Integrated MUSIC array for high-precision damage diagnosis in complex composite structures.

Guided Wave (GW)-based Multiple Signal Classification (MUSIC) damage imaging presents several advantages, such as high resolution, which makes it a promising technique for localizing damage in composite structures. However, the application of this technology in aircraft is confronted with various challenges. The variability in performance of MUSIC array sensors is attributed to material and manufacturing process dispersion. Additionally, the conventional wiring of MUSIC array sensors adds considerable weight and is not compatible with complex structural configurations. Furthermore, within intricate configurations, the attenuation of scattering signals induced by structural damage impacts the accuracy of imaging. Moreover, the manual and individual placement of sensors on structures, along with structural anisotropy, may introduce phase errors in the signals detected by MUSIC array sensors. This can lead to a reduction in the accuracy of MUSIC imaging and result in compromised long-term sensor reliability. This paper proposes a high-precision integrated MUSIC array for the diagnosis of complex composite damage. This approach aims to address the challenges related to damage imaging in materials with complex structures. Impedance curve screening and surface-mount co-curing technology are utilized to manage the performance variation of MUSIC array sensors, enhance layout uniformity, and improve long-term stability. Subsequently, a focus compensation algorithm is proposed within the integrated MUSIC design to enhance precision, reduce weight, and adapt to complex structures. The effectiveness of the proposed method is confirmed through experimental validation on an actual complex composite wing box segment, demonstrating a maximum error of 2 cm in locating impact damage.

Stereoselective Electrophilic Sulfenylation of ß,ß-Disubstituted Enesulfinamides: Asymmetric Construction of Less Accessible Acyclic α,α-Disubstituted α-Sulfenylated Ketimines.

Current methods for the asymmetric α-sulfenylation of carbonyls cannot be applied to acyclic carbonyls that have two similar substituents at the α-position. This research demonstrated that the electrophilic sulfenylation of geometry-defined acyclic ß,ß-disubstituted enesulfinamides using S-aryl or S-alkyl benzenethiosulfonates can be highly stereoselective. This process results in enantioenriched α,α-disubstituted α-sulfenylated ketone surrogates with sulfur-containing acyclic tetrasubstituted carbon stereocenters bearing two electronically and sterically similar substituents (e.g., methyl and ethyl). Furthermore, by employing the corresponding stereoisomers of enensulfinamides, any of the four stereoisomers of α-sulfenylated ketimines can be selectively accessed.

Influence of γ-PGA on greenhouse gas emissions and grain yield from paddy rice under different rice varieties.

BACKGROUND: Significant efforts have been devoted to assess the effects of the poly-gamma-glutamic acid (γ-PGA) on crop growth, yield and quality, soil water retention and fertilizer use efficiency. However, few studies have evaluated the effects of γ-PGA on greenhouse gas (GHG) emissions and grain yield from paddy fields with different rice varieties. METHODS: In the present study, a split-plot field experiment was performed to comprehensively evaluate the effects of γ-PGA concentrations (i.e., no application [P0] and 25.0 kg ha-1 of γ-PGA fermentation solution [P1]) and rice varieties (i.e., conventional rice [Huanghuazhan, H], red rice [Gangteyou 8024, R] and black rice [Black indica rice, B]) on the grain yield, GHG emissions, global warming potential (GWP), greenhouse gas intensity (GHGI), net ecosystem economic profit (NEEP) and carbon footprint (CF) during 2022 and 2023 rice-growing seasons in central China. RESULTS: Application of γ-PGA significantly affected the GHGs emissions, NEEP and CF. Compared with P0 treatments, P1 treatments significantly increased the NEEP by 1.2-11.2 %, and decreased the GWP by 12.9-35.4 %, the GHGI by 16.5-35.9 % and the CF by 13.8-26.2 % in 2022-2023. Application of γ-PGA showed a tendency to increase the yield. Under γ-PGA application condition, R treatment exhibited the lowest GWP, GHGI and CF, and the highest yield and NEEP compared with B and H treatments. CONCLUSION: Our results suggest that γ-PGA application is an ecological agricultural management to increase rice yield, reduce greenhouse gas emission and increase economic benefit, and its advantage is more significant for red rice than for other rice varieties.

Intense Circularly Polarized Luminescence Induced by Chiral Supramolecular Assembly: The Importance of Intermolecular Electronic Coupling.

Herein we report on circularly polarized luminescence (CPL) emission originating from supramolecular chirality of organic microcrystals with a |glum| value up to 0.11. The microcrystals were prepared from highly emissive difluoroboron ß-diketonate (BF2dbk) dyes R-1 or S-1 with chiral binaphthol (BINOL) skeletons. R-1 and S-1 exhibit undetectable CPL signals in solution but manifest intense CPL emission in their chiral microcrystals. The chiral superstructures induced by BINOL skeletons were confirmed by XRD analysis. Spectral analysis and theoretical calculations indicate that intermolecular electronic coupling, mediated by the asymmetric stacking in the chiral superstructures, effectively alters excited-state electronic structures and facilitates electron transitions perpendicular to BF2bdk planes. The coupling increases cosθµ,m from 0.05 (monomer) to 0.86 (tetramer) and triggers intense optical activity of BF2bdk. The results demonstrate that optical activity of chromophores within assemblies can be regulated by both orientation and extent of intermolecular electronic couplings.

Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study.

OBJECTIVE: To develop a nomogram based on tumor and peritumoral edema (PE) radiomics features extracted from preoperative multiparameter MRI for predicting brain invasion (BI) in atypical meningioma (AM). METHODS: In this retrospective study, according to the 2021 WHO classification criteria, a total of 469 patients with pathologically confirmed AM from three medical centres were enrolled and divided into training (n = 273), internal validation (n = 117) and external validation (n = 79) cohorts. BI was diagnosed based on the histopathological examination. Preoperative contrast-enhanced T1-weighted MR images (T1C) and T2-weighted MR images (T2) for extracting meningioma features and T2-fluid attenuated inversion recovery (FLAIR) sequences for extracting meningioma and PE features were obtained. The multiple logistic regression was applied to develop separate multiparameter radiomics models for comparison. A nomogram was developed by combining radiomics features and clinical risk factors, and the clinical usefulness of the nomogram was verified using decision curve analysis. RESULTS: Among the clinical factors, PE volume and PE/tumor volume ratio are the risk of BI in AM. The combined nomogram based on multiparameter MRI radiomics features of meningioma and PE and clinical indicators achieved the best performance in predicting BI in AM, with area under the curve values of 0.862 (95% CI, 0.819-0.905) in the training cohort, 0.834 (95% CI, 0.780-0.908) in the internal validation cohort and 0.867 (95% CI, 0.785-0.950) in the external validation cohort, respectively. CONCLUSIONS: The nomogram based on tumor and PE radiomics features extracted from preoperative multiparameter MRI and clinical factors can predict the risk of BI in patients with AM.

Unveiling Local Current Behavior and Manipulating Grain Homogenization of Perovskite Films for Efficient Solar Cells.

Achieving high power conversion efficiency in perovskite solar cells (PSCs) heavily relies on fabricating homogeneous perovskite films. However, understanding microscopic-scale properties such as current generation and open-circuit voltage within perovskite crystals has been challenging due to difficulties in quantifying intragrain behavior. In this study, the local current intensity within state-of-the-art perovskite films mapped by conductive atomic force microscopy reveals a distinct heterogeneity, which exhibits a strong anticorrelation to the external biases. Particularly under different external bias polarities, specific regions in the current mapping show contrasting conductivity. Moreover, grains oriented differently exhibit varied surface potentials and currents, leading us to associate this local current heterogeneity with the grain orientation. It was found that the films treated with isopropanol exhibit ordered grain orientation, demonstrating minimized lattice heterogeneity, fewer microstructure defects, and reduced electronic disorder. Importantly, devices exhibiting an ordered orientation showcase elevated macroscopic optoelectronic properties and boosted device performance. These observations underscore the critical importance of fine-tuning the grain homogenization of perovskite films, offering a promising avenue for further enhancing the efficiency of PSCs.

Single-Digit Nanobubble Sensing via Nanopore Technology.

Nanobubbles play an important role in diverse fields, including engineering, medicine, and agriculture. Understanding the characteristics of individual nanobubbles is essential for comprehending fluid dynamics behaviors and advancing nanoscale science across various fields. Here, we report a strategy based on nanopore sensors for characterizing single-digit nanobubbles. We investigated the sizes and diffusion coefficients of nanobubbles at different voltages. Additionally, the finite element simulation and molecular dynamics simulation were introduced to account for counterion concentration variation around nanobubbles in the nanopore. In particular, the differences in stability and surface charge density of nanobubbles under various solution environments have been studied by the ion-stabilized model and the DLVO theory. Additionally, a straightforward method to mitigate nanobubble generation in the bulk for reducing current noise in nanopore sensing was suggested. The results hold significant implications for enhancing the understanding of individual nanobubble characterizations, especially in the nanofluid field.

Selective venous sampling for secondary hypertension.

Selective venous sampling (SVS), an invasive radiographic procedure that depends on contrast media, holds a unique role in diagnosing and guiding the treatment of certain types of secondary hypertension, particularly in patients who may be candidates for curative surgery. The adrenal venous sampling (AVS), in particular, is established as the gold standard for localizing and subtyping primary aldosteronism (PA). Throughout decades of clinical practice, AVS could be applied not only to PA but also to other endocrine diseases, such as adrenal Cushing syndrome (ACS) and Pheochromocytomas (PCCs). Notably, the application of AVS in ACS and PCCs remains less recognized compared to PA, with the low success rate of catheterization, the controversy of results interpretation, and the absence of a standardized protocol. Additionally, the AVS procedure necessitates enhancements to boost its success rate, with several helpful but imperfect methods emerging, yet continued exploration remains essential. We also observed renal venous sampling (RVS), an operation akin to AVS in principle, serves as an effective means of diagnosing renin-dependent hypertension, aiding in the identification of precise sources of renin excess and helping the selection of surgical candidates with renin angiotensin aldosterone system (RAAS) abnormal activation. Nonetheless, further basic and clinical research is needed. Selective venous sampling (SVS) can be used in identifying cases of secondary hypertension that are curable by surgical intervention. Adrenal venous sampling (AVS) and aldosterone measurement for classificatory diagnosis of primary aldosteronism (PA) are established worldwide. While its primary application is for PA, AVS also holds the potential for diagnosing other endocrine disorders, including adrenal Cushing's syndrome (ACS) and pheochromocytomas (PCCs) through the measurements of cortisol and catecholamine respectively. In addition, renal venous sampling and renin measurement can help to diagnose renovascular hypertension and reninoma.

Research on Tire Surface Damage Detection Method Based on Image Processing.

The performance of the tire has a very important impact on the safe driving of the car, and in the actual use of the tire, due to complex road conditions or use conditions, it will inevitably cause immeasurable wear, scratches and other damage. In order to effectively detect the damage existing in the key parts of the tire, a tire surface damage detection method based on image processing was proposed. In this method, the image of tire side is captured by camera first. Then, the collected images are preprocessed by optimizing the multi-scale bilateral filtering algorithm to enhance the detailed information of the damaged area, and the optimization effect is obvious. Thirdly, the image segmentation based on clustering algorithm is carried out. Finally, the Harris corner detection method is used to capture the "salt and pepper" corner of the target region, and the segmsegmed binary image is screened and matched based on histogram correlation, and the target region is finally obtained. The experimental results show that the similarity detection is accurate, and the damage area can meet the requirements of accurate identification.

Design and construction of chemical-biological module clusters for degradation and assimilation of poly(ethylene terephthalate) waste.

The rising accumulation of poly(ethylene terephthalate) (PET) waste presents an urgent ecological challenge, necessitating an efficient and economical treatment technology. Here, we developed chemical-biological module clusters that perform chemical pretreatment, enzymatic degradation, and microbial assimilation for the large-scale treatment of PET waste. This module cluster included (i) a chemical pretreatment that involves incorporating polycaprolactone (PCL) at a weight ratio of 2% (PET:PCL = 98:2) into PET via mechanical blending, which effectively reduces the crystallinity and enhances degradation; (ii) enzymatic degradation using Thermobifida fusca cutinase variant (4Mz), that achieves complete degradation of pretreated PET at 300 g/L PET, with an enzymatic loading of 1 mg protein per gram of PET; and (iii) microbial assimilation, where Rhodococcus jostii RHA1 metabolizes the degradation products, assimilating each monomer at a rate above 90%. A comparative life cycle assessment demonstrated that the carbon emissions from our module clusters (0.25 kg CO2-eq/kg PET) are lower than those from other established approaches. This study pioneers a closed-loop system that seamlessly incorporates pretreatment, degradation, and assimilation processes, thus mitigating the environmental impacts of PET waste and propelling the development of a circular PET economy.

Comparison of Different Fusion Radiomics for Predicting Benign and Malignant Sacral Tumors: A Pilot Study.

Differentiating between benign and malignant sacral tumors is crucial for determining appropriate treatment options. This study aims to develop two benchmark fusion models and a deep learning radiomic nomogram (DLRN) capable of distinguishing between benign and malignant sacral tumors using multiple imaging modalities. We reviewed axial T2-weighted imaging (T2WI) and non-contrast computed tomography (NCCT) of 134 patients pathologically confirmed as sacral tumors. The two benchmark fusion models were developed using fusion deep learning (DL) features and fusion classical machine learning (CML) features from multiple imaging modalities, employing logistic regression, K-nearest neighbor classification, and extremely randomized trees. The two benchmark models exhibiting the most robust predictive performance were merged with clinical data to formulate the DLRN. Performance assessment involved computing the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, negative predictive value (NPV), and positive predictive value (PPV). The DL benchmark fusion model demonstrated superior performance compared to the CML fusion model. The DLRN, identified as the optimal model, exhibited the highest predictive performance, achieving an accuracy of 0.889 and an AUC of 0.961 in the test sets. Calibration curves were utilized to evaluate the predictive capability of the models, and decision curve analysis (DCA) was conducted to assess the clinical net benefit of the DLR model. The DLRN could serve as a practical predictive tool, capable of distinguishing between benign and malignant sacral tumors, offering valuable information for risk counseling, and aiding in clinical treatment decisions.

Xuefu Zhuyu decoction promotes synaptic plasticity by targeting miR-191a-5p/BDNF-TrkB axis in severe traumatic brain injury.

BACKGROUND: Xuefu Zhuyu decoction (XFZYD) is a traditional Chinese herbal formula known for its ability to eliminate blood stasis and improve blood circulation, providing neuroprotection against severe traumatic brain injury (sTBI). However, the underlying mechanism is still unclear. PURPOSE: We aim to investigate the neuroprotective effects of XFZYD in sTBI from a novel mechanistic perspective of miRNA-mRNA. Additionally, we sought to elucidate a potential specific mechanism by integrating transcriptomics, bioinformatics, and conducting both in vitro and in vivo experiments. METHODS: The sTBI rat model was established, and the rats were treated with XFZYD for 14 days. The neuroprotective effects of XFZYD were evaluated using a modified neurological severity score, hematoxylin and eosin staining, as well as Nissl staining. The anti-inflammatory effects of XFZYD were explored using quantitative real-time PCR (qRT-PCR), Western blot analysis, and immunofluorescence. Next, miRNA sequencing of the hippocampus was performed to determine which miRNAs were differentially expressed. Subsequently, qRT-PCR was used to validate the differentially expressed miRNAs. Target core mRNAs were determined using various methods, including miRNA prediction targets, mRNA sequencing, miRNA-mRNA network, and protein-protein interaction (PPI) analysis. The miRNA/mRNA regulatory axis were verified through qRT-PCR or Western blot analysis. Finally, morphological changes in the neural synapses were observed using transmission electron microscopy and immunofluorescence. RESULTS: XFZYD exhibited significant neuroprotective and anti-inflammatory effects on subacute sTBI rats' hippocampus. The analyses of miRNA/mRNA sequences combined with the PPI network revealed that the therapeutic effects of XFZYD on sTBI were associated with the regulation of the rno-miR-191a-5p/BDNF axis. Subsequently, qRT-PCR and Western blot analysis confirmed XFZYD reversed the decrease of BDNF and TrkB in the hippocampus caused by sTBI. Additionally, XFZYD treatment potentially increased the number of synaptic connections, and the expression of the synapse-related protein PSD95, axon-related protein GAP43 and neuron-specific protein TUBB3. CONCLUSIONS: XFZYD exerts neuroprotective effects by promoting hippocampal synaptic remodeling and improving cognition during the subacute phase of sTBI through downregulating of rno-miR-191a-5p/BDNF axis, further activating BDNF-TrkB signaling.

Single-incision plus one-port laparoscopy surgery versus conventional multi-port laparoscopy surgery for colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: The efficacy of single-incision plus one-port laparoscopic surgery (SILS + 1) versus conventional laparoscopic surgery (CLS) for colorectal cancer treatment remains unclear. This study compares the short-term and long-term outcomes of SILS + 1 and CLS using a high-quality systematic review and meta-analysis. METHOD: Literature search followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, drawing from PubMed, Embase, Web of Science, and the Cochrane Library until December 10, 2023. Statistical analysis was conducted using RevMan and Stata. RESULT: The review and meta-analysis included seven studies with 1740 colorectal cancer patients. Compared to CLS, SILS + 1 showed significant improvements in operation time (WMD = - 18.33, P < 0.00001), blood loss (WMD = - 21.31, P < 0.00001), incision length (WMD = - 2.07, P < 0.00001), time to first defecation (WMD = - 14.91, P = 0.009), time to oral intake (WMD = - 11.46, P = 0.04), and time to ambulation (WMD = - 11.52, P = 0.01). There were no significant differences in lymph node harvest, resection margins, complications, anastomotic leakage, hospital stay, disease-free survival, overall survival, and postoperative recurrence. CONCLUSIONS: Compared to CLS, SILS + 1 demonstrates superiority in shortening the surgical incision and promoting postoperative recovery. SILS + 1 can provide a safe and feasible alternative to CLS.

Unsupervised OCT image despeckling with ground-truth- and repeated-scanning-free features.

Optical coherence tomography (OCT) can resolve biological three-dimensional tissue structures, but it is inevitably plagued by speckle noise that degrades image quality and obscures biological structure. Recently unsupervised deep learning methods are becoming more popular in OCT despeckling but they still have to use unpaired noisy-clean images or paired noisy-noisy images. To address the above problem, we propose what we believe to be a novel unsupervised deep learning method for OCT despeckling, termed Double-free Net, which eliminates the need for ground truth data and repeated scanning by sub-sampling noisy images and synthesizing noisier images. In comparison to existing unsupervised methods, Double-free Net obtains superior denoising performance when trained on datasets comprising retinal and human tissue images without clean images. The efficacy of Double-free Net in denoising holds significant promise for diagnostic applications in retinal pathologies and enhances the accuracy of retinal layer segmentation. Results demonstrate that Double-free Net outperforms state-of-the-art methods and exhibits strong convenience and adaptability across different OCT images.

Radiomics for predicting MGMT status in cerebral glioblastoma: comparison of different MRI sequences.

Using radiomics to predict O6-methylguanine-DNA methyltransferase promoter methylation status in patients with newly diagnosed glioblastoma and compare the performances of different MRI sequences. Preoperative MRI scans from 215 patients were included in this retrospective study. After image preprocessing and feature extraction, two kinds of machine-learning models were established and compared for their performances. One kind was established using all MRI sequences (T1-weighted image, T2-weighted image, contrast enhancement, fluid-attenuated inversion recovery, DWI_b_high, DWI_b_low and apparent diffusion coefficient), and the other kind was based on single MRI sequence as listed above. For the machine-learning model based on all sequences, a total of seven radiomic features were selected with the Maximum Relevance and Minimum Redundancy algorithm. The predictive accuracy was 0.993 and 0.750 in the training and validation sets, respectively, and the area under curves were 1.000 and 0.754 in the two sets, respectively. For the machine-learning model based on single sequence, the numbers of selected features were 8, 10, 10, 13, 9, 7 and 6 for T1-weighted image, T2-weighted image, contrast enhancement, fluid-attenuated inversion recovery, DWI_b_high, DWI_b_low and apparent diffusion coefficient, respectively, with predictive accuracies of 0.797-1.000 and 0.583-0.694 in the training and validation sets, respectively, and the area under curves of 0.874-1.000 and 0.538-0.697 in the two sets, respectively. Specifically, T1-weighted image-based model performed best, while contrast enhancement-based model performed worst in the independent validation set. The machine-learning models based on seven different single MRI sequences performed differently in predicting O6-methylguanine-DNA methyltransferase status in glioblastoma, while the machine-learning model based on the combination of all sequences performed best.

A Novel Network Pharmacology Strategy Based on the Universal Effectiveness-Common Mechanism of Medical Herbs Uncovers Therapeutic Targets in Traumatic Brain Injury.

Purpose: Many herbs can promote neurological recovery following traumatic brain injury (TBI). There must lie a shared mechanism behind the common effectiveness. We aimed to explore the key therapeutic targets for TBI based on the common effectiveness of the medicinal plants. Material and methods: The TBI-effective herbs were retrieved from the literature as imputes of network pharmacology. Then, the active ingredients in at least two herbs were screened out as common components. The hub targets of all active compounds were identified through Cytohubba. Next, AutoDock vina was used to rank the common compound-hub target interactions by molecular docking. A highly scored compound-target pair was selected for in vivo validation. Results: We enrolled sixteen TBI-effective medicinal herbs and screened out twenty-one common compounds, such as luteolin. Ten hub targets were recognized according to the topology of the protein-protein interaction network of targets, including epidermal growth factor receptor (EGFR). Molecular docking analysis suggested that luteolin could bind strongly to the active pocket of EGFR. Administration of luteolin or the selective EGFR inhibitor AZD3759 to TBI mice promoted the recovery of body weight and neurological function, reduced astrocyte activation and EGFR expression, decreased chondroitin sulfate proteoglycans deposition, and upregulated GAP43 levels in the cortex. The effects were similar to those when treated with the selective EGFR inhibitor. Conclusion: The common effectiveness-based, common target screening strategy suggests that inhibition of EGFR can be an effective therapy for TBI. This strategy can be applied to discover core targets and therapeutic compounds in other diseases.

Thrombin receptor activating peptide-6 decreases acute graft-versus-host disease through activating GPR15.

G-protein coupled receptor 15 (GPR15) is expressed on T-cells. We previously reported knockout of GPR15 increased acute graft-versus-host disease (GvHD) in mice. In this study, we identified thrombin receptor activating peptide-6 (TRAP-6, peptide sequence: SFLLRN) as an activator of GPR15. GRP15 and ß-arrestin2 were needed for TRAP-6-mediated inhibition of mixed lymphocyte reactions. TRAP-6 decreased acute GvHD in allotransplant models in mice, an effect dependent on GPR15-expression in donor T-cells. RNA-seq and protein analyses indicated TRAP-6 increased binding of ß-arrestin2/TAB1 and inhibited phosphorylation of TAK1 and NF-κB-P65. GPR15 is expressed differently on CD4+ T-cells and CD8+ T-cells. TRAP-6 inhibited phosphorylation of NF-κB-P65 in CD4+ T-cells but increased granzyme B expression in CD8+ T-cells. TRAP-6 decreased acute GvHD without inhibiting graft-versus-tumor (GvT) efficacy against A20 lymphoma cells. SALLRN, a mutant of TRAP-6, preserved the anti-acute GvHD effect but avoided the adverse effects of TRAP-6. TRAP-6 and SALLRN also decreased allogeneic and xenogeneic reactions induced by human blood mononuclear cells. In conclusion, TRAP-6 activated GPR15 on T-cells and decreased acute GvHD in mice without impairing GvT efficacy.

Ginseng fermentation solution affects the gut microbiota in zebrafish with alcoholic liver disease via PI3K/Akt pathway.

BACKGROUND: Ginsenosides have received increased amounts of attention due to their ability to modulate the intestinal flora, which may subsequently alleviate alcoholic liver disease (ALD). The effects of ginseng fermentation solution (GFS) on the gut microbiota and metabolism in ALD patients have not been explored. PURPOSE: This research aimed to explore the regulatory effect of GFS on ALD both in vitro and in vivo. METHOD: This study assessed the anti-ALD efficacy of GFS using an LO2 cell model and a zebrafish model. Untargeted metabolomics was used for differentially abundant metabolite analysis, and high-throughput 16S rRNA sequencing was used to examine the effect of GFS on ALD. RESULTS: The LO2 cell line experiments demonstrated that GFS effectively mitigated alcohol-induced oxidative stress and reduced apoptosis by upregulating PI3K and Bcl-2 expression and decreasing the levels of malondialdehyde, total cholesterol, and triglycerides. In zebrafish, GFS improved morphological and physiological parameters and diminished oxidative stress-induced ALD. Meanwhile, the results from Western blotting indicated that GFS enhanced the expression of PI3K, Akt, and Bcl-2 proteins while reducing Bax protein expression, thereby ameliorating the ALD model in zebrafish. Metabolomics data revealed significant changes in a total of 46 potential biomarkers. Among them, metabolites such as prostaglandin F2 alpha belong to arachidonic acid metabolism. In addition, GFS also partly reversed the imbalance of gut microbiota composition caused by alcohol. At the genus level, alcohol consumption elevated the presence of Flectobacillus, Curvibacter, among others, and diminished Elizabethkingia within the intestinal microbes of zebrafish. Conversely, GFS reversed these effects, notably enhancing the abundance of Proteobacteria and Archaea. Correlation analyses further indicated a significant negative correlation between prostaglandin F2 alpha, 11,14,15-THETA, Taurocholic acid and Curvibacter. CONCLUSION: This study highlights a novel mechanism by which GFS modulates anti-ALD activity through the PI3K/Akt signalling pathway by influencing the intestinal flora-metabolite axis. These results indicate the potential of GFS as a functional food for ALD treatment via modulation of the gut flora.

Buyang huanwu decoction promotes remyelination via miR-760-3p/GPR17 axis after intracerebral hemorrhage.

ETHNOPHARMACOLOGICAL RELEVANCE: The repairment of myelin sheaths is crucial for mitigating neurological impairments of intracerebral hemorrhage (ICH). However, the current research on remyelination processes in ICH remains limited. A representative traditional Chinese medicine, Buyang Huanwu decoction (BYHWD), shows a promising therapeutic strategy for ICH treatment. AIM OF THE STUDY: To investigate the pro-remyelination effects of BYHWD on ICH and explore the underlying mechanisms. MATERIALS AND METHODS: The collagenase-induced mice ICH model was created for investigation. BYHWD's protective effects were assessed by behavioral tests and histological staining. Transmission electron microscopy was used for displaying the structure of myelin sheaths. The remyelination and oligodendrocyte differentiation were evaluated by the expressions of myelin proteolipid protein (PLP), myelin basic protein (MBP), MBP/TAU, Olig2/CC1, and PDGFRα/proliferating cell nuclear antigen (PCNA) through RT-qPCR and immunofluorescence. Transcriptomics integrated with disease database analysis and experiments in vivo and in vitro revealed the microRNA-related underlying mechanisms. RESULTS: Here, we reported that BYHWD promoted the neurological function of ICH mice and improved remyelination by increasing PLP, MBP, and TAU, as well as restoring myelin structure. Besides, we showed that BYHWD promoted remyelination by boosting the differentiation of PDGFRα+ oligodendrocyte precursor cells into olig2+/CC1+ oligodendrocytes. Additionally, we demonstrated that the remyelination effects of BYHWD worked by inhibiting G protein-coupled receptor 17 (GPR17). miRNA sequencing integrated with miRNA database prediction screened potential miRNAs targeting GPR17. By applying immunofluorescence, RNA in situ hybridization and dual luciferase reporter gene assay, we confirmed that BYHWD suppressed GPR17 and improved remyelination by increasing miR-760-3p. CONCLUSIONS: BYHWD improves remyelination and neurological function in ICH mice by targeting miR-760-3p to inhibit GPR17. This study may shed light on the orchestration of remyelination mechanisms after ICH, thus providing novel insights for developing innovative prescriptions with brain-protective properties.

Guided Lamb Wave Array Time-Delay-Based MUSIC Algorithm for Impact Imaging.

Composite materials, valued in aerospace for their stiffness, strength and lightness, require impact monitoring for structural health, especially against low-velocity impacts. The MUSIC algorithm, known for efficient directional scanning and easy sensor deployment, is gaining prominence in this area. However, in practical engineering applications, the broadband characteristics of impact response signals and the time delay errors in array elements' signal reception lead to inconsistencies between the steering vector and the actual signal subspace, affecting the precision of the MUSIC impact localization method. Furthermore, the anisotropy of composite materials results in time delay differences between array elements in different directions. If the MUSIC algorithm uses a fixed velocity value, this also introduces time delay errors, further reducing the accuracy of localization. Addressing these challenges, this paper proposes an innovative MUSIC algorithm for impact imaging using a guided Lamb wave array, with an emphasis on time delay management. This approach focuses on the extraction of high-energy, single-frequency components from impact response signals, ensuring accurate time delay measurement across array elements and enhancing noise resistance. It also calculates the average velocity of single-frequency components in varying directions for an initial impact angle estimation. This estimated angle then guides the selection of a specific single-frequency velocity, culminating in precise impact position localization. The experimental evaluation, employing equidistantly spaced array elements to capture impact response signals, assessed the effectiveness of the proposed method in accurately determining array time delays. Furthermore, impact localization tests on reinforced composite structures were conducted, with the results indicating high precision in pinpointing impact locations.