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Additional file 1:Table S1. Deaths of NASH-related liver cancer attributable to HFPG in 1990 and 2019, and its temporal trends from 1990 to 2019. Table S2. YLDs of NASH-related liver cancer attributable to HFPG in 1990 and 2019, and its temporal trends from 1990 to 2019. Table S3. YLLs of NASH-related liver cancer attributable to HFPG in 1990 and 2019, and its temporal trends from 1990 to 2019. Table S4. Deaths and DALYs of NASH-related liver cancer attributable to HFPG in countries and territories. Table S5. EAPC of NASH-related liver cancer deaths and DALYs attributable to HPFG in countries and territories. Figure. S1. The deaths of NASH-related liver cancer attributable to HFPG in countries and territories. (A) The ASR of NASH-related liver cancer deaths attributable to HFPG in 2019; (B) The relative change in percentage of NASH-related liver cancer deaths attributable to HFPG between 1990 and 2016. ASR, age-standardized rate. Figure. S2. The DALYs of NASH-related liver cancer attribute to HFPG in countries and territories. (A) The ASR of DALYs of NASH-related liver cancer attributable to HFPG in 2019; (B) The relative change in percentage of NASH-related liver cancer DALYs attributable to HFPG between 1990 and 2016. ASR, age-standardized rate. DALYs, disability adjusted life years. Figure. S3. The clusters of countries and territories in terms of the temporal trends of the NASH-related liver cancer burden attributable to HFPG. Figure. S4: Temporal trend of deaths rate of NASH-related liver cancer attributable to HFPG for different age group, 1990–2019.

Additional file 1: Figure S1. Rapid causes of cancer mortality worldwide for females and males, 1990–2019. Figure S2. Tracheal, bronchus, and lung cancer age-standardized mortality rates in 2019 (A) and percent change (%) in age-standardized rates during 1990–2019 (B) for 204 countries and territories by sociodemographic index. Figure S3. The colon and rectal cancer age-standardized mortality rates in 2019 (A) and percent change (%) in the age-standardized rate during 1990–2019 (B) for 204 countries and territories by sociodemographic index. Figure S4. Breast cancer age-standardized mortality rates in 2019 (A) and percent change (%) in age-standardized rates during 1990–2019 (B) for 204 countries and territories by sociodemographic index. Figure S5. Pancreatic cancer age-standardized mortality rates in 2019 (A) and percent change (%) in age-standardized rates during 1990–2019 (B) for 204 countries and territories by sociodemographic index. Figure S6. Local drifts of tracheal, bronchus, and lung cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S7. Local drifts of colon and rectal cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S8. Local drifts of breast cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S9. Local drifts of pancreatic cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S10. Age distribution of tracheal, bronchus, and lung cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S11. Age distribution of colon and rectal cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S12. Age distribution of breast cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S13. Age distribution of pancreatic cancer mortality attributable to HFPG by SDI quintiles, 1990–2019. Figure S14. Age, period and cohort effects on tracheal, bronchus, and lung cancer mortality attributable to HFPG by SDI quintiles. Figure S15. Age, period and cohort effects on colon and rectal cancer mortality attributable to HFPG by SDI quintiles. Figure S16. Age, period and cohort effects on breast cancer mortality attributable to HFPG by SDI quintiles. Figure S17. Age, period and cohort effects on pancreatic cancer mortality attributable to HFPG by SDI quintiles. Figure S18. Age, period and cohort effects on tracheal, bronchus, and lung cancer mortality attributable to HFPG for representative countries. Figure S19. Age, period and cohort effects on colon and rectal cancer mortality attributable to HFPG for representative countries. Figure S20. Age, period and cohort effects on breast cancer mortality attributable to HFPG for representative countries. Figure S21. Age, period and cohort effects on pancreatic cancer mortality attributable to HFPG for representative countries. Table S1. Percent changes (%) in the age-standardized mortality rate 1990–2019 for all risk factors. Table S2. Trends in cancer mortality attributable to HPFG for females and males across SDI quintiles, 1990 − 2019. Table S3. Trends in tracheal, bronchus, and lung cancer mortality attributable to HPFG for both females and males across SDI quintiles, 1990 − 2019. Table S4. Trends in colon and rectal cancer mortality attributable to HPFG for both females and males across SDI quintiles, 1990 − 2019. Table S5. Trends in breast cancer mortality attributable to HPFG for female across SDI quintiles, 1990 − 2019. Table S6. Trends in pancreatic cancer mortality attributable to HPFG for both females and males across SDI quintiles, 1990 − 2019. Table S7. Trends in cancer mortality attributable to HPFG for both genders in 204 countries and regions, 1990–2019. Table S8. Trends in cancer mortality attributable to HPFG for both females and males in representative countries, 1990–2019. Table S9. Trends in tracheal, bronchus, and lung cancer mortality attributable to HPFG for both females and males in representative countries, 1990–2019. Table S10. Trends in colon and rectal cancer mortality attributable to HPFG for both females and males in representative countries, 1990–2019. Table S11. Trends in breast cancer mortality attributable to HPFG for both females in representative countries, 1990–2019. Table S12. Trends in pancreatic cancer mortality attributable to HPFG for both females and males in representative countries, 1990–2019.

To evaluate the clinical effects of Xiyanping injection intervention in pediatric patients with mild hand foot and mouth disease (HFMD).A total of 329 patients were stratified and block-randomized for symptomatic treatment of HFMD and assigned to one of the following groups: Western Medicine (group A, n = 103), Xiyanping injection (group B, n = 109), or Xiyanping injection and symptomatic treatment using Western Medicine (group C, n = 117). During the trial, fever, rash, ulcers of the mouth were observed among participants in each group before and after treatment, and conversion rates from mild to severe HFMD were measured.After 3-7 days' treatment, no significant differences in the conversion rates from mild to severe HFMD were observed among the three groups (P0.05). There was a significantly low number of patients with the onset time of antifebrile effect, vanished time of hand and foot rashes and cumulative time for the ulcers in the mouth vanished, among the three groups (P0.05, P0.01). The onset time of antifebrile effect of patients in groups B and C were markedly shorter compared with those in group A (P0.05, P0.01); there was no statically significant difference observed between groups B and C (P0.05). No significant differences were observed in the time for body temperature recovery among the three groups (P0.05). There were no significant differences in adverse effects among the three groups (P0.05).Xiyanping injection together with use of Western Medicine is most effective for symptomatic treatment of mild HFMD. No severe adverse reactions were observed.

Premature ovarian insufficiency (POI) affects seriously physical and mental health of the patients. Studies show that acupuncture may be promising in treating POI, yet evidence is insufficient. International patient registry, one form of observational study, is designed for evaluating effectiveness and safety of acupuncture in real-world clinical settings. We will face a series of opportunities and challenges. The opportunities are as follows: (1) Interdisciplinary cooperation can improve the effect of acupuncture for POI. (2) The protocol for acupuncture to treat POI has room for improvement. (3) The patient registry study can make up the shortcomings of randomized controlled trials. (4) The patient registry study can collect real-world data and explore responses of different populations to acupuncture and can be the foundation for the successive studies. International patient registry may face technological, ethical and financial challenges, while the established International Patient Registry Platform of Acupuncture-Moxibustion ( www.amreg.org:8082/v3 ) is actively responding to these challenges. Till now there have been more than 300 patients of POI enrolled on this platform.

In recent years, a growing number of dynamic, double-blind and randomized trials for traditional Chinese medicine (TCM) have been designed with adaptive treatment regimens. The blind envelope or current randomization and trial supply management (RTSM) system have not met this requirement. Therefore, a more efficient platform for subject randomization and medicine dispensation was required. After we had done much research on dynamic TCM treatment trials’ protocols, a new RTSM was designed and developed, which is suitable for TCM clinical trial during randomizing the groups for subject and medicine allocation in China. In a recurrent tuberculosis study of TCM, this RTSM system was involved in the management of subjects and medicines. By this system, a suit of TCM formulas or placeboes were assigned to patients based on their TCM syndrome diagnosis results by investigators at different visit points. The new RTSM system was convenient to operate, reduced operational errors, enhanced the management efficiency, and improved the data quality.

Objective To preliminarily analyze key factors influencing curative effect through clinical observations of acupoint application for “treatment of winter disease in summer” used to prevent and treat bronchial asthma in children. Methods In an observational study and prospective cohort study, we observed children in remission of asthma at three class III grade A TCM hospitals in Liaoning, Hubei, and Chengdu. Results A total of 609 children conformed to diagnostic and inclusive standards for remission of bronchial asthma. Through follow-up visits, we observed their skin reactions and the time and chance of treatment with different therapies in the three hospitals; we also compared and analyzed different drugs, acupoints, and preparations. We found that the key Chinese drugs were Bai Jie Zi (Semen Sinapis Albae) and Yian Hu Suo (Rhizoma Corydalis); the key acupoints were Feishu (BL 13), Gaohuang (BL 43), Dingchuan (EX-B1), Tiantu (CV 22), and Shanzhong (CV 17); and the best preparation was a mixture of drugs, ginger juice, and musk. Acupoint application was practiced on the hottest days of summer and the coldest days of winter for 0.5 to 2 h with the lowest rate of asthma relapse. Conclusions The present data analysis shows that the curative effect of acupoint application for “treatment of winter disease in summer” may be influenced by recipes of Chinese drugs, preparations, prescriptions of acupoints, chance, time, and skin reactions. A curative effect is the result of the comprehensive action of these factors.

Patient-reported outcome (PRO), which is directly obtained from patients, is a multidimensional measure to evaluate the health condition of a patient. The obtained data give evidence of effectiveness from patients' point of view. This article reviews the application of PRO in the study of cancer. The application of PRO is studied from aspects, such as evaluating cancer clinical trials, formulating health policies, evaluating adverse events, evaluating compliance, approving new drugs, and studying the relation between health-related quality of life and PRO.

The light extraction has an important effect on LED encapsulation to obtain a high efficiency. The influence of packaging structure on LED light extraction was investigated in TracePro. Four kinds of high-power LED packaging methods based on the structure and the character of flip chip were presented, flip chip on board (1 reflective-cup), flip chip to substrate (1 reflective-cup), flip chip on board (100 reflective-cups) and flip chip to substrate (100 reflective-cups). Flip chip on board was that the LED chip was directly bonded to the aluminum substrate, flip chip to substrate was the LED chip bonded to the Si-Substrate before bonded to the aluminum. Two different structures of aluminum substrate were analyzed, 1 substrate with only 1 reflective cup and 1 substrate with 100 reflective cups. The final result shows that the luminous efficiency of flip chip on board (100 reflective-cups) is 0.03% higher than flip chip to substrate (100 reflective-cups); luminous efficiency of flip chip on board (1 reflective-cup1) is 0.04% lower than flip chip to substrate(1 reflective-cup). Luminous efficiency of flip chip on board (100 reflective-cups) is 10% higher than flip chip on board(1 reflective-cups); luminous efficiency of flip chip to substrate (100 reflective-cups) is 6.3% higher than flip chip to substrate(1 reflective-cup).

Rough set based rule generation methods need discretization of the continuous values. However, most existing discretization methods cause inconsistencies. In this paper, we propose an algorithm that can eliminate the inconsistencies caused during the course of discretization. The algorithm can be integrated into the discaretization algorithms that cannot avoid causing inconsistencies to eliminate the inconsistencies. Three data experimental results show that the algorithm is available.

Rough set discernibility matrix method is a valid method to attribute reduction. However, it is a NP-hard problem. Up until now, though some methods have been proposed to improve this problem, the case is not improved well. We find that the idea of discernibility matrix can be used to not only the whole data but also partial data. So we present a new algorithm to reduce the computational complexity. Firstly, select a condition attribute C that holds the largest measure of γ(C, D) in which the decision attribute D depends on C. Secondly, with the examples in the non-positive region, build a discernibility matrix to create attribute reduction. Thirdly, combine the attributes generated in the above two steps into the attribute reduction set. Additionally, we give a proof of the rationality of our method. The larger the positive region is; the more the complexity is reduced. Four Experimental results indicate that the computational complexity is reduced by 67%, 83%, 41%, and 30% respectively and the reduced attribute sets are the same as the standard discernibility matrix method.

Most of the existing discretization methods such as k-interval discretization, equal width and equal frequency methods do not take the dependencies of decision attributes on condition attributes into account. In this paper, we propose a discretization algorithm that can keep the dependencies of the decision attribute on condition attributes, or keep the positive regions of the partition of the decision attribute. In the course of inducing classification rules from a data set, keeping these dependencies can achieve getting the set of the least condition attributes and the highest classification precision.

In a real world data set there are usually four kinds of mistaken values, the first one is the mistake in unit; the second one is the mistake of putting the radix points in wrong place, the third one is a scribal error, and the fourth one is a computational mistake. In this paper, we propose two algorithms for finding these four kinds of mistaken data. SARS and coronary heart disease data sets experimental results show that the two algorithms are available, that is, using the two algorithms we find some mistakes in the SARS and coronary heart disease data sets, and the results correspond to that found manually by medical experts.

In fault diagnosis and medical diagnosis fields, often there is more than one fault or disease that occur together. In order to obtain the factors that cause a single fault to change to multi-faults, the standard rough set based methods should be rebuilt. In this paper, we propose a decernibilty matrix based algorithm with which the cause of every single fault to change to multi-faults can be revealed. Additionally, we propose another rough set based algorithm to induce the common causes of all the single faults to change to their corresponding multi-faults, which is a process of knowledge discovery in rule base, i.e., not the usual database. Inducing more abstract rules in knowledge base is a very challenging problem that has not been resolved well.

Because of the amount of missing values in our SARS data set is very large, to fill in them wholly with the existing methods is impossible or the results of being filled in are not reliable. Only taking two attributes into account can avoid using the large amount of missing values, which is the feature of rough set that other machine learning method cannot hold. In this paper, we induced some rules based on rough set from the SARS data set that have not been detected by medical experts in clinic practice.