A comprehensive exploration of astrocytes in migraine: a bibliometric and visual analysis.

BACKGROUND: Migraine, as a prevalent neurologic disorder, involves intricate and yet incompletely elucidated pathophysiological mechanisms. A plethora of research findings underscores the pivotal role played by astrocytes in the progression of migraines. In order to elucidate the current advances and directions in research pertaining to astrocytes in migraines, we conducted bibliometric analysis of relevant literature and visualized the results. Subsequently, we expound upon these findings to contribute to the evolving understanding of the role of astrocytes in migraine pathophysiology. METHODS: On November 21, 2023, we conducted a search on Web of Science (WOS), restricting the document type to articles or reviews and language to English. Following a meticulous selection process involving three researchers, we identified the literature to be included in our analysis. Subsequently, we employed Microsoft Office Excel programs, R, VOSviewer, Scimago Graphica, and CiteSpace software to conduct visualization analysis of basic information and trends regarding journals, countries/regions, and influential authors, institutions, keywords, and papers. RESULTS: As of November 21, 2023, relevant literature has been published in 71 journals across 27 countries/regions. This corpus comprises contributions from 576 authors affiliated with 220 institutions, encompassing 865 keywords and referencing 6065 scholarly articles. CEPHALALGIA stands out as the most influential journal in this field, while authors PIETROBON D and DALKARA T have significant impact. The United States is highly influential, with CNR and UNIV PADUA emerging as highly influential institutions. The predominant category is Neurosciences. CONCLUSIONS: Future investigators may continue to focus on migraines with aura, familial hemiplegic migraine (FHM), and the crucial calcitonin gene-related peptide (CGRP) system. Employing advanced observational techniques, such as imaging, researchers should pay attention to cellular and tissue structures, such as microglia and the trigeminal ganglion, as well as mechanisms involving inflammation and central sensitization. Moreover, animal models are paramount in obtaining high-quality evidence.

Paris saponin VII inhibits triple-negative breast cancer by targeting the MEK/ERK/STMN1 signaling axis.

BACKGROUND: Triple-negative breast cancer (TNBC) is a category of breast cancer characterized with high molecular heterogeneity. Owing to the lack of effective therapeutic strategies, patients with TNBC have a poor prognosis. Paris saponin VII (PSⅦ), a steroidal saponin extracted from the rhizome of Trichillium tschonoskii Maxim, exhibits excellent anti-cancer activity in a variety of solid tumors. However, the role and potential mechanism of PSⅦ against TNBC remain unexplored. PURPOSE: This study aimed to elucidate the therapeutic effects of PSⅦ against TNBC and explore the potential mechanism of action. METHODS: We combined the analysis of public single-cell sequencing data with weighted gene co-expression network analysis (WGCNA) to identity differentially expressed genes (DEGs) that distinguished malignant and normal epithelial cells in TNBC. Subsequently, the biological features of DEGs in TNBC were evaluated. Gene set enrichment analysis (GSEA) was used to define potential pathways associated with the DEGs. The pharmacological activity of PSⅦ for TNBC was evidenced via in vitro and in vivo experiments, and molecular docking, molecular dynamics (MD), surface plasmon resonance (SPR) assay and western blotting were employed to confirm the relative mechanisms. RESULTS: Single-cell sequencing and WGCNA revealed STMN1 as a pivotal biomarker of TNBC. STMN1 overexpression in TNBC was associated with poor patient prognosis. GSEA revealed a significant accumulation of STMN1 within the MAPK signaling pathway. Furthermore, In vitro experiments showed that PSⅦ showed significantly suppressive actions on the proliferation, migration and invasion abilities for TNBC cells, while inducing apoptosis. Molecular docking, MD analysis and SPR assay indicated a robust interaction between PSⅦ and the MEK protein. Western blotting revealed that PSⅦ may inhibit tumor progression by suppressing the phosphorylation of MEK1/2 and the downstream phosphorylation of ERK1/2 and STMN1. Intraperitoneal injection of PSⅦ (10 mg/kg) notably reduced tumor growth by 71.26 % in a 4T1 xenograft model. CONCLUSION: In our study, the systems biology method was used to identify potential therapeutic targets for TNBC. In vitro and in vivo experiments demonstrated PSⅦ suppresses cancer progression by targeting the MEK/ERK/STMN1 signaling axis. For the first time, the inhibition of STMN1 phosphorylation has been indicated as a possible mechanism for the anticancer effects of PSⅦ. These results emphasize the potential value of PSⅦ as a promising anti-cancer drug candidate for further development in the field of TNBC therapeutics.

Identifying suicide attempter in major depressive disorder through machine learning: the importance of pain avoidance, event-related potential features of affective processing.

How to achieve a high-precision suicide attempt classifier based on the three-dimensional psychological pain model is a valuable issue in suicide research. The aim of the present study is to explore the importance of pain avoidance and its related neural features in suicide attempt classification models among patients with major depressive disorder. By recursive feature elimination with cross-validation and support-vector-machine algorithms, scores from the measurements and the task-based EEG signals were chosen to achieve a suicide attempt classification model. In the multimodal suicide attempt classifier with an accuracy of 83.91% and an area under the curve of 0.90, pain avoidance ranked as the top one in the optimal feature set. Theta (reward positive feedback minus neutral positive feedback) was the shared neural representation ranking as the top one of event-related potential features in pain avoidance and suicide attempt classifiers. In conclusion, the suicide attempt classifier based on pain avoidance and its related affective processing neural features has excellent accuracy among patients with major depressive disorder. Pain avoidance is a stable and strong indicator for identifying suicide risks in both traditional analyses and machine-learning approaches. A novel methodology is needed to clarify the relationship between cognitive and affective processing evoked by punishment stimuli and pain avoidance.

Drug-related side effects and adverse reactions in the treatment of migraine: a bibliometric and visual analysis.

Background: Migraine imposes a substantial global burden, impacting patients and society. Pharmacotherapy, as a primary treatment, entails specific adverse reactions. Emphasizing these reactions is pivotal for improving treatment strategies and enhancing patients' well-being. Thus, we conducted a comprehensive bibliometric and visual analysis of relevant literature. Methodology: We conducted a comprehensive search on the Science Citation Index Expanded within the Web of Science, restricting the literature for analysis based on criteria such as document type, publication date, and language. Subsequently, we utilized various analytical tools, including VOSviewer, Scimago Graphica, the R package 'bibliometrix', CiteSpace, and Excel programs, for a meticulous examination and systematic organization of data concerning journals, authors, countries/regions, institutions, keywords, and references. Results: By August 31, 2023, the literature was distributed across 379 journals worldwide, authored by 4,235 individuals from 1726 institutions. It featured 2,363 keywords and 38,412 references. 'HEADACHE' led in publication count, with 'SILBERSTEIN S' as the most prolific author. The United States ranked highest in publication volume, with 'UNIV COPENHAGEN' leading among institutions. Conclusion: Our research findings indicate that researchers in the field continue to maintain a focus on the calcitonin gene-related peptide (CGRP) system and explore diverse mechanisms for drug development through the application of novel biotechnological approaches. Furthermore, it is imperative to enhance the assessment of clinical trial outcomes, consistently monitor the efficacy and safety of prominent drugs such as Erenumab and Fremanezumab. There is a need for further evaluation of acute and preventive treatments tailored to different populations and varying types of migraine.

Polysaccharide from Clitocybe squamulosa: Gel-forming properties and its compound effect with food thickener.

To study the gel-forming properties of polysaccharide from the fruiting body of Clitocybe squamulosa (CSFP) and its degradation product (UH-CSFP), the changes in steady-state and dynamic rheological properties of CSFP and UH-CSFP under different conditions (polysaccharide mass fraction, temperature, pH, and salt ion concentration) were studied. Polysaccharides with good gel-forming properties were selected and mixed with common edible thickeners (gelatin, guar gum, and locust bean gum), after which the properties of the composite gel were assessed. The steady-state rheological results showed that CSFP and UH-CSFP were pseudoplastic fluids, their apparent viscosity decreased with increasing temperature, the viscosity was greatest when the pH was 7. The addition of Na+ and Ca2+ could increase the viscosity, and the viscosity of UH-CSFP was lower than that of CSFP at the same mass fraction. The results of dynamic rheology indicated that G´ and G´´ of CSFP and UH-CSFP increased with increasing mass fraction, pH, and ion concentration (0.01 M to 1 M), and G´´ was always smaller than G´ indicating weak gel behavior. The thixotropy-related experimental results showed that the thixotropy ring area of CSFP and UH-CSFP increased with increasing mass fraction, the ring area of CSFP was larger than that of UH-CSFP, and the gel strength of CSFP was greater than that of UH-CSFP. The results of CSFP and three types of edible gels showed that the composite gels were pseudoplastic fluids, and their apparent viscosity was ranked (in descending order) as follows: guar bean gum, locust bean gum, and gelatin. The addition of CSFP improved the gel-forming properties of guar gum but did not significantly improve the gel properties of locust bean gum and gelatin. This study provides a theoretical basis for the selection of processing methods and the application of polysaccharides.

Pharmacokinetics and pharmacodynamics of cyclodextrin-based oral drug delivery formulations for disease therapy.

Oral drug administration has become the most common and preferred mode of disease treatment due to its good medication adherence and convenience. For orally administered drugs, the safety, efficacy, and targeting ability requirements have grown as disease treatment research advances. It is difficult to obtain prominent efficacy of traditional drugs simply via oral administration. Numerous studies have demonstrated that cyclodextrins (CDs) can improve the clinical applications of certain orally administered drugs by enhancing their water solubility and masking undesirable odors. Additionally, deeper studies have discovered that CDs can influence disease treatment by altering the drug pharmacokinetics (PK) or pharmacodynamics (PD). This review highlights recent research progress on the PK and PD effects of CD-based oral drug delivery in disease therapy. Firstly, the review describes the characteristics of current drug delivery modes in oral administration. Besides, we minutely summarized the different CD-containing drugs, focusing on the impact of CD-based alterations in PK or PD of orally administered drugs in treating diseases. Finally, we deeply discussed current challenges and future opportunities with regard to PK and PD of CD-based oral drug delivery formulations.

The blockade of the TGF-ß pathway alleviates abnormal glucose and lipid metabolism of lipodystrophy not obesity.

TGF-ß is thought to be involved in the physiological functions of early organ development and pathological changes in substantial organ fibrosis, while studies around adipose tissue function and systemic disorders of glucolipid metabolism are still scarce. In this investigation, two animal models, aP2-SREBP-1c mice and ob/ob mice, were used. TGF-ß pathway showed up-regulated in the inguinal white adipose tissue (iWAT) of the two models. SB431542, a TGF-ß inhibitor, successfully increased inguinal white adipocyte size by more than 1.5 times and decreased the weight of Peripheral organs including liver, Spleen and Kidney to 73.05%/62.18%/73.23% of pre-administration weights. The iWAT showed elevated expression of GLUTs and lipases, followed by a recovery of circulation GLU, TG, NEFA, and GLYCEROL to the wild-type levels in aP2-SREBP-1c mice. In contrast, TGF-ß inhibition did not have similar effects on that of ob/ob mice. In vitro, TGF-ß blocker treated mature adipocytes had considerably higher levels of glycerol and triglycerides than the control group, whereas GLUTs and lipases expression levels were unchanged. These findings show that inhibiting the abnormally upregulated TGF-ß pathway will only restore iWAT expansion and ameliorate the global metabolic malfunction of glucose and lipids in lipodystrophy, not obesity.

The Effects of Naematelia aurantialba on the Pasting and Rheological Properties of Starch and the Research and Development of Soft Candy.

To study the effects of Naematelia aurantialba (NA) on the rheological and gelatinization properties of starch, the processing methods of NA were diversified. In this study, the gelatinization and rheological properties of corn starch (CS) and edible cassava starch (ECS) were investigated by adding NA with different mass fractions. Starch soft candy was prepared using NA, CS, and ECS as the main raw materials. Rheological studies showed that both CS-NA and ECS-NA exhibited elastic modulus (G') > viscosity modulus (G″), implying elastic behavior. G' was such that CS+1%NA > CS+5%NA > CS+3%NA > CS > CS+2%NA > CS+4%NA > ECS+4%NA > ECS+3%NA > ECS+5%NA > ECS+2%NA > ECS+1%NA > ECS. The gelatinization implied showed that after adding NA, the pasting temperature of CS-NA and ECS-NA increased by 1.33 °C and decreased by 2.46 °C, while their breakdown values decreased by 442.35 cP and 866.98 cP, respectively. Through a single-factor test and orthogonal test, the best formula of starch soft candy was as follows: 0.4 f of NA, 10 g of white granulated sugar, a mass ratio of ECS to CS of 20:1 (g:g), 0.12 g of citric acid, 1 g of red date power, and 16 mL of water. The soft candy was stable when stored for two days. This study offers a new direction for the research and development of NA starch foods.

Cyclodextrin based nanoparticles for smart drug delivery in colorectal cancer.

The advancement of colorectal cancer (CRC) prevention, detection, and treatment is essential to ensure that survivors live longer and higher-quality lives. The field of cancer detection and therapy has undergone a revolution with the development of nanotechnology for targeted drug delivery. The significant problems with the delivery of cancer drugs are their solubility, stability, and nonspecific distribution. There is a challenge that the acidic and enzymatic environment in the digestive tract will modify or destroy the medication or the active pharmaceutical ingredient. To overcome the problems, nanoparticles have been widely employed during the past several years to increase the specificity, selectivity, and controlled release of drug delivery systems. The site-specific and targeted delivery leads to reduce toxicity and side effects. With respect to the capability and utilization of cyclodextrin-based nanoparticles in different aspects of the tumour microenvironment and gut microbiota, a survey of current research papers was conducted via looking through databases including GoogleScholar, PubMed, Web of Science, and Scopus. This review aims to summarize cutting-edge nanoparticulate-based technologies and therapies for CRC.

Low-cost and simple optical system based on wavefront coding and deep learning.

With the development of computational imaging, the integration of optical system design and digital algorithms has made more imaging tasks easier to perform. Wavefront coding (WFC) is a typical computational imaging technique that is used to address the constraints of optical aperture and depth of field. In this paper, we demonstrated a low-cost and simple optical system based on WFC and deep learning. We constructed an optimized encoding method for the phase plate under the framework of deep learning, which reduces the requirement for aberration correction in the full field of view. Optical coding was achieved with just a double-bonded lens and a simple cubic phase mask, and digital decoding used the deep residual UNet++ network framework. The final image obtained has good resolution, whereas the depth of field of the system expanded by a factor of 13, which is of great significance for the high-precision inspection and attaching of small parts of machine vision.

Research Progress of Natural Matrine Compounds and Synthetic Matrine Derivatives.

Matrine is a quinoline alkaloid extracted and separated from the dried root, fruit, and other parts of the plant Sophora flavescens using an organic solvent. Matrine exhibits a variety of biological activities and is widely used in pharmacy, agronomy, and other fields. Due to its low bioavailability, poor chemical stability, and toxicity to the central nervous system, a large number of researchers have searched for matrine derivatives with higher biological activity and safety by modifying its structure. In this review article, the research progress of matrine derivatives obtained using two methods (extraction from Sophora flavescens and structural modifications) from 2018 to 2022 in terms of pharmacological activity, mechanism of action, and structure-activity relationship are presented. The modification of matrine over the past five years has been mainly on the D-ring. Many new matrine alkaloids have been extracted from natural products, some of which have good pharmacological activity, which broadens the strategy for matrine structural modification in the future.

MAT as a promising therapeutic strategy against triple-negative breast cancer via inhibiting PI3K/AKT pathway.

Triple-negative breast cancer (TNBC), a highly aggressive and heterogeneous subtype of breast cancer, lacks effective treatment options. Sophora flavescens Aiton, a Chinese medicinal plant, is often used in traditional Chinese medicine to treat cancer. Matrine (MAT) is an alkaloid extracted from Sophora flavescens. It has good anticancer effects, and thus can be explored as a new therapeutic agent in TNBC research. We performed bioinformatics analysis to analyze the differentially expressed genes between normal breast tissues and TNBC tissues, and comprehensive network pharmacology analyses. The activity and invasion ability of TNBC cells treated with MAT were analyzed. Apoptosis and cell cycle progression were determined using cytometry. We used Monodansylcadaverine (MDC) staining to determine the condition of autophagosomes. Finally, the expression levels of the key target proteins of the PI3K/AKT pathway were determined using western blotting. The proliferation and invasion ability of MDA-MB-231 and MDA-MB-468 can be effectively inhibited by MAT. The results of flow cytometry indicated that MAT arrested the TNBC cell cycle and induced apoptosis. In addition, we confirmed that MAT inhibited the expression of BCL-2 while up-regulating the expression of cleaved caspase-3. Moreover, enhanced intensity of MDC staining and high LC3-II expression were observed, which confirmed that MAT induced autophagy in TNBC cells. Western blotting showed that MAT inhibited the PI3K/AKT pathway and downregulated the expressions of PI3K, AKT, p-AKT, and PGK1. This study provides feasible methods, which include bioinformatics analysis and in vitro experiments, for the identification of compounds with anti-TNBC properties. MAT inhibited the PI3K/AKT signaling pathway, arrested cell cycle, as well as promoted cell apoptosis and autophagy. These experiments provide evidence for the anti-TNBC effect of MAT and identified potential targets against TNBC.

Simultaneous quantification of pirarubicin, doxorubicin, cyclophosphamide, and vincristine in human plasma of patients with non-Hodgkin's lymphoma by LC-MS/MS method.

Pirarubicin (THP), doxorubicin (DOX), cyclophosphamide (CTX), and vincristine (VCR) are widely used in the treatment of patients with non-Hodgkin's Lymphoma. Herein, a precise and sensitive method was developed for the determination of THP, DOX, CTX and VCR in human plasma by high-performance liquid-chromatography-tandem mass spectrometry (LC-MS/MS). Liquid-liquid extraction was applied to extract THP, DOX, CTX, VCR, and the internal standard (IS, Pioglitazone) in plasma. Agilent Eclipse XDB-C18 (3.0 mm × 100 mm) was utilized and chromatographic separation was obtained in eight minutes. Mobile phases were composed of methanol and buffer (10 mM ammonium formate containing 0.1% formic acid). The method was linear within the concentration range of 1-500 ng/mL for THP, 2-1000 ng/mL for DOX, 2.5-1250 ng/mL for CTX, and 3-1500 ng/mL for VCR. The intra- and inter-day precisions of QC samples were found to be below 9.31 and 13.66%, and accuracy ranged from -0.2 to 9.07%, respectively. THP, DOX, CTX, VCR and the internal standard were stable in several conditions. Finally, this method was successfully utilized to simultaneously determine THP, DOX, CTX and VCR in human plasma of 15 patients with non-Hodgkin's Lymphoma after intravenous administration. Finally, the method was successfully employed in the clinical determination of THP, DOX, CTX, and VCR in patients with non-Hodgkin lymphoma after administration of RCHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) regimens.

A quantum algorithm for heat conduction with symmetrization.

Heat conduction, driven by thermal non-equilibrium, is the transfer of internal thermal energy through physical contacts, and it exists widely in various engineering problems, such as spacecraft and state-of-the-art dilution refrigerators. The mathematical equation for heat conduction is a prototypical partial differential equation. Here we report a quantum algorithm for heat conduction (QHC) that significantly outperforms classical algorithms. We represent the original heat conduction system by a symmetric system with an ancilla qubit so that the quantum circuit complexity is polylogarithmic in the number of discretized grid points. Compared with the existing algorithms based on solving linear equations via the Harrow-Hassidim-Lloyd (HHL) algorithm, our method evolves the linear process directly without phase estimation, which involves complex quantum operations and large output error. Therefore, this algorithm is experimental-friendly and without output error after the discretization procedure. We experimentally implemented the algorithm for a one-dimensional thermal conduction process with two-edge constant temperatures and adiabatic conditions on a nuclear spin quantum processor. The spatial and temporal distributions of the temperature are accurately determined from the experimental results. Our work can be naturally applied to any physical processes that can be reduced to the heat equation.

Exploring the mechanism of anti-fatigue of resveratrol based on network pharmacology and molecular docking, and in vitro studies.

To investigate the potential mechanism of resveratrol in anti-fatigue by network pharmacology and molecular docking, and to investigate the anti-fatigue efficacy of resveratrol through in vitro animal experiments. Resveratrol action targets and fatigue-related targets were obtained using various databases. The anti-fatigue targets of resveratrol were obtained using the Venn diagram, uploaded to the String database, imported into Cytoscape 3.7.1, and constructed into a Protein-protein interaction network. The target genes were then subjected to Gene ontology and Kyoto encyclopedia of gene and genome enrichment analysis. Molecular docking verification was performed on the binding ability of the core target to resveratrol. Using swimming-trained mice as exercise models, exhaustive swimming time and fatigue-related biochemical parameters were used as indicators to investigate the effects of resveratrol on exercise endurance and energy metabolism. 104 anti-fatigue targets and 10 core target genes of resveratrol were obtained. KEGG analysis enrichment included AGE-RAGE signaling pathway in diabetic complications, Human cytomegalovirus infection, and Pathways in cancer. Molecular docking showed that the core target genes TP53, PIK3R1, AKT1, PIK3CA, and MAPK1 had good binding activity to resveratrol. Animal experiments showed that resveratrol could prolong the exhaustive swimming time of endurance-trained mice (P < 0.01), decrease aspartate aminotransferase, alanine aminotransferase, uric acid, blood lactate (P < 0.01), decrease blood urea nitrogen (P < 0.05), increase the liver glycogen, muscle glycogen (P < 0.01). Conclusion: Resveratrol has the characteristics of multiple targets and multiple pathways in anti-fatigue; resveratrol can enhance exercise endurance in mice.

Fusion of pain avoidance and the contingent negative variation induced by punitive condition predict suicide ideation in a college population.

This study examined behavioral and ERP features involved in pain processing as predictors of suicide ideation. Twenty-seven depressed undergraduates with high suicide ideation (HSI), 23 depressed undergraduates with low suicide ideation (LSI), and 32 healthy controls (HCs) completed the clinical Scales. The amplitudes of LPP, P2, P3, CNV, FRN, power in the beta, theta, and delta bands in the SAID task were multimodal EEG features. A machine learning algorithm known as support vector machine was used to select optimal feature sets for predicting pain avoidance, depression, and suicide ideation. The accuracy of suicide ideation classification was significantly higher for multimodal features (78.16%) which pain avoidance ranked the first and the CNV ranked the fifth than a single ERP feature model (66.62%). Pain avoidance emerged as the most optimal feature of suicide ideation classification than depression. And the CNV elicited by punitive cues may be a biomarker in suicide ideation. Pain avoidance and its related EEG components may improve the efficacy of suicide ideation classification as compared to depression.

Fixed-point oblivious quantum amplitude-amplification algorithm.

The quantum amplitude amplification algorithms based on Grover's rotation operator need to perform phase flips for both the initial state and the target state. When the initial state is oblivious, the phase flips will be intractable, and we need to adopt oblivious amplitude amplification algorithm to handle. Without knowing exactly how many target items there are, oblivious amplitude amplification also suffers the "soufflé problem", in which iterating too little "undercooks" the state and too much "overcooks" the state, both resulting in a mostly non-target final state. In this work, we present a fixed-point oblivious quantum amplitude-amplification (FOQA) algorithm by introducing damping based on methods proposed by A. Mizel. Moreover, we construct the quantum circuit to implement our algorithm under the framework of duality quantum computing. Our algorithm can avoid the "soufflé problem", meanwhile keep the square speedup of quantum search, serving as a subroutine to improve the performance of quantum algorithms containing oblivious amplitude amplification procedure.

Comparative Analysis of the Microbial Community Structures Between Healthy and Anthracnose-Infected Strawberry Rhizosphere Soils Using Illumina Sequencing Technology in Yunnan Province, Southwest of China.

Anthracnose caused by Colletotrichum spp. was widespread in recent years and resulted in great damage to strawberry production. Soil microbial communities were key contributors to host nutrition, development, and immunity; however, the difference between the microbial communities of healthy and anthracnose-infected strawberry rhizosphere soils remains unclear. In this study, the Illumina sequencing technique was used to comparatively study the prokaryotic and fungal community compositions and structures between healthy and anthracnose-infected strawberry rhizosphere soils in Yuxi, Yunnan Province. Both microbial community diversities and richness of anthracnose-infected strawberry rhizosphere soils were higher than those of healthy strawberry rhizosphere soils. A total of 2,518 prokaryotic and 556 fungal operational taxonomic units (OTUs) were obtained at the 97% similarity threshold. Proteobacteria, Thaumarchaeota, and Acidobacteria were the dominant prokaryotic phyla; Ascomycota, unclassified_k__Fungi, and Mortierellomycota were the dominant fungal phyla. The relative abundances of beneficial bacterial phyla Actinobacteria and Firmicutes, genera Streptomyces, Azospirillum, and Bacillus were significantly reduced in anthracnose-infected strawberry rhizosphere soils; the relative abundance of beneficial fungal species Trichoderma asperellum shows a similar tendency with bacterial abundance. Besides Colletotrichum, 15 other potential fungal pathogen genera and seven fungal pathogen species were identified; among the potential pathogen genera and species, eight pathogen genera and Fusarium oxysporum showed significant differences between healthy and anthracnose-infected strawberry rhizosphere soils. The results suggested that strawberry planted in this area may be infected by other fungal pathogens except for Colletotrichum spp. Our present research will provide theoretical basis and data reference for the isolation and identification of strawberry pathogens and potential probiotics in future works.

Methyl Gallate Suppresses the Migration, Invasion, and Epithelial-Mesenchymal Transition of Hepatocellular Carcinoma Cells via the AMPK/NF-κB Signaling Pathway in vitro and in vivo.

Methyl gallate (MG), a polyphenolic compound found in plants, is widely used in traditional Chinese medicine. MG is known to alleviate several cancer symptoms. However, most studies that have reported the antitumor effects of MG have done so at the cellular level, and the inhibitory effect and therapeutic mechanism of MG in hepatocellular carcinoma (HCC) have not been extensively explored in vivo. We aimed to understand the therapeutic mechanism of MG in HCC in vitro and in vivo. MTT and colony formation assays were used to determine the impact of MG on the proliferation of a human HCC cell line, BEL-7402; wound healing and transwell assays were used to quantify the migration and invasion of HCC cells. Western blotting was used to quantify the expression of the AMPK/NF-κB signaling pathway proteins. In vivo tumor growth was measured in a xenograft tumor nude mouse model treated with MG, and hematoxylin-eosin staining and immunohistochemistry (IHC) were used to visualize the histological changes in the tumor tissue. We found that MG showed anti-proliferative effects both in vitro and in vivo. MG downregulated the protein expression of AMPK, NF-κB, p-NF-κB, and vimentin and upregulated the expression of E-cadherin in a dose-dependent manner. Additionally, MG inhibited the migration and invasion of HCC cells by decreasing MMP9 and MMP2 expression and increasing TIMP-2 expression. These were consistent with the results of IHC in vivo. MG inhibited the proliferation, migration, and invasion of HCC cells. This effect potentially involves the regulation of the AMPK/NF-κB pathway, which in turn impacts epithelial-mesenchymal transition and MMP expression.

Quantum Multi-Round Resonant Transition Algorithm.

Solving the eigenproblems of Hermitian matrices is a significant problem in many fields. The quantum resonant transition (QRT) algorithm has been proposed and demonstrated to solve this problem using quantum devices. To better realize the capabilities of the QRT with recent quantum devices, we improve this algorithm and develop a new procedure to reduce the time complexity. Compared with the original algorithm, it saves one qubit and reduces the complexity with error ϵ from O(1/ϵ2) to O(1/ϵ). Thanks to these optimizations, we can obtain the energy spectrum and ground state of the effective Hamiltonian of the water molecule more accurately and in only 20 percent of the time in a four-qubit processor compared to previous work. More generally, for non-Hermitian matrices, a singular-value decomposition has essential applications in more areas, such as recommendation systems and principal component analysis. The QRT has also been used to prepare singular vectors corresponding to the largest singular values, demonstrating its potential for applications in quantum machine learning.