Biology of tongue coating in different disease stages of RA and its value in disease progression.

OBJECTIVE: To assess and compare the composition of tongue coating microbiota among patients at different stages of rheumatoid arthritis (RA). METHODS: A total of 47 patients diagnosed with RA, as per the American College of Rheumatology criteria, and 10 healthy individuals were enrolled in this study. The RA patients were stratified considering their Disease Activity Score 28 (DAS28), a composite measure based on the 28 tender and swollen joint count and erythrocyte sedimentation rate (ESR). The study population was further categorized into active phase group (LMH group) and inactive phase group (RE group) according to their DAS28 values. DNA extraction was extracted from tongue coating samples. Subsequently, the V3-V4 16S rDNA region was selectively amplified and sequenced through high-throughput 16S rDNA analysis. The resulting data were then utilized to ascertain the microbial contents. RESULTS: Significant variations were observed in the tongue coating microbiota of patients with RA during active and inactive phases, in comparison to healthy individuals (p < 0.05). At the genus level, the presence of Prevotellan, Veillonella, Rothia, and Neisseria in RA patients was notably more evident than in the healthy control (HC) group. These disparities find support in existing research on gut and oral microbiota. During the active phase of RA, the relative abundance of Veillonella, Rothia, and Neisseria in the tongue coating microbiota of patients was significantly higher than in those with inactive RA. These findings underscore the need for further and in-depth research on the potential impact of these microorganisms on the progression of RA disease. CONCLUSION: The results substantiate the hypothesis that tongue coating microbes actively contribute to the progression of RA.

Research on the spatial patterns and evolution trends of the coupling coordination between digital finance and sustainable economic development in the Yellow River Basin, China.

In the current global context, digital finance (DF) and sustainable economic development (SED) are important topics. The synergies between DF and SED have already been proven. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of DF and SED have not received sufficient attention to date. Based on data from 55 cities in the Yellow River Basin (YRB) from 2011 to 2021, this study constructs an evaluation index system of DF and SED and measures their level, respectively. The proposed CCD model is then used to measure the CCD between the two systems. In addition, kernel density estimation, Markov chain, σ-convergence, ß-convergence, and the quadratic assignment procedure (QAP) method are used to study the spatial pattern, distribution dynamic evolution trend, convergence, and influencing factors of the regional differences in the CCD. The results show that: (1) From 2011 to 2021, the CCD level showed a stable upward trend and regional heterogeneity, and the time stage characteristics were more obvious. (2) The center position and change interval of the overall distribution curve of the kernel density estimation gradually shifted to the right. The Markov transfer probability matrix shows that the CCD is more stable among different levels, indicating a phenomenon of "club convergence". (3) A convergence analysis shows that there are significant σ-convergence, absolute ß-convergence, and conditional ß-convergence. (4) The QAP regression shows that factors such as the regional differences in GDP per capita have a significant impact on the regional differences in the CCD. This study offers a comprehensive structure that can be used to examine the synergistic effects between DF and SED; the research findings can also provide perspectives for other areas.

Learning Spatiotemporal Manifold Representation for Probabilistic Land Deformation Prediction.

Landslides refer to occurrences of massive ground movements due to geological (and meteorological) factors, and can have disastrous impacts on property, economy, and even lead to the loss of life. The advances in remote sensing provide accurate and continuous terrain monitoring, enabling the study and analysis of land deformation which, in turn, can be used for land deformation prediction. Prior studies either rely on predefined factors and patterns or model static land observations without considering the subtle interactions between different point locations and the dynamic changes of the surface conditions, causing the prediction model to be less generalized and unable to capture the temporal deformation characteristics. To address these issues, we present DyLand, a dynamic manifold learning framework that models the dynamic structures of the terrain surface. We contribute to the land deformation prediction literature in four directions. First, DyLand learns the spatial connections of interferometric synthetic aperture radar (InSAR) measurements and estimates the conditional distributions on a dynamic terrain manifold with a novel normalizing flow-based method. Second, instead of modeling the stable terrains, we incorporate surface permutations and capture the innate dynamics of the land surface while allowing for tractable likelihood estimations on the manifold. Third, we formulate the spatiotemporal learning of land deformations as a dynamic system and unify the learning of spatial embeddings and surface deformation. Finally, extensive experiments on curated real-world InSAR datasets (land slopes prone to landslides) show that DyLand outperforms existing benchmark models.

Blinding assessment in clinical trials of traditional Chinese medicine: Exploratory principles and protocol.

As one of the key components of clinical trials, blinding, if successfully implemented, can help to mitigate the risks of implementation bias and measurement bias, consequently improving the validity and reliability of the trial results. However, successful blinding in clinical trials of traditional Chinese medicine (TCM) is hard to achieve, and the evaluation of blinding success through blinding assessment lacks established guidelines. Taking into account the challenges associated with blinding in the TCM field, here we present a framework for assessing blinding. Further, this study proposes a blinding assessment protocol for TCM clinical trials, building upon the framework and the existing methods. An assessment report checklist and an approach for evaluating the assessment results are presented based on the proposed protocol. It is anticipated that these improvements to blinding assessment will generate greater awareness among researchers, facilitate the standardization of blinding, and augment the blinding effectiveness. The use of this blinding assessment may further advance the quality and precision of TCM clinical trials and improve the accuracy of the trial results. The blinding assessment protocol will undergo continued optimization and refinement, drawing upon expert consensus and experience derived from clinical trials. Please cite this article as: Wang XC, Liu XY, Shi KL, Meng QG, Yu YF, Wang SY, Wang J, Qu C, Lei C, Yu XP. Blinding assessment in clinical trials of traditional Chinese medicine: Exploratory principles and protocol. J Integr Med. 2023; 21(6): 528-536.

A novel evolutionary method for parameter-free MEMS structural design and its application in piezoresistive pressure sensors.

In this paper, a novel simulation-based evolutionary method is presented for designing parameter-free MEMS structures with maximum degrees of freedom. This novel design method enabled semiautomatic structure evolution by weighing the attributes of each segment of the structure and yielded an optimal design after multiple iterations. The proposed method was utilized to optimize the pressure-sensitive diaphragm of a piezoresistive pressure sensor (PPS). Finite element method (FEM) simulations revealed that, in comparison to conventional diaphragms without islands and with square islands, the optimized diaphragm increased the stress by 10% and 16% and reduced the nonlinearity by 57% and 77%, respectively. These improvements demonstrate the value of this method. Characterization of the fabricated PPS revealed a high sensitivity of 8.8 mV V-1 MPa-1 and a low nonlinearity of 0.058% FS at 20 °C, indicating excellent sensor performance.

The association between retina thinning and hippocampal atrophy in Alzheimer's disease and mild cognitive impairment: a meta-analysis and systematic review.

Introduction: The retina is the "window" of the central nervous system. Previous studies discovered that retinal thickness degenerates through the pathological process of the Alzheimer's disease (AD) continuum. Hippocampal atrophy is one of the typical clinical features and diagnostic criteria of AD. Former studies have described retinal thinning in normal aging subjects and AD patients, yet the association between retinal thickness and hippocampal atrophy in AD is unclear. The optical coherence tomography (OCT) technique has access the non-invasive to retinal images and magnetic resonance imaging can outline the volume of the hippocampus. Thus, we aim to quantify the correlation between these two parameters to identify whether the retina can be a new biomarker for early AD detection. Methods: We systematically searched the PubMed, Embase, and Web of Science databases from inception to May 2023 for studies investigating the correlation between retinal thickness and hippocampal volume. The Newcastle-Ottawa Quality Assessment Scale (NOS) was used to assess the study quality. Pooled correlation coefficient r values were combined after Fisher's Z transformation. Moderator effects were detected through subgroup analysis and the meta-regression method. Results: Of the 1,596 citations initially identified, we excluded 1,062 studies after screening the titles and abstract (animal models, n = 99; irrelevant literature, n = 963). Twelve studies met the inclusion criteria, among which three studies were excluded due to unextractable data. Nine studies were eligible for this meta-analysis. A positive moderate correlation between the retinal thickness was discovered in all participants of with AD, mild cognitive impairment (MCI), and normal controls (NC) (r = 0.3469, 95% CI: 0.2490-0.4377, I2 = 5.0%), which was significantly higher than that of the AD group (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%) (p < 0.05). Among different layers, the peripapillary retinal nerve fiber layer (pRNFL) indicated a moderate positive correlation with hippocampal volume (r = 0.1209, 95% CI:0.0905-0.1510, I2 = 0.0%). The retinal pigmented epithelium (RPE) was also positively correlated [r = 0.1421, 95% CI:(-0.0447-0.3192), I2 = 84.1%]. The retinal layers and participants were the main overall heterogeneity sources. Correlation in the bilateral hemisphere did not show a significant difference. Conclusion: The correlation between RNFL thickness and hippocampal volume is more predominant in both NC and AD groups than other layers. Whole retinal thickness is positively correlated to hippocampal volume not only in AD continuum, especially in MCI, but also in NC. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, CRD42022328088.

Pregnancy-Specific Glycoprotein 9 Enhances Store-Operated Calcium Entry and Nitric Oxide Release in Human Umbilical Vein Endothelial Cells.

We explored changes in pregnancy-specific glycoprotein 9 (PSG9) levels in the serum of patients with preeclampsia and the effects and underlying mechanisms of PSG9 effects on calcium (Ca2+) homeostasis and nitric oxide (NO) release in human umbilical vein endothelial cells (HUVECs). Western blotting was used to detect protein expression levels, and an NO fluorescence probe was used to examine NO production. Intracellular Ca2+ concentrations were measured using a Ca2+-sensitive fluorescent dye under a fluorescence microscope. Compared with those in healthy pregnant women, serum PSG9 levels were significantly decreased in patients with preeclampsia. PSG9 (0.1 µg/mL) treatment of HUVECs significantly enhanced the expression levels of store-operated calcium entry (SOCE) channel proteins Orai1 and Orai2, but not Orai3, and of endothelial nitric oxide synthase (eNOS) and NO production. Pretreatment with an inhibitor of SOCE (BTP2) abolished PSG9-enhanced Orai1, Orai2, and eNOS expression levels and NO production in HUVECs. The mechanisms underlying SOCE that were PSG9 enhanced in HUVECs appear to involve the Ca2+/eNOS/NO signaling pathway. These findings suggest that serum PSG9 levels may be a potential biomarker for monitoring the occurrence or development of preeclampsia in pregnancy and that PSG9 may be a potential therapeutic target for the treatment of preeclampsia.

Synchronization of Generally Uncertain Markovian Inertial Neural Networks With Random Connection Weight Strengths and Image Encryption Application.

This article focuses on the synchronization problem of delayed inertial neural networks (INNs) with generally uncertain Markovian jumping and their applications in image encryption. The random connection weight strengths and generally uncertain Markovian are discussed in the INNs model. Compared with most existing INNs models that have constant connection weight strengths, our model is more practical because connection weight strengths of INNs may randomly vary due to the external and internal environment and human factor. The delay-range-dependent synchronization conditions (DRDSCs) could be obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII). In addition, the desired controllers are obtained by solving a set of linear matrix inequalities. Finally, two examples are shown to demonstrate the effectiveness of the proposed results.

Dissipativity-Based Consensus Tracking Control of Nonlinear Multiagent Systems With Generally Uncertain Markovian Switching Topologies and Event-Triggered Strategy.

This article focuses on the dissipativity-based consensus tracking control (DBCTC) problems of time-varying delayed leader-following nonlinear multiagent systems (LFNMASs) with the event-triggered transmission strategy. The switching topologies of the LFNMASs are subject to the uncertain and partially unknown generally Markovian jumping process. The control inputs of the following agents are updated according to the proposed event-triggered transmission strategy, which could reduce the communication burden. Based on the event-triggered transmission condition and distributed consensus protocol, some dissipativity-based criteria obtained by adopting the delay-product-term Lyapunov-Krasovskii functional (DPTLKF) and higher order polynomial-based relaxed inequality (HOPRII) are proposed to guarantee the LFNMAS consensus. The validity of the main results is verified by two simulation examples.

Development and characterization of type I interferon receptor knockout sheep: A model for viral immunology and reproductive signaling.

Type I interferons (IFNs) initiate immune responses to viral infections. Their effects are mediated by the type I IFN receptor, IFNAR, comprised of two subunits: IFNAR1 and IFNAR2. One or both chains of the sheep IFNAR were disrupted in fetal fibroblast lines using CRISPR/Cas9 and 12 lambs were produced by somatic cell nuclear transfer (SCNT). Quantitative reverse transcription-polymerase chain reaction for IFN-stimulated gene expression showed that IFNAR deficient sheep fail to respond to IFN-alpha. Furthermore, fibroblast cells from an IFNAR2 -/- fetus supported significantly higher levels of Zika virus (ZIKV) replication than wild-type fetal fibroblast cells. Although many lambs have died from SCNT related problems or infections, one fertile IFNAR2 -/- ram lived to over 4 years of age, remained healthy, and produced more than 80 offspring. Interestingly, ZIKV infection studies failed to demonstrate a high level of susceptibility. Presumably, these sheep compensated for a lack of type I IFN signaling using the type II, IFN-gamma and type III, IFN-lambda pathways. These sheep constitute a unique model for studying the pathogenesis of viral infection. Historical data supports the concept that ruminants utilize a novel type I IFN, IFN-tau, for pregnancy recognition. Consequently, IFNAR deficient ewes are likely to be infertile, making IFNAR knockout sheep a valuable model for studying pregnancy recognition. A breeding herd of 32 IFNAR2 +/- ewes, which are fertile, has been developed for production of IFNAR2 -/- sheep for both infection and reproduction studies.

Bibliometric Analysis of Network Pharmacology in Traditional Chinese Medicine.

Aim: We evaluated the developmental process, research status, and existing challenges of network pharmacology. Moreover, we elucidated the corresponding solutions to improve and develop network pharmacology. Methods: Research data for the current study were retrieved from the Web of Science. The developmental process of network pharmacology was analyzed using HisCite, whereas cooccurrence analysis of countries, institutions, keywords, and references in literature was conducted using CiteSpace. Results: In literature, there was a trend of annual increase of studies on network pharmacology and China was found to be the country with the most published literature on network pharmacology. The main publishing research institutions were universities of traditional Chinese medicine (TCM). The keywords with more research frequency were TCM, mechanisms, molecular docking, and quercetin, among others. Conclusion: Currently, studies on network pharmacology are mainly associated with the exploration of action mechanisms of TCM. The main active ingredient in many Chinese medicines is quercetin. This ingredient may lead to deviation of research results, inability to truly analyze active ingredients, and even mislead the research direction of TCM. Such deviation may be because the database fails to reflect the content and composition changes of Chinese medicinal components. The database does not account for interactions among components, targets, and diseases, and it ignores the different pathological states of the disease. Therefore, network pharmacology should be improved from the databases and research methods.

[Priority ranking of Chinese patent medicine prescriptions for type 2 diabetes mellitus (syndrome of deficiency of both Qi and Yin): based on analytic hierarchy process (AHP)].

Clinical expertise, patient preference, and the best evidence are the three elements of evidence-based medicine. Based on high-level and high-quality evidence, qualitative and quantitative analysis of the prescribing decisions of physicians is beneficial to improving clinical efficacy. A mature methodological system is available for the retrieval, analysis, summary, evaluation, and recommendation of the evidence, but there are still few studies on physicians' prescribing decisions. How to analyze the trend of physicians' prescribing decisions based on the priority ranking in addition and subtraction of prescriptions? Analytic hierarchy process(AHP) is a method for decision making, which arranges the elements of the decision problem into overall goal, criteria, and operational sub-criteria, and uses the matrix eigenvector method to solve the problem. This study aims to analyze the priority of physicians' prescribing decisions for diabetes mellitus with deficiency of both Qi and Yin based on AHP. To be specific, a database of diabetes mellitus cases with deficiency of both Qi and Yin was established and AHP was used to yield the priority ranking of Chinese patent medicine prescriptions in specific clinical scenarios. In the selected cases of diabetes mellitus with deficiency of both Qi and Yin, Xiaoke Pills was the best prescription for the treatment of type 2 diabetes mellitus(deficiency of both Qi and Yin)(normalized=0.388), followed by Liuwei Dihuang Pills(normalized=0.269), Qishen Capsules(normalized=0.230), and Shengmai Injection(normalized=0.113). According to the analysis the available data, for type 2 diabetes mellitus(deficiency of both Qi and Yin), Xiaoke Pills was the most effective prescription in specific scenarios. When the physicians' prescribing decisions are consistent with the evidence, quantitative analysis of physicians' cognition will boost the evidence-based medical decision-making. However, the research results are also affected by the quality of literature, evidence level and priority, which are thus have some limitations. It is recommended that further small data research based on individual cases be carried out to lay a evidence-based basis for the clinical decision-making of type 2 diabetes mellitus.

No Reference Quality Assessment for Screen Content Images Using Stacked Autoencoders in Pictorial and Textual Regions.

Recently, the visual quality evaluation of screen content images (SCIs) has become an important and timely emerging research theme. This article presents an effective and novel blind quality evaluation metric for SCIs by using stacked autoencoders (SAE) based on pictorial and textual regions. Since the SCI consists of not only the pictorial area but also the textual area, the human visual system (HVS) is not equally sensitive to their different distortion types. First, the textual and pictorial regions can be obtained by dividing an input SCI via an SCI segmentation metric. Next, we extract quality-aware features from the textual region and pictorial region, respectively. Then, two different SAEs are trained via an unsupervised approach for quality-aware features that are extracted from these two regions. After the training procedure of the SAEs, the quality-aware features can evolve into more discriminative and meaningful features. Subsequently, the evolved features and their corresponding subjective scores are input into two regressors for training. Each regressor can obtain one output predictive score. Finally, the final perceptual quality score of a test SCI is computed by these two predicted scores via a weighted model. Experimental results on two public SCI-oriented databases have revealed that the proposed scheme can compare favorably with the existing blind image quality assessment metrics.

A Piezoresistive Pressure Sensor with Optimized Positions and Thickness of Piezoresistors.

In this paper, a piezoresistive pressure sensor based on silicon on insulator (SOI) was presented, which was composed of an SOI layer with sensing elements and a glass cap for a hermetic package. Different from its conventional counterparts, the position and thickness of the four piezoresistors was optimized based on numerical simulation, which suggests that two piezoresistors at the center while the other two at the edge of the pressure-sensitive diaphragm and a thickness of 2 µm can produce the maximum sensitivity and the minimum nonlinearity. Due to the use of silicon rather than metal for electrical connections, the piezoresistive pressure sensor was fabricated in a highly simplified process. From the experimental results, the fabricated piezoresistive pressure sensor demonstrated a high sensitivity of 37.79 mV·V-1·MPa-1, a high full-scale (FS) output of 472.33 mV, a low hysteresis of 0.09% FS, a good repeatability of 0.03% FS and a good accuracy of 0.06% FS at 20 °C. A temperature coefficient of sensitivity of 0.44 mV·MPa-1·°C-1 and a low zero drift were also shown at different temperatures. The piezoresistive pressure sensor developed in this study may function as an enabling tool in pressure measurements.

Comparing mRNA and sncRNA profiles during the maternal-to-embryonic transition in bovine IVF and scNT embryos†.

Production of embryos with high developmental competence by somatic cell nuclear transfer (scNT) is far less efficient than for in vitro fertilized (IVF) embryos, likely due to an accumulation of errors in genome reprogramming that results in aberrant expression of RNA transcripts, including messenger RNAs (mRNA) and, possibly, microRNAs (miRNA). Thus, our objectives were to use RNAseq to determine the dynamics of mRNA expression in early developing scNT and IVF embryos in the context of the maternal-to-embryonic transition (MET) and to correlate apparent transcriptional dysregulation in cloned embryos with miRNA expression profiles. Comparisons between scNT and IVF embryos indicated large scale transcriptome differences, which were most evident at the 8-cell and morula stages for genes associated with biological functions critical for the MET. For two miRNAs previously identified as differentially expressed in scNT morulae, miR-34a and miR-345, negative correlations with some predicted mRNA targets were apparent, though not widespread among the majority of predicted targets. Moreover, although large-scale aberrations in expression of mRNAs were evident during the MET in cattle scNT embryos, these changes were not consistently correlated with aberrations in miRNA expression at the same developmental stage, suggesting that other mechanisms controlling gene expression may be involved.

A metabolomic approach to elucidate the inhibitory effects of baicalin in pulmonary fibrosis.

CONTEXT: Baicalin, a major flavonoid extracted from Scutellaria baicalensis Georgi (Lamiaceae), has been shown to exert therapeutic effects on pulmonary fibrosis (PF). OBJECTIVE: To use serum metabolomics combined with biochemical and histopathological analyses to clarify anti-PF mechanisms of baicalin on metabolic pathways and the levels of potential biomarkers. MATERIALS AND METHODS: Forty male Sprague-Dawley rats were randomly divided into the control, PF model, prednisolone acetate-treated (4.2 mg/kg/day) and baicalin-treated (25 and 100 mg/kg/day) groups. A rat model of PF was established using a tracheal injection of bleomycin, and the respective drugs were administered intragastrically for 4 weeks. Histomorphology of lung tissue was examined after H&E and Masson's trichrome staining. Biochemical indicators including SOD, MDA and HYP were measured. Serum-metabonomic analysis based on UPLC-Q-TOF/MS was used to clarify the changes in potential biomarkers among different groups of PF rats. RESULTS: Both doses of baicalin effectively alleviated bleomycin-induced pathological changes, and increased the levels of SOD (from 69.48 to 99.50 and 112.30, respectively), reduced the levels of MDA (from 10.91 to 5.0 and 7.53, respectively) and HYP (from 0.63 to 0.41 and 0.49, respectively). Forty-eight potential biomarkers associated with PF were identified. Meanwhile, the metabolic profiles and fluctuating metabolite levels were normalized or partially reversed after baicalin treatment. Furthermore, baicalin was found to improve PF potentially by the regulation of four key biomarkers involving taurine and hypotaurine metabolism, glutathione metabolism, and glycerophospholipid metabolism. CONCLUSIONS: These findings revealed the anti-fibrotic mechanisms of baicalin and it may be considered as an effective therapy for PF.

Dynamics of small non-coding RNAs in bovine scNT embryos through the maternal-to-embryonic transition†.

The efficiency of somatic cell nuclear transfer (scNT) for production of viable offspring is relatively low as compared to in vitro fertilization (IVF), presumably due to deficiencies in epigenetic reprogramming of the donor cell genome. Such defects may also involve the population of small non-coding RNAs (sncRNAs), which are important during early embryonic development. The objective of this study was to examine dynamic changes in relative abundance of sncRNAs during the maternal-to-embryonic transition (MET) in bovine embryos produced by scNT as compared to IVF by using RNA sequencing. When comparing populations of miRNA in scNT versus IVF embryos, only miR-2340, miR-345, and miR34a were differentially expressed in morulae, though many more miRNAs were differentially expressed when comparing across developmental stages. Also of interest, distinct populations of piwi-interacting like RNAs (pilRNAs) were identified in bovine embryos prior to and during embryonic genome activation (EGA) as compared bovine embryos post-EGA and differentiated cells. Overall, sncRNA sequencing analysis of preimplantation embryos revealed largely similar profiles of sncRNAs for IVF and scNT embryos at the 2-cell, 8-cell, morula, and blastocyst stages of development. However, these sncRNA profiles, including miRNA, piRNA, and tRNA fragments, were notably distinct prior to and after completion of the MET.

Global Research Trends of Herbal Medicine for Pain in Three Decades (1990-2019): A Bibliometric Analysis.

PURPOSE: The aim of this study was to explore the global research trends of herbal medicine for pain from 1990 to 2019, using bibliometric methods, and explore international collaborations, intellectual structure, the evolution of active topics, emerging trends, and research frontiers. METHODS: Articles on herbal medicine for pain were retrieved from WoSCC. Two information visualization softwares including CiteSpace and HistCite were used to process bibliographic catalogs. Identification of international collaborations, intellectual structure, the evolution of active topics, emerging trends, and research frontiers were performed based on results from bibliometric analysis. RESULTS: A total of 2986 original articles published between 1990 and 2019 were identified based on the inclusion criteria. The number of publications on herbal medicine for pain in WoSCC significantly increased. China ranked highest in the number of scientific outputs; however, articles with the highest citation rates were found to be from the United States. China-Japan reported the most active collaborations, whereas Kyung Hee University from South Korea was the most productive institution. Zhang Y was the most productive author, whereas research by Sherman KJ and Vane JR had the highest influence. Journal of Ethnopharmacology was the most active journal, whereas Integrative and Complementary Medicine was the most active research area. History of herbal medicine for pain research comprises three major phases of activities. The main points of focus of bibliometric analysis of herbal medicine for pain include "knee osteoarthritis", "cancer", "low back pain", etc.. Moreover, research on mechanisms of action of herbal medicine for pain remains at the forefront of this field. CONCLUSION: This paper provides a basis for future development of research on herbal medicine for pain, which may help researchers explore new directions for future research and identify new perspectives on potential collaborations in this field.

Retracted: The Effects of Ludartin on Cell Proliferation, Cell Migration, Cell Cycle Arrest and Apoptosis Are Associated with Upregulation of p21WAF1 in Saos-2 Osteosarcoma Cells In Vitro.

The authors repeated experiments and found that the results shown in figure 2 were not reproducible. Reference: Shuang-li Zhang, Bao-lin Li, Wei Li, Ming Lu, Lin-ying Ni, Hui-li Ma, Qing-gang Meng. The Effects of Ludartin on Cell Proliferation, Cell Migration, Cell Cycle Arrest and Apoptosis Are Associated with Upregulation of p21WAF1 in Saos-2 Osteosarcoma Cells In Vitro. Med Sci Monit 2018; 24: LBR4926-4933. 10.12659/MSM.909193.