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The availability of large healthcare datasets offers the opportunity for researchers to navigate the traditional clinical and translational science research stages in a nonlinear manner. In particular, data scientists can harness the power of large healthcare datasets to bridge from preclinical discoveries (T0) directly to assessing population-level health impact (T4). A successful bridge from T0 to T4 does not bypass the other stages entirely; rather, effective team science makes a direct progression from T0 to T4 impactful by incorporating the perspectives of researchers from every stage of the clinical and translational science research spectrum. In this exemplar, we demonstrate how effective team science overcame challenges and, ultimately, ensured success when a diverse team of researchers worked together, using healthcare big data to test population-level substance use disorder (SUD) hypotheses generated from preclinical rodent studies. This project, called Advancing Substance use disorder Knowledge using Big Data (ASK Big Data), highlights the critical roles that data science expertise and effective team science play in quickly translating preclinical research into public health impact.
Developing alternatives to antibiotics is an urgent need in livestock production. Antimicrobial peptides (AMPs) are regarded as powerful antibiotic substitutes (ASs) because AMPs have broad-spectrum antimicrobial activities and growth-promoting ability. Here, we aimed to comprehensively assess the effects of AMPs on the growth performance, diarrhea rate, intestinal morphology and immunity of healthy or challenged piglets, compared with an antibiotics group or negative control group. We performed a set of meta-analyses of feeding trials from database inception to 27 May 2019. Among the 1379 identified studies, 20 were included in our meta-analyses (56 arms and 4067 piglets). The meta-analyses revealed that (1) compared with the negative control group, AMPs significantly improved the healthy piglets’ average daily gain (ADG), average daily feed intake (ADFI), gain : feed ratio (G/F), levels of immune globulin (Ig) IgM and IgG, and intestinal villus height : crypt depth ratio (V/C) (P < 0.05). Meanwhile, AMPs significantly increased the challenged piglets’ ADG, ADFI, G/F and V/C of the jejunum and ileum, and notably deceased the diarrhea rate (P < 0.05); (2) compared with antibiotics group, the effects of AMPs were slightly weaker than those of antibiotics in the healthy piglets, but AMPs have similar effects to those of antibiotics in challenged piglets. In a higher purity, the optimal dose of AMPs may be approximately 0.01%. Our findings indicate that AMPs can improve piglet growth performance, enhance immunity, benefit intestinal morphology and decrease the diarrheal rate. AMPs could be great ASs especially under infection conditions.
Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium.
A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing.
Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects.
In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.
Mindfulness based art therapy induces emotional relaxation in cancer patients and is a treatment known to improve psychological stability. The objective of this research was to evaluate the treatment effects of MBAT for breast cancer patients.
Twenty-four breast cancer patients were selected as subjects of the study. Two groups, the MBAT group and control group with 12 patients each, were randomly assigned. The patients in the MBAT group were given 12 sessions of treatments. To measure depression and anxiety, low scales of the Personality Assessment Inventory (PAI) was used. Health-related quality of life was evaluated using the European organization for research and treatment of cancer quality of life questionnaire (EORTC-QLQ-C30). The treatment results were analyzed using Ancova and two-way repeated measures Anova.
The results showed that depression and anxiety decreased significantly and health-related quality of life improved significantly in the MBAT group. In the control group, however, there was no significant change.
MBAT can be seen as an effective treatment method that improves breast cancer patients’ psychological stability and quality of life. Evaluation of treatment effects using program development and large-scale research for future clinical application is needed.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
The search for life in the Universe is a fundamental problem of astrobiology and modern science. The current progress in the detection of terrestrial-type exoplanets has opened a new avenue in the characterization of exoplanetary atmospheres and in the search for biosignatures of life with the upcoming ground-based and space missions. To specify the conditions favourable for the origin, development and sustainment of life as we know it in other worlds, we need to understand the nature of global (astrospheric), and local (atmospheric and surface) environments of exoplanets in the habitable zones (HZs) around G-K-M dwarf stars including our young Sun. Global environment is formed by propagated disturbances from the planet-hosting stars in the form of stellar flares, coronal mass ejections, energetic particles and winds collectively known as astrospheric space weather. Its characterization will help in understanding how an exoplanetary ecosystem interacts with its host star, as well as in the specification of the physical, chemical and biochemical conditions that can create favourable and/or detrimental conditions for planetary climate and habitability along with evolution of planetary internal dynamics over geological timescales. A key linkage of (astro)physical, chemical and geological processes can only be understood in the framework of interdisciplinary studies with the incorporation of progress in heliophysics, astrophysics, planetary and Earth sciences. The assessment of the impacts of host stars on the climate and habitability of terrestrial (exo)planets will significantly expand the current definition of the HZ to the biogenic zone and provide new observational strategies for searching for signatures of life. The major goal of this paper is to describe and discuss the current status and recent progress in this interdisciplinary field in light of presentations and discussions during the NASA Nexus for Exoplanetary System Science funded workshop ‘Exoplanetary Space Weather, Climate and Habitability’ and to provide a new roadmap for the future development of the emerging field of exoplanetary science and astrobiology.
Solar coronal dimmings have been observed extensively in the past two decades and are believed to have close association with coronal mass ejections (CMEs). Recent study found that coronal dimming is the only signature that could differentiate powerful flares that have CMEs from those that do not. Therefore, dimming might be one of the best candidates to observe the stellar CMEs on distant Sun-like stars. In this study, we investigate the possibility of using coronal dimming as a proxy to diagnose stellar CMEs. By simulating a realistic solar CME event and corresponding coronal dimming using a global magnetohydrodynamics model (AWSoM: Alfvén-wave Solar Model), we first demonstrate the capability of the model to reproduce solar observations. We then extend the model for simulating stellar CMEs by modifying the input magnetic flux density as well as the initial magnetic energy of the CME flux rope. Our result suggests that with improved instrument sensitivity, it is possible to detect the coronal dimming signals induced by the stellar CMEs.
Rabies is one of the major public health problems in China, and the mortality rate of rabies remains the highest among all notifiable infectious diseases. A meta-analysis was conducted to investigate the post-exposure prophylaxis (PEP) vaccination rate and risk factors for human rabies in mainland China. The PubMed, Web of Science, Chinese National Knowledge Infrastructure, Chinese Science and Technology Periodical and Wanfang databases were searched for articles on rabies vaccination status (published between 2007 and 2017). In total, 10 174 human rabies cases from 136 studies were included in this meta-analysis. Approximately 97.2% (95% confidence interval (CI) 95.1–98.7%) of rabies cases occurred in rural areas and 72.6% (95% CI 70.0–75.1%) occurred in farmers. Overall, the vaccination rate in the reported human rabies cases was 15.4% (95% CI 13.7–17.4%). However, among vaccinated individuals, 85.5% (95% CI 79.8%–83.4%) did not complete the vaccination regimen. In a subgroup analysis, the PEP vaccination rate in the eastern region (18.8%, 95% CI 15.9–22.1%) was higher than that in the western region (13.3%, 95% CI 11.1–15.8%) and this rate decreased after 2007. Approximately 68.9% (95% CI 63.6–73.8%) of rabies cases experienced category-III exposures, but their PEP vaccination rate was 27.0% (95% CI 14.4–44.9%) and only 6.1% (95% CI 4.4–8.4%) received rabies immunoglobulin. Together, these results suggested that the PEP vaccination rate among human rabies cases was low in mainland China. Therefore, standardised treatment and vaccination programs of dog bites need to be further strengthened, particularly in rural areas.
Climate change has greatly affected agricultural production, and will lead to further changes in cropping system, varietal type and cultivation techniques for each region. The potential effects of climate change on rice production in Fujian Province, China, were explored in the current study with CERES-Rice model and climate-change scenarios, based on the self-adaptation of rice production. The results indicated that simulated yields of early rice in the double-rice region in south-eastern Fujian under scenarios A2, B2 and A1B increased by 15·9, 18·0 and 19·2%, respectively, and correspondingly those of late rice increased by 9·2, 7·4 and 7·4% when self-adaptation adjustment was considered, compared to scenarios without that consideration. In the double-rice region in north-western Fujian, simulated yields of early rice increased by 21·2, 20·5 and 18·9% and those of late rice by 14·7, 14·8 and 7·2% under scenarios A2, B2 and A1B, respectively, when self-adaptation was considered, compared to without consideration. Similar results were obtained for the single-rice region in the mountain areas of north-western Fujian, correspondingly increasing by 4·9, 5·0 and 2·9% when self-adaptation was considered compared to when it was not. In this single-rice region, double rice might be grown in the future at the Changting site under scenarios A1 and B2. When the self-adaptation adjustment was considered, the simulated overall output of rice crops in Fujian under scenarios A2, B2 and A1B increased by 5·9, 5·2 and 5·1%, respectively. Thus, more optimistic results were obtained when the self-adaptation ability of rice production was considered.
Rural-to-urban migrant workers are a large marginalised population in urban China. Prevalence estimates of common mental health problems (CMHPs) in previous studies varied widely and very few studies have investigated migration-related factors of CMHPs in migrant workers. The objective of this study was to determine the prevalence and risk factors of CMHPs among Chinese migrant workers.
A random sample of 3031 migrant workers of ten manufacturing factories in Shenzhen, China, completed a standardised questionnaire containing socio-demographic and migration-related variables and the Chinese 12-item General Health Questionnaire (GHQ-12). A GHQ-12 score of three or higher was used to denote the presence of CMHPs.
The prevalence of CMHPs was 34.4% in Chinese migrant workers. In multiple logistic regression, risk factors for CMHPs included being 16–25 years old (odd ratio [OR] 1.65, 95% confidence interval [CI] 1.28, 2.12), being 26–35 years old (OR 1.36, 95% CI: 1.05, 1.75), low monthly income (OR 1.42, 95% CI 1.04, 1.92), poor living condition (OR: 1.76, 95% CI: 1.22, 2.54), physical illness in the past 2 weeks (OR 1.72, 95% CI 1.43, 2.05), having worked in many cities (OR 1.34, 95% CI 1.03, 1.74), infrequently visiting hometown (OR 1.56, 95% CI 1.22, 1.99), poor Mandarin proficiency (OR 1.51, 95%CI 1.13, 2.01), a low level of perceived benefits of migration (OR 1.33, 95% CI 1.14, 1.55) and working more than 8 h/day (OR 1.39, 95% CI 1.14, 1.70).
CMHPs are very prevalent among Chinese migrant workers. Given the large number of Chinese migrant workers, there is an urgent need to address the mental health burden of China's migrant worker population.
We determined the prevalence and seasonality of infections by Fasciola of goats and bovine species (cattle and water buffalo) in Hubei and Anhui provinces of China. Faecal samples were collected at 2- to 3-month intervals from 200 goats in Hubei province and from 152 bovine species in Anhui province. All faecal samples were examined for the presence of parasites. We determined the nucleotide sequences of the first and second internal transcribed spacers (ITS-1 and ITS-2) of the nuclear ribosomal DNA (rDNA) of 39 Fasciola worms from Anhui province. The prevalence of Fasciola infection in goats ranged between 3.5 and 37.0%, with mean eggs per gram (EPG) ranging between 29.0 and 166.0. Prevalence and EPG exhibited downward trends over time with significant differences. The prevalence of Fasciola infection in cattle ranged between 13.3 and 46.2% (mean EPG, 36.4–100.0), and that of water buffalo ranged between 10.3 and 35.4% (mean EPG, 25.0–89.6), with a higher prevalence of infection and EPG from June to October compared with December to March. Analysis of ITS-1 and ITS-2 sequences revealed that F. hepatica and F. gigantica were present in all bovine species of Anhui province and that F. gigantica mainly infected water buffalo. This is the first demonstration of Fasciola infection in Hubei province and detection of F. hepatica and F. gigantica in Anhui province. The present study of Hubei province shows that mass treatment of livestock with closantel sodium injections in April and August/September controlled Fasciola infection effectively.