Clinical performance of metagenomic next-generation sequencing for diagnosis of invasive fungal disease after hematopoietic cell transplant.

Background: Timely diagnosis and appropriate antifungal therapy are critical for improving the prognosis of patients with invasive fungal disease (IFD) after hematopoietic stem cell transplantation (HSCT). We evaluated the performance of metagenomic next-generation sequencing (mNGS) and conventional microbiological testing (CMT), as well as the diagnosis, therapeutic management, and outcomes of IFD after HSCT. Methods: We retrospectively studied 189 patients who underwent HSCT and were considered at risk for IFD. In total, 46 patients with IFD were enrolled in this study. The IFD consensus was followed for classifying IFD incidents. Results: Forty-six patients were diagnosed with proven/probable (n = 12), possible (n = 27), and undefined (n = 7) IFD. Aspergillus was the most commonly detected fungal genus. Mucormycosis was found in 15 patients; two had Aspergillus, and one had Candida infections. Compared to CMT, mNGS significantly reduced the time required to identify pathogens (P = 0.0016). mNGS had a much higher sensitivity than CMT (84.78% vs. 36.96%; P < 0.0001). A total of 76.09% of patients received antifungal prophylaxis during fungal infections. All Pneumocystis infections occurred later than 100 days after transplantation. Among patients with Pneumocystis infection, 71.43% occurred following sulfonamide withdrawal, and subsequent treatment with sulfonamide alone or in combination with other drugs was effective. Based on the empirical antifungal treatment, the dosages, modes of administration, frequency of administration, or antifungal of 55.26% of the patients were changed according to the mNGS results. The 4-year overall survival rate of patients diagnosed with IFD after transplantation was 71.55% (95% CI, 55.18%-85.82%). Hypoproteinemia and corticosteroid use are independent risk factors for IFD. Conclusion: mNGS, which has a high sensitivity and a short detection time, aids in the diagnosis and prognosis of pathogenic fungi. As a powerful technology, mNGS can influence treatment decisions in patients with IFD following HSCT.

Enhancing Diagnostic Images to Improve the Performance of the Segment Anything Model in Medical Image Segmentation.

Medical imaging serves as a crucial tool in current cancer diagnosis. However, the quality of medical images is often compromised to minimize the potential risks associated with patient image acquisition. Computer-aided diagnosis systems have made significant advancements in recent years. These systems utilize computer algorithms to identify abnormal features in medical images, assisting radiologists in improving diagnostic accuracy and achieving consistency in image and disease interpretation. Importantly, the quality of medical images, as the target data, determines the achievable level of performance by artificial intelligence algorithms. However, the pixel value range of medical images differs from that of the digital images typically processed via artificial intelligence algorithms, and blindly incorporating such data for training can result in suboptimal algorithm performance. In this study, we propose a medical image-enhancement scheme that integrates generic digital image processing and medical image processing modules. This scheme aims to enhance medical image data by endowing them with high-contrast and smooth characteristics. We conducted experimental testing to demonstrate the effectiveness of this scheme in improving the performance of a medical image segmentation algorithm.

A novel center-based deep contrastive metric learning method for the detection of polymicrogyria in pediatric brain MRI.

Polymicrogyria (PMG) is a disorder of cortical organization mainly seen in children, which can be associated with seizures, developmental delay and motor weakness. PMG is typically diagnosed on magnetic resonance imaging (MRI) but some cases can be challenging to detect even for experienced radiologists. In this study, we create an open pediatric MRI dataset (PPMR) containing both PMG and control cases from the Children's Hospital of Eastern Ontario (CHEO), Ottawa, Canada. The differences between PMG and control MRIs are subtle and the true distribution of the features of the disease is unknown. This makes automatic detection of potential PMG cases in MRI difficult. To enable the automatic detection of potential PMG cases, we propose an anomaly detection method based on a novel center-based deep contrastive metric learning loss function (cDCM). Despite working with a small and imbalanced dataset our method achieves 88.07% recall at 71.86% precision. This will facilitate a computer-aided tool for radiologists to select potential PMG MRIs. To the best of our knowledge, our research is the first to apply machine learning techniques to identify PMG solely from MRI. Our code is available at: https://github.com/RichardChangCA/Deep-Contrastive-Metric-Learning-Method-to-Detect-Polymicrogyria-in-Pediatric-Brain-MRI. Our pediatric MRI dataset is available at: https://www.kaggle.com/datasets/lingfengzhang/pediatric-polymicrogyria-mri-dataset.

Vicious Cycle-Breaking Lipid Nanoparticles Remodeling Multicellular Crosstalk to Reverse Liver Fibrosis.

During liver fibrogenesis, the reciprocal crosstalk among capillarized liver sinusoidal endothelial cells (LSECs), activated hepatic stellate cells (HSCs), and dysfunctional hepatocytes constructs a self-amplifying vicious cycle, greatly exacerbating the disease condition and weakening therapeutic effect. Limited by the malignant cellular interactions, the previous single-cell centric treatment approaches show unsatisfactory efficacy and fail to meet clinical demand. Herein, a vicious cycle-breaking strategy is proposed to target and repair pathological cells separately to terminate the malignant progression of liver fibrosis. Chondroitin sulfate-modified and vismodegib-loaded nanoparticles (CS-NPs/VDG) are designed to efficiently normalize the fenestrae phenotype of LSECs and restore HSCs to quiescent state by inhibiting Hedgehog signaling pathway. In addition, glycyrrhetinic acid-modified and silybin-loaded nanoparticles (GA-NPs/SIB) are prepared to restore hepatocytes function by relieving oxidative stress. The results show successful interruption of vicious cycle as well as distinct fibrosis resolution in two animal models through multiregulation of the pathological cells. This work not only highlights the significance of modulating cellular crosstalk but also provides a promising avenue for developing antifibrotic regimens.

Increasing Donor-Acceptor Interactions and Particle Dispersibility of Covalent Triazine Frameworks for Higher Crystallinity and Enhanced Photocatalytic Activity.

Covalent triazine frameworks (CTFs) have recently emerged as an efficient class of photocatalysts due to their structural diversity and excellent stability. Nevertheless, the synthetic reactions of CTFs have usually suffered from poor reversibility, resulting in a low crystallinity of the materials. Here, we report the introduction of methoxy groups on the monomer 2,5-diphenylthiazolo[5,4-d]thiazole to reinforce interlayer π-π interactions of the resulting donor-acceptor type CTFs, which improved crystallinity, further increasing the visible light absorption range and allowing for efficient separation and transport of carriers. The morphology is strongly correlated to the wettability, which has a significant impact on the mass transfer capacity and photocatalytic activity in the photocatalytic reaction. To further improve crystallinity and photocatalytic activity, CTF-NWU-T3 photocatalysts in a bowl shape were prepared using a SiO2 template. The energy band structure, photocatalytic hydrogen evolution, and pollutant degradation efficiency of involved materials were investigated. The donor-acceptor type CTF-NWU-T3 with a bowl-shaped morphology, synthesized using the template method and the introduction of methoxy groups, exhibited an excellent photocatalytic hydrogen production rate of 32064 µmol·h-1·g-1. This study highlights the significance of improving donor-acceptor interactions and increasing the dispersibility of catalyst particles in dispersion to enhance the photocatalytic activity of heterogeneous photocatalysts.

An Autologous Macrophage-Based Phenotypic Transformation-Collagen Degradation System Treating Advanced Liver Fibrosis.

In advanced liver fibrosis (LF), macrophages maintain the inflammatory environment in the liver and accelerate LF deterioration by secreting proinflammatory cytokines. However, there is still no effective strategy to regulate macrophages because of the difficulty and complexity of macrophage inflammatory phenotypic modulation and the insufficient therapeutic efficacy caused by the extracellular matrix (ECM) barrier. Here, AC73 and siUSP1 dual drug-loaded lipid nanoparticle is designed to carry milk fat globule epidermal growth factor 8 (MFG-E8) (named MUA/Y) to effectively inhibit macrophage proinflammatory signals and degrade the ECM barrier. MFG-E8 is released in response to the high reactive oxygen species (ROS) environment in LF, transforming macrophages from a proinflammatory (M1) to an anti-inflammatory (M2) phenotype and inducing macrophages to phagocytose collagen. Collagen ablation increases AC73 and siUSP1 accumulation in hepatic stellate cells (HSCs) and inhibits HSCs overactivation. Interestingly, complete resolution of liver inflammation, significant collagen degradation, and HSCs deactivation are observed in methionine choline deficiency (MCD) and CCl4 models after tail vein injection of MUA/Y. Overall, this work reveals a macrophage-focused regulatory treatment strategy to eliminate LF progression at the source, providing a new perspective for the clinical treatment of advanced LF.

Progress on the pathological tissue microenvironment barrier-modulated nanomedicine.

Imbalance in the tissue microenvironment is the main obstacle to drug delivery and distribution in the human body. Before penetrating the pathological tissue microenvironment to the target site, therapeutic agents are usually accompanied by three consumption steps: the first step is tissue physical barriers for prevention of their penetration, the second step is inactivation of them by biological molecules, and the third step is a cytoprotective mechanism for preventing them from functioning on specific subcellular organelles. However, recent studies in drug-hindering mainly focus on normal physiological rather than pathological microenvironment, and the repair of damaged physiological barriers is also rarely discussed. Actually, both the modulation of pathological barriers and the repair of damaged physiological barriers are essential in the disease treatment and the homeostasis maintenance. In this review, we present an overview describing the latest advances in the generality of these pathological barriers and barrier-modulated nanomedicine. Overall, this review holds considerable significance for guiding the design of nanomedicine to increase drug efficacy in the future.

Global estimates of gap-free and fine-scale CO2 concentrations during 2014-2020 from satellite and reanalysis data.

Carbon dioxide (CO2) is a crucial greenhouse gas with substantial effects on climate change. Satellite-based remote sensing is a commonly used approach to detect CO2 with high precision but often suffers from extensive spatial gaps. Thus, the limited availability of data makes global carbon stocktaking challenging. In this paper, a global gap-free column-averaged dry-air mole fraction of CO2 (XCO2) dataset with a high spatial resolution of 0.1° from 2014 to 2020 is generated by the deep learning-based multisource data fusion, including satellite and reanalyzed XCO2 products, satellite vegetation index data, and meteorological data. Results indicate a high accuracy for 10-fold cross-validation (R2 = 0.959 and RMSE = 1.068 ppm) and ground-based validation (R2 = 0.964 and RMSE = 1.010 ppm). Our dataset has the advantages of high accuracy and fine spatial resolution compared with the XCO2 reanalysis data as well as that generated from other studies. Based on the dataset, our analysis reveals interesting findings regarding the spatiotemporal pattern of CO2 over the globe and the national-level growth rates of CO2. This gap-free and fine-scale dataset has the potential to provide support for understanding the global carbon cycle and making carbon reduction policy, and it can be freely accessed at https://doi.org/10.5281/zenodo.7721945.

Bioinformatics Identification of Regulatory Genes and Mechanism Related to Hypoxia-Induced PD-L1 Inhibitor Resistance in Hepatocellular Carcinoma.

The combination of a PD-L1 inhibitor and an anti-angiogenic agent has become the new reference standard in the first-line treatment of non-excisable hepatocellular carcinoma (HCC) due to the survival advantage, but its objective response rate remains low at 36%. Evidence shows that PD-L1 inhibitor resistance is attributed to hypoxic tumor microenvironment. In this study, we performed bioinformatics analysis to identify genes and the underlying mechanisms that improve the efficacy of PD-L1 inhibition. Two public datasets of gene expression profiles, (1) HCC tumor versus adjacent normal tissue (N = 214) and (2) normoxia versus anoxia of HepG2 cells (N = 6), were collected from Gene Expression Omnibus (GEO) database. We identified HCC-signature and hypoxia-related genes, using differential expression analysis, and their 52 overlapping genes. Of these 52 genes, 14 PD-L1 regulator genes were further identified through the multiple regression analysis of TCGA-LIHC dataset (N = 371), and 10 hub genes were indicated in the protein-protein interaction (PPI) network. It was found that POLE2, GABARAPL1, PIK3R1, NDC80, and TPX2 play critical roles in the response and overall survival in cancer patients under PD-L1 inhibitor treatment. Our study provides new insights and potential biomarkers to enhance the immunotherapeutic role of PD-L1 inhibitors in HCC, which can help in exploring new therapeutic strategies.

Post-transplantation cyclophosphamide as GVHD prophylaxis in allogenic hematopoietic stem cell transplantation: Recent advances and modification.

Allogenic hematopoietic stem cell transplantation (allo-HSCT) is the most important therapeutic option for hematological disorders, although graft-versus-host disease (GVHD) remains the main cause of mortality. Post-transplantation cyclophosphamide (PTCY) induces immune tolerance and is associated with a low incidence of GVHD and non-relapse mortality. Therefore, PTCY has emerged as a safe and effective GVHD prophylaxis in haploidentical transplantation and has been expanded to matched related or unrelated donor and mismatched unrelated donor HSCT. On the basis of current understanding of the mechanisms of PTCY and antithymocyte globulin (ATG) in the prevention of GVHD, growing evidence suggests that the combination of ATG and PTCY could improve allo-HSCT clinical outcomes. Further research will focus on optimizing PTCY regimens by modifying the timing of administration or adding other immunosuppressive agents.

Research trends in transient receptor potential vanilloid in cardiovascular disease: Bibliometric analysis and visualization.

Background: Transient receptor potential vanilloid (TRPV) is one of the transient receptor potential protein groups; cardiovascular system disease is a crucial cause of mortality among people globally. Objective: This article is intended to accomplish a bibliometric analysis of the trends and public interest since TRPV was reported for the first time. Methods: The article summarized the Web of Science (WOS) Core Collection on the relationship between TRPV and cardiovascular system disease each year from 2000 to 2021. Data extraction and visualization were completed by R package bibliometrix. Keyword citation burst and co-citation networks were generated and produced by CiteSpace. The map evaluating the distribution of country and region was painted in GunnMap 2 (lert.co.nz). The ranking was performed using the Standard Competition Ranking method. Co-authorship and co-occurrence were analyzed with VOSviewer. Results: After removing duplicated data, books, conference proceedings, and articles of uncertain age, 493 were included, and 17 were excluded. The pattern of publication years showed that the number of publications increased rapidly from 2008 to 2021 with no peak in the number of publications until 2021. The geographical distribution pattern revealed a considerable gap in the number of publications between the United States, China, and other countries, with East Asian institutions leading the world in this area. The pattern of co-authorship showed that 77 institutions were divided into 19 clusters, each covering one country or region.These results suggest that intercontinental cooperation among institutions should be strengthened. The core authors section displayed the change in the most published authors. Keyword analysis listed six burst keywords. Co-citation analysis of references from 2011 to 2021 showed the number and centrality of citations to leading articles. Conclusion: Our findings reveal trends and public interest in transient receptor potential vanilloid for cardiovascular disease. These findings suggest that the field has experienced significant growth since 2008, with the United States and China in dominant positions. Our findings also suggest that intercontinental cooperation should be strengthened, and that future research hotspots may focus on pharmacological mechanisms and in-depth exploration of drug clinical trials and new clinical disease application areas such as hypertension, diabetes, and cardiac arrhythmias, which could serve as a foundation for further research.

Development and Validation of a Combined MRI Radiomics, Imaging and Clinical Parameter-Based Machine Learning Model for Identifying Idiopathic Central Precocious Puberty in Girls.

BACKGROUND: Idiopathic central precocious puberty (ICPP) impairs child development, without early intervention. The current reference standard, the gonadotropin-releasing hormone stimulation test, is invasive which may hinder diagnosis and intervention. PURPOSE: To develop a model for accurate diagnosis of ICPP, by integrating pituitary MRI, carpal bone age, gonadal ultrasound, and basic clinical data. STUDY TYPE: Retrospective. POPULATION: A total of 492 girls with PP (185 with ICPP and 307 peripheral precocious puberty [PPP]) were randomly divided by reference standard into training (75%) and internal validation (25%) data. Fifty-one subjects (16 with ICPP, 35 with PPP) provided by another hospital as external validation. FIELD STRENGTH/SEQUENCE: T1-weighted (spin echo [SE], fast SE, cube) and T2-weighted (fast SE-fat suppression) imaging at 3.0 T or 1.5 T. ASSESSMENT: Radiomics features were extracted from pituitary MRI after manual segmentation. Carpal bone age, ovarian, follicle and uterine volumes and endometrium presence were assessed from radiographs and gonadal ultrasound. Four machine learning methods were developed: a pituitary MRI radiomics model, an integrated image model (with pituitary MRI, gonadal ultrasound and bone age), a basic clinical model (with age and sex hormone data), and an integrated multimodal model combining all features. STATISTICAL TESTS: Intraclass correlation coefficients were used to assess consistency of segmentation. Receiver operating characteristic (ROC) curves and the Delong tests were used to assess and compare the diagnostic performance of models. P < 0.05 was considered statistically significant. RESULTS: The area under of the ROC curve (AUC) of the pituitary MRI radiomics model, integrated image model, basic clinical model, and integrated multimodal model in the training data was 0.668, 0.809, 0.792, and 0.860. The integrated multimodal model had higher diagnostic efficacy (AUC of 0.862 and 0.866 for internal and external validation). CONCLUSION: The integrated multimodal model may have potential as an alternative clinical approach to diagnose ICPP. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Orbital-Hybridization-Driven Charge Density Wave Transition in CsV3 Sb5 Kagome Superconductor.

Owing to its inherent non-trivial geometry, the unique structural motif of the recently discovered kagome topological superconductor AV3 Sb5 (A = K, Rb, Cs) is an ideal host of diverse topologically non-trivial phenomena, including giant anomalous Hall conductivity, topological charge order, charge density wave (CDW), and unconventional superconductivity. Despite possessing a normal-state CDW order in the form of topological chiral charge order and diverse superconducting gaps structures, it remains unclear how fundamental atomic-level properties and many-body effects including Fermi surface nesting, electron-phonon coupling, and orbital hybridization contribute to these symmetry-breaking phenomena. Here, the direct participation of the V3d-Sb5p orbital hybridization in mediating the CDW phase transition in CsV3 Sb5 is reported. The combination of temperature-dependent X-ray absorption and first-principles studies clearly indicates the inverse Star-of-David structure as the preferred reconstruction in the low-temperature CDW phase. The results highlight the critical role that Sb orbitals play and establish orbital hybridization as the direct mediator of the CDW states and structural transition dynamics in kagome unconventional superconductors. This is a significant step toward the fundamental understanding and control of the emerging correlated phases from the kagome lattice through the orbital interactions and provides promising approaches to novel regimes in unconventional orders and topology.

Experimental Study on the Bending and Shear Behaviors of Chinese Paulownia Wood at Elevated Temperatures.

Chinese Paulownia wood has been extensively used in the construction of timber buildings and lightweight sandwich structures. However, the bending and shear behaviors at elevated temperatures were not well understood. A total of 162 specimens were tested to investigate the bending, tangential shear, and radial shear performances of Chinese Paulownia wood under temperatures from 20 to 220 °C. It was found that the bending specimens exhibited ductile failure due to the progressive damage after reaching the peak load, while the tangential and radial shear specimens exhibited brittle shear failure along the shear plane. The elevated temperatures had limited effects on the failure modes. Under the same temperature, the retention rate of the modulus of elasticity is significantly higher than that of the modulus of rupture. Moreover, the bending strength, tangential shear strength, and radial shear strength generally and nonlinearly decreased with the increasing temperature. The EN 1995-1-2 design curve for the shear strength of wood at elevated temperatures is conservative for both the tangential and radial shear specimens. However, the design curve may not be adopted to estimate the tangential shear strength at temperatures higher than 220 °C.

Modelling of Web-Crippling Behavior of Pultruded GFRP I Sections at Elevated Temperatures.

The concentrated transverse load may lead to the web crippling of pultruded GFRP sections due to the lower transverse mechanical properties. Several investigations have been conducted on the web-crippling behavior of the GFRP sections under room temperature. However, the web-crippling behavior is not yet understood when subjected to elevated temperatures. To address this issue, a finite element model considering the temperature-dependent material properties, Hashin failure criterion and the damage evolution law are successfully developed to simulate the web-crippling behavior of the GFRP I sections under elevated temperatures. The numerical model was validated by the web-crippling experiments at room temperature with the end-two-flange (ETF) and end bearing with ground support (EG) loading configurations. The developed model can accurately predict the ultimate loads and failure modes. Moreover, it was found that the initial damage was triggered by exceeding the shear strength at the web-flange junction near the corner of the bearing plate and independent of the elevated temperatures and loading configurations. The ultimate load and stiffness decreased obviously with the increasing temperature. At 220 °C, the ultimate load of specimens under ETF and EG loading configurations significantly decreased by 57% and 62%, respectively, whereas the elastic stiffness obviously reduced by 87% and 88%, respectively.

Evaluation of the Shear Performance of Douglas-Fir Wood at Elevated Temperatures.

Shear fracture frequently occurs in timber beams and panels subjected to transverse loads. At elevated temperatures, wood will undergo complex physical and chemical processes which significantly affect the shear properties. In this paper, the v-notched Douglas-fir specimens with three different shear planes: (a) Radial-Tangential (RT); (b) Radial-Longitudinal (RL), and (c) Longitudinal-Radial (LR), were fabricated and tested under the elevated temperatures from 20 °C to 180 °C. The digital image correlation (DIC) technique was used to measure the shear strain. It was found that the shear plane had a significant effect on the failure modes, shear strength, and shear modulus. The shear strength and shear modulus generally decreased with the increase of temperature. However, the shear strength was significantly improved when the hardening of the dry lignin occurred between 100 °C and 140 °C. Moreover, the design curve for the shear strength in Eurocode 5 is conservative for all the specimens with different shear planes.

Calculation of Radiative Properties for [82%Ar-18%CO2]-Fe Plasmas in MAG Welding Arc.

This paper is dedicated to the calculation of the radiative properties of 82%argon-18%CO2 thermal plasmas with the addition of metallic vapors (iron, in the present case, due to workpiece and wire erosion), this mixture being representative of metal active gas (MAG) arc welding processes. These radiative properties are obtained in the frame of the net emission coefficient (NEC) theory, using the recent and accurate "line by line" method. All significant radiative contribution mechanisms are taken into account in the calculation: atomic lines, atomic continuum (radiative attachment, radiative recombination, and bremsstrahlung), molecular bands for diatomic and polyatomic molecules, and molecular continuum. Broadening phenomena (Doppler and pressure effects) are also carefully treated for bound-bound transitions (atomic lines and molecular bands). Regarding 82%Ar-18%CO2 plasma, the results obtained demonstrate the key role of molecular bands at low temperatures (T < 4 kK), whereas the atomic line and continuum prevailed at intermediate and high temperatures. With the addition of a few percentages of iron vapor, it was shown that the total NEC is significantly increased (especially at low temperatures) and that the atomic and ionic lines become dominant in all the studied temperature ranges (3−30 kK). This theoretical study will constitute a groundwork to build a diagnostic method (based on the calculation of partial NECs for accurately chosen spectral intervals) for the determination of plasma temperature and iron vapor concentration in welding arcs.

Sequential Nano-Penetrators of Capillarized Liver Sinusoids and Extracellular Matrix Barriers for Liver Fibrosis Therapy.

During liver fibrogenesis, liver sinusoidal capillarization and extracellular matrix (ECM) deposition construct dual pathological barriers to drug delivery. Upon capillarization, the vanished fenestrae in liver sinusoidal endothelial cells (LSECs) significantly hinder substance exchange between blood and liver cells, while excessive ECM further hinders the delivery of nanocarriers to activated hepatic stellate cells (HSCs). Herein, an efficient nanodrug delivery system was constructed to sequentially break through the capillarized LSEC barrier and the deposited ECM barrier. For the first barrier, LSEC-targeting and fenestrae-repairing nanoparticles (named HA-NPs/SMV) were designed on the basis of the modification with hyaluronic acid and the loading of simvastatin (SMV). For the second barrier, collagenase I and vitamin A codecorated nanoparticles with collagen-ablating and HSC-targeting functions (named CV-NPs/siCol1α1) were prepared to deliver siCol1α1 with the goal of inhibiting collagen generation and HSC activation. Our in vivo results showed that upon encountering the capillarized LSEC barrier, HA-NPs/SMV rapidly released SMV and exerted a fenestrae-repairing function, which allowed more CV-NPs/siCol1α1 to enter the space of Disse to degrade deposited collagen and finally to achieve higher accumulation in activated HSCs. Scanning electronic microscopy images showed the recovery of liver sinusoids, and analysis of liver tissue sections demonstrated that HA-NPs/SMV and CV-NPs/siCol1α1 had a synergetic effect. Our pathological barrier-normalization strategy provides an antifibrotic therapeutic regimen.

Efficacy and safety of sodium oligomannate in the treatment of Alzheimer's disease.

To evaluate the efficacy and safety of sodium oligomannate in the treatment of Alzheimer's disease. Patients with mild-to-moderate AD were randomly divided into three groups, the scores of ADAS-Cog, ADL, CIBIC-plus, NPI and CSDD were evaluated at the 0th, 12th, 24th, 36th and 48th weeks of medication. Comparing the mean scores of each scale in each cycle of each group. Using SPSS21.0 software for measurement data using t test, Chi-square test was used for counting data. A total of 72 patients with AD were included. The difference of CIBIC-plus score at week 12(P=0.007) and 24(P=0.005), ADAS-Cog scores (P=0.01) at week 24 in GV-971 group was statistically significant compared with that in the control group. The CIBIC-plus score at week 24(P=0.01) and week 48 (P=0.04), CSDD scores at week 48(P=0.02) of GV-971 group was statistically significant compared with that of donepezil group. There were 2 cases of adverse reaction of increased stool frequency in GV-971 (5.67%), and 2 cases of adverse reaction of nausea in donepezil group (8.33%), the difference was statistically significant. GV-971 is as effective as donepezil in the treatment of Alzheimer's disease, and may even be better. It has good safety.

MiR-223-3p alleviates trigeminal neuropathic pain in the male mouse by targeting MKNK2 and MAPK/ERK signaling.

BACKGROUND: Trigeminal neuralgia (TN) is a neuropathic pain that occurs in branches of the trigeminal nerve. MicroRNAs (miRNAs) have been considered key mediators of neuropathic pain. This study was aimed to elucidate the pathophysiological function and mechanisms of miR-223-3p in mouse models of TN. METHODS: Infraorbital nerve chronic constriction injury (CCI-ION) was applied in male C57BL/6J mice to establish mouse models of TN. Pain responses were assessed utilizing Von Frey method. The expression of miR-223-3p, MKNK2, and MAPK/ERK pathway protein in trigeminal ganglions (TGs) of CCI-ION mice was measured using RT-qPCR and Western blotting. The concentrations of inflammatory cytokines were evaluated using Western blotting. The relationship between miR-223-3p and MKNK2 was tested by a luciferase reporter assay. RESULTS: We found that miR-223-3p was downregulated, while MKNK2 was upregulated in TGs of CCI-ION mice. MiR-223-3p overexpression by an intracerebroventricular injection of Lv-miR-223-3p attenuated trigeminal neuropathic pain in CCI-ION mice, as well as reduced the protein levels of pro-inflammatory cytokines in TGs of CCI-ION mice. MKNK2 was verified to be targeted by miR-223-3p. Additionally, miR-223-3p overexpression decreased the phosphorylation levels of ERK1/2, JNK, and p38 protein in TGs of CCI-ION mice to inhibit MAPK/ERK signaling. CONCLUSIONS: Overall, miR-223-3p attenuates the development of TN by targeting MKNK2 to suppress MAPK/ERK signaling.