prospects in deuterium metabolic imaging (DMI): a systematic review of in vivo studies.

BACKGROUND: Deuterium metabolic imaging (DMI) has emerged as a promising non-invasive technique for studying metabolism in vivo. This review aims to summarize the current developments and discuss the futures in DMI technique in vivo. METHODS: A systematic literature review was conducted based on the PRISMA 2020 statement by two authors. Specific technical details and potential applications of DMI in vivo were summarized, including strategies of deuterated metabolites detection, deuterium-labeled tracers and corresponding metabolic pathways in vivo, potential clinical applications, routes of tracer administration, quantitative evaluations of metabolisms, and spatial resolution. RESULTS: Of the 2,248 articles initially retrieved, 34 were finally included, highlighting 2 strategies for detecting deuterated metabolites: direct and indirect DMI. Various deuterated tracers (e.g., [6,6'-2H2]glucose, [2,2,2'-2H3]acetate) were utilized in DMI to detect and quantify different metabolic pathways such as glycolysis, tricarboxylic acid cycle, and fatty acid oxidation. The quantifications (e.g., lactate level, lactate/glutamine and glutamate ratio) hold promise for diagnosing malignancies and assessing early anti-tumor treatment responses. Tracers can be administered orally, intravenously, or intraperitoneally, either through bolus administration or continuous infusion. For metabolic quantification, both serial time point methods (including kinetic analysis and calculation of area under the curves) and single time point quantifications are viable. However, insufficient spatial resolution remains a major challenge in DMI (e.g., 3.3-mL spatial resolution with 10-min acquisition at 3 T). CONCLUSIONS: Enhancing spatial resolution can facilitate the clinical translation of DMI. Furthermore, optimizing tracer synthesis, administration protocols, and quantification methodologies will further enhance their clinical applicability. RELEVANCE STATEMENT: Deuterium metabolic imaging, a promising non-invasive technique, is systematically discussed in this review for its current progression, limitations, and future directions in studying in vivo energetic metabolism, displaying a relevant clinical potential. KEY POINTS: • Deuterium metabolic imaging (DMI) shows promise for studying in vivo energetic metabolism. • This review explores DMI's current state, limits, and future research directions comprehensively. • The clinical translation of DMI is mainly impeded by limitations in spatial resolution.

Acceleration of uterine 3D T2 weighted imaging by compressed SENSE--a multicenter study.

OBJECTIVES: To find the optimal acceleration factor (AF) of the compressed SENSE (CS) technique for uterine isotropic high-resolution 3D T2-weighted imaging (3D-ISO-T2WI). METHODS: A total of 91 female volunteers from the XXX, XXX and XXX were recruited. A total of 44 volunteers received uterus sagittal 3D-ISO-T2WI scans on 3.0 T MRI device with different CS AFs (including SENSE3, CS3, CS4, CS5, CS6, and CS7), 51 received 3D-ISO-T2WI scans with different degrees of fat suppression (none, light, moderate, and severe), while 4 volunteers received both series of scans. Image quality was subjectively evaluated with a three-point scoring system. Junction zone signal-to-noise ratio (SNR) and contrast to noise ratio (CNR) and myometrial SNR were also calculated. Intraclass correlation coefficients (ICC) were used to analyze the consistency of the measurement results by two observers. ANOVA test or Friedman rank sum test was used to compare the differences in subjective scores, SNR and CNR under different AFs/different degrees of fat suppression. RESULTS: Images by AFs of CS3, CS4, and CS5 had the highest SNR and CNR. Among them, CS5 had the shortest scan time. CS5 also had one of the highest subjective scores. There was no significant difference in SNR and CNR among images acquired with different degrees of fat suppression. Also, images with moderate fat suppression had the highest subjective scores. CONCLUSION: The CS5 combined with moderate fat suppression is recommended for routine female pelvic 3D-ISO-T2WI scan. ADVANCES IN KNOWLEDGE: The CS5 has the highest images quality and has the shortest scan time, which is the best AF. Moderate fat suppression has the highest subjective scores. The CS5 and moderate fat suppression are the best combination for female pelvic 3D-ISO-T2WI scan.

A vision chip with complementary pathways for open-world sensing.

Image sensors face substantial challenges when dealing with dynamic, diverse and unpredictable scenes in open-world applications. However, the development of image sensors towards high speed, high resolution, large dynamic range and high precision is limited by power and bandwidth. Here we present a complementary sensing paradigm inspired by the human visual system that involves parsing visual information into primitive-based representations and assembling these primitives to form two complementary vision pathways: a cognition-oriented pathway for accurate cognition and an action-oriented pathway for rapid response. To realize this paradigm, a vision chip called Tianmouc is developed, incorporating a hybrid pixel array and a parallel-and-heterogeneous readout architecture. Leveraging the characteristics of the complementary vision pathway, Tianmouc achieves high-speed sensing of up to 10,000 fps, a dynamic range of 130 dB and an advanced figure of merit in terms of spatial resolution, speed and dynamic range. Furthermore, it adaptively reduces bandwidth by 90%. We demonstrate the integration of a Tianmouc chip into an autonomous driving system, showcasing its abilities to enable accurate, fast and robust perception, even in challenging corner cases on open roads. The primitive-based complementary sensing paradigm helps in overcoming fundamental limitations in developing vision systems for diverse open-world applications.

Raman Monitoring of the Electro-Optical Synergy-Induced Enhancements in Carbon-Bromine Bond Cleavage, Reaction Rate, and Product Selectivity of p-Bromothiophenol.

Electro-optical synergy has recently been targeted to improve the separation of hot carriers and thereby further improve the efficiency of plasmon-mediated chemical reactions (PMCRs). However, the electro-optical synergy in PMCRs needs to be more deeply understood, and its contribution to bond dissociation and product selectivity needs to be clarified. Herein, the electro-optical synergy in plasmon-mediated reduction of p-bromothiophenol (PBTP) was studied on a plasmonic nanostructured silver electrode using in situ Raman spectroscopy and theoretical calculations. It was found that the electro-optical synergy-induced enhancements in the cleavage of carbon-bromine bonds, reaction rate, and product selectivity (4,4'-biphenyl dithiol vs thiophenol) were largely affected by the applied bias, laser wavelength, and laser power. The theoretical simulation further clarified that the strong electro-optical synergy is attributed to the matching of energy band diagrams of the plasmonic silver with those of the adsorbed PBTP molecules. A deep understanding of the electro-optical synergy in PBTP reduction and the clarification of the mechanism will be highly beneficial for the development of other highly efficient PMCRs.

Intraspecific transitioning of ecological strategies in Pinus massoniana trees across restoration stages.

Intraspecific variation in plant functional traits and ecological strategies is typically overlooked in most studies despite its pivotal role at the local scales and along short environmental gradients. While CSR theory has been used to classify ecological strategies (competitive C; stress-tolerant, S; ruderal, R) in different plant species, its ability to explain intraspecific variation in ecological strategies remains uncertain. Here, we sought to investigate intraspecific variation in ecological strategies for Pinus massoniana, a pioneer conifer tree for ecological restoration in Changting County, southeast China. By measuring key leaf traits and canopy height of 252 individuals at different ontogenetic stages from three plots spanning distinctive stages along early ecological restoration and calculating their C, S, and R scores, we constructed an intraspecific CSR system. All individual strategies shifted across three restoration stages, with adults from higher S component to higher C component while juveniles from higher S component to higher R component. Our results suggest that while strategies of all P. massoniana individuals start with tolerance to environmental stress, as restoration proceeds, adult transition towards completion for light, whereas juveniles shift to an acquisitive resource use. The study reveals an intraspecific pattern of strategy variation during forest restoration, contributing to our understanding of how plants adapt to diverse environments.

Characterization of a broad-spectrum antifungal strain, Streptomyces graminearus STR-1, against Magnaporthe oryzae.

Fungal diseases such as the devastating rice blast pose severe threats to crop production worldwide. Biological control of crop diseases caused by fungal pathogens is an environment-friendly approach for safeguarding crop production. But the insufficient availability of microbial agents effective against various fungal diseases has hampered the development of green production in crops. In this study, we identified a broad-spectrum antifungal bacterium, Streptomyces graminearus STR-1, showing antagonistic activity to diverse fungal pathogens including Magnaporthe oryzae, Rhizoctonia solani, Fusarium graminearum, Ustilaginoidea virens, and Bipolaris maydis. Its antifungal activity was relatively stable and less affected by temperature and pH. Evaluation of the biocontrol activity of STR-1 revealed that STR-1 prevented and controlled rice blast disease via eliciting plant immunity and suppressing fungal infection-structure development. STR-1 broth extract inhibited spore germination, likely through inhibiting protein synthesis. Combining LC-MS and chromatography analysis of the antimicrobial compounds purified from STR-1 broth extract, together with decoding STR-1 genomic sequence, we identified 4-oxo-4-[(1-phenylethyl)amino]but-2-enoic acid, 1,3,5-Trimethylpyrazole and SMA-1 as the potential main STR-1 secondary metabolites associated with its antifungal effects. This study suggests that bacterial strain STR-1 could be used for identifying highly effective and broad-spectrum secondary metabolites for containing rice blast and other crop diseases. The application of the active compounds offers a promising measure to tackle fungal disease.

Use of Dixon in magnetic resonance breast contrast-enhanced T1 weighted high-resolution imaging for mastectomy patients at 3T: A prospective study in single center.

BACKGROUND: For patients with complete breast resection, conventional contrast-enhanced T1-weighted imaging (CE-T1WI) with frequency-selective spectral attenuated inversion recovery (SPAIR) provides limited fat suppression on the postoperative side due to the uneven skin surface, inhomogeneous tissue environment, and frequency-selective feature of the SPAIR scheme, leading to difficulties in precise diagnosis. This study aimed to investigate the image quality and performance of the Dixon method compared with SPAIR in breast high-resolution CE-T1WI for mastectomy patients. MATERIALS AND METHODS: Sixty female patients who had not performed any breast surgeries were randomly selected retrospectively as the control group. Postmastectomy female patients were enrolled to undergone high-resolution CE-T1WI with SPAIR and Dixon breast scans. Subjective scores were rated using a 5-point scale. Objective parameters, including contrast-to-noise ratio (CNR), edge sharpness, and signal uniformity were measured and calculated. The Wilcoxon rank-sum test and Kappa statistic were used. RESULTS: A total of 114 consecutive postmastectomy patients were included. Subjective scores of T1WI-SPAIR in the control group were all significantly better than those with SPAIR on the postoperative side of mastectomy patients (P < 0.01). Dixon outperformed SPAIR with significantly better subjective scores in regards to uniformity and degree of fat-suppression, anatomical structures depiction, lesion conspicuity, and axillary visibility (p < 0.05) in both post- and non-operative sides and bilateral axillary areas through the paired comparison. The objective parameters of Dixon were significantly better than those of SPAIR. CONCLUSION: The Dixon method provided better image uniformity and higher fat suppression efficiency, and showed significant advantages in delineating the anatomical structures, with better axillary and lesion visibilities, especially on the completely removed breast side.

CFANet: Context fusing attentional network for preoperative CT image segmentation in robotic surgery.

Accurate segmentation of CT images is crucial for clinical diagnosis and preoperative evaluation of robotic surgery, but challenges arise from fuzzy boundaries and small-sized targets. In response, a novel 2D segmentation network named Context Fusing Attentional Network (CFANet) is proposed. CFANet incorporates three key modules to address these challenges, namely pyramid fusing module (PFM), parallel dilated convolution module (PDCM) and scale attention module (SAM). Integration of these modules into the encoder-decoder structure enables effective utilization of multi-level and multi-scale features. Compared with advanced segmentation method, the Dice score improved by 2.14% on the dataset of liver tumor. This improvement is expected to have a positive impact on the preoperative evaluation of robotic surgery and to support clinical diagnosis, especially in early tumor detection.

T1 Mapping and Amide Proton Transfer Weighted Imaging for Predicting Lymph Node Metastasis in Patients with Rectal Cancer.

BACKGROUND: Accurate preoperative judgment of lymph node (LN) metastasis is a critical step in creating a treatment strategy and evaluating prognosis in rectal cancer (RC) patients. OBJECTIVE: This study aimed to explore the value of T1 mapping and amide proton transfer weighted (APTw) imaging in predicting LN metastasis in patients with rectal cancer. METHODS: In a retrospective study, twenty-three patients with pathologically confirmed rectal adenocarcinoma who underwent MRI and surgery from August 2019 to August 2021 were selected. Then, 3.0T/MR sequences included conventional sequences (T1WI, T2WI, and DWI), APTw imaging, and T1 mapping. Patients were divided into LN metastasis (group A) and non-LN metastasis groups (group B). The intra-group correlation coefficient (ICC) was used to test the inter-observer consistency. Mann-Whitney U test was used to compare the differences between the two groups. Spearman correlation analysis was performed to evaluate the correlation between T1 and APT values. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter and their combination. The difference between AUCs was compared using the DeLong test. RESULTS: The APT value in patients with LN metastasis was significantly higher than in those without LN metastasis group (P=0.020). Also, similar results were observed for the T1 values (P=0.001). The area under the ROC curve of the APT value in the prediction of LN metastasis was 0.794; when the cutoff value was 1.73%, the sensitivity and specificity were 71.4% and 88.9%, respectively. The area under the ROC curve of the T1 value was 0.913; when the cutoff value was 1367.36 ms, the sensitivity and specificity were 78.6% and 100.0%, respectively. The area under the ROC curve of T1+APT was 0.929, with a sensitivity of 78.6% and specificity of 100.0%. CONCLUSION: APT and T1 values show great diagnostic efficiency in predicting LN metastasis in rectal cancer.

Early prediction of pathological response to neoadjuvant chemotherapy of breast tumors: a comparative study using amide proton transfer-weighted, diffusion weighted and dynamic contrast enhanced MRI.

Objective: To examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer. Materials: In this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups. Results: APT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax). Conclusion: APTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment.

Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal.

OBJECTIVE: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS due to serious overlaps of metabolite signals, imperfections because of non-ideal acquisition conditions, and interference with strong background signals mainly from macromolecules. The most popular method, LCModel, adopts complicated non-linear least square to quantify metabolites and addresses these problems by designing empirical priors such as basis-sets, imperfection factors. However, when the signal-to-noise ratio of MRS signal is low, the solution may have large deviation. METHODS: Linear Least Squares (LLS) is integrated with deep learning to reduce the complexity of solving this overall quantification. First, a neural network is designed to explicitly predict the imperfection factors and the overall signal from macromolecules. Then, metabolite quantification is solved analytically with the introduced LLS. In our Quantification Network (QNet), LLS takes part in the backpropagation of network training, which allows the feedback of the quantification error into metabolite spectrum estimation. This scheme greatly improves the generalization to metabolite concentrations unseen in training compared to the end-to-end deep learning method. RESULTS: Experiments show that compared with LCModel, the proposed QNet, has smaller quantification errors for simulated data, and presents more stable quantification for 20 healthy in vivo data at a wide range of signal-to-noise ratio. QNet also outperforms other end-to-end deep learning methods. CONCLUSION: This study provides an intelligent, reliable and robust MRS quantification. SIGNIFICANCE: QNet is the first LLS quantification aided by deep learning.

Boosting interpersonal emotion regulation through facial imitation: functional neuroimaging foundations.

Empathic function, which is primarily manifested by facial imitation, is believed to play a pivotal role in interpersonal emotion regulation for mood reinstatement. To explore this association and its neural substrates, we performed a questionnaire survey (study l) to identify the relationship between empathy and interpersonal emotion regulation; and a task-mode fMRI study (study 2) to explore how facial imitation, as a fundamental component of empathic processes, promotes the interpersonal emotion regulation effect. Study 1 showed that affective empathy was positively correlated with interpersonal emotion regulation. Study 2 showed smaller negative emotions in facial imitation interpersonal emotion regulation (subjects imitated experimenter's smile while followed the interpersonal emotion regulation guidance) than in normal interpersonal emotion regulation (subjects followed the interpersonal emotion regulation guidance) and Watch conditions. Mirror neural system (e.g. inferior frontal gyrus and inferior parietal lobe) and empathy network exhibited greater activations in facial imitation interpersonal emotion regulation compared with normal interpersonal emotion regulation condition. Moreover, facial imitation interpersonal emotion regulation compared with normal interpersonal emotion regulation exhibited increased functional coupling from mirror neural system to empathic and affective networks during interpersonal emotion regulation. Furthermore, the connectivity of the right orbital inferior frontal gyrus-rolandic operculum lobe mediated the association between the accuracy of facial imitation and the interpersonal emotion regulation effect. These results show that the interpersonal emotion regulation effect can be enhanced by the target's facial imitation through increased functional coupling from mirror neural system to empathic and affective neural networks.

Boosted Oxygen Kinetics of Hierarchically Mesoporous Mo2C/C for High-current-density Zn-air Battery.

The high-current-density Zn-air battery shows big prospects in next-generation energy technologies, while sluggish O2 reaction and diffusion kinetics barricade the applications. Herein, the sequential assembly is innovatively demonstrated for hierarchically mesoporous molybdenum carbides/carbon microspheres with a tunable thickness of mesoporous carbon layers (Meso-Mo2C/C-x, where x represents the thickness). The optimum Meso-Mo2C/C-14 composites (≈2 µm in diameter) are composed of mesoporous nanosheets (≈38 nm in thickness), which possess bilateral mesoporous carbon layers (≈14 nm in thickness), inner Mo2C/C layers (≈8 nm in thickness) with orthorhombic Mo2C nanoparticles (≈2 nm in diameter), a high surface area of ≈426 m2 g-1, and open mesopores (≈6.9 nm in size). Experiments and calculations corroborate the hierarchically mesoporous Mo2C/C can enhance hydrophilicity for supplying sufficient O2, accelerate oxygen reduction kinetics by highly-active Mo2C and N-doped carbon sites, and facilitate O2 diffusion kinetics over hierarchically mesopores. Therefore, Meso-Mo2C/C-14 outputs a high half-wave potential (0.88 V vs RHE) with a low Tafel slope (51 mV dec-1) for oxygen reduction. More significantly, the Zn-air battery delivers an ultrahigh power density (272 mW cm-2), and an unprecedented 100 h stability at a high-current-density condition (100 mA cm-2), which is one of the best performances.

LSKANet: Long Strip Kernel Attention Network for Robotic Surgical Scene Segmentation.

Surgical scene segmentation is a critical task in Robotic-assisted surgery. However, the complexity of the surgical scene, which mainly includes local feature similarity (e.g., between different anatomical tissues), intraoperative complex artifacts, and indistinguishable boundaries, poses significant challenges to accurate segmentation. To tackle these problems, we propose the Long Strip Kernel Attention network (LSKANet), including two well-designed modules named Dual-block Large Kernel Attention module (DLKA) and Multiscale Affinity Feature Fusion module (MAFF), which can implement precise segmentation of surgical images. Specifically, by introducing strip convolutions with different topologies (cascaded and parallel) in two blocks and a large kernel design, DLKA can make full use of region- and strip-like surgical features and extract both visual and structural information to reduce the false segmentation caused by local feature similarity. In MAFF, affinity matrices calculated from multiscale feature maps are applied as feature fusion weights, which helps to address the interference of artifacts by suppressing the activations of irrelevant regions. Besides, the hybrid loss with Boundary Guided Head (BGH) is proposed to help the network segment indistinguishable boundaries effectively. We evaluate the proposed LSKANet on three datasets with different surgical scenes. The experimental results show that our method achieves new state-of-the-art results on all three datasets with improvements of 2.6%, 1.4%, and 3.4% mIoU, respectively. Furthermore, our method is compatible with different backbones and can significantly increase their segmentation accuracy. Code is available at https://github.com/YubinHan73/LSKANet.

Amide proton transfer weighted combined with diffusion kurtosis imaging for predicting lymph node metastasis in cervical cancer.

OBJECTIVE: To investigate the value of amide proton transfer weighted (APTw) combined with diffusion kurtosis imaging (DKI) in quantitative prediction of lymph node metastasis (LNM) in cervical carcinoma (CC). METHODS: Data of 19 LNM(+) and 50 LNM(-) patients with CC were retrospectively analyzed. 3.0 T MRI scan was performed before the operation, including APTw and DKI. After post-processing, quantitative magnetization transfer ratio asymmetric at 3.5 ppm [MTRasym (3.5 ppm)], mean kurtosis (MK), and mean diffusivity (MD) maps were obtained. The MTRasym(3.5 ppm), MK, and MD values were respectively measured by two observers, and intra-class correlation coefficients (ICC) were used to test the consistency of the results. The independent samples t-test or Mann-Whitney U test was used to compare the differences in the values of each parameter. The ROC curve was used to analyze the predictive performance of parameters with significant differences and their combination parameter. RESULTS: The two observers had good agreement in the measurement of each data (ICC > 0.75). The MTRasym(3.5 ppm) and MK values of the LNM(+) group(3.260 ± 0.538% and 0.531 ± 0.202) were higher than those of the LNM(-) group(2.698 ± 0.597% and 0.401 ± 0.148) (P < 0.05), while there was no significant difference in MD values between the two groups(P > 0.05). The area under the curves (AUCs) of MTRasym(3.5 ppm), MK value, and MTRasym(3.5 ppm) + MK value were 0.763, 0.716, and 0.813, respectively, when predicting LNM status of CC. CONCLUSION: APTw and DKI can quantitatively predict LNM status of CC, which is of importance in clinical diagnosis and treatment.

Circular RNA DLGAP4 alleviates sevoflurane-induced neurotoxicity by regulating miR-9-5p/Sirt1/BDNF pathway.

BACKGROUND: Sevoflurane is a widely used anesthetic in infants. However, long and repeated exposure to this drug can cause developmental neurotoxicity. This study aimed to investigate the role and mechanism of circular RNA DLGAP4 (circDLGAP4) in sevoflurane-induced neurotoxicity. METHODS: Neonatal mice and mouse hippocampal neuronal cell line HT22 were used to construct sevoflurane-induced nerve injury models. The role of circDLGAP4 in sevoflurane-induced neurotoxicity was evaluated by gain-and/or loss-of-function methods. Pathological alterations in hippocampus were analyzed by hematoxylin-eosin and Tunel staining. Cell injury was assessed by cell viability and apoptosis, which was detected by CCK-8 and flow cytometry. The expression of circDLGAP4 and miR-9-5p was determined by real-time PCR. Sirt1 and BDNF levels were measured by Western blot. Productions of TNF-α and IL-6 were examined by ELISA. Dual-luciferase reporter assay and/or RNA pull-down assay were used to confirm the direct binding among circDLGAP4, miR-9-5p, and Sirt1. Rescue experiments were used to further verify the mechanism of circDLGAP4. RESULTS: CircDLGAP4 expression was decreased by sevoflurane both in vivo and in vitro. Overexpression of circDLGAP4 elevated cell viability, reduced apoptosis and levels of TNF-α and IL-6, while circDLGAP4 knockdown showed the opposite effects in sevoflurane-induced HT22 cells. Mechanically, circDLGAP4 functioned via directly binding to and regulating miR-9-5p, followed by targeting the Sirt1/BDNF pathway. Additionally, circDLGAP4 upregulation relieved sevoflurane-induced nerve injury, reduced levels of TNF-α, IL-6 and miR-9-5p, but increased the expression of Sirt1 and BDNF in hippocampus. CONCLUSIONS: Our studies found that circDLGAP4 relieved sevoflurane-induced neurotoxicity by sponging miR-9-5p to regulate Sirt1/BDNF pathway.

Stereoelectronic Switches of Single-Molecule Junctions through Conformation-Modulated Intramolecular Coupling Approaches.

Stereoelectronic effects in single-molecule junctions have been widely utilized to achieve a molecular switch, but high-efficiency and reproducible switching remain challenging. Here, we demonstrate that there are three stable intramolecular conformations in the 9,10-diphenyl-9,10-methanoanthracen-11-one (DPMAO) systems due to steric effect. Interestingly, different electronic coupling approaches including weak coupling (through-space), decoupling, and strong coupling (through-bond) between two terminal benzene rings are accomplished in the three stable conformations, respectively. Theoretical calculations show that the molecular conductance of three stable conformations differs by more than 1 order of magnitude. Furthermore, the populations of the three stable conformations are highly dependent on the solvent effect and the external electric field. Therefore, an excellent molecular switch can be achieved using the DPMAO molecule junctions and external stimuli. Our findings reveal that modulating intramolecular electronic coupling approaches may be a useful manner to enable molecular switches with high switching ratios. This opens up a new route for building high-efficiency molecular switches in single-molecular junctions.

Three-Phase Catassembly of 10 nm Au Nanoparticles for Sensitive and Stable Surface-Enhanced Raman Scattering Detection.

Interfacial self-assembly with the advantage of providing large-area, high-density plasmonic hot spots is conducive to achieving high sensitivity and stable surface-enhanced Raman scattering (SERS) sensing. However, rapid and simple assembly of highly repeatable large-scale multilayers with small nanoparticles remains a challenge. Here, we proposed a catassembly approach, where the "catassembly" means the increase in the rate and control of nanoparticle assembly dynamics. The catassembly approach was dropping heated Au sols onto oil chloroform (CHCl3), which triggers a rapid assembly of plasmonic multilayers within 15 s at the oil-water-air (O/W/A) interface. A mixture of heated sol and CHCl3 constructs a continuous liquid-air interfacial tension gradient; thus, the plasmonic multilayer film can form rapidly without adding functional ligands. Also, the dynamic assembly process of the three-phase catassembly ranging from cluster to interfacial film formation was observed through experimental characterization and COMSOL simulation. Importantly, the plasmonic multilayers of 10 nm Au NPs for SERS sensing demonstrated high sensitivity with the 1 nM level for crystal violet molecules and excellent stability with an RSD of about 10.0%, which is comparable to the detection level of 50 nm Au NPs with layer-by-layer assembly, as well as breaking the traditional and intrinsic understanding of small particles of plasmon properties. These plasmonic multilayers of 10 nm Au NPs through the three-phase catassembly method illustrate high SERS sensitivity and stability, paving the way for small-nanoparticle SERS sensing applications.

Sub-second whole brain T2mapping via multiband SENSE multiple overlapping-echo detachment imaging and deep learning.

Objective. Most quantitative magnetic resonance imaging (qMRI) methods are time-consuming. Multiple overlapping-echo detachment (MOLED) imaging can achieve quantitative parametric mapping of a single slice within around one hundred milliseconds. Nevertheless, imaging the whole brain, which involves multiple slices, still takes a few seconds. To further accelerate qMRI, we introduce multiband SENSE (MB-SENSE) technology to MOLED to realize simultaneous multi-slice T2mapping.Approach.The multiband MOLED (MB-MOLED) pulse sequence was carried out to acquire raw overlapping-echo signals, and deep learning was utilized to reconstruct T2maps. To address the issue of image quality degradation due to a high multiband factor MB, a plug-and-play (PnP) algorithm with prior denoisers (DRUNet) was applied. U-Net was used for T2map reconstruction. Numerical simulations, water phantom experiments and human brain experiments were conducted to validate our proposed approach.Main results.Numerical simulations show that PnP algorithm effectively improved the quality of reconstructed T2maps at low signal-to-noise ratios. Water phantom experiments indicate that MB-MOLED inherited the advantages of MOLED and its results were in good agreement with the results of reference method.In vivoexperiments for MB = 1, 2, 4 without the PnP algorithm, and 4 with PnP algorithm indicate that the use of PnP algorithm improved the quality of reconstructed T2maps at a high MB. For the first time, with MB = 4, T2mapping of the whole brain was achieved within 600 ms.Significance.MOLED and MB-SENSE can be combined effectively. This method enables sub-second T2mapping of the whole brain. The PnP algorithm can improve the quality of reconstructed T2maps. The novel approach shows significant promise in applications necessitating high temporal resolution, such as functional and dynamic qMRI.

Roles of exosome-derived non-coding RNA in tumor micro-environment and its clinical application. / å¤–æ³Œä½“æ¥æºéžç¼–ç RNA在肿瘤微环境中的作用及临床应用价值.

Tumor-derived exosomes play an important role in the tumor micro-environment. The exosome-derived non-coding RNAs are transmitted in the tumor microenvironment in three ways, communication between tumor cells, normal cells affecting tumor cells, and tumor cells affecting normal cells. Through these three ways, exosomal non-coding RNAs are involved in the regulation of tumor progression, affecting tumor angiogenesis, tumor invasiveness, drug resistance, stemness, tumor metabolic repro-gramming and immune escape, resulting in dual roles in promoting or inhibiting tumor development. Exosomes have a membranous structure and their contents are resistant to degradation by extracellular proteases and remain highly stable in body fluids, thus exosome-derived non-coding RNAs are expected to serve as diagnostic and prognostic indicators for a variety of cancers. In addition, exosomes can be used to deliver non-coding RNAs for targeted therapy, or to knock down or modify tumor-promoting non-coding RNAs for tumor therapy. This article reviews the function and communication mechanism of exosomal non-coding RNAs in the tumor microenvironment, including their pathways of action, effects, potential values for tumor biomarkers and treatment targets. This article also points out the issues that need to be further studied in order to promote the progress of extracellular non-coding RNAs in cancer research and their application in tumor diagnosis and treatment.