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Ab initio calculations have an essential role in our fundamental understanding of quantum many-body systems across many subfields, from strongly correlated fermions1-3 to quantum chemistry4-6 and from atomic and molecular systems7-9 to nuclear physics10-14. One of the primary challenges is to perform accurate calculations for systems where the interactions may be complicated and difficult for the chosen computational method to handle. Here we address the problem by introducing an approach called wavefunction matching. Wavefunction matching transforms the interaction between particles so that the wavefunctions up to some finite range match that of an easily computable interaction. This allows for calculations of systems that would otherwise be impossible owing to problems such as Monte Carlo sign cancellations. We apply the method to lattice Monte Carlo simulations15,16 of light nuclei, medium-mass nuclei, neutron matter and nuclear matter. We use high-fidelity chiral effective field theory interactions17,18 and find good agreement with empirical data. These results are accompanied by insights on the nuclear interactions that may help to resolve long-standing challenges in accurately reproducing nuclear binding energies, charge radii and nuclear-matter saturation in ab initio calculations19,20.
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We present the first ab initio lattice calculations of spin and density correlations in hot neutron matter using high-fidelity interactions at next-to-next-to-next-to-leading order in chiral effective field theory. These correlations have a large impact on neutrino heating and shock revival in core-collapse supernovae and are encapsulated in functions called structure factors. Unfortunately, calculations of structure factors using high-fidelity chiral interactions were well out of reach using existing computational methods. In this Letter, we solve the problem using a computational approach called the rank-one operator (RO) method. The RO method is a general technique with broad applications to simulations of fermionic many-body systems. It solves the problem of exponential scaling of computational effort when using perturbation theory for higher-body operators and higher-order corrections. Using the RO method, we compute the vector and axial static structure factors for hot neutron matter as a function of temperature and density. The ab initio lattice results are in good agreement with virial expansion calculations at low densities but are more reliable at higher densities. Random phase approximation codes used to estimate neutrino opacity in core-collapse supernovae simulations can now be calibrated with ab initio lattice calculations.
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BACKGROUND: The perfect repair of damaged skin has always been a constant goal for scientists; however, the repair and reconstruction of skin is still a major problem and challenge in injury and burns medicine. Human amniotic membrane (hAM), with its good mechanical properties and anti-inflammatory, antioxidant and antimicrobial benefits, containing growth factors that promote wound healing, has evolved over the last few decades from simple skin sheets to high-tech dressings, such as being made into nanocomposites, hydrogels, powders, and electrostatically spun scaffolds. This paper aims to explore the historical development, applications, trends, and research hotspots of hAM in wound healing. METHODS: We examined 2660 publications indexed in the Web of Science Core Collection (WoSCC) from January 1, 1975 to July 12, 2023. Utilizing bibliometric methods, we employed VOSviewer, CiteSpace, and R-bibliometrix to characterize general information, identify development trends, and highlight research hotspots. Subsequently, we identified a collection of high-quality English articles focusing on the roles of human amniotic epithelial stem cells (hAESCs), human amniotic mesenchymal stem cells (hAMSCs), and amniotic membrane (AM) scaffolds in regenerative medicine and tissue engineering. RESULTS: Bibliometric analysis identified Udice-French Research Universities as the most productive affiliation and Tseng S.C.G. as the most prolific author. Keyword analysis, historical direct quotations network, and thematic analysis helped us review the historical and major themes in this field. Our examination included the knowledge structure, global status, trends, and research hotspots regarding the application of hAM in wound healing. Our findings indicate that contemporary research emphasizes the preparation and application of products derived from hAM. Notably, both hAM and the cells isolated from it - hADSCs and hAESCs are prominent and promising areas of research in regenerative medicine and tissue engineering. CONCLUSION: This research delivers a comprehensive understanding of the knowledge frameworks, global dynamics, emerging patterns, and primary research foci in the realm of hAM applications for wound healing. The field is rapidly evolving, and our findings offer valuable insights for researchers. Future research outcomes are anticipated to be applied in clinical practice, enhancing methods for disease prevention, diagnosis, and treatment.
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Amnios , Cicatrización de Heridas , Humanos , Ingeniería de Tejidos/métodos , Apósitos Biológicos , Andamios del Tejido , Células Epiteliales/fisiologíaRESUMEN
BACKGROUND: Medical school learning environment (MSLE) has a holistic impact on students' psychosomatic health, academic achievements, and personal development. Students in different grades perceive MSLE in different ways. Thus, it is essential to investigate the specific role of student's grade in the perception of MSLE. METHODS: Using the Johns Hopkins Learning Environment Scale (JHLES) as a quantification instrument for the perception level of MSLE, 10,901 medical students in 12 universities in China were categorized into low or high JHLES group according to their questionnaires. We investigated the relationship between student's grade and JHLES category by univariate analysis employing Pearson Chi-square test and Welch's ANOVA. Then multivariable logistic regression analysis confirmed the predictive efficacy of student's grade. A nomogram concerning the prediction of low JHLES score probability in medical students was also constructed. RESULTS: A significant difference between two JHLES categories among students in different grades was observed (p < 0.001), with the proportion of the high JHLES group dominating in grade 1, 5, and the graduate subgroups (p < 0.001). The mean JHLES score declined especially in the third and fourth graders compared to freshmen (p < 0.001), while the mean score among the fifth graders had a remarkable rebound from the third graders (p < 0.001). Most imperatively, identified by multivariable logistic regression analysis, students in grade 3 (OR = 1.470, 95% CI = 1.265-1.709, p < 0.001) and 4 (OR = 1.578, 95% CI = 1.326-1.878, p < 0.001) perceived more negatively than freshmen. The constructed nomogram provided a promising prediction model for student's low JHLES score probability, with accuracy, accordance, and discrimination (area under the curve (AUC) = 0.627). CONCLUSION: The student's grade was a significant influencing factor in medical students' perception of MSLE. The perceptions among the third and fourth graders got worse, probably due to the worrying changes in various aspects of MSLE during that period. The relevant and appropriate interventions to improve medical students' perceptions are urgently needed.
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Estudiantes de Medicina , Humanos , Estudiantes de Medicina/psicología , Estudios Transversales , China , Femenino , Masculino , Aprendizaje , Encuestas y Cuestionarios , Facultades de Medicina , Adulto Joven , Percepción , Educación de Pregrado en Medicina , AdultoRESUMEN
While first order perturbation theory is routinely used in quantum Monte Carlo (QMC) calculations, higher-order terms present significant numerical challenges. We present a new approach for computing perturbative corrections in projection QMC calculations. We demonstrate the method by computing nuclear ground state energies up to second order for a realistic chiral interaction. We calculate the binding energies of several light nuclei up to ^{16}O by expanding the Hamiltonian around the Wigner SU(4) limit and find good agreement with data. In contrast to the natural ordering of the perturbative series, we find remarkably large second-order energy corrections. This occurs because the perturbing interactions break the symmetries of the unperturbed Hamiltonian. Our method is free from the sign problem and can be applied to QMC calculations for many-body systems in nuclear physics, condensed matter physics, ultracold atoms, and quantum chemistry.
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The strong interactions among nucleons have an approximate spin-isospin exchange symmetry that arises from the properties of quantum chromodynamics in the limit of many colors, N_{c}. However this large-N_{c} symmetry is well hidden and reveals itself only when averaging over intrinsic spin orientations. Furthermore, the symmetry is obscured unless the momentum resolution scale is close to an optimal scale that we call Λ_{large-N_{c}}. We show that the large-N_{c} derivation requires a momentum resolution scale of Λ_{large-N_{c}}â¼500 MeV. We derive a set of spin-isospin exchange sum rules and discuss implications for the spectrum of ^{30}P and applications to nuclear forces, nuclear structure calculations, and three-nucleon interactions.
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We propose a new Monte Carlo method called the pinhole trace algorithm for ab initio calculations of the thermodynamics of nuclear systems. For typical simulations of interest, the computational speedup relative to conventional grand-canonical ensemble calculations can be as large as a factor of one thousand. Using a leading-order effective interaction that reproduces the properties of many atomic nuclei and neutron matter to a few percent accuracy, we determine the location of the critical point and the liquid-vapor coexistence line for symmetric nuclear matter with equal numbers of protons and neutrons. We also present the first ab initio study of the density and temperature dependence of nuclear clustering.
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Nuclear clustering describes the appearance of structures resembling smaller nuclei such as alpha particles (^{4}He nuclei) within the interior of a larger nucleus. In this Letter, we present lattice Monte Carlo calculations based on chiral effective field theory for the ground states of helium, beryllium, carbon, and oxygen isotopes. By computing model-independent measures that probe three- and four-nucleon correlations at short distances, we determine the shape of the alpha clusters and the entanglement of nucleons comprising each alpha cluster with the outside medium. We also introduce a new computational approach called the pinhole algorithm, which solves a long-standing deficiency of auxiliary-field Monte Carlo simulations in computing density correlations relative to the center of mass. We use the pinhole algorithm to determine the proton and neutron density distributions and the geometry of cluster correlations in ^{12}C, ^{14}C, and ^{16}C. The structural similarities among the carbon isotopes suggest that ^{14}C and ^{16}C have excitations analogous to the well-known Hoyle state resonance in ^{12}C.
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How do protons and neutrons bind to form nuclei? This is the central question of ab initio nuclear structure theory. While the answer may seem as simple as the fact that nuclear forces are attractive, the full story is more complex and interesting. In this work we present numerical evidence from ab initio lattice simulations showing that nature is near a quantum phase transition, a zero-temperature transition driven by quantum fluctuations. Using lattice effective field theory, we perform Monte Carlo simulations for systems with up to twenty nucleons. For even and equal numbers of protons and neutrons, we discover a first-order transition at zero temperature from a Bose-condensed gas of alpha particles (^{4}He nuclei) to a nuclear liquid. Whether one has an alpha-particle gas or nuclear liquid is determined by the strength of the alpha-alpha interactions, and we show that the alpha-alpha interactions depend on the strength and locality of the nucleon-nucleon interactions. This insight should be useful in improving calculations of nuclear structure and important astrophysical reactions involving alpha capture on nuclei. Our findings also provide a tool to probe the structure of alpha cluster states such as the Hoyle state responsible for the production of carbon in red giant stars and point to a connection between nuclear states and the universal physics of bosons at large scattering length.
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BACKGROUND: Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP. METHODS: RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors. RESULTS: In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP. CONCLUSIONS: We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.
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Carcinoma de Células Renales , Neoplasias Renales , Células Madre Neoplásicas , Humanos , Pronóstico , Neoplasias Renales/genética , Neoplasias Renales/patología , Carcinoma de Células Renales/genética , Carcinoma de Células Renales/patología , Células Madre Neoplásicas/metabolismo , Células Madre Neoplásicas/patología , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Masculino , Biomarcadores de Tumor/genética , Femenino , Perfilación de la Expresión Génica , Persona de Mediana Edad , Transducción de Señal/genéticaRESUMEN
Background: Prostate cancer (PCa) is one of the most threatening health problems for the elderly males. However, our understanding of the disease has been limited by the research technology for a long time. Recently, the maturity of sequencing technology and omics studies has been accelerating the studies of PCa, establishing themselves as an essential impetus in this field. Methods: We assessed Web of Science (WoS) database for publications of sequencing and omics studies in PCa on July 3rd, 2023. Bibliometrix was used to conduct ulterior bibliometric analysis of countries/affiliations, authors, sources, publications, and keywords. Subsequently, purposeful large amounts of literature reading were proceeded to analyze research hotspots in this field. Results: 3325 publications were included in the study. Research associated with sequencing and omics studies in PCa had shown an obvious increase recently. The USA and China were the most productive countries, and harbored close collaboration. CHINNAIYAN AM was identified as the most influential author, and CANCER RESEARCH exhibited huge impact in this field. Highly cited publications and their co-citation relationships were used to filtrate literatures for subsequent literature reading. Based on keyword analysis and large amounts of literature reading, 'the molecular pathogenesis of PCa' and 'the clinical application of sequencing and omics studies in PCa' were summarized as two research hotspots in the field. Conclusion: Sequencing technology had a deep impact on the studies of PCa. Sequencing and omics studies in PCa helped researchers reveal the molecular pathogenesis, and provided new possibilities for the clinical practice of PCa.
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BACKGROUND: Malignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO. METHOD: Three databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation. RESULT: A total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation. CONCLUSION: Fibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.
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BACKGROUND: Burn injuries with ≥70% total body surface area (TBSA) are especially acute and life-threatening, leading to severe complications and terrible prognosis, while a powerful model for prediction of overall survival (OS) is lacked. The objective of this study is to identify prognostic factors for the OS of patients with burn injury ≥70% TBSA, construct and validate a feasible predictive model. MATERIALS AND METHODS: Patients diagnosed with burns ≥70% TBSA admitted and treated between 2010 and 2020 in our hospital were included. A cohort of the patients from the Kunshan explosion were assigned as the validation set. The Chi-square test and K-M survival analysis were conducted to identify potential predictors for OS. Then, multi-variate Cox regression analysis was performed to identify the independent factors. Afterwards, we constructed a nomogram to predict OS probability. Finally, the Kunshan cohort was applied as an external validation set. RESULTS: Gender, the percentage of third- and fourth-degree burn as well as organ dysfunction were identified as significant independent factors. A nomogram only based on the factors of the individuals was built and evidenced to have promising predictive accuracy, accordance, and discrimination by both internal and external validation. CONCLUSIONS: This study recognized significant influencing factors for the OS of patients with burns ≥70% TBSA. Furthermore, our nomogram proved to be an effective tool for doctors to quickly evaluate patients' outcomes and make appropriate clinical decisions at an early stage of treatment.
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Background: Study engagement is regarded important to medical students' physical and mental wellbeing. However, the relationship between learning environment of medical schools and the study engagement of medical students was still unclear. This study was aimed to ascertain the positive effect of learning environment in study engagement. Methods: We collected 10,901 valid questionnaires from 12 medical universities in China, and UWES-S was utilized to assess the study engagement levels. Then Pearson Chi-Square test and Welch's ANOVA test were conducted to find the relationship between study engagement and learning environment, and subgroup analysis was used to eradicate possible influence of confounding factors. After that, a multivariate analysis was performed to prove learning environment was an independent factor, and we constructed a nomogram as a predictive model. Results: With Pearson Chi-Square test (p < 0.001) and Welch's ANOVA test (p < 0.001), it proved that a good learning environment contributed to a higher mean of UWES scores. Subgroup analysis also showed statistical significance (p < 0.001). In the multivariate analysis, we could find that, taking "Good" as reference, "Excellent" (OR = 0.329, 95%CI = 0.295-0.366, p < 0.001) learning environment was conducive to one's study engagement, while "Common" (OR = 2.206, 95%CI = 1.989-2.446, p < 0.001), "Bad" (OR = 2.349, 95%CI = 1.597-3.454, p < 0.001), and "Terrible" (OR = 1.696, 95%CI = 1.015-2.834, p = 0.044) learning environment only resulted into relatively bad study engagement. Depending on the result, a nomogram was drawn, which had predictive discrimination and accuracy (AUC = 0.680). Conclusion: We concluded that learning environment of school was an independent factor of medical student's study engagement. A higher level of learning environment of medical school came with a higher level of medical students' study engagement. The nomogram could serve as a predictive reference for the educators and researchers.
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The carbon atom provides the backbone for the complex organic chemistry composing the building blocks of life. The physics of the carbon nucleus in its predominant isotope, 12C, is similarly full of multifaceted complexity. Here we provide a model-independent density map of the geometry of the nuclear states of 12C using the ab initio framework of nuclear lattice effective field theory. We find that the well-known but enigmatic Hoyle state is composed of a "bent-arm" or obtuse triangular arrangement of alpha clusters. We identify all of the low-lying nuclear states of 12C as having an intrinsic shape composed of three alpha clusters forming either an equilateral triangle or an obtuse triangle. The states with the equilateral triangle formation also have a dual description in terms of particle-hole excitations in the mean-field picture.
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Background: Rheumatoid Diseases (RDs) are a group of systemic auto-immune diseases that are characterized by chronic synovitis, and fibroblast-like synoviocytes (FLSs) play an important role in the occurrence and progression of synovitis. Our study is the first to adopt bibliometric analysis to identify the global scientific production and visualize its current distribution in the 21st century, providing insights for future research through the analysis of themes and keywords. Methods: We obtained scientific publications from the core collection of the Web of Science (WoS) database, and the bibliometric analysis and visualization were conducted by Biblioshiny software based on R-bibliometrix. Results: From 2000 to 2022, a total of 3,391 publications were reviewed. China is the most prolific country (n = 2601), and the USA is the most cited country (cited 7225 times). The Center of Experimental Rheumatology at University Hospital Zürich supported the maximum number of articles (n = 40). Steffen Gay published 85 records with 6263 total citations, perhaps making him the most impactful researcher. Arthritis and Rheumatism, Annals of Rheumatic Diseases, and Rheumatology are the top three journals. Conclusion: The current study revealed that rheumatoid disease (RD)-related fibroblast studies are growing. Based on the bibliometric analysis, we summarized three important topics: activation of different subsets of fibroblasts; regulation of fibroblast function; and in vitro validation of existing discoveries. They are all valuable directions, which provide reference and guidance for researchers and clinicians engaged in the research of RDs and fibroblasts.
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Artritis Reumatoide , Enfermedades Reumáticas , Sinovitis , Humanos , Masculino , Bibliometría , FibroblastosRESUMEN
Background: Rheumatism covers a wide range of diseases with complex clinical manifestations and places a tremendous burden on humans. For many years, our understanding of rheumatism was seriously hindered by technology constraints. However, the increasing application and rapid advancement of sequencing technology in the past decades have enabled us to study rheumatism with greater accuracy and in more depth. Sequencing technology has made huge contributions to the field and is now an indispensable component and powerful tool in the study of rheumatism. Methods: Articles on sequencing and rheumatism, published from 1 January 2000 to 25 April 2022, were retrieved from the Web of Science™ (Clarivate™, Philadelphia, PA, USA) database. Bibliometrix, the open-source tool, was used for the analysis of publication years, countries, authors, sources, citations, keywords, and co-words. Results: The 1,374 articles retrieved came from 62 countries and 350 institutions, with a general increase in article numbers during the last 22 years. The leading countries in terms of publication numbers and active cooperation with other countries were the USA and China. The most prolific authors and most popular documents were identified to establish the historiography of the field. Popular and emerging research topics were assessed by keywords and co-occurrence analysis. Immunological and pathological process in rheumatism, classification, risks and susceptibility, and biomarkers for diagnosis were among the hottest themes for research. Conclusions: Sequencing technology has been widely applied in the study of rheumatism and propells research in the area of discovering novel biomarkers, related gene patterns and physiopathology. We suggest that further efforts be made to advance the study of genetic patterns related to rheumatic susceptibility, pathogenesis, classification and disease activity, and novel biomarkers.
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Enfermedades Reumáticas , Humanos , Bibliometría , China , Bases de Datos Factuales , TecnologíaRESUMEN
The pseudospin symmetry (PSS) is a relativistic dynamical symmetry connected with the small component of the Dirac spinor. The origin of PSS in single particle bound states in atomic nuclei has been revealed and studied extensively. By examining the zeros of Jost functions corresponding to the small components of Dirac wave functions and phase shifts of continuum states, we show that the PSS in single particle resonant states in nuclei is conserved when the attractive scalar and repulsive vector potentials have the same magnitude but opposite sign. The exact conservation and the breaking of the PSS are illustrated for single particle resonances in spherical square-well and Woods-Saxon potentials.
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Background: Rheumatic diseases (RD) are a group of multi-system inflammatory autoimmune diseases whose causes are still under study. In the past few decades, researchers have found traces of the association between rheumatic diseases and intestinal microbiota, which can partially explain the pathogenesis of rheumatic diseases. We aimed to describe the research trend and main divisions on how gut flora interreacts with rheumatic diseases, and discussed about the possible clinical applications. Methods: We analyzed bibliometric data from the Web of Science core collection (dated 15th May 2022). Biblioshiny R language software packages (bibliometrix) were used to obtain the annual publication and citations, core sources according to Bradford's law, and country collaboration map. We designed and verified the keyword co-occurrence network and strategic diagram with the help of VOSviewer and CiteSpace, subdivided the research topic into several themes and identified research dimensions. The tables of most local cited documents and core sources were processed manually. Furthermore, the Altmetric Attention Score and the annual Altmetric Top 100 were applied to analyze the annual publication and citation. Results: From a total of 541 documents, we found that the overall trend of annual publication and citation is increasing. The major research method is to compare the intestinal microbial composition of patients with certain rheumatic disease and that of the control group to determine microbial alterations related to the disease's occurrence and development. According to Bradford's law, the core sources are Arthritis and Rheumatology, Annals of the Rheumatic Diseases, Current Opinion in Rheumatology, Nutrients, Rheumatology, and Journal of Rheumatology. Since 1976, 101 countries or regions have participated in studies of rheumatology and intestinal microbes. The United States ranks at the top and has the broadest academic association with other countries. Five themes were identified, including the pivotal role of inflammation caused by intestinal bacteria in the rheumatic pathogenesis, the close relationship between rheumatic diseases and inflammatory bowel disease, immunoregulation mechanism as a mediator of the interaction between rheumatic diseases and gut flora, dysbiosis and decreased diversity in intestine of patients with rheumatic diseases, and the influence of oral flora on rheumatic diseases. Additionally, four research dimensions were identified, including pathology, treatment, disease, and experiments. Conclusion: Studies on rheumatic diseases and the intestinal microbiota are growing. Attention should be paid to the mechanism of their interaction, such as the microbe-immune-RD crosstalk. Hopefully, the research achievements can be applied to diseases' prevention, diagnosis, and treatment, and our work can contribute to the readers' future research.
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The operational performance of a full-scale subsurface-flow constructed wetland, which treated the mixed industrial and domestic wastewater with BOD5/COD mean ratio of 0.33 at Shatian, Shenzhen City was studied. The constructed wetland system consists of screens, sump, pumping station, and primary settling basin, facultative pond, first stage wetland and secondary stage wetland. The designed treatment capacity is 5000 m3/d, and the actual influent flow is in the range of < 2000 to > 10000 m3/d. Under normal operational conditions, the final effluent quality well met the National Integrated Wastewater Discharge Standard (GB 8978-1996), with the following parameters(mean values): COD 33.90 mg/L, BOD, 7.65 mg/L, TSS 7.92 mg/L, TN 9.11 mg/L and TP 0.56 mg/L. Seven species of plants were selected to grow in the wetland: Reed, Sweetcane flower Silvergrass, Great Bulrush, Powdery Thalia and Canna of three colours. The growing season is a whole year-round. The seasonal discrepancy could be observed and the plants growing in the wetland are vulnerable to lower temperature in winter. The recycling of the effluent in the first stage of the wetland system is an effective measure to improve the performance of the wetland system. The insufficient DO value in the wetland system not only had significant effect on pollutants removal in the wetland, but also was unfavourable to plant growth. The recycling of effluent to the inlet of wetland system and artificial pond to increase DO value of influent to the wetland is key to operate the subsurface constructed wetland steadily and effectively.