Neuroprotection of rhubarb extract against cerebral ischaemia-reperfusion injury via the gut-brain axis pathway.

BACKGROUND: The gut-brain axis (GBA) plays a central role in cerebral ischaemia-reperfusion injury (CIRI). Rhubarb, known for its purgative properties, has demonstrated protective effects against CIRI. However, it remains unclear whether this protective effect is achieved through the regulation of the GBA. AIM: This study aims to investigate the mechanism by which rhubarb extract improves CIRI by modulating the GBA pathway. METHODS: We identified the active components of rhubarb extract using LC-MS/MS. The model of middle cerebral artery occlusion (MCAO) was established to evaluate the effect of rhubarb extract. We conducted 16S rDNA sequencing and untargeted metabolomics to analyze intestinal contents. Additionally, we employed HE staining, TUNEL staining, western blot, and ELISA to assess intestinal barrier integrity. We measured the levels of inflammatory cytokines in serum via ELISA. We also examined blood-brain barrier (BBB) integrity using Evans blue (EB) penetration, transmission electron microscopy (TEM), western blot, and ELISA. Neurological function scores and TTC staining were utilized to evaluate neurological outcomes. RESULTS: We identified twenty-six active components in rhubarb. Rhubarb extract enhanced α-diversity, reduced the abundance of Enterobacteriaceae, and partially rectified metabolic disorders in CIRI rats. It also ameliorated pathological changes, increased the expressions of ZO-1, Occludin, and Claudin 1 in the colon, and reduced levels of LPS and d-lac in serum. Furthermore, it lowered the levels of IL-1ß, IL-6, IL-10, IL-17, and TNF-α in serum. Rhubarb extract mitigated BBB dysfunction, as evidenced by reduced EB penetration and improved hippocampal microstructure. It upregulated the expressions of ZO-1, Occludin, Claudin 1, while downregulating the expressions of TLR4, MyD88, and NF-κB. Similarly, rhubarb extract decreased the levels of IL-1ß, IL-6, and TNF-α in the hippocampus. Ultimately, it reduced neurological function scores and cerebral infarct volume. CONCLUSION: Rhubarb effectively treats CIRI, potentially by inhibiting harmful bacteria, correcting metabolic disorders, repairing intestinal barrier function, alleviating BBB dysfunction, and ultimately improving neurological outcomes.

Addition of immunotherapy to chemotherapy for metastatic triple-negative breast cancer: A systematic review and meta-analysis of randomized clinical trials.

BACKGROUND: One of the front treatment regimens used for metastatic triple-negative breast cancer (mTNBC) is treatment with programmed death-1 (PD-1) or programmed death ligand-1 (PD-L1) blockade combine with chemotherapy. However, the results of such studies have been controversial. METHODS: A systematic searched of PubMed, Embase, Cochrane Library, and the proceedings of the last 5 years of several meetings until February 18, 2021. The primary endpoint was the progression-free survival (PFS) of PD-L1-positive patients treated with PD1/PD-L1 blockade plus chemotherapy compare with chemotherapy. RESULTS: Overall, 4 studies that included a total of 3007 mTNBC patients were analyzed in this meta-analysis. PFS was significantly improved in the PD1/PD-L1 blockade plus chemotherapy group compared with the chemotherapy group in PD-L1-positive mTNBC patients (hazard ratios, (HR), 0.69; 95% CI, 0.59-0.80; P < .001), also in intention-to-treat (ITT) population (HR, 0.82; 95% CI, 0.74-0.90; P < .001). However, no significant benefit in overall survival (OS) was observed regardless of PD-L1 status or ITT population. The immunotherapy plus chemotherapy has higher adverse events (AEs) compared with chemotherapy (all AEs, Odds ratios (ORs), 2.33; 95% CI, 1.50-3.62; P < .001; grade 3-5 AEs, OR, 1.27; 95% CI, 1.04-1.55; P = .019). CONCLUSIONS: This meta-analysis showed that the addition of PD1/PD-L1 blockade to chemotherapy improved PFS in PD-L1 positive mTNBC patients, also in the ITT population. However, no significant benefit in OS was observed in patients of PD-L1 positive or in the ITT population after adding PD1/PD-L1 blockade. We found a higher rate of AEs with the addition of PD1/PD-L1 blockers to chemotherapy.

Proximity-Induced Hybridization Chain Reaction-Based Photoacoustic Imaging System for Amplified Visualization Protein-Specific Glycosylation in Mice.

Glycosylation is a key cellular mechanism that regulates several physiological and pathological functions. Therefore, identification and characterization of specific-protein glycosylation in vivo are highly desirable for studying glycosylation-related pathology and developing personalized theranostic modalities. Herein, we demonstrated a photoacoustic (PA) nanoprobe based on the proximity-induced hybridization chain reaction (HCR) for amplified visual detection of protein-specific glycosylation in vivo. Two kinds of functional DNA probes were designed. A glycan probe (DBCO-GP) was attached to glycans through metabolic oligosaccharide engineering (MOE) and protein probe (PP)-targeted proteins by aptamer recognition. Proximity-induced hybridization of the complementary domain between the two kinds of probes promoted conformational changes in the protein probes and in situ release of the HCR initiator domain. Gold nanoparticles (AuNPs) modified by complementary sequences (Au-H1 and Au-H2) self-assembled into Au aggregates via the HCR, thereby converting DNA signals to photoacoustic signals. Due to the high contrast and deep penetration of photoacoustic imaging, this strategy enabled in situ detection of Mucin 1 (MUC1)-specific glycosylation in mice with breast cancer and successfully monitored its dynamic states during tunicamycin treatment. This imaging technique provides a powerful platform for studying the effects of glycosylation on the protein structure and function, which helps to elucidate its role in disease processes.

Motion correction of chemical exchange saturation transfer MRI series using robust principal component analysis (RPCA) and PCA.

BACKGROUND: Chemical exchange saturation transfer (CEST) MRI requires the acquisition of multiple saturation-weighted images and can last several minutes. Misalignments among these images, which are often due to the inevitable motion of the subject, will corrupt CEST contrast maps and result in large quantification errors. Therefore, the registration of the CEST series is critical. However, registration is challenging since common intensity-based registration algorithms may fail to differentiate CEST signals from motion artifacts. Herein, we studied how different patterns of motion affect CEST quantification and proposed a cascaded two-step registration scheme by utilizing features extracted from the entire Z-spectral image series instead of direct registration to a single image. METHODS: The proposed approach is conducted in two stages: during the first coarse registration, the Z-spectral image series is decomposed by robust principal component analysis (RPCA) to separate CEST contrast from motion. The recomposed image series using only the low-rank component, which contains minimized motion, are averaged to generate a reference for the alignment of the image series. To further remove residual misalignments, the coarse registration is followed by a refinement stage, which uses PCA iteratively to generate motionless synthetic reference series with the first few principal components (PCs) that correspond to CEST contrast. In the end, the quality check is performed to exclude the images with unsuccessful registration. RESULTS: The proposed registration scheme (RPCA + PCA_R) was assessed by both phantom experiments and in vivo data of tumor-bearing mouse brain, with simulated random rigid motion in different patterns applied to the acquired static Z-spectral image series. For comparison, previous correction schemes using an explicit image [either S0 or Ssat(∆ω)] as registration reference were also performed, named as S0_R and Ssat_R respectively. To illustrate the advantage of combination of RPCA and PCA, registration was also exploited using either only the RPCA-based method (RPCA_R) or only the PCA-based one (PCA_R). Compared with the above four methods, RPCA + PCA_R allowed for more accurate correction of the corrupted Z-spectral images, exhibiting smaller MTRasym(∆ω) error maps and lower residual Z-spectra referring to the static data. Among all the five correction methods, the corrected Z-spectral image series by RPCA + PCA_R and the resulting MTRasym(∆ω) maps achieved the highest correlation coefficients (CC) with respect to the static ones. CONCLUSIONS: The registration scheme of RPCA + PCA_R provides robust motion correction between two specific Z-spectral images and among an entire image series, through extraction of the static component from the entire Z-spectra set and inclusion of a PCA-based refinement step. Therefore, this method can help improve CEST acquisition and quantification.

Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP) for Z-spectra fitting in chemical exchange saturation transfer (CEST) MRI.

BACKGROUND: Chemical exchange saturation transfer (CEST) MRI is a promising approach for detecting biochemical alterations in cancers and neurological diseases, but the quantification can be challenging. Among numerous quantification methods, Lorentzian difference (LD) is relatively simple and widely used, which employs Lorentzian line-shape as a reference to describe the direct saturation (DS) of water and takes account of difference against experimental CEST spectra data. However, LD often overestimates CEST and nuclear overhauser enhancement (NOE) effects. Specifically, for fast-exchanging CEST species require higher saturation power (B1_sat) or in the presence of strong magnetization transfer (MT) contrast, Z-spectrum appears more like a Gaussian line-shape rather than a Lorentzian line-shape. METHODS: To improve the conventional LD analysis, the present study developed and validated a novel fitting algorithm through a linear combination of Gaussian and Lorentzian function as the reference spectra, namely, Voxel-wise Optimization of Pseudo Voigt Profile (VOPVP). The experimental Z-spectra were pre-fitted with Gaussian and Lorentzian method independently, in order to determine Lorentzian proportionality coefficient (a). To further compensate for the line-shape changes under different B1_sat's, a B1-dependent adjustment was applied to the experimental Z-spectra (Z_exp) according to the prior knowledge learned from 5-pool Bloch equation-based simulations at a range of B1_sat's. Then, the obtained Z-spectra (Z_B1adj) was fitted by the previously defined VOPVP function. Considering the asymmetric component of MT, the positive- and negative-side of Z-spectra were fitted separately, while the middle part (-0.6 to 0.6 ppm, consisted primarily of DS) was fitted using Lorentzian function. Finally, the difference between Z_VOPVP and Z_exp was defined as the CEST and NOE contrast. To validate our VOPVP method, an extensive simulation of CEST Z-spectra was performed using 5-pool model and 6-pool model with greater MT component. RESULTS: In comparison with LD approach, VOPVP exhibited lower sum of squares due to error (SSE) and higher goodness of fit (R-square) for the experimental Z-spectra at all B1_sat. Moreover, the results indicated that VOPVP fitting improved the overestimated contributions from amide proton transfer (APT) and NOE through LD at all B1_sat. Despite that the relationship for B1-dependent adjustment was pre-determined using a single 5-pool model, the VOPVP fittings obtained accurate quantification for multiple 6-pool models with a range of T1w's and T2w's. The robustness of VOPVP fitting was also proved by simulations using 3T parameters. Furthermore, we assessed VOPVP in vivo in a glioblastoma-bearing mouse. Compared to LD maps, VOPVP quantification maps displayed higher contrast-to-noise ratio between tumor and normal contralateral tissue for APT, glutamate and nuclear overhauser effect (NOE), when B1_sat >1 µT. CONCLUSIONS: As an improvement of LD method, VOPVP fitting can serve as a simple, robust and more accurate approach for quantifying CEST and NOE contrast.