Explore the vast range of titles available.

Glycerol is an attractive carbon source for biofuel production since it is cheap and abundant due to the increasing demand for renewable and clean energy sources, which includes production of biodiesel. This research aims to enhance hydrogen production by Escherichia coli from glycerol by manipulating its metabolic pathways via targeted deletions. Since our past strain, which had been engineered for producing hydrogen from glucose, was not suitable for producing hydrogen from glycerol, we rescreened 14 genes related to hydrogen production and glycerol metabolism. We found that 10 single knockouts are beneficial for enhanced hydrogen production from glycerol, namely, frdC (encoding for furmarate reductase), ldhA (lactate dehydrogenase), fdnG (formate dehydrogenase), ppc (phosphoenolpyruvate carboxylase), narG (nitrate reductase), focA (formate transporter), hyaB (the large subunit of hydrogenase 1), aceE (pyruvate dehydrogenase), mgsA (methylglyoxal synthase), and hycA (a regulator of the transcriptional regulator FhlA). On that basis, we created multiple knockout strains via successive P1 transductions. Simultaneous knockouts of frdC, ldhA, fdnG, ppc, narG, mgsA, and hycA created the best strain that produced 5-fold higher hydrogen and had a 5-fold higher hydrogen yield than the parent strain. The engineered strain also reached the theoretical maximum yield of 1 mol H₂/mol glycerol after 48 h. Under low partial pressure fermentation, the strain grew over 2-fold faster, indicating faster utilization of glycerol and production of hydrogen. By combining metabolic engineering and low partial pressure fermentation, hydrogen production from glycerol was enhanced significantly.

Recently, sustainable development has become a global requirement. Every country strives to achieve this essential goal, and this attracts the attention of researchers and policymakers. This study investigates the impact of green finance, eco-innovation, and creativity on the sustainable development goals in ASEAN countries. Using CUP-FM and CUP-BC techniques, the study examines the association between variables, and finds that green finance (such as green credit), renewable energy production, eco-innovation, and creativity, have positive associations with sustainable development goals. The control variable, economic growth, has a negative association with sustainable development goals. Based on the evidence, the ASEAN region must increase the quantity of green bonds as a part of green finance. This financial measure would guarantee adequate returns for private investors.

Escherichia coli has been a robust host strain for much biological research, in particular, research in metabolic engineering, protein engineering, and heterologous gene expression. In this mini review, to understand bacterial hydrogen production by E. coli, the effect of glucose and glycerol metabolism on hydrogen production is compared, and the current approaches to enhance hydrogen production from glycerol as a substrate are reviewed. In addition, the argument from past to present on the functions of E. coli hydrogenases, hydrogenase 1, hydrogenase 2, hydrogenase 3, and hydrogenase 4 is summarized. Furthermore, based on the literature that the E. coli formate-hydrogen lyase is essential for bacterial hydrogen production via recombinant hydrogenases, research achievements from the past regarding heterologous production of hydrogenase are rethought.

Breast self-examination (BSE) is a simple, feasible, and suitable method for breast cancer screening in low–middle setting countries. The aim of this study was to assess the knowledge and practice of BSE among female textile workers in Vietnam. A cross-sectional study was conducted among 1036 female workers, aged 43.9 ± 3.1 years old, who were working in 4 textile enterprises in Hanoi and Ho Chi Minh City, in 2016. Overall, 22.7% of participants showed sufficient knowledge on BSE; 15.2% performed monthly BSE; and 7.7% completely performed all 5 steps of BSE. The prevalence of insufficient BSE knowledge was higher among participants with low level of education (odds ratio [OR]: 1.71; 95% confidence interval [CI]: 1.22-2.39, below vs above secondary school), and those whose husbands were farmers or workers (OR: 1.76; 95% CI: 1.27-2.45, compared to other sectors). This prevalence was, however, negatively associated with receiving information on BSE (OR: 0.16; 95% CI: 0.11-0.23, yes vs no). The prevalence of insufficient BSE practice was also higher among females with husbands who were farmers or workers (OR: 1.67; 95% CI: 1.15-2.43, compared to other sectors). In contrast, it was much lower among participants who had history of breast-related diseases (OR: 0.46; 95% CI: 0.24-0.88, yes vs no), received BSE information (OR: 0.13; 95% CI: 0.08-0.19, yes vs no), and had sufficient overall BSE knowledge (OR: 0.09; 95% CI: 0.06-0.13, yes vs no), compared to those who did not. There was a low prevalence of sufficient BSE knowledge (22.7%) and practice (15.8%) among female textile workers in Hanoi and Ho Chi Minh City. Low level of education and not being provided BSE information were associated with insufficient BSE knowledge and practice among Vietnamese female textile workers. Health education programs are essential to encourage and improve women’s knowledge and practice of BSE.

The colon is the largest compartment of the immune system, with innate immune cells exposed to antigens in the environment. However, the mechanisms by which the innate immune system is instigated are poorly defined in colorectal cancer (CRC). Here, a population of CD16+ neutrophils that specifically accumulate in CRC tumor tissues by imaging mass cytometry (IMC), immune fluorescence, and flow cytometry, which demonstrated pro‐tumor activity by disturbing natural killer (NK) cells are identified. It is found that these CD16+ neutrophils possess abnormal cholesterol accumulation due to activation of the CD16/TAK1/NF‐κB axis, which upregulates scavenger receptors for cholesterol intake including CD36 and LRP1. Consequently, these region‐specific CD16+ neutrophils not only competitively inhibit cholesterol intake of NK cells, which interrupts NK lipid raft formation and blocks their antitumor signaling but also release neutrophil extracellular traps (NETs) to induce the death of NK cells. Furthermore, CD16‐knockout reverses the pro‐tumor activity of neutrophils and restored NK cell cytotoxicity. Collectively, the findings suggest that CRC region‐specific CD16+ neutrophils can be a diagnostic marker and potential therapeutic target for CRC. A population of CD16+ neutrophils that specifically accumulate in colorectal cancer tumor tissues which demonstrates pro‐tumor activity by disturbing nature killer (NK) cells is identified. It is found that these CD16+ neutrophils not only competitively inhibit cholesterol intake of NK cells, but also release NETs to induce death of NK cells. CD16‐knockout reverses the pro‐tumor activity of neutrophils and restores NK cell cytotoxicity.

The Chief Executive Officer (CEO) is pivotal in firm governance and is tasked with policy implementation and maximizing shareholder benefit. However, predicting CEO behaviour remains challenging, especially when considering CEO power (CEOP). Hence, this study explores the link between CEOP and firm risk-taking (FRT) in selected firms on the stock market in Vietnam from 2010 to 2020. Utilizing the Entropy weight methodology, a CEOP index combines structural, ownership, and expert power indicators. The SYS-GMM approach mitigates potential endogeneity issues, revealing a positive correlation between CEOP and FRT. Interestingly, CEO risk aversion increases in state-owned firms’ participants, suggesting heightened supervision. Moreover, each characteristic of the CEOP index uniquely influences FRT. The findings offer theoretical and practical insights for enhancing governance and supervision mechanisms to optimize stakeholder benefits.In business, avoiding all risks is impractical, and risk-taking endeavours can present growth opportunities. However, uncertainties from risks can impact financial performance, requiring corporations to demonstrate effective risk management. Decision-making and oversight of organizational activities are decided by the Chief Executive Officer (CEO). Hence, this study explores the interaction between CEO power and firm risk-taking in the context of Vietnam. Powerful CEOs tend to gravitate towards risks, but effective governance mechanisms and board independence can balance this tendency. The study recognizes the influential role of CEO power in shaping risk-taking behaviours and emphasizes the positive impact of state ownership. Balancing CEO empowerment with organizational supervision is crucial, and solutions include comprehensive risk assessments and clear operating frameworks. However, the study acknowledges limitations and recommends guidelines for a more comprehensive analysis in future research.

Coronary artery disease (CAD) is one of the most common pathological conditions and the major global cause of death. Myocardial perfusion imaging (MPI) using single-photon emission computed tomography (SPECT) is a non-invasive method and plays an essential role in diagnosing CAD. However, there is currently a shortage of doctors who can diagnose using SPECT-MPI in developing countries, especially Vietnam. Research on deploying machine learning and deep learning in supporting CAD diagnosis has been noticed for a long time. However, these methods require a large dataset and are therefore time-consuming and labor-intensive. This study aims to develop a cost-effective and high-performance CAD classification model to support doctors in these countries. In this paper, we propose a transfer learning framework for a multi-stage training process with different learning rates. The process consists of two training stages: a warming up stage in which all layers of a pre-trained model (on ImageNet dataset) are frozen; and a fine-tuning stage in which a small amount of the top layers are unfrozen and then retrained with a lower learning rate. The dataset for this study consists of the polar maps from 218 patients. Various popular CNN-based pre-trained models have been investigated, and ResNet152V2-based model has obtained the highest performances with an accuracy of 95.5%, area under the receiver operating characteristic curve (AUC) score 0.932, sensitivity 94.4%, precision 96.4%, and F1-score 95.2%. These performances are competitive or even better than all state-of-the-art approaches in terms of classification accuracy and sensitivity. We also apply the class activation mapping technique to help explain the model’s predictions and increase the model’s reliability, proving capable of assisting the SPECT image readers in the CAD diagnosis.

Federated Learning is a novel decentralized methodology that enables multiple clients to collaboratively train a global model while preserving the privacy of their local data. Although federated learning enhances data privacy, it faces challenges related to data quality and client behavior. A fundamental issue is the presence of noisy labels in certain clients, which damages the global model's performance. To address this problem, this paper introduces a Federated learning framework with Noisy client Detection and robust Aggregation, FedNDA. In the first stage, FedNDA detects noisy clients by analyzing the distribution of their local losses. A noisy client exhibits a loss distribution distinct from that of clean clients. To handle class imbalance issue in local data, we utilize per-class losses instead of the total loss. We then assign each client a noisiness score, calculated as the Earth Mover’s Distance between the per-class loss distribution of the client and the average distribution of all clean clients. This noisiness metric is more sensitive for detecting noisy clients compared to conventional metrics such as Euclidean distance or L1 norm. The noisiness score is subsequently transfered to and used in the server-side aggregation function to prioritize clean clients while reducing the influence of noisy clients. Experimental results demonstrate that FedNDA outperforms FedAvg and FedNoRo by 4.68% and 3.6% on the CIFAR-10 dataset, and by 10.65% and 0.48% on the ICH dataset, respectively, in a high noisy setting.

Glycerol is an inexpensive and abundant source for biofuel production on a large scale. Escherichia coli is a robust bacterium for producing hydrogen; however, its hydrogen productivity from glycerol is low. In this study, we conducted random transposon mutagenesis to identify uncharacterized genes whose inactivation is beneficial for hydrogen production from glycerol. Through screening, four mutant strains were found that are able to have from 1.3- to 1.6-fold higher hydrogen productivity (μmol H₂/mg protein) than that of their parent strain (p < 0.05). These mutations were identified as aroM, gatZ, ycgR, and yfgI. The hydrogen yield (mol H₂/mol glycerol consumed) of the aroM, gatZ, ycgR, and yfgI strains was 1.7-, 1.4-, 2.4-, and 2.1-fold higher than that of their parent strain, respectively. Moreover, a single disruption in these genes resulted in a faster cell growth and glycerol consumption under anaerobic conditions. In E. coli, AroM is predicted to be involved in the shikimate pathway, GatZ is tagatose-1,6-bisphosphate aldolase 2 which converts dihydroxyacetone phosphate to 1,6-biphosphate, and YcgR acts as a molecular brake limiting the swimming speed and ATP consumption. So far, the function of YfgI in general and in hydrogen production in particular remains unknown.

Poverty reduction is considered as the top priority of governments and international institutions. At the same time income inequality is a far-reaching concern especially in emerging nations. US former president even labelled income inequality and poverty are the challenges of our times. Theoretically there are different views on the impact of microfinancing and financial inclusion on income inequality and poverty, hence, it is interesting to evaluate these estimations in Vietnamese context from 1986 to 2020. The researchers have applied the Bayesian Auto-regressive Distributed Lags (BARDL) model and exposed that microfinancing, financial inclusion, educational loans increase income equality and reduces poverty. Based on the evidences, the paper implies that government institutions must focus on microfinancing and financial inclusion aspects to facilitate poor and boost prosperity which ultimately brings income equality. First published online 21 November 2023