Tuberculous meningitis is often lethal. Early antituberculosis treatment and adjunctive treatment with glucocorticoids improve survival, but nearly one third of patients with the condition still die. ...We hypothesized that intensified antituberculosis treatment would enhance the killing of intracerebral Mycobacterium tuberculosis organisms and decrease the rate of death among patients.
We performed a randomized, double-blind, placebo-controlled trial involving human immunodeficiency virus (HIV)-infected adults and HIV-uninfected adults with a clinical diagnosis of tuberculous meningitis who were admitted to one of two Vietnamese hospitals. We compared a standard, 9-month antituberculosis regimen (which included 10 mg of rifampin per kilogram of body weight per day) with an intensified regimen that included higher-dose rifampin (15 mg per kilogram per day) and levofloxacin (20 mg per kilogram per day) for the first 8 weeks of treatment. The primary outcome was death by 9 months after randomization.
A total of 817 patients (349 of whom were HIV-infected) were enrolled; 409 were randomly assigned to receive the standard regimen, and 408 were assigned to receive intensified treatment. During the 9 months of follow-up, 113 patients in the intensified-treatment group and 114 patients in the standard-treatment group died (hazard ratio, 0.94; 95% confidence interval, 0.73 to 1.22; P=0.66). There was no evidence of a significant differential effect of intensified treatment in the overall population or in any of the subgroups, with the possible exception of patients infected with isoniazid-resistant M. tuberculosis. There were also no significant differences in secondary outcomes between the treatment groups. The overall number of adverse events leading to treatment interruption did not differ significantly between the treatment groups (64 events in the standard-treatment group and 95 events in the intensified-treatment group, P=0.08).
Intensified antituberculosis treatment was not associated with a higher rate of survival among patients with tuberculous meningitis than standard treatment. (Funded by the Wellcome Trust and the Li Ka Shing Foundation; Current Controlled Trials number, ISRCTN61649292.).
The coronavirus disease 2019 (COVID-19) epidemic affects people's health and health-related quality of life (HRQoL), especially in those who have suspected COVID-19 symptoms (S-COVID-19-S). We ...examined the effect of modifications of health literacy (HL) on depression and HRQoL. A cross-sectional study was conducted from 14 February to 2 March 2020. 3947 participants were recruited from outpatient departments of nine hospitals and health centers across Vietnam. The interviews were conducted using printed questionnaires including participants' characteristics, clinical parameters, health behaviors, HL, depression, and HRQoL. People with S-COVID-19-S had a higher depression likelihood (OR, 2.88;
< 0.001), lower HRQoL-score (B, -7.92;
< 0.001). In comparison to people without S-COVID-19-S and low HL, those with S-COVID-19-S and low HL had 9.70 times higher depression likelihood (
< 0.001), 20.62 lower HRQoL-score (
< 0.001), for the people without S-COVID-19-S, 1 score increment of HL resulted in 5% lower depression likelihood (
< 0.001) and 0.45 higher HRQoL-score (
< 0.001), while for those people with S-COVID-19-S, 1 score increment of HL resulted in a 4% lower depression likelihood (
= 0.004) and 0.43 higher HRQoL-score (
< 0.001). People with S-COVID-19-S had a higher depression likelihood and lower HRQoL than those without. HL shows a protective effect on depression and HRQoL during the epidemic.
In response to the rapid spread of coronavirus disease-2019 (COVID-19) within and across countries and the need to protect public health, governments worldwide introduced unprecedented measures such ...as restricted road and air travel and reduced human mobility in 2020. The curtailment of personal travel and economic activity provided a unique opportunity for researchers to assess the interplay between anthropogenic emissions of primary air pollutants, their physical transport, chemical transformation, ultimate fate and potential health impacts. In general, reductions in the atmospheric levels of outdoor air pollutants such as particulate matter (PM), nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and volatile organic compounds (VOCs) were observed in many countries during the lockdowns. However, the levels of ozone (O3), a secondary air pollutant linked to asthma and respiratory ailments, and secondary PM were frequently reported to remain unchanged or even increase. An increase in O3 can enhance the formation of secondary PM2.5, especially secondary organic aerosols, through the atmospheric oxidation of VOCs. Given that the gaseous precursors of O3 (VOCs and NOx) are also involved in the formation of secondary PM2.5, an integrated control strategy should focus on reducing the emission of the common precursors for the co-mitigation of PM2.5 and O3 with an emphasis on their complex photochemical interactions. Compared to outdoor air quality, comprehensive investigations of indoor air quality (IAQ) are relatively sparse. People spend more than 80% of their time indoors with exposure to air pollutants of both outdoor and indoor origins. Consequently, an integrated assessment of exposure to air pollutants in both outdoor and indoor microenvironments is needed for effective urban air quality management and for mitigation of health risk. To provide further insights into air quality, we do a critical review of scientific articles, published from January 2020 to December 2020 across the globe. Finally, we discuss policy implications of our review in the context of global air quality improvement.
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•We studied the effects of the implementation of lockdown on air quality.•Reduction in primary air pollutants was observed in most cities during lockdowns.•Secondary PM and O3 increased in some cities under favorable weather conditions.•Exposure to high levels of PM can aggravate the health status of COVID-19 patients.•Indoor air quality assessment merits a serious consideration during lockdowns.
Chloroplast sequences are widely used for phylogenetic analysis due to their high degree of conservation in plants. Whole chloroplast genomes can now be readily obtained for plant species using new ...sequencing methods, giving invaluable data for plant evolution However new annotation methods are required for the efficient analysis of this data to deliver high quality phylogenetic analyses. In this study, the two main tools for chloroplast genome annotation were compared. More consistent detection and annotation of genes were produced with GeSeq when compared to the currently used Dogma. This suggests that the annotation of most of the previously annotated chloroplast genomes should now be updated. GeSeq was applied to species related to coffee, including 16 species of the Coffea and Psilanthus genera to reconstruct the ancestral chloroplast genomes and to evaluate their phylogenetic relationships. Eight genes in the plant chloroplast pan genome (consisting of 92 genes) were always absent in the coffee species analyzed. Notably, the two main cultivated coffee species (i.e. Arabica and Robusta) did not group into the same clade and differ in their pattern of gene evolution. While Arabica coffee (Coffea arabica) belongs to the Coffea genus, Robusta coffee (Coffea canephora) is associated with the Psilanthus genus. A more extensive survey of related species is required to determine if this is a unique attribute of Robusta coffee or a more widespread feature of coffee tree species.
BMI, waist circumference (WC) and waist-to-height ratio (WHtR) can be used for discriminating children and adolescents at risk of CVD. However, consensus on how to use these anthropometric indicators ...is lacking for children and adolescents in Asia. Discrete criteria are promoted internationally, but continuous variables could be used. Data from a survey of 10 949 Vietnamese school-aged children (6-18 years) were used to evaluate the performance of anthropometric indicators to identify elevated blood pressure (BP), dyslipidaemia or at least three cardiovascular risk factors (CVRF). Weight, height, WC and BP were measured using standardised protocols; 1009 participants who had blood lipids were analysed. AUC was used to assess the performance, and the Youden index to identify optimal cut-offs. The prevalence of elevated BP, dyslipidaemia and CVRF was 26·5, 49·3 and 12·2 %, respectively. BMI, WC and WHtR had low capacity to identify elevated BP and dyslipidaemia (AUC range 0·61-0·66) but moderate capacity to identify CVRF (0·72-0·74). Optimal BMIZ cut-offs to identify elevated BP, dyslipidaemia and CVRF were 0·40, 1·01 and 1·1 sd; for WC z-score, they were 0·06, 0·49 and 0·62 sd; for WHtR, optimal cut-offs were close to 0·5. A BMIZ cut-off of 1·0 sd and a WHtR cut-off of 0·5 would, therefore, be useful criteria to identify Vietnamese children who are likely to have CVRF. However, further validation of these criteria in other studies of Asian children and adolescents is needed.
Microbial polysaccharides have been reported to possess remarkable bioactivities. Physarum polycephalum is a species of slime mold for which the microplasmodia are capable of rapid growth and can ...produce a significant amount of cell wall-less biomass. There has been a limited understanding of the polysaccharides produced by microplasmodia of slime molds, including P. polycephalum. Thus, the primary objectives of this research were first to chemically characterize the exopolysaccharides (EPS) and intracellular polysaccharides (IPS) of P. polycephalum microplasmodia and then to evaluate their cytotoxicity against several cancer cell lines.
The yields of the crude EPS (4.43 ± 0.44 g/l) and partially purified (deproteinated) EPS (2.95 ± 0.85 g/l) were comparable (p > 0.05) with the respective crude IPS (3.46 ± 0.36 g/l) and partially purified IPS (2.45 ± 0.36 g/l). The average molecular weight of the EPS and IPS were 14,762 kDa and 1788 kDa. The major monomer of the EPS was galactose (80.22%), while that of the IPS was glucose (84.46%). Both crude and purified IPS samples showed significantly higher cytotoxicity toward Hela cells, especially the purified sample and none of the IPSs inhibited normal cells. Only 38.42 ± 2.84% Hela cells remained viable when treated with the partially purified IPS (1 mg/ml). However, although only 34.76 ± 6.58% MCF-7 cells were viable when exposed to the crude IPS, but the partially purified IPS displayed non-toxicity to MCF-7 cells. This suggested that the cytotoxicity toward MCF-7 would come from some component associated with the crude IPS sample (e.g. proteins, peptides or ion metals) and the purification process would have either completely removed or reduced amount of that component. Cell cycle analysis by flow cytometry suggested that the mechanism of the toxicity of the crude IPS toward MCF-7 and the partially purified IPS toward Hela cells was due to apoptosis.
The EPS and IPS of P. polycephalum microplasmodia had different chemical properties including carbohydrate, protein and total sulfate group contents, monosaccharide composition and molecular weights, which led to different cytotoxicity activities. The crude and partially purified IPSs would be potential materials for further study relating to cancer treatment.
Epileptic seizure is a neurological condition caused by short and unexpectedly occurring electrical disruptions in the brain. It is estimated that roughly 60 million individuals worldwide have had an ...epileptic seizure. Experiencing an epileptic seizure can have serious consequences for the patient. Automatic seizure detection on electroencephalogram (EEG) recordings is essential due to the irregular and unpredictable nature of seizures. By thoroughly analyzing EEG records, neurophysiologists can discover important information and patterns, and proper and timely treatments can be provided for the patients. This research presents a novel machine learning-based approach for detecting epileptic seizures in EEG signals. A public EEG dataset from the University of Bonn was used to validate the approach. Meaningful statistical features were extracted from the original data using discrete wavelet transform analysis, then the relevant features were selected using feature selection based on the binary particle swarm optimizer. This facilitated the reduction of 75% data dimensionality and 47% computational time, which eventually sped up the classification process. After having been selected, relevant features were used to train different machine learning models, then hyperparameter optimization was utilized to further enhance the models' performance. The results achieved up to 98.4% accuracy and showed that the proposed method was very effective and practical in detecting seizure presence in EEG signals. In clinical applications, this method could help relieve the suffering of epilepsy patients and alleviate the workload of neurologists.
More than 32.5 million American adults suffer from osteoarthritis, and current treatments including pain medicines and anti-inflammatory drugs only alleviate symptoms but do not cure the disease. ...Here, we have demonstrated that a biodegradable piezoelectric poly(L-lactic acid) (PLLA) nanofiber scaffold under applied force or joint load could act as a battery-less electrical stimulator to promote chondrogenesis and cartilage regeneration. The PLLA scaffold under applied force or joint load generated a controllable piezoelectric charge, which promoted extracellular protein adsorption, facilitated cell migration or recruitment, induced endogenous TGF-β via calcium signaling pathway, and improved chondrogenesis and cartilage regeneration both in vitro and in vivo. Rabbits with critical-sized osteochondral defects receiving the piezoelectric scaffold and exercise treatment experienced hyaline-cartilage regeneration and completely healed cartilage with abundant chondrocytes and type II collagen after 1 to 2 months of exercise (2 to 3 months after surgery including 1 month of recovery before exercise), whereas rabbits treated with nonpiezoelectric scaffold and exercise treatment had unfilled defect and limited healing. The approach of combining biodegradable piezoelectric tissue scaffolds with controlled mechanical activation (via physical exercise) may therefore be useful for the treatment of osteoarthritis and is potentially applicable to regenerating other injured tissues.
Recent experimental and observational research has suggested that childhood allergic asthma and other conditions may be the result of prenatal exposure to environmental contaminants, such as ...di-(2-ethylhexyl) phthalate (DEHP). In a previous epidemiological study, we found that ancestral exposure (F0 generation) to endocrine disruptors or the common plasticizer DEHP promoted allergic airway inflammation via transgenerational transmission in mice from generation F1 to F4. In the current study, we employed a MethylationEPIC Beadchip microarray to examine global DNA methylation in the human placenta as a function of maternal exposure to DEHP during pregnancy. Interestingly, global DNA hypomethylation was observed in placental DNA following exposure to DEHP at high concentrations. Bioinformatic analysis confirmed that DNA methylation affected genes related to neurological disorders, such as autism and dementia. These results suggest that maternal exposure to DEHP may predispose offspring to neurological diseases. Given the small sample size in this study, the potential role of DNA methylation as a biomarker to assess the risk of these diseases deserves further investigation.
Dengue fever (DF) represents a significant health burden in Vietnam, which is forecast to worsen under climate change. The development of an early-warning system for DF has been selected as a ...prioritised health adaptation measure to climate change in Vietnam.
This study aimed to develop an accurate DF prediction model in Vietnam using a wide range of meteorological factors as inputs to inform public health responses for outbreak prevention in the context of future climate change.
Convolutional neural network (CNN), Transformer, long short-term memory (LSTM), and attention-enhanced LSTM (LSTM-ATT) models were compared with traditional machine learning models on weather-based DF forecasting. Models were developed using lagged DF incidence and meteorological variables (measures of temperature, humidity, rainfall, evaporation, and sunshine hours) as inputs for 20 provinces throughout Vietnam. Data from 1997-2013 were used to train models, which were then evaluated using data from 2014-2016 by Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).
LSTM-ATT displayed the highest performance, scoring average places of 1.60 for RMSE-based ranking and 1.95 for MAE-based ranking. Notably, it was able to forecast DF incidence better than LSTM in 13 or 14 out of 20 provinces for MAE or RMSE, respectively. Moreover, LSTM-ATT was able to accurately predict DF incidence and outbreak months up to 3 months ahead, though performance dropped slightly compared to short-term forecasts. To the best of our knowledge, this is the first time deep learning methods have been employed for the prediction of both long- and short-term DF incidence and outbreaks in Vietnam using unique, rich meteorological features.
This study demonstrates the usefulness of deep learning models for meteorological factor-based DF forecasting. LSTM-ATT should be further explored for mitigation strategies against DF and other climate-sensitive diseases in the coming years.
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