Receptor tyrosine kinases (RTKs) are transmembrane cell-surface proteins that act as signal transducers. They regulate essential cellular processes like proliferation, apoptosis, differentiation and metabolism. RTK alteration occurs in a broad spectrum of cancers, emphasising its crucial role in cancer progression and as a suitable therapeutic target. The use of small molecule RTK inhibitors however, has been crippled by the emergence of resistance, highlighting the need for a pleiotropic anti-cancer agent that can replace or be used in combination with existing pharmacological agents to enhance treatment efficacy. Curcumin is an attractive therapeutic agent mainly due to its potent anti-cancer effects, extensive range of targets and minimal toxicity. Out of the numerous documented targets of curcumin, RTKs appear to be one of the main nodes of curcumin-mediated inhibition. Many studies have found that curcumin influences RTK activation and their downstream signaling pathways resulting in increased apoptosis, decreased proliferation and decreased migration in cancer both in vitro and in vivo. This review focused on how curcumin exhibits anti-cancer effects through inhibition of RTKs and downstream signaling pathways like the MAPK, PI3K/Akt, JAK/STAT, and NF-κB pathways. Combination studies of curcumin and RTK inhibitors were also analysed with emphasis on their common molecular targets.
Background/Purpose: In this systematic review and meta-analysis, we assessed the effects of exercise (EX) combined with calorie restriction (CR) intervention on inflammatory biomarkers, and correlations between biomarkers and participants' characteristics were calculated in overweight and obese adults. Methods: An article search was conducted through PubMed, Web of Science, EMBASE, the Cochrane database, Scopus, and Google Scholar to identify articles published up to April 2021. Studies that examined the effect of EX + CR intervention on inflammatory biomarkers, including C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α), and compared them with a CR trial in overweight and obese adults were included. We calculated the pooled effect by meta-analysis, identified the correlations (between inflammatory biomarkers and participants' characteristics) through meta-regression, and explored the beneficial variable through subgroup analysis. The Cochrane risk of bias tool and Methodological Index for Non-randomized Studies were used to assess the risk of bias for the included trials. Results: A total of 23 trials, including 1196 overweight and obese adults, were included in the meta-analysis. The pooled effect showed that EX + CR intervention significantly decreased CRP levels (P = 0.02), but had no effect on IL-6 (P = 0.62) and TNF-α (P = 0.11). Meta-regression analysis showed that the effect of EX + CR on CRP, IL-6, and TNF-α changes was correlated with lifestyle behavior of adults (Coef. = -0.380, P = 0.018; Coef. = -0.359, P = 0.031; Coef. = -0.424, P = 0.041, respectively), but not with age and BMI. The subgroup analysis results revealed that participants with sedentary lifestyle behavior did not respond to EX + CR intervention, as we found no changes in CRP, IL-6, and TNF-α concentrations (P = 0.84, P = 0.16, P = 0.92, respectively). However, EX + CR intervention significantly decreased CRP (P = 0.0003; SMD = -0.39; 95%CI: -0.60 to -0.18), IL-6 (P = 0.04; SMD = -0.21; 95%CI: -0.40 to -0.01) and TNF-α (P = 0.006; SMD = -0.40, 95%CI: -0.68 to -0.12) in adults without a sedentary lifestyle or with a normal lifestyle. Furthermore, the values between sedentary and normal lifestyle subgroups were statistically significant for CRP, IL-6, and TNF-α. Conclusion: Our findings showed that combination EX + CR intervention effectively decreased CRP, IL-6, and TNF-α in overweight and obese adults with active lifestyles, but not with sedentary lifestyle behavior. We suggest that 'lifestyle behavior' is a considerable factor when designing new intervention programs for overweight or obese adults to improve their inflammatory response.
With both theories and empirical studies supporting the benefits of having a romantic relationship, there remains an increasing tendency of staying single being documented globally. It is thus important to understand the antecedent factors of such voluntary single movement. Guided by the Investment Model of Commitment (IMC) process, the roles of subjective socioeconomic status (SSES), relational mobility, and desirability of control in attitudes toward singlehood were investigated. A total of 1,108 undergraduate students from Malaysia (n=444), Japan (n=316), and India (n=348) answered an online survey consisting of the Attitudes toward Singlehood Scale, MacArthur Scale of SSES, Relational Mobility Scale, Desirability of Control Scale, Mini-Social Phobia Inventory, and Single Item Narcissism Scale. Hierarchical multiple regression analysis showed a persistent positive relationship between desirability of control, but not socioeconomic status and relational mobility, with attitudes toward singlehood, even after statistically excluding the effects of social anxiety and narcissism. A similar pattern was also observed among those who were currently single. Moreover, an interaction effect of socioeconomic status and relational mobility was found in further exploratory analysis. The results highlight that retaining the autonomy and flexibility of managing one's own life and financial concern are the key reasons young adults prefer staying single to engaging in a romantic relationship. Implications and recommendations for future research are also presented in this study.
Affected by coronavirus disease (COVID-19), in addition to keeping away the impact of the pandemic on their business practices, many enterprises have proposed relevant measures to protect their employees' job safety and security. Especially for enterprises with high dependence on knowledge resources, employees' innovation and knowledge sharing play a vital role. In the context of global economic austerity, how to put forward the corresponding plan of knowledge sharing intention to improve the knowledge sharing behavior of employees for enterprises is worth discussing. Mainland China and Malaysia have different quarantine policies and similar industrial structures. This study examines the awareness of Mainland China vs. Malaysian employees, and evaluates the relationship among self-efficacy, job security, market orientation, knowledge sharing intention, and knowledge sharing behavior from the theory of planned behavior. In this study, a total of 627 Mainland China and 434 Malaysian participants were collected to compare both groups in the development of employees' knowledge sharing behavior. In this study, a variance-based partial least squares structural equation modeling (PLS-SEM) was performed to test the proposed hypothesis and conduct comparative analysis. The results in both the samples show that self-efficacy, job security, and market orientation have positive and significant effects on knowledge sharing intention; self-efficacy has positive and significant effects on job security; knowledge sharing intention has positive and significant effects on knowledge sharing behavior. Moreover, there are several significant differences between Mainland China and Malaysia in the examinations of path comparisons.
Malaria remains a global health burden with Plasmodium falciparum accounting for the highest mortality and morbidity. Malaria in pregnancy can lead to the development of placental malaria, where P. falciparum-infected erythrocytes adhere to placental receptors, triggering placental inflammation and subsequent damage, causing harm to both mother and her infant. Histopathological studies of P. falciparum-infected placentas revealed various placental abnormalities such as excessive perivillous fibrinoid deposits, breakdown of syncytiotrophoblast integrity, trophoblast basal lamina thickening, increased syncytial knotting, and accumulation of mononuclear immune cells within intervillous spaces. These events in turn, are likely to impair placental development and function, ultimately causing placental insufficiency, intrauterine growth restriction, preterm delivery and low birth weight. Hence, a better understanding of the mechanisms behind placental alterations and damage during placental malaria is needed for the design of effective interventions. In this review, using evidence from human studies and murine models, an integrated view on the potential mechanisms underlying placental pathologies in malaria in pregnancy is provided. The molecular, immunological and metabolic changes in infected placentas that reflect their responses to the parasitic infection and injury are discussed. Finally, potential models that can be used by researchers to improve our understanding on the pathogenesis of malaria in pregnancy and placental pathologies are presented.
A global gold standard framework for primary immunodeficiency (PID) care, structured around six principles, was published in 2014. To measure the implementation status of these principles IPOPI developed the PID Life Index in 2020, an interactive tool aggregating national PID data. This development was combined with a revision of the principles to consider advances in the field of health and science as well as political developments since 2014. The revision resulted in the following six principles: PID diagnosis, treatments, universal health coverage, specialised centres, national patient organisations and registries for PIDs. A questionnaire corresponding to these principles was sent out to IPOPI's national member organisations and to countries in which IPOPI had medical contacts, and data was gathered from 60 countries. The data demonstrates that, regardless of global scientific progress on PIDs with a growing number of diagnostic tools and better treatment options becoming available, the accessibility and affordability of these remains uneven throughout the world. It is not only visible between regions, but also between countries within the same region. One of the most urgent needs is medical education. In countries without immunologists, patients with PID suffer the risk of remaining undiagnosed or misdiagnosed, resulting in health implications or even death. Many countries also lack the infrastructure needed to carry out more advanced diagnostic tests and perform treatments such as hematopoietic stem cell transplantation or gene therapy. The incapacity to secure appropriate diagnosis and treatments affects the PID environment negatively in these countries. Availability and affordability also remain key issues, as diagnosis and treatments require coverage/reimbursement to ensure that patients with PID can access them in practice, not only in theory. This is still not the case in many countries of the world according to the PID Life Index. Although some countries do perform better than others, to date no country has fully implemented the PID principles of care, confirming the long way ahead to ensure an optimal environment for patients with PID in every country.
MeSH terms: Combined Modality Therapy; Delivery of Health Care/methods; Delivery of Health Care/organization & administration; Delivery of Health Care/statistics & numerical data*; Disease Susceptibility; Humans; Infant, Newborn; Insurance, Health; Mass Screening; Population Surveillance; Primary Health Care/statistics & numerical data; Registries; Global Health; Neonatal Screening; Insurance Coverage; Disease Management; Standard of Care
Background: Exposure to genotoxic stress such as radiation is an important public health issue affecting a large population. The necessity of analyzing cytogenetic effects of such exposure is related to the need to estimate the associated risk. Cytogenetic biological dosimetry is based on the relationship between the absorbed dose and the frequency of scored chromosomal aberrations. The influence of confounding factors on radiation response is a topical issue. The role of ethnicity is unclear. Here, we compared the dose-response curves obtained after irradiation of circulating lymphocytes from healthy donors of African and European ancestry. Materials and Methods: Blood samples from six Africans living in Africa, five Africans living in Europe, and five Caucasians living in Europe were exposed to various doses (0-4 Gy) of X-rays at a dose-rate of 0.1 Gy/min using an X-RAD320 irradiator. A validated cohort composed of 14 healthy Africans living in three African countries was included and blood samples were irradiated using the same protocols. Blood lymphocytes were cultured for 48 h and chromosomal aberrations scored during the first mitosis by telomere and centromere staining. The distribution of dicentric chromosomes was determined and the Kruskal-Wallis test was used to compare the dose-response curves of the two populations. Results: No spontaneous dicentric chromosomes were detected in African donors, thus establishing a very low background of unstable chromosomal aberrations relative to the European population. There was a significant difference in the dose response curves between native African and European donors. At 4 Gy, African donors showed a significantly lower frequency of dicentric chromosomes (p = 8.65 10-17), centric rings (p = 4.0310-14), and resulting double-strand-breaks (DSB) (p = 1.32 10-18) than European donors. In addition, a significant difference was found between African donors living in Europe and Africans living in Africa. Conclusion: This is the first study to demonstrate the important role of ethnic and environmental factors that may epigenetically influence the response to irradiation. It will be necessary to establish country-of-origen-specific dose response curves to practice precise and adequate biological dosimetry. This work opens new perspective for the comparison of treatments based on genotoxic agents, such as irradiation.
The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearables and the ever-decreasing cost of sensor-based technology. The cost of related healthcare will rise as the global population of elderly people grows in parallel with an overall life expectancy that demands affordable healthcare services, solutions, and developments. IoMT may bring revolution in the medical sciences in terms of the quality of healthcare of elderly people while entangled with machine learning (ML) algorithms. The effectiveness of the smart healthcare (SHC) model to monitor elderly people was observed by performing tests on IoMT datasets. For evaluation, the precision, recall, fscore, accuracy, and ROC values are computed. The authors also compare the results of the SHC model with different conventional popular ML techniques, e.g., support vector machine (SVM), K-nearest neighbor (KNN), and decision tree (DT), to analyze the effectiveness of the result.
The high dimensionality of software metric features has long been noted as a data quality problem that affects the performance of software defect prediction (SDP) models. This drawback makes it necessary to apply feature selection (FS) algorithm(s) in SDP processes. FS approaches can be categorized into three types, namely, filter FS (FFS), wrapper FS (WFS), and hybrid FS (HFS). HFS has been established as superior because it combines the strength of both FFS and WFS methods. However, selecting the most appropriate FFS (filter rank selection problem) for HFS is a challenge because the performance of FFS methods depends on the choice of datasets and classifiers. In addition, the local optima stagnation and high computational costs of WFS due to large search spaces are inherited by the HFS method. Therefore, as a solution, this study proposes a novel rank aggregation-based hybrid multifilter wrapper feature selection (RAHMFWFS) method for the selection of relevant and irredundant features from software defect datasets. The proposed RAHMFWFS is divided into two stepwise stages. The first stage involves a rank aggregation-based multifilter feature selection (RMFFS) method that addresses the filter rank selection problem by aggregating individual rank lists from multiple filter methods, using a novel rank aggregation method to generate a single, robust, and non-disjoint rank list. In the second stage, the aggregated ranked features are further preprocessed by an enhanced wrapper feature selection (EWFS) method based on a dynamic reranking strategy that is used to guide the feature subset selection process of the HFS method. This, in turn, reduces the number of evaluation cycles while amplifying or maintaining its prediction performance. The feasibility of the proposed RAHMFWFS was demonstrated on benchmarked software defect datasets with Naïve Bayes and Decision Tree classifiers, based on accuracy, the area under the curve (AUC), and F-measure values. The experimental results showed the effectiveness of RAHMFWFS in addressing filter rank selection and local optima stagnation problems in HFS, as well as the ability to select optimal features from SDP datasets while maintaining or enhancing the performance of SDP models. To conclude, the proposed RAHMFWFS achieved good performance by improving the prediction performances of SDP models across the selected datasets, compared to existing state-of-the-arts HFS methods.
Background: A recommender system captures the user preferences and behaviour to provide a relevant recommendation to the user. In a hybrid model-based recommender system, it requires a pre-trained data model to generate recommendations for a user. Ontology helps to represent the semantic information and relationships to model the expressivity and linkage among the data. Methods: We enhanced the matrix factorization model accuracy by utilizing ontology to enrich the information of the user-item matrix by integrating the item-based and user-based collaborative filtering techniques. In particular, the combination of enriched data, which consists of semantic similarity together with rating pattern, will help to reduce the cold start problem in the model-based recommender system. When the new user or item first coming into the system, we have the user demographic or item profile that linked to our ontology. Thus, semantic similarity can be calculated during the item-based and user-based collaborating filtering process. The item-based and user-based filtering process are used to predict the unknown rating of the original matrix. Results: Experimental evaluations have been carried out on the MovieLens 100k dataset to demonstrate the accuracy rate of our proposed approach as compared to the baseline method using (i) Singular Value Decomposition (SVD) and (ii) combination of item-based collaborative filtering technique with SVD. Experimental results demonstrated that our proposed method has reduced the data sparsity from 0.9542% to 0.8435%. In addition, it also indicated that our proposed method has achieved better accuracy with Root Mean Square Error (RMSE) of 0.9298, as compared to the baseline method (RMSE: 0.9642) and the existing method (RMSE: 0.9492). Conclusions: Our proposed method enhanced the dataset information by integrating user-based and item-based collaborative filtering techniques. The experiment results shows that our system has reduced the data sparsity and has better accuracy as compared to baseline method and existing method.
Background: Studies have revealed an increase in discrimination, neglect, and abuse among the older adult population during this period. This study assessed the validity and reliability of the Persian version of the ageism survey instrument tested on a sample of the Iranian older adult population during coronavirus disease (COVID-19) pandemic. An important move in counteracting ageism is to classify the ageism scale comprehensively by employing adequate psychometrics. Methods: The Persian version of the ageism scale was developed using a two-step procedure. The first step involved translating and revising the original scale to develop a Persian version of the ageism scale. The second step involved assessing the psychometric features of the newly adapted scale using construct validity through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) and thereafter assessing the reliability through the average inter-item correlation (AIC), Cronbach's alpha. The sample consisted of 400 older adults (age 65 and older), who were recruited through online data collection, with samples for EFA and CFA randomly selected from the total samples. Results: The Persian version of the ageism survey has three factors: age-related deprivation with five items, dignity with three items, and employment with three items; all of which explained 57.02% of the total variance. The outcome of the EFA was verified by the CFA, with internal consistency reliability being excellent (Cronbach's alpha was 0.725, 0.698, and 0.708 for the three factors). Conclusion: This study specifically offers a restructured three factors Persian version of the ageism survey for Iranian older adults with acceptable construct validity and reliability.
Cardiothoracic intensive care unit (CICU) nurses have shared the role and responsibility for ventilator-weaning to expedite decision-making in patient care. However, the actions taken are based on individual's unstructured training experience as there is no clinical practice guideline (CPG) for nurses in Malaysia. Hence, this study aims to design a CPG for the process of weaning from mechanical ventilation (MV) for a structured nursing training in a CICU at the National Heart Institute (Institut Jantung Negara, IJN) Malaysia. The Fuzzy Delphi Method (FDM) was employed to seek consensus among a panel of 30 experts in cardiac clinical practice on the guidelines. First, five experts were interviewed and their responses were transcribed and analyzed to develop the items for a FDM questionnaire. The questionnaire, comprising of 73 items, was distributed to the panel and their responses were analyzed for consensus on the design of the CPG. The findings suggested that the requirements expected for the nurses include: (a) the ability to interpret arterial blood gases, (b) knowledge and skills on the basics of mechanical ventilation, and (c) having a minimum 1-year working experience in the ICU. On the other hand, the CPG should mainly focus on developing an ability to identify criteria of patient eligible for weaning from MV. The learning content should focus on: (a) developing the understanding and reasoning for weaning and extubating and (b) technique/algorithm for extubating and weaning. Also, the experts agreed that the log book/competency book should be used for evaluation of the program. The CPG for structured nursing training at IJN in the context of the study is important for developing the professionalism of CICU nurses in IJN and could be used for training nurses in other CICUs, so that decision for ventilator-weaning from postcardiac surgery could be expedited.
MeSH terms: Humans; Practice Guidelines as Topic; Nurse's Role*
The advancement of technology in medical equipment has significantly improved healthcare services. However, failures in upkeeping reliability, availability, and safety affect the healthcare services quality and significant impact can be observed in operations' expenses. The effective and comprehensive medical equipment assessment and monitoring throughout the maintenance phase of the asset life cycle can enhance the equipment reliability, availability, and safety. The study aims to develop the prioritisation assessment and predictive systems that measure the priority of medical equipment's preventive maintenance, corrective maintenance, and replacement programmes. The proposed predictive model is constructed by analysing features of 13,352 medical equipment used in public healthcare clinics in Malaysia. The proposed system comprises three stages: prioritisation analysis, model training, and predictive model development. In this study, we proposed 16 combinations of novel features to be used for prioritisation assessment and prediction of preventive maintenance, corrective maintenance, and replacement programme. The modified k-Means algorithm is proposed during the prioritisation analysis to automatically distinguish raw data into three main clusters of prioritisation assessment. Subsequently, these clusters are fed into and tested with six machine learning algorithms for the predictive prioritisation system. The best predictive models for medical equipment's preventive maintenance, corrective maintenance, and replacement programmes are selected among the tested machine learning algorithms. Findings indicate that the Support Vector Machine performs the best in preventive maintenance and replacement programme prioritisation predictive systems with the highest accuracy of 99.42 and 99.80%, respectively. Meanwhile, K-Nearest Neighbour yielded the highest accuracy in corrective maintenance prioritisation predictive systems with 98.93%. Based on the promising results, clinical engineers and healthcare providers can widely adopt the proposed prioritisation assessment and predictive systems in managing expenses, reporting, scheduling, materials, and workforce.
Focal adhesions (FAs) are specialized structures that enable cells to sense their extracellular matrix rigidity and transmit these signals to the interior of the cells, bringing about actin cytoskeleton reorganization, FA maturation, and cell migration. It is known that cells migrate towards regions of higher substrate rigidity, a phenomenon known as durotaxis. However, the underlying molecular mechanism of durotaxis and how different proteins in the FA are involved remain unclear. Zyxin is a component of the FA that has been implicated in connecting the actin cytoskeleton to the FA. We have found that knocking down zyxin impaired NIH3T3 fibroblast's ability to sense and respond to changes in extracellular matrix in terms of their FA sizes, cell traction stress magnitudes and F-actin organization. Cell migration speed of zyxin knockdown fibroblasts was also independent of the underlying substrate rigidity, unlike wild type fibroblasts which migrated fastest at an intermediate substrate rigidity of 14 kPa. Wild type fibroblasts exhibited durotaxis by migrating toward regions of increasing substrate rigidity on polyacrylamide gels with substrate rigidity gradient, while zyxin knockdown fibroblasts did not exhibit durotaxis. Therefore, we propose zyxin as an essential protein that is required for rigidity sensing and durotaxis through modulating FA sizes, cell traction stress and F-actin organization.
Background: Necrotizing fasciitis (NF) is a life-threatening infection of the skin and soft tissue that spreads quickly and requires immediate surgery and medical treatment. Amputation or radical debridement of necrotic tissue is generally always required. The risks and benefits of both the surgical options are weighed before deciding whether to amputate or debride. This study set forth to create an easy-to-use risk scoring system for predicting the risk scoring system for amputation in patients with NF (ANF). Methods: This retrospective study included 1,506 patients diagnosed with surgically confirmed NF at three general hospitals in Thailand from January 2009 to December 2012. All diagnoses were made by surgeons who strictly observed the guidelines for skin and soft tissue infections produced by the Infectious Diseases Society of America. Patients were randomly allocated to either the derivation (n = 1,193) or validation (n = 313) cohort. Clinical risk factors assessed at the time of recruitment were used to create the risk score, which was then developed using logistic regression. The regression coefficients were converted into item scores, and the total score was calculated. Results: The following four clinical predictors were used to create the model: female gender, diabetes mellitus, wound appearance stage 3 (skin necrosis and gangrene), and creatinine ≥1.6 mg/dL. Using the area under the receiver operating characteristic curve (AuROC), the ANF system showed moderate power (78.68%) to predict amputation in patients with NF with excellent calibration (Hosmer-Lemeshow χ2 = 2.59; p = 0.8586). The positive likelihood ratio of amputation in low-risk (score ≤ 4) and high-risk (score ≥ 7) patients was 2.17 (95%CI: 1.66-2.82) and 6.18 (95%CI: 4.08-9.36), respectively. The ANF system showed good performance (AuROC 76.82%) when applied in the validation cohort. Conclusion: The developed ANF risk scoring system, which includes four easy to obtain predictors, provides physicians with prediction indices for amputation in patients with NF. This model will assist clinicians with surgical decision-making in this time-sensitive clinical setting.
Background and Aims: This study aimed to examine the associations between the total protein intake as well as types and sources of proteins with the gestational diabetes mellitus (GDM) risk. Method and Results: This was a prospective cohort study of the pregnant women in Malaysia. In this study, the total, animal, and plant protein intakes were assessed using a semi-quantitative food frequency questionnaire. Of the 452 women, 48 (10.62%) were diagnosed with GDM. From pre-pregnancy to second trimester, most of the women had 10-20% of energy intake from protein (88.9-90.3%) and ≥75% of recommended protein intake (74.6-86.5%). The women in the highest tertile (T3) of total animal protein intake [adjusted odds ratio (AOR) = 2.76, 95% CI = 1.27-6.04] and red meat protein (AOR = 2.69, 95% CI = 1.27-5.70), specifically in the second trimester, had significantly higher GDM risk compared with the women in the middle tertile of intake (T2). Interestingly, the women in the T3 of egg protein in the second trimester were significantly at lower GDM risk (AOR = 0.43, 95% CI = 0.18-0.91) compared with those in T2. Conclusion: The highest tertile of animal protein (≥42.15 g/day) intake, particularly red meat protein in the second trimester was positively associated with the GDM risk, whereas the highest tertile of egg protein was inversely associated with the GDM risk. Protein intake before or during early pregnancy was not associated with the GDM risk. These findings underscore the importance of sources and types of protein intake, particularly after the first trimester of pregnancy, in relation to GDM risk.
Vitamin K antagonist such as warfarin reduces the risk of stroke in atrial fibrillation (AF) patients. Since warfarin has a narrow therapeutic index, its administration needs to be regularly monitored to avoid any adverse clinical outcomes such as stroke and bleeding. The quality of anticoagulation control with warfarin therapy can be measured by using time in therapeutic range (TTR). This review focuses on the prevalence of AF, quality of anticoagulation control (TTR) and adverse clinical outcome in AF patients within different ethnic groups receiving warfarin therapy for stroke prevention. A literature search was conducted in Embase and PubMed using keywords of "prevalence," "atrial fibrillation," "stroke prevention," "oral anticoagulants," "warfarin," "ethnicities," "race" "time in therapeutic range," "adverse clinical outcome," "stroke, bleeding." Articles published by 1st February 2020 were included. Forty-one studies were included in the final review consisting of AF prevalence (n = 14 studies), time in therapeutic range (n = 18 studies), adverse clinical outcome (n = 9 studies) within different ethnic groups. Findings indicate that higher prevalence of AF but better anticoagulation control among the Whites as compared to other ethnicities. Of note, non-whites had higher risk of strokes and bleeding outcomes while on warfarin therapy. Addressing disparities in prevention and healthcare resource allocation could potentially improve AF-related outcomes in minorities.
Critically Endangered orangutans are translocated in several situations: reintroduced into historic range where no wild populations exist, released to reinforce existing wild populations, and wild-to-wild translocated to remove individuals from potentially risky situations. Translocated orangutans exposed to human diseases, including Coronavirus Disease 2019 (COVID-19), pose risks to wild and previously released conspecifics. Wildlife disease risk experts recommended halting great ape translocations during the COVID-19 pandemic to minimize risk of disease transmission to wild populations. We collected data on orangutan releases and associated disease risk management in Indonesia during the COVID-19 pandemic, and developed a problem description for orangutan disease and conservation risks. We identified that at least 15 rehabilitated ex-captive and 27 wild captured orangutans were released during the study period. Identified disease risks included several wild-to-wild translocated orangutans in direct contact or proximity to humans without protective equipment, and formerly captive rehabilitated orangutans that have had long periods of contact and potential exposure to human diseases. While translocation practitioners typically employ mitigation measures to decrease disease transmission likelihood, these measures cannot eliminate all risk, and are not consistently applied. COVID-19 and other diseases of human origin can be transmitted to orangutans, which could have catastrophic impacts on wild orangutans, other susceptible fauna, and humans should disease transmission occur. We recommend stakeholders conduct a Disease Risk Analysis for orangutan translocation, and improve pathogen surveillance and mitigation measures to decrease the likelihood of potential outbreaks. We also suggest refocusing conservation efforts on alternatives to wild-to-wild translocation including mitigating human-orangutan interactions, enforcing laws and protecting orangutan habitats to conserve orangutans in situ.
Messastrum gracile SE-MC4 is a non-model microalga exhibiting superior oil-accumulating abilities. However, biomass production in M. gracile SE-MC4 is limited due to low cell proliferation especially after prolonged cultivation under oil-inducing culture conditions. Present data consist of next generation RNA sequencing data of M. gracile SE-MC4 under exponential and stationary growth stages. RNA of six samples were extracted and sequenced with insert size of 100 bp paired-end strategy using BGISEQ-500 platform to produce a total of 59.64 Gb data with 314 million reads. Sequences were filtered and de novo assembled to form 53,307 number of gene sequences. Sequencing data were deposited in National Center for Biotechnology Information (NCBI) and can be accessed via BioProject ID PRJNA552165. This information can be used to enhance biomass production in M. gracile SE-MC4 and other microalgae aimed towards improving biodiesel development.