ABSTRACT
Background: In an interim analysis of Asian pts with uHCC in the observational REFINE study of regorafenib (NCT03289273), treatment-emergent adverse events (TEAEs) were consistent with those reported in the global, phase 3 RESORCE trial. Here, we present the final analysis of Asian pts with uHCC in REFINE. Method(s): REFINE is an international, prospective, multicenter study that enrolled pts with uHCC for whom a decision to treat with regorafenib was made by the treating physician prior to enrollment, according to the local health authority approved label. The primary objective is safety, including the incidences of TEAEs and dose modifications due to TEAEs (NCI-CTCAE v4.03). Secondary endpoints include overall survival, progression-free survival, and treatment duration. Result(s): Of the 1005 evaluable pts, 557 (55%) were from Asia (Korea [31%], Japan [26%], Taiwan [24%], China [18%], Thailand [1%]) and 82% were male. At baseline, median age was 65 years (range 21-94) and the most common HCC etiology in Asian pts was hepatitis B (60%) and in non-Asian pts was alcohol use (36%;Table). More Asian pts (71%) had received prior transarterial chemoembolization vs non-Asian pts (42%). The initial daily regorafenib dose was 160/120/80/40 mg in 51%/12%/35%/3% of Asian pts and 42%/9%/45%/4% of non-Asian pts. The median treatment duration was 3.7 months (range 0-34.4) in Asian pts and 3.6 months (range 0-38.9) in non-Asian pts. The most common TEAEs in Asian pts were hand-foot skin reaction (40%), diarrhea (27%), and decreased appetite (17%). TEAEs led to dose modification in 44% of Asian pts. [Formula presented]. Conclusion(s): These final data from REFINE confirm the safety and effectiveness of regorafenib in Asian pts with uHCC from a broad population in real-world practice. Final analyses from REFINE are ongoing and will be presented at the conference. Clinical trial identification: NCT03289273. Editorial acknowledgement: Editorial assistance in the preparation of this manuscript was provided by Matthew Reynolds of OPEN Health Communications (London, UK), with financial support from Bayer. Legal entity responsible for the study: Bayer. Funding(s): Bayer. Disclosure: Y.J. Kim: Financial Interests, Personal, Advisory Role: Bayer, Bristol Myers Squibb, Samil, PharmaKing, Celltrion, Bukwang;Financial Interests, Personal, Invited Speaker: Roche, AbbVie, Eisai, Ipsen, Boston Scientific, Bristol Myers Squibb, BTG, Bayer, MSD, Gilead Sciences, Novo Nordisk, Green Cross Cell, Boehringer Ingelheim, AstraZeneca;Financial Interests, Personal, Funding: BTG, Bayer, Boston Scientific, AstraZeneca, Gilead Sciences, Samjin, BL&H. M. Kurosaki: Financial Interests, Personal, Speaker's Bureau: Gilead Sciences, AbbVie, Eisai, Chugai, Lilly, Takeda. H.Y. Lim: Financial Interests, Personal, Advisory Role: Bayer, Eisai, Roche, Ipsen. M. Ikeda: Financial Interests, Personal, Advisory Board: AstraZeneca, Chugai, Eli Lilly Japan, Eisai, Nihon Servier, Novartis, Ono, Takeda, GlaxoSmithKline;Financial Interests, Personal, Invited Speaker: AstraZeneca, Bayer, Bristol Myers Squibb, Chugai, Eli Lilly Japan, Eisai, Nihon Servier, Novartis, Taiho, Yakult, Teijin Pharma, AbbVie, Abbott Japan, Fujifilm Toyama Chemical, Incyte Biosciences Japan, ASLAN, Chugai, Nihon Servier, Takeda;Financial Interests, Institutional, Invited Speaker: Bayer, Bristol Myers Squibb, Eisai, AstraZeneca, Eli Lilly Japan, Chugai Pharmaceutical, Merck Serono, MSD, Ono, Yakult, Novartis, Takeda, J-Pharma, Pfizer, Chiome Bioscience, Nihon Servier, Delta-Fly Pharma, Syneos Health, Merus.N.V. M. Kudo: Financial Interests, Personal, Invited Speaker: Eisai, Chugai, Eli Liiy, Bayer, Takeda, MSD;Financial Interests, Institutional, Research Grant: Otsuka, Sumitomo Dainippon Pharma, EA Pharma, Taiho, Eisai, AbbVie, Gilead Sciences, Takeda, GE Healthcare, Chugai. Y. Huang: Financial Interests, Personal, Advisory Role: Eisai, Bayer, BMS, Ono, Gilead, Lilly, AbbVie, Roche;Financial Interests, Personal, Invited Speaker: Eisai, Bayer, BMS, Ono, Gilead, Lilly, AbbVie, Roche;Financial Inte ests, Personal, Speaker's Bureau: Eisai, Bayer, BMS, Ono, Gilead, Lilly, AbbVie, Roche;Financial Interests, Institutional, Funding: Gilead. N. Kato: Financial Interests, Personal, Invited Speaker: Gilead Sciences Inc., AbbVie G.K., Ohtsuka Pharmaceutical Co., Ltd., Bayer Yakuhin Ltd., Chugai Pharmaceutical Co., Ltd., AstraZeneca K.K., Sumitomo Dainippon Pharma Co., Ltd., Takeda Pharmaceutical Co., Ltd., Zeria Pharmaceutical Co., Ltd., Olympus Corporation, Eisai Co., Ltd., Aska Pharmaceutical Co., Ltd., Tsumura & Co., Mochida Pharmaceutical Co., Ltd., Miyarisan Pharmaceutical Co., Ltd., Covidien Japan Inc., Eli Lilly Japan K.K., Nobelpharma Co., Ltd., Kowa Company, Ltd., Incyte Biosciences Japan GK, Yakult Honsha Co.,Ltd., Olympus Marketing, Inc., Taisho Pharmaceutical Co.,Ltd., Janssen Pharmaceutical K.K.;Financial Interests, Institutional, Research Grant: AbbVie G.K., Ohtsuka Pharmaceutical Co., Ltd., Bayer Yakuhin Ltd., Chugai Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Sumitomo Dainippon Pharma Co., Ltd., Shionogi & Co., Ltd., Eisai Co., Ltd., Tsumura & Co., Nippon Kayaku Co., Ltd., JIMRO Co., Ltd., Kowa Company, Ltd. C. Hsu: Financial Interests, Personal, Speaker's Bureau: Bristol Myers Squibb, Ono Pharmaceutical, Merck Sharp & Dohme, Roche, Eisai;Financial Interests, Institutional, Funding: Ono Pharmaceutical, AstraZeneca, MSD, Merck Serono, Taiho Pharmaceutical, Bristol Myers Squibb, BeiGene, NuCana BioMed, Johnson & Johnson, Roche/Genentech, BeiGene;Financial Interests, Personal, Advisory Role: Ono Pharmaceutical, MSD, Bristol Myers Squibb, Merck Serono, Roche/Genentech. B. Chewaskulyong: Financial Interests, Personal, Advisory Role: Pfizer, STADA;Financial Interests, Personal, Invited Speaker: AstraZeneca, Pfizer, DKSH, Janssen, BMS, MSD, Roche, TAIHO;Financial Interests, Personal, Speaker's Bureau: AstraZeneca, Pfizer, DKSH, Janssen, BMS, MSD, Roche, TAIHO;Financial Interests, Institutional, Funding: Bayer. J. Khan: Financial Interests, Institutional, Full or part-time Employment: Bayer. K. Ozgurdal: Financial Interests, Institutional, Full or part-time Employment: Bayer;Financial Interests, Personal, Stocks/Shares: Bayer. All other authors have declared no conflicts of interest. Copyright © 2022
ABSTRACT
Intercity traveling has been recognized as a leading cause for the continuation of the COVID-19 global pandemic. However, there lacks credible prediction of the spatiotemporal spread of COVID-19 with humans traveling between metropolitan areas. This study attempts to establish a novel framework to simulate human traveling and the spread of virus across an intercity population mobility network. A Markov process was introduced to capture the stochastic nature of travelers’ migration. A backward derivation algorithm was adopted and the Nelder-Mead simplex optimization method applied to overcome the limitation of existing deterministic epidemic models, including the difficulties in estimating the initial susceptible population and the optimal hyper-parameters required for simulation. We conducted two case studies with data from 24 cities in China and Italy. Our framework yielded state-of-the-art accuracy while being modular and scalable, indicating the addition of population mobility and stochasticity significantly improves prediction performance compared to using epidemic data alone. Moreover, our results revealed that transmission patterns of COVID-19 differ significantly with different population mobility, offering valuable information to the understanding of the correlation between traveling activities and COVID-19 transmission. © 2022, Springer Nature Switzerland AG.
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Vaccines are one of the biggest successes in modern history and are particularly important in light of the multiple ongoing epidemics. Recently, vaccines have protected peoples' health and lives around the world during the coronavirus disease 2019 pandemic. Different types of vaccines have their own characteristics and advantages and are used in the context of different epidemics. Responses to vaccination are also different, and can include adverse reactions and absent responses. These individual differences are thought to be influenced by host genes. In this review, we first discuss vaccine types and characteristics. Second, we discuss different responses to vaccination, primarily focusing on the association between genetic variation and inter-individual differences.
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The long-lasting global pandemic of Coronavirus disease 2019 (COVID-19) has changed our daily life in many ways and put heavy burden on our mental health. Having a predictive model of negative emotions during COVID-19 is of great importance for identifying potential risky population. To establish a neural predictive model achieving both good interpretability and predictivity, we have utilized a large-scale (n =542) longitudinal dataset, alongside two independent samples for external validation. We built a predictive model based on psychologically meaningful resting state neural activities. The whole-brain resting-state neural activity and social-psychological profile of the subjects were obtained from Sept. to Dec. 2019 (Time 1). Their negative emotions were tracked and re-assessed twice, on Feb 22 (Time 2) and Apr 24 (Time 3), 2020, respectively. We first applied canonical correlation analysis on both the neural profiles and psychological profiles collected on Time 1, this step selects only the psychological meaningful neural patterns for later model construction. We then trained the neural predictive model using those identified features on data obtained on Time 2. It achieved a good prediction performance (r =0.44, p =8.13 ×10-27). The two most important neural predictors are associated with self-control and social interaction. This study established an effective neural prediction model of negative emotions, achieving good interpretability and predictivity. It will be useful for identifying potential risky population of emotional disorders related to COVID-19. IEEE
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Objective To investigate the influence of negative emotions on risk perception in frontline medical staff at the early stage of coronavirus disease 2019 (COVID-19) outbreak. Methods An online questionnaire survey was conducted on the dispatched medical staff of Wuhan Huoshenshan Hospital and the frontline anti-epidemic medical staff of Changhai Hospital of Naval Medical University (Second Military Medical University) from Feb. 3 to 5, 2020. The negative emotions were measured by the reduced version of negative affection scale composed of 7 negative emotions. The risk perception level was evaluated by the risk perception questionnaire of frontline anti-epidemic medical staff adapted from nursing staff risk perception questionnaire. Results A total of 220 valid questionnaires were collected, with an effective rate of 85.94%. The total score of negative emotions of frontline medical staff at the early stage of COVID-19 outbreak was 11.18±4.58, and the scores of 7 negative emotions from high to low were tension (1.92±0.90), upset (1.75±0.92), fear (1.61±0.84), impatience (1.58±0.84), sadness (1.51±0.83), trembling (1.50±00.83) and guilt (1.31±0.64). The scores of impatience, sadness, upset and guilt of non-nursing staff were significantly higher than those of nursing staff (all P＜0.05). The total score of risk perception of medical staff was 17.68±4.60, and the score of time risk dimension was the highest (3.20±1.20). The organizational risk score (3.39±1.01 vs 2.88±1.01) and time risk score (3.46±1.22 vs 3.09±1.18) of the non-nursing staff were significantly higher than those of the nursing staff (P＜0.01 or P＜0.05). There was a positive correlation between the total score of negative emotions and the total score of risk perception (r＝0.499, P＜0.01). The score of each negative emotion classification had an indicating effect on different risk perception tendencies, and impatience had the most obvious indicating effect on time risk (β＝0.227, P＝0.033). Conclusion Medical staff with high negative emotions have high risk perception. The negative emotion management at the early stage of the epidemic can help frontline anti-epidemic medical staff to correctly understand the risk. © 2021 Second Military Medical University Press. All rights reserved.
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Artemisinin, extracted from the traditional Chinese medicine Artemisia annua Linn., has a powerful antimalarial effect. With further research, artemisinin and its derivatives have been found to have antiviral effects against a variety of viruses from different viral families, including Herpesviridae, Flaviridae, and Coronaviraceae, and can inhibit virus-induced inflammatory responses. The possible antiviral mechanisms include alkylation of DNA binding domain of NF-κB P65 subunit, inhibition of plasmidic nuclear transport of NF-κB p65, production of reactive oxygen species or activation of carbon center free radicals to regulate host Keap1/Nrf2/ARE pathway to inhibit viral replication. The inflammatory response was alleviated by inhibiting the activation of NF-κB and ERK pathways induced by the virus. This paper reviews the possible antiviral mechanism of artemisinin and its derivatives to provide reference for artemisinin to fight new viruses and promote new use of old drugs. © 2022 by the authors.
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With the development of biomedicine, and significant success achieved by targeted therapy in the treatment of complex and refractory diseases such as cancers, clinical treatment and drug discovery based on molecular targets become the main direction of modern medical research. Guided by holistic concept, traditional Chinese medicine (TCM) has a unique advantage with regards to the prevention and treatment of complex diseases through its comprehensive effect. However, at present, TCM research is insufficient and problems such as inaccurate clinical findings, lack of dominant diseases, unclear evaluation of efficacy, and unclear mechanisms, cannot be solved easily. Therefore, the authors believe that the development of TCM should adopt an innovative approach that integrates the advantages of TCM and western medicine, and positively influences the development of TCM and even future medicine. This article proposes Target-combined Holistic Treatment (THT), a new concept based on the integration of TCM and western medicine. While being guided by the holistic and systematic perspective of TCM, THT also factors in the latest advances in both TCM and modern biomedical research, and uses macro-micro combination, target-syndrome combination, and internal and external codivision, as the primary strategies to establish a clinical diagnosis model that combines disease differentiation, syndrome differentiation, and target differentiation. It also uses drug ingredients/components to enable comprehensive interventions against multiple targets linked to a disease, and establishes target medication and research strategy of TCM, so as to improve its pertinence, efficacy, and safety, and ensure precise and effective medication. The theories and methods of THT fully integrate the advantages of TCM and western medicine, factoring in both macro-control and micro intervention, and also systematic confrontation, precision treatment, and embracing TCM theory and modern technology. This can guide the further development of TCM, western medicine, as well as the combination of TCM and western medicine. It will therefore help promote the integration and innovation of both TCM and western medicine, and the in-depth development of TCM. The theories and methods of THT can be used to guide not only the whole process of clinical diagnosis but also the development of innovative drugs. THT has been used to guide the formulation of TCM diagnosis and treatment for COVID-19 and has shown remarkable results. We have developed a Chinese herbal prescription "Keguan-1", to prevent and treat COVID-19 based on the theory and method of THT, and use the doctrine of "resist foreign aggression and pacify the interior" of TCM against COVID-19. Using the findings of research in modern medicine, THT can innovate and develop TCM based treatments, and thus aid in the treatment of various diseases, and also help promote the integration and development of TCM and western medicine. © 2021, Science Press. All right reserved.
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The goal of the 20th International Workshop on Data Mining in Bioinformatics (BIOKDD 2021) is to encourage KDD researchers to tackle the numerous problems and challenges in Bioinformatics using Data Mining technologies. Based on the organizers' expertise and the BIOKDD communities, BIOKDD 2021 features the theme of "Artificial Intelligence in Medicine". This topic focuses on the use of machine learning and data mining techniques for the analysis of large amounts of heterogeneous, complex, biological and medical data, with a particular focus on deep learning methods that have seen rapid advance and wider adoption in Bioinformatics (e.g., DeepVariant, AlphaFold 2). We also particularly welcome COVID-19 related research. The key goal is to accelerate the convergence between Data Mining and Bioinformatics communities to expedite discoveries in basic biology, medicine and healthcare. © 2021 Owner/Author.
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Rationale: A dysregulated host inflammatory response in COVID-19 is considered a central pathogenetic mechanism of acute lung injury and extrapulmonary end-organ damage. However, limited comparative data are available as to whether the host-response in COVID-19 ARDS differs from patients with other (non-COVID) ARDS etiologies, and how such differences may inform targeted immunomodulating therapeutics. Methods: We prospectively enrolled 36 intubated patients with COVID-19 ARDS and 70 hospitalized non-intubated patients with COVID-19 (COVID-19 non-ARDS), and compared them with a pre-COVID-19 cohort of patients with bacterial (n=21), viral (n=14), and culture-negative ARDS (n=30). We measured 10 host-response biomarkers of innate immunity and epithelial/endothelial injury (IL-6, IL-8, IL-10, RAGE, TNFR1, Angiopoeitin-2, Procalcitonin, Fractalkine, Pentraxin-3, ST2) in plasma. Using a 4-variable predictive model (TNFR1, Angiopoeitin-2, Procalcitonin and bicarbonate levels), we classified patients into hyper-vs. hypo-inflammatory subphenotypes. We compared biomarker levels, subphenotypes and outcomes between the clinical groups. Results: Host-response biomarker levels were widely distributed between the 5 groups, with a characteristic pattern for IL-6, IL-8, Angiopoeitin-2, Procalcitonin, ST-2 and fractalkine: COVID-19 ARDS patients had higher biomarker levels than COVID-19 non-ARDS (p<0.01), lower levels than bacterial or culture-negative ARDS (p<0.01), and similar levels to viral ARDS (Figure 1A example for IL-6). A lower proportion of the COVID-19 ARDS cohort was classified in the adverse hyper-inflammatory subphenotype (15%) compared to bacterial (47%) and culture-negative ARDS (31%) (Figure 1B). Despite the lower level of inflammatory host responses, COVID-ARDS patients had longer median duration of mechanical ventilation (20.5 [10.0-40.8] days) compared to bacterial (8.0 [5.0-25.0]), culture-negative (7.0 [5.2-9.8]) and viral ARDS (7.5 [3.5-14.8]) (p<0.01). Patients with COVID-19 but without ARDS had lower 30-day mortality (6%) compared to patients with ARDS from COVID-19 (31%) or other etiologies (bacterial 33%, culture-negative 40% and viral 21%). Conclusion: Development of ARDS from COVID-19 is characterized by intensified inflammation compared to hospitalized COVID-19 patients not requiring mechanical ventilation. Compared to ARDS from other etiologies, host-response inflammatory profiles in COVID-19 ARDS appear similar to other viral etiologies of ARDS, and are lower compared to bacterial or culture-negative ARDS. The etiology of worse clinical outcomes of COVID-19 ARDS despite the lower frequency of the prognostically adverse hyper-inflammatory subphenotype warrant urgent investigation. (Table Presented).
ABSTRACT
Iron is the most widely used metal in China. There have been many changes in the international iron ore market due to the covid-19. Analyzing the reasons for the changes in the international iron ore supply, demand and market structure and predicting the future trends are of great significance for the stable supply of iron ore. This paper first analyzes the global steel production, iron ore supply and price trends under the covid-19 and believes that the global iron ore supply and demand pattern is further concentrated, showing a pattern of "two countries, two 60%". That is to say, China's steel production will further improve its global share, approaching 60%;Australia's supply share in the global iron ore shipping market will further increase, approaching 60%, because of the covid-19. Secondly, this paper predicts the changing trend of China's and global steel demand in the next 2-3 years, and believes that the main reason for the increase in China's steel production in recent years is the country's need for stable economic growth. China's steel production will remain high in the next 2~3 years, but in the long run, China's iron ore demand will slow down after a period of time. Finally, this paper analyzes the global iron ore price trend and believes that the global iron ore price will rise and fall to less than 100 US dollars/ton in the fourth quarter of 2020. The iron ore price will slowly fluctuate and fall down to 60~80 US dollars/ton in the next 2~3 years. © 2021, Science Press. All right reserved.
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In the view of the fact that online information in complex networks has an increasingly powerful impact on real society, an improved network public opinion diffusion model under public crisis is established in this paper. The model updates SEIR infectious disease model by using Mean Field Theory based on BA scale-free network, which presents scale-free characteristics as well as enhances the model accuracy and applicability. It conducts a sensitivity analysis and takes “2019-nCoV Explosion” as a sample, crawling through related 180-day microblogs, forwards, comments and likes on Weibo. The results demonstrate that the propagation is greatly influenced by propagation probability, the network structure, the initial spreader and social effects, which contributes to the understanding of network public opinion diffusion and the control of the information dissemination direction. © 2021
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Objective: To evaluate the clinical efficacy of traditional Chinese medicine Lianhua Qingwen Granules in treating suspected cases of children with Corona Virus Disease 2019. Methods: Clinical retrospective study method was used to collect 83 cases of common type children who met the diagnostic criteria of suspected cases of Corona Virus Disease 2019 and were admitted to Xiangyang No.1 People's Hospital from January 28, 2020 to March 31. Among them, 42 patients in the treatment group received routine treatment (antiviral and symptomatic support treatment, combined with antibacterial treatment for infected patients) combined with traditional Chinese medicine Lianhua Qingwen Granules. The control group of 41 patients received routine treatment only. Clinical data were collected after 5 d of treatment, and the disappearance of main symptoms (fever and cough), the duration of fever, and other single symptoms (cough, nasal obstruction, runny nose, shortness of breath, muscle pain, and gastrointestinal symptoms) were compared between the two groups. Results: The disappearance rates of fever and cough in the treatment group were 83.3% and 57.9%, respectively, and those in the control group were 51.2% and 30.3%, respectively. The treatment group was significantly better than the control group (P<0.05). The disappearance rates of phlegm, shortness of breath and digestive tract symptoms in the treatment group were 66.7%, 100% and 87.5%, respectively, and those in the control group were 20%, 60% and 28.6%, respectively, with significant increases (P<0.05). Conclusion: Traditional Chinese medicine Lianhua Qingwen Granules can significantly improve fever, cough, phlegm, shortness of breath and gastrointestinal symptoms in children suspected of Corona Virus Disease 2019, providing preliminary clinical evidence for the prevention and treatment of pediatric cases.
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The prevention and control of the novel coronavirus (COVID-19) is the priority work to maintain the public health security of the world nowadays. The COVID-19 prevention and control model using multi-agent modeling and simulation technology is proposed. The model can simulate the different dynamic development trend of the epidemic under different prevention and control measures. Taking Taiyuan as an example, according to the researched COVID-19 transmission rules, the prevention and control simulation of COVID-19 has been achieved under the designing rule of the interactive infection process and status transition process between various resident agents. Multi-scenario simulation experiments are realized under different policy measures of hospital and government. The experimental results show that the multi-agent modeling method is effective in analyzing the spread of COVID-19 and can provide decision support for city epidemic prevention and control. © 2020, The Editorial Board of Journal of System Simulation. All right reserved.
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Close contacts with high-risk exposure to COVID-19 cases are more robust in statistics for inferring future development of COVID-19 epidemic. In Beijing, the proportion of close contact cases in newly confirmed cases had increased from about 50% at the end of January to nearly 100% in mid-February, indicating that contact tracing and quarantine measures are effective non-pharmaceutical interventions for containing the epidemic. In addition, we show at the national level that the cumulative number of close contacts was stabilized at about eight times as much as infected individuals, and the growth rate of daily close contacts was consistent with that of daily confirmed cases 5~6 days later. Consequently, tracking the daily change of close contacts is beneficial to predict the trend of the epidemic, based on which advanced medical supplies scheduling and effective epidemic prevention can be achieved. © 2020, Editorial Board of Journal of the University of Electronic Science and Technology of China. All right reserved.