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Background Microbial melanins possess a broad spectrum of biological activities. However, there is little understanding of their neuroprotective and neuronal cell differentiation properties. This study aimed to extract, purify, and modify melanins from two medicinal fungi ( Daedaleopsis tricolor and Fomes fomentarius ), and to evaluate their antioxidant activity, as well as their cell protective ability against neurotoxins. In addition, the study also investigated the feasibility of combining melanins or modified melanins with retinoic acid (RA) to induce neuronal differentiation. Methods Melanin was extracted and purified using alkaline acid-based methods. Antioxidant activities and neuroprotective effects were evaluated using the DPPH (1,1-diphenyl-2-picrylhydrazyl) and MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assays, respectively. In addition, morphological changes of SH-SY5Y cells were recorded by using a Pannoramic MIDI scanner. Results All melanins and arginine-modified melanins displayed mild DPPH scavenging activities, which were statistically lower than that of ascorbic acid ( p < 0.05). In terms of neuroprotection, both melanins and arginine-modified melanins exhibited significant cell protection against H 2 O 2 after 24 h exposure ( p < 0.05). Notably, there is no significant difference between F. fomentarius melanin and its modified form as they both increased cell viability by about 20%. Contrarily, while D. tricolor melanin enhanced the cell viability with 16%, its modified form increased the cell viability with 21%. These activities, however, are significantly lower than the positive control ( N -acetylcysteine, p < 0.05). Regarding MPTP, only the arginine-modified melanins of the two fungi significantly protected the cells after 24 h exposure to the toxin ( p < 0.05). Specifically, F. fomentarius and D. tricolor modified melanins enhanced the cell viability with 10.2% and 11.1%, respectively, whereas that of the positive control was 13.2%. Interestingly, combining RA (10 µM) with 20 µg/mL of either F. fomentarius , or especially D. tricolor arginine-modified melanin, significantly promoted neuroblastoma cell differentiation into mature neuronal cells compared to using RA alone ( p < 0.05). Conclusions The arginine-modified melanins of D. tricolor and F. fomentarius have potential for neuroprotection against Parkinsonian neurotoxins. In addition, the arginine-modified melanin of D. tricolor may serve as an excellent material for research in neuroblastoma treatment.

Background 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. Results 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. Conclusions 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.

BackgroundAs tumor biology takes precedence over anatomic staging to determine breast cancer (BC) prognosis, there is growing interest in limiting axillary surgery. There is a need for tools to identify patients at the lowest risk of harboring axillary lymph node (ALN) disease, to determine when omission of sentinel lymph node biopsy (SLNB) may be appropriate. We examined whether a nomogram using preoperative axillary ultrasound (axUS) findings, clinical tumor size, receptor status, and grade to calculate the probability of nodal metastasis (PNM) has value in surgical decision making.MethodsThis was a retrospective analysis of female patients (February 2011–October 2014) with invasive BC who underwent preoperative axUS and axillary surgery. Cases with locally advanced BC, neoadjuvant treatment, or bilateral BC were excluded. PNM was calculated for each case. Using various PNM thresholds, the proportion of cases with ALN metastasis on pathology was examined to determine an optimal PNM cut-point to predict ALN negativity.ResultsOf 357 included patients, 72% were node-negative on surgical staging, and 69 (19.6%) had a PNM < 9.3%. Of these 69 patients, 6 had ALN metastasis on surgical pathology, yielding a false negative rate (FNR) of 8.7% for predicting negative ALN when a PNM threshold of < 9.3% was used.ConclusionA nomogram incorporating axUS findings and tumor characteristics identified a sizeable subgroup (19.6%) in whom ALN was predicted to be negative, with an 8.7% FNR. Surgeons can use this nomogram to quantify the probability of ALN metastasis and select patients who may benefit from omitting SLNB.

Fungal melanins have remarkable bioactivities, but their practical applications are limited, partly due to their hydrophobic nature. Melanin modification with amino acids was reported to improve their water solubility. This research aimed to extract, and modify the melanins from Calvatia craniiformis and Xylaria plebeja with arginine, and to evaluate their neuroprotective effects against Parkinsonian toxins. MTT assay showed that all melanins and melanin derivatives could protect SH-SY5Y neuroblastoma cells from 1 mM H2O2. Xylaria plebeja melanin and melanin derivative at 100 µg/mL increased the cell viability about 16.0% compared to the negative control, whereas C. craniiformis melanin and its modified form enhanced the cell viability by 18.4% and 8.3%, respectively and that of the positive control (20 µM resveratrol) was 35.5%. Regarding neuroprotective effects against MPTP, the positive control, C. craniiformis melanin, and modified melanin increased the cell viability with approximately 5.0%, but that of X. plebeja melanin and modified melanin were 13.0%. Both melanins and melanin derivatives from C. craniiformis and X. plebeja showed significant neuroprotective effects against H2O2. However, only X. plebeja melanin and modified melanin displayed significant neuroprotective effects against MPTP and therefore they would be potential materials for follow-up research in Parkinson’s disease prevention.

Land cover and plant species identification using satellite images and deep learning approaches have recently been a widely addressed area of research. However, mangroves, a specific species that have significantly declined in quantity and quality worldwide despite their numerous benefits, have not been the subject of attention. The novelty of this research is to deal with this species based on an advanced deep learning solution (a proposed ensemble U-Net model) and a high-resolution Planet satellite imagery (5 m x 5 m) in a case study of Ngoc Hien district, Ca Mau province, Vietnam. Twelve single U-Net backbone models were trained, and three quantitative metrics (Intersection over Union, F 1 -score, and Overall Accuracy) were used to evaluate. The findings indicate that three out of twelve models (MobileNet, SEResNeXt-101 and Efficientnet-B7) experienced the most efficient assessment results for identifying all classes, in which the MobileNet model was the best. These models were applied for the ensemble model’s development. The ensemble model’s quantitative assessment metrics increased considerably by about 3–10% compared to the single-component models. The IoU, F 1 -score, and OA values of this model were 80.08%, 95.82%, and 95.90%, respectively. Three classes of mangrove species ( Avicennia alba , Rhizophora apiculate, and mixed mangroves) in the ensemble model had more uniform assessment results. In conclusion, to achieve optimal classification outcomes, a land-cover map comprising mangrove species is possibly established using the proposed ensemble model, while a distribution map of mangrove species enables to be developed using the MobileNet model.

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.

Background The Perceived Stress Scale 10 item (PSS-10) has been translated into more than 20 languages and used widely in different populations. Yet, to date, no study has tested psychometric properties of the instrument among older women and there is no Vietnamese version of the instrument. Methods This study translated the PSS-10 into Vietnamese and assessed Vietnamese version of the Perceived Stress Scale 10 items (V-PSS-10) for translation equivalence, face validity, construct validity, correlations, internal consistency reliability, and test-retest reliability among 473 women aged 60 and over. Results The study found that V-PSS-10 retained the original meaning and was understood by Vietnamese older women. An exploratory factor analysis of the V-PSS-10 yielded a two-factor structure, and these two factors were significantly correlated (0.56, p < .01) with all item loadings exceeded .50. The V-PSS-10 score was positively correlated with general sleep disturbance (ρ = .12, p  < .05), CES-D score for depression symptoms (ρ = .60, p  < .01), and negatively correlated with mental (ρ = −.46, p  < .01), and physical health scores (ρ = −.19, p  < .01). The Cronbach’s alpha for the V-PSS-10 was .80, and the test-retest correlation at one month’s interval was .43. Conclusion Findings from this study suggest that the V-PSS-10 has acceptable validity and reliability levels among older women. The V-PSS-10 can be used to measure perceived stress in future research and practice. However, future research would be useful to further endorse the validity and reliability of the V-PSS-10.

The main objective of this study is to assess the spatio-temporal dynamics of land cover/land use changes in the lower Mekong Delta over the last 40 years with the coastal Tran Van Thoi District of Ca Mau Province, Vietnam as a case study. Land cover/land use change dynamics are derived from moderate to high spatial resolution (Landsat and SPOT) satellite imagery in six time intervals ranging from 1973 to 2011. Multi-temporal satellite images were collected, georeferenced, classified using per-pixel method, validated, and compared in post classification for the land use/land cover change detection in decades. Seven major land cover/land use classes were obtained, including cultivated lands, aquaculture ponds, mangrove forest, melaleuca forest, built up areas, bare lands, and natural water bodies. The accuracies of the land cover/land use maps for 1973, 1979, 1989, 1995, 2004, and 2011 were 81%, 82%, 86%, 87%, 89%, and 89%, respectively. The results show that the area of cultivated lands reduced over the period 1973–2011, however, it still represents the dominant land use in the case study. Aquaculture ponds were almost absent in 1973 but greatly increased from 1995 to 2004, to represent 20% of the land surface in 2011. Overall, from 1973 to 2011, bare lands, cultivated lands, mangrove forest, and melaleuca forest decreased by 104 km2, 77 km2, 61 km2, and 5 km2, respectively. In contrast, aquaculture lands and built up areas increased by 123 km2 and 120 km2, respectively. Temporal analysis highlights that these changes took place mostly between 1995 and 2004. This study is a first step to identify the main drivers of land use changes in this delta region, which include economical policies as well as demographic, socio-economic, and environmental changes.

This study aimed to describe knowledge, attitudes, and practices (KAP) in controlling COVID-19 and some related factors among the Vietnamese population in 2020. A cross-sectional study was conducted involving 1999 participants aged 18–59 years old, through an online questionnaire. The results showed that 92.2% of the participants had a high knowledge level regarding COVID-19 prevention measures, 68.6% had a positive attitude toward COVID-19 prevention measures, and 75.8% practiced all six measures for preventing the spread of the virus. Age, sex, marital status, knowledge, and fear were significantly associated with the practices aimed at COVID-19 prevention. Married people and participants with high levels of knowledge were more likely to practice all preventive measures. In contrast, young people, men, and those who fear COVID-19 were less likely to practice all preventative measures. Good KAP among Vietnamese people could be an important factor in helping authorities gain initial success in containing the coronavirus and COVID-19. In addition to continuously raising and maintaining the community's awareness, attitude, and practices in disease prevention, the introduction and strict implementation of sanctions and regulations were also important in ensuring good practices were implemented and sustained over time. Groups with lower KAP levels should be provided with more information and support to promote appropriate disease prevention practices.