Modeling risk assessment of soil heavy metal pollution using partial least squares and fuzzy logic: A case study of a gully type coal-based solid waste dumpsite.

Continuous release and migration of heavy metals from coal-based solid waste (CSW) dumpsites often results in significant encroachment on ecological lands and pollution of natural environments. As a result, there is an urgent need for long-term and rapid monitoring, analysis, and assessment to control environmental risks associated with large CSW dumpsites. We constructed a new composite model (PLS-FL) that uses partial least squares regression (PLSR) and fuzzy logic inference (FLI) to accurately predict heavy metal concentrations in soils and assess pollution risk levels. The potential application of the PLS-FL was tested through a gully type CSW case study. We compared 20 modeling strategies using the PLS-FL: five types heavy metals (Cd, Zn, Pb, Cr and As) * four spectral transformation methods (first derivative (FD), second derivative (SD), reverse logarithm (RL), and continuum removal (CR)) * one variable selection method (competitive adaptive reweighted sampling (CARS)). The results showed that the combination of derivative transformation and CARS was recommended for estimation, with R2C > 0.80 and R2P > 0.50. When comparing the PLSR model with four traditional machine learning methods (Support Vector Machines (SVM), Random Forests (RF), Extreme Learning Machines (ELM), and KNN), the PLSR model demonstrated the highest average prediction accuracy. Additionally, the FLI process no longer relies on human perception and expert opinion, enhancing the model's objectivity and reliability. The evaluation results revealed that the heavy metal contamination areas of the CSW dumpsite are concentrated at the bottom of the gully, with more severe contamination in the north. Furthermore, a high-risk zone exists in the interim storage area for CSW to the east of the dump. These findings align with the initial detections at the sampling sites and highlight the need for targeted monitoring and control in these areas. The application of the model will empower regulators to quickly assess the overall situation of large-scale heavy metal pollution and provide scientific program and data support for continuous large-scale pollution risk monitoring and sustainable risk management.

Cost-effective production of alginate oligosaccharides from Laminaria japonica roots by Pseudoalteromonas agarivorans A3.

BACKGROUND: Alginate oligosaccharides (AOs) are the degradation products of alginate, a natural polysaccharide abundant in brown algae. AOs generated by enzymatic hydrolysis have diverse bioactivities and show broad application potentials. AOs production via enzymolysis is now generally with sodium alginate as the raw material, which is chemically extracted from brown algae. In contrast, AOs production by direct degradation of brown algae is more advantageous on account of its cost reduction and is more eco-friendly. However, there have been only a few attempts reported in AOs production from direct degradation of brown algae. RESULTS: In this study, an efficient Laminaria japonica-decomposing strain Pseudoalteromonas agarivorans A3 was screened. Based on the secretome and mass spectrum analyses, strain A3 showed the potential as a cell factory for AOs production by secreting alginate lyases to directly degrade L. japonica. By using the L. japonica roots, which are normally discarded in the food industry, as the raw material for both fermentation and enzymatic hydrolysis, AOs were produced by the fermentation broth supernatant of strain A3 after optimization of the alginate lyase production and hydrolysis parameters. The generated AOs mainly ranged from dimers to tetramers, among which trimers and tetramers were predominant. The degradation efficiency of the roots reached 54.58%, the AOs production was 33.11%, and the AOs purity was 85.03%. CONCLUSION: An efficient, cost-effective and green process for AOs production directly from the underutilized L. japonica roots by using strain A3 was set up, which differed from the reported processes in terms of the substrate and strain used for fermentation and the AOs composition. This study provides a promising platform for scalable production of AOs, which may have application potentials in industry and agriculture.

ChatGPT: promise and challenges for deployment in low- and middle-income countries.

In low- and middle-income countries (LMICs), the fields of medicine and public health grapple with numerous challenges that continue to hinder patients' access to healthcare services. ChatGPT, a publicly accessible chatbot, has emerged as a potential tool in aiding public health efforts in LMICs. This viewpoint details the potential benefits of employing ChatGPT in LMICs to improve medicine and public health encompassing a broad spectrum of domains ranging from health literacy, screening, triaging, remote healthcare support, mental health support, multilingual capabilities, healthcare communication and documentation, medical training and education, and support for healthcare professionals. Additionally, we also share potential concerns and limitations associated with the use of ChatGPT and provide a balanced discussion on the opportunities and challenges of using ChatGPT in LMICs.

Eye movement characteristics and visual fatigue assessment of virtual reality games with different interaction modes.

This study aimed to investigate the eye movement characteristics and visual fatigue of virtual reality games with different interaction modes. Eye movement data were recorded using the built-in eye tracker of the VR device and eye movement parameters were calculated from the recorded raw data. The Visual Fatigue Scales and Simulator Sickness Questionnaire were used to subjectively assess visual fatigue and overall discomfort of the VR experience. Sixteen male and 17 female students were recruited for this study. Results showed that both the primary and 360 mode of VR could cause visual fatigue after 30 min of gameplay, with significant differences observed in eye movement behavior between the two modes. The primary mode was more likely to cause visual fatigue, as shown by objective measurements of blinking and pupil diameter. Fixation and saccade parameters also showed significant differences between the two modes, possibly due to the different interaction modes employed in the 360 mode. Further research is required to examine the effects of different content and interactive modes of VR on visual fatigue, as well as to develop more objective measures for assessing it.

Analysis and Prediction of Corporate Finance and Exchange Rate Correlation Based on Machine Learning Algorithms.

Based on the risk management of exposure to foreign exchange assets and liabilities and the application of financial derivatives, this paper provides an in-depth analysis of the financial and exchange rate risks of foreign-funded enterprises. Therefore, a method of evaluating the financial performance of listed financial enterprises based on principal component analysis and neural network model is proposed. First, principal components of alternative financial performance input-output indicators are extracted using principal component analysis. Subsequently, these principal components are used as input-output data for the DEA model to derive the relative validity evaluation results of the financial performance of individual financial enterprises and to provide a reference for decision making to improve the financial performance level of financial enterprises. Combined with the economic business data of the enterprises, an empirical test on exchange rate risk management is conducted and relevant suggestions are made on how foreign enterprises can reduce exchange rate risk losses. It has important theoretical value and practical significance for enterprise finance and exchange rate management.

A Review of the Methods of Non-Invasive Assessment of Intracranial Pressure through Ocular Measurement.

The monitoring of intracranial pressure (ICP) is essential for the detection and treatment of most craniocerebral diseases. Invasive methods are the most accurate approach to measure ICP; however, these methods are prone to complications and have a limited range of applications. Therefore, non-invasive ICP measurement is preferable in a range of scenarios. The current non-invasive ICP measurement methods comprise fluid dynamics, and ophthalmic, otic, electrophysiological, and other methods. This article reviews eight methods of non-invasive estimation of ICP from ocular measurements, namely optic nerve sheath diameter, flash visual evoked potentials, two-depth transorbital Doppler ultrasonography, central retinal venous pressure, optical coherence tomography, pupillometry, intraocular pressure measurement, and retinal arteriole and venule diameter ratio. We evaluated and presented the indications and main advantages and disadvantages of these methods. Although these methods cannot completely replace invasive measurement, for some specific situations and patients, non-invasive measurement of ICP still has great potential.

Assessment of a cancer genomic profile test for patients with metastatic breast cancer.

Comprehensive cancer genomic profile (CGP) tests are being implemented under Japanese universal health insurance system. However, the clinical usefulness of CGP test for breast cancer patients has not been evaluated. Of the 310 patients who underwent CGP testing at our institution between November 2019 and April 2021, 35 patients with metastatic breast cancer whose treatment strategy was discussed by our molecular tumor board within the study period were investigated after exclusion of 2 cases that could not be analyzed. The turn-around time, drug accessibility, and germline identification detection were evaluated. The subtype was luminal in 20 patients (57.1%), triple-negative in 12 patients (34.3%), and luminal-HER2 in 3 patients (8.6%). Actionable gene mutations were detected in 30 patients (85.7%), and 7 patients (20.0%) were recommended for clinical trial participation, with the drug administered to 2 patients (5.7%). Three patients (8.6%) died due to disease progression before the test results were disclosed. We report the results of an initial assessment of the utility of CGP testing for patients with metastatic breast cancer under Japanese universal health insurance system. Conducting CGP tests at a more appropriate time could provide patients with greater benefit from treatments based on their specific gene mutations.

Assessment of Pazopanib-Related Heart Failure in Patients With Advanced Soft Tissue Sarcoma　- A Single Institute Analysis.

BACKGROUND: Heart failure (HF) is one of the potential adverse events of pazopanib treatment for soft tissue sarcoma (STS), but detailed reports of such HF cases are scarce. This study determined the incidence and risk factors of HF following pazopanib treatment for STS at our Institute and the clinical outcomes.Methods and Results:This study retrospectively analyzed the cases of STS patients treated with pazopanib (n=151) between 2012 and 2020. HF occurred in 6 patients (3.9%) at the median onset of 137 (range 14-468) days after the treatment initiation. When their HF was diagnosed, pazopanib was interrupted in all 6 patients. No patients experienced HF-related death, and HF development was not a significant factor for poor overall survival. The cumulative doses of anthracyclines (>225 mg/m2) before pazopanib initiation (83% vs. 37%, P=0.031), pazopanib initiation at age ≥60 years (83% vs. 35%, P=0.026), and the baseline B-type natriuretic peptide (BNP) concentration (≥50 pg/mL) before pazopanib (67% vs. 11%, P=0.002) initiation were predictive factors for post-pazopanib treatment HF. CONCLUSIONS: The study findings highlight the effect of past anthracycline exposure and baseline BNP for pazopanib-associated HF. Although the study patients' clinical outcomes were generally favorable, periodic monitoring of cardiac function using ultrasonic echocardiography or serum markers is essential to detect events early and begin therapeutic intervention appropriately under a cardiologist's instructions.

Genomic Landscape and Phenotypic Assessment of Cronobacter sakazakii Isolated From Raw Material, Environment, and Production Facilities in Powdered Infant Formula Factories in China.

Cronobacter is a foodborne pathogen associated with severe infections and high mortality in neonates. The bacterium may also cause gastroenteritis, septicemia, and urinary tract and wound infectious in adults. A total of 15 Cronobacter isolates collected from 617 raw materials and environment samples from Powdered Infant Formula manufacturing factories during 2016 in Shaanxi, China, were analyzed for antimicrobial susceptibilities, species identification, biofilm formation, and whole-genome sequencing. The results showed that all 15 isolates were Cronobacter sakazakii, while the antimicrobial susceptibility test showed that all 15 C. sakazakii were pan susceptible. Most isolates were able to produce a weak biofilm, and two isolates from soil samples produced a strong biofilm formation. All isolates were classified into seven STs including ST4, ST40, ST64, ST93, ST148, ST256, and ST494, with ST64 (4/15, 26.7%) being dominant, and most were clinically related. The isolates harbored at least 11 virulence genes and two plasmids, with one isolate being positive for all virulence genes. Phylogenetic and ANI analysis showed strong clustering by sequence types and isolates from different sources or regions with a similar genomic background. The fact that isolates were obtained from raw materials and environment samples of PIF facilities shared a close phylogeny with one another suggests that cross-contamination events may have occurred between the processing room and external environments, which may give rise to a recurring risk of a continuous contamination during production.

Comparison of the safety of outpatient cervical disc replacement with inpatient cervical disc replacement: A protocol for a meta-analysis.

BACKGROUND: Cervical disc replacement (CDR) has been widely used as an effective treatment for cervical degenerative disc diseases in recent years. However, the cost of this procedure is very high and may bring a great economic burden to patients and the health care system. It is reported that outpatient procedures can reduce nearly 30% of the costs associated with hospitalization compared with inpatient procedures. However, the safety profile surrounding outpatient CDR remains poorly resolved. This study aims to evaluate the current evidence on the safety of outpatient CDR METHODS:: Four English databases were searched. The inclusion and exclusion criteria were developed according to the PICOS principle. The titles and abstracts of the records will be screened by 2 authors independently. Records that meet the eligibility criteria will be screened for a second time by reading the full text. An extraction form will be established for data extraction. Risk of bias assessment will be performed by 2 authors independently using Cochrane risk of bias tool or Newcastle-Ottawa scale. Data synthesis will be conducted using Stata software. Heterogeneity among studies will be assessed using I test. The funnel plot, Egger regression test, and Begg rank correlation test will be used to examine the publication bias. RESULTS: The results of this meta-analysis will be published in a peer-review journal. CONCLUSION: This will be the first meta-analysis that compares the safety of outpatient CDR with inpatient CDR. Our study will help surgeons fully understand the complications and safety profile surrounding outpatient CDR. OSF REGISTRATION NUMBER:: doi.org/10.17605/OSF.IO/3597Z.

Source assessment of atmospheric fine particulate matter in a Chinese megacity: Insights from long-term, high-time resolution chemical composition measurements from Shanghai flagship monitoring supersite.

Here we present a long-term, hourly resolution dataset (from January 2014 to April 2015) of secondary inorganic aerosol (SIA) matter, organic matter (OM) and black carbon (BC) as PM2.5 chemical components in China. Seasonally differentiated weekly diurnal profiles of major particulate species were investigated in conjunction with potential source contribution function (PSCF) analysis. The average concentration of PM2.5 was 48.3 ± 35.1 µg m-3, in which OM was the major constituent (29.7 ± 13.9%), followed by sulfate (25.1 ± 8.1%), nitrate (18.5 ± 8.3%), ammonium (13.3 ± 3.8%), and other trace species (6.8 ± 4.0%). Interestingly, unlike other PM species, OM concentrations kept very similar level among different seasons, indicating on-road traffic is a stable source of PM2.5. Besides, a persistently strong particulate OM pollution belt was found along the lower reaches of Yangtze River. Significant enhancement of SIA (mainly nitrate) was coincided with high PM2.5 mass loading. Source apportionment were conducted and found the overwhelming dominance of long-range transport of the pollutants from north China. Using a case study, we further integrate Weather Research and Forecasting (WRF) meteorological modeling and lidar observation to better understand the evolution process of a typical pollution episode. Our assessment of the extremely large datasets derived from Shanghai supersite demonstrated the online instrumentation as a robust and credible alternative to filter-based sampling techniques for long-term PM2.5 monitoring and characterization in heavily polluted areas.

Safety and use of pulmonary function tests: a retrospective study from a single center over seven years' clinical practice.

BACKGROUND: To promote the utilization of pulmonary function tests (PFT) through analyzing the data of PFT during the past seven years in one large teaching hospital in China. METHODS: Through a retrospective analysis, the allocation of full-time staff in PFT room, the demographic characteristics of patients, cost-effectiveness of PFT, positive rate and failure rate of PFT, adverse events were analyzed. RESULTS: 1) From 2012 to 2018, the numbers of PFT showed the trend of escalation year by year. The proportion of patients receiving PFT rose from 29.0/10,000 in 2012 to 34.7/10,000 in 2018. The best allocation of PFT room was 20-25/ person / day. 2) The number of PFT provided by Department of Pulmonary and Critical Care Medicine (PCCM) accounted for 97.2, 97.1, 97.3, 97.8, 97.8, 98.0, and 98.2% of the total cases of outpatient PFT in the same year. The top three departments in the inpatient department were Department of Thoracic Surgery, Department of General Surgery, and Department of Urinary Surgery, the total cases of PFT in these three departments accounted for 65.1, 64.4, 62.1, 63.5, 62.4, 65.3 and 69.1% of the total cases of inpatient PFT in the same year. 3) Data from 2018 showed that the revenue from PFT was about 3.7 million Chinese Yuan, and that the salary of personnel and expenditure on machine maintenance and wear were about 800,000 Chinese Yuan. 4) 58.2% of the patients who had undergone PFT had ventilatory dysfunction. 5) The average failure rate of PFT in the past seven years was 1.91%. 6) The main adverse events of PFT examination were dizziness, amaurosis, limb numbness, lip numbness and falls. The incidence rates were 0.49, 0.42, 0.41, 0.39, 0.44, 0.48, and 0.45% respectively, with an average of 0.44%. CONCLUSIONS: The number of PFT showed an upward trend in the past seven years, and the optimal staffing of PFT room was 20-25 cases per person per day. The positive rate of pulmonary dysfunction was 58.2%. The failure rate of PFT and the incidence of adverse events were very low, suggesting it is a simple and safe clinical examination. It's worthy of further popularization and promotion.

Ultrasensitive Electrochemiluminescence Aptasensor for Assessment of Protein Heterogeneity in Small Cell Population.

Development of sensitive method for assay of proteins secreted from small cell population is important for the assessment of cellular heterogeneity. Here, we developed an ultrasensitive electrochemiluminescence (ECL) aptasensor for secreted protein in small cell population of RAW 264.7 cells for cellular heterogeneity assessment. Tumor necrosis factor-alpha (TNF-α) was chosen as target secreted protein, and specific anti-TNF-α aptamer was chosen as molecule recognition element, while dichlorotris (1,10-phenanthroline) ruthenium(II) hydrate (Ru(phen)32+) was chosen as ECL signal compound. An ECL signal probe was prepared by combining aptamer, Ru(phen)32+, and graphene oxide (GO) through electrostatic interaction and π-π stacking interaction. An aptasensor was fabricated by self-assembly specific aptamer on gold nanoparticles modified electrode for the detection of TNF-α using sandwich assay. High sensitivity and good selectivity were obtained for TNF-α. Parallel analysis was conducted to detect TNF-α secreted by RAW 264.7 cells stimulated by either lipopolysaccharides (LPS) or lupeol for assessing the cell heterogeneity in small cell population and for estimating the intracellular signal transduction in inflammation. Compared to ELISA, our ECL method offers both high sensitivity and good accuracy. The distinct heterogeneity among the secreted protein in small cell population, for the first time, was observed and further correlated to the cell's nature of cluster growth. The developed ECL method incorporating the amplification of nanomaterial and selectivity of aptamer is promising for sensitive and selective analysis of biomolecules in small cell population.

Auxiliary variable-enriched biomarker-stratified design.

Clinical trials in the era of precision medicine require assessment of biomarkers to identify appropriate subgroups of patients for targeted therapy. In a biomarker-stratified design (BSD), biomarkers are measured on all patients and used as stratification variables. However, such a trial can be both inefficient and costly, especially when the prevalence of the subgroup of primary interest is low and the cost of assessing the biomarkers is high. Efficiency can be improved and costs reduced by using enriched biomarker-stratified designs, in which patients of primary interest, typically the biomarker-positive patients, are oversampled. We consider a special type of enrichment design, an auxiliary variable-enriched design (AEBSD), in which enrichment is based on some inexpensive auxiliary variable that is positively correlated with the true biomarker. The proposed AEBSD reduces the total cost of the trial compared with a standard BSD when the prevalence rate of true biomarker positivity is small and the positive predictive value (PPV) of the auxiliary biomarker is larger than the prevalence rate. In addition, for an AEBSD, we can immediately randomize the patients selected in the screening process without waiting for the result of the true biomarker test, reducing the treatment waiting time. We propose an adaptive Bayesian method to adjust the assumed PPV while the trial is ongoing. Numerical studies and an example illustrate the approach. An R package is available.

Assessment on the Self-Discharge Behavior of Lithium-Sulfur Batteries with LiNO3-Possessing Electrolytes.

It is generally understood that the reduction of nitrate on the metallic Li surface aids in the formation of a solid-electrolyte interphase. LiNO3 is, therefore, frequently used as an electrolyte additive to help suppress the polysulfide redox shuttle in lithium-sulfur (Li-S) batteries. Although LiNO3 enables cycling of cells with considerably improved Coulombic efficiency and cyclic performance, the self-discharge behavior has largely been neglected. We present in this work a basic but systematic study to assess self-discharge of Li-S batteries with electrolytes possessing LiNO3. Comparative electrochemical tests and interfacial analysis reveal that the redox shuttle is fast enough to cause cells to self-discharge at a relatively rapid rate with limited concentration of the LiNO3 additive. Despite the capacity loss of a full-charged cell under rest for one day can be controlled to 2% with LiNO3 concentration as high as 0.5 M, the development of a practically viable Li-S technology looks like a daunting challenge. Further increasing LiNO3 would potentially cause more irreversible reduction of LiNO3 on the cathode during the first discharge. Therefore, a possible pathway for a long shelf life and low self-discharge is offered as well by the synergic protection of the separator and stabilization of the Li anode surface. The cell using a nanosized Al2O3-coated microporous membrane and a LiNO3-possessing electrolyte exhibits an extremely suppressed self-discharge, providing an alternative perspective for the practical use of Li-S batteries.

Cost-effective biodiesel production from wet microalgal biomass by a novel two-step enzymatic process.

In this study, a novel two-step enzymatic process was firstly established to produce microalgae biodiesel using wet Chlorella biomass. In the first hydrolysis step, to reduce energy consumption and effectively disrupt microalgal cell wall, among cellulase, hemicellulase, papain, lysozyme and pectinase, the highest hydrolysis efficiency (67.52%) was obtained by cellulase at pH 5.0 with enzyme dosage of 200 U/g dry biomass at 40 °C for 12 h. In the second transesterification step, compared with liquid CAL-A/B from Candida antarctica and PLA from Aspergillus oryzae, liquid lipase TL from Thermomyces lanuginosus achieved the highest biodiesel conversion at 81.15:1 (v/w) ethanol/g TFAs ratio in 78-83% water content with 100 PLU/g TFAs lipase loading at 25 °C for 48 h. Moreover, similar results were obtained with three Chlorella species by this process. Overall, this two-step enzymatic process was a green, low-energy and efficient method for cost-effective biodiesel production using wet microalgal biomass.

Assessment of the cytotoxic and mutagenic potential of the Jialu River and adjacent groundwater using human-hamster hybrid cells.

The Jialu River in China has been seriously polluted by the direct discharge of industrial and domestic wastewater. The predominant contaminants of the Jialu River and its adjacent groundwater were recently investigated. However, the potential genotoxic impact of polluted water on human health remains to be clarified. Here, we used human-hamster hybrid (AL) cells, which are sensitive for detecting environmental mutagens. We found that the cytotoxicity and mutagenicity of the groundwater in the Jialu River basin were influenced by the infiltration of the Jialu River. Hydrological periods significantly affected the cytotoxicity, but not the mutagenic potential, of surface and groundwater. Further, the mutagenic potential of groundwater samples located <1km from the Jialu River (SM-2 water samples) was detected earlier than that of groundwater samples located approximately 20km from the Jialu River (SN water samples). Because of high cytotoxicity, the mutagenic potential of water samples from the Jialu River (SM-1 water samples) was not significantly enhanced compared with that of untreated controls. To further assess the mutagenic dispersion potential, an artificial neural network model was adopted. The results showed that the highest mutagenic potential of groundwater was observed approximately 10km from the Jialu River. Although further investigation of mutagenic spatial dispersion is required, our data are significant for advancing our understanding of the origin, dispersion, and biological effects of water samples from polluted areas.

On Enrichment Strategies for Biomarker Stratified Clinical Trials.

In the era of precision medicine, drugs are increasingly developed to target subgroups of patients with certain biomarkers. In large all-comer trials using a biomarker stratified design, the cost of treating and following patients for clinical outcomes may be prohibitive. With a fixed number of randomized patients, the efficiency of testing certain treatments parameters, including the treatment effect among biomarker-positive patients and the interaction between treatment and biomarker, can be improved by increasing the proportion of biomarker positives on study, especially when the prevalence rate of biomarker positives is low in the underlying patient population. When the cost of assessing the true biomarker is prohibitive, one can further improve the study efficiency by oversampling biomarker positives with a cheaper auxiliary variable or a surrogate biomarker that correlates with the true biomarker. To improve efficiency and reduce cost, we can adopt an enrichment strategy for both scenarios by concentrating on testing and treating patient subgroups that contain more information about specific treatment parameters of primary interest to the investigators. In the first scenario, an enriched biomarker stratified design enriches the cohort of randomized patients by directly oversampling the relevant patients with the true biomarker, while in the second scenario, an auxiliary-variable-enriched biomarker stratified design enriches the randomized cohort based on an inexpensive auxiliary variable, thereby avoiding testing the true biomarker on all screened patients and reducing treatment waiting time. For both designs, we discuss how to choose the optimal enrichment proportion when testing a single hypothesis or two hypotheses simultaneously. At a requisite power, we compare the two new designs with the BSD design in terms of the number of randomized patients and the cost of trial under scenarios mimicking real biomarker stratified trials. The new designs are illustrated with hypothetical examples for designing biomarker-driven cancer trials.

Remission assessment of rheumatoid arthritis in daily practice in China: a cross-sectional observational study.

The objective of this study is to evaluate the remission rate and describe the current use of medication in a large cohort of rheumatoid arthritis (RA) patients under routine clinical care in China. RA patients were recruited from 40 large teaching hospitals nationwide in China. Data regarding RA disease activity, medication treatment, and adverse events were recorded using a standardized clinical data questionnaire. RA remission was evaluated by the 28 Joint Disease Activity Score DAS28-ESR Clinical Disease Activity Index (CDAI), Simplified Disease Activity Index (SDAI), and American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) remission criteria. A total of 1945 patients with RA were included in the study. The proportions of patients who fulfilled the DAS28-ESR, CDAI, SDAI, and ACR/EULAR remission criteria were 10.90%, 6.17%, 5.04% , and 1.75%, respectively. Most patients had taken at least one disease-modifying anti-rheumatic drug (DMARD), and the most common prescriptions included leflunomide (LEF) and methotrexate (MTX). DMARD combined with botanics were the most common and dominant strategy for RA management (29.16%). Overall, 433 patients (22.27%) had at least one adverse event. Gastrointestinal adverse events (41.27%) were the most frequently reported events. The incidence of side effects in patients using biologics DMARDs (bDMARDs) was significantly lower than that in those taking MTX, LEF, or sulfasalazine (SSZ). The remission rate of RA disease activity, as assessed in Chinese clinical practice, was very low. Adverse effects of the medicine occurred in approximately one in five RA patients, with bDMARDs were demonstrated to be the medication with the lowest side effects.