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Apoptosis is an important process that directly affects the response of cancer cells to anticancer drugs. Among different factors involved in this process, the BcL-xL protein plays a critical role in inhibiting apoptosis induced by chemotherapy agents. Henceforth, its downregulation may have a synergistic activity that lowers the necessary dose of anticancer agents. In this study, anti-Bcl-xL siRNA were formulated within an EGFR-targeted nanomedicine with scFv ligands (NM-scFv) and its activity was tested in the non-small cell lung cancer (NSCLC) cell line H460. The obtained NMs-scFv anti-Bcl-xL were suitable for intravenous injection with sizes around 100 nm, a high monodispersity level and good siRNA complexation capacity. The nanocomplex's functionalization with anti-EGFR scFv ligands was shown to allow an active gene delivery into H460 cells and led to approximately 63% of gene silencing at both mRNA and protein levels. The NM-scFv anti-Bcl-xL improved the apoptotic activity of cisplatin and reduced the cisplatin IC50 value in H460 cells by a factor of around three from 0.68 ± 0.12 μM to 2.21 ± 0.18 μM (p 0.05).

The Central Highlands region is considered as the center with the highest biodiversity in Vietnam because it has the majority of national parks such as Yok Don, Chu Yang Sin, Bidoup-Nui Ba, Ta Dung, Chu Mon Ray, and Kon Ka Kinh and nature reserves such as Ngoc Linh, Kon Chu Rang, Ea So, Nam Ka, and Nam Nung with different ecosystems [1]. Of the national parks and nature reserves, Yok Don has the most different ecosystem. Yok Don is the second biggest national park, and it is the only national park that conserves dry deciduous dipterocarp forests in Vietnam [2]. Presently, the decrease in forest area and global warming have led to the continuous reduction in microbial resources in this region. Thus, a dataset of the soil microbiome in this region has been established to explore microbial resources for conservation and further application in sustainable agricultural production in this region [3]; however, to the best of our knowledge, a dataset of water microbiome remains unknown. This work presented a microbiome dataset from surface water samples collected from Serepok River in Yok Don National Park, Vietnam. Metagenomic next-generation sequencing was used to characterize microbial communities in the sample. The raw sequence in this work was uploaded in Fastq format on NCBI, which can be accessed at https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA853090. This metagenome dataset can provide valuable information on surface water microbial communities and their functionality. It can also be used for further studies on the conservation and application of indigenous microbial resources for sustainable crop production in this region.

Abstract Background Developing efficient and successful computational methods to infer potential miRNA-disease associations is urgently needed and is attracting many computer scientists in recent years. The reason is that miRNAs are involved in many important biological processes and it is tremendously expensive and time-consuming to do biological experiments to verify miRNA-disease associations. Methods In this paper, we proposed a new method to infer miRNA-disease associations using collaborative filtering and resource allocation algorithms on a miRNA-disease-lncRNA tripartite graph. It combined the collaborative filtering algorithm in CFNBC model to solve the problem of imbalanced data and the method for association prediction established multiple types of known associations among multiple objects presented in TPGLDA model. Results The experimental results showed that our proposed method achieved a reliable performance with Area Under Roc Curve (AUC) and Area Under Precision-Recall Curve (AUPR) values of 0.9788 and 0.9373, respectively, under fivefold-cross-validation experiments. It outperformed than some other previous methods such as DCSMDA and TPGLDA. Furthermore, it demonstrated the ability to derive new associations between miRNAs and diseases among 8, 19 and 14 new associations out of top 40 predicted associations in case studies of Prostatic Neoplasms, Heart Failure, and Glioma diseases, respectively. All of these new predicted associations have been confirmed by recent literatures. Besides, it could discover new associations for new diseases (or miRNAs) without any known associations as demonstrated in the case study of Open-angle glaucoma disease. Conclusion With the reliable performance to infer new associations between miRNAs and diseases as well as to discover new associations for new diseases (or miRNAs) without any known associations, our proposed method can be considered as a powerful tool to infer miRNA-disease associations.

(1) Background: Exhaled nitric oxide (NO) has been considered as a biomarker of airway inflammation. The measurement of fractional exhaled NO (FENO) is a valuable test for assessing local inflammation in subjects with allergic rhinitis (AR). (2) Objective: To evaluate (a) the correlation between nasal FENO with anthropometric characteristics, symptoms of AR and nasal peak flows in children without and with AR; and (b) the cut-off of nasal FENO for diagnosis of AR in symptomatic children. (3) Methods: The study was a descriptive and cross-sectional study in subjects with and without AR < 18 years old. All clinical and functional characteristics of the study subjects were recorded for analysis. They were divided into healthy subjects for the control group and subjects with AR who met all inclusion criteria. (4) Results: 100 subjects (14 ± 3 years) were included, including 32 control subjects and 68 patients with AR. Nasal FENO in AR patients was significantly higher than in control subjects: 985 ± 232 ppb vs. 229 ± 65 ppb (p < 0.001). In control subjects, nasal FENO was not correlated with anthropometric characteristics and nasal inspiratory or expiratory peak flows (IPF or EPF) (p > 0.05). There was a correlation between nasal FENO and AR symptoms in AR patients and nasal IPF and EPF (p = 0.001 and 0.0001, respectively). The cut-off of nasal FENO for positive AR diagnosis with the highest specificity and sensitivity was ≥794 ppb (96.7% and 92.6%, respectively). (5) Conclusion: The use of nasal FENO as a biomarker of AR provides a useful tool and additional armamentarium in the management of allergic rhinitis.

In this study, the effect of dimethyl ether enriched air (DMEA) on pollutants and performance characteristics a diesel engine was evaluated. The combustion parameters have been evaluated by simulation method. Simulation results show that the in-cylinder pressure increases slightly while the combustion duration is shorter for DMEA-engine compared to the original case. In addition, a comparative test on DMEA-engine was carried out, in which DME was supplied into the intake manifold at a constant concentration to the mass of intake air. The results show that, when operating with DMEA, the brake specific energy consumption (BSEC) reduces slightly at full load condition by 2.20%. While, at a speed of 1600 rpm, the BSEC increases from 2.6% to 7.7% at low load and slides from 3.1% to 5.5% at high load condition. The smoke level reduces moderately when the test engine operating with DMEA by 6.25% on average at full load and 2.0% to 8.2% as load increases at intermediate speed condition. The CO emission reduces 5.28% while NOx and HC emission increase 5.62% and 7.1% on average at full load condition. At the speed of 1600 rpm, CO reduces 5.9% while NOx and HC increase by 7.1% and 27.5% on average.

BackgroundThe COVID-19 outbreak witnessed in the autumn of 2021 led to unprecedented changes in healthcare systems in some emerging countries. Many field-hospitals, temporary sites of care for COVID-19 patients, were built around the country and followed by the healthcare workers who were mobilized. This study aimed to measure sleep disorders, depression, and fatigue in volunteers working at field hospitals during the COVID-19 outbreak.MethodsThis was a cross-sectional study. The self-report questionnaire was used for each study subject. Sleep characters, including STOP's elements were questioned. Healthcare workers' burnout was detected by using Pichot's questionnaire.ResultsOne hundred front-line healthcare workers (FHWs), predominantly last year and graduated medical students, were included in the study (86% female subjects). The mean sleep-time of FHWs before, while working, and during the isolation period after working at COVID-19 field hospitals were: 7.78 ± 1.48, 5.71 ± 1.40, and 8.78 ± 2.31 h per day, respectively. Burnout was not a crucial issue for these volunteer subjects. The mean scores of Pichot's Fatigue Scale and Pichot's Depression Scale, measured after 4 weeks working at field hospitals, were 4.18 ± 5.42 and 2.54 ± 3.36, respectively. Thirteen participants were suspected of depression. The fatigue scores decreased significantly in the group who claimed short sleep latency. The factor that increased the depression score was “anxious feeling” (p = 0.001). Other significant factors were “short sleep latency,” “observed sleep apnea,” “tiredness, daily sleepiness” and “snoring.”ConclusionAppropriate work schedule, better sleep conditions, and mental health support could be helpful for FHWs. The mandatory 2 weeks of isolation after working in field hospitals provided opportunity for FHWs' recovery.

In this article, an extensive examination is provided on the possible uses of membranes and hybrid processes in wastewater treatment. While membrane technologies face certain constraints, such as membrane fouling and scaling, the incomplete elimination of emerging contaminants, elevated expenses, energy usage, and brine disposal, there are approaches that can address these challenges. Methods such as pretreating the feed water, utilizing hybrid membrane systems and hybrid dual-membrane systems, and employing other innovative membrane-based treatment techniques can enhance the efficacy of membrane processes and advance sustainability.

Abstract Preterm birth risk is associated with early softening of the uterine cervix in pregnancy due to the accelerated remodeling of collagen extracellular matrix. Studies of mice model of pregnancy were performed with an imaging Mueller polarimeter at different time points of pregnancy to find polarimetric parameters for collagen scoring. Mueller matrix images of the unstained sections of mice uterine cervices were taken at day 6 and day 18 of 19-days gestation period and at different spatial locations through the cervices. The logarithmic decomposition of the recorded Mueller matrices mapped the depolarization, linear retardance, and azimuth of the optical axis of cervical tissue. These images highlighted both the inner structure of cervix and the arrangement of cervical collagen fibers confirmed by the second harmonic generation microscopy. The statistical analysis and two-Gaussians fit of the distributions of linear retardance and linear depolarization in the entire images of cervical tissue (without manual selection of the specific regions of interest) quantified the randomization of collagen fibers alignment with gestation time. At day 18 the remodeling of cervical extracellular matrix of collagen was measurable at the external cervical os that is available for the direct optical observations in vivo. It supports the assumption that imaging Mueller polarimetry holds promise for the fast and accurate collagen scoring in pregnancy and the assessment of the preterm birth risk.

Vietnam is the most prominent black pepper producer and exporter in the world. In 2020, the cultivated area of black pepper in Vietnam was 132.000 hectares and its production was 270.000 tons, in which the Central Highlands region took about 70% of both the cultivated area and production [1]. Hence, this region is thought to be the capital of black pepper cultivation and production in Vietnam. Numerous researches have investigated biodiversity and collected various beneficial endophytic bacteria from this plant in this region; however, traditional methods only were used to isolate such bacteria [2–5]. Therefore, these studies have a limitation to providing insight into the profiles of the endophytic microorganism dataset in the black pepper plant. Most recently, our work based on the 16S rRNA gene amplicon sequencing revealed an insight into profiles of microbial diversity and its functionality from the sample collected from a forest in this region; however, that work was just focused on soil microbiome dataset from the dry deciduous dipterocarp forest in Yok Don national park [6]. To our knowledge, a dataset of endophytic microbiome of black pepper plant cultivated in the Central Highlands remains unclear.This report presents a dataset of the endophytic microbiome from a representative sample combined from five different root samples of black pepper (Vinh Linh local variety) cultivated in the Central Highlands of Vietnam using 16S rRNA gene metagenomic next-generation sequencing. The dataset in this work can provide information on the endophytic microbial diversity and its functionality. It can also be useful for developing cultivation techniques by applying endophytic microbial genetic resources for sustainable black pepper production in the Central Highlands, Vietnam, towards the nutrient need in different stages of development and growth.

Vietnam has been identified as a country at high-risk for emergence and re-emergence of zoonotic diseases. The government of Vietnam recognized five priority zoonoses, including highly pathogenic avian influenza, rabies, leptospirosis, anthrax, and Streptococcus suis, and established a framework for One Health investigation and response to these diseases. From July 2020 to February 2021, quantitative data of zoonoses were collected from an online survey in 61 of 63 provinces based on either clinical diagnosis or laboratory confirmation. The responses were followed up by using in-depth interviews, and scientific literatures on zoonoses in Vietnam during 2010 to 2020 were reviewed. A total of 234 human health professionals and 95 animal health professionals responded to the survey. The proportion of clinical-based respondents was higher than laboratory-based respondents in both human health (130/234, 55.6%) and animal health (65/95, 68.4%) sectors. There were differences in the reported frequency of zoonoses between human and animal health professionals, and between clinical-based and laboratory-based respondents. Rabies was the most serious zoonotic disease based on the number of human cases and the geographic distribution. No human cases of avian influenza infection have been reported since 2015, although the H5 subtype viruses have been found in poultry. Besides, some bacterial, fungal, and parasitic zoonoses were detected in both humans and animals. Out of the 75 zoonoses identified, we recommend that the original five prioritized zoonoses, plus 24 additional zoonoses, should be targeted for future prevention, detection, and control under One Health approach in Vietnam.

Groundwater contamination by arsenic (As) is a serious issue in many countries, particularly in middle- and low-income nations. High concentrations of As in drinking water and groundwater cause serious health problems. Numerous technologies, such as ion exchange, oxidation, coagulation–flocculation, phytoremediation, membrane filtration, and adsorption, have been applied to remove As from the water environment. Among these technologies, adsorption is the preferred method in low- and middle-income countries due to its affordability, high efficiency, and ease of design, operation, and maintenance. Along with this technology, a variety of materials have been developed and investigated for their ability to remove As from water environments, though iron-based adsorbents have been reported to be the most effective. Thus, the aim of this paper is to briefly review the sources of As and the prevalence of As species in water bodies, as well as the currently available technologies for As removal. A detailed analysis of recent studies on iron-based adsorbents used to remove As from aqueous solutions in both laboratory conditions and field conditions is presented.