su rongsheng manufacturer

HONG KONG (Reuters) - Jiangsu Rongsheng Heavy Industries Co Ltd has appointed Morgan Stanleyand JP Morganto finalize plans for its long-awaited IPO in Hong Kong, aiming to raise up to $1.5 billion in the fourth quarter, sources told Reuters on Tuesday.

This is Rongsheng’s latest bid to go public after it failed to raise more than $2 billion from a planned IPO in Hong Kong in 2008, mainly as a result of the global financial crisis.

Rongsheng"s early main shareholders included an Asia investment arm of Goldman Sachs, U.S. hedge fund D.E. Shaw and New Horizon, a China fund founded by the son of Chinese Premier Wen Jiabao.

The three investors sold off their stakes in Rongsheng for a profit early this year, said the sources familiar with the situation. Representatives for the banks, funds and Rongsheng all declined to comment.

Rongsheng’s revived IPO plan comes at a challenging time. Smaller domestic rival, New Century Shipbuilding, slashed its Singapore IPO in half last week, planning to raise up to $560 million from the originally planned $1.24 billion due to weak market conditions.

Given uncertainty in the global shipbuilding business environment as well as growing concerns over a huge flow of fund-raising events in Hong Kong, investment bankers suggest the potential size for Rongsheng could be $1 billion to $1.5 billion, according to the sources.

Rongsheng is seeking to tap capital markets to fund fast growth and aims to catch up with bigger state-owned rivals such as Guangzhou Shipyard International Co Ltd.

Rongsheng won a $484 million deal to build four ships for Oman Shipping Co last year. The vessels would carry exports from an iron ore pellet plant in northern Oman which is expected to begin production in the second half of 2010.

HONG KONG, Nov 26 (Reuters) - China Rongsheng Heavy Industries Group, the country’s largest private shipbuilder, said its chairman had stepped down just three months after the company posted its sharpest fall in half-year net profit.

Listed in November 2010, Rongsheng was hit by an insider dealing scandal involving a firm owned by Zhang ahead of the $15.1 billion bid for Canadian oil firm Nexen Inc by China offshore oil and gas producer CNOOC.

Rongsheng said earlier this month that investment firm Well Advantage, controlled by Zhang, had agreed to pay $14 million as part of a settlement deal with the U.S. Securities and Exchange Commission (SEC).

In August, Rongsheng posted an 82 percent drop in half-year profit on a dearth of new orders and warned economic uncertainties would continue to weigh on the global shipping market.

As part of the changes at China Rongsheng, the company said that Zhang De Huang was retiring and had resigned as an executive director and as vice chairman of the board.

(31 March 2015, Hong Kong) - China Rongsheng Heavy Industries Group Holdings Limited ("China Rongsheng Heavy Industries", the "Company" or "We", and together with its subsidiaries, the "Group"; stock code: 01101.HK) announced its audited annual results for the twelve months ended 31 December 2014 (the "Period").

Launched a fresh start, China Rongsheng Heavy Industries implemented its strategy of business transformation in 2014 and completed the acquisition of oilfield project in Kyrgyzstan in September. We are proactively transforming into an oil and natural gas exploitation and production operator.

Meanwhile, we demonstrated the strong production capacity of our shipbuilding facilities and outstanding technical expertise of the Group. Our shipbuilding segment has delivered 11 vessels, with a total volume of 2,059,660 DWT, successfully in 2014. More proactively sorting and optimising our order book, we decisively reduced the number of vessels under construction and cancelled some shipbuilding orders. We believe this action not only was in alignment with the Group"s strategic plan to optimize the production and operation of its shipbuilding business during the Period, but also effectively reduced our burden on working capital and the credit risk of our order book, in spite of the fact that we have recorded a relatively larger amount of comprehensive net loss for the Period and a reversal of revenue of RMB4,530.7 solely resulted from the cancellation of shipbuilding contracts.

non-cash provisions and impairments, supporting us to strive for a strategic transformation towards energy sector and being well-equipped for future challenges.

In 2014, we sorted and optimised our order book by reducing the number of vessels under construction and cancelling some shipbuilding orders. We negotiated proactively with ship owners and reached agreement with them on certain orders on hand, resulting in the cancellation, revision and variation of a number of shipbuilding contracts. We believe that this action will reduce our burden on working capital and effectively reduce the credit risk of our order book. Thus, the shipbuilding segment of the Company recorded a negative revenue of RMB3,891.4 million which is mainly attribute to the reversal of revenue from cancellation of shipbuilding contracts for the Period.

As at 31 December 2014, our total orders on hand consisted of 35 vessels, representing a total volume of approximately 4,203,700 DWT with a total contract value of approximately USD1,668.4 million. They included 18 Panamax bulk carriers, 1 very large ore carrier, 1 Panamax crude oil tanker, 12 Suezmax crude oil tankers, 1 very large crude oil carrier, and 2 7,000-TEU containerships.

We utilised existing facilities and technical expertise to construct the No. 28 and No. 29 steel caisson projects of the Shanghai Yangtze River Bridge and successfully delivered them during the Period, demonstrating our ability in building non-vessel steel structures and securing new sources of revenue. The No. 29 steel caisson, weighing approximately 15,000 tons, is the largest steel caisson of its kind in the world.

On 11 September 2014, we completed the acquisition of 60% interest in the project (the "Kyrgyzstan Project") involving four oilfields located in the Fergana Valley of the Republic of Kyrgyzstan, which marked our breakthrough in the energy exploration and development sector. The Kyrgyzstan Project comprises of five oilfield zones namely, Maili-Su IV, Eastern Izbaskent, Izbaskent, Changyrtash and Chigirchik. The first three oilfield zones are located at the northeastern part of the Fergana Valley while the latter two are located at the Southeastern part of Fergana Valley. The total area covered by these five fields is approximately 545 square kilometres. The remaining recoverable reserves is estimated to be around 638 million barrels (MMbbl) of oil. Under the agreements entered into with the national oil company of Kyrgyzstan, Kbprb3>KepHeq:nera3 ("Kyrgyzjer Neftegaz" Limited Liability Company*), our indirect wholly-owned subsidiary was granted rights to cooperate with the national oil company of Kyrgyzstan in the operation of the five oilfields zones.

From 11 September 2014 to 31 December 2014, we have made satisfactory progress in the project. As at 31 December 2014, we had successfully completed drilling of 10 wells and had produced 16,260 barrels (bbl) of light crude oil, our daily production rate being about 252 bbl of light crude oil, even though only part of the oil wells were in operation. After initial drilling and production, we further understood and acknowledgedt the geological condition of the project. We will continue the process of perforating, testing and fracturing of the new wells to ramp up production. Since the project is still at the initial development stage, the sales of oil has not been reflected as revenue for the Period under relevant accounting treatment.

We have taken certain measures to mitigate the liquidity pressure and to improve financial position. In 2014, we completed issue of convertible bonds amounted to a total net proceeds of HKD3,985 million to strategic investors. In October, we has signed debt optimization framework agreements with a syndicate of domestic banks in Hefei of

Anhui Province. Plus, the debt optimization framework agreement we have entered into with a syndicate formed by more than ten banks in Jiangsu Province, including Bank of China, The Export-Import Bank of China and China Minsheng Bank, such measures effectively mitigated liquidity pressure of the Company.

Global economic recovery will remain a challenging course in 2015. Freight fees will remain at lower levels as any fundamental improvements to the situation of surplus capacity in the shipping market will be unlikely. It is well within expectations that the China"s shipbuilding industry will generally enter into a stage of structural realignment and rebuilding of strengths.

In September 2014, we obtained the rights to co-operate with the national oil company of Kyrgyzstan in respect of five oilfield zones in Kyrgyzstan by way of the allotment of shares as consideration. Central Asia is a region subject mainly to the influence of Russia, whose export oil prices have not plunged in tandem with international oil prices and have remained apart from the international price level. Local domestic oil prices of Kyrgyzstan have not changed significantly despite the dramatic decline in international oil prices. In view of the low costs and stable local oil prices, we are of the view that, under the current adverse market conditions of the shipbuilding industry, exposure to the energy sector will enable us to diversify our operations and broaden our source of revenue, as well as drive our active transformation from a manufacturer to a supplier in the energy service sector, thereby enhancing contributions to the overall interests of our shareholders.

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The chemical industry is central to modern China"s economy. It uses special methods to alter the structure, composition or synthesis of substances to produce new products, such as steel, plastic, and ethyl. Chemical industry provides building materials for China"s infrastructure, including subway, high-speed train, and highway.

Tu Youyou is a pharmaceutical chemist of China. She discovered qinghaosu (artemisinin) and applied to cure malaria. Qinghaosu saves millions of lives in South China, South America, Southeast Asia, and Africa. It is an important breakthrough in the medicine area last century, and Tu Youyou received the 2015 Nobel Prize in Physiology or Medicine and Lasker Award in Clinical Medicine for her work. She is the first Chinese female to receive a Nobel Prize in Physiology or Medicine.

According to statistics, by 1984, there were actually about 9 million chemical substances in the world, of which about 43% were materials. Although the number of materials is large, if classified according to chemical composition, it can be summarized into three categories: metal materials, inorganic non-metal materials and composite materials.

The composite material is new structural material. It is characterized by a combination of volumetric strength, volumetric stiffness and corrosion resistance over metallic materials. It is composed of a matrix material such as synthetic resin, metal or ceramic, and a reinforcing material composed of inorganic or organic synthetic fibres. There are a variety of substrates and reinforcing materials so that a selective fit can be made to produce various composites with satisfactory performance, which has a broader prospect for chemical materials.

Sinochem and Shanghai Chemical Industry Institute have set up a laboratory for composite materials. The two sides will jointly develop technology, transform the results and apply in the industry of carbon fiber and its curing resins, in order to promote the technologies and products of high-performance composite materials and facilitate its industrialization and marketization. At present, this laboratory has launched a project to research and develop the spray-free carbon fiber composite material. At first, this material will be applied to new energy cars, which can not only reduce the weight of the cars but also reduce the cost of applying composite materials while improving production efficiency significantly.

Chinese companies plan to go into the specialties side of the market, and some of them already become one of the players in the market, such as Zhejiang NHU, a vitamin maker; Yantai Wanhua, an isocyanates maker; and Bairun, the leader in the Chinese flavors-and-fragrances market.

China government set up policy goals to solve the unemployment issue and boost the economy, in order to against the increasing population. The government"s policies and goals have progressed as the economy was opened up in 1978. It can be divided into three periods:

China"s chemical industry has developed over the past 40 years, from an economic backwater to the largest chemicals manufacturing economy, that consumes raw materials and energy. This change has helped hundreds of millions of Chinese out of poverty but polluted China"s air and water at the same time.

Chemical industries in China are starting to research and develop green technologies by the recommendation of the government such as the use of alternative fuels to produce chemical products. Some industries are using carbon dioxide and others naturally available to produce industrial products, fuels and other substances. For example, a specialty chemicals company called Elevance Renewable Sciences produces highly concentrated detergents by using green technology metathesis, which significantly lowers the energy consumption and minimizes pollution.

On June 28, China Rongsheng Heavy Industry Group Holdings Co., Ltd. announced that the new construction machinery factory in Hefei Economic and Technological Development Zone was officially put into operation, and the first excavator was also successfully rolled off the line that day. With the commissioning of the new plant, in the future, construction machinery, as a growth point for new businesses, will also play an important role in the group"s diversified development and strengthening of the RMB business strategy.

On the 28th, relying on the front-end excavator to slowly drive off the production line also means that China Rongsheng Heavy Industry"s construction machinery sector has entered a stage of comprehensive development.

The new plant in Hefei is one of the production base projects of China Rongsheng Heavy Industry"s construction machinery sector. The production base is listed by the Anhui Provincial Government as a key construction project of the "861 Action Plan" and is a key promotion of the Hefei Municipal Government’s "Twelfth Five-Year Plan" The project, the excavator project covers an area of 850 mu. According to reports, the construction of the new factory has also created a new Rongsheng speed. From the official start of construction in November 2010 to the start of production on June 28, 2011, it only took more than 7 months. The 18-month assembly workshop construction cycle was shortened to 6 months, creating a miracle in the engineering construction of the same industry.

At the beginning of the establishment of China Rongsheng Heavy Industry, it was recognized that the risks of the shipbuilding industry fluctuate greatly with the economic cycle. The development of diversified industries with high added value and diversified profit growth is a good way to resist systemic risks. According to this strategy, and in response to the industrial planning policy of Anhui Province to build Hefei into the "Construction Machinery Capital", in March 2010, China Rongsheng Heavy Industry registered and established "Rongsheng Machinery Co., Ltd." (Rongsheng Machinery) in Hefei. ), mainly engaged in the manufacturing and sales of construction machinery. 10% of the planned listing and financing will be used in the construction machinery sector

In 2010, through the acquisition of Hefei Zhenyu, Rongsheng Machinery currently produces 16 types of hydraulic excavators and two types of hydraulic crawler cranes. While building a new production base, Rongsheng Machinery has also entered the pre-development stage and will replace the original The direct sales model was changed to an agency model and expanded to 10 companies, and the overall cooperation with financial companies was strengthened. Through the acquisition of Quanchai Group, the construction machinery sector has obtained a stable supply of engine parts. With the commissioning of the new plant, Rongsheng Machinery will enter a stage of comprehensive development. In the future, the new production base will have a production capacity of 30,000 excavators.

As the Chinese government increases investment in infrastructure and gradually implements a series of policies to promote the development of the central and western regions, the market demand for construction machinery is expected to continue to increase. Su Zimeng, secretary-general of the China Construction Machinery Industry Association, revealed at the "2011 China Construction Machinery Industry Development Strategy Forum" held recently that the "12th Five-Year Plan" of the construction machinery industry has been reported to the relevant state departments before May 1st this year. Monthly release. He pointed out that during the "Twelfth Five-Year Plan" period, the sales revenue of the construction machinery industry is expected to reach 900 billion yuan, with an average annual growth rate of 17%, and the export target is set at 26 billion US dollars. Sales of 10,000 units rose to 250,000 units.

At the same time, the development of construction machinery business will also help China Rongsheng Heavy Industries develop RMB business and effectively resist exchange rate risks. Chen Qiang, president of China Rongsheng Heavy Industry, said that the company will vigorously expand its domestic shipbuilding and construction machinery business due to the continuous appreciation of the RMB against the US dollar.

At present, a considerable part of China Rongsheng Heavy Industries" orders are from overseas. Therefore, most of the shipbuilding contracts are settled in U.S. dollars, while the costs are calculated in RMB. How to effectively control exchange rate risks has always been the focus of China Rongsheng Heavy Industries. At present, China Rongsheng Heavy Industry has consciously increased its RMB settlement business. It is expected that with the full development of construction machinery, the group"s future income sources will also show a diversified trend, and the income of RMB and US dollars will be more balanced.

GUID: F3731A0F-5907-49F5-9B6F-5EC21F716A9BThe original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.

Results: A total of 3195 patients with RA received IM (n = 1379, 43.2%) or WM (n = 1816, 56.8%). Following 1:1 propensity score matching, 1,331 eligible patients prescribed IM were compared to 1,331 matched patients prescribed WM. The GEE analysis with PSM showed that the IM was more beneficial to significantly decrease the levels of VAS, PGA and PhGA (VAS: odds ratio (OR), 0.76; 95% CI, 0.63–0.92; p = 0.004; PGA: OR, 0.76; 95% CI, 0.64–0.92; p = 0.007; and PhGA: OR, 0.77; 95% CI, 0.64, 0.93; p = 0.004), and reduce DAS28 (OR, 0.84; 95% CI, 0.73–0.98; p = 0.030) in the per-protocol population.

Conclusion: This study suggests that compare to WM, IM has advantages in improving RA-related outcomes. However, the statistical significance might not reveal significant clinical difference. Further studies should be focused on specific treatment strategies and/or disease stages.

Management of rheumatoid arthritis (RA) symptoms using Integrative medicine (IM), such as a combination of Chinese medicine (CM) and Western medicine (WM), has been widely adopted among Chinese populations (Zhao et al., 2013). With growing needs in the public and interests among investigators, number of clinical studies, including trials and reviews, have been trending up in recent decades.

Eligible patients aged 18 years or older with RA for at least 3 months who fulfilled the 1987 American College of Rheumatology (ACR) or 2010 European Alliance of Associations for Rheumatology (EULAR) diagnostic criteria diagnosed by physicians (Britsemmer et al., 2011; Kay and Upchurch, 2012). Patients were excluded if they had little or were lack of ability for self-care; confusion in diagnosis caused by acute and chronic infections; been diagnosed with severe, progressive, or uncontrolled diseases on heart, liver, kidney, gastroenterology, endocrinology, hematology, or cancer; history of joint surgery; medical history of neurological diseases or psychiatric disorders; been currently participating in clinical trials. All the participants gave written informed consent. Patients included in the study received either 1) IM or 2) WM during the treatment based on clinical considerations of physicians. The IM is defined as combined treatment of WM and CM. WM consists of pharmacotherapy for RA including steroids, NSAIDs, and DMARDs. On the other hand, CM involved Chinese herbal decoctions, or tablets/capsules composed solely of Chinese herbs and their extracts. The types of medications used by patients with RA at baseline and during follow-up were shown in Table 1. All participants were then followed up 1 year with 3-month intervals: at 3 months, 6 months, 9 months, and 12 months from the baseline visit. Since there were cases with a discrepancy between the medication at each follow-up, we defined study populations as follows to delineate the genuine effect of IM or WM treatment; intention-to-treat (ITT) and per-protocol (PP) populations. The ITT population was defined by patients who received medication at baseline. The PP population was restricted to the population who received the same medication at baseline and at follow-up.

The primary outcome was change in disease activity score 28 (DAS28) during 4 follow-up visits. The secondary outcomes included change in tender joint count (TJC), swollen joint count (SJC), morning stiffness (MS), visual analog scale (VAS), patient’s and physician’s global assessment of disease activity based on visual analogue scale (PGA, PhGA), erythrocyte sedimentation rate (ESR), c-reactive protein (CRP), rheumatoid factor (RF), anti-cyclic citrullinated peptide (Anti-CCP), simplified disease activity index (SDAI), clinical disease activity index (CDAI), health assessment questionnaire (HAQ) during 4 follow-up visits.

Continuous variables were expressed as mean (standard deviation) or medians (interquartile range, IQR), depending on the data distribution pattern. Categorical variables were described using frequencies and percentages. The Multiple Imputation (MI) by chained equations method was used to interpolate the missing data. Baseline characteristics before and after PSM were compared between IM and WM groups using the variance analysis Kruskal–Wallis rank-sum test for continuous variables and Chi-square test for categorical variables. Generalized estimating equation (GEE) models that controlled for variables were used to investigate a time trend and assess group differences in the primary outcome and secondary outcomes after PSM. This was done using a GEE autoregressive time-lag model that correlates the IM or WM on RA related clinical outcomes 1 year later. The IM or WM was used as an independent variable, each RA related clinical outcomes at baseline was used as control variable, and the corresponding continuous clinical outcomes were used as dependent variables. Significance levels were set at a 2-tailed p < 0.05. Statistical analyses were performed using R (Version 4.1.0).

A total of 3195 patients with RA received IM (n = 1379, 43.2%) or WM (n = 1816, 56.8%) and were included in the ITT population (Figure 1). During the 1-year observational period, 996 patients lost to follow up, and a comparison of baseline characteristics between the lost and follow-up groups was shown in Supplementary Table S1. 1619 (50.7%) patients continued the same medication until 12 months and were considered as the PP population. During the 1-year follow-up, a total of 1576 ITT patients changed the type of medication from WM to IM or vis versa. The comparison of baseline characteristics between the unchanged medication group and the medication changed group was shown in Supplementary Table S2. The frequency of missing baseline information of the unchanged medication patients was 38 (1.19%) cells (Supplementary Table S3). Throughout the study, we recorded abnormal values from the patients based on their laboratory test results. However, we are not able to judge whether the abnormalities were caused by the disease or/and the treatments. In the study, no serious adverse event was observed. There was no direct evidence showing a significant difference in the rate of self-reporting adverse events in the PP population between the two groups (p = 0.713), which was 1.35% and 1.72% in the WM and IM groups, respectively.

In the unmatched groups (1,816 patients treated by WM compared to 1,379 patients treated by IM), the IM group was older (mean age 62.02 versus 60.34 years, p < 0.001) and had a higher level of BMI (22.09 versus 21.89 kg/m2, p = 0.036) compared to the WM group in the ITT population (Supplementary Table S4). Compared to the WM group, the IM group had similar proportion of males, family history and operation history of RI-related. The IM group had higher rates of smoking and drinking. 256 (18.6%) patients reported at least one comorbidity in the IM group which was slightly higher than the WM group (p = 0.044). However, the prevalence of hypertension and diabetes was similar in both groups. The median duration of RA of both groups was about 6 years.

Following 1:1 propensity score matching, 1,331 eligible patients prescribed IM were compared to 1,331 matched patients prescribed WM. After matching, the demographic and clinical characteristics of both groups were well balanced (Supplementary Table S4).

Comparisons of treatment groups in the PP population before PSM showed that the IM group were older than the WM group (mean age 64.66 versus 60.96 years, p < 0.001). The proportions of male patients were about 19% in both groups. 56 (5.4%) patients in the WM group had family history of RI-related which was higher than the IM group (p = 0.018). Patients in the WM group had higher smoking rates (2.4% versus 1.0%, p = 0.050). 553 eligible patients prescribed IM were compared to 553 matched patients prescribed WM after PSM. No statistically significant differences were found in baseline variables after matching between groups (Table 2).

Changes in clinical manifestations measures of RA in the ITT and PP population from baseline to 4 follow-up visits were shown in Supplementary Table S5 and Table 3, respectively. The comparison in different rheumatoid arthritis clinical manifestations between baseline and visit 4 in medication changed group was shown in Supplementary Table S6. In the ITT population, the time × group interaction for all outcomes was not significant (p > 0.05). Figure 2 shows the changes of outcomes in six domains related to RA, including joint, morning stiffness, and pain, between baseline and the fourth follow-up, and overall decreased in both IM and WM group in PP population. The results indicated a significant time × group interaction for MS (p = 0.049), PGA (p = 0.049), and PhGA (p = 0.047), indicating that the scores for these three domains in the 2 groups had different trends over the 5 time points. Compared with the WM, the IM significantly decreased the levels of VAS, PGA and PhGA in the PP analysis (VAS: odds ratio (OR), 0.76; 95%CI, 0.63–0.92; p = 0.004; PGA: OR, 0.76; 95% CI, 0.64–0.92; p = 0.007; and PhGA: OR, 0.77; 95% CI, 0.64, 0.93; p = 0.004).

PP, per-protocol; IM, integrative medicine; WM, western medicine; IQR, interquartile range; TJC, tender joint court; SJC, swollen joint count; MS, morning stiffness; VAS, visual analog scale; PGA, patient’s global assessment of disease activity; PhGA, physician’s global assessment of disease activity; ESR, erythrocyte sedimentation rate; CRP, c-reaction protein; RF, rheumatoid factor; Anti-CCP, anti-cyclic citrullinated peptide; DAS28, disease activity score 28; SDAI, simplified disease activity index; CDAI, clinical disease activity index; HAQ, health assessment questionnaire.

Box plots of changes in joint, morning stiffness, and pain outcomes during the first year of follow-up in PP population. IM: Integrative medicine, WM: Western medicine, PGA, PhGA, patient’s and doctor’s global assessment of disease activity based on visual analogue scale.

The variation patterns of laboratory outcomes in the IM and WM groups in PP population at baseline and follow-up were shown in Figure 3. The average level of RA related laboratory indicators in each domain in both two groups gradually decreased over time (Table 3). The result indicated a significant time × group interaction for ESR (p = 0.032). The ESR level of patients in the IM and WM groups decreased gradually from baseline 28 mm/h to 21 and 22 mm/h, respectively. However, the level of CRP, RF and CCP reduced by IM was not significantly higher than that of WM (p > 0.05).

Box plots of changes in laboratory outcomes during the first year of follow-up in PP population. IM: Integrative medicine, WM: Western medicine, PGA, PhGA, patient’s and doctor’s global assessment of disease activity based on visual analogue scale.

Box plots of changes in Composite outcomes during the first year of follow-up in PP population. IM: Integrative medicine, WM: Western medicine, PGA, PhGA, patient’s and doctor’s global assessment of disease activity based on visual analogue scale.

Biologically, the involvement of Chinese herbal medicine induces multiple treatment pathways and mechanisms especially single herb can contain various kinds of active ingredients targeting RA-related receptors and biomarkers (Chen et al., 2004; van der Greef et al., 2010; Seca and Franconi, 2018). With human clinical trials and animal studies suggested the efficacy and safety of IM with Chinese herbal medicine and their extractions (Liu et al., 2018; Wang et al., 2019), IM approaches are expected to motivate improvements in RA treatments strategies and outcomes. Moreover, as biological agents for rheumatoid arthritis are gradually under consideration for national health insurance coverage, we look forward to investigating the role of biological agents in IM treatment strategies in future studies.

Prevalence of RA is estimated to be 0.2–0.3% in China with approximately 3-million patients (Zeng et al., 2008). Data provided by this perspective cohort will play a key role in reflection of the health service in China by revealing the medical treatments given to the RA patients. In recent years, IM approaches have been receiving attention globally not only among the patients, but also among physicians, researchers, and decision-makers. However, in many diseases, the benefits brought by IM over WM are still unclear. As a result, we hope our analysis could facilitate other teams/nations to carry out further IM-related research for RA in particular through clinical trials with investigation of underlying treatment mechanisms, and eventually, facilitate development of corresponding IM clinical practice guidelines.

This study suggests that compare to WM, IM has advantages in improving RA-related outcomes. However, the statistical significance might not reveal significant clinical difference. Further studies should be focused on specific treatment strategies and/or disease stages.

We thank all the patients participated for data contribution and our colleagues for their dedicated work on the cohort. We would also like to thank Shu Yang, School of Intelligent Medicine, Chengdu University of Traditional Chinese Medicine, for the support in statistical analysis.

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.

This work was supported by following funding programs: Leading Talents in Shanghai; Shanghai Municipal Health Commission, and East China Region based Chinese and Western Medicine Joint Disease Specialist Alliance [ZY (2021-2023)-0302]; The 2020 Guangdong Provincial Science and Technology Innovation Strategy Special Fund (Guangdong-Hong Kong-Macau Joint Lab), [No: 2020B1212030006]; and Science and Technology Commission of Shanghai Municipality [STCSM Q12 19401934600].

RA, Rheumatoid arthritis; IM, Integrative medicine; CM, Chinese medicine; WM, Western medicine; NSAIDs, non-steroidal anti-inflammatory drugs; DMARDs, disease-modifying antirheumatic drugs; ACR, American College of Rheumatology; EULAR, European Alliance of Associations for Rheumatology; ITT, intention-to-treat; PP, per-protocol; BMI, body mass index; RI, rheumatic immunity; PSM, propensity score matching; DAS28, disease activity score 28; TJC, tender joint count; SJC, swollen joint count; MS, morning stiffness; VAS, visual analog scale; PGA, patient’s global assessment of disease activity; PhGA, physician’s global assessment of disease activity; ESR, erythrocyte sedimentation rate; CRP, c-reactive protein; RF, rheumatoid factor; Anti-CCP, anti-cyclic citrullinated peptide; SDAI, simplified disease activity index; CDAI, clinical disease activity index; HAQ, health assessment questionnaire; MI, multiple imputation.

Britsemmer K., Ursum J., Gerritsen M., van Tuyl L. H., van Schaardenburg D., van Schaardenburg D. (2011). Validation of the 2010 ACR/EULAR classification criteria for rheumatoid arthritis: Slight improvement over the 1987 ACR criteria. Ann. Rheum. Dis.

Liu W., Zhang Y., Zhu W., Ma C., Ruan J., Long H., et al. (2018). Sinomenine inhibits the progression of rheumatoid arthritis by regulating the secretion of inflammatory cytokines and monocyte/macrophage subsets. Front. Immunol.

Zhang C., Jiang M., He X. J., Lu A. P. (2015). Clinical trials of integrative medicine for rheumatoid arthritis: Issues and recommendations. Chin. J. Integr. Med.

Zhao J., Zha Q., Jiang M., Cao H., Lu A. (2013). Expert consensus on the treatment of rheumatoid arthritis with Chinese patent medicines. J. Altern. Complement. Med.

The intestine is the main organ for nutrient digestion and absorption and colonizes trillions of microorganisms (Yang et al., 2018). According to statistics, the human intestine inhabits over 1014 microorganisms, about 10 times the total amount of human cells (Koboziev et al., 2014). Mounting evidence indicated that gut microbiota played essential roles in immunity, intestinal homeostasis, and epithelium differentiation (Liu et al., 2020; Xiang et al., 2020). Moreover, numerous investigations also revealed the positive regulation roles of gut microbiota in intestinal barrier function, metabolism, and host health (Cani and Delzenne, 2009; Dong et al., 2020). Some bacteria have the ability to restrict the proliferation of pathogenic and opportunistic pathogens in the intestine by producing beneficial metabolites, which was considered a vital barrier against pathogen infection (Wang et al., 2018a). Although intestinal microorganisms reside in the intestine, they may cause systemic effects. Numerous studies provided supporting evidence that gut microbiota was a central or driving factor of many diseases, injuring both near and far organ systems (Acharya and Bajaj, 2021). Gut microbial alterations may extend their detrimental influences beyond the intestine and impair liver and brain (Albhaisi et al., 2020). However, gut microbial homeostasis is easily affected by many factors, such as stress, antibiotics, heavy metal, and pesticide (Kakade et al., 2020). Early studies revealed that gut microbial alternations were associated with many diseases, including diarrhea, diabetes, obesity, and even colorectal cancer (Frazier et al., 2011; Wang et al., 2018b).

Thiram (tetramethyl thiuram disulfide), a broad-spectrum antibacterial pesticide, is widely used in field crops, such as wheat, corn, cotton, and multiple vegetables (Zhang et al., 2018). However, thiram has been demonstrated to be toxic to many animals, including chickens, goats, mice, and fish (Oruc, 2010; Huang et al., 2018). Previous research has indicated that thiram significantly could stimulate the respiratory tract, skin, and gastrointestinal mucosa and inhibit the formation of white blood cells (Walia et al., 2009). Moreover, long-term thiram exposure also caused dysfunction of the central nervous system, internal organs, and endocrine system (Oruc, 2010). Recent studies on thiram toxicity demonstrated that thiram exposure could decrease the quality of the chicken and induce lipid metabolism disorder (Kong et al., 2020). Additionally, other studies indicated that exposure to thiram significantly altered the biochemical indices of liver function and induced bone disease by inhibiting the development of chondrocytes (Mehmood et al., 2019). However, the relationship between thiram exposure and gut microbiota of chickens remains scarce. Herein, we dissected the shifts of gut microbiota in thiram-induced chickens.

The collected intestinal and liver tissues were fixed immediately in 4% paraformaldehyde for subsequently preparing histological sections. The specific methods and details of hematoxylin and eosin (H&E) stains were conducted according to previous research (Mehmood et al., 2019).

Total RNA of liver was extracted using TRIzol reagent as per the efficient RNA extraction method. Subsequently, the isolated RNA was reverse-transcribed into cDNA based on the manufacturer"s guidelines. The RT-qPCR was conducted in Step One-PlusTM Real-Time PCR System (Applied Biosystems). The reaction condition and mixture specification were determined as described previously (Mehmood et al., 2019). The relative expression of each gene was calculated with 2−ΔΔCT method and normalized to GAPDH expression. Related primers used in this experiment, such as Atg5, Bak1, Bax, Bcl2, Beclin1, Casp3, Lc3b, and P53, are shown in Supplementary Table S1.

The collected liver was homogenized and centrifuged at 12,000 rpm for 10 min to obtain the supernatant for evaluating total protein concentration. The total protein concentration was assessed by the Coomassie Brilliant Blue g-250 method. Western blot analysis was performed based on the method of previous studies. The main antibodies used in this study were Atg5, Bax, Cytc, Beclin1, Lc3b, and P62. Data were indicated as the protein normalized to GAPDH expression.

All frozen intestinal samples were thawed on ice and homogenized, and the homogenized samples (approximately 200 mg) of each intestinal segment were applied to total genomic DNA extraction based on the manufacturer"s protocol. Subsequently, the quality evaluation (integrality, purity, and concentration) of extracted DNA was performed. The specific primers (338F: ACTCCTACGGGAGGCAGCA and 806R: GGACTACHVGGGTWTCTAAT) with adaptors synthesized as per the 16S rRNA conserved regions were used to amplify the V3/V4 hypervariable regions. PCR amplification procedure was performed in triplicates, and reaction conditions and volume were based on previous studies. Afterward, the obtained amplified products were subjected to quality evaluation, recycle target fragment, fluorescent quantitation, and purification. The final libraries were subjected to sequencing following the standard protocols.

The obtained raw reads were subjected to filter, identify, and remove primer sequences by Trimmomatic (v0.33) and Cutadapt software (1.9.1) to obtain clean reads that do not contain primer sequences. The clean reads of each intestinal sample were performed double-ended sequence splicing using Usearch software (v10), and then the spliced data were filtered by length based on the length range of different areas. The final effective reads were obtained after identifying and removing the chimera sequence using UCHIME software (v4.2). The obtained effective reads were clustered as operational taxonomic units (OTUs) as per 97% similarity. Multiple diversity indices were generated according to the abundance distribution of OTUs in different samples to evaluate the gut microbial diversity. PCoA was employed to visualize the gut microbial difference between control and thiram-exposure groups. Differentially represented microbial taxa between both groups were analyzed utilizing the LEfSe and Metastats analysis. GraphPad Prism (v8.0) was used for performing statistical analysis. Probability values (means ± SD) <0.05 were considered statistically significant.

The histopathological alterations in the intestine and liver are shown in Figure 1. HE staining indicated that the intestinal structures in controls were integrated with clear borders, whereas those in thiram-treated chickens were arranged loosely, irregularly, and disorderly (Figures 1A1,A2,B1,B2). Additionally, the liver tissues in the control chickens were displayed as regular and normal structures. However, thiram exposure caused a decrease in glycogen vacuoles of hepatocytes (Figures 1C1,C2,D1,D2).

Figure 1. Thiram exposure caused intestinal and liver injury. (A1,A2,B1,B2) Histopathological observation in intestinal tissues of the control group and thiram-treated group. (C1,C2,D1,D2) Histopathological observation in liver tissues of the control group and thiram-treated group. (E) Changes in gene expression related to liver apoptosis and autophagy. (F) Changes in protein expression related to liver apoptosis and autophagy.

To investigate the effect of thiram on liver autophagy and apoptosis, we detected the expression of genes related to autophagy and apoptosis in the liver by RT-qPCR analysis. Results indicated that thiram exposure significantly affected autophagy and apoptosis-related gene expression. As shown in Figure 1E, apoptosis-related gene expressions including Bax and Bcl2 were dramatically increased in the thiram-treated group as compared to the control group, whereas no significant differences in P53, Casp3, and Bak1 levels were found between both groups. Moreover, the mRNA levels of apoptosis-related genes, such as Beclin1 in the thiram-treated group, were significantly increased via comparing the control group, but no obvious differences in Atg5 and Lc3b levels were observed between both groups. Similarly, the results of western blot also indicated that the expression of Bax was significantly improved in the thiram-treated group in comparison with the control group (Figure 1F).

In this microbiome investigation, six ileal samples were conducted amplicon sequencing and 480,338 (CI = 239,765, TI = 240,573) raw sequences were collected (Table 1). After quality evaluation and data optimization, we totally acquired 458,546 (CI = 228,428, TI = 230,118) effective reads, with a median read count of 76,424 (ranging from 75,852 to 77,136) per sample. Both rarefaction and rank abundance curves of each sample supported the adequacy of the sampling efforts (Figures 2A–C). In addition, a total quantity of 333 OTUs was recognized and 199 OTUs were shared by both groups, which together made up 59.76% of the overall OTUs (Figure 2D). Moreover, 77 and 57 OTUs were uniquely recognized in CI and TI, respectively (Figures 2E,F).

Figure 2. Thiram exposure changed the gut microbial composition and diversity of chickens. (A,B) Rarefaction curves. (C) Rank abundance curve. (D–F) Venn diagrams. (G–I) Chao1, ACE, and Simpson indices were employed to evaluate gut microbial alpha diversity. (J) PCoA map based on the unweighted UniFrac distance. (K) Clustering analysis. (L,M) Relative proportion of preponderant bacteria at the phylum and genus levels.

To further dissect the gut microbial alternations during thiram exposure, we calculated the alpha and beta diversity in the microbial community. There were statistically significant differences in the Chao1 (224.95 ± 9.63 vs. 166.64 ± 1.14, p = 0.0039) and ACE (225.6421 ± 5.8365 vs. 162.4799 ± 1.0765, p = 0.0004) indices, whereas the Simpson index (0.392 ± 0.05 vs. 0.4916 ± 0.0791, p = 0.3469) was not dramatically different between the CI and TI (Figures 2G–I). Statistical analysis of alpha diversity showed that thiram exposure significantly decreased the gut microbial richness of chickens but had no effect on the microbial diversity. Moreover, the beta diversity reflecting the differences between intergroup and intra-group individuals was evaluated using PCoA and UPGMA tree. PCoA plots revealed aggregation of intra-group samples, but a separation of samples in different groups, which was consistent with the UPGMA tree, implying that the gut microbial principal component was strongly affected by the thiram exposure (Figures 2J,K).

The relative proportions of preponderant taxa at different levels were assessed by microbial taxon assignment, and significant variations in the gut microbial community of CI and TI were observed. There were nine phyla identified in six samples, varying from seven to nine phyla per sample. The phyla Proteobacteria (76.94, 71.60%), Firmicutes (22.52, 25.30%), and Actinobacteria (0.37, 1.74%) were the three most preponderant phyla in the CI and TI regardless of health status, which accounted for over 98% of all bacterial taxa (Figure 2L). Other bacterial phyla including Gemmatimonadetes (0.0018, 0.088%), Fusobacteria (0.0063, 0.069%), and Epsilonbacteraeota (0.00090, 0.021%) in CI and TI were indicated with lower abundances. To further dissect the influence of thiram exposure on taxonomic compositions, 168 genera were totally identified in the bacterial populations. Among them, Escherichia–Shigella (76.57%) was the most prevalent genus in the CI, followed by Candidatus Arthromitus (11.25%) and Enterococcus (3.15%) (Figure 2M). Moreover, Escherichia–Shigella (41.99%), Acinetobacter (26.63%), and Candidatus Arthromitus (11.07%) were abundantly present in the TI, which together made up approximately 80% of the bacterial composition. The heatmap reflecting the genus-level cluster analysis displayed the bacterial distribution in different samples and revealed the alternations in bacterial compositions during thiram exposure (Figure 3).

To further determine the shifts in microbial compositions of chickens during thiram exposure, Metastats analysis was conducted to characterize the differences in the gut microbiota of both groups. At the phylum level, the abundances of Actinobacteria (P < 0.01) and Acidobacteria (P < 0.05) in the TI group were dramatically dominant than in the CI group (Figure 4). At the genus level, 18 genera were totally detected to be significantly different between CI and TI groups. Among them, the relative richness of eight genera (Lachnospiraceae_FCS020_group, Oribacterium, Tyzzerella_4, Lachnospiraceae_UCG-008, Marvinbryantia, Ruminiclostridium, Lachnospiraceae_UCG-004, and Ruminococcus_2) dramatically reduced, whereas the relative abundances of 10 genera (Prevotella_7, Pseudochrobactrum, Aerococcus, uncultured bacterium_f_Beggiatoaceae, Arthrobacter, Pseudomonas, Rummeliibacillus, Lysobacter, Sphingomonas, and uncultured_bacterium_f_Xanthobacteraceae) significantly increased during thiram exposure. Among decreased bacterial genera, seven genera (Lachnospiraceae_FCS020_group, Oribacterium, Tyzzerella_4, Lachnospiraceae_UCG-008, Marvinbryantia, Lachnospiraceae_UCG-004, and Ruminococcus_2) even cannot be found in the gut microbiota of thiram-induced chicken. Given this discriminant analysis could not distinguish the dominant taxon, LEfSe was employed for generating a cladogram to identify the specific bacteria related to thiram exposure (Figure 5). We also found that Anaerofilum, Macrococcus, and Faecalibacterium were the most preponderant bacteria in the CI group, whereas Lactobacillus, Klebsiella, and Bradyrhizobium were observably overrepresented in the TI group.

Figure 4. Significant shifts in the gut microbial compositions during thiram exposure. Metastats analysis displayed microbial changes between both groups. All data were represented as mean ± SD. *p < 0.05, **p < 0.01.

Figure 5. Cladogram showing the phylogenetic distribution of gut microbial community related to the control and thiram-exposure groups (A). LDA scores > 2 were considered statistically significant (B).

Pesticides have been extensively used in agricultural production, but they may be accumulated and enriched in multiple ecosystems, posing a great threat to food safety and public health (Fu et al., 2018; Xu et al., 2020). Early investigations revealed that thiram exposure could cause decreased growth performance, liver toxicity, oxidative damage, and even osteogenesis disorders in chickens, but its potential influence on gut microbiota, apoptosis, and autophagy in chickens remains uncertain (Mehmood et al., 2019; Zhang et al., 2019). Here, the thiram poisoning model was constructed to investigate its influence on gut microbiota, apoptosis, and autophagy, and significant alterations of gut microbiota were observed.

Given feces cannot fully display the gut microbial abundance and diversity, we collected intestinal content for 16S rDNA amplicon sequencing. Our results indicated an observably reduced alpha diversity in the gut microbial community of chickens exposed to thiram, indicating its gut microbial dysbiosis. Typically, the gut microbial community changes dynamically within limits under the influence of age, diet, and environment and these physiological fluctuations cannot affect normal intestinal functions (Wang et al., 2018b; Li et al., 2021). However, the ecological balance of the gut microbial community may be broken and changed significantly, when the external environment shifts dramatically, including long-term exposure to antibiotics, heavy metals, and pesticides (Li et al., 2019; Zhong et al., 2021). Early investigations demonstrated that the higher gut microbial diversity and abundance were beneficial to the intestine to perform complex physiological functions and energy utilization, whereas the decreased microbial diversity may threaten the host"s health (Wang et al., 2018b, 2021). Several previous studies revealed that the declined gut microbial diversity can significantly affect the metabolism of fat and carbohydrates, thereby further accelerating fat accumulation and inducing obesity and diabetes (DiBaise et al., 2008; Cani et al., 2012). Furthermore, the reduced gut microbial diversity has also been demonstrated to be closely related to the occurrence of cardiovascular diseases, diarrhea, allergies, and asthma (Tang and Hazen, 2014; Han et al., 2017). The intestine is closely associated with host immunity, metabolism, and nutrient absorption, which in turn depends on the stabilized gut microbial community (Tremaroli and Backhed, 2012; Rooks and Garrett, 2016). Therefore, imbalanced gut microbiota can also affect the immunological function and intestinal permeability of the host, which may increase morbidity (Liu et al., 2019). Moreover, gut microbial dysbiosis can impair intestinal functions and selectively promote the growth of pathogens, which may induce the occurrence of many diseases in neighbor or local organs, such as diarrhea, hepatic injury, and inflammatory bowel diseases (Frazier et al., 2011; Sheehan and Shanahan, 2017). Notably, some opportunistic pathogens that do not initially exhibit pathogenicity may also induce the occurrence of diseases, in the case of hypoimmunity and gut microbial dysbiosis (Wang et al., 2019). During gut microbial alternations, some toxic metabolites produced from pathogens can enter the intestinal hepatic circulation via the intestinal barrier, thereby further exacerbating the hepatic injury (Hussain et al., 2020; Zhong et al., 2021). Currently, thiram has been demonstrated to induce hepatic injury, but the potential relationship between gut microbial dysbiosis and thiram-induced liver damage remained to be investigated (Zhang et al., 2018). The results of PCoA analysis revealed that the experimental group and control group were separated from each other, suggesting an obvious difference in the gut microbial principal component between CI and TI groups. Consequently, we suspected that thiram exposure may the important driving force for shifts in the principal components of gut microbiota.

Importantly, we also observed considerable variability in some bacteria during the induction of thiram and those altered bacteria may play vital roles in the intestinal ecosystem and functions. Interestingly, some of the quantitatively reduced bacteria were considered probiotics in the intestine and seven genera even cannot be observed, suggesting that these bacteria cannot adapt to the present intestinal environment. We suspected that long-term thiram exposure disrupts the intestinal structure and environment, which inhibited the colonization of those bacteria. Lachnospiraceae was negatively related to intestinal inflammation (Zhao et al., 2017). Ruminiclostridium could improve growth performance and reduce gastrointestinal diseases (Tan et al., 2014). Ruminococcus is involved in the degradation of cellulose and starch (Zhao et al., 2018). Notably, the above-mentioned bacteria such as Ruminiclostridium, Ruminococcus, and Lachnospiraceae can also produce short-chain fatty acids (SCFAs). Early investigations revealed that SCFAs can inhibit the invasion and colonization of pathogenic and conditional pathogens by affecting the pH of the intestine (Van Immerseel et al., 2004; Zhou et al., 2014). Moreover, short-chain fatty acids can improve the intestinal environment (Goverse et al., 2017; Melbye et al., 2019). Recent studies on short-chain fatty acids have also shown their vital roles in alleviating inflammation, preventing cancer, regulating cell apoptosis, and lowering cholesterol (Chaudhary et al., 2021; Jiao et al., 2021). Notably, thiram exposure also resulted in a significant increase in pathogenic bacteria, such as Aerococcus. Aerococcus has been demonstrated to cause urinary tract infection and endocarditis (Yabes et al., 2018).

In summary, the current study explored the alterations of gut microbiota in thiram-exposed chickens. Results indicated that thiram exposure not only obviously changed gut microbial composition and diversity but also induced liver apoptosis and autophagy. The altered gut microbiota may play crucial roles in the potential mechanism of thiram-induced intestinal toxicity and hepatotoxicity. Moreover, this research also extended the understanding of the toxicity of thiram and provided a theoretical basis for the toxicity study on prolonged thiram exposure in chickens. However, this study has some limitations including relatively small sample size and the inability to control for potentially important variables, such as individual variation and individual dietary habits.

ZW and RS conceived and designed the experiments, contributed sample collection and reagents preparation, analyzed the data, and revised and reviewed the manuscript. ZW wrote the manuscript. All authors contributed to the article and approved the submitted version.

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